Longitudinal dispersion coefficient (LDC) plays an essential role in modeling the transport of pollution and sediment in the natural rivers. As a result of transportation processes, the concentration of pollution changes along the river. Different studies have been conducted to provide simple equations for estimating LDC. In this study, Support Vector Regression (SVR), Gaussian Process Regression (GPR), M5P and Random Forest (RF) examined to predict the LDC in the natural streams. The hydraulic and geometric features of different rivers gathered for developing the mentioned models for LDC estimation and various statistical criteria were utilized to scrutinize of the models. Furthermore, the Taylor chart was used to evaluate the models and achieved results showed that among machine learning models, M5P displayed the superior performance with CC of 0.823, SI of 0.812, NS of 0.577 and WI of 0.879. As well, S-D model with CC of 0.795 SI of 0.827, NS of 0.558 and WI of 0.890 had more precise results than other empirical models. The results indicates that the developed M5P model with simple formulations was superior to other machine learning models and empirical models and therefore, it can be used as a proper tool for estimating LDC in natural rivers.

Although different assessments and evaluations of Dual-Miller cycle performed, specified output power and thermal performance associated with engine determined. Besides, multi objective optimization of thermal efficiency, Ecological Coefficient of performance ( ) and Ecological function ( ) by the mean of NSGA-II technique and thermodynamic analysis performed. The Pareto optimal frontier obtaining the best optimum solution is chosen by fuzzy Bellman-Zadeh, LINMAP, and TOPSIS decision-making techniques. Based on the results, performances of dual-Miller cycles and their optimization are improved.

Future cyber-physical systems may extend over broad geographical areas, like cities or regions, thus requiring the deployment of large real-time networks. A strategy to guarantee predictable communication over such networks is to synthesize an offline time-triggered communication schedule. However, this synthesis problem is computationally hard (NP-complete), and existing approaches do not scale satisfactorily to the required network sizes. This article presents a segmented offline synthesis method which substantially reduces this limitation, being able to generate time-triggered schedules for large hybrid (wired and wireless) networks. We also present a series of algorithms and optimizations that increase the performance and compactness of the obtained schedules while solving some of the problems inherent to segmented approaches. We evaluate our approach on a set of realistic large-size multi-hop networks, significantly larger than those considered in the existing literature. The results show that our segmentation reduces the synthesis time up to two orders of magnitude.

A common reactor type in the chemical and process industry is the fixed-bed reactor. Accurate modeling can be achieved with particle-resolved Computational Fluid Dynamic (CFD) simulations. However, the underlying bed morphology plays a paramount role. Synthetic bed-generation methods are much more flexible and faster than image-based approaches. In this study, we look critically at the two different bed generation methods: Discrete Element Method (DEM) (in the commercial software STAR-CCM+) and the rigid-body model (in the open-source software Blender). The two approaches are compared in terms of synthetically generated beds with experimental data of overall and radial porosity, particle orientation, as well as radial velocities. Both models show accurate agreement for the porosity. However, only Blender shows similar particle orientation than the experimental results. The main drawback of the DEM is the long calculation time and the shape approximation with composite particles.

The combination of artificial intelligence algorithms and numerical methods has recently become popular in the prediction of macroscopic and microscopic hydrodynamics parameters of bubble column reactors. The multi inputs and outputs machine learning can cover small phase interactions or large fluid behavior in industrial domains. This numerical combination can develop the smart multiphase bubble column reactor with the ability of low-cost computational time. It can also decrease case studies for the optimization process when big data is appropriately used during learning. There are still many model parameters that need to be optimized for a very accurate artificial algorithm, including data processing and initialization, the combination of inputs and outputs, number of inputs and model tuning parameters. For this study, we aim to train four inputs big data during learning process by an adaptive neuro-fuzzy inference system or adaptive-network-based fuzzy inference system (ANFIS) method, and we consider the superficial gas velocity as one of the input variables, while for the first time, one of the computational fluid dynamics (CFD) outputs named gas velocity is used as an output of the artificial algorithm. The results show that the increasing number of input variables improves the intelligence of the ANFIS method up to , and the number of rules during learning process has a significant effect on the accuracy of this type of modeling. The results also show that propper selection of model parameters results in more accuracy in prediction of the flow characteristics in the column structure.

The energy efficiency of ice hockey arenas is a central concern for the administrations, as these buildings are well known to consume a large amount of energy. Since they are composite, complex systems, solutions to such a problem can be approached from many different areas, from managerial to technological to more strictly physical. In this paper we consider heat transfer processes in an ice hockey hall, during operating conditions, with a bottom-up approach based upon on-site measurements. Detailed heat flux, relative humidity and temperature data for the ice pad and the indoor air are used for a heat balance calculation in the steady-state regime, which quantifies the impact of each single heat source. We then solve the heat conduction equation for the ice pad in transient regime, and obtain a generic analytical formula for the temperature profile that can be used in practical applications. We then apply this formula to the resurfacing process for validation, and find good agreement with an analogous numerical solution. Since it is given with implicit initial condition and boundary conditions, it can be used not only in ice hockey halls, but in a large variety of engineering applications.

HybridAC/DC microgrids(HMG) are emerging as an attracting method for integrating the AC/DC distributed energy resources(DERs) with the features of high-performance and low-cost. In the isolated hybrid AC/DC microgrid (IHMG), the key problem is how to balance the power variation and regulate the voltage and frequency. Various energy storage systems (ESS)and interlinking converter (IC) technologies are viable for this application. The present study proposes a novel unified power flow model to evaluate and compare the abilities of the ESS with different connection topologies and ICs with different control approaches to maintain the voltage and frequency stability of the IHMG. In order to investigate the performance of the proposed scheme, five operation modes of the IHMG are defined and explained. The classification is based on the connection topologies and control modes of the ESS/IC in the IHMG. Then, a set of generic PF equations are derived. Moreover, three binary matrices are applied in the construction of the unified power equations. These matrices are used for describing the running state of the IHMG. Finally, in order to verify the proposed scheme, it is applied to several case studies of the IHMG. The operation characteristics of multi-DC subgrids IHMG in different modes, particularly when an external disturbance occurs, are investigated.

Tissue engineering has the potential for repairing large bone defects, which impose a heavy financial burden on the public health. However, difficulties with O₂ delivery to the cells residing in the interior of tissue engineering scaffolds make it challenging to grow artificial tissues of clinically-relevant sizes. This study uses image-based simulation in order to provide insight into how to better optimize the scaffold manufacturing parameters, and the culturing conditions, in order to resolve the O₂ bottleneck. To do this, high resolution 3D X-ray images of two common scaffold types (salt leached foam and non-woven fiber mesh) are fed into a Lattice Boltzmann Method fluid dynamics and reactive Lagrangian Scalar Tracking mass transfer solvers. The obtained findings indicate that the scaffolds should have maximal surface area-to-solid volume ratios, for higher chances of the molecular collisions with the cells. Furthermore, the cell culture media should be flown through the scaffold pores as fast as practically possible (without detaching or killing the cells). Finally, we have provided a parametric sweep that maps how the molecular transport within the scaffolds is affected by variations in rates of O₂ consumption by the cells. Ultimately, the results of this study are expected to benefit the computer-assisted design of tissue engineering scaffolds and culturing experiments.

In this study, an optimization of the first blade in new test rig presented. Blade tuning is conducted using 3D geometrical parameters. Sweep and dihedral play an essential role in this study. Compressor characteristics and blades vibrational behavior are the main objective of the evaluation. Here, the attachments are designed to isolate blade dynamics from Disk. So, the Vibrational behaviors of the one's blade are tuned based on the self-excited and forced vibration phenomenon. Using a semi analytical MATLAB code instability conditions are satisfied. The code takes advantages of whitehead and force response theory to predict classically and stall flutter speeds. Beside, Forced vibrations instability is controlled using a theory presented by Campbell. Aerodynamics of new blade geometry determined using multistage simulations Computational fluid dynamics (CFD) software. Numerical results show increasing performance near the surge line and working interval along with increasing mass flow.

Pipelines are widely used for transportation of hydrocarbon fluids over millions of miles over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distributions deport. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses on pipelines leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed.

In order to perceive the behavior presented by the multiphase chemical reactors, ant colony optimization algorithm was combined with CFD data. This intelligent algorithm creates a probabilistic technique for computing flow and it can predict various levels of three-dimensional bubble column reactor. This artificial ant algorithms is mimicking the real ant behavior. We found that this method can anticipate the flow characteristics in the reactor using almost 30 % of whole data in the domain. Following discovering the suitable parameters, the method is used for predicting the points not being simulated with CFD, which represent mesh refinement of Ant colony method. In addition, it is possible to anticipate the bubble-column reactors in the absence of numerical results or training of exact values of evaluated data. The major benefits include reduced computational costs and time savings.

Recently, generative adversarial networks (GANs) can be used to generate the photo-realistic image from a low-dimension random noise. It is very dangerous that the synthesized or generated image is used on inappropriate contents in social media network. In order to successfully detect such fake image, an effective and efficient image forgery detector is desired. However, conventional image forgery detectors are failed to recognize the synthesized or generated images by using GAN-based generator since they are all generated but manipulation from the source. Therefore, we propose a deep learning-based approach to detect the fake image by combining the contrastive loss. First, several state-of-the-art GANs will be collected to generate the fake-real image pairs. Then, the contrastive will be used on the proposed common fake feature network (CFFN)to learn the discriminative feature between the fake image and real image (i.e., paired information). Finally, a smaller network will be concatenated to the CFFN to determine whether the feature of the input image is fake or real. Experimental results demonstrated that the proposed method significantly outperforms other state-of-the-art fake image detectors.

Poly(hydroxyalkanoates) (PHAs) are currently considered competent candidates to replace traditional plastics in several market sectors. However, commercial PHA grades exhibit unsatisfactory smell that can negatively affect the quality of the final product. The cause of this typical rancid odour is attributed to oxidized cell membrane glycolipids, coming from Gram negative production strains, which remain frequently attached to PHAs granules after extraction. The aim of this research is the development of customised PHA nano-biocomposites for industrial applications containing organo-modified nanoclays with high adsorption properties able to capture volatile compounds responsible of the displeasing fragrance in PHAs. To this end, a methodology for the detection and identification of the key volatiles released due to oxidative degradation of PHAs has been established using a headspace solid-phase microextraction technique. We report the development of nine nano-biocomposite materials based on three types of commercial PHA matrices loaded with three species of nanoclays which represent a different polar behaviour. It has been demonstrated that although the reached outcome effect depends on the volatile nature, natural sepiolite (T2) might result in the most versatile candidate for all PHA matrices selected.

This paper concerns the effect of proppant embedment related with hydraulic fracturing treatment. This phenomenon occurs if the strength of the reservoir rock is lower than proppant grains. The aim of the research is laboratory determining the loss of width of the proppant pack built of light ceramic grains. The laboratory simulation of the embedment phenomenon was carried out for a shale rock on a hydraulic press, in a specially prepared for this purpose a heated embedment chamber. Tests were conducted at high temperature and axial compressive stress conditions. The surfaces of the cylindrical core plugs (fracture faces) were imaged under an optical microscope equipped with 3D software. The fracture faces were examined and compared before and after the embedment phenomenon. The analysis of the obtained images of the fracture face were made based on the research method of the embedment phenomenon developed at Oil and Gas Institute-NRI. On the basis of laboratory tests, the parameters characterizing the embedment phenomenon were collected and discussed. In addition, the percentage reduction in the width of the proppant pack was determined.

