We live in the world that is completely entangled on energy and thus, Humankind can no longer do without it, power. With electricity being the main form of energy today, this has increased the complexity of our life today. In Uganda, electricity generation is mainly through hydropower which put the country in the bottleneck of over dependence on one source of energy. Yet, there are many energy systems out there that country can diversify its electricity generation. Therefore, the need to understand, the level of development and utilization of various energy systems has been the underlying question for this present study. Comprehensive literature survey was conducted from the electronic databases including ScienceDirect, Wiley, Sage, Scopus, Taylor & Francis, and Google Scholar. The publications in form of reports, conference papers, working papers, discussion papers, journal articles, book sections and textbooks were considered in this study. In total, 11 energy systems including human and animal energy, solid biomass (firewood), hydropower, wind, geothermal, solar, nuclear, peat, coal, petroleum, and non-solid biomass (methanol, hydrogen, ethanol, biodiesel, and biogas) are described. The current and the future development and utilization of these energy systems has been described. The challenges with their development and utilization were elaborated and the solution the challenges were presented. The hydropower with River Nile being the main river for large hydropower plant construction is the dominance energy system in Uganda. Nuclear energy will be the salvation for the country’s electric energy supply in the near future. Therefore, Uganda needs to bet big on nuclear energy.

Considering increasingly ambitious pledges by countries, pressure from society, investors, and clients further up the supply chain, the question for companies is not so much whether to take decarbonisation action, but what action and by when. However, determining an ideal mix of measures to apply ‘decarbonisation efficiency’ requires more than knowledge of technically feasible measures and how to combine them to achieve the most economic outcome: In this paper, the author describes seven aspects which heavily influence the composition of an ‘ideal mix’ that executive leadership needs to take a (strategic) position on. These aspects consider underlying motivations and span across (socio-)economic, technical, regulatory, strategic, corporate culture and environmental factors and further underline the necessity of clarity of definitions. How these decisions influence the determination of the decarbonisation-efficient ideal mix of measures, both in principle but also in terms of specific impact is further explored by providing examples. What choices are taken by German manufacturers in several of the aspects is disclosed by insights from about 850 responses to the ‘Energy Efficiency Index of German Industry’. Knowledge of the status quo, and clarity in definitions, objectives, time frames and scope are key.

Wave energy converter (WEC) arrays deployed in coastal regions may create physical disturbances potentially resulting in environmental stresses. Presently, limited information is available on the nature of these physical disturbance or the resultant effects. A quantitative Spatial Environmental Assessment Tool (SEAT) for evaluating potential effects of wave energy converter (WEC) arrays on nearshore hydrodynamics and sediment transport is presented for the central Oregon coast (USA) through coupled numerical model simulations of an array of WECs. Derived climatological wave conditions were used as inputs to the model to allow for the calculation of risk metrics associated with various hydrodynamic and sediment transport variables such as maximum shear stress, bottom velocity, and change in bed elevation. The risk maps provided simple, quantitative, and spatially-resolved means of evaluating physical changes in the vicinity of a hypothetical WEC array in response to varying wave conditions. Near-field risk of sediment mobility was determined to be moderate in the lee of the densely spaced array, where the potential for increased sediment deposition could result in benthic habitat alteration. Modifications to the nearshore sediment deposition and erosion patterns were observed near headlands and topographic features, which could have implications for littoral sediment transport. The results illustrate the benefits of a risk evaluation tool for facilitating coastal resource management at early market marine renewable energy sites.

It is shown that de Sitter accelerated expansion of the Universe (dark energy effect) is an exact solution to the set of self-consistent stochastic nonlinear gravitational waves in the FLRW metric coming to the Universe from “nowhere”.

Synergy, emerges from synchronized reciprocal positive feedback loops between a network of diverse actors. For this process to proceed, compatible information from different sources synchronically coordinates the actions of the actors resulting in a nonlinear increase in the useful work or potential energy the system can manage. In contrast noise is produced when incompatible information is mixed. This synergy produced from the coordination of different agents achieves non-linear gains in free energy and in information (negentropy) that are greater than the sum of the parts. The final product of new synergies is an increase in individual autonomy of an organism that achieves increased emancipation from the environment with increases in productivity, efficiency, capacity for flexibility, self-regulation and self-control of behavior through a synchronized division of ever more specialized labor. Examples that provide quantitative data for this phenomenon are presented. Results show that increases in free energy density require decreases in entropy density. This is proposed as a law of thermodynamics.

As predicted by the theory of super dielectric materials, simple tests demonstrate that dielectric material on the outside of a parallel plate capacitor dramatically increases capacitance, energy density, and power density. Simple parallel plate capacitors with only ambient air between the plates behaved as per standard theory. Once the same capacitor was partially submerged in deionized water [DI], or DI with low dissolved NaCl concentrations, still with only ambient air between the electrodes, the capacitance, energy density, and power density, at low frequency, increased by more than seven orders of magnitude. Notably, conventional theory precludes the possibility that material outside the volume between the plates will in any fashion impact capacitive behavior.

All hydropower project type requires an ample availability of stream flow data. Unfortunately most of the hydropower projects especially small hydropower projects are conducted on ungauged river and consequently hydrologists have for a longtime used stream flow estimation methods using the mean annual flows to gauge rivers. Unfortunately flow estimation methods which include the runoff data method, area ratio method and the correlation flow methods employ a lot of assumptions which affect their uncertainty. Although hydropower energy is one of most promising clean energy technologies available, it has potential drawbacks as compared with various other forms of renewable energy, such as biomass, solar and wind energy, due in particular to it high capital investment costs. For most of the rural population in Mozambique, access to conversional energy in the form of electricity is limited. The aim of the present investigation was to analyze the functions of the Chua micro-hydropower plant in the Manica district in Mozambique and to examine the possibility of increasing energy production there. The total power generation capacity currently installed in Mozambique is about 939 MW. Hydropower accounts for 561 MW or 61% of this, oil and natural gas in turn, for 27% and 12% of it, respectively.

Hybrid Renewable Energy Systems (HRES) integrate renewable sources, storage, and optionally conventional energies, offering an eco-friendly solution to fossil fuels. Microgrids (MGs) bolster HRES integration, enhancing energy management, resilience, and reliability at various levels. This study, emphasizing the need for refined optimization methods, investigates three themes: renewable energy, microgrid, and multiobjective optimization (MOO), through a bibliometric analysis of 470 Scopus documents from 2010-2023, analyzed with SciMAT software. It segments the research into two periods, 2010-2019 and 2020-2023, revealing a surge in MOO focus, especially in the latter period, with a 35% increase in MOO-related research. This indicates a shift towards com-prehensive energy ecosystem management that balances environmental, technical, and economic elements. The initial focus on MOO, genetic algorithms, and energy management systems has expanded to include smart grids and electric power systems, with MOO remaining a primary theme in the second period. The increased application of Artificial Intelligence (AI) in optimizing HMGS within the MOO framework signals a move towards more sustainable, intelligent energy solutions. Despite progress, challenges remain, including high battery costs, the need for reliable MOO data, the intermittency of renewable energy sources, and HMGS network scalability issues, highlighting directions for future research.

As the global transition towards renewable energy accelerates, the integration of grid-scale energy storage systems has become increasingly critical for stabilizing energy supply and enhancing grid reliability. Among various storage technologies, lithium-ion batteries stand out for their high energy density, scalability, and relatively low environmental impact. This study investigates the performance and longevity of lithium-ion batteries in grid-scale applications, focusing on the impact of operational parameters such as cycling frequency, depth of discharge, temperature fluctuations, and charging/discharging rates. Employing a mixed-methods approach, we combined quantitative analysis of performance metrics (cycle life, capacity fade, efficiency) with qualitative assessments from case studies of existing grid-scale projects. Our findings reveal that while lithium-ion batteries exhibit robust performance in grid-scale storage, their longevity and efficiency are significantly influenced by operational conditions. Specifically, temperature management and optimized cycling strategies were identified as key factors in mitigating degradation and extending battery life. This research provides a comprehensive understanding of lithium-ion battery behavior in grid-scale environments, offering valuable insights for the design, optimization, and management of energy storage systems. By addressing the challenges of battery performance and longevity, our study contributes to the development of more sustainable and reliable grid storage solutions, facilitating the broader adoption of renewable energy sources.

Energy distance is used to eigenvalue distributions in this new Wishart distribution study, providing a new perspective on high-dimensional data. Multivariate statistics relies on Wishart distribution to explain covariance matrices. This analysis shows how degrees of freedom and covariance matrix configurations affect eigenvalue dispersion. We use energy distance based on eigenvalue distributions to assess Wishart distribution differences without the "curse of dimensionality" via extensive simulation simulations. This approach improves measurement accuracy and processing efficiency in distribution comparisons and enables new analytical pathways in scientific fields that need data covariance comprehension. Our results show that degrees of freedom and matrix structure considerably affect energy distances, expanding the theoretical framework and practical applications of statistical models.

Compressed carbon dioxide energy storage (CCES) offers several benefits over other existing energy storage systems, including ease of liquefaction, high energy storage density, and environmental friendliness. As a result, the research progress, economic and technological feasibility, and system operation of the CCES system are all discussed in depth in this study. The system evaluation method is summarized and the compressed carbon dioxide storage is analyzed, and the performance optimization direction of the compressed carbon dioxide energy storage technology is discussed. When the overall performance of a transcritical CCES system, a supercritical CCES system and a liquid CCES system are compared, it is discovered that the supercritical CCES system has better thermodynamic characteristics and a simpler system configuration, making it suitable for large-scale development and use. The goal of the CCES system's future development is to create a design with an optimum compression and expansion ratio, a more precise analysis and system model, and multi-field coupling. This review's discussion serves as a guide for the best design and use of the CCES system.

The wave energy converter (WEC) technology constantly develops new designs and models. To encourage its development within the energy sector, research is required to improve current designs and create durable and effective devices. However, it is also crucial to investigate the suitability of a WEC to a site-specific sea condition as this can impact its optimal power absorption and constructability. This study evaluates and compares the efficiency of a heaving buoy with varied geometries in one of the most energetic places along the Mexican coast. A statistical analysis of the wave climate on the coast of Ensenada during the last 42 years is performed to define the conditions to which the device is subjected. The location of the WEC in shallow waters is chosen using a computational model which solves the modified mild slope equation in its elliptic shape. The heaving buoy floater is studied using three distinct geometries: a semi-sphere, a cylinder, and a proposed rounded semi-rectangle. The hydrodynamic response of the three geometries is then analysed in the frequency and time domain using ANSYS AQWA. The hydrodynamic study involves the assessment of the floating body dynamics, exerted forces, the power absorbed as well as the suitability of the proposed power take-off (PTO) system. Findings reveal that the proposed geometry absorbs the most energy, with an annual power of 135.11 MW, and that the transmission PTO design is appropriate for this type of technology.

In the context of the French tertiary decree, it is crucial to reduce the energy consumption of buildings by first addressing the design of the electrical architecture. Implementing Direct Current (DC) nanogrids in buildings could offers a promising advantage for energy efficiency, significantly impacting overall energy consumption and sustainability goals. For an insulated area with a subtropical climate, such as La Réunion island, DC nanogrids could also facilitate the insertion of local renewable energy sources, especially solar energy. This article presents the deployment and efficiency evaluation of an end-to-end Low Voltage Direct Current (LVDC) nanogrid, from conception to real-world installation within a company. The nanogrid consists of a photovoltaic power plant, a Lithium-Iron-Phosphate (LFP) battery, and DC end-use equipment such as LED lighting and DC fans for two individual offices. An innovation is provided for the power supply and energy management of terminal equipment using the Power Over Ethernet (PoE) standard IEEE 802.3bt. The efficiency of the nanogrid is measured to be 40% higher than the efficiency of an installation powered by PV and distributed at 230 VAC. These results are obtained under certain deployment conditions, which are discussed in this article, in order to enhance the energy efficiency of buildings by using 48VDC. The nanogrid hardware and software infrastructure, the methodology employed for efficiency quantification and the measurement results are described in the paper.

The increasing expansion of the use of renewable distributed generation (RDG) technologies in electrical networks such as solar plants or wind farms and others has changed the nature of the distributed system and transformed it from the traditional system into an efficient system. This system has led to various technical effects in the host networks, with regard to voltage, electrical energy losses, fault levels, stability and electrical energy quality. These effects are not generic to any network; It can be positive, negative or neutral depending on the structure of the studied network, its operational condition and the various technology of the distributed generators. This research aims to quantitatively correct the effects of (RDG) in terms of voltage and electrical energy losses in the host networks. , since efficient distribution systems contain generators of a special nature and often contain bidirectional flux energy, it was necessary to construct a mathematical model of the distribution system hosting RDG units, which is fundamentally different from the traditional model of defining the reference electrical distribution bus bar. In order to achieve the systematic analysis, evaluation criteria and indicators were determined and mathematical formulas for them were completed. Based on the accomplished mathematical basis, an algorithm designed in such a way that it can be applied to any multi-voltage distribution system and to different distributed regenerative generation techniques is proposed. To demonstrate the algorithm's capabilities, it was tested on typical distribution networks using Factory Power DigSilent software, which is somewhat similar to MATLAB but more suitable for large capacity systems.

