This thesis completion works it out to deepen into diverse modeling techniques for Point Absorbers. A combined frequency-time domain model is conceived, designed and developed in Matlab with Fortran as a base, leading to obtain physical variables of primary importance, namely position, velocity and power to energy net balance relationships of absorption. Integration of different degrees of freedom with heave as main executable leads in turn to a single buoy motion focus. Acquisition of the needed hydrodynamic coefficients is provided through application of NEMOH \& BEMIO solvers due to the Boundary Element Methodology. Initially, this Wave-to-motion model is validated by comparison with previous experimental results for a floating cone cylinder shape (Buldra-FO3). A single, generic, vertical floating cylinder is contemplated then, that responds to the action of the passing regular waves excitation. Later, two equally sized vertical floating cylinders aligned with the incident wave direction are modeled for a variable distance between the bodies. For both unidirectional regular and irregular waves as an input in deep water, we approximate the convolutive radiation force function term through the Prony method. By changing the spatial disposition of the axisymmetric buoys, using for instance triangular or rectangular shaped arrays of three and four bodies respectively, the study delves into motion characteristics for regular waves. The results highlight efficient layouts for maximizing the energy production whilst providing important insights into their performance, revealing displacement amplification- and capture width-ratios, while deriving in possible interpretations of scenarios related to the the known park effect. These terms are encompassed by the novelty of a new conceptual Post-Processing methodology in the field, which leads to obtain an optimal distance for the separated bodies with effective energy absorption in a regular wave regime. In conclusion, this computational excursion envisions and proposes potential fields of study, which will surely enhance new connections and link this renewable energy form.

This paper presents the design and implementation of a multichannel bio-impedance spectroscopy system on field programmable gate arrays (FPGA). The proposed system is capable of acquiring multiple signals from multiple bio-impedance sensors, process the data on the FPGA and store the final data in the on-board Memory. The system employs the Digital Automatic Balance Bridge (DABB) method to acquire data from biosensors. The DABB measures initial data of a known impedance to extrapolate the value of the impedance for the device under test. This method offers a simpler design because the balancing of the circuit is done digitally in the FPGA rather than using an external circuit. Calculations of the impedance values for the device under test were done in the processor. The final data is sent to an onboard Flash Memory to be stored for later access. The control unit handles the interfacing and the scheduling between these different modules (Processor, Flash Memory) as well as interfacing to multiple Balance Bridge and multiple biosensors. The system has been simulated successfully and has comparable performance to other FPGA based solutions. The system has a robust design that is capable of handling and interfacing input from multiple biosensors. Data processing and storage is also performed with minimal resources on the FPGA.

Ventilation in cities is crucial for the well being of their inhabitants. Therefore, local governments require air ventilation assessments (AVAs) prior to the construction of new buildings. In a standard AVA, however, only neutral stratification is considered, although diabatic and particularly unstable conditions may be observed more frequently in nature. The results presented here indicate significant changes in ventilation within most of the area of Kowloon City, Hong Kong, included in the study. A new definition for calculating ventilation was introduced, and used to compare the influence of buildings on ventilation under conditions of neutral and unstable stratification. The overall ventilation increased due to enhanced vertical mixing. In the vicinity of exposed buildings, however, ventilation was weaker for unstable stratification than for neutral stratification. The influence on ventilation by building parameters, such as the plan area index, was altered when unstable stratification was considered. Consequently, differences in stratification were shown to have marked effects on ventilation estimates, which should be taken into consideration in future AVAs.

An ultra-low power (ULP), power gated static random access memory (SRAM) is presented for Internet of Things (IoT) applications, which operates in sub-threshold voltage ranges from 300mV to 500mV. The proposed SRAM has tendency to operate in low supply voltages with high static and dynamic noise margins. The IoT application involves battery enabled low leakage memory architecture in subthreshold regime which has low power consumption. Therefore, to improve power consumption along with better cell stability, a power gated 10T SRAM is presented. The proposed cell uses a power gated p-MOS transistor to reduce the leakage power or static power in standby mode. Moreover, due to the schmitt triggering and read decoupling of 10T SRAM the static and dynamic behavior in read, write and standby mode has shown enhanced tolerance at different process, voltage and temperature (PVT) conditions. The proposed SRAM shows better results in terms of leakage power, read static noise margin (RSNM), write static noise margin (WSNM), write-ability or write trip point (WTP), read-write energy and dynamic read margin (DRM). Further, these parameters are observed at 8-Kilo bit (Kb) and compared with already existing SRAM architectures. It is observed that the leakage power is reduced by 1/81×, 1/75× of the conventional 6T (C6T) SRAM and read decoupled 8T (RD8T) SRAM, respectively at 300mV VDD. On the contrary, RSNM, WSNM, WTP and DRM values are improved by 3×, 2×, 11.11% and 31.8% as compared to C6T SRAM, respectively. Similarly, proposed 10T has 1.48×, 25% and 9.75% better RSNM, WSNM and WTP values as compared to RD8T SRAM, respectively at 300mV VDD.

Load transfer through orthopaedic joint implants is poorly understood. The longer-term outcomes of these implants are just starting to be studied, making it imperative to monitor contact loads across the entire joint implant interface to elucidate the force transmission and distribution mechanisms exhibited by these implants in service. This study proposes and demonstrates the design, implementation, and characterization of a 3D-printed smart polymer sensor array using conductive polyaniline (PANI) structures embedded within a polymeric parent phase. The piezoresistive characteristics of PANI were studied to characterize the sensing behaviours inherent to these embedded pressure sensor arrays. PANI's stable response to a continuous load, its stability throughout loading and unloading cycles, and its repeatable and linear response to incremental loading cycles together with the accuracy of these measurements were investigated. It is demonstrated that this specially developed multi-material additive manufacturing process for polyaniline is an attractive approach for the fabrication of implant components having embedded smart-polymer sensors for the measurement and analysis of joint loads in orthopaedic implants.

Solar energy is derived from photons of light coming from the sun in a form called radiation. Solar energy finds extensive application in air and water heating, solar cooking, as well as electrical power generation, depending on the way of capturing, converting and distribution. To enable such application, it is necessary to analyze the horizontal tilt angle of horizontal surfaces – in order that when the solar energy reaches the earth surface to be completely absorbed. This paper tends to describe the availability of solar radiation for south-facing flat surfaces. The optimal monthly, seasonal, and annual tilt angles have been estimated for Pristina. The solar radiation received by the incident plane is estimated based on isotropic sky analysis models, namely Liu and Jordan model. The annual optimum tilt angle for Pristina was found to be 34.7°. The determination of annual solar energy gains is done by applying the optimal monthly, seasonal and annual tilt angles for an inclined surface compared to a horizontal surface. Monthly, seasonal and annual percentages of solar energy gains have been estimated to be 21.35%, 19.98%, and 14.43%. Losses of solar energy were estimated by 1.13 % when a surface was fixed at a seasonal optimum tilt angle, and when it was fixed at an annual optimum tilt angle, those losses were 5.7%.

A compact 2-DOF (two degrees of freedom) piezoelectric-driven platform for 3D cellular bio-assembly systems has been proposed based on “Z-shaped” flexure hinges. Multiple linear motions with high resolution both in x and y directions are achieved. The “Z-shaped” flexure hinges and the parallel-six-connecting-rods structure are utilized to obtain the lowest working stress while compared with other types of flexure hinges. In order to achieve the optimized structure, matrix-based compliance modeling (MCM) method and finite element method (FEM) are used to evaluate both the static and dynamic performances of the proposed 2-DOF piezoelectric-driven platform. Experimental results indicate that the maximum motion displacements for x stage and y stage are lx=17.65 μm and ly=15.45 μm, respectively. The step response time for x stage and y stage are tx=1.7 ms and ty =1.6 ms, respectively.

As the core of intelligent manufacturing, CPS has serious security issues, especially for the communication security of its terminal M2M. In this paper, blockchain technology is introduced to address such a security problem of communications between different types of machines in CPS. According to the principles of blockchain technology, we design a blockchain for secure M2M communications. As a communication system of M2M consists of public network areas, equipment areas and private areas, we design a sophisticated blockchain structure between the public area and private area. For validating our design, we take cotton spinning production as a case study to demonstrate our solution to M2M communication problems under the CPS framework.

That how to improve the sensitivity and the detection ability of the Large-caliber sensor is critical to satisfy the requirement of heavy vehicle wear condition monitoring. In this paper, we introduced the LC resonance principle to the design of sensor with large flow channel (7mm). The resonant exciting coil increases the impedance change of the exciting circuit caused by wear particles which magnify the current difference between the two exciting coils and improve the sensitivity of the sensor. The resonant induction coil greatly suppresses the interference signals and magnifies the weak induced electromotive force which is beneficial to enhance the detection ability. In order to boost the detectability for different materials particles, a phase controlled variable-frequency exciting system (PCVFES) was adopted to automatically switch the exciting frequency between 284kHz for ferromagnetic particles and 420KHz for non-ferromagnetic particles. For the weak signal detection, based on the essential characteristic of the signal, we apply a simpler method that modified lock-in amplifier (MLIA) rather than the conventional algorithms (Wavelet transform, EMD). Results show that using these methods the sensitivity and the detection ability of the sensor are significantly improved and the 75μm iron particles and 220μm copper particles were successfully detected which realizes the initial abnormal wear monitoring for the large flow project.