Immersion in salt-lake solution was adopted to periodically test the concrete chloride-ion diffusion coefficient. The regression analysis was also completed. Also investigated was the time-dependent law of concrete chloride-ion diffusion coefficient with time. The influence of chloride-ion concentration in solution, water-to-cement ratio, and corrosion time on the largeness and accumulation rate of the concrete chloride-ion diffusion coefficient was also analyzed. Test results show that the concrete chloride-ion diffusion coefficient gradually decreased with increasing time and increased with increasing chloride-ion concentration in a salt lake . Taking into account the influence of factors such as water–binder ratio, chloride-ion concentration, and time-varying characteristics, a multi-factor calculation model for the concrete chloride-ion diffusion coefficient was established. Combining the prediction results and the measured data reported in this paper, the effectiveness and applicability of the established concrete chloride-ion diffusion coefficient calculation model were compared and verified, and the durability design and service life of a concrete structure under cool chlorine were compared. The results of analysis provide important boundary conditions.

Aluminum profile surface defects can greatly affect the performance, safety and reliability of products. Traditional human-based visual inspection is low accuracy and time consuming, and machine vision-based methods depend on hand-crafted features which need to be carefully designed and lack robustness. To recognize the multiple types of defects with various size on aluminum profiles, a multiscale defect detection network based on deep learning is proposed. Then, the network is trained and evaluated using aluminum profile surface defects images. Results show 84.6%, 48.5%, 96.9%, 97.9%, 96.9%, 42.5%, 47.2%, 100%, 100%, 43.3% average precision(AP) for the ten defect categories, respectively, with a mean AP of 75.8%, which illustrate the effectiveness of the network in aluminum profile surface defects detection. In addition, saliency maps also show the feasibility of the proposed network.

Buildings have started to play a critical role in the stability and resilience of modern smart grids, leading to a refocusing of large scale energy management strategies from the supply side to the consumer side. When the buildings integrate local renewable energy generation in the form of renewable energy resources they become prosumers and this reflects into additional complexity into the operation of the interconnected complex energy systems. A class of methods of modelling the energy consumption patterns of the building have recently emerged as black-box input-output approaches with the ability to capture underlying consumption trends. These make use and require large quantities of quality data produces by non-deterministic processes underlying the energy consumption. We present an application of a class of neural networks, namely deep learning techniques for time series sequence modelling with the goal of accurate and reliable building energy load forecasting. The Recurrent Neural Network implementation uses Long Short-Term Memory layers in increasing density of nodes to quantify prediction accuracy. The case study is illustrated on four university buildings from temperate climates over one year of operation using a reference benchmarking dataset that allows replicable results. The obtained results are discussed in terms of accuracy metrics and computational and network architecture aspects and are considered suitable for further used in future in situ energy management at the building and neighbourhood levels.

Impact of Nitrogen Foamed Stimulation Fluids Stabilized by Nanoadditives on Reservoir Rocks of Hydrocarbon Deposits

Hydraulic fracturing is the most effective method of stimulation for hydrocarbon reservoirs. However the use of water-based fracturing fluids, can be a problem in water-sensitive formations due to the permeability damage hazard caused by clay minerals swelling. For this reason, the foamed fracturing fluids with addition of natural, fast hydrating guar gum were examined. The rheology and filtration coefficients of foamed fracturing fluids were examined and compared to the properties of conventional water-based fracturing fluid. Laboratory results provided the input for numerical simulation of the fractures geometry for water-based fracturing fluids and 50% N₂ foamed fluids. The results show, that the foamed fluids were able to create shorter and thinner fractures compared to the fractures induced by the non-foamed fluid. The simulation proved that the concentration of proppant in the fracture and its conductivity are similar or slightly higher when using the foamed fluid. Moreover such fluids are able to significantly reduce the amount of water necessary for fracturing treatments, limiting clay minerals swelling, and reducing the reservoir permeability damage. The foamed fluids, when injected to the reservoir, provide additional energy, that allow for more effective flowback, and maintain the proper fracture geometry and proppant placing. The results of laboratory work in combination with the 3D simulation showed, that the foamed fluids have suitable viscosity which allows opening the fracture, and transport the proppant into the fracture, providing successful fracturing operation.

A sufficient condition for the almost global sta-bility of nonlinear switched systems under average dwell timerestriction is obtained. This condition is derived leaning uponthe existence of multiple Lyapunov densities, which are associ-ated to subsystems and satisfy some compatibility conditions.An upper bound for the average dwell time that ensures almostglobal stability is obtained.

In the Netherlands, the assessment of existing prestressed concrete slab-between-girder bridges showed that the thin, transversely prestressed slabs may be critical for static and fatigue punching when evaluated using the recently introduced Eurocodes. On the other hand, compressive membrane action increases the capacity of these slabs and changes the failure mode from bending to punching shear. To improve the assessment of the existing prestressed slab-between-girder bridges in the Netherlands, two 1:2 scale models of an existing bridge, the Van Brienenoord Bridge, were built in the laboratory and tested monotonically as well as under cycles of loading. The result of these experiments is: 1) the static strength of the decks, showing that compressive membrane action significantly enhances the punching capacity, and 2) the Wöhler curve of the decks, showing that compressive membrane action remains under fatigue loading. The experimental results can then be used for the assessment of the most critical existing slab-between-girder bridge. The outcome is that the bridge has sufficient punching capacity for static and fatigue loads, and thus that the existing slab-between-girder bridges in the Netherlands fulfil the code requirements for static and fatigue punching.

The energy transition towards renewable and more decentral power production triggers the need for grid and storage expansion on all voltage levels. Today's power system planning focuses on certain voltage levels or spatial resolutions. In this work we present an open source software tool eGo which is able to optimize grid and storage expansion throughout all voltage levels in a developed top-down approach. System costs are minimized by applying a linear optimal power flow considering the grid infrastructure of the extra-high and high-voltage (380 to 110 kV) level. Hence, the common differentiation of transmission and distribution grid is partly dissolved, integrating the high-voltage level into the optimization problem. Consecutively, optimized curtailment and storage units are allocated in the medium voltage grid in order to lower medium and low voltage grid expansion needs, that are consequently determined. Here, heuristic optimization methods using the non-linear power flow were developed. Applying the tool on future scenarios we derived cost-efficient grid and storage expansion for all voltage levels in Germany. Due to the integrated approach storage expansion and curtailment can significantly lower grid expansion costs in medium and low voltage grids and at the same time serve the optimal functioning of the overall system. Nevertheless, the cost-reducing effect for the whole of Germany was marginal. Instead, the consideration of realistic, spatially differentiated time series lead to substantial overall savings.

Building a new power plant to address the growing demand for power due to population concentration in the metropolitan area is one of the world's major concerns. However, since a large power plant can not be located around the city due to burden of economic cost, building power plant outside metropolitan and cities is necessary. Therefore, new power generation facilities are promoting policies to provide distributed generator(DG) with a small capacity relatively near the metropolitan. When the DG (photovoltaic, wind farm, etc.) is connected with the grid using medium voltage direct current (MVDC) system, voltage sourced converter(VSC) should supply reactive power to the grid, because of fault ride through(FRT) operation in grid fault. If the voltage drop is severe, the converter should be disconnected from the grid immediately without supplying the reactive power, resulting in a considerable economic loss. In general, superconducting fault current limiter(SFCL) is introduced as a measure to enhance FRT capability. In this paper, we use trigger type SFCL which protects superconducting element and reduces low voltage. On the other hand, the active power unbalance of the DC-link and the DC voltage rise due to the reactive power supply of the grid-side converter. The rise of the DC voltage causes the P (active power), Q (reactive power) control of the converter to deviate, causing malfunction and damage of the DC equipment. Therefore, the rise of the DC voltage must be prevented. In this paper, we consider the suppression the DC voltage rising caused by the FRT operation through the active power tracking control (APTC).

The development of hydrogen plasma smelting reduction as a CO₂ emission-free steel-making process is a promising approach. This study presents a concept of the reduction of hematite using hydrogen thermal plasma. A laboratory scale and pilot scale hydrogen plasma smelting reduction (HPSR) process are introduced. To assess the reduction behavior of hematite, a series of experiments has been conducted and the main parameters of the reduction behavior, namely the degree of hydrogen utilization, degree of reduction and the reduction rate are discussed. The thermodynamic aspect of the hematite reduction is considered and the pertinent calculations have been carried out using FactSage^TM 7.2. The degree of hydrogen utilization and the degree of reduction were calculated using the off-gas chemical composition. The contribution of carbon, introduced from the graphite electrode, ignition pin and steel crucible, to the reduction reactions was studied. The degree of reduction of hematite, regarding H₂O, CO and CO₂ as the gaseous reduction products, is determined. It is shown that the degree of hydrogen utilization and the reduction rate were high at the beginning of the experiments, then decreased during the reduction process owing to the diminishing of iron oxide. Conducting experiments with the high basicity of slag B₂=2 led to a decrease of the phosphorus concentration in the produced iron.

The role of the submission was to find out what changes people think they need to make in their home because of getting older. At advanced age, the likelihood of different limitations such as vision impairment, hearing impairment or physical inability is increased. Currently, tenants are often forced to leave their long-term living space, as these spaces cannot serve “new” individual needs. This transition from the privacy of their home to the new environment often appears to be a painful change. They will not have a well-known environment because their homes cannot be adapted to their new needs. The aim is a comprehensive approach to the design of such an exterior and interior space which could serve people at all stages of their life, including the terms of mobility. This means that even if there is an unexpected situation and changes in movement abilities and physiological limitations of man, not only by natural aging, but according to accidents or disabilities we can adapt the living space to the given conditions. The survey results are presented in Germany and Slovakia. In the survey, respondents expressed their opinion on what they considered important in creating an adaptive environment considering various life changes. Results are processed graphically with explanation. The results could be of an interest to architects and designers of the environment. Based on the results of the questionnaire survey, studies of possible modifications of flats and houses were developed. The contribution brought these results to three age groups of respondents; people aged 35, 50 and over 50.

The current study focused on reviewing the rapid growing of using magnetic water in different fields of science and measure the influence of several intensities of magnetization on the chemical and electrical properties of tap water treated by reverse osmosis. The work includes circulation of water for 24 h. in magnetic fields of intensity 500, 1000, 1500, and 2000 G. The magnetization of water causes increasing some positive and negative ions in water such as (Mg, K, Na, Cl¯, Alkaline and SiO₂) and decreasing some positive and negative ions (Ca and SO₃). In the near future, the application of concepts of sustainability development in civil engineering have the to produce structures in harmony with these concepts through using of high-performance materials with less impacts on the environmental and have low cost. The main application of using magnetic water is improvement the geotechnical properties of soil through precipitation of calcite which increases the bond between soil particles and then strength of soil.