The ubiquitous problem of electrical energy waste is driven by human error, in which people regularly forget to turn off appliances when they leave a room, resulting in excessive consumption. The paper presents an energy-efficient TRIZ-inspired (EETRIZ) paradigm to automate consumer electronic devices in order to address this problem. Employing motion detection at entry and exit points, the system discerns room occupancy, effectively managing electrical appliances like lamps, fans, and air conditioners. The integration of theory of inventive problem solving (TRIZ) principles guides the ideation and design of an efficient switching mechanism. The system demonstrates that it is flexible by controlling multiple electronic consumer devices simultaneously. This paradigm can be used in a variety of environments, such as homes, offices, schools, and universities, and its goal is to reduce excessive energy use that results from human negligence. With an emphasis on economic viability and environmental impact, the proposed EETRIZ paradigm not only offers enhanced energy efficiency but also lays the groundwork for long-term sustainability practices, aligning with global efforts towards greener and smarter energy management. The proposed EETRIZ is implemented on C platform with support of MPLAB, Nuvoton 8051 Serie MCU Programming, GMPLibrary (GMP-5.1.1) and, Miracl Library. The proposed EETRIZ outperforms current state-of-the-art methods in terms of energy efficiency, cost-effectiveness, precision, and user-friendliness, according to hardware testing.

This research review paper comprehensively assesses the environmental impacts of diverse energy sources and proposes sustainable solutions. Fossil fuels contribute to pollution, habitat destruction, and greenhouse gas emissions. Renewable energy offers cleaner alternatives but faces challenges in manufacturing and disposal. Nuclear power has low emissions but poses risks in waste management and radiation. Biomass can be sustainable if responsibly sourced, but unsustainable practices lead to deforestation and emissions. Solutions include renewable technologies, energy efficiency, carbon capture, and sustainable transportation. Effective policies, incentives, and individual actions are crucial for a greener future. This review highlights the urgency of addressing energy-related environmental impacts and offers valuable insights for policymakers and individuals to take decisive actions for a sustainable energy future that protects the environment and promotes well- being.

Transportation is the primary consumer of oil, accounting for a significant portion of global energy consumption (34%) and CO2 emissions (40%). Electrifying road transportation is crucial to mitigate the effects of global warming. The abundant potential of renewable energy sources like solar and wind is hindered by their intermittent nature and incongruity with peak energy demands. This calls for the development of sophisticated energy storage solutions. Metal-air batteries (MABs), emerging as viable alternatives to lithium-ion batteries (LIBs), have attracted considerable attention due to their promising applications in the transportation sector. Despite substantial progress in MAB development over the past two decades, overcoming critical challenges such as electrolyte decomposition, carbon cathode degradation, anodic dendrite growth, and air impurities remains essential for their commercial viability. This mini-review provides a comprehensive overview of MAB fundamentals and the challenges associated with their development. The insights presented in this review serve to illuminate the current landscape and future prospects of MABs in the transportation sector.

This review focuses on the Just Energy Transition (JET) policies of the BRICS member countries, with the aim of finding lessons and possible adoption of some of the key energy policy aspects utilized in other countries for benchmarking for the South African context. Considerations of the present stage of JET in South Africa and the energy-source mix supporting the electricity sector, cognisant of the lifespan and condition of power plants. Analysis of the energy mix revealed that all nations were energy dependent on electricity which was produced by predominantly fossil fuelled power plants with high GHG (concentrating on high CO2 emissions). It was concluded that some of the learnings and lessons learnt from the BRICS countries might be incorporated into a South African energy plan for the transition with options and guidance for formulation of policies. This study will attract responsible environmentally conscious audience that has a commitment and drive to combat global warming and curbing climate change.

Commercial development of tidal stream energy is hampered by technical and financial challenges, and impeded by uncertainty about potential environmental effects that drive environmental risk assessments and permitting (consenting) processes. The effect of greatest concern for operational tidal stream energy devices is the potential for marine animals to collide with turbine blades, resulting in injury or death. Due to the turbulent and often turbid waters that frequently characterize tidal turbine sites, there is an absence of empirical evidence about collisions with marine animals. This paucity of observations often leads to risk-averse permitting decisions that further restrict the deployment of tidal energy devices that are needed to collect this evidence. This paper relies on the framework of stressors and receptors that is used widely in marine energy studies and outlines a stepwise probabilistic methodology that applies existing knowledge to further elucidate the risk to marine animals from operational tidal turbines. A case study using striped bass from the Bay of Fundy, Canada, accompanies the methodology, to partially demonstrate its application.

The IPCC’s sixth assessment report projects 15% to 43% (44 EJ/y – 310 EJ/y) of global primary energy to be generated by biomass in 2050 across multiple GHG mitigation scenarios. That report also emphasises the importance of electrification to meet GHG reduction targets. With increased reliance on electric power, and increased appeal to biomass, bioenergy for electricity is expected to play a major role in future energy markets. What makes the bioenergy solution more attractive is its reported reasonable Energy Return on Investment (EROI). However, generation at large scale is projected to be greatly dependent on crops and plantations. This shifts the GHG emissions concern to be concerns over land use and other emissions integrated in the bioenergy lifecycle. It is therefore vital to know whether the potential of electricity generation from biomass outweighs environmental impact of bioenergy. This paper evaluates the potential of biomass electricity mainly generated from short rotation woody crops combustion in generating green energy. This is done using the “Green EROI (EROIg)” quantification methodology, which indicates the net energy generated to society after investing in ecosystem maintenance energy (ESME). ESME is a non-monetary weighting mechanism of an entity’s different lifecycle environmental impacts. This study found that the EROIg of bioelectricity is marginally larger than unity when converted to its primary equivalent form (EROIg-PE) which indicates that the technology is somewhat energetically viable if its production was to be green. Three design options were proposed to improve bioenergy’s EROIg performance, these include adding 20% waste wood in the combustion mix, staggered harvesting and plantation to achieve annual harvest and pelletizing wood. This approach appeared to improve the EROIg especially for pelletizing, due to its simultaneous reduction in storage and transport costs, making the production energetically and environmentally viable even at a 1 : 1 secondary : primary ratio with an EROIg of 1.11 and an EROIg-PE of 3.17. We conclude with the discussion of the multiple indirect advantages of growing crops that can be used for energy generation, and a discussion on how this technique can be used alongside others to help them generate cleaner energy while facing the current global climate, biodiversity and waste issues.

In hydraulic systems, energy dissipation can be significant. The pressure drops that can occur in the hydraulic circuit, influenced by the adopted drive architecture, result in an absorbed power often significantly greater than that required by the mechanical system. In this paper, a comparative study of energy efficiency among five drive common architectures in industrial hydraulic axes is carried out. The analysis is applied to a hydraulic blanking press with variable speed and force, a fairly frequent industrial system, e.g. in the production of semi-finished brass products. Standard, regenerative, high-low, variable displacement pump and variable speed drive for a fixed displacement pump configurations have been analysed and compared. An adequate and optimized sizing of the various components of the system has been carried out in each case and subsequently the energy consumption has been estimated for a load cycle common to all the considered cases. The results show that the choice of power generation architecture of the hydraulic system has a very significant impact on energy efficiency and consequently operating costs and carbon footprint. The performed quantification of the potential energy efficiency of the considered drive architectures can be very useful in guiding energy-conscious choices.

The economic downturn caused by the financial crisis of 2008-2009 and the intensifying glob-al climate policy trends forced changes in the energy management of the European Union. The study examined how the most relevant energy economic variables affected the economic growth of the EU between 2010-2019. The study examined the relationship between GDP (dependent variable) and energy consumption, greenhouse gas emissions, the average energy price, and renewable energy use (independent variables) using the PSL-PM methodology. The results show an asymmetric picture because the independent variables influenced the eco-nomic growth of the EU in the examined period with different correlations and with different strengths. One of the significances of the study is that the presented and analyzed variables, as well as the results of the relationships between them, can contribute to the optimization of the EU's currently critical energy management and economic growth.

Development of methods and algorithms to predict the effect of mutations on protein stability, protein-protein, and protein-DNA/RNA binding is necessitated by the needs of protein engineering and for understanding the molecular mechanism of disease-causing variants. The vast majority of the leading methods are either methods with adjustable parameters or machine learning algorithms, both requiring a database of experimentally measured folding and binding free energy changes. These databases are collections of experimental data taken from scientific investigations typically aimed at probing the role of particular residue on the above-mentioned thermodynamics characteristics, i.e., the mutations are not introduced at random and do not necessarily represent mutations originating from single nucleotide variant (SNV). Thus, the reported performance of the leading algorithms assessed on these databases or other limited cases, may not be applicable for predicting the effect of SNVs seen in the human population. Indeed, we demonstrate that the SNVs and non-SNVs are not equally presented in the corresponding databases and the distribution of the free energy changes are not the same. Furthermore, the Pearson correlation coefficients (PCCs) obtained on cases involving SNVs are less impressive than for non-SNVs, indicating that caution should be used in applying them to reveal the effect of human SNVs. All methods are found to underestimate the energy changes by roughly a factor of 2.

Data centres, though a necessary part of modern society, are being stigmatised for consuming vast amounts of electricity for their operational and cooling needs. Due to Ireland’s reliance on fossil fuels to meet the increased energy demand of data centres, the data centres are contributing significantly to Ireland’s total carbon emissions. As much of this energy is expelled from data centres as waste heat energy, the potential for recycling some of this wasted heat energy was explored using environmentally friendly systems from recent publications. The recovered waste heat energy was applied in a vertical farming system, and the benefits of this waste heat to the vertical farm were analysed and quantified in two scenarios. Using conservative estimates, it was predicted that each vertical farm could be between 5-23% the size of the data centre and produce enough food to feed between 14-61 adults their daily calorie needs, and between 13-58 people their daily fresh produce requirements, depending on the scenario applied. For a more accurate prediction, each vertical farm would have to be assessed on a case-by-case basis. However, there was not enough data available on Irish data centres to perform these calculations.

This paper proposes how to reduce the consumption of active electrical energy (kwh) by 90.3% while maintaining the same mechanical work speed (RPM) at variable torque loads (fans or air-fluid blowers, centrifugal pumps are not included). of water and similar fluids), by using the “Fan Law” in an innovative way in PMSM-type synchronous motors (a comparative study never before carried out on the Fan Law). The work is carried out comparatively between brushless a-synchronous motors with starting loop (or motor with a short-circuited loop) versus brushed a-synchronous motors and PMSM-type synchronous motors without the need to use VDF (variable frequency drives), simplifying technology (electronics) and saving costs in an innovative way (R+D+i). The case study was developed on a design applied to a centrifugal air extractor/blower with PMSM/IPM type synchronous motor. Applying one of the fan affinity laws –with the impeller diameter 10.5 (mm) constant- the electrical power absorbed by the blower motor is proportional to the cube of the shaft speed: . Being “P” power (Watts) and “N” speed (RPM). Carrying out a comparative study between power (watts), active energy consumption (kwh) and rotational speed (RPM). This has a direct impact on the costs of residential and commercial single-phase active electrical energy consumption, measured in kilowatt-hours (kwh). Carrying out a comparative study between three (3) types of alternating current (AC) electrical machines, according to the NEMA (National Electrical Manufacturers Association); AC motors fall into three (3) categories. One (1), synchronous motors (Syncrhonous Motor) of three types: (1a) excitation by DC (DC Excited Motor), (1b) permanent magnet (Permanent Magnet Motor) and (1c) reluctance motor (Reluctance Motor) or motor Step by Step. Two (2), asynchronous induction motors of two types: (2a) Squirrel-Cage Induction Motor and (2b) Wound-Rotor Induction Motor. Three (3) series-wound motor (Series-Wound Motor) also called universal motor (they have carbons).

We investigate the performance of a novel flat photovoltaic-thermal (PV-T) module under high-vacuum through a 1D numerical model based on steady-state energy balance, with the aims of optimizing the simultaneous production of thermal and electrical energy. In the proposed design, the photovoltaic (PV) cell is positioned directly above the selective solar absorber (SSA), in a multilayer or fully integrated PV-SSA structure, which allows full exploitation of spectral solar radiation. In fact, in this configuration the losses related to non-absorption of low-energy photons and thermalization, typical of a classical single-junction PV cell, are reduced. The present study is conducted as the emittance and energy bandgap of the PV layer varied, thus admitting a wide variety of materials into the analysis. The dependence of the temperature coefficient, β(%/K), on the energy bandgap of the PV cell is also included. In the last part of the work, we discuss the performance of the proposed evacuated PV-T equipped with a SSA layer and thin film solar cells, namely those made of CdTe, CdS and GaAs. Overall, the paper highlights the great advantage of using high vacuum insulation, which suppresses conductive losses, and the versatility of the proposed system, which could be adapted to the user's needs simply by choosing the appropriate material for the photovoltaic layer.