The precise prediction of air contaminant dispersion is essential to the air quality monitoring and the emergency management of the contaminant gases leakage incidents in the chemical industry park. The conventional atmospheric dispersion models can seldom give precise prediction due to inaccurate input parameters. In order to improve the prediction accuracy of dispersion model, two data assimilation methods (i.e. one is merely based on the typical particle filter while the other is a combination of particle filter and expectation-maximization algorithm) are proposed to assimilate the UAV observations into the atmospheric dispersion model. Two emission cases are taken into consideration, the difference between which is the different dimensions of state variables. To test the performances of the proposed methods, experiments corresponding to the two emission cases are designed and implemented. The results show that the particle filter can effectively estimate the model parameters and improve the accuracy of model prediction when the dimension of state variables is low. In contrast, when the dimension of state variables becomes higher, the method of particle filter combining expectation-maximization algorithm performs better in the parameter estimation accuracy and warm-up time. Therefore, the data assimilation methods are able to effectively support the air quality monitoring and emergency management in chemical industry parks.

Many of engineering’s problems are about to optimise equations, functions and process models equations which appear on common or even complex science’s cases. Most applied optimisation methods nowadays can only be used on particular cases, so the main objective of this article is to define a computational method that can optimise or even find target values for specified objective functions and variables, by just using computer effort. Chemical plants involve many differential equations and they can be optimised with more facility now. On this paper, there are shown as example, an optimisation for a chemical reactor, which is found the optimal temperature and volumetric flow rate of feed, for the given objective function being the composition of the desired product. Named Domain’s Sweep, it is an algorithm that evaluate given(s) mathematical function(s) and/or equation(s) by varying your(s) independent variable(s) through loops with a given step size and solving it after closing the degrees of freedom, and finally, with some condition statements, store all the optimum values of given or created objective functions with its respective independent variables. In another words, the user create an objective function and this method find the function’s maximum, minimum or a certain chosen target value, even if it does not have an inflection point in the given search interval of the independent variables.

The objective of this paper is to research the impact of electrical and physical parameters that characterize the complementary MOSFET transistors (NMOS and PMOS transistors) in the CMOS inverter for static mode of operation. In addition to this, the paper also aims at exploring the directives that are to be followed during the design phase of the CMOS inverters that enable designers to design the CMOS inverters with the best possible performance, depending on operation conditions. The CMOS inverter designed with the best possible features also enables the designing of the CMOS logic circuits with the best possible performance, according to the operation conditions and designers’ requirements.

The three-dimensional single fin configuration finds application in an intake geometry where the cowl-shock wave interacts with the side-wall boundary-layer. Accurate numerical simulation of such three-dimensional shock/turbulent boundary-layer interaction flows, which are characterized by the appearance of strong crossflow separation, is a challenging task. Reynolds-averaged Navier-Stokes computations using the shock-unsteadiness modified Spalart-Allmaras model is carried out at Mach of 5 at large fin angle of 23^◦. The computed results using the modified model are compared to the standard Spalart-Allmaras model and validated against the experimental data. The focus of work is to implement the modified model and to study the flow physics in detail in the complex region of swept-shock-wave turbulent boundary-layer interaction in terms of the shock structure, expansion fan, shear layer and the surface streamlines. The flow structure is correlated to the wall pressure and skin friction in detail. It is observed that the standard model predicts an initial pressure location downstream of the experiments. The modified model reduces the eddy viscosity at the shock and predicts close to the experiments. Overall, the surface pressure using modified model is predicted accurately at all the locations. The skin friction is under predicted by both the models in the reattachment region and is attributed to the poor performance of turbulence models due to flow laminarization.

Cellular response to mechanical stimuli is an integral part of cell homeostasis. The interaction of the extracellular matrix with the mechanical stress plays an important role in cytoskeleton organisation and cell alignment. Insights from the response can be utilised to develop cell culture methods that achieve predefined cell patterns, which are critical for tissue remodelling and cell therapy. We report the working principle, design, simulation and characterisation of a novel electromagnetic cell stretching platform based on the double-sided axial stretching approach. The device is capable of introducing a cyclic and static strain pattern on a cell culture. The platform was tested with fibroblasts. The experimental results are consistent with the previously reported cytoskeleton reorganisation and cell reorientation induced by strain. The orientation of the cells is highly influenced by external mechanical cues. Cells reorganise their cytoskeleton to avoid external strain and to maintain intact extracellular matrix arrangements.

The Wind Energy Conversion System (WECS) plays an inevitable role across the world. In particular, the attention for Permanent Magnet Synchronous Generators (PMSGs) connected with wind farm is popular. This paper deals with the literature review that describes the recent advances, progresses and innovatory trends on PMSGs for WECS. Comparison between geared and direct-driven conversion systems and the classification of electrical machines used in WECS are discussed. A detailed analysis on the design aspects considering various topologies of PMSGs are encompassed in the literature. The PMSG design and optimization problems are solved by field computation techniques and optimized by using Soft Computing (SC) techniques .The three-dimensional, finite element software platform for the analysis and design of PMSGs is discussed. This paper also deals with the interdisciplinary modeling, analysis, and optimization of PMSG using Finite Element Analysis (FEM) and SC techniques. Finally, PMSGs are reviewed and compared for further exploration.

This paper presents a methodology for determining the sensitivity of the main air flow directions in ventilation subnetworks to changes of aerodynamic resistance and of air density in mine workings. Formulae for determination of the sensitivity of the main subnetwork air flows by establishing the degree of dependency of the air volume stream in a given working on the variations in resistance or air density of other workings of the network have been developed. They have been implemented in the VentGraph mine ventilation network simulator. This software, widely used in Polish collieries provides an extended possibility to predict the process of ventilation, air distribution and, in the case of underground fire, also the spread of combustion gasses. The new method facilitates assessment by mine ventilation services of the stability of ventilation systems in exploitation areas and determine of the sensitivity of the main subnetwork air flow directions to changes of aerodynamic resistance and air density. Recently in some Polish collieries new longwalls are developed in seams located deeper then the bottom of the intake shaft. Such solution is called “exploitation below the level of access” or “sublevel”. The new approach may be applied to such developments to assess the potential of changes of direction and air flow rates. In addition, interpretation of the developed sensitivity indicator is presented. While analyzing air distributions for sublevel exploitation, application of current numerical models for calculations of the distribution results in tangible benefits, such as the evaluation of the safety or risk levels for such exploitation. Application of the VentGraph computer program, and particularly the module POŻAR (fire) with the newly developed options, enables an additional approach to the sensitivity indicator in evaluating air flow safety levels for the risks present during exploitation below the level of the intake shaft. The analyses performed and examples presented enabled useful conclusions in mining practice to be drawn.

Though Cyber Physical Systems (CPS) become very popular in last the decade, dependability of CPS is still a critical issue and related survey is rare. We try to spell out the jigsaw of technologies and figure out the technical trends of dependable self-managing CPS. This survey first recalls the motivation and the similar concepts. By analyzing four generic architectures, we summarize the common characteristics and related assurance technologies, and propose a more generic environment-in-loop processing flow of CPS and a formal interaction flow between physical space and cyber space. Further, the similarity between correctness and dependability is formally analyzed and the new five research questions of dependable self-managing CPS are presented. Then we review the critical technologies and related correctness verification & validation (V&V) methods, the architectures for dependable self-managing CPS. Further, the detail dependability management and V&V technologies are surveyed, which covers the areas of running-time fault management methods and whole life cycle V&V technologies, maintenance and available tool sets. For holistic CPS development, Modeling techniques and MDE (model driven engineering) based V&V methods are analyzed in detail. Then we complete the jigsaw of technologies and figure out the missing part. Further, we propose the technical challenges and the further direction. To our best knowledge, this is the first comprehensive survey on dependable self-managing CPS development and evaluation.

A rheological modifier was used to prepare solutions with viscosities of 1, 4, 6 and 8 cp, which exhibited Newtonian behavior. These solutions were later used to prepare suspensions of monosize quartz (53, 45 and 38 microns) at 60 % in solids. Monosize grinding tests in a laboratory ball mill were performed to determine breakage parameters, with different ball diameters. A model was developed to determine the specific rate of breakage in terms of the system rheology. With this model, it was demonstrated that an increase in suspending fluid viscosity until 6 cp, leads to an increased fracture rate and consequently affects the grinding degree. The above test is considered as an alternative for improving and optimizing such operations with excellent quality products with low energy and steel consumption, thereby minimizing environmental impact.

Supply chain management requires regular updates of the location of assets, which can be enabled by low power wide area networks, such as Sigfox. While it is useful to localize a device simply by its communication signals, this is very difficult to do with Sigfox because of wide area and ultra narrowband nature. On the other hand, installing a satellite localization element on the device greatly increases its power consumption. We investigated using information about nearby Wi-Fi access points as a way to localize the asset over the Sigfox network, so without connecting to those Wi-Fi networks. This paper reports the location error that can be achieved by this type of outdoor localization. By using a combination of two databases, we could localize the device on all 36 test locations with a median location error of 39 m. This shows that the localization accuracy of this method is promising enough to warrant further study, most specifically the minimal power consumption.