This paper reports design of a 2 × 4 hybrid multimode interferometer-Mach-zehnder interferometer (MMI-MZI) configuration and compact thermo-optical switch consisting of slab waveguides on the silicon-on-insulator (SOI), platform. The device consisted of two identical MMIs as power splitters and couplers that are connected with two identical MMI-based phase shifters, and linear tapers at both ends of the MMIs to minimize the power coupling loss. A thin Al pad is used as a heating element, and a trench is created around this pad to prevent heat from spreading and to minimize loss. The calculated average thermo-optical switching power consumption, excess loss, and power imbalance are 1.4 mW, 0.9 dB, and 0.1 dB, respectively. The overall footprint of the device is 6 × 304 μm². The new heating method has advantages of compact size, ease of fabrication on SOI platform with the current CMOS technology, and offers low excess loss and power consumption as demanded by devices based on SOI technology. The device can act as two independent optical switches in one structure.

Common buckwheat (Fagopyrum esculentum Moench) is an annual spring-emerging crop that is classified among dicotyledons, yet due to the manner of its cultivation, use, and chemical composition of seeds. The use of buckwheat straw for energy purposes, for example, for the production of second generation bioethanol might enable its wider application and increase the cost-effectiveness of tillage. In this study, we examined the usability of buckwheat straw for the production of bioethanol. We pretreated the raw material with using ionic liquids and subsequently performed enzymatic hydrolysis and alcoholic fermentation. The obtained chemometric data was analyzed using the Partial Least Squares (PLS) regression model. PLS regression in combination with the spectral analysis within near-infrared (NIR) spectrum allowed for the rapid determination of amount of cellulose in the raw material and also provided information on the changes taking place in its structure. According to our results, we obtained good results for the combination of 1-ethyl-3-methylimidazolium acetate as the ionic liquid and Cellic CTec2 and the enzymatic preparation for the pretreatment of buckwheat straw. The highest concentration of glucose following 72 hours of enzymatic hydrolysis was found to be around 5.5 g/dm3. The highest concentration of ethanol (3.31 g/dm3) was obtained with the combination of 1-butyl-3-methylimidazolium acetate for the pretreatment and the cellulase from Trichoderma reesei for enzymatic hydrolysis. In summary, the efficiency of the fermentation process is strictly associated with the pool of available fermenting sugars, and it depends on the type of ionic liquid used during the pretreatment and on the enzymatic preparation. It is possible to obtain bioethanol from buckwheat straw using ionic liquid for the pretreatment of the raw material prior to the enzymatic hydrolysis and alcoholic fermentation of the material.

Stainless steel grade AISI 304 is one of the most widespread modern structural material, alas its sliding wear and cavitation wear resistance are limited. Thus, AlTiN and TiAlN coatings can be deposited for increasing the resistance to wear of stainless steel components. The aim of the work was to investigate the cavitation erosion and sliding wear mechanisms of magnetron sputtered AlTiN and TiAlN coatings deposited on SS304 stainless steel. Films surface morphology and structure were examined using a profilometer, light optical microscope (LOM) and scanning electron microscope (SEM). The mechanical properties (hardness, elastic modulus) were tested by nanoindentation tester. The adhesion of deposited coatings was determined by means of the scratch test and Rockwell test. Cavitation erosion tests were performed according to ASTM G32 (vibratory apparatus) with stationary specimen procedure. Sliding wear tests were conducted using a nano-tribo testes i.e. ball-on-disc apparatus. Wear mechanisms are strongly contingent upon the structure and morphology of the tested materials. In relation to stainless steel substrate, the PVD films present a superior resistance to sliding wear and cavitation erosion. Higher resistance was noticed for AlTiN than for TiAlN film, mainly due to its superior hardness and elastic modulus. Cavitation erosion mechanism of both, AlTiN and AlTiN coatings is prone to embrittlement, imputable to fatigue processes that result in coating rupture and spallation that consist in coating fragmentation, formation of pits and finally detachment from the substrate. Additionally, films nanoindentation results measured before and after cavitation testing indicate changes in coatings structure, that acknowledged wear mechanism that starts with coating internal delamination in flake spallation mode. In contrary to PVD coatings, steel substrate is characterized by developed cavitation erosion wear with roughened surface and plastically deformed, semi-brittle, eroded surface. Sliding wear of thin films is based on micro-ploughing mechanism. For stainless steel adhesive sliding wear mode and plastic deformation with smearing, material transfer and grooving were observed. It was confirmed that various fluid machinery components made from austenitic stainless steel that undergo cavitation erosion, can be prevented by deposition of AlTiN and TiAlN films.

Wave overtopping, i.e., excess of water over the crest of a coastal protection infrastructure due to wave run-up, of a smooth slope can be reduced by introducing slope roughness. A stepped revetment ideally constitutes a slope with uniform roughness. Apart from reducing overtopping, a stepped revetment provides safer access to a beach compared to conventional rubble. In recent years, research studies on stepped revetments have provided valuable findings regarding the performance and design optimization of stepped revetments as a typical mean of coastal protection. A stepped revetment can reduce overtopping volumes of breaking waves up to compared to a smooth slope. The effectiveness of the overtopping reduction decreases with increasing Iribarren number. However, up to date a unique approach applicable for a wide range of boundary conditions is still missing. The present paper critically reviews previous findings, gathers and analyzes data from previous studies and proposes a new formula for robust prediction of overtopping of stepped revetments. By means of this approach a critical assessment based on beforehand disclosed parameter ranges between a smooth slope on the one hand and a plain vertical wall on the other are contrasted. By analysis of a new data set compounded from different original studies a novel empirical formulation is derived to predict the roughness reduction coefficient of a stepped revetment for breaking and non-breaking waves. This coefficient is developed and adjusted for a direct incorporation into the present design guidelines. Underlying uncertainties are clearly addressed and quantified. Scale effects are highlighted.

Knowledge about laminar-turbulent transition on operating multi-megawatt wind turbine blades needs sophisticated equipment like hot-films or microphone arrays. Contrarily thermographic pictures can easily be taken from the ground and temperature differences indicate different states of the boundary layer. The accuracy however, still is an open question, so that an aerodynamic glove known from experimental research on aero-planes was used to classify the boundary-layer state of a 2 megawatt wind turbine blade operating in the orthern part of Schleswig-Holstein, Germany. State-of-the-art equipment for measurering static surface pressure was used for monitoring the lift distribution. To distinguish laminar and turbulent parts of the boundary layer (suction side only) 48 microphones were applied together with ground-based thermographic cameras from two teams. Additionally, an optical camera mounted on the hub was used to survey vibrations. During start-up (from 0 to 9 rpm) extended, but irregularly shaped regions of a laminar boundary layer were observed which had the same extension measured both with microphones and Thermography. When an approximately constant rotor rotation (9 rpm corresponding to approximately 6 m/s wind-speed) was achieved, a flow transition was visible at the expected position of 40 % chord length on the rotor blade, which was fouled with dense turbulent wedges and an almost complete turbulent state on the glove was detected. In all observations, quantitative determination of the flow transition positions from thermography and microphones agree well within their accuracy.

The hybrid system is analyzed and optimized to produce electric energy in Non-Interconnected Zones in the Colombian Caribbean region, contributing both to the improvement in the reduction of greenhouse gas emissions and to the rational use of energy. A comparative analysis of the performance of these systems was carried using a dynamic model in real wind and solar data. The model is integrated by a Southwest Wind Power Inc. wind turbine. AIR 403, a proton exchange fuel cell (PEM), an electrolyze, a solar panel and a charge regulator based on PID controllers to manipulate oxygen and hydrogen flows in the cell. The transient responses of the cell voltage, current, and power were obtained for the demand of 200 W for changes in solar radiation and wind speed for all days of the year 2013 in the Ernesto Cortissoz airport, Puerto Bolívar, Alfonso Lopez airport and Simon Bolívar airport, by regulating the flow of hydrogen and oxygen into the fuel cell. The maximum contribution of power generation from the fuel cell was presented for the Simon Bolívar airport in November with a value of 158,358W (9.45%). A multi-objective design optimization under a Pareto front is presented for each place studied to minimize the Levelized Cost of Energy and CO₂ emission, where the objective variables are the number of panel and stack in the PV system and PEM.

A novel configuration for a super-wide impedance planar antenna is presented based on a 2 × 2 microstrip patch antenna (MPA). The antenna comprises a symmetrical arrangement of four-square patches that are interconnected to each other with cross-shaped high impedance microstrip lines. The antenna array is exciting through a single feedline connected to one of the patches. The proposed antenna array configuration overcomes the main drawback of conventional MPA of narrow bandwidth that is typically <5%. The antenna exhibits a super-wide frequency bandwidth from 20 GHz to 120 GHz for S₁₁<−15 dB, which corresponds to a fractional bandwidth of 142.85%. The antenna’s performance of bandwidth, impedance match, and radiation gain were enhanced by etching slots on the patches. The slotted microstrip patch essentially acts like a left-handed capacitance to exhibit metamaterial properties over a given frequency range. With the inclusion of the slot the maximum radiation gain and efficiency of the MPA have increased to 15.11 dBi and 85.79% at 80 GHz, which show an improvement of 2.58 dBi and 12.54%, respectively. The dimension of each patch antenna is 30 × 30 mm². The results show that the proposed MPA is useful for various communications existing and emerging systems such as ultra-wideband (UWB) communications, RFID systems, massive multiple-output multiple-input (MIMO) for 5G, and radar systems.

For the effective utilization of rice husk, organosolv fractionation was investigated to separate three main components (glucan, xylose, and lignin) with low acid concentration. Reaction temperatures of 170–190 °C, ethanol concentrations of 50–70% (v/v), and sulfuric acid concentrations of 0–0.7% (w/v) were investigated, with the reaction time and liquid-to-solid ratio kept constant at 60 min and 10, respectively. The fractionation conditions for the efficient separation into the three components of rice husk were determined to be 180 °C, 60% (v/v) of ethanol, and 0.25% (w/v) of sulfuric acid. Under these fractionation conditions, 86.8% of the xylan and 77.5% of the lignin were removed from the rice husk, and xylose and lignin were obtained from the liquid in 67.6% and 49.8% yields, respectively. The glucan digestibility of the fractionated rice husk was 85.2% with an enzyme loading of 15 FPU (filter paper unit) of cellulase per g-glucan.

Gray cast iron is one of the most important engineering materials that has many applications in various industries including automotive and machinery manufacturing due to its mechanical properties, wear resistance, machining potentials and low price. In this research effect of adding aluminum and silicon to composition of gray cast iron on microstructure and wear resistance was studied. Moreover, it was investigated the role of formation of Fe-Al-Si intermetallic compound in final properties of the alloy. For studying wear resistance of samples pin-on-disc method was carried out. The results showed that addition of aluminum to gray cast iron causes formation of ferrite matrix, which leads to a decrease in hardness value. Increasing silicon content up to 2 wt. % in cast iron with 4 wt. % aluminum intensifies the formation of ferrite matrix, while further increase to 3 wt. % causes emerging a Fe-Al-Si intermetallic phase. Improvement in hardness value was achieved by increasing silicon content from 3 wt. % to 4 wt. % due to the increased percentage of intermetallic phase. Effect of intermetallic phase on decreasing wear rate was showed by studying microstructure and hardness values, however the lowest wear resistance was observed in aluminum bearing cast iron containing 2 wt. % silicon.