This article is devoted to a bibliometric analysis of IEEE Energy Internet and Energy Systems Integration Conference proceedings posted in IEEE Xplore in 2017-2021. The main objective of the study was to identify the actual research issues on the Energy Internet topic. Author Keywords, INSPEC Controlled Terms, and terms compiled from n-grams derived from conference papers title and abstract texts were used to describe the actual issues. The terms were clustered using VOSviewer, and the terms included in each cluster were treated as a description of the actual issues. Brief descriptions of several publications relevant to the issue in question were given for task detail. The actual issue, which in my opinion deserves further, more detailed analysis, is proposed.

Steel fibers (SF) and polyolefin (PF) are widely used for shotcrete, especially in tunnelling. Both SF and PF and have shown to meet the standards in order to reduce or substitute the conventional steel mesh as reinforcement of concrete showing mechanical and productive advantages. This study sought the analysis and assessment of the mechanical properties of fiber reinforced shotcrete, comparing in-situ with laboratory results. This was performed with low and high fiber dosages of SF and PF as well as a combination of them (hybrid mixtures). A total of seven mixtures, two of steel, two of polyolefins, two hybrids and a control mixture were manufactured at laboratory and in situ. By performing tests according to EN 14651 and slabs according to EN 14488-5, it was possible to characterize the residual flexural strengths (fRj), and energy absorption capacity (E25mm) in slabs. In addition, a fracture surface analysis was performed, and the orientation factor was obtained. This allowed the authors to quantify the loss of residual strength on site and correlate it with the fiber content and positioning. Moreover, some relationships between beam and slab tests were found, allowing to correlate the most relevant type of tests in the field of fiber reinforced concrete.

The construction field uses up over one-third of the global energy consumption and contribute to 40% of CO2 emissions according to the International Energy Agency (IEA) and the 2020 annual reporter of United Nation, Goal 11 (Make cities inclusive, safe, resilient and sustainable) which discusses sustainable, safe and efficient buildings. Therefore, Morocco has a commitment to this program by publishing the law 47-09 of energy efficiency. This work aims to study the energy efficiency of two types of building, a conventional and a natural building. Conventional building is constructed using concrete, while the natural one uses sand clay and straws. As for the technique of making the natural building, it perpetually follows the same approach accustomed in rural zones of Atlas Mountains in Morocco. In this research we also simulate, temperature and humidity variation inside these buildings using TRNSYS software. Sketch Up software was employed to design these houses. The weather database is used for a typical meteorological year (TMY). In the case of natural building, many building configurations were simulated: roof insulation, floor insulation, different types of glazing and sun protection. What's more, the thermal comfort is revealed to be more conspicuous in the case of natural building.

The energy transition requires integration of different energy carriers, including electricity, heat, and transport sectors. Energy modeling methods and tools are essential to provide a clear insight into the energy transition. However, the methodologies often overlook the details of small-scale energy systems. The study states an innovative approach to facilitate sub-national energy systems with 100% renewable penetration and sectoral integration. An optimization model, OSeEM-SN, is developed under the Oemof framework. The model is validated using the case study of Schleswig-Holstein. The study assumes three scenarios representing 25%, 50%, and 100% of the total available biomass potentials. OSeEM-SN reaches feasible solutions without additional offshore wind investment, indicating that they can be reserved for supplying other states’ energy demand. The annual investment cost varies between 1.02 bn – 1.44 bn €/yr for the three scenarios. The electricity generation decreases by 17%, indicating that with high biomass-based combined heat and power plants, the curtailment from other renewable plants can be decreased. Ground source heat pumps dominate the heat mix; however, their installation decreases by 28% as the biomass penetrates fully into the energy mix. The validation confirms OSeEM-SN as a beneficial tool to examine different scenarios for sub-national energy systems.

Growing energy demand in the distributed energy system (DES) besides new charging loads of electric vehicles (EVs) make DES infrastructure unavailable earlier than normal projections. DES lines need to be upgraded to carry the modern demand of customers. DES line upgrade (LU) cost minimized and deferred to the next years by using energy storage system (ESS). ESS offers the opportunity to use energy flexibly in the distribution grid. It is possible to use ESS to shift the inevitable upgrade costs of the distribution grid elements and increase the power quality of the distribution grid. In this study, a method is proposed to extend the lifespan of DES with ESS and reduce line upgrade and investment costs in the distribution system. For this purpose, the IEEE 33 bus test grid is used, and the proposed method is tested and analyzed with different case studies. According to the results, the proposed method can reduce the investment cost by up to 80%. Besides, ESS usage considering load increase and line conditions of the distribution grid, upgrade costs of distribution grid are shifted, resulting in an optimal dimensioning and positioning while extending the lifespan of the distribution grid elements and, at the same time, offering significant improvements in energy quality. Additionally, it is seen that the power losses of the distribution grid are reduced up to 26%, and the voltage profile of buses is improved with the usage of ESS.

Machine learning (ML) is penetrating in all walks of life and is one of the major driving forces behind the fourth industrial revolution, typically known as Industry 4.0. This study reviews the state-of-the-art ML applications in the biofuels’ life cycle stages, i.e., soil, feedstock, production, consumption, and emissions. A keyword search is performed to retrieve relevant articles from the databases of the Web of Science and Google Scholar. ML applications in the soil stage were mostly based on the use of satellite images of land for estimation of biofuels yield or suitability analysis of agricultural land. In the second stage of the life cycle, assessment of rheological properties of the feedstocks and their effect on the quality of biofuels were dominant studies reported in the literature. The production stage included estimation and optimization of quality, quantity, and process conditions. The fuel consumption and emissions stage included analysis of engine performance and estimation of emissions temperature and composition, such as NOx, CO, and CO2. This study identified the following trends: dominant ML method, the stage of life cycle getting more usage of ML, the type of data used for the development of the ML-based models, and the stage-wise frequently used input and output variables. The findings of this article are beneficial for academia and industry-related people involved in model development in different stages of biofuel’s life cycle.

Machine learning (ML) is penetrating in all walks of life and is one of the major driving forces behind the fourth industrial revolution, typically known as Industry 4.0. The purpose of the present study is to review the state-of-the-art ML applications in the biofuels' life cycle stages, i.e., soil, feedstock, production, consumption, and emissions. A keyword search is performed to retrieve relevant articles from the databases of the Web of Science and Google Scholar. ML applications in the soil stage were mostly based on the use of satellite images of land for estimation of biofuels yield or suitability analysis of agricultural land. In the second stage of the life cycle, assessment of rheological properties of the feedstocks and their effect on the quality of biofuels were dominant studies reported in the literature. The production stage included estimation and optimization of quality, quantity, and process conditions. The fuel consumption and emissions stage included analysis of engine performance and estimation of emissions temperature and composition, such as NOx CO, and CO2. This study identified the following trends: dominant ML method, the stage of life cycle getting more usage of ML, the type of data used for the development of the ML-based models, and the stage-wise frequently used input and output variables. The findings of this article are beneficial for academia and industry-related people involved in model development in different stages of biofuel’s life cycle.

The cutting-edge photovoltaic cells are an indispensable part of the ongoing progress of earth-friendly plans for daily life energy consumption. However, the continuous electrical demand that extends to the night time requires a prior deployment of efficient real-time storage systems. In this regard, metal-air batteries have presented themselves as the most suitable candidates for solar energy storage, combining extra lightweight with higher power outputs and promises of longer life cycles. Scientific research over non-precious functional catalysts has always been the milestone and still contributing significantly to exploring new advanced materials and moderating the cost of both complementary technologies. Metal-organic frameworks (MOFs) derived functional materials have found their way to the application as storage and conversion materials, owing to their structural variety, porous advantages, as well as the tunability and high reactivity. In this review, we provide a detailed overview of the latest progress of MOF-based materials operating in metal-air batteries and photovoltaic cells.

According the JKR theory of adhesive contact, changes of the contact configuration after formation of the adhesive neck and before detaching are completely reversible. This means, that after formation of the initial contact, the force-distance dependencies should coincide, independently on the direction of the process (indentation or pull-off). In the majority of real systems, this invariance is not observed. The reasons for this may be either plastic deformation in the contacting bodies or surface roughness. One further mechanism of irreversibility (and corresponding energy dissipation) may be chemical heterogeneity of the contact interface leading to the spatial dependence of the specific work of adhesion. In the present paper, this "chemical" mechanism is analyzed on a simple example of an axisymmetric contact (with axisymmetric heterogeneity). It is shown that in the asymptotic case of a "microscopic heterogeneity", the system follows, during both indentation and pull-off, JKR curves, however, corresponding to different specific surface energies. After the turning point of the movement, the contact area first does not change and the transition from one JKR curve to the other occurs via a linear dependency of the force on indentation depth. The macroscopic behavior is not sensitive to the absolute and relative widths of the regions with different surface energy but depends mainly on the values of the specific surface energy.

Because of the significant enabling role smart meters can play in securing the transition towards sustainable energy distribution, the paper provides insights to support smart meters implementation projects. Energy utilities must propose adequate solutions to manage grid-upgrading projects and, in the meantime, increase efficiency levels. Based on empirical data analysis the paper provides insights aimed at maximize probability of success of smart meters projects. Results show common patterns of variables that may support project undertakers, policymakers and scholar when it comes to analyze projects to predict to maximize opportunities. For smart meters projects to succeed, regulatory stability is essential as long-period investments grids produce benefits for energy utilities, and for society.

The sensor nodes have limited computation, sensing, communication capabilities and generally operated by batteries in a harsh atmosphere with non-replenish able power sources. These limitations force the sensor network subject to failure because most of the energy is spent on sensing, computing and data transmission. This paper introduces an Energy Efficient Clustering and Shortest-Path Routing Protocol (EECSRP) to assist Wireless Sensor Networks (WSNs) by (a) extending the lifespan of the network (b) effectively using the battery power (c) decreasing the network overhead and (d) ensuring a high packet transmission ratio with minimal delay. The delay time-based Cluster Head (CH) is elected based on the node degree, residual energy and Received Signal Strength (RSS) to accomplish the goal. Additionally, the RSS-based network partitioning is implemented to evaluate the gradient based on demand routing between source (sensing node) and destination (BS). Whenever the current CH residual energy goes under the threshold level, the proposed protocol performs the clustering process, reducing the exchange of control packets. However, the BS periodically gathers the data from every single CH which helps to reduce the collision and Medium Access Control (MAC) layer conflict. From the simulation results, it is the evident that the proposed protocol performance in terms of average end-to-end latency, packet delivery ratio, average energy consumption and control overhead is better than the well-known current protocols.

A lack of trust in Energy Service Company (ESCo) is the most critical factor affecting the development of Energy Performance Contracting (EPC) in China compared with other constraints. One cannot easily estimate the energy-saving performance of an EPC project. Under that condition, lack of trust may cause the Energy-Consuming Unit (ECU) to suspect the energy-saving performance promised by the ESCo, thus leaving potentially profitable projects without necessary funding. Currently, specific studies taking an across-projects viewpoint on annual energy-saving performance of EPC projects in multiple subsectors objectively and quantitatively are lacking. This paper studies the regression relationships of annual energy-saving quantity in terms of revamping cost and the regression relationships of annual cost saving in terms of revamping cost. The regression results show that there are statistically significant correlations in the above relationships in the nine subsectors investigated. This is significant for ESCos and ECUs because knowledge on energy-saving performance could contribute to EPC investment decisions and trust relationships between ESCos and ECUs. Then a multiple linear regression model of revamping cost is set up to analyze its influencing factors. The model indicates that the subsector the sample belongs to, financing, registered capital of the ESCo, and contract period have significant effects on revamping cost. Thus, policy implications regarding innovation of EE promotion technology, clarifying ESCos’ exit mechanism, innovation of financing mechanism, and improving the market credit environment for promoting investment in EPC projects are provided.

Clausius’ virial theorem set a basis for relating kinetic energy in a body of independent material particles to its potential energy, pointing to their complementary role with respect to the second law of maximum entropy. In action mechanics, expressing the entropy of ideal gases as a capacity factor for sensible heat or enthalpy plus the configurational work to sustain the relative translational, rotational and vibrational action yields algorithms for estimating chemical reaction rates and positions of equilibrium. All properties of state including entropy, work potential as Helmholtz and Gibbs energies and activated transition state reaction rates can be estimated, using easily accessible molecular properties, such as atomic weights, bond lengths, moments of inertia and vibrational frequencies. Understanding how Clausius’ virial theorem balances the internal kinetic energy with field potential energy justifies partitioning between thermal and statistical properties of entropy, yielding a more complete view of the evolutionary nature of the second law of thermodynamics. The ease of performing these operations is illustrated by three important chemical gas phase reactions, the reversible dissociation of the hydrogen molecules, lysis of water to hydrogen and oxygen and the reversible formation of ammonia from nitrogen and hydrogen. Employing the ergal also introduced by Clausius to define the reversible internal work to overcome molecular interactions plus the configurational internal work of negative Gibbs energy as a function of volume or pressure may provide a practical guide for managing risk in industrial processes and climate change at the global scale.