Flow sensing in hostile environment is of increasing interest for applications in automotive, aerospace, and chemical and resource industries. Compared to their counterparts, thermal flow sensors are attractive candidates due to the ease of fabrication, lack of moving parts and higher sensitivity. Recently, a number of thermal flow sensor prototypes have been reported in the literature demonstrating the measurement of fluid flows under hostile conditions. This paper summarizes the concept of thermal flow sensing, operational modes and transduction mechanisms. Then, the choice of materials and their corresponding properties are presented in details. The paper also reports recent progress in the development of thermal flow sensors for harsh environment. In addition, the issues and considerations in packaging are reviewed. Finally, we conclude the review with the future prospects.

In this paper, an improved system to efficiently utilize the low-temperature waste heat (WHUS) from the flue gas of coal-fired power plants is proposed based on heat cascade. The essence of the proposed system is that the waste heat of exhausted flue gas is not only used to preheat air for assisting coal combustion as usual but also to heat up feedwater and the low-pressure steam extraction. Preheated by both the exhaust flue gas in the boiler island and the low-pressure steam extraction in the turbine island, thereby part of the flue gas heat in the air preheater can be saved and introduced to heat the feedwater and the high-temperature condensed water. Consequently, part of the high-pressure steam is saved for further expansion in the steam turbine, which obtains additional net power output. Based on the design data of a typical 1000 MW ultra-supercritical coal-fired power plant in China, in-depth analysis of the energy-saving characteristics of the optimized WHUS and the conventional WHUS is conducted. When the optimized WHUS is adopted in a typical 1000 MW unit, net power output increases by 19.51 MW, exergy efficiency improves to 45.46%, and net annual revenue reaches 4.741 million USD. In terms of the conventional WHUS, these aforementioned performance parameters are only 5.83 MW, 44.80% and 1.244 million USD, respectively. The research of this paper can provide a feasible energy-saving option for coal-fired power plants.

This article addresses reinsurance decision making process, which involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. In contrast to existing literature on pure proportional reinsurance or stop-loss reinsurance, this article focuses on the combination into Proportional-Stop-loss reinsurance design which better addresses interest of both parties. In terms of methodology, the significant contribution of the study is to incorporate Multiple Attribute Decision Making (MADM) into modelling the reinsurance selection. The Multi-Objective Decision Making (MODM) model is applied in designing reinsurance alternatives. Then MADM is applied to aid insurance companies in choosing the most appropriate reinsurance contract. To illustrate the feasibility of incorporating intelligent decision supporting system in reinsurance market, the study includes a numerical case study using simulation software @Risk in modeling insurance claims, and programming in MATLAB to realize MADM. Managerial implications could be drawn from the case study results. More specifically, when choosing the most appropriate reinsurance, insurance companies should base their decision on multiple measurements instead of single-criteria decision making models for their decisions to be more robust.

In this work, the Pumped Storage Unit (PSU) is proposed to be integrated with wind-thermal generation system owned by a company whose aim is to maximize its profit through optimal self-scheduling of its units by finding the best bidding strategy in day-ahead energy market. The mathematical formulation of the scenario based unit-commitment and coordinated trading problem is formulated as a stochastic mixed integer linear program. The formulation takes into account several uncertain parameters; such as the wind power generation, energy market prices, and imbalances up/down prices. The expected total profit obtained from energy trading with and without coordinating pumped storage system (PSS) with thermal-wind generation system were compared, and a significant improvement in profit resulted from coordination was observed. Furthermore, coordination between PSS and wind-thermal generation improve the conditional value at risk (CVaR) which monitors the biding risk level.

In thermal power plants equipped with air-cooled condensers, axial cooling fans operate under the influence of ambient flow fields. Under inlet cross-flow conditions, the resultant asymmetric flow field is known to introduce additional harmonic forces to the fan blades. This effect has previously been studied only numerically or using blade mounted strain gauges. For this study, Laser Scanning Vibrometry was used to assess fan blade vibration under inlet cross-flow conditions in an adapted fan test rig inside a wind tunnel test section. Two co-rotating laser beams scanned a low pressure axial fan, resulting in spectral, phase resolved surface vibration patterns of the fan blades. Two distinct operating points were examined, with and without inlet cross-flow influence. While almost identical fan vibration patterns were found for both reference operating points, overall blade vibration increased by 100% at low fan flow rate due to cross-flow, and by 20% at high fan flow rate. While numerically predicted natural frequency modes could be confirmed from experimental data as minor peaks in the vibration amplitude spectrum, they were not excited significantly by cross-flow. Instead, primarily higher rotation rate harmonics were amplified, i.a. a synchronous blade tip flapping was strongly excited at the blade pass frequency.

An acrobot is a planar robot with a passive actuator in its first joint. The control problem of the acrobot tries to make it rise from the rest position to the inverted pendulum position. This control problem can be divided in the swing-up problem, when the robot has to rise itself through swinging up as a human acrobat does, and the balancing problem, when the robot has to maintain itself on the inverted pendulum position. We have developed three controllers for the swing-up problem applied to two types of motors: small and big. For small motors, we used the SARSA controller and the PD with a trajectory generator. For big motors, we propose a new controller to control the acrobot, a PWM controller. All controllers except SARSA are tuned using a Genetic Algorithm.

One of the major steps toward the industrialization of microbial product(s) is to optimize the cultivation conditions at the large scale bioreactor and successfully control the microbial behavior within large scale production environment. Statistical Design of Experiment was proven to optimize a vast number of microbial processes to achieve robustness and explore possible interactions among the variables. In this research, Taguchi Orthogonal Array was applied to optimize the cultivation condition of a newly isolated Prodigiosin-producing marine bacterial strain, Serratia AM8887, at bioreactor level. Two steps fermentation process was applied; as the productivity was scaled up from shake flask level to a bench top bioreactor (5L) and subsequently to an in-situ sterilization bioreactor system (20L) leading to a yield of 7g/L compared to 100mg/L prior to optimization confirming that; applying Taguchi experimental design is a reliable and good positive option for the optimization of biotechnological processes.. The produced pigment was purified and the chemical structure was revealed by means of Spectrophotometric, Maas Spectrum (MS), Fourier transform infrared (FT-IR), and proton nuclear magnetic resonance (1H-NMR) spectroscopy analysis. The biological activity including antibacterial, antioxidants and cytotoxicity to cancer cells line of the pigment were explored. The pigment showed very characteristic features that could helpful in food, pharmaceuticals and/or textile industries.

This paper outlines a tool developed with the purpose of creating a simple configurable emulated network environment that can be used in cyber defence exercises. Research has been conducted into the various related subject areas: cyber defence exercises, network threats, network emulation, network traffic replay, network topologies, and common network services. From this research a requirements specification was produced to encapsulate the features required to create this tool. A network, containing many of the aspects researched, was designed and implemented using Netkit-NG to act as a blueprint for the tool and to further knowledge in the construction of an emulated network. Following this the tool was developed and tested to ensure requirements were met.

: The cyber-physical gap (CPG) is the difference between the 'real' state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is an inevitable issue in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach for capturing, explaining, and mitigating the CPG, on top of and in sync with the conventional system model, and as an inherent systems engineering activity. This approach enhances the systems engineer’s ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions, actions, and hazardous implications. CPGAME is a generic, conceptual approach, specified and demonstrated with Object Process Methodology (OPM). OPM is a holistic conceptual modeling paradigm for multidisciplinary, complex, dynamic systems, which is also ISO-19450. We analyze the 1979 Three Miles Island 2 nuclear accident as a prime example of the disastrous consequences of unmitigated CPGs in complex systems.

This paper presents an improved indoor localization system based on RF and ultrasonic signal which we named SNSH system. This system composes of a transmitter mounted in a mobile target, and a series of receiver nodes which are managed by a coordinator. By measuring Time Delay of Arrival (TDoA) of RF and ultrasonic signal from the transmitter, distance from target to receiver node is calculated and sent to the coordinator through CAN network, and all the information are gathered in PC to estimate 3D position of the target. Sine wave detector and dynamic threshold filter are applied to provide excellent accuracy of range measurement from TDoA result, and multilateration algorithms is realized to optimize coordinate determination accuracy. Specifically, Linear Least Square and Non-linear Least Square techniques are implemented to contrast their performances in target coordinate estimation. RF signal encoding/decoding time, time delay in CAN network and math calculating are carefully considered to ensure optimal system performance and get ready for field application. Experiments show that sine wave detector algorithm has greatly improved range measurement accuracy, with mean error at 2.2mm and maximum error at 6.7 mm, for distance below 5m. In addition, 3D position accuracy is greatly enhanced by multilateration methods, with mean error in position stay under 15mm, and 90% confident error values at 23mm for LLS, 20mm for NLS. Overall system update period has been verified in real system operation, with maximum rate at 25ms, and compared with other existing researches.