The calculation of power flow in power systems with the presence of harmonics has been properly studied in the scientific literature. However, power flow calculation considering interharmonic components is still an open question. Traditional methods based on the IEEE1459 standard have proven to be valid and accurate only for linear and sinusoidal systems, but have been criticized for non-linear and non-sinusoidal systems because they are not able to explain correctly the current and voltage interactions beyond the active power. This paper proposes the use of a novel mathematical framework called geometric algebra (GA) to study the power flow considering the interaction of current and voltage harmonics and interharmonics. The use of GA enables the precise determination of the direction and magnitude of the total and single active power flow for each component, as well as other power elements related to the non-active power due to cross interaction. Moreover, this paper makes a novel contribution to the definition of interharmonics in geometric algebra space that has not been done before. To test the validity of the method, both linear and non-linear circuits are proposed and solved by applying voltages and currents with harmonic and interharmonic components. The results obtained show that power flow can be analyzed under the prism of the principle of energy conservation (PoCoE) in a way that allows a better understanding of the power spectrum due to the interaction of harmonics and interharmonics of voltage and current.

Intended for the high voltage gain and wide-range operation of DC/DC converters for photovoltaic energy storage systems, a topology for four-phase interleaved DC/DC converters for photovoltaic power generation is proposed. This topology increases output voltage for output in series, and reduces the input current ripple by paralleling the input. Compared with traditional boost converter topology, the proposed topology reduces the output current and output voltage ripple, reduces the stress of the switching device, and reduces the withstanding voltage of the output capacitor under the premise of ensuring the boost ratio. Experimental results show that the maximum efficiency of the converter reaches 95.37%. Compared with traditional boost converters, the proposed converter offers obvious advantages in efficiency under the conditions that the output voltage and load are variable.

This paper sets out three visions for the year 2035 which bring about a radical change in the level of walking, cycling and public transport in Turkish urban areas. A participatory visioning technique was structured according to a three-stage technique: (i) Extensive online comprehensive survey. In which potential transport measures were researched for their relevance to promoting sustainable transport in future Turkish urban areas; (ii) Semi-structured interviews. Where transport strategy suggestions were developed in the context of the possible imaginary urban areas and their associated contextual description of the imaginary urban areas for each vision; (iii) Participatory workshops. Where an innovative method was developed to explore various creative future choices and alternatives. Overall, this paper indicates that the content of the visions was reasonable, but such visions need a considerable degree of consensus and radical approaches to tackling them.

A ducted photovoltaic façade (DPV) unit Studied using experimental Prototype and simulated in a full scale Computational Fluid Dynamics CFD Model. The Study comes in two parts; This is Part I with the title detailed above and Part II titled ‘A Ducted Photovoltaic Façade Unit with Buoyancy Cooling: Part II CFD Simulation’.. The process adopted in the experimental study is replicated in the simulation Part. The aim was to optimize the duct width behind the solar cells to allow for maximum buoyancy-driven cooling for the cells during operation. Duct widths from 5 to 50 cm were tested in a Proto-type. A duct width of 45 cm had the maximum calculated heat removed from the duct; however, the lowest cell-operating temperature was reported for duct width of 50 cm. It was found that the DT between ducts' inlets and outlets range from 5.47 °C to 12.32 °C for duct widths of 5–50 cm, respectively. The ducted system enhanced module efficiency by 12.69% by reducing PV temperature by 27 °C from 100°C to 73 °C. The maximum calculated heat recovered from the ducted PV system is 422 W. This is 47.98% from the incident radiation in the test. Total summation of heat recovered and power enhanced by the ducted system is 61.67%.

The recent growing attention to energy saving and environmental protection issues has brought to attention the possibility of exploiting syngas from gasification of biomass and coal for the firing of industrial plants included the so called Integrated Gasification Combined Cycle ones. In order to improve the knowledge about the employ of syngas in lean premixed turbulent flames, a large scale swirl stabilized gas-turbine burner has been operated with a simplified model of H₂ enriched syngas from coal gasification. The experimental campaign has been performed at atmospheric pressure with operating conditions derived from scaling the real gas turbines ones. The results are here reported and consist of OH-PLIF measurements carried out at decreasing air equivalence ratio conditions and are analysed together with the mean aerodynamic characterisation of the burner flowfield in isothermal condition. The OH concentration distributions have been analysed statistically in order to obtain information about the location of the most reactive zones and an algorithm has been applied to the data in order to identify the flame fronts. In addition, the flame front locations have been successively interpreted statistically in order to obtain information about their main features and about their dependence on the air to fuel ratio behaviour.

This work focuses on forced combustion with regards to the relationship between vent mixer models and several injection locations in unheated supersonic flow. A plasma jet torch was used to ignite the hydrogen–air mixture in a laboratory-scaled combustor duct. The flow field of the combustion was visualized with pressure and gas-sampling measurements. The vent mixers indicate good dispersion characteristics of the mixture for both parallel and normal 1 injections. However, forced combustion is dominantly governed by the injection rate toward the plasma jet (hot source) because the combustible region is restricted under the cold main flow. For this reason, the parallel injection, which provides the hydrogen–air mixture directly toward the plasma jet, shows good combustion performance. The normal 1 injection interacted with the vent mixers and shows slightly good combustion performance. Lastly, the normal 2 injection is little affected by the vent mixers and has poor combustion performance.

We write the mutual information between an input speech utterance and its reconstruction by a Code-Excited Linear Prediction (CELP) codec in terms of the mutual information between the input speech and the contributions due to the short term predictor, the adaptive codebook, and the fixed codebook. We then show that a recently introduced quantity, the log ratio of entropy powers, can be used to estimate these mutual informations in terms of bits/sample. A key result is that for many common distributions and for Gaussian autoregressive processes, the entropy powers in the ratio can be replaced by the corresponding minimum mean squared errors. We provide examples of estimating CELP codec performance using the new results and compare to the performance of the AMR codec and other CELP codecs. Similar to rate distortion theory, this method only needs the input source model and the appropriate distortion measure.

The present paper deals with the stochastic modeling of bio-colonization for the computation of stochastic hydrodynamic loading on jacket-type offshore structures. It relies on a multidisciplinary study gathering biological and physical research fields that accounts of uncertainties at all the levels. Indeed, bio-colonization of offshore structures is a complex phenomenon with two major but distinct domains (i) marine biology whose processes are modeled with biomathematics methods and (ii) hydrodynamic processes. This paper aims to connect these two domains. It proposes a stochastic model for the marine organism’s growth and then continues with transfers for assessment of drag coefficient and forces probability density functions that accounts for marine growth evolution. A case study relies on the characteristics (growth and shape) of the blue mussel (Mytilus edulis) in northeastern Atlantic.

There is an increasing trend that Unmanned Combat Air Vehicles (UCAVs) are employed to complete different combat missions in modern wars. This paper investigates a UCAV routing problem, which simultaneously considers the decisions for the configuration of weapons carried by the UCAV subject to its capacity and the allocation of weapons to the targets subject to their destroying requirements. An integer linear programming model is developed to formulate the problem. An adaptive large neighborhood search (ALNS) heuristic is proposed to solve the problem, in which seven neighborhood structures are designed and employed. Randomly generated instances covering the small, medium and large sizes are used to test the proposed ALNS algorithm. CPLEX is also utilized to solve the small-size instances, whose results are compared with that obtained by the ALNS algorithm. And the extensive experimental results confirm the effectiveness and superiority of the proposed ALNS algorithm.

It's challenging to achieve robust lane detection depending on single frame when considering complicated scenarios. In order to detect more credible lane markings by using sequential frames, a novel approach to fusing vision and Inertial Measurement Unit (IMU) is proposed in this paper. The hough space is employed as the space where lane markings are stored and it's calculated by three steps. Firstly, a basic hough space is extracted by Hough Transform and primary line segments are extracted from it. In order to measure the possibility about line segments belong to lane markings, a CNNs based classifier is introduced to transform the basic hough space into a probabilistic space by using the networks outputs. However, this probabilistic hough space based on single frame is easily disturbed. In the third step, a filtering process is employed to smooth the probabilistic hough space by using sequential information. Pose information provided by IMU is applied to align hough spaces extracted at different times to each other. The final hough space is used to eliminate line segments with low possibility and output those with high confidence as the result. Experiments demonstrate that the proposed approach has achieved a good performance.

This paper presents a device for measuring and maintaining the constant water level in a tank. The device uses a capacity sensor to measure the water level. The sensor has a DC voltage output proportional to the water level in the tank. This voltage can be used in other automation too. The water level, in percentages, is displayed on a vu meter with 8 LEDs. The circuit for maintaining the constant level consists in a comparator with hysteresis. The level of the water is adjustable, using a reference voltage from a potentiometer (marked in percentages). The level of the water is compared with the prescribed level and the difference between them commands the start/stop of the water pump which supplies the tank through a relay. The device is powered by 220 V and is isolated from the environment.

In this paper, the physical station of space network was extended in time dimension by combining the train diagram information and station technical operation standard time. At the same time, the topology of railway space-time network which considered the secondary operation process of train was constructed and an improved A* algorithm based on car flow routing was proposed to generate feasible path sets. On this basis, a dynamic car flow organization optimization model was built to simulate the railway car flow organization process under abnormal conditions, and the results of solving the model could be used to obtain the real-time quantity of cars at each station.This paper can identify the dynamic bottleneck by comparing the real-time quantity of cars with the maximum quantity of cars at the station. Finally, the feasibility of this method was analyzed and verified by a case.

Prolonged high-intensity grinding can modify the crystal structure of solid substances and/or induce chemical reaction, which is referred to as mechanochemical reaction. Such reactions can exert positive influences on hydrometallurgical processes, therefore, many researchers have applied mechanochemical reactions for metals dissolution from minerals. The mechanism of mechanochemical reaction has been investigated using solid analyses and simulations. Structural changes caused by mechanochemical reaction are not yet sufficiently clarified because the ground samples are amorphous. The objective of this study was to analyze structural changes of cerianite in weathered residual rare earth ore by mechanochemical reduction. Structural change was analyzed by x-ray absorption near-edge structure and extended x-ray absorption fine structure analysis at the cerium L_III- and K-edges. These analyses revealed that the structural change of cerianite in this ore induced by mechanochemical reduction involved oxygen vacancy production. The process of the oxygen vacancy formation was closely coupled with the quantum effect of localization–delocalization of the 4f electron of cerium.

Spent nuclear fuel and high-level radioactive waste can be disposed in deep horizontal drillholes in sedimentary, metamorphic, or igneous rocks. Horizontal drillhole disposal has safety, operational, and economic benefits: The repository is deep in the brine-saturated zone far below aquifers in a reducing environment of formations that can be shown to have been isolated from the surface for millions of years; its depth provides safety against inadvertent intrusion, earth¬quakes, and near-surface perturbations; it can be placed close to the reactors and interim storage facilities, minimizing transportation; disposal costs per ton of waste can be kept substantially lower than for mined repositories by its smaller size, reduced infrastructure needs, and staged imple¬mentation; and, if desired, the waste could be retrieved using “fishing” technology. In the proposed disposal concept, corrosion-resistant canisters containing unmodified fuel assemblies from commercial reactors would be placed end-to-end in up to 50 cm diameter horizontal drill¬holes, a configuration that reduces mechanical stresses and keeps the temperatures below the boiling point of the brine. Other high-level wastes, such as capsules containing 137Cs and 90Sr, can be disposed in small-diameter drillholes. We provide an overview of this novel disposal concept and its technology, discuss some of its safety aspects, and compare it to mined repositories and the deep vertical borehole disposal concept.