Poland is the 3^rdproducer of mushrooms in the world. Mushroom production in Poland accounts for nearly 25% of the total production in the EU, and it is still growing. One type of waste generated during mushroom production is mushroom spent compost (MSC), with a 5:1 (MSC: mushrooms) production rate. We investigated valorizing the MSC to produce fuel via torrefaction (‘roasting’, a.k.a. low-temperature pyrolysis). Specifically, we developed models for the MSC torrefaction kinetics using thermogravimetric analyses (TGA) and the effects of torrefaction temperature (200~300 °C) and process duration time (20~60 min) on the resulting biochar (fuel) properties. The estimated activation energy value of MSC torrefaction was 22.3 kJ^.mol^-1. The highest higher heating value(HHV) = 17.9 MJ^.kg^-1d.m. was found for 280 °C (60 min torrefaction time). The temperature of torrefaction significantly (p<0.05) increased the HHVfor constant process duration. The torrefaction duration time significantly (p<0.05) increased the HHVfor 220 °C and decreased HHVfor 300 °C. The highest mass yield 98.5% was found for 220 °C (60 min), while the highest energy yield was found for 280 °C (60 min). In addition, estimations of the value (€132.3·Mg^-1d.m. or 27.7 €·Mg^-1w.m) and quantity of resulting biochar (from torrefied MSC with 65.3% moisture content) were made based on the 280°C (60 min) torrefaction variant, assuming the price of commercially available coal fuel. We have shown a concept for an alternative utilization of abundant biowaste (MSC). The initial economic evaluation showed that MSC torrefaction might be profitable. This research provides a basis for alternative use of an abundant biowaste and can help charting improved, sustainable mushroom production.

The Energy Performance of Buildings Directive 2010 calls for the Nearly Zero Energy Standard for new buildings from 2021 onwards: Buildings using “almost no energy” are powered by renewable sources or energy produced by the building itself. For residential buildings, this ambitious new standard has already been reached. But for other building types this goal is still far away. The potential of these buildings to meet a Nearly Zero Energy Standard was investigated by analyzing ten case studies representing non-residential buildings with different uses. The analysis shows that the primary characteristics common to critical building types are a dense building context with a very high degree of technical installation (such as hospital, research and laboratory buildings). The large primary energy demand of these types of buildings cannot be compensated by building and property-related energy generation including off-site renewables. If the future Nearly Zero Energy Standard were to be defined with lower requirements because of this, the state related properties of Bavaria suggest that the real potential energy savings available in at least 85% of all new buildings would be insufficiently exploited. Therefore, it would be useful to instead individualize the legal energy verification process for new buildings to distinguish critical building types such as laboratories and hospitals.

The safety of lithium-ion batteries is critical to the safety of battery electric vehicles (BEVs). The purpose of this work is to develop a method to predict battery thermal runaway in full electric vehicle crash simulation. The thermal-electrical-mechanical coupled finite element analysis is used to model an individual lithium-ion battery cell, a battery module, a battery pack, and a battery electric vehicle with 24 battery modules in a live circuit connection. The lithium-ion battery is modeled using a representative approach, with each battery internal component individually modeled to represent its geometric shape and realistic thermal, mechanical, and electrical properties. A resistance heating solver and Randles circuit model built with generalized voltage source are used to simulate the battery electrical behavior. The thermal simulation of the battery accounts for the heat capacity and thermal conductivity of various cell component materials, as well as heat conduction, radiation, and convection at their interfaces. The mechanical property of battery cell and battery module models is validated using spherical punch tests. The electrical property of the battery cell and battery module models is verified against CircuitLab simulation in an external short circuit test. The simulation result of battery module’s internal resistance agrees with the experimental data and the literature value. The multi-physics coupling phenomenon is demonstrated with a cylindrical compression simulation on the battery module. The multi-physics BEV model with 24 live battery modules is used to simulate the external short-circuit test and the side pole impact test. The simulations run time is less than 24 hours. The results demonstrated the feasibility of using representative battery model and multi-physics analysis to predict battery thermal runaway in full electric vehicle crash analysis.

The object of this work is to determine the correlation on the Nusselt number on the individual rows of a four-row tubular finned heat exchanger with continuous fins with a staggered tube arrangement using CFD modelling. Correlations for calculating Darcy-Weisbach friction factors on individual tube rows were also determined. Relationships for the Nusselt number and friction factor derived for the entire exchanger based on CFD modelling were compared with those available in the literature determined using experimental data. The maximum relative differences between the Nusselt number for a four-row exchanger determined experimentally and by CFD modelling are in the range from 22% for a Reynolds number based on a tube's outside diameter of 1,000 to 30% for a Reynolds number of 13,000. The maximum relative differences between the friction factor for a four-row exchanger determined experimentally and by CFD modelling are in the range of 50% for a Reynolds number based on a tube outer diameter of 1,000 to 10% for a Reynolds number of 13,000. The CFD modeling performed shows that in the range of Reynolds numbers based on hydraulic diameters from 150 to 1,400, the Nusselt number for the first row in a four-row finned heat exchanger is about 22% to 15% higher than the average Nusselt number for the entire exchanger. In the range of Reynolds number changes based on hydraulic diameter from 2,800 to 6,000, the Nusselt numbers on the first and second rows of tubes are close to each other. Correlations on Nusselt numbers and friction factors derived for individual tube rows can be used in the design of plate-fin and tube heat exchangers used in equipment such as air-source heat pumps, automotive radiators, air-conditioning systems and in air hot-liquid coolers. In particular, the correlations can be used to select the optimum number of tube rows in the exchanger.

The Xihan River basin is located in the southern part of Gansu Province, where flood disasters occur frequently in summer and autumn, which easily pose significant risks to human life. In order to improve the accuracy of flood disaster predictions and early warnings, a flood model suitable for this region was constructed based on the HEC-HMS (Hydrologic Engineering Center's-hydrologic modeling system) model and used to determine the critical areal rainfall for flood disasters. Calibration of this model was performed using data of four flood events from May to October between 2020 and 2021, reserving data of two additional flood events for model validation. Using the calibrated HEC-HMS model, the critical areal rainfall was determined for the Pingluo and Tanjiaba hydrological stations in the basin through the model testing method. The results indicate that: (1) The stable infiltration rate of the XiHanShui River Basin was between 0.06 and 0.10 mm/h, with runoff concentration times primarily varying from 22.5 to 24.1 hours, a direct runoff storage coefficient was 0.2 hours, and a base flow index decay constant seted at 0.03 hours. (2) During the calibration and validation periods, the average peak flow relative error was 7.56%, the average runoff volume relative error was 14.76%, the average peak occurrence time difference was -0.5 hours, and the Nash efficiency coefficient was 0.769. (3) The warning areal rainfall for the Pingluo and Tanjiaba hydrological stations were 108.1mm and 128.5mm, and the guaranteed areal rainfall were 230.8mm and 184.6mm. The HEC-HMS model demonstrated high applicability and accuracy in simulating flood events in the XiHanShui River Basin, providing technical support for hydrological research and operational applications in the region.

Refractory materials are used worldwide in process equipment. However, gaseous and liquid process products penetrate the surface layer, and deep into the volume of refractories destructing rather expensive constructions complicated to repair. To address this challenge, there is a need to develop protective coatings for refractory that can limit the penetration of working media and extend their operational lifespan. In this work, the application of gas-dynamic cold spraying (CGDS) to produce a coating on the refractory using fine titanium dioxide (TiO2) particles is explored. These particles are accelerated within a nitrogen flow, passing through a Laval nozzle, and then sprayed onto a fireclay surface. The mechanisms of particle deposition and layer formation on porous surfaces through experiments and numerical simulations were investigated. The geometry of a typical refractory pore was determined, which was then incorporated into Computational Fluid Dynamics (CFD) simulations to model the cold spraying process of porous substrates. As a result, the influence of the particle size on its velocity and angle of penetration into pores was established. Experimental findings demonstrate the effective closure of pores and the formation of a particle layer on the refractory surface. Furthermore, the nanoindentation tests for the refractory samples showcase capabilities for checking coating thickness for porous materials.

This study presents the design and comprehensive 3D multiphysics simulation of a novel microfluidic immunosensor for real-time, non-invasive monitoring of pro-inflammatory biomarkers in human sweat. The patch-like device, designed using COMSOL Multiphysics, integrates magnetofluidic manipulation with direct-field capacitive sensing. The sensor comprises two distinct units: an immunocomplex enhancement unit, employing a series of microcoils to optimize the binding efficiency, reaction kinetics, and homogeneity of biomarker-magnetic nanoparticle (MNP) interactions, thereby enhancing the sensor's specificity; and a layered capacitive sensing unit, designed to concentrate and detect biomarker-tagged MNPs, thus amplifying sensitivity. Simulations of the capacitive sensing unit revealed a substantial sensitivity increase of up to 42.48\% at an 85\% MNP concentration within the detection zone. These findings highlight the potential of the proposed immunosensor for efficient and precise real-time biomarker monitoring, which may facilitate early disease diagnosis and enable personalized healthcare interventions.

Amorphous Indomethacin has enhanced bioavailability over its’ crystalline forms, yet amorphous forms can still possess a wide variety of structures. Here, Empirical Potential Structure Refinement (EPSR) has been used to provide accurate molecular models on the structure of five different amorphous Indomethacin samples, that are consistent with their high energy x-ray diffraction patterns. It is found that the majority of molecules in amorphous Indomethacin are non-bonded or bonded to one neighboring molecule via a single hydrogen bond, in contrast the doubly bonded dimers found in the crystalline state. The EPSR models further indicate a substantial variation in hydrogen bonding between different amorphous forms, leading to a diversity of chain structures not found in any known crystal structures. The majority of hydrogen bonds are associated with the carboxylic acid group, although a significant number of amide hydrogen bonding interactions are also found in the models. Evidence of some dipole-dipole interactions are also observed in the more structurally ordered models. The results are consistent a distribution of Z-isomer intra-molecular type conformations in the more disordered structures, that dis-tort when stronger inter-molecular hydrogen bonding occurs. The findings are supported by 1H and 2H NMR studies of the hydrogen bond dynamics in amorphous Indomethacin.

As the automotive industry undergoes a phase of rapid transformation driven by technological advancements, the integration of driving simulators stands out as an important tool for research and development. The usage of such simulators offers a controlled environment for studying driver behavior; the alignment of data, however, remains a complex aspect that warrants a thorough investigation. This research investigates driver state classification using a dataset obtained from real-road and simulated conditions, recorded through JINS MEME ES_R smart glasses. The data set encompasses electrooculography signals, with a focus on standardizing and processing data for subsequent analysis. For this purpose, we used a recurrent neural network model, which yielded a high accuracy on the testing dataset (86.5%). The findings of this study indicate that the proposed methodology could be used in real scenarios and that it could be used for the development of intelligent transportation systems and driver monitoring technology.

Abstract Safflower (Carthamus tinctorius L.) is a multipurpose minor crop consumed by developed and developing nations around the world with a limited research fund and genetic resources. Genomic selection (GS) is an effective modern breeding tool which could help to fast track the genetic diversity preserved in genebank collections to facilitate rapid and efficient germplasm improvement and variety development. In the present study, we simulated four GS strategies to compare genetic gains and inbreeding rates during breeding cycles in a safflower recurrent selection breeding program targeting grain yield (GY) and seed oil content (OL). We observed positive genetic gains over cycles in all four GS strategies, where the first cycle delivered the largest genetic gain. Single traits GS strategies had the greatest gain for the target trait but with very limited genetic improvement for the other trait. Simultaneous selection for GY and OL via index indicated higher gains for both traits than crossing between the two single trait independent culling strategies. The the multi-trati GS strategy with inbreeding control (GS_GY+OL+Rel) showed lower inbreeding rate but similar gain compared to GS_GY+OL (without inbreeding control) after few cycles. Our finding lay the foundation for the future safflower GS breeding.