In the current study, the failure behavior of retrofitted steel structures was studied experimentally and theoretically with steel/CFRP double strap joints (DSJs) under quasi-static tensile loading. A series of DSJs with different bonding lengths are also considered and examined to experimentally assess the effective bond length. To predict the failure load values of the tested specimens, a new stress-based criterion, namely the point stress (PS) criterion is proposed. Although some theoretical predictive modelling for the strength between steel/CFRP joints under various loading conditions has been presented, in this work by using the new proposed approach, one can calculate rapidly and conveniently the failure loads of the steel/CFRP specimens. Furthermore, to assess the validity of the new proposed criterion, further experimental data on steel/CFRP DSJs available in the open literature are predicted using the PS criterion. Finally, it was found that a good agreement exists between the experimental results and the theoretical predictions based on the PS criterion.

This paper introduces a sliding mode control (SMC) based equivalent control method to a novel high output gain Cuk converter. An additional inductor and capacitor improves the efficiency and output gain of the classical Cuk converter. Classical PI controllers are widely used in DC-DC converters. However, it is a very challenging task to design a single PI controller operating in different load and disturbances. SMC based equivalent control method which achieves a robust operation in a wide operation range is also proposed. Switching frequency is kept constant in appropriate interval in different loading and disturbance conditions by implementing a dynamic hysteresis control method. Numerical simulations conducted on Matlab/Simulink confirm the accuracy of analytical analysis of high output gain modified Cuk converter. In addition, proposed equivalent control method is validated in different perturbations to demonstrate the robust operation in wide operation range.

Penetration of grid connected inverters (GCI) has arisen in power systems due to increasing integration of renewable sources. However, restrictive grid codes require that renewable sources connected to the grid with power electronic systems must be properly connected and appropriate currents must be injected to support stability of the grid under grid faults. Simultaneous injection of symmetrical positive and negative sequence currents is mandatory to support stabilization of grid at the instant of grid faults. Conventional synchronously rotating frame dq current controllers are insufficient under grid faults due to low bandwidth of PI controllers. This paper proposes a new grid current control strategy for grid connected voltage source inverters under unbalanced grid voltage conditions. A proportional current controller with a first order low pass filter disturbance observer (DOb) is proposed which establishes positive sequence power requirements and independently control negative sequence current components under unbalanced voltage conditions. The method does not need any parameter, since it estimates nonlinear terms with low pass filter DOb. Simulations are implemented in Matlab/Simulink platform demonstrating the effectiveness of proposed method.

Repair mortar is commonly used to rehabilitate reinforced concrete structures or components that exhibit a relatively high level of distresses. Yet, this repair mortar can be contaminated by salt from its service environment. This work employs a two-dimensional finite element model to investigate the transport behavior of ionic species in salt-contaminated and water-saturated repair mortar under an externally applied electric field. The model was experimentally validated and then utilized to evaluate the effectiveness of electrochemical chloride extraction (ECE) with or without electrical injection of corrosion inhibitor (EICI). In the case study, both the ECE alone and the ECE+EICI treatment was found effective in decontaminating the zone in front of the steel rebar. In both techniques, the magnitude of current density has a significant effect on removing chloride out of the mortar and increasing the pH of the pore solution near the rebar, whereas the treatment time any not have a significant effect under some scenarios. The injection of the organic corrosion inhibitor significantly slowed down the removal of chloride. Changes in the ionic distribution in the mortar were generally beneficial in reducing the corrosion risk of the steel rebar and thus extending the service life of the repair mortar.

Three dimension (3D) Multi-input-multi-output (MIMO) scheme, which exploits another dimension of the spatial resource, is one of the enabling technologies for the next generation mobile communication. As the elevation angle in 3D-MIMO channel model might varies against the height of the base station transmit antenna, it has to be taken into account carefully. In this paper, the impact of antenna height on the channel characteristics of 3D MIMO channel is investigated by using the intelligent ray launching algorithm (IRLA). Three typical street scenarios, i.e., the straight street, the fork road and the cross road, are selected as benchmarks. On the basis of simulations, joint and marginal probability density functions (PDFs) of both the elevation angle of departure (EAoD) and the elevation angle of arrival (EAoA) are obtained. The elevation angle spread (AS) and the delay spread (DS) under various antenna heights are also discussed. Simulation results indicate that the PDFs of EAoD and EAoA vary characteristics under different street scenarios. Moreover, the minimum value of the DS can be achieved when the antenna height is half of the building height.

We present observations from evaluation of internal environmental quality of industrial halls with priority on daylighting in combination with the integral lighting. The physical parameters related to indoor lighting in large industrial halls in winter and summer periods were analyzed using in situ measurements and computational methods. These are part of a comprehensive research on indoor environmental quality of industrial halls with the aims of saving energy and providing a comfortable environment for the workers while improving the productivity. The results showed that the procedures used for evaluation of residential or office buildings may not be used for industrial buildings. We also observed that the criteria of occupants’ comforts for indoor industrial buildings may differ from those of other kinds of buildings. Based on these results, an adequate attention is required for designing the industrial buildings. For this reason, appropriate evaluation methods and criteria should be created. We found the measured values of daylight factor very close to the skylight component of the total illumination. The skylight component was observed on average 30% that of the measured daylight factor values. Although the daylight is not emphasized when designing the industrial buildings and its contribution is small, but it is very important for the workers psychology and physiology. The workers must feel a connection with the exterior environment; otherwise, their productivity decreases.

Sailing sports are experiencing a period of radical innovations. Traditional displacing monohulls have always been the reference for yachting in the past, but the continuous quest for performances has generated many variations and many convergences with surprising results. On the aerodynamic side conventional soft sails have been sometime replaced by rigid wings, but the biggest innovation has been the use of traction kites as a propulsion device. On the hydrodynamic side we have seen the rapid growth of hydrofoils, an old concept that is having a rebirth. Probably the most remarkable expression of innovation and integration between concepts having different roots is the hydrofoil kite-board, point of encounter of the traditional wave surfing, the traction kite innovation and the hydrofoil technology. Hydrofoil kite-board can reach speeds up to 3 times the wind speed, are at least one order of magnitude cheaper than any boat with comparable performances, easy to manage and races are spectacular. Hydrofoil are object of investigation trying to further improve performances as well as to increase the stability and the “sailability". In the following we will present a concept that extends the range of efficiency of the foil through a completely passive morphing of the wing.

In this paper, we present the design of a wearable photoplethysmography (PPG) system, R-band for acquiring the PPG signals. PPG signals are influenced by the respiration or breathing process and hence can be used for estimation of respiration rate. R-Band detects the PPG signal that is routed to a Bluetooth low energy device such as a nearbyplaced smartphone via microprocessor. Further, we developed an algorithm based on Extreme Learning Machine (ELM) regression for the estimation of respiration rate. We proposed spectral kurtosis features that are fused with the state-ofthe-art respiratory-induced amplitude, intensity and frequency variations-based features for the estimation of respiration rate (in units of breaths per minute). In contrast to the neural network (NN), ELM does not require tuning of hidden layer parameter and thus drastically reduces the computational cost as compared to NN trained by the standard backpropagation algorithm. We evaluated the proposed algorithm on Capnobase data available in the public domain.

DC residential distribution system (RDS) consisted by DC living home will be a significant integral part in the future green transmission. Meanwhile, the increasing number of distributed resources and intelligent devices will change the power flow between main grid and demand sides. The utilization of distributed generations (DGs) requires an economic operation, stability, environmentally friendly in the whole DC system. This paper not only presents an optimization schedule and transactive energy (TE) approach through centralized energy management system (CEMS), but a control approach to implement and ensure DG output voltages to various DC buses in DC RDS. Based on data collection, prediction and a certain objection, the expert system in CEMS can work out the optimization schedule, after this, the voltage droop control for steady voltage is aligned with the command of unit power schedule. In this work, a DC RDS is as a case study to demonstrate the process, the RDS is associated with unit economic models, cost minimization objective is proposed to achieve based on real-time electrical price. The results show that the proposed framework and methods will help the targeted DC residential system to reduce the total cost and reach stability and efficiency.

This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved.

This thesis completion works it out to deepen into diverse modeling techniques for Point Absorbers. A combined frequency-time domain model is conceived, designed and developed in Matlab with FoRtran as a base., leading to obtain physical variables of primary importance, namely position, velocity and power to Energy net balance relationships of absorption. Integration of different degrees of freedom with heave as main executable leads in turn to a single buoy motion focus. Acquisition of the needed hydrodynamic coefficients is provided though application of NEMOH & BEMIO solvers due to the Boundary Element Methodology. Initially, this Wave-to-motion model is validated through comparison with previous experimental results for a floating cone cylinder shape (Buldra-FO3). A single, generic, vertical floating cylinder is contemplated then, that responds to the action of the passing regular waves excitation. Later, two equally sized vertical floating cylinders aligned with the incident wave direction are modeled for a variable distance between the bodies. For both unidirectional regular and irregular waves as an input in deep water, we approximate the convolutive radiation force function term through the Prony method. By changing the spatial disposition of the axisymmetric buoys, using for instance triangular or rectangular shaped arrays of three and four bodies respectively, the study delves into motion characteristics for regular waves. The results highlight efficient layouts for maximizing the energy production whilst providing important insights into their performance, revealing displacement amplification- and capture width-ratios, while deriving in possible interpretations of scenarios related to the the known park effect. These terms are encompassed by the novelty of a new conceptual Post-Processing methodology in the field, which leads to obtain an optimal distance for the separated bodies with effective energy absorption in a regular wave regime. In conclusion, this computational excursion envisions and proposes potentials fields of study, which will surely enhance new connections and link this renewable energy form.