This paper outlines a new methodology for developing strategy for supply chain integration of Autonomous Electrical Vehicles (AEV) to the Internet of Things (IoT). The methodology consists of external architecture and internal design that anticipates the business strategy in the development process. The methodology is designed to anticipate the impact of developments in new road transport technologies, such as Tesla Truck or Tesla Pickup. Since the methodology is designed to anticipate the impact of non-existing technologies, it represents green-field analysis. Green-field is defined as a new and non-existent operation. Green-field strategy architecture in this paper is presented as a process of accepting the world and acting upon that version of the world. The results of the analysis are presented as pathways and outcomes, emerging from the interrelated relationship between AEV and IoT. The emerging methodology is applied through two case studies to evaluate the impact to environment, performance and operationalisation. The methodology proposes architecture and design for integrating AEV and IoT in the supply chain strategy, and a set of new evaluation criteria that promote acceptance of Artificial Intelligence (AI) in the design process. The main contribution to knowledge is a new methodology for integrating AEV and the IoT to the supply chains. The paper applies interplay between inductive and deductive case study and grounded theory approach to build upon the concept of supply chain architecture and contribute to knowledge to the topic of formulating green-field integrated AEV- IoT supply chain strategy.

This paper developed a new theory for supply chain architecture, and engineering design that enables integration of the business and supply chain strategies. The architecture starts with individual supply chain participants and derives insights into the complex and abstract concept of green-field integration design. The paper presented a conceptual system for depicting the interactions between business and supply chain strategy engineering. The system examines the decisions made when engineering the business strategy, with regards to the supply chain design. The system derived with a new understanding of how strategies are integrated, and what are the implications for engineering successful strategies. The study revealed that supply chain design is not considered in great detail before architecting the business strategies. Thus, companies consequentially experience supply chain problems that are likely to be detrimental to the growth potentials. The paper also derived with the findings that proactive and pre-emptive involvement of supply chain participants in the strategy engineering process, would lead to a more robust strategic design.

The focus of this paper is on supply chain strategy formulation. A conceptual theory approach is used for investigating and identifying the relationship between multiple elements, dimensions, forces and factors that influence and affect the supply chain strategy formulation in Greenfield context, specific to the slate mining industry. The research study involved secondary data review and series of 20 qualitative interviews, followed by 2 group discussions, one with mining and transportation experts external to the supply chain and one group discussion with supply chain internal experts. Through critical analysis, a number of problems emerge and the process of addressing these problems, results in a new framework for evaluating the relationship between business and supply chain strategy, specific to Greenfield project and integration design context.

In this paper is discussed sediment transport as a mechanical process that characterises a natural stream or channel flow regime. The objective of experimental work presented in this paper is to recall and to give another prospect of well-known Meyer-Peter and Müller approach for estimation of Shield’s number (θ_c,θ) in laboratory conditions, and calibration of dimensionless MPM number (A). For this purpose two different experiments are conducted, during the first experiment water amount flushed on the flume and bed slope was changed simultaneously until equilibrium state is achieved, meanwhile is estimated the critical Shield’s number (θ_c). While, during the second experiment, water amount was kept constant, only bed slope of flume was continuously tilted, meanwhile sediment, discharge and Shield’s number (θ) was determined for given hydraulic conditions. In addition calibration of dimensionless MPM number (A) was performed, where several iteration were considered until for (A=3.42), sediment discharge measured become almost equal with sediment discharge computed by using MPM formula. After these experiments, is concluded that MPM formula can be used also for other certain initial condition and similar procedure may be adopted to calibrate the dimensionless MPM number (A) .

We present an updated design process for adapting and integrating existing cyber risk assessment approaches for impact assessment for the risk from IoT to the digital economy. The new design process includes a set of changes to the original standards (e.g. NIST) that are adapted for the IoT cyber risk in this paper. This paper also presents a new framework for impact assessment of IoT cyber risk, specific for the digital economy.

Requirements for cloud services include security and privacy. Although many security patterns, privacy patterns, and non-pattern-based knowledge have been reported, knowing which pattern or combination of patterns to use in a specific scenario is challenging due to the sheer volume of options and the layered cloud stack. To deal with security and privacy in cloud services, this study proposes the Cloud Security and Privacy Metamodel (CSPM). CSPM uses a consistent approach to classify and support existing security and privacy patterns. In addition, CSPM is used to develop a security and privacy awareness process to develop cloud systems. The effectiveness and practicality of CSPM is demonstrated via several case studies.

The theoretical limits of water sorbate based chemical sorption heat storage are investigated in this study. First, a classification of \textit{thermochemical heat storage} is proposed based on bonding typology. Then, thermodynamics of chemical solid/gas sorption is introduced. The analysis of the reaction enthalpy from the literature indicates that this value is only slightly varying for one mole of water. Using this observation, and with the help of thermodynamical considerations, it is possible to derive conclusions on energy efficiency of closed and open heat storage systems. Whatever the salt, the main results are 1) the energy required for evaporation of water is, at least, 65% of the available energy of reaction and 2) the maximum theoretical energy efficiency of the system is about 1.8.

Lung nodule segmentation in CT images and its subsequent volume analysis can help determinethe malignancy status of a lung nodule. While several efficient segmentation schemes have beenproposed, only a few studies evaluated the segmentation’s performance for large nodules. In thisresearch, we contribute a semi-automatic system which is capable of performing robust 3-D segmen-tations on both small and large nodules with good accuracy. The target CT volume is de-noisedwith an anisotropic diffusion filter and a region of interest is selected around the target nodule ona reference slice. The proposed model performs nodule segmentation by incorporating a mean in-tensity based threshold in Geodesic Active Contour model in level sets. We also devise an adaptivetechnique using image intensity histogram to estimate the desired mean intensity of the nodule.The proposed system is validated on both lung nodules and phantoms collected from publicly avail-able diverse databases. Quantitative and visual comparative analysis of the proposed work withthe Chan-Vese algorithm and statistic active contour model of 3D Slicer platform is also presented.The resulting mean spatial overlap between segmented nodules and reference nodules is 0.855, themean volume bias is 0.10±0.2 ml and the algorithm repeatability is 0.060 ml. The achieved resultssuggest that the proposed method can be used for volume estimations of small as well as large-sizednodules.

One of the key areas of the International Renewable Energy Agency’s (IRENA) programme of work is the analysis of renewable technology costs and performance and the dissemination of these results to as wide an audience as possible. In addition to analysis, IRENA seeks to engage a broad range of stakeholders in the context of this work through the Renewable Costing Alliance. The Costing Alliance brings together companies, industry association, governments and researchers to share, confidentially, data for real-world renewable energy project cost and performance, helping to build further on IRENA’s costing work to date. In this context the authors analyse the current cost differentials and cost reduction potentials for solar PV in Japan compared to best practice levels and identify the reasons for higher costs in Japan and how to reduce them. This study analyses the current installed cost differentials for utility-scale, commercial and residential rooftop solar PV systems. In addition to identifying the reasons for the cost differentials, potential policy recommendations to reduce the cost differential are identified.

This computational research study analyzes the increase of the specific charge capacity that comes with the reduction of the anisotropic volume expansion during lithium ion insertion within silicon nanowires. This research paper is a continuation from previous work that studied the expansion rate and volume increase. It has been determined that when the lithium ion concentration is decreased by regulating the amount of Li ion flux, the lithium ions to silicon atoms ratio, represented by x, decreases within the amorphous lithiated silicon (a-LixSi) material. This results in a decrease in the volumetric strain of the lithiated silicon nanowire as well as a reduction in Maxwell stress that was calculated and Young’s elastic module that was measured experimentally using nanoindentation. The conclusion as will be seen is that as there is a decrease in lithium ion concentration there is a corresponding decrease in anisotropic volume and a resulting increase in specific charge capacity. In fact the amplification of the electromagnetic field due to the electron flux that created detrimental effects for a fully lithiated silicon nanowire at x = 3.75 which resulted in over a 300% volume expansion becomes beneficial with the decrease in lithium ion flux as x approaches 0.75 which leads to a marginal volume increase of ~25 percent. This could lead to the use of crystalline silicon, c-Si, as an anode material that has been demonstrated in many previous research work to be ten times greater charge capacity than carbon base anode material for lithium ion batteries.

The success of source protection in ensuring safe drinking water is centered around being able to understand the hazards present in the catchment then plan and implement control measures to manage water quality risk to levels which can be controlled through downstream barriers. The programs in place to manage source protection are complex sociotechnical systems involving policy, standards, regulators, technology, human factors and so on. This study uses System Theoretic Process Analysis (STPA) to analyze the operational hazards of a typical drinking water source protection (DWSP) program and identify control measures to ensure safe operations. To validate the results a questionnaire was developed and distributed to specialists in DWSP in Taiwan, Australia and Greece. Using Principle Components Analysis (PCA) of the questionnaire responses, the study identified four critical success factors (CSFs) for DWSP. The four factors identified are ‘Policy and Government Agency Support of Source Protection’, ‘Catchment Risk Monitoring and Information’, ‘Support of Operational Field Activities’ and ‘Response to Water Quality Threats’. The results of this study provide insight into the approach of grouping of source protection measures to identify a series of targeted CSF for operational source protection programs. Using CSF can aide catchment management agencies in ensuring that the risk level in the catchment is managed effectively and that threats to public health from drinking water are managed appropriately.

In this research, the computational fluid dynamic (CFD) approach that has been used in wind power generation field was applied for the solution of the problems of local strong wind areas in railway fields, and the mechanism of wind generation was discussed. At the same time, the affectivity of the application of computational fluid dynamic approach to railway field was discussed. The problem of local wind that occurs on the railway line in winter was taken up in this research. A computational simulation for the prediction of wind conditions by LES was implemented and it was clarified that the local strong wind area is mainly caused by separated flows originating from the small‐scale terrain positioned at its upstream (at approximately 180.0 m above sea level). Meanwhile, the effects of the size of calculation area and spatial grid resolution on the result of calculation and the effect of atmospheric stability were also discussed. It was clarified that when the air flow characteristic of the separated flow originating from the small‐scale terrain (at altitude of approximately 180.0 m) targeted in this research is reproduced at high accuracy by computational simulation of wind conditions, approximately 10.0 m of spatial resolution of computational grid in horizontal direction is required. As a result of the computational simulation of wind conditions of stably stratified flow (Fr = 1.0), lee waves were excited at the downstream of the terrain over time. As a result, the reverse‐flow region lying behind the terrain that had been observed at a neutral time was inhibited. Consequently, local strong wind area was generated at the downstream of the terrain and the strong wind area passing through the observation mast was observed. By investigating the speed increasing rate of local strong wind area induced at the time of stable stratification, it was found that the wind was approximately 1.2 times stronger than what was generated at a neutral time.