Heat transfer enhancement and hydrodynamic characteristics of nanofluid use in a micro heat exchanger is investigated for cooling electronic components working in hot climatic conditions. The cooling fluid employed was water and TiO2 nanoparticles at concentrations of 1% and 5%, Reynolds numbers ranged from 400 to 2000, and inlet temperatures ranged between 35ºC and 65ºC. At a nanofluid inlet temperature of 55ºC and a nanoparticle concentration of 1%, the Nusselt number increased by 23% up to 54% as the Reynolds number varied between 400 and 2000. At a nanoparticle concentration of 5%, the percentages which correspondingly enhanced the Nusselt number were 32% and 63%. The temperature of the electronic heating component decreased by 4.6-5.2ºC when the nanofluid concentration was increased from 0 to 5% at a Reynolds number of 400 and a nanofluid inlet temperature of 35ºC. Small increments in pressure drop of about 6% and 13% were observed at nanofluid concentrations of 1% and 5%, respectively. With nanoparticle concentrations of 1% and 5%, a Reynolds number of 2000 and a nanofluid inlet temperature of 35ºC, performance evaluation criterion (PEC) values of 1.36 and 1.45 were obtained. When the nanofluid inlet temperature was increased to 65ºC, the PEC parameter decreased to 1.02-1.10 for both concentrations.

The years 2021 and 2022 showed that maritime logistics are prone to interruptions. Especially the ports turned out to be bottlenecks with long queues of waiting vessels. This leads to the question of whether this can be (at least partly) mitigated by means of better and more flexible terminal operations. Digital Twins have been in use in production and logistics to increase flexibility in operations and are considered a reasonable fit. They are suitable for real-time data integration to support decision-making. However, the true potential of Digital Twins to enhance terminal operations still needs to be further investigated. A Delphi study is conducted to explore operational pain points, best practices to counter them, and how these best practices can be supported by Digital Twins. A questionnaire with 16 propositions is developed, and a panel of 17 experts is asked for their degrees of confirmation for each. The results indicate that today’s terminal operations are far from ideal and leave space for optimisation. The experts see great potential in analysing past working shifts data to identify reasons for poor terminal performance. Moreover, they agree on the proposed best practices and support the use of aiding IT solutions.

In the recent years, tubular nanostructures have been related with immense advances in various fields of science and technology. Considerable research efforts have been centered on the theoretical prediction and manufacturing of non-carbon nanotubes (NTs), which meet modern requirements for the developing of novel devices and systems. In this context, diatomic inorganic nanotubes formed by atoms of elements from the 13th group of the periodic table (B, Al, Ga, In, Tl) and nitrogen (N), have received much research attention. In the present work, the elastic properties of single-walled boron nitride, aluminium nitride, gallium nitride, indium nitride and thallium nitride nanotubes were numerically evaluated using the nanoscale continuum modelling approach (also called molecular structural mechanics). The elastic properties (rigidities, surface Young´s and shear moduli, and Poisson´s ratio) of nitride nanotubes are discussed with respect to the bond length of the corresponding diatomic hexagonal lattice. The results obtained contribute to a better understanding of the mechanical response of nitride compound-based nanotubes, covering a broad range from the well-studied boron nitride NTs to the hypothetical thallium nitride NTs.

Point defects induced by doping rare earth elements RE (Nd, Er) into the magnesium oxide host were investigated by classical atomistic simulations utilising the General Utility Lattice Program (GULP). Formation and association energies were calculated for the potential defect structures. Both isolated defects and defect complexes were considered. The most energetically favourable structures of defect complexes were found for rare earth doped and Li co-doped systems. The correlation between the association energy and the structure of the defect complex was investigated. The influences of Li were revealed with respect to energy and structure. The simulation results contribute to the understanding of the point defects of doped MgO and how Li influences the doping of rare earth elements in the MgO host.

In recent years, the economics of emotions (EoE) field, which aims to create models of the human mind, has grown quickly. EoE models work well with simulation theory (ST), which is one of the main theories of mind. EoE models show how people's behavior and emotions change based on their knowledge and perception of others. It is hoped that by developing this model, it will be possible to quantitatively analyze not only the mental states of real others, but also the subtleties of the minds of characters in novels in the future. Until now, the decision-making or the factual-reasoning mechanisms have been a black box in ST. This study analyzes how EoE models add to the understanding of ST.

Autonomous vehicle technology, employing image sensors for road marking recognition, is largely dependent on the Lane Departure Warning System (LDWS) to prevent vehicular deviations from driving lanes. The effectiveness of image-based lane recognition, however, is susceptible to environmental influences like weather conditions and the surrounding road environment. This study investigates the impact of road marking retro-reflectivity on LDWS under varied environmental conditions. Conducted at the Yeoncheon SOC Demonstration Research Center, the experiments encompassed a spectrum of weather scenarios, incorporating rainfall and shifts between day and night lighting. Controlled wear was applied to white, yellow, and blue road markings, followed by measuring their retro-reflectivity at different stages of degradation. The LDWS's performance was evaluated by assessing the recognition rates of these markings under these diverse environmental settings. The study reveals that enhanced retro-reflectivity significantly boosts LDWS detection, especially in challenging weather conditions. Furthermore, the research led to the development of a simulation framework to analyze the cost-effectiveness of road marking maintenance, aligning it with the safety needs of autonomous vehicles. This framework suggests the necessity for updated road marking guidelines that cater to the advanced needs of driver assistance systems and autonomous vehicle technology.

This study aims to analyse the technical viability and economic feasibility of rainwater harvesting systems for single and multifamily residential buildings in the city of Florianópolis, Brazil. Simulations were conducted for representative buildings in the city under different water usage scenarios and system designs, in a total of 36 simulation scenarios. An economic analysis was performed for four scenarios over a twenty-year period. Both initial and operational costs were considered and net present value, internal rate of return and payback used as feasibility indicators. Almost all of the cases simulated were technically viable for the group of houses, and up to 78.9% for flats. As for the economic analysis, for houses, between 60.1% and 74.8% of the cases were economically feasible, achieving a discounted payback period ranging from 6.2 to 8.6 years. For flats, between 57.8% and 64.2% of the cases were economically feasible, achieving a discounted payback period ranging from 4.8 to 5.6 years. As the water tariff in the city underwent changes recently, the former and current tariff formats were compared. The current tariff format provides more economic benefits for saving potable water, and leads to a higher net present value and a shorter discounted payback period.

The multiphase motors due to their reliability find new areas of application in the industry and transportation. Developing of any system with multiphase motors at first requires elaborate model of the system, define control mode and controllers. The model of control system for the six-phase drive is based on its conventional d-q mathematical model and indirect field-oriented control. Simulink model of six-phase drive with indirect field-oriented control and simulated with two types PID and PID fuzzy controllers. The simulation results, reflecting step response and provided speed reference law as well as load application at constant speed, are presented and analyzed. Fuzzy controller with 49 rules is considered and applied. Six-phase electric drive with field-oriented control at well-tuned PID controller has good step response specifications: settling time 0.13 s at starting without load, step response has no overshoot, small about 1 % short time decrease of speed at load of 5 Nm application. The system employing PID fuzzy controller shows slightly better results in response to torque application: the decrease in speed 1 % is eliminated in shorter time. Simulation results indicate the robustness of both systems with six-phase drive to disturbance and provide high quality transient specifications at determined reference speed.

This paper provides the first-time ever analytic modelling for Pointwise Stationary Fluid Flow Approximation(PSFFA) model of the non-stationary

In rock blasting for mining production, stress waves play a major role in rock fracturing along with explosion gases. Better energy distribution improves fragmentation and safety, lowers production costs, increases productivity, and controls ore losses and dilution. Blast outcomes vary significantly with the choice of the explosive and the properties of the rock mass encountered. This study analyzes the effects of rock mass and explosives properties on the blast outcomes through numerical simulation using data from the case study and later validates the simulation results from the field blast fragmentation. The outcomes suggest that, for a given set of rock properties, the choice of explosive has a major influence on the resulting fragmentation. Strong explosives favor large fracture extents in hard rocks, while less strong explosives offer a better distribution of explosive energy and fractures. The presence of rock structures such as rock con-tacts and joints influences the propagation of stress waves and fractures depending on the structures' material properties, intensity and orientations, and the direction and strength of the stress wave. To achieve effective fragmentation, the blast design should mitigate the effect of variability in the rock mass by ensuring adequate energy distribution within the limits of geo-metrical design.

Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas mesoscopic models achieve better performances in dense situations. This paper proposes and evaluates a novel agent-based architecture to enable agents to dynamically change their operational model based on local density. The ability to combine microscopic and mesoscopic models for multi-scale simulation is studied through a use case of pedestrians at the Festival of Lights, Lyon, France. Pedestrian outflow data is extracted from video recordings of exiting crowds at the festival. The hybrid model is calibrated and validated using a genetic algorithm that optimizes the match between simulated and observed outflow data. Additionally, a local sensitivity analysis is then conducted to identify the most sensitive parameters in the model. Finally, the performance of the hybrid model is compared to different models in terms of density map and computation time. The results demonstrate that the hybrid model has the capacity to effectively simulate pedestrians across varied density scenarios while optimizing computational performance compared to other models.

This research paper presents a comprehensive study on the gasification of wheat straw pellets in a 10-kW fixed bed gasifier through a combination of Computational Fluid Dynamics (CFD) simulation and experimental validation. The developed 2D CFD model in ANSYS meshing simulates the gasification process in ANSYS Fluent software. The investigation evaluates key parameters such as equivalence ratio, higher heating value, and temperature distribution within the gasifier to enhance syngas production efficiency. The simulated results exhibit a noteworthy agreement with experimental data obtained from gasification. The impact of the equivalence ratio on gas production and lower heating value (LHV) is systematically explored, revealing that an equivalence ratio of 0.35 is optimal for syngas production. The resulting producer gas composition at this optimum condition includes CO (~27.67%), CH4 (~3.29%), CO2 (~11.09%), H2 (~11.09%), and N2 (~51%). The study further investigates the positive influence of reactor temperature on increasing syngas quantity while considering the uneven shape of the reactor and various thermal reactions affecting temperature, static pressure, velocity, and density. The findings contribute valuable insights to improve the efficiency of fixed-bed gasifiers, offering essential information on performance parameters for sustainable and optimized syngas production.

The application of numerical simulation methods for studying vertical-axis wind turbines offers significant advantages over conventional horizontal-axis wind turbines regarding wind energy utilisation, start-up wind speed, and environmental impact. This paper aims to investigate and establish the aerodynamic design performance of asymmetrical (NACA 4412) airfoils used in the application of vertical-axis wind turbines. The computational fluid dynamics (CFD) simulation uses Ansys software based on the Reynolds Averaged Navier-Stokes (RANS) equations. The aerodynamic parameters (pressure and velocity) are evaluated and compared within a range of angles of attack (AoA) 5-12 degrees at a fixed Reynolds number, as is a usual condition for wind turbine application. The lift coefficient (Cl), drag coefficient (Cd), and Cl/Cd ratio are obtained within the range AoA for the asymmetrical airfoils, and the performances have been predicted using the potential flow panel and CFD methods. This study suggests that while Xfoil may not be as precise as computational fluid dynamics (CFD), its predicted lift and drag coefficients generally align with experimental results. These help us to understand the best air-foil selection in a wind turbine application and predict its optimum AoA at which it performs at its best.

Natural gas is an important energy source among various fossil fuels. However, natural gas typically contains a significant amount of water vapor, which can pose challenges in its usage. Therefore, the process of removing water vapor from natural gas, known as gas dehydration, is crucial in the gas industry. The presence of water vapor in the gas supply can lead to the formation of hydrates, which can cause issues such as blockages in pipelines. To tackle this problem effectively, gas dehydration makes use of Tri ethylene glycol (TEG) as a drying agent. TEG works by selectively absorbing water vapor from the natural gas flow, thereby significantly reducing its moisture content.In the gas dehydration process, wet gas is treated by using lean glycol in an absorber, where the water vapor is removed. The resulting rich glycol is then recovered and recycled for further use. In this study, we explore the possibility of replacing nitrogen with dry natural gas in the re-generator of the glycol dehydration system. The aim is to evaluate the feasibility and effectiveness of this alternative approach. To assess the performance of both techniques, we employed HYSYS modeling and simulation. Through this analysis, we compared the capital and utility expenses associated with each method while ensuring that the glycol purity requirements remained unchanged. By examining the results obtained from the simulations, we can gain insights into the economic viability and efficiency of utilizing dry natural gas in the re-generator stage of the glycol dehydration process.In addition to the primary purpose of removing water vapor, the wet gas obtained from the stripping mechanisms in the glycol dehydration process can serve additional functions. It can be utilized to power steam pumps and compressors, thereby maximizing energy efficiency within the system. Alternatively, the wet gas can be recycled back into the process for further treatment. To develop a comprehensive understanding of the entire mechanism, we constructed a model based on the actual flow diagram. This model takes into account the various components and processes involved in the glycol dehydration system, including the stripping mechanisms and their connection to other equipment. By analyzing the data and outcomes generated by this model, we can derive valuable insights. These findings can be utilized to optimize the heat and material balance within the plant, ensuring efficient operation and potentially leading to the design of an improved system in terms of energy consumption and overall performance

In this work, the degassing process of corn seeds was experimentally and numerically analyzed by removing air or other gases from around the seeds, specifically from the seed coating, in a rough vacuum chamber. The two complementary variants are employed to understand and optimize this process to improve the quality and germination rate of the seeds. Several experiments were conducted with well-established durations and masses of corn seeds at different temperatures to observe and record the behavior of the system, facilitating the modeling of the degasification process in the vacuum compartment. Modeling the degasification operation in the vacuum chamber allowed for determining the pressure profiles on the vacuum chamber and its lid. Numerical simulations were either conducted using a simulation program developed in the Visual Basic Applications (VBA) language for Microsoft Excel to model the degassing process in the vacuum chamber, or with the assistance of specialized software (transient structural analysis and simulation program in the ANSYS Workbench environment). Statistical analysis of the correlation between experimental and estimated pressure values revealed that both the proposed mathematical model and the solution method are well-chosen, with differences expressed through the absolute error (EA) being very small. Structural dynamic analysis carried through the Finite Element Method (FEM) highlights that the chosen materials for manufacturing the vacuum chamber vessel (316 stainless steel) or the chamber lid (transparent acrylic plastic) are durable and capable of withstanding the desired pressure and temperature demands in the seed treatment process. Additionally, through structural dynamic analysis, it was possible to study the deformation of system components, providing a detailed perspective on their structural distribution.