In the present work, a portable device system applied in the detection and classification of different metallic ions was proposed and developed, aiming at its application in the monitoring of hydrological systems like rivers, lakes and groundwater. Considering the system features, a portable colorimetric system was developed by using a multispectral optoelectronic sensor. All the technology of quantification and classification of metallic ions using Optoelectronic Multispectral sensors was fully integrated in the embedded hardware FPGA technology and software based on virtual Instrumentation (NI LabView ®). The system was used as a colorimeter by using the chromogen reagent of 1-(2-pyridylazo)-2-naphthol (PAN) as an indicator and the results obtained together with the signal processing and pattern analysis using the method of the linear discriminant analysis, allowed to obtain excellent results in detection and classification of Pb(II), Cd(II), Zn(II), Cu(II), Fe(III) and Ni(II) ions, with almost the same level of performance in relation to those obtained from the UV-VIS spectrometers of high spectral resolution.

Manufacturing organizations shall recognize sustainability as a business occasion to capitalize on, rather than an undesirable pressing situation. Still, empirical evidence shows that this opportunity is hard to capture and communicate in global strategic decisions, through planning by tactical management, to daily operational activities. This paper systematically reviews the modeling challenges at the crossroad of value and sustainability decisions making, spotlighting methods and tools proposed in literature to link sustainability to customer value creation at strategic, tactical and operational level. While statistical results show that the topic of sustainability and value modeling is trending in literature, findings from content analysis reveal that recent attempts to promote a value-based view in the sustainability discussion remain at a strategic level, with most of the proposed indicators being suited for managerial decision-making. The lack of support at operational level points to the opportunity of cross-pollinating sustainability research with value-centered methodologies originating from the aerospace sector. The Value Driven Design framework is proposed as main hub from which to derive models supporting engineers and technology developers in the identification of win-win-win situations, where sustainable improvements are aligned with business advantages.

First, a brief overview is provided on humanoid robots, and also models for the dynamic behavior are discussed. As base for these models these two methods Denavit-Hartenberg and Newton-Euler are used. Main aim of this work is to investigate the stability of a biped robot developed from IHRT. There is currently the low base of robot - consisting of feet, legs, hips and upper part of robots body. This structure currently has ten degrees of freedom.

An empirical model is presented for estimating discharge on the Ubombo Sugar Limited (USL) main gravity canal to enhance bulk water management and water use efficiency. It uses stage readings obtained from measuring flumes A, B, C, and UPS to simulate discharge. The rationale for the development of the mathematical flow simulation model is the significance of the UPS flume as it measures readings that influence the daily operations of the farm, and the experiences with the ultrasonic flow meter installed in the flume. The model also provides a first for the simulation of accurate flow rates for flumes A, B, and C. A spreadsheet program that enables express prediction of canal flow rates was developed to influence timely implementation of these water management decisions. Calibrations demonstrated that the model is capable of predicting discharge at high accuracy (p>95%), and can be reliably used as a decision support tool for bulk water management. It can also be expanded to include other water measuring structures along Canal 1 and Canal 2, as well as the development of a stand-alone water management application for desktop and mobile computers.

A novel fiber optic sensing technology for high frequency dynamics detection is proposed in this paper, specifically tailored for structural health monitoring applications based on strain wave analysis, including both passive impact identification and active Lamb wave monitoring. The sensing solution relies on a fiber optic-based interferometric architecture associated to an innovative coherent detection scheme, which retrieves in a completely passive way the high-frequency phase information of the received optical signal. The optical fiber can be arranged into different configurations in order to meet the requirement of the specific application, the sensor sensitivity being maximized while still ensuring a limited gauge length if a local measure is required. For the active Lamb wave monitoring, this results in a sensing fiber arranged in multiple loops glued on an aluminum thin panel in order to increase the phase signal relative only to the sensing points of interest. Instead, for passive impact identification, the sensitivity is simply increased by exploiting a longer gauge length glued to the structure. The fiber optic coherent (FOC) sensor detects the strain waves emitted by a piezoelectric transducer placed on the aluminum panel or generated by an impulse hammer, respectively. The FOC sensor measurements have been compared with both a numerical model based on Finite Elements and traditional piezoelectric sensors, confirming a very good agreement between experimental and simulated results for both the active and passive impact monitoring scenarios.

The purpose of this work is to optimize angular extrusion for sever plastic deformation of tubular specimens. A finite element model (FEM) was built in Deform-3D^® for three extrusion dies and analyzed. The dies were ECAP (135°), TCAP with external groove of 90° (denoted as TCAP-e) and TCAP with internal groove of 90° (denoted as TCAP-i). The analysis for process parameters (such as coefficient of friction-μ, die angles-ѱ and φ, temperature - T, and radius ratio-R) showed that TCAP-i was the optimal die in processing Al6063 tubes based on strain and load distribution of the model. The TCAP-i die model was further optimized for different parameters namely die angles, coefficient of friction, deformation ratio and temperature. The results showed that at constant process temperature of 25 °C, the optimal TCAP-i has the following parameters: φ₂=80⁰, Ѱ₁=30⁰, Ѱ₂=80⁰, Ѱ₃=30⁰, μ =0.4 and R =1.5.

RO membrane fouling is one of the main challenges that membrane manufactures, the scientific community and industry professionals have to deal with. The consequences of this inevitable phenomenon have a negative effect on the performance of the desalination system. Predicting fouling in RO systems is key to evaluating the long-term operating conditions and costs. Much research has been done on fouling indices, methods, techniques and prediction models to estimate the influence of fouling on the performance of RO systems. This paper offers a critical review evaluating the state of industry knowledge in the development of fouling indices and models in membrane systems for desalination in terms of use and applicability. Despite major efforts in this field, there are gaps in terms of effective methods and models for the estimation of fouling in full-scale RO desalination plants. In existing models applied to full-scale RO desalination plants, neither the spacer geometry of membranes nor the efficiency and frequency of chemical cleanings - which play an important role in the performance of this process - are considered.

The greenhouse gases and air pollution generated by extensive energy use have exacerbated climate change. An electric-bus (e-bus) transportation system favors reducing pollution and carbon emissions. This study analyzed the minimization of construction costs for an all battery-swapping public e-bus transportation system. A simulation was conducted according to existing timetables and routes. Daytime charging was incorporated during the hours of operation; the two parameters of the daytime charging scheme were the residual battery capacity and battery-charging energy during various intervals of daytime peak electricity hours. The parameters were optimized using three algorithms: particle swarm optimization (PSO), a genetic algorithm (GA), and a PSO–GA. This study observed the effects of optimization on cost changes (e.g., number of e-buses, on-board battery capacity, number of extra batteries, charging facilities, and energy consumption) and compared the plug-in and battery-swapping e-bus systems. The results revealed that daytime charging can reduce the construction costs of both systems. In contrast to the other two algorithms, the PSO–GA yielded the most favorable optimization results for the charging scheme. Finally, according to the cases investigated and the parameters of this study, the construction cost of the plug-in e-bus system was lower than that of the battery-swapping e-bus system.

Object segmentation on remotely-sensed images: aerial (or very high resolution, VHS) images and satellite (or high resolution, HR) images, has been applied to many application domains, especially road extraction in which the segmented objects are served as a mandatory layer in geospatial databases. Several attempts in applying deep convolutional neural network (DCNN) to extract roads from remote sensing images have been made; however, the accuracy is still limited. In this paper, we present an enhanced DCNN framework specifically tailored for road extraction on remote sensing images by applying landscape metrics (LMs) and conditional random fields (CRFs). To improve DCNN, a modern activation function, called exponential linear unit (ELU), is employed in our network resulting in a higher number of and yet more accurate extracted roads. To further reduce falsely classified road objects, a solution based on an adoption of LMs is proposed. Finally, to sharpen the extracted roads, a CRF method is added to our framework. The experiments were conducted on Massachusetts road aerial imagery as well as THEOS satellite imagery data sets. The results showed that our proposed framework outperformed Segnet, the state-of-the-art object segmentation technique on any kinds of remote sensing imagery, in most of the cases in terms of precision, recall, and F1.

Multidisciplinary Design Optimization (MDO) is the most active field in the design of current complex system engineering, which is possessed with such two difficulties as subsystem information exchange and analytical and computational complexity of systems. Therefore, an improved collaborative optimization algorithm based on ANN (artificial neural network) response surface was proposed dependent on the consistency constraint algorithm and concurrent subspace algorithm. As an optimization method with secondary structure, it satisfied only local constraints in discipline layer, but provided a coordinated mechanism for interdisciplinary conflict in system layer. Finally, it was applied in the multidisciplinary design optimization of autonomous underwater vehicle (AUV). As shown from the result, the MDO convergence stability and reliability of low resistance, low noise and high maneuvering performance of the AUV shape can be ensured by the improved collaborative optimization algorithm, thus verifying the effectiveness of the algorithm.