The assessment of rockfall risks on human activities and infrastructure is of great importance. Rock falls pose a significant risk to a) transportation infrastructure b) inhabited areas and c) Cultural Heritage sites. The paper presents a method to assess rockfall susceptibility at national scale in Greece, using a simple rating approach and GIS techniques. An extensive inventory of rockfalls for the entire country was compiled for the period between 1935 and 2019. The rockfall events that were recorded are those, which have mainly occurred as distinct rockfall episodes in natural slopes and have impacted human activities, such as roads, inhabited areas and archaeological sites. Through a detailed analysis of the recorded data, it was possible to define the factors which determine the occurrence of rockfalls. Based on this analysis, the susceptibility zoning against rockfalls at national scale was prepared, using a simple rating approach and GIS techniques. The rockfall susceptibility zoning takes into account the following parameters: (a) the slope gradient, (b) the lithology, (c) the annual rainfall intensity, (d) the earthquake intensity and (e) the active fault presence. Emphasis was given on the study of the earthquake effect as a triggering mechanism of rockfalls. Finally, the temporal and spatial frequency of the recorded events and the impact of rockfalls on infrastructure assets and human activities in Greece were evaluated.

Nowadays, the development or improvement of actuation mechanisms is a crucial topic for the achievement of dextrous manipulation using soft robots. Then, a primary target of research is the design of actuation and driving devices. Consequently, in this paper, we introduce a soft driving epicyclical mechanism that mimics human muscle behavior and fulfills motion requirements to achieve grasping gestures using a robotic finger. The prototype is experimentally assessed, and results show that our approach has enough performance for the implementation in grasping tasks. Furthermore, we introduce the basis for a new soft epicyclical mechanism merger with shape memory alloys to allow active stiffness control of the mechanism.

In this paper, we present the design, manufacturing and characterization of a soft textile-based clutch (TBC) that switches between locking and unlocking of its linear displacement by exploiting vacuum stimulation. The applied vacuum locks the relative sliding motion between two elaborated textile webbings covered by an elastic silicone rubber bag. Based on different fabrication techniques, such as silicone casting on textile, melt embossing for direct fabrication of miniature patterns on textile and sewing, we developed three groups of TBC samples based on friction and interlocking principles and we compared their performance in blocking configuration. The clutch with interlocking mechanism presented the highest withstanding force (150 N) respect to the one (54 N) recorded for the friction-based clutch. The simple and compact structure of the proposed clutch, together with the intrinsic adaptability of fabric with other clothing and soft materials, make it a proper solution for applications in soft wearable robotics and generally as locking and variable stiffness solution for soft robotic applications.

The Batch process of Adsorption were conducted using Congo red (CR) as the adsorbate and Jatropha curcas seed (chaff) as the adsorbent material. Adsorption kinetics and isotherms analysis were conducted and results obtained confirmed the adsorption process as highly dependent on effects such as; contact time, adsorbent dosage, initial dye concentration and the particle sizes of adsorbate. However, the sorption equilibrium for Congo red dye unto jatropha curcas seed (chaff) was reached within 180 minutes, more so, the Adsorption efficiency was recorded at 82.05%. The process of the experimental sorption kinetics followed a pseudo-second-order kinetic model while Freundlich isotherm model was best applicable for obtaining the equilibrium of the parameters. These is an effective confirmation and validation of jatropha curcas seed (chaff) application as environmentally friendly and low-cost biomaterial for dye removal from aqueous solutions and industrial effluents.

A Micro holes in a diamond are presented by using a homemade femtosecond (fs) Yb:KGW laser. An fs laser source was used emitting pulse duration of 230 fs at 1030 nm wavelength, whereas the spot size amounted to 8.9 μm. Parameters like pulse energy, and pulse number were varied over a wide range in order to evaluate their influence both on the micro hole geometry like hole diameter, circularity, taper angle, and on the drilling quality. Hourglass-shaped micro holes whose diameters decrease and increase again after a certain depth have important applications. The results demonstrate the feasibility of extending the drilling of an hourglass-shaped hole in a diamond sample, which has similar diameters at the hole entrance (92 μm) and exit (95 μm), but a much smaller diameter (28 μm) at a certain waist section inside the hole.

The vibration feature of weak gear fault is often covered in strong background noise, which makes it necessary to establish weak feature enhancement methods. Among the enhancement methods, stochastic resonance (SR) has the unique advantage of transferring noise energy to weak signals and has a great application prospection in weak signal extraction. But the traditional SR potential model cannot form a richer potential structure and may lead to system instability when the noise is too great. To overcome these shortcomings, the article presents a periodic potential underdamping stochastic resonance (PPUSR) method after investigating the potential function and system signal-to-noise ratio (SNR). In addition, system parameters are further optimized by using ant colony algorithm. Through simulation and gear experiments, the effectiveness of the proposed method was verified. We concluded that compared with the traditional underdamped stochastic resonance (TUSR) method, the PPUSR method had a higher recognition degree and better frequency response capability.

This study was designed to assess the reliability of geographic information using satellite image information in ungauged basins. For this, this study constructed geographic information using actual gauged data and satellite information data and conducted runoff analysis through S-RAT, a rainfall–runoff model, and performed the comparison and analysis of geographic information and runoff data. For actual gauged data, the gauged geographic information of the Water Resources Management Information System (WAMIS) was collected, and for satellite information, the image information of moderate-resolution imaging spectroradiometer (MODIS) observation sensor loaded on Terra Satellite was collected. As analysis areas, three basins where mountains occupy more than 80% and another three basins where urban areas occupy more than 7% in the Han River basin were selected. According to the analysis result, the gauged information and satellite image information showed great difference in runoff, maximum 50% in peak flood and maximum 17% in total flood, in the rivers with many urban areas, while the runoff difference in the rivers with many mountains showed maximum 13% in peak flood and 4% in total flood. What showed the greatest difference in image information was land use, and it turned out that the MODIS satellite recognized the urban rivers as cities for more than maximum 60% compared to WAMIS-gauged data. Meanwhile, in the forest area, the MODIS satellite image showed error of less than 5% of the WAMIS-gauged data, which indicates that it has higher applicability in Mountain Rivers.

Here, we propose a novel scheme based on advanced techniques of digital modulation in optical communications to achieve a single-channel transmission rate above 100 Gb/s. We utilize a hybrid scheme amplitude/phase/frequency/dual polarization, combined with multidimensional dual lattice and a low-density parity-check-coded modulation. The Stokes parameters are applied to the proposed scheme to map the four-dimensional classical polarization \({I_X},{Q_X},{I_Y},{Q_Y}\) in a three-dimensional space. In addition, in the proposed system, the packing theory is applied to the bit interleaver process, three wavelengths are packaged before being transmitted over a wavelength-division multiplexing optical channel. This modulation process is carried out using symmetrical geometric shapes, such as a hypercube or a polyhedron, based on the molecular links theory using a grouping of 12 and 13/15 bits for the cubic and spherical lattices, respectively. The proposed technique is evaluated in the context of long distance communications over distances up to 100 km. The bit error rate results showed that the optical signal-to-noise ratio was approximately 4 dB over a distance of 50 km. In addition, the power spectral efficiency was found to be 3 lambda, which is considered good performance considering the effects of distance and the non-linear effects influencing the number of lambdas. Also, we use an optical time division multiplexing scheme (OTDM) in order to achieve a transmission rate beyond 1Tbit/s, where the speed effect is evaluated, taking into consideration that the power spectral efficiency is degraded. Furthermore, the average noise floor is -60dBm for all transmission distances. These findings are expected to contribute to the future implementation of robust long-distance optical communication infrastructure.

Many causal factors to marine traffic accidents (MTA) influence each other and have associated effects. It is necessary to quantify the correlation path mode of these factors to improve accident prevention measures and their effects. In the application of human factors to the accident mechanisms, the complex structural chains on causes to MTA systems were analyzed combining the Human Failure Analysis and Classification System (HFACS) with theoretical Structural Equation Modeling (SEM). First, the accident causation model was established as a human error analysis classification in sight of MTA, and the constituent elements of the causes of accident was conducted. Second, a hypothetical model of Human factors classification was proposed applying the practice of the structural model. Third, with the data resource from ship accident cases, this hypothetical model was discussed and simulated, and as a result the relationship path dependency mode between the latent independent variable of the accident was quantitatively analyzed based on the observed dependent variable of human behaviors. Application examples show that relationships in HFACS are verified and in line with the path developing mode, and resource management factors have a pronounced influence and a strong relevance to the causal chain of the accidents. Appropriate algorithms for the theoretical model can be used to numerically understand the safety performance of marine traffic systems under different parameters through mathematical analysis. Hierarchical assumptions in the HFACS model are quantitatively verified.

Appropriate estimation of soil settlement is of significant importance since it directly influences the performance of building and infrastructures that are built on soil. In particular, the settlement of fine-grained soils is critical because of low permeability and continuous settlement with time. Coefficient of consolidation (Cc) is a key parameter to estimate settlement of fine-grained soil layers. However, estimation of this parameter is time consuming, needs skilled technicians, and specific equipment. In this study, Cc was estimated using several soil parameters such as liquid limit (LL), plastic limit (PL), and initial void ratio (e0). Estimating such parameters in laboratory is straight forward and needs substantially less time and cost compared to conventional tests to estimate Cc such as Oedometer test. This study presents a novel prediction model for Cc of fine-grained soils using gene-expression programming (GEP). GEP is a biologically inspired technique capable of offering closed-form solution for the optimal solution. A database consisted of 108 different data points was used to develop the model. A closed-form equation solution was derived to estimate Cc based on LL, PL, and e0. The performance of developed GEP-based model was evaluated through coefficient of determination (R2), root mean squared error (RMSE), and mean average error (MAE). High R2 and low error values indicated the descent performance of the model. Furthermore, the model was evaluated using the additional performance measures and met all the suggested criteria. Furthermore, the model had a better performance in terms of R2, RMSE, and MAE compared to most of existing models. It is expected that the developed model will decrease the time and cost associate with determining Cc of fine-grained soils.

Appropriate estimation of soil settlement is of significant importance since it directly influences the performance of building and infrastructures that are built on soil. In particular, the settlement of fine-grained soils is critical because of low permeability and continuous settlement with time. Coefficient of consolidation (C_c) is a key parameter to estimate settlement of fine-grained soil layers. However, estimation of this parameter is time consuming, needs skilled technicians, and specific equipment. In this study, C_c was estimated using several soil parameters such as liquid limit (LL), plastic limit (PL), and initial void ratio (e₀). Estimating such parameters in laboratory is straight forward and needs substantially less time and cost compared to conventional tests to estimate C_c such as oedometer test. This study presents a novel prediction model for C_c of fine-grained soils using gene-expression programming (GEP). GEP is a biologically inspired technique capable of offering closed-form solution for the optimal solution. A database consisted of 108 different data points was used to develop the model. A closed-form equation solution was derived to estimate C_c based on LL, PL, and e₀. The performance of developed GEP-based model was evaluated through coefficient of determination (R²), root mean squared error (RMSE), and mean average error (MAE). High R² and low error values indicated the descent performance of the model. Furthermore, the model was evaluated using the additional performance measures and met all the suggested criteria. Furthermore, the model had a better performance in terms of R², RMSE, and MAE compared to most of existing models. It is expected that the developed model will decrease the time and cost associate with determining C_c of fine-grained soils.Keywords: evolutionary model, gene-expression programming (GEP), prediction, soil compression index, estimation, soil engineering, soil informatics, civil engineering, machine learning, data science, big data, soft computing, deep learning, forecasting, subject classification codes, construction informatics, computational intelligence (CI), artificial intelligence (AI), estimation

The diffusion of electric vehicles (EVs) can be sustained by the presence of integrated solutions offering parking and clean power supply. The recourse to DC systems allows to better integrate EV bidirectional energy exchange, photovoltaic panels and energy storage. In this paper, a methodology for optimal techno-economic sizing of a DC-microgrid for covering EV mobility needs is carried out. It is based on the definition of different scenarios of operation, according to typical EV usage outlooks and environmental conditions. In each scenario, optimal operation is carried out by means of a specific approach for EV commitment on different stations. The sizing procedure is able to handle the modular structure of microgrid devices. The proposed approach is applied to a case study of envisaged EV service fleet for Bari port authority.