This paper introduces an innovative framework for the integration of artificial empathy into robot swarms to enhance communication and cooperation. The proposed model relies on fuzzy state vectors to represent the knowledge and environment of individual agents, accommodating uncertainties in the real world. Utilizing similarity measures, the model compares states, enabling empathetic reasoning for synchronized swarm behavior. A practical application example demonstrates the model’s efficacy in a robot swarm striving for a common goal. The evaluation methodology involves the Open Source Physical-based Experimentation Platform (OPEP), emphasizing empirical validation in real-world scenarios. The paper proposes a transitional environment that allows automated and repeatable execution of experiments on a swarm of robots using physical devices.

The CMT (Cold Metal Transfer) arc welding process is a convenient instrument for the assembly of thin sheets [1], [2]. More particularly, it permits the decrease of the amount of heat transferred to the parts to-be assembled, thus reducing their subsequent deformations. The present work aims at simulating the CMT welding of thin stainless-steel sheets in order to develop an approach that allows the prediction of temperature fields, as well as final deformations induced by the welding process. For that purpose, instrumented tests and numerical simulations were set aiming at comparing the experiments with simulations. Butt-welding of stainless-steel sheets was considered, with a thickness ranging from 1 to 1.2 mm. The weld seam samples were observed in order to set an equivalent heat source for each configuration. Moreover, the electric current and voltage were surveyed, and temperature measurements were performed using K-type thermocouples. In addition, displacement measurements were obtained using the DIC (Digital Image Correlation) technique. Thermomechanical simulations were then carried out using an equivalent heat source approach, considering the phase changes of elements, i.e. the transitions from solid to liquid and from liquid to solid. These simulations also consider the actual geometry of seams induced by addition of a filler material.

Folk residence in the cold region of Northeast China is an important part of China's traditional folk residence, with significant geographical representation. In this paper, we take the residential compounds of villages and towns in the cold region of Northeast China as the research object, summarize four typical layout forms of residential compounds of villages and towns in the cold region of Northeast China, simulate the wind environment of compounds of different layout forms in winter by using the computer numerical simulation software Fluent, and then analyze and evaluate the wind environment of compounds by combining with the evaluation standard of wind speed ratio and considering the area of wind shadows, number of vortices and other factors.

Chromium poisoning strongly influences the performance of solid oxide fuel cell (SOFC) stacks. A three-dimensional, time-dependent, computational fluid dynamics model of a single channel of a F10 SOFC stack in Forschungszentrum Jülich GmbH is developed to investigate chromium poisoning for different stack designs, temperatures and absolute air humidities. The model takes into account both chemical and electrochemical mechanisms of chromium poisoning and is able to predict the spatial distribution of SrCrO4 and Cr2O3. The voltage degradation over 100 kh can be simulated quantitatively. According to the simulation results, chromium poisoning is almost eliminated by the application of the protective coating fabricated by the atmospheric plasma-spraying (APS) technology. Besides, with the help of the APS protective coating, operating a SOFC stack with less dehumidified air at 650 oC is possible according to the simulation.

Knowledge of water availability in terms of spatial (i.e., depth) and temporal variability of soil water is essential to describe soil water infiltration and storage processes accurately. Therefore, performing simulations of soil water dynamics can be a valuable tool to evaluate different land uses and their impact on water availability. Consequently, this study aimed to model the volumetric soil water content (θ, cm3 cm-3) under agroforestry systems (AFS) with cocoa. For this purpose, the θ was monitored at different depths (0-20, 20-40, 40-60, 60-80, 80-100 cm) in the soil profile of four plots (20 × 50 m) of cocoa under agroforestry systems. Environmental conditions significantly influenced the water balance of the cocoa crop. There were seven moments when evapotranspiration (ET0) was higher than 5 mm d-1. During those moments, the environment exhibited higher PAR values of 1041 µmol m-2 s-1, very low atmospheric relative humidity (RHa) levels (around 45%), higher ambient temperatures of 32.2 ºC and a vapor pressure deficit of 1.6 kPa whose θ levels reached 0.32 cm3 cm-3 and a water balance of -5.7 mm, which presented negative values during most of the study period. The θ obtained from the HYDRUS-1D model presented a slight bias as a high level of coherence between the observed values, based on the model's goodness-of-fit estimators. The above provides accurate simulations of soil water content at various depths, much-needed information for management schemes for cocoa cultivation under agroforestry systems.

The steel grid structure with bolted ball joints is gaining popularity in offshore platforms and aquaculture cages, but the corrosion resistance of these joints is a critical safety concern. This article introduces an innovative method to enhance the sealing performance of bolted ball joints, preventing seawater ingress and corrosion. The approach involves creating a sealed surface within the contact gap between the sleeve and connecting components. Circular grooves and sealing washers are added to both ends of the sleeve. A two-dimensional finite element analysis model of the bolted ball joint with the sealing structure was created using SOLIDWORKS and ANSYS. The study analyzes the sealing gasket's contact pressure at various compression levels and evaluates its performance with bubble tests for air tightness. Research results show a linear relationship between contact pressure and compression rate, with a sealing pressure of 5.95MPa achieved at a 14% compression rate. This simple, cost-effective sealing method effectively prevents corrosion from seawater, making it ideal for marine environments.

In the process of construction and operation of the pumping station, a large number of axial flow pumps pose a threat to the survival of fish in the natural environment. Through experiments, the survival conditions of many kinds of fish in extreme positive and negative pressure environment are explored, and -40 kPa is established as the low pressure damage threshold, which is used as a reference to analyze the probability of fish damage caused by pumps. The immersion boundary-lattice Boltzmann numerical method (LES-IB-LBM) based on large eddy simulation is used to optimize the parameters of the prototype runner of axial flow pump. A new type of runner with leading edge thickness of 11.4mm and blade cutting angle of 18 ° is optimized. This kind of runner has both hydraulic performance and fish-passing ability. The runner of the fish-friendly axial flow pump effectively guides the fish into the low risk area and reduces the risk of friction, shear and impact damage to the fish. the total impact mortality ratio of the runner of the axial flow pump before and after optimization is close to 7:1. The pressure damage analysis shows that the lowest negative pressure of the fish is -59.2 kPa, which is higher than -64.5 kPa of the prototype pump, and the highest positive pressure of the body surface is 11.8 kPa, which is lower than the 43.8 kPa of the prototype pump. Shear damage analysis shows that the fish will not be damaged by shear in the prototype pump and fish-friendly pump.

The cities of the future are places of sustainable mobility and a continuous reduction in the amount of harmful substances entering the surrounding environment. Current emission models are mainly dedicated to fully combustion vehicles and do not fully reflect the actual emissions of vehicles in the fleet, which is becoming increasingly diverse. The increasing share of hybrid and electric vehicles is generating the need to measure emissions and energy consumption from these vehicles and to develop new emission models that are accurate. This problem mainly concerns low-emission zones in cities, where mobility planning should be based on simulation models that are based on a continuously updated database. This work concerns the proposal of a two-dimensional model of emissions from hybrid vehicles using artificial neural networks for low-emission zones. The results can be used to further develop such emission models.

It is imperative to examine the performance of wind turbines both in steady and unsteady states due to their significant role in generating renewable energy by utilizing wind power. The computational fluid dynamics method (CFD) is one of the most efficient tools in this field, and the unsteady state has a great deal of importance when predicting turbine performance. Using the CFD method, the hydrodynamic performance of two types of offshore and onshore horizontal-axis wind turbines in the unsteady state was examined. Offshore wind turbines were modeled using the SST turbulence model and onshore wind turbines were modeled using the large eddy simulation (LES). Three-dimensional results of the simulation were compared and validated with experimental results, and good agreement between the two results indicates that the assumptions and method were accurate. Vortices were also studied in relation to the blade tip and their formation and development. Increasing the number of blades results in a reduction in torque, as well as a rise in vortices caused by the tips of the rotor blades. Due to the intensity of turbulence, the distribution of pressure on the surfaces will become irregular as the wind speed increases.

Controlling injection parameters is paramount when it comes to producing high-quality green parts using powder injection molding. This work combines experimental and numerical approaches to study the impact of injection parameters on mold in-cavity pressure and on the overall quality of green parts produced by low-pressure powder injection molding. The properties of two low-viscosity feedstocks (formulated from a water-atomized stainless-steel powder and wax-based binder system) were measured and implemented in an Autodesk Moldflow numerical model to quantify the molding pressures, which were finally validated using experimental real-scale injections. The results confirmed that an increase in mold temperature, an increase in feedstock temperature, and a decrease in solid loading decrease the mold in-cavity pressure, which was correlated with the feedstock viscosity. As a key result, real-scale injections confirmed that a minimum flow rate was required to avoid atypical high in-cavity pressure leading in several visual defects such as weld lines, flow marks, cracks, sinks, and incomplete filling. Due to differences in its thermal transfer properties, this flow rate threshold value decreases as the feedstock solid loading increases. For injection speeds higher than this value, the injection pressure measured experimentally was linearly correlated with the injection flow rate.

The extraction of roof feature lines is an important foundation for realizing large-scale and batch 3D modeling. However, the current traditional point cloud segmentation algorithms do not have satisfactory results in extracting roof feature lines of Chinese traditional residential buildings. In this paper, taking Jingping Village in Western Hunan as an example, we propose a method that combines multiple algorithms based on slope segmentation of roof patches to extract feature lines. Firstly, VDVI and CSF algorithms are used to extract the building and roof point cloud based on the MVS point cloud. Secondly, according to roof features, village buildings are classified, and 3D roof point cloud is projected into 2D regular grid data. Finally, the roof slope is segmented via slope direction, and internal and external feature lines are obtained after refinement through Canny edge detection and Hough straight line detection. Results reveal that this method effectively extracts feature lines of low-building roofs in traditional villages, with slope-based roof surface segmentation accuracy surpassing 99.6%. This method significantly outperforms the RANSAC algorithm and region segmentation algorithm.

BMAP-27 peptide known to exert cytotoxic effects against cancer cells by membrane integrity disruption. In the current investigation, we aimed to study the role of the BMAP-27 peptide in reducing colon cancer cell proliferation and inducing apoptosis. This study utilized both primary and metastatic colon cancer cell lines (SW480 and SW620). Proliferation was measured using CCK-8, and cellular damage was analyzed by lactate dehydrogenase assay. The study assessed apoptosis, cell cycle, and proliferation by measuring the expression of CASPASE3, BAX, BCL-2, TP53, CDK-6, PCNA, Wnt11, AXIN1, and CTNNB1. Additionally, in-silico studies were conducted to determine the binding affinities of BMAP-27 with APC and β-catenin proteins. BMAP-27 peptide reduced colon cancer cell proliferation, upregulated CASPASE3, BAX, TP53, AXIN1 expression, and downregulated BCL-2, CDK-6, PCNA, WNT11, CTNNB1 in both colon cancer cell lines, however, demonstrated higher activity in primary than metastatic colon cancer cells. The molecular dynamic simulation revealed substantial binding affinity of the peptide to adenomatous polyposis coli and β-catenin proteins.BMAP-27 peptide effectively inhibited the proliferation and enhanced apoptosis in the primary than in metastatic colon cancer cells. In-silico findings suggest that BMAP-27 exhibits a strong binding affinity with APC and β-catenin, highlighting its potential role as an anti-colon cancer agent.