The deformation of underground gateroads tends to be asymmetric and complex. Traditional instrumentation fails to accurately and conveniently monitor the full cross-sectional deformation of underground gateroads. Here, a full cross-sectional laser scanner was developed together with a visualization software package. The developed system used polar coordinate measuring method and the full cross-sectional measurement was realized by 360° rotation of laser sensor driven by an electrical motor. Later on, the potential impact of gateroad wall flatness, roughness and geometrical profile as well as coal dust environment on the performance of the developed laser scanner were evaluated. The studies show that a high-level flatness is favorable in application of the developed full cross-sectional deformation monitoring system. For a smooth surface of gateroad, the sensor cannot receive reflected light when the incidence angle of laser beam is large, causing data loss. Conversely, the roughness surface shows its priority as the diffuse reflection light can be received by the sensor. With regards to the coal dust in measurement environment, the fine particles of floating coal dust in the air can lead to the loss of measurement data to some certain due to scattering of laser beam.

This paper shows a method for pipeline leak detection using a transient-based method with MATLAB® functions. The simulation of a pipeline systems in the time domain are very complex. In the case of the dissipative model, transfer functions are hyperbolic Bessel functions. Simulating a pipeline system in the frequency domain using a dissipative model we could find an approximate transfer function with equal frequency domain response to in order get the pipeline system's time domain response. The method described in this paper can be used to detect, by comparison, to detect a leak in a pipeline system model.

Smart sensors based on graphene field effect transistor and biologically receptors are regarded as a promising nanomaterial that could be the basis for future generations of selective real-time monitoring of target analytes and smaller electronics. So the purpose of this paper is to provide details a real-time and selective explosive sensor based on GFETs and PDA-based lipid membranes coupled with biologically inspired TNT peptide receptors. Following an introduction, this paper describes the way of fabrication of the GFETs device by investigation methods for transferring graphene sheet from Cu substrates to target substrates, which is functionalized by the TNT peptide receptors, in order to offer a system which has the capability of answering the presence of related target molecules. Field effet transistor was fabricated using graphene as a channel and monitored by the source-drain current and back-gate voltage curves in the measurement. The transport property changed compared to that of the FET made by intrinsic graphene, that is, the Dirac point position moved from positive Vg to negative Vg, indicating the transition of graphene from p-type to n-type after annealing in TNT, and GFET sensor show good sensitivity and selectivity response.

Τhe concept of remote insect surveillance at large spatial scales for a number of serious insect pests of agricultural and medical importance is introduced in a series of our papers. We augment typical, low-cost plastic traps for many insect pests with the necessary optoelectronic sensors to guard the entrance of the trap in order to detect, time-stamp, GPS tag, and –in relevant cases- identify the species of the incoming insect from their wingbeat. For every important crop pest there are monitoring protocols to be followed in order to decide when to initiate a treatment procedure before a serious infestation occurs. Monitoring protocols are mainly based on specifically designed insect traps. Traditional insect monitoring suffers in that the scope of such monitoring: is curtailed by its cost, requires intensive labor, is time consuming, an expert is often needed for sufficient accuracy and can sometimes raise safety issues for humans. These disadvantages reduce the extent to which manual insect monitoring is applied and therefore its accuracy, which finally results in significant crop loss due to damage caused by pests. With the term ‘surveillance’ we intend to push the monitoring idea to unprecedented levels of information extraction regarding the presence, time-stamping detection events, species identification and population density of targeted insect pests. Insect counts as well as environmental parameters that correlate with insect’s population development are wirelessly transmitted to the central monitoring agency in real time, are visualized and streamed to statistical methods to assist enforcement of security control to insect pests. In this work we emphasize on how the traps can be self-organized in networks that collectively report data at local, regional, country, continental, and global scales using the emerging technology of the Internet of Things (IoT). This research is necessarily interdisciplinary and falls at the intersection of entomology, optoelectronic engineering, data-science and crop science and encompasses the design and implementation of low-cost, low-power technology to help reduce the extent of quantitative and qualitative crop losses by many the most significant agricultural pests. We argue that smart traps communicating through IoT to report in real-time the level of the pest population from the field straight to a human controlled agency can, in the very near future, have a profound impact on the decision making process in crop protection and will be disruptive of existing manual practices. In the present study, three cases are investigated : monitoring Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) using a) Picusan and b) Lindgren trap, and c) monitoring various stored grain beetle pests using the pitfall trap.

The aim of this research was to investigate the mass, substances and energy flow through two-stroke low speed Diesel engines. For this reason, a zero-dimensional model of the combustion in the engine was developed with a calculated amount and composition of exhaust gases. Due to the large amount of oxygen in the exhaust gases, a ratio of real air consumption and stoichiometric amount of air required for combustion of injected fuel was set. The calculated ratio showed that the engine consumes four times more air than needed for combustion in AFR_stoich. In this work it is called the Air Consumption Factor or Ratio and has not been mentioned in scientific literature before. Air Consumption Ratio is defined as a factor of dry or humid air. To be more comprehensive, a modified diagram of composition of the flow in and out of a two-stroke fuel injection engine and the cylinder was drawn.

This paper deals with a generic methodology to evaluate the magnetic parameters of contactless power transfer systems. Neumann's integral has been used to create a matrix method that can model the magnetics of single coils (circle, square, rectangle). The principle of superposition has been utilised to extend the theory to multi-coil geometries such as double circular, double rectangle and double rectangle quadrature assuming linearity of magnetics. Numerical and experimental validation has been performed to validate the analytical models developed. A rigorous application of the analysis has been carried out to study misalignment and hence the efficacy of various geometries to misalignment tolerance. Comparison of single-coil and multi-coil shapes considering coupling variation with misalignment, power transferred and maximum efficiency is carried out.

The creep behaviors of TA2 and R60702 at low and intermediate temperature were presented and discussed in this paper. Experimental results indicated that an apparent threshold stress exhibited in the creep deformation of R60702. Meanwhile, the primary creep phase was found as the main pattern in the room temperature creep behavior of TA2. Compared with exponential law, the power law has been proved to be a proper constitutive model in the description of primary creep phase. It also showed that θ projection method had its significant advantage in the evaluation of accelerated creep stage. Thus, a composite model which combined power law with θ projection method was applied in the creep curves evaluation at low and intermediate temperature. Based on the multiaxial creep deformation results, the model was modified and discussed. A linear relationship existed between composite model parameters and applied load. Finally, the creep life could be accurately predicted and the composite model method is suitable for application in low and intermediate temperature creep life analysis.

A multiscale (micro-macro) approach is proposed for the establishment of the full thermal and induced stress fields in cracked composites that are subjected to heat flow. Both the temperature and stresses distributions are determined by the solution of a boundary value problem with one-way coupling. In the micro level and for combined thermomechanical loading, a micromechanical analysis is employed to determine the effective moduli, coefficients of thermal expansion and thermal conductivities of the undamaged composite. In the macro level, the representative cell method is employed according to which the periodic damaged composite region is reduced, in conjunction with the discrete Fourier transform, to a finite domain problem. As a result, a boundary value problem is obtained in the Fourier transform domain which is appropriately discretized and solved. The inverse transform and an iterative procedure provide the full thermal and stress fields. The proposed method is verified by comparisons with exact solutions. Applications are given for the determination of the thermal and stress fields in cracked fiber-reinforced polymeric composite, cracked porous ceramic material and cracked periodically layered ceramic composite caused by the application of heat flow. The presented formulation admits however the application of a combined mechanical and heat flux on cracked composites.

This paper discusses about control of the linear switched reluctance machines (LSRMs) network for the zero phase-difference tracking to a sinusoidal reference. The dynamics of each LSRM is derived by online system identification and modeled as a second-order linear system. Accordingly, based on the coupled harmonic oscillators synchronization manner, a distributed control is proposed to synchronize each LSRM state to a virtual LSRM node representing the external sinusoidal reference for tracking it with zero phase-difference. Subsequently, a simulation scenario and an experimental platform with the identical parameter setup are designed to investigate the tracking performance of the LSRMs network constructed by the proposed distributed control. Finally, the simulation and experimental results verify the effectiveness of the proposed LSRMs network controller, and also prove that the coupled harmonic oscillators synchronization method can improve the synchronization tracking performance and precision.

In this study, the physical properties of briquettes produced from two different biomass feedstocks (sawdust and date palm trunk) and different plastic wastes were investigated, without using any external binding agent. The biomass feedstocks were blended with different ratios of two WEEE plastics (halogen-free wire and print circuit boards (PCB)) and automotive shredder residues (ASR). The briquettes production is studied at different waste proportions (10-30%), pressures (22-67 MPa) and temperatures (room-130 ˚C). Physical properties as density and durability rating were measured, usually increasing with temperature. Palm trunk gave better results than sawdust in most cases, due to its moisture content and the extremely fine particles that are easily obtained.