Improving the efficiency of the supply process in prefabricated components is challenging and requires accounting for a variety of risks involved in the management of the suppliers. The purpose of this study is to present a method to account for the systematic trade-offs between several supplier alternatives. A novel framework is presented for the whole assessment of supplier alternatives by taking advantage of the information extracted from customized building information modeling (BIM) and a database required for assessment of impacts. A data library related to assessment criteria for supply alternatives is built to facilitate the storage and sharing of information. Analytic hierarchy process (AHP) is used to select the optimal supplier that is able to provide the most satisfaction for the determined criteria. The proposed framework was also illustrated by the implementation in a mega project. The study implication is that BIM-enabled supplier selection can indeed lead to more benefits and higher values for all stakeholders.

Background: Mitigating climate change requires fundamentally redesigned energy systems in which renewable energy sources ultimately replace fossil fuels such as natural gas. In this context, the question how and to which extent the gas sector can contribute to an increasingly climate-neutral future EU energy system is heavily debated among scholars, energy industry experts and policy makers. Methods: We take a two-step approach: We begin with a review of studies from energy industry and academia to discuss potential gas sector contributions from a holistic energy system design point of view; this is followed by a comprehensive discussion of technical potentials, micro-economic conditions and societal implications of renewable gas. We then enrich our findings with the results of an empirical focus group process. Results: The gas sector can not only contribute to balancing volatile renewable energy production but also enable the supply of renewable energy to end-users in gaseous form; based on existing infrastructure. This could reduce costs for society, increase public acceptance and ultimately speed up the energy system transformation. There is the theoretical technical potential to substitute major parts of natural gas with renewable gas of biogenic and synthetic nature. This, however, crucially requires a supportive policy framework like the one established for renewable electricity. Conclusion: Given the societal benefits and the competitiveness of renewable gas as compared to renewable alternatives, energy policy makers should incorporate renewable gas and the existing gas infrastructure in the future energy system framework. The objective should be an optimized interplay of various energy vectors and their infrastructure along the entire energy supply chain. This requires a level playing field for different renewable technologies across different policy areas and a form of public support that strikes the balance between facilitating the gradual substitution of natural gas by renewable gas while maintaining public acceptance for this transformation despite higher costs for end-users.: Given the societal benefits and the competitiveness of renewable gas as compared to renewable alternatives, energy policy makers should incorporate renewable gas and the existing gas infrastructure in the future energy system framework. The objective should be an optimized interplay of various energy vectors and their infrastructure along the entire energy supply chain. This requires a level playing field for different renewable technologies across different policy areas and a form of public support that strikes the balance between facilitating the gradual substitution of natural gas by renewable gas while maintaining public acceptance for this transformation despite higher costs for end-users.

The reinforcement of concrete by using polyolefin fibres may be considered in structural design to meet the requirements of the applicable code rules. In order to achieve a reliable use of such a composite material, use of full-scale real structures is needed. The conversion of lab testing data into real practice properties is challenging and significantly influenced by various aspects, among which the size effect is a key one. Given that the available literature does not report coinciding conclusions about such an effect on quasi-brittle materials reinforced with fibres, further research is justified. Therefore, this work studies the behaviour of notched beams with three proportional sizes by using self-compacting polyolefin reinforced concrete with a fibre volume fraction of 1.1%. Flexural testing was carried out according to the standard EN-14651, with the results revealing the existence of the size effect. In addition, a reduction of the residual strength identified in the larger specimens was observed in fracture surfaces with equal fibre content.

Objective:The application of information technology (IT( is fundamental in the hospitals to stay competitive.In this regard, recognizing the main risks to the implementation of IT in hospitals can provide vastopportunities to improve its efficiency and help to make strategic decisions. This study aimed tosearch for the main risks of implementation of IT projects in the hospitals of Tehran. Methods: This was a practical and cross-sectional study which was conducted in the 18 hospitals of Tehran,Iran, 2018; in which a sample of 65 members were studied. The required data were collected using a questionnaire to examine seven main risks, including market, project management, human resources, technical, organizational, financial, strategic risks. The collected data were analyzed using SPSS 19.0. Additionally, the method used to test the risks in this study was structural equation modeling, which was ran using LISREL 9.30. Results: The results showed that among the seven main risks of to the implementation of IT in hospitals, the highest and lowest means were related to the human resource risks and the market risks, respectively. Also, according to the SEM, human resource risks and market risks had the highest and lowest effects, respectively. Conclusion: Announcing the use of IT in the hospitals, holding conferences about new IT developments with employees, suitable training, encouraging them to use IT tools, providing a motivating atmosphere to use IT tools for employees, are a few effective ways of overcoming the human resource risks.

The NCO functional group of 3-isocyanatoproply triethoxysilane (IPTS) and the OH functional group of DOPO-BQ were used to conduct an addition reaction. Following completion of the reaction, triglycidyl isocyanurate (TGIC) was introduced to conduct a ring-opening reaction. Subsequently, a sol-gel method was used to take place a hydrolysis- condensation reaction on TGIC-IPTS-DOPO-BQ to form a hyperbranched nitrogen–phosphorous–silicon (HBNPSi) flame retardant. This flame retardant was incorporated into a polyurethane (PU) matrix to prepare a hybrid material. Fourier-transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), limiting oxygen index (LOI), UV-VIS spectrophotometry, and Raman analysis were conducted to structure characterization and analyzed transparency, thermal stability, flame retardancy, and residual char to understand the flame retardant mechanism of prepared hybrid materials. After the flame retardant was added, the maximum degradation rate decreased from −36 wt%/min to −17 wt%/min, the integral procedure decomposition temperature (IPDT) increased from 348 ℃ to 488 ℃, and the char yield increased from 0.7 to 8.1 wt%. The aforementioned results verified that thermal stability of PU can be improved after adding HBNPSi. The LOI analysis indicated that the pristine PU was flammable because the LOI of pristine PU was only 19. When the content of added HBNPSi was 40%, the LOI value was 26; thus the PU hybrid became nonflammable.

Since electrical resistivity of concrete can be measured in a more rapid and simple way than chloride diffusivity, it should be primarily regular quality control of the electrical resistivity of concrete which provides the basis for indirect of quality control of concrete durability during the concrete construction. If this is realized, the electrical resistivity of concrete can be a crucial parameter to establish maintenance strategy for marine concrete structures. Electrical resistivity of concrete is important to estimate two processes involved in corrosion of reinforcement: initiation (chloride penetration) and propagation (corrosion rate). The resistivity of concrete structure exposed to chloride indicates the risk of early corrosion damage, because a low resistivity is related to rapid chloride penetration and to high corrosion rate. Concrete resistivity is a geometry-independent material property that describes the electrical resistance, which is the ratio between applied voltage and resulting current in a unit cell. The current is carried by ions dissolved in the pore liquid. While some data exist on the relationship between moisture content on electrical resistivity of concrete, very little research has been conducted to evaluate the effect of chloride on the conduction of electricity through concrete. The purpose of this study is to examine and quantify the effect of pore water and chloride content on surface electrical resistivity measurement of concrete. It was obvious that chloride content had influenced the resistivity of concrete and the relationship showed a linear function. That is, concrete with chloride ions had a comparatively lower resistivity. Chloride can lead to underestimate the electrical resistivity of concrete. Conclusively, this paper suggested the quantitative solution to depict the electrical resistivity of concrete with various chloride contents.

Bioelectrochemical systems (BES) encompass a group of biobased technologies capable of directly converting organic matter into electricity. In these systems, which are derived from conventional electrochemical systems, the ion exchange membrane represents a key element because of its influence on the economic feasibility and on the performance of BES. This study examines the impact of long-term operation of a BES on the mechanical, chemical and electrochemical properties of five different kind of cation exchange membranes (Nafion-117, CMI-7001, Zirfon UTP 500, FKE and FKB) through several techniques: (i) scanning electron microscopy (SEM) and atomic force microscopy (AFM) to assess the changes on the membranes surface, (ii) thermogravimetric analysis (TGA) to evaluate the structural stability of the membranes, and (iii) ion exchange capacity (IEC) to monitor any change in their electrochemical properties. Results confirmed that there is not an ideal membrane for BES. While Nafion and CMI-7000 exhibited the strongest chemical structure, they also underwent the highest fouling as revealed by a fast increase in surface roughness.

This paper presents an overview of the smart electro-clothing systems (SeCSs) targeted at health monitoring, sports benefits, fitness tracking, and social activities. Technical features of the available SeCSs, covering both textile and electronic components, are thoroughly discussed and their applications in the industry and research purposes have been highlighted. In addition, it also presents the developments in the associated areas of wearable sensor systems and textile-based dry sensors. As it became evident during the literature research, such a review on SeCSs covering all relevant issues has not been presented before. This paper will be particularly helpful for new generation researchers investigating the design, development, function and comforts of the sensor integrated clothing materials.

The study presents a comparative approach between response surface methodology (RSM) and hybridized, genetic algorithm artificial neural network (GA-ANN) in predicting the water absorption, compressive strength, flexural strength split tensile strength and slump for steel fiber reinforced concrete. The effect of process variables such as aspect ratio, water cement ratio and cement content were investigated using the central composite design of response surface methodology. This same experimental design was used in training the hybrid-training approach of artificial neural network. The predicting ability of both methodologies were compared using the root mean sqaured error (RMSE), mean absolute error (MAE), model predictive error (MPE) and absolute average deviation (AAD). The RSM model was found more accurate in prediction compared to hybrid GA-ANN.

The growing market penetration of heat pumps indicates the need for a performance test method which better reflects the dynamic behavior of heat pumps. In this contribution, we developed and implemented a dynamic test method for the evaluation of the seasonal performance of heat pumps by means of laboratory testing. Current standards force the heat pump control inactive by fixing the compressor speed. In contrast, during dynamic testing, the compressor runs unfixed while the heat pump is subjected to a temperature profile. The profile consists of the different outdoor temperatures of a typical heating season based on the average European climate and also includes temperature changes to reflect the dynamic behavior of the heat pump. The seasonal performance can be directly obtained from the measured heating energy and electricity consumption making subsequent data interpolation and recalculation with correction factors obsolete. The method delivers results with high precision and high reproducibility and could be an appropriate method for a fair rating of heat pumps.

The tradeoff between the design phase and the experimental setup is crucial to satisfy the accuracy requirement of Large Deployable Reflectors. Manufacturing errors and tolerances change the RMS of the reflecting surface and require careful calibration of the tie rod system to be able to fit into the initial design specifications. To give a possible solution to this problem, here two calibration methods, respectively for rigid and flexible ring truss support, are described. Starting from the acquired experimental data on the net nodal coordinates, the initial problem of satisfying the static equilibrium at the measured configuration is described. Then, two constrained optimization problems, for rigid and flexible ring truss support, are defined to meet RMS accuracy of the reflecting surface modifying the tie lengths. Finally, a case study to demonstrate the validity of the proposed methods is presented.