In recent years discrete element method (DEM) has gradually been applied to the traditional fluidization simulation of fine particles in micro fluidized bed (MFB). The application of DEM in simulating fast fluidization of fine particles in MFB has not yet received attention. This article presents a drag model that relies on the surrounding environment of particles, namely particle circumstance-dependent drag modle or PCDD model. Fast fluidization in MFB of fine particles is simulated using DEM based on the PCDD model. It is found that the gas-solid two-phase flow in MFB meets the common law of fast fluidization in circulating fluidized bed (CFB) to a certain extent, and also presents a special law that is significantly different from that in CFB. Simulations indicate that the local structure in MFB exhibits particle aggregation which is a natural property of fast fluidized, forming a structure where continuous dilute phase and dispersed concentrated phase coexist. The formation and fragmentation of particle clusters in different local regions of the bed have time synchronization. There exists strong effect of solid back-mixing in MFB, leading to relatively low outlet solid flux. The gas back-mixing effect is, however, not so distinct. The axial porosity shows a monotonically increasing distribution with the bed height, but does not strictly follow the single exponential distribution. The solid volume fraction at the bottom of the bed is significantly lower than the correlated value in CFB. The axial heterogeneous distribution of the cross-sectional average porosity in the lower half of the bed is also weakened. The radial porosity shows a distribution pattern of higher in the central region and lower in the sidewall region. Compared with the correlation results in CFB, the porosity near the central region in MFB is relatively low, while the porosity near the sidewall region is relatively high. The geometric size of the container, especially the radial size, is much smaller than that of a CFB. The relative area of contact between the MFB wall and particles is larger, and the wall friction factor becomes more significant. This may be the main reason for the time synchronization of particle agglomeration, severe particle back-mixing, low outlet solid flux, monotonically increasing axial porosity and weak core-annular structure of radial porosity.

This work focused on proposing a plan for improvement and control of the customer service process in a customer service center, based on a waiting line analysis where it describes all the elements that interact in the system and a statistical analysis of processes to define the state in which it operates. Subsequently, the simulation of processes is applied to represent the system studied, and with it, to be able to evaluate different strategies for improvement and increase in productivity. The following strategies were evaluated: correction of the instability of customer service processes, establishment of new specification limits according to the promise of value to be fulfilled to customers, human resource management, administrative technical support. Finally, with the results obtained from the simulation of the system, the improvement and productivity increase plan is planned according to the DMAMC (Define, Measure, Analyze, Improve, Control, or DMAIC) continuous improvement cycle established in six sigma

Shape Memory Polymer (SMP) actuators are smart materials that adapt and switch shape in response to environmental conditions, allowing controlled and dynamic building systems. The integrated SMP strip enabled the adaptive facade shading system to operate independently and with flexibility under certain thermoresponsive conditions to regulate building performance. This study aims to improve adaptive façade performance in a hot-humid climate by determining optimal thermal activation factors for the shape memory polymer. This was achieved by comprehensively examining and analysing the impact of various SMP activation parameters on energy efficiency, thermal comfort, and visual comfort. In addition, dynamic IES-VE building energy simulation was used to evaluate the thermal performance of the adaptable facade. The results were validated using a multicriteria approach to compare with the existing glass façade of a high-rise apartment. The results showed that the coactivation technique, which combines solar radiation and air temperature triggers, proved to be the most efficient strategy to improve the performance of the adaptive façade. This strategy minimised heat gain, lowered indoor temperatures, reduced glare, and enhanced daylight comfort, resulting in notable energy savings through reduced cooling consumption. The study concluded that the utilisation of SMP actuators with fine-tuning activation parameters significantly optimised adaptive façade performance, promoting functionality, efficiency, and sustainability in buildings.

Traditional numerical techniques such as sliding mesh, dynamic grid mesh, and others, have many limitations in dealing with flow simulation with large-scale movement of solid boundaries; which is the case for complex-shaped hydraulic turbomachinery such as propellers, pumps and turbines. The immersed boundary (IB) method provides a new approach to solve the above limitations. Therefore, this study proposes an sharp-interface IB method based on the level-set function that is suitable for simulating the flow through turbomachinery with complex geometries. This method is applied to actual three-dimensional numerical simulations of high-Reynolds number propellers using an in-house computational fluid dynamics solver. The results show that the proposed method can provide comparatively accurate predictions of unsteady load coefficients within the propeller flow passage, and capture the correct propeller wake characteristics as well as the interaction between the propeller wake and free surface. This study aims at providing a theoretical basis and engineering reference for the application of the IB method in engineering numerical simulations.

Polymethyl methacrylate (PMMA) polymer is widely used in various fields today. In order to thoroughly reveal the structural impact performance of PMMA materials, this paper is based on the comprehensive Johnson-Cook constitutive model and damage failure model, and accurately confirm the J-C constitutive and damage failure model parameters of PMMA through material test data, The dynamic process of steel bullet impacting PMMA plate structure is analyzed by finite element software ABAQUS. The calculation results show that the numerical simulation results in this paper are in good agreement with the experimental test data. Therefore, the feasibility and accuracy of the impact analysis of PMMA structures based on J-C constitutive and damage failure models in this paper are studied. Finally, based on the J-C constitutive model and damage failure model, the variation of the residual velocity of the bullet with the PMMA plate thickness is analyzed in depth, that is, the results show that the residual velocity of the bullet has a certain linear relationship with the plate thickness.

This paper presents a comparison of two methods to represent variable blade inertia in two codes for aero-servo-elastic simulations of wind turbines: the nonlinear aeroelastic multi-body model HAWC2 and the nonlinear geometrically exact beam model BeamDyn for OpenFAST. The main goal is to enable these tools to simulate the dynamic behavior of a wind turbine with variable blade inertia. However, in order to simulate the structural response of wind turbines with variable blade inertias, the source code of load simulation tools need to be modified. This is due to the fact that, currently, state-of-the-art load simulation tools for wind turbines are unable to simulate variable rotor blade inertias. The validity of the modified codes is proven based on a simple beam model. The validation shows very good agreement between the modified codes of HAWC2, BeamDyn and an analytical calculation. The add-on of variable blade inertias is applied to reduce the mechanical loads of a 5 megawatt reference wind turbine with an integrated hydraulic-pneumatic flywheel in its rotor blades.

Sowing accuracy is a critical factor in evaluating the precision of sowing equipment, and the sowing rate of the sowing equipment developed at home and abroad cannot reach 100 %, so this paper designs a seed reseeding device, aiming to improve the sowing rate secondly. Firstly, the structural composition of the seed reseeding device is introduced; secondly, according to the production object selected in this paper, kale seed (Jingfeng No.1), the best combination of factors and levels of the suction nozzle is 8 m/s inlet speed, 1.8 mm aperture, 18 mm lead and V-shaped nozzle by using orthogonal experiment; then, the EDEM software was used to conduct the vibration test, and it was found that the seed group “boils” steadily at about 15.13 mm (the depth of the reseeding tray is 23 mm), which can effectively improve the suction rate of the suction nozzle; finally, by combining the simulation results of the flow field using Fluent/ANSYS software and the spatial distribution of seeds, the number of seeds in the effective adsorption range of a single suction nozzle is about 4. The determined number of seeds, approximately 4, accounts for only 0.04% of the total number of seeds generated by the simulation. This percentage ensures high suction precision and a single seed rate, particularly under working conditions where a 72-hole tray is being sowed. In general, domestic sowing accuracy ranges from 90% to 95%. With this configuration, the purpose of improving the sowing rate twofold can be achieved.

To effectively estimate airport terminal area capacity and assess the maximum throughput the sector can achieve when the capacity is given, this research proposes an approach to assess the terminal area capacity from the viewpoint of service provision resources. Terminal area capacity is optimized based on the equilibrium of air traffic service resource supply and demand. The supply-demand nexus is examined in consideration of terminal area route structure, traffic flow characteristics, and safety regulations. A flight service probability matrix and a terminal area demand and supply service time model are constructed to quantify resource expenditure at varied capacity levels. A optimization model is then developed to apportion maximal capacity under resource limitations. Model computation and computation results demonstrate the deviation between estimated and amended capacities is under 0.3 flight sorties per hour. The outcomes are congruent with historical statistics, thereby validating the accuracy and reliability of the model proposed in this study. Given capacity parameters, the model can deduce the maximal aircraft quantity served concurrently in terminal areas during peak periods. These revelations indicate the submitted model furnishes theoretical foundation and reference for terminal area sector partition and traffic alerting.

Taking a certain type of test centrifuge as the research object, the finite element model of the test centrifuge is established, the vibration characteristics and aerodynamic performance of the test centrifuge are analyzed, and the structural optimization design of the test centrifuge is carried out. In this paper, the load is applied according to the actual working condition of a certain type of test centrifuge. The vibration of the mounting seat of the test centrifuge is analyzed and the structure of the mounting seat is optimized. After optimization, the vibration of the mounting seat is 77.38 % lower than that of the original mounting seat. Then, the aerodynamic analysis of the test centrifuge is carried out. The analysis results show that the test centrifuge moves more smoothly under the whole package shell and the steady flow shell, and the resistance decreases and the shaft load decreases. Finally, the steady flow shell of the test centrifuge is optimized. The analysis shows that the increase of the width of the steady flow shell can reduce the resistance coefficient, which is helpful to the stability of the test centrifuge during operation and reduces the unbalanced response of the system caused by air resistance.

In econometrics and finance, volatility modelling has long been a specialised field for addressing a variety of issues pertaining to the risk and uncertainties of an asset. This study presents a robust framework, through a step-by-step design, that is relevant for effective Monte Carlo simulation (MCS) with empirical verifications to estimate volatility using the Generalized Autoregressive Score (GAS) model. The framework describes an organised approach to the MCS experiment that includes "background (optional), defining the aim, research questions, method of implementation, and summarised conclusion". The method of implementation is a workflow that consists of writing the code, setting the seed, setting the true parameter a priori, data generation process, and performance assessment through meta-statistics. Among the findings, it is experimentally demonstrated in the study that the GAS model with a lower unconditional shape parameter value can generate a dataset that adequately reflects the behaviour of financial time series data, relevant for volatility estimation. This dynamic framework is intended to help interested users on MCS experiments utilising the GAS model for reliable volatility calculations in finance and other areas.

A simulation test system for the two-dimensional (2D) fuze overload loading process was designed to address the loading issues of recoil overload and centrifugal overload in fuze safety and arming (S&amp;A) devices. By incorporating centrifuge rotation energy storage, impact acceleration simulation, and equivalent centrifugal rotation simulation, a block equipped with a fuze S&amp;A device was accelerated instantly upon being impacted by a centrifuge-driven impact hammer, simulating recoil overload loading. The impact hammer was retracted instantaneously by adopting an electromagnetic brake, which resulted in the centrifugal rotation of the block around its track, to simulate the centrifugal overload loading. The dynamic equations of the simulation test system and the equations of impact hammer motions were established, whereby the rotation speed of the centrifuge and the braking force of the electromagnetic brake were calculated and selected. A dynamic model of the collision between the impact hammer and block was established using ANSYS/LS-DYNA software for simulation analysis. The acceleration curves of the recoil overload and centrifugal overload with variations in the centrifuge speed, cushion material, and buffer thickness were obtained, which verified the feasibility of the proposed loading simulation method. 2D overload loading simulation tests were performed using the developed simulation system, and the acceleration curves of the recoil overload and centrifugal overload were measured. The test results indicated that the proposed system can accomplish 2D overload loading simulations for a recoil overload of several 10000 g and centrifugal overload of several 1000 g.

Road intersections are made of asphalt pavement, a popular road surface material used worldwide. The pavement may suffer deformities and deterioration, resulting in higher maintenance expenses and an elevated likelihood of road accidents, due to factors such as heavy vehicles and environmental variables like temperature and rainfall. To tackle these obstacles, researchers have devised several machine-learning algorithms and optimization techniques. These tools aim to forecast and scrutinize pavement deformation, with the goal of refining pavement design and maintenance approaches, as well as obtaining a more comprehensive comprehension of the factors that impact pavement effectiveness. This paper shows that heavy vehicles contribute significantly more to road erosion, and the retention and braking of vehicles greatly impact roadways. We also emphasize the statistical errors computed on the actual data range and demonstrate the results of the multilayer perceptron (MLP) model. The MLP model used the lath erosion standard to simulate future impact. Even though the model given is based on a small sample of data from one intersection, its estimates for road erosion in a year were found to be accurate when contrasted to real data. Controlling traffic flow can significantly improve road conditions, reducing erosion decay by reducing the time spent at intersections and other parameters. We conclude that machine learning can help control traffic flow, which can significantly improve road conditions, reducing vehicle time stretches at intersections.