This study presents a vibration control using actively tunable vibration absorbers (ATVA) to suppress vibration of a thin plate. The ATVA’s is made of a sandwich hollow structure embedded with the electrorheological fluid (ERF). ERF is considered to be one of the most important smart fluids and it is suitable to be embedded in a smart structure due to its controllable viscosity property. ERF’s apparent viscosity can be controlled in response to the electric field and the change is reversible in 10 microseconds. Therefore, the physical properties of the ERF-embedded smart structure, such as the stiffness and damping coefficients, can be changed in response to the applied electric field. A mathematical model is difficult to be obtained to describe the exact characteristics of the ERF embedded ATVA because of the nonlinearity of ERF’s viscosity. Therefore, a fuzzy modeling and experimental validations of ERF-based ATVA from stationary random vibrations of thin plates are presented in this study. Because Type-2 fuzzy sets generalize Type-1 fuzzy sets so that more modelling uncertainties can be handled, a semi-active vibration controller is proposed based on Type-2 fuzzy sets. To investigate the different performances by using different types of fuzzy controllers, the experimental measurements employing type-1 fuzzy and interval type-2 fuzzy controllers are implemented by the Compact RIO embedded system. The fuzzy modeling framework and solution methods presented in this work can be used for design, performance analysis, and optimization of ATVA from stationary random vibration of thin plates.

Grid energy storage system for PV Applications is connected with three different power sources i.e. PV Array, Battery and the Grid. It is advisable to have Isolation between these three different sources to provide safety for the equipment. The configuration proposed in this paper provides the complete isolation between the three sources. A Power Balancing Control (PBC) for this configuration is proposed to operate the system in three different modes of operation. Control of a dual active bridge (DAB) based battery charger which provides a galvanic isolation between batteries and other sources is explained briefly. Various modes of operation of a Grid energy storage system are also presented in this paper. Hardware-In-Loop (HIL) Simulation is carried out to check the performance of the system and the PBC algorithm. Power circuit (comprises of inverter, dual active bridge based battery charger, grid, PV cell, batteries, contactors and switches) is simulated and the controller hardware and user interface panel are connected as HIL with the simulated power circuit through Real Time Digital Simulator (RTDS). HIL simulation results are presented to explain the control operation, steady state performance in different modes of operation and the dynamic response of the system.

A turbomachinery is essential part in the power generation cycle. But, it is main noise source to annoy workers and users and to make environmental problem. Thus it is important to reduce this noise for operating the power generation cycle. This noise is created by flow instability on rotor blade trailing edge. An airfoil that becomes a section of a rotor blade of a rotating machine is manufactured as a blunt trailing edge (TE) with a round or flatback shape rather than the ideal sharp TE shape for the purposes of producibility and durability. This increases the tonal noise and flow-induced vibration at low frequency owing to vortex shedding behind TE when compared with a sharp TE. In order to overcome this problem, this study investigates the oblique TE shape using numerical simulation. In order to do so, the flow was simulated using large eddy simulation (LES) and the noise was analysed by acoustic analogy coupled with LES result. Once the simulation results were verified using the flatback airfoil measurements of Sandia National Laboratories, numerical prediction was performed for airfoils modified to have oblique trailing edge angles of 60°, 45°, and 30° to analyse the flow and noise characteristics. From the simulation results for an airfoil having an oblique TE, it could be seen that the vortex shedding frequency moves in accordance with the oblique angle and that the vortex shedding noise characteristics change according to this angle when compared to the flatback TE airfoil. Therefore, it is considered that modifying the flatback TE airfoil to have an appropriate oblique angle can reduce noise and change the tonal frequency to a bandwidth that is suitable for mechanical systems.

To implement renewable energy resources, microgrid systems have been adopted and developed into the technology of choice to assure mass electrification in the next decade. Microgrid systems have a number of advantages over the conventional utility grid systems, however, it faces severe instability issues due to continually increasing constant power loads. To improve the stability of the entire system, load side compensation technique is chosen because of its robustness and cost effectiveness. In this particular occasion, a sliding mode controller is developed for microgrid system in the presence of CPL to assure certain control objective of keeping the output voltage constant at 480V. After that, the robustness analysis of the sliding mode controller against parametric uncertainties is presented. The sliding mode controller robustness against parametric uncertainties, frequency variations, and additive white Gaussian noise (AWGN) are illustrated in this paper. Later, the performance of the PID and sliding Mode controller is compared in case of nonlinearity, parameter uncertainties, and noise rejection to justify the selection of Sliding Mode controller over PID controller. All the necessary calculations are reckoned mathematically and results are verified in the virtual platform such as MATLAB/Simulink with the appreciable outcome.

Frequency, amplitude and phase information of the grid voltage are of great importance in constructing a robust controller structure for grid connected inverter systems. This paper presents a simple and robust approach for the instantaneous estimation of positive and negative sequence voltage components under distorted voltage conditions. A second order generalized integrator (SOGI) is used to filter the distorted voltage and to generate orthogonal voltage components for each of the three phases. These filtered and orthogonal components are used for instantaneous calculation of symmetrical components. The implemented method is frequency adaptive; the method is demonstrated and compared to a conventional phase locked loop (PLL) technique with both MATLAB/Simulink simulations and experiments utilizing the dSPACE ds1103 digital controller.

The concept of smart morphing blades, which can control themselves to reduce or eliminate the need for active control systems, is a highly attractive solution in blade technology. In this paper an innovative passive control system based on Shape Memory Alloys (SMAs) is proposed. On the basis of previous thermal and shape characterization of a single morphing blade for a heavy-duty automotive cooling axial fan, this study deals with the numerical analysis of the aerodynamic loads acting on the fan. By coupling CFD and FEM approaches it is possible to analyze the actual blade shape resulting from both the aerodynamic and centrifugal loads. The numerical results indicate that the polymeric blade structure ensures proper resistance and enables shape variation due to the action of the SMA strips.

Autonomous aerial refueling technology is an effective solution to extend flight duration of unmanned aerial vehicles, and also a great challenge due to its high risk. For autonomous probe-and-drogue refueling tasks, relative navigation to provide relative position between the receiver aircraft and the refueling drogue is the first and essential step, and vision-based method is the most frequently used. A new monocular vision navigation sensor with image processing strategy consisting of the drogue detection method and the tracking method is developed for autonomous aerial refueling in this paper. In the drogue detection method, thresholding and mathematical morphology method are adopted to eliminate image interference, and contours extraction method is applied to obtain all contours, which are then subsequently checked to achieve target contour of drogue. In the tracking method, a rectangle of interest (ROI) of current frame image is determined by positioning results of last frame, and then processed by the previous drogue detection method. Finally, the proposed image processing strategy in monocular vision navigation sensor is validated using real flight images, which are captured from an autonomous aerial refueling testbed using a micro six-rotor aircraft as receiver aircraft.

This paper presents a thermal runaway prognosis scheme based on the big-data platform and entropy method for battery systems in electric vehicles. It can simultaneously realize the diagnosis and prognosis of thermal runaway caused by the temperature fault through monitoring battery temperature during vehicular operations. A vast quantity of real-time voltage monitoring data was collected in the National Service and Management Center for Electric Vehicles (NSMC-EV) in Beijing to verify the effectiveness of the presented method. The results show that the proposed method can accurately forecast both the time and location of the temperature fault within battery packs. Furthermore, a temperature security management strategy for thermal runaway is proposed on the basis of the Z-score approach and the abnormity coefficient is set to make real-time precaution of temperature abnormity.

The excessive vibration caused by crowds walking across footbridges has attracted great public concerns in the past few decades. This paper presents, from considering the dynamic characteristics of the bipedal crowd model, a new stability limit criterion based on the bipedal excitation model. The stability limit can be used to estimate the upper boundary of crowd size. In addition, the dynamic stable performances of a structure, under a certain walking crowd size, can be predicted by the stability criterion. This proposed mechanism provides an alternative comprehension how crowd excite the excessive sway motion with a large-span structure.

The attention to sustainable-related issues has grown fast in recent decades. The experience gained with these themes reveals the importance of considering this topic in the construction industry, which represents an important sector in the world. This work consists on conducting a multicriteria analysis of four cement powders, with the objective of calculating and analysing the environmental, human health and socio-economic effects of their production processes. The economic, technical, environmental and safety performances of the examined powders result from official, both internal and public, documents prepared by the producers. The Analytic Hierarchy Process permitted to consider several indicators (i.e. environmental, human health related and socio-economic parameters) and to conduct comprehensive and unbiased analyses which gave the best, most sustainable cement powder. As assumed in this study, the contribution of each considered parameter to the overall sustainability has a different incidence, therefore the procedure could be used to support on-going sustainability efforts under different conditions. The results also prove that it is incorrect to consider only one parameter to select the ‘best’ cement powder, but several impact categories should be considered and analysed if there is an interest for pursuing different, often conflicting interests.

The air side thermal hydraulic performance of multi-louvered aluminium fin heat exchangers is investigated. A detailed study was performed to analyse the thermal performance of air over a wide range of Reynolds number i.e. from 30 to 250. Air-side heat transfer coefficient and air pressure drop were calculated and validated over the mentioned band of Reynolds numbers. Critical Reynolds number was determined numerically and the variation in flow physics along with the thermal and hydraulic performance of microchannel heat exchanger associated with R_cri has been reported. Moreover, a parametric study of the multi-louvered aluminium fin heat exchangers was also performed for 36 heat exchanger configurations with the louver angles (19-31°), fin pitches (1.0, 1.2, 1.4 mm) and flow depths (16, 20, 24 mm); and the geometric configuration exhibiting the highest thermal performance was reported. The air-side heat transfer coefficient and pressure drop results for different geometrical configurations were presented in terms of Colburn j factor and Fanning friction factor f, as a function of Reynolds number based on louver pitch.