This paper presents a study and implementation of a convolutional neural network to identify and recognize humpback whale specimens from the unique patterns of their tails. Starting from a dataset composed of images of whale tails, all the phases of the process of creation and training of a neural network are detailed – from the analysis and pre-processing of images to the elaboration of predictions, using TensorFlow and Keras frameworks. Other possible alternatives are also explained when it comes to tackling this problem and the complications that have arisen during the process of developing this paper.

Cost estimating based on building cost index plays an important role in project planning and management by providing accurate cost information. Recently, tremendous advances in cost estimating has been made but serious inaccuracies in it are still too frequently witnessed. This study aims to improve estimating accuracy for residential building costs in New Zealand. In this study, the New Zealand house prices index is involved in the transfer function models to produce forecasts of building costs for one-storey house, two-storey house, and town house in New Zealand. To demonstrate the effectiveness of the proposed models, this study compares the estimate results of the transfer function models with the univariate ARIMA models. The results indicate that the proposed transfer function models can achieve better outcomes than ARIMA models by considering the causality between building costs and New Zealand house prices. During the modelling process, the better cost estimation approach can be identified, and the movements of building costs are shown.

Machine learning (ML) methods has recently contributed very well in the advancement of the prediction models used for energy consumption. Such models highly improve the accuracy, robustness, and precision and the generalization ability of the conventional time series forecasting tools. This article reviews the state of the art of machine learning models used in the general application of energy consumption. Through a novel search and taxonomy the most relevant literature in the field are classified according to the ML modeling technique, energy type, perdition type, and the application area. A comprehensive review of the literature identifies the major ML methods, their application and a discussion on the evaluation of their effectiveness in energy consumption prediction. This paper further makes a conclusion on the trend and the effectiveness of the ML models. As the result, this research reports an outstanding rise in the accuracy and an ever increasing performance of the prediction technologies using the novel hybrid and ensemble prediction models.

Opportunistic routing uses the broadcasting nature of the wireless medium to increase the number of potential forwarding nodes in the network. This, in turn improves the delivery rate and reliability of data transmission in the network. Compared to all previous classes of protocols, opportunistic routing offers numerous advantages which is exploited by the latest applications for efficient communication and resource sharing in dynamic ad hoc networks. The objective of this research work is to review and classify all the major opportunistic routing protocols proposed for dynamic ad hoc networks. Further the issues and challenges with each of these existing protocol is discussed and future research directions are put forward.

This research article reports the results of a qualitative case study that correlates academic literature with five Industry 4.0 cyber trends, seven cyber risk frameworks and two cyber risk models. While there is a strong interest in industry and academia to standardise existing cyber risk frameworks, models and methodologies, an attempt to combine these approaches has not been done until present. We apply the grounded theory approach to derive with integration criteria for the reviewed frameworks, models and methodologies. Then, we propose a new architecture for the integration of the reviewed frameworks, models and methodologies. We therefore advance the efforts of integrating standards and governance into Industry 4.0 and offer a better understanding of a holistic economic impact assessment model for IoT cyber risk.

In this paper we present an understanding of cyber risks in the Internet of Things (IoT), we explain why it is important to understand what IoT cyber risks are and how we can use risk assessment and risk management approaches to deal with these challenges. We introduce the most effective ways of doing Risk assessment and Risk Management of IoT risk. As part of our research, we also developed methodologies to assess and manage risk in this emerging environment. This paper will take you through our research and we will explain: what we mean by the IoT; what we mean by risk and risk in the IoT; why risk assessment and risk management are important; the IoT risk management for incident response and recovery; what open questions on IoT risk assessment and risk management remain.

In this paper we describe many important aspects connected with lubricants, namely: the most cheapest organic lubricant in the word, how effectively save lubricant between pairs of friction, what kind of rational shapes for the lubricant must be, what it will be connected with wear and tear using the new organic lubricant (for this purpose formulas and curves are shown in computer program MathCad with calculation). Moreover, there is one physical model which helps to catch car exhausted gases. In conclusion, some recommendations will be given to realize them into the practice during the operation for the different mechanisms including ecology.

The purpose of this study is nutrient resources recovery by achieving the optimal chemical oxygen demand (COD) and carbon to nitrogen ratio (C/N) in co-composting wastewater treatment plant sludge with Municipal Solid Wastes (MSW). In this effort, the co-composting has been conducted in form of a case study in the northern region of Iran. In this research, 192 tests were carried out on four series of samples examined in terms of waste to sludge ratio, different aeration period, the percent of porous materials and the moisture content. This study was carried out at a temperature of 50 °C for a 15 day period by application of the in-vessel system and shows that the best ratio for waste to sludge is 2:1, while the 8 hour period is the best aeration period. The porous material which can be added to the composting process is limited to 15% in weight. In other words, any more or less amount of this material will adversely impact the process. Moreover, this research suggests that the sludge dewatering is not required in such processes. In Addition, the efficiency of both COD and C/N reductions equals to about 40%.

Reliability is essential in industrial networks. In addition, most of the data from nodes of industrial Internet of Things (IIoT) are generated in real time. Thus, those data are mainly used for the time-sensitive applications. Furthermore, device failures should be considered when modeling reliable fog computing for IIoT. In this paper, we provide fundamental aspects to model reliable fog computing for IIoT. First, existing models of fog computing are compared. Then, the most feasible communication type to achieve a reliable system is determined from model analysis. Interaction modes are elaborated to study the advantages and drawbacks when communication is deployed in fog computing for IIoT, and challenges and solutions for reliable fog computing are discussed.

The world is currently experiencing the fourth industrial revolution driven by the newest wave of digitisation in the manufacturing sector. The term Industry 4.0 (I4.0) represents at the same time: a paradigm shift in industrial production, a generic designation for sets of strategic initiatives to boost national industries, a technical term to relate to new emerging business assets, processes and services, and a brand to mark a very particular historical and social period. I4.0 is also referred to as Industrie 4.0 the New Industrial France, the Industrial Internet, the Fourth Industrial Revolution and the digital economy. These terms are used interchangeably in this text. The aim of this article is to discuss major developments in this space in relation to the integration of new developments of IoT and cyber physical systems in the digital economy, to better understand cyber risks and economic value and risk impact. The objective of the paper is to map the current evolution and its associated cyber risks for the digital economy sector and to discuss the future developments in the Industrial Internet of Things and Industry 4.0.

The New Zealand housing sector is experiencing rapid growth that boosts the national economy but also results in the loss of valuable resources. In line with the growth, the housing market for both residential and business purposes has been booming, as have house prices. To sustain the housing development, it is critical to accurately monitor and predict housing prices so as to support the decision-making process in housing sector. This study is devoted to applying a mathematical method to predict housing prices. The forecasting performance of two types of models: ARIMA and multiple linear regression analysis are compared. The ARIMA and regression models are developed based on a training-validation sample method. The results show that the ARIMA model generally performs better than the regression model. However, the regression model explores, to some extent, the significant correlations between house prices in New Zealand and the macro-economic conditions.

Waste heat dissipated in the exhaust system in a combustion engine represents a major source of energy to be recovered and converted into useful work. A waste heat recovery system (WHRS) based on an Organic Rankine Cycle (ORC) is a promising approach, and has gained interest in the last few years in an automotive industry interested in reducing fuel consumption and exhaust emissions. Understanding the thermodynamic response of the boiler employed in an ORC plays an important role in steam cycle performance prediction and control system design. The aim of this study is therefore to present a methodology to study these devices by means of pattern recognition with infrared thermography. In addition, the experimental test bench and its operating conditions are described. The methodology proposed identifies the wall coordinates, traces paths, and tracks wall temperature along them in a way that can be exported for subsequent post-processing and analysis. As for the results, through the wall temperature paths on both sides (exhaust gas and working fluid) it was possible to quantitatively estimate the temperature evolution along the boiler and, in particular, the beginning and end of evaporation.

The Internet-of-Things (IoT) enables enterprises to obtain profits from data but triggers data protection questions and new types of cyber risk. Cyber risk regulations for the IoT however do not exist. The IoT risk is not included in the cyber security assessment standards, hence, often not visible to cyber security experts. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. The outcome of such self-assessment needs to define a current and target state, prior to creating a transformation roadmap outlining tasks to achieve the stated target state. In this article, a comparative empirical analysis is performed of multiple cyber risk assessment approaches, to define a high-level potential target state for company integrating IoT devices and/or services. Defining a high-level potential target state represent is followed by a high-level transformation roadmap, describing how company can achieve their target state, based on their current state. The transformation roadmap is used to adapt IoT risk impact assessment with a Goal-Oriented Approach and the Internet of Things Micro Mart model.

The relationships among the potential causes of a car and motorcycle collision involving turn maneuvers as well as the perception of rear and front turn signal (on/off) configuration is examined in this paper. The investigation has been based on data pooled from the answers of a survey proposed to 136 people, with special regards to the correct detection of indicators aspect. Experimental videos have been realized during the tests campaign, both in urban and suburban areas, using a 360-camera attached to a motorcyclist’s helmet, reproducing vehicular conflicts able to potentially generate crash risks. The detection of the blinker was combined with other factors (e.g. age, gender, location of the test site, presence of the car behind tester vehicles and if the bikers are also habitual car or bike drivers) in a stepwise logistic regression that modelled the odds of detecting the turn signal turned on as a function of all of these factors. The results suggest the existence of a connection between the detection of the turn signal aspect and some of the variables considered (e.g. age, being a cyclist or a car driver and the presence of a protecting car).

After conducting a detailed survey among the villagers of Pallissery and Karukutty, it was observed that in most of the villages the native people have to travel long distances for their basic health needs. Also most of the villagers lack knowledge regarding live health updates. At times, these problems have even resulted in death of many people including pregnant women and children. The objective of our research is to propose an integrated and easy to use Medical Kiosk that can be installed at various locations in rural areas. The Kiosk will provide an integrated environment for all medical related activities and would perform numerous functions like sending notifications regarding medical camps, mobile medical help, important dates for vaccinations, child care, insurance policies and provide other live medical updates to the villagers. It would also support the basic facilities for measurement of body parameters like height, weight, BMI, blood pressure, and heartbeat and also facilitate live consultation facilities with specialized doctors through video and voice chats.

Original and improved version of the Hardy Cross iterative method with related modifications are today widely used for calculation of fluid flow through conduits in loops-like distribution networks of pipes with known node fluid consumptions. Fluid in these networks is usually natural gas for distribution in the municipalities, water in waterworks or hot water in district heating system, air in the case of ventilation systems in buildings or mines, etc. Since, the resistances in these networks depend of flow, problem is not linear like in electrical circuits, and iterative procedure must be used. In both version of the Hardy Cross method, in original and in the improved one, initial results of calculation in iteration procedure is not flow, but rather the correction of flow. Unfortunately, these corrections should be added to or subtracted from a flow calculated in previous iteration according to complicate algebraic rules. After the here presented node-loop method, final results in each of the iterations is flow directly rather than flow correction. In that way complex algebraic scheme for sign of flow correction is avoided, while the final results still remain unchanged. Numbers of required iterations for the same results are comparable with the improved Hardy Cross method.