This research investigated the antihypertensive effects of tamarind products and compared their potentials based on their animal model’s data verified by molecular docking, multitarget interactions in network pharmacology, and dynamic simulation assays. The GC-MS characterized tamarind products were administered to the cholesterol-induced hypertensive Wistar albino rat models. Two-week-intervened animals were dissected to collect serum and organs which were respectively subjected to the analyses of hypertension-linked markers and tissue architectures. Lead biometabolites of tamarinds interacted with eight target receptors in molecular docking and dynamic simulation studies and they were tested for multitarget interactions using network pharmacological analyses. Results showed that serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), C-reactive protein (CRP), Troponin I, and lipid profiles were maximally reinstated by the phenolic-enriched ripened sour over the sweet tamarind flesh extracts, but seed extracts had a smaller influence. Among the tamarind’s biometabolites, Gamma-sitosterol (ϒ-sitosterol) was found to be the best ligand in managing hypertension via the possible ligand-receptor interactions with the guanylate cyclase which displayed the best drug-likeliness through the highest binding energy -9.3 Kcal. Multitargeted interactions-based degree algorithm and phylogenetic tree of pathways showed 14 targeted genes, of which NR3C1, REN, PPARG, and CYP11B1 hub genes, were consistently modulated by the ϒ-sitosterol to reduce hypertension and related risk factors. The dynamic simulation study showed that the P-RMSD values of ϒ-sitosterol-guanylate cyclase were stable between 75.00 to 100.00 ns at the binding pocket. The findings demonstrate that ripened sour tamarind extract may be supplemented to be a more prospective antihypertensive target or nutraceuticals affirming through advanced preclinical and clinical studies.

Home care centers face both an increase in demand and many variations during the execution of routes, compromising the routes initially planned: robust solutions are not effective enough, it is necessary to move on to resilient approaches. We create a close to reality use case supported by interviews of staff at home health care centers, where caregivers are faced with unexpected events that compromise their initial route. We model, analyze and compare three resilient approaches to deal with these disruptions: a baseline approach without any collaboration, a distributed collaborative approach, and a centralized collaborative approach, where we propose a centralization and sharing of information to improve local decision-making. The latter reduces the number of late arrivals by 11% and the total time of late arrival by 21%, and also halves the number of routes exceeding the end of work time (contrary to the distributed collaborative approach, due to the time wasted reaching colleagues). The use of a device, such as a smartphone application, to centralize and share information thus allows better mutual assistance between caregivers. Moreover, we highlight several possible openings like the coupling of simulation and optimization to propose a more resilient approach.

The adsorption of proteins on polymer is widely used in biosensors. Here, molecular dynamics (MD) simulation was used to study the immobilization of angiotensin converting enzyme II (ACE2) with six initial orientations proposed on polystyrene (PS) at the ambient conditions of pH (4.5, 6, 7, 8, 9.5) and NaCl (0.01, 0.05, 0.1, 0.15, 0.2, 0.25 M). ACE2 immobilization under favorable ambient conditions was characterized by minimum distance (short), settlement time (fast), interaction energy (substantial) and protein configuration (stable). ACE2 orientations proposed in 0.15M NaCl were respectively preferable to (90, 0, 0), (0, 0, 0) and (0, 270, 0), (180, 0, 0) and (0, 90, 0), (90, 0, 0) at pH 4.5, 6, 7, 9.5. ACE2 immobilization was further evaluated at pH 7 by optimizing NaCl concentration. Its proposed orientations of (i) (0, 270, 0), (ii) (0, 0, 0) and (90, 0, 0), and (iii) (0, 90, 0) and (90, 0, 0) were preferable in 0.05, 0.1 and 0.2 M NaCl, respectively. The great significance of cubic-orientation settlement mode provides tangible improvement for the microfabrication of biochips for rapid diagnosis of severe acute respiratory syndrome coronavirus II (SARS-CoV-2).

In response to the new concept of the impact of total climate production factors on plant phenology, this study will verify the feasibility of simulating plant phenology and triggering thresholds based on total climatic production factors by using the phenological and meteorological observation data of S. krylovii plant from 1985 to 2018 at the Xilinhot National Climate Observatory of China Meteorological Administration. The results indicate that the total climate production factors influencing plant phenological changes can be well used for phenological simulation and its triggering thresholds. The mutation of cumulative climate production potential based on total climate production factors can effectively indicate the green-up date and the wilting date of S. krylovii plant, and their triggering thresholds depend on the parameters of climate resource change and plant biology, which are (0.085, –5.363) and (0.086, –27.620), respectively. The cumulative climate production potential based on total climate production factors can effectively indicate the heading date of S. krylovii plant, and its triggering thresholds also depends on the parameters of climate resource change and plant biology, which is (394.632，–38026.268). Furthermore, the results support the viewpoint that the climate abrupt changes determine the beginning and the ending of plant growth, while the accumulative climate resources determine the other phenological dates. This study provides new ideas for the study of plant phenology.

This study aimed to establish and verify the validity of an acoustic simulation method during sustained phonation of the Japanese vowels /i/ and /u/. The study participants were six healthy adults. First, vocal tract models were constructed based on computed tomography (CT) data, such as the range from the frontal sinus to the glottis, during sustained phonation of /i/ and /u/. Next, cylindrical shapes virtually extended by 12 cm were added to the vocal tract models to imitate the trachea between the tracheal bifurcation and lower part of the glottis. The Kirchhoff–Helmholtz integral equation was formulated as the wave equation for sound propagation, and the boundary element method was used for discretization. As a result, the relative discrimination thresholds of the vowel formant frequencies for /i/ and /u/ against actual voice were 1.1%–10.2% and 0.4%–9.3% for the first formant and 3.9%–7.5% and 5.0%–12.5% for second formant, respectively. In the vocal tract model with nasal coupling, a pole–zero pair was observed at around 500 Hz, and for both /i/ and /u/, a pole–zero pair was observed at around 1000 Hz regardless of the presence or absence of nasal coupling. These findings demonstrated that /i/ and /u/ could be simulated with high validity in a vocal tract model constructed from CT data obtained during sustained phonation using the boundary element method.

Air conditioners are indispensable necessities in daily life and industrial production. However, the heat generation of their internal core power components can limit their performance release. In this work, we explore the application of thermoelectric coolers (TECs) in the field of power device heat dissipation through finite element simulation. First, we geometrically modeled the structure and typical operating conditions of core power devices in air conditioners. We compared the temperature fields in air cooling and TEC active cooling modes for high power consumption power devices in a 319 K operating environment. The simulation results show that in the single air cooling mode, the maximum temperature of the 173.8 W power device reaches 394.4 K and the average temperature reaches 373.9 K, which exceeds its rated operating temperature of 368.1 K. However, after adding TEC, the maximum temperature of the power device drops to 331.8 K at an operating current of 7.5 A and the average temperature of the device is 326.5 K. It indicates that TEC active cooling has a significant effect on the temperature control of the power device. At the same time, we also studied the effect of TEC working current on the temperature control effect of power devices. For TEC, there is a minimum working current of 5 A; when it is less than 5 A, TEC has no cooling effect; the cooling effect of TEC increases with an increase in working current. When the TEC working current is 10 A, the average temperature of the power device can be reduced to 292.9 K. This study has made a meaningful exploration of the application of TEC in chip temperature control and heat dissipation, providing a new solution for chip thermal management and accurate temperature control.

A real-time flight simulation tool is proposed using a Virtual Reality Head-Mounted Display (VR-HMD) for airships operating in beyond the line-of-sight (BLOS) conditions. Particularly, the VR-HMD is developed for stratospheric airships flying at low/high altitudes. The proposed flight simulation tool uses the corresponding aerodynamics characteristics of the airship, the buoyancy effect, mass balance, added mass, propulsion contributions and ground reactions in the FlightGear Fight Simulator (FGFS). The VR headset has been connected to the FGFS along with the radio controller containing the real-time orientation/state of each button that is also simulated to provide better situational awareness and a Head-Up Display (HUD) that has been developed to provide the required flight data. In this work, a system was developed to connect the FGFS and the VR-capable graphics engine, Unity, to a PC and a wireless VR-HMD in real-time with minimal lag between data transmission. A balance was found for FGFS to write to a CSV file at a period of 0.01s. For Unity, the file was read every frame which translates to around 0.0167s (60 Hz). A test procedure was also conducted with a similar rating technique based on the NASA TLX questionnaire that identifies the pilot’s spare mental capacity when completing an assigned task to assure the comfortability of the proposed VR-HMD. Accordingly, a comparison has been made for the aircraft control using the desktop simulator and the VR-HMD tool. Results, showed that the current iteration of the system is ideal to train pilots on using similar systems in a safe and immersive environment. Furthermore, such an advanced portable system may even increase the situational awareness of pilots and allow them to complete a sizeable portion of actual flight tests with the same data transmission procedures in simulation. The resulting VR-HMD flight simulator is also conceived to express the ground control station (GCS) concept and transmit flight information as well as the point of view (POV) visuals in real-time using the real environment broadcasted using an onboard camera.

In Lubumbashi, the capital of Haut Katanga in the Democratic Republic of the Congo (DR Congo), diesel power plants are a common source of electricity. The need to utilise local renewable energy sources in DR Congo has increased due to the unreliability of the state grid and the rising cost of running Diesel generators. Solar photovoltaic (PV) panels and batteries, in particular, have recently seen significant price drops. Therefore, it is important for operators and suppliers to choose optimal generators together with a renewable energy system to lessen the energy deficit. Diesel generators are still widely used in DRC, but their efficiency pales in contrast to that of more recent power facilities. Consuming fossil fuels results in high expenses for upkeep and operation, in addition to severe environmental damage. This study assessed the feasibility of using local weather and technical data to evaluate the efficiency of a diesel power plant hybridized with a PV system. Hybrid Optimization Model for Electric Renewable (HOMER) simulations suggest that the hybrid system schedule is preferable due to its many economic and environmental advantages for the local community and its inhabitants. The promotion of such a hybrid system, then, may encourage the sustainable economic development of a stable source of electricity for the Congo Region.

Kinetic modeling is an essential tool in systems biology research, enabling the quantitative analysis of biological systems and predicting their behavior. However, the development of kinetic models is a complex and time-consuming process. In this article, we propose a novel approach called KinModGPT, which generates kinetic models directly from natural language text. KinModGPT employs GPT-3 as a natural language interpreter and Tellurium as an SBML generator. We demonstrate the effectiveness of KinModGPT in creating SBML models from complex natural language descriptions of biochemical reactions. KinModGPT successfully generates valid SBML models from a range of natural language model descriptions of metabolic pathways, protein-protein interaction networks, and heat shock response. This article demonstrates the potential of KinModGPT in kinetic modeling automation.

Solar cosmic rays (SCR) are generated during the primordial energy release in solar flares. This explosive process takes place in the solar corona above the active region. It represents fast release of the magnetic field energy of the current sheet, which is formed near a singular magnetic field line. Solar cosmic rays appear as a result of acceleration of charged particles, mainly protons, by an inductive electric field in the current sheet, equal to the field E=V´B/c near the current sheet. To study the mechanism of solar flares and obtain conditions for stydy SCR acceleration it is necessary to carry out magnetohydrodynamic (MHD) simulation of a flare situation in the solar corona above a real active region. The methods of stabilization were developed which made it possible to solve partially the problem of numerical instabilities. MHD simulations showed complicated configuration near the singular line. Comparison of the results of MHD simulations with observations showed a general agreement of the positions of the current sheets with regions of intense flare radiation. However, there are some problems with the details of such coincidences. The results show the possibility of improving the methods of MHD simulation in order to solve the arisen problems.

The second-order factor effect of burner optical ports and edge inter-matrices (EIM) and the first-order factor of pressure on the soot formation process and behavior of premixed sooting flames in a high-pressure burner are numerically investigated here. Three-dimensional computational fluid dynamics (CFD) simulations of a premixed flame C₂H₄/air at p = 1.01 and 10 bar using a one-step chemistry approach are first performed to justify the satisfied predictability of the prospective axisymmetric two-dimensional (2D) and one-dimensional (1D) simulations. The justified 2D simulation approach shows the generation of an axial vorticity around the EIM and axial multi-vorticities due to the high expansion rate of burnt gases at the high pressure of 10 bar. This leads to the development of axial multi-sooting zones, which are manifested experimentally by visible luminous soot streaks, and to the boosting of soot formation conditions of a relatively low-temperature field, < 1800 K, and a high mixing rate of gases in combustion around and above the EIM location. Nevertheless, a tolerable effect on the centerline soot volume fraction (f_V) profile, f_V < 3%, is manifested only at high heights above the burner of the atmospheric sooting flame C₂H₄/air ϕ = 2.1, and early at the high pressure of 10 bar of this flame, f_V < 10%. Enhancing the combustion process reactivity by decreasing the rich equivalence ratio of the fuel/air mixture and/or rising the pressure results in the prior formation of soot precursors, which shifts the sooting zone upstream.

Simulation-based education is a part of Intelligent Transportation Systems (ITS) education. The paper discusses the experimental success of using Virtual Reality (VR) technology in simulation-based ITS education to improve the quality of education while increasing immersion and motivation. The study documents the application of VR technology to a microscopic simulation model and the methodology to capture and evaluate student experiences. The study discusses findings and ways to improve the planned VR technology implementation in the ITS laboratory.