The evolving multiphase induction generators (MPIG) with more than three phases are receiving prominence in high power generation systems. This paper aims at the development of a comprehensive model of the wind turbine driven seven-phase induction generator (7PIG) along with necessary the power electronic converters and controller for grid interface. The dynamic model of the system is developed in Maltlab/Simulink. Synchronous reference frame phase-locked loop (SRFPLL) system is incorporated for grid synchronization. The modeling aspects are detailed and the system response is observed for various wind velocities. The effectiveness of seven phase induction generator is demonstrated with the fault tolerant capability and high output power with reduced phase current when compared to conventional 3-phase wind generation scheme. The response of the PLL is analyzed and the results are presented.

Electric vehicles (EV) are getting more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace the internal combustion engine (ICE) vehicles in near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system can face huge instabilities with enough EV penetration; but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of smart grid. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emission from the transportation sector. However, there are some major obstacles for EVs to overcome before replacing the ICE vehicles totally. This paper is focused on reviewing all the useful data available on EV configurations, energy sources, motors, charging techniques, optimization techniques, impacts, trends, and possible directions of future developments. Its objective is to provide an overall picture of the current EV technology and ways of future development to assist in future researches in this sector.

Fourteen (14) rack-mounted polycrystalline modules installed on the concrete roof of the solar energy applications laboratory at the Kwame Nkrumah University of Science and Technology (KNUST) in Ghana, a hot humid environment were assessed after 19 years of continuous outdoor expodure. The physical state of the modules was documented using a visual inspection checklist. They were further assessed by current-voltage (I-V) characterization and thermal imaging. The modules were found to be in good physical state, except some bubbles on front side and minor discolouration/corrosion at edge of the cells. Compared with reference values, the performance decline of the modules observed over the exposure period was: nominal power (P_nom), 21% to 35%; short circuit current (I_sc), 5.8% to 11.7%; open circuit voltage (V_oc) 3.6% to 5.6% and 11.9% to 25.7% for fill factor (FF). It is hoped that this study will provide some helpful information to project developers, manufacturers and the research community on the long-term performance of PV modules in Ghana.

It is well known that working PV plants show several maintenance needs due to wiring and modules degradation, mismatches, dust and PV cells defects and faults. There are a wide range of studies that show the theoretical and some laboratory tests of how these circumstances may affect the PV production. Thus, it results mandatory to evaluate the whole PV plant performance and, then, it’s payback time, profitability and environmental impact or carbon footprint. However, very few studies include a systematic procedure to quantify and supervise the real degradation effects and faults impacts on the field. In this paper, the authors first conduct a brief review of the most frequent PV faults and degradation that can be found on real conditions operative PV Plants. Then, they propose and develop an innovative Geographic Information System application to locate and supervise them. The designed tool has been applied to either a large PV plant of 108 kWp and a small PV plant of just 9 kWp installed on a home rooftop. For the large PV plant, 24 strings of PV modules have been modelized and introduced into the GIS application and every module in the power plant has been studied including voltage, current, power, series and parallel resistance, fill factor, normalized PV curve to STC, thermography and visual analysis. For the small PV installation 3 strings of PV panels have been studied identically. It must be noticed that PV modules in this case include power optimizers. The precision of the study allows the researchers to locate and supervise up to a third part of every PV cell in the system, which are adequately georreferenciated. The developed tool allows both the researchers and the investors to increase control on the PV plant performance and conducts to a better planification of maintenance actuations and to evaluate several PV modules replacement strategies in a preventive maintenance programme. Found PV faults include hot spots, snail tracks, EVA discoloration, PV cells fractures, busbars discoloration, bubbles and Si discoloration.

The purpose of this work is to present an adaptive sliding mode luenberger state observer with improved disturbance rejection capability and better tracking performance under dynamic conditions. The sliding hyperplane is altered by incorporating the estimated disturbance torque with the stator currents. Also, the effects of parameter detuning on the speed convergence is observed and compared with the conventional disturbance rejection mechanism. The entire drive system is first built in simulink environment. Then, the simulink model is integrated with RT-Lab blocksets and implemented in a relatively new real-time environment using OP4500 real-time simulator. Real-time simulation and testing platforms have succeeded offline simulation and testing tools due to their reduced development time. The real-time results validate the improvement in the proposed state observer and also correspond to the performance of the actual physical model.

Distribution systems can form islands when faults occur. Each island represents a subsection with variable boundaries subject to the location of a fault(s) in the system. A subsection with variable boundaries is referred to as island in this paper. For operation in autonomous mode, it is imperative to detect the island configurations and stabilize these subsections. This paper presents a novel scheme for the detection of islanding boundaries and stabilizing the system during autonomous operation. In the first stage, a boundary detection method is proposed to detect the configuration of the island. In the second stage a dynamic voltage sensitivity factor (DVSF) is proposed to assess the dynamic performance of the system. In the third stage, a wide area load shedding program is adopted based on DVSF to shed the load in weak busbars and stabilize the system. The proposed scheme is validated and tested on a generic 18-bus system using a combination of EMTDC/PSCAD and MATLAB softwares.

In this paper a variable’s involved in assessing the quality of a distributed generation system are reviewed, aiming to minimize the electric power losses (unused power consumption) and optimize the voltage profile. To provide this assessment, several experiments have been made to the IEEE 34-bus test case and various actual test cases with the respect of multiple DG units. The possibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been verified. Finally, four algorithms were trailed: simulated annealing (SA), hybrid genetic algorithm (HGA), genetic algorithm (GA) and variable neighbourhood search. The HGA algorithm was found to produce the best solution at a cost of longer processing time.

Within the context of ever wider expansion of direct injection in spark ignition engines, this investigation was aimed at improved understanding of the correlation between fuel injection strategy and emission of nanoparticles. Measurements performed on a wall guided engine allowed identifying the mechanisms involved in the formation of carbonaceous structures during combustion and their evolution in the exhaust line. In-cylinder pressure was recorded in combination with cycle-resolved flame imaging, gaseous emissions and particle size distribution. This complete characterization was performed at three injection phasing settings, with butanol and commercial gasoline. Optical accessibility from below the combustion chamber, allowed visualization of diffusive flames induced by fuel deposits; these localized phenomena were correlated to observed changes in engine performance and pollutant species. With gasoline fueling, minor modifications were observed with respect to combustion parameters, when varying the start of injection. The alcohol, on the other hand, featured marked sensitivity to the fuel delivery strategy. Even though the start of injection was varied in a relatively narrow crank angle range during the intake stroke, significant differences were recorded, especially in the values of particle emissions. This was correlated to the fuel jet-wall interactions; the analysis of diffusive flames, their location and size confirmed the importance of liquid film formation in direct injection engines, especially at medium and high load.

Geological disposal facilities for radioactive waste pose significant challenges for robust monitoring of environmental conditions within the engineered barriers that surround the waste canister. Temperatures are elevated, due to the presence of heat generating waste, relative humidity varies from 20% to 100%, and swelling pressures within the bentonite barrier can typically be 2-10 MPa. Here, we test the robustness of a bespoke design MEMS sensor-based monitoring system, which we encapsulate in polyurethane resin. We place the sensor within an oedometer cell and show that despite a rise in swelling pressure to 2 MPa, our relative humidity (RH) measurements are unaffected. We then test the sensing system against a traditional RH sensor, using saturated bentonite with a range of RH values between 50% and 100%. Measurements differ, on average, by 2.87% RH, and are particularly far apart for values of RH greater than 98%. However, bespoke calibration of the MEMS sensing system using saturated solutions of known RH, reduces the measurement difference to an average of 1.97% RH, greatly increasing the accuracy for RH values close to 100%.

Active contour models present a robust segmentation approach which make efficient use of specific information about objects in the input data rather than processing all the data. They have been widely used in many applications including image segmentation, object boundary localisation, motion tracking, shape modelling, stereo matching and object reconstruction. In this paper, we investigate the potential of active contour models in extracting roads from Mobile Laser Scanning (MLS) data. The categorisation of active contours based on their mathematical representation and implementation are discussed in detail. We discuss an integrated version in which active contour models are combined to overcome their limitations. We review various active contour based methodologies which have been developed to extract roads and other features from LiDAR and digital imaging datasets. We present a small case study in which an integrated version of active contour models is applied to automatically extract road edges from MLS dataset. An accurate extraction of left and right edges from the tested road section validates the use of active contour models. The present study provides a valuable insight on the potential of active contours for extracting roads and other infrastructures from 3D LiDAR point cloud data.

Clock Network Design (CDN) is a critical step while designing any Integrated-Circuits (ICs). It holds vital importance in the performance of entire circuit. Due to continuous scaling, 3D ICs stacked with TSV are gaining importance, with an objective to continue with the Moore's law. Through-Silicon-Via (TSV) provides the vertical interconnection between two die, which allows the electrical signal to flow through it. 3D ICs has many advantages over conventional 2D planar ICs like reduced power, area, cost, wire-length etc. The proposed work is mainly focused on power reduction and obstacle avoidance for 3D ICs. Various techniques have already been introduced for minimizing clock power within specified clock constraints of the 3D CND network. Proposed 3D Clock Tree Synthesis (CTS) is a combination of various algorithms with an objective to meet reduction in power as well as avoidance of obstacle or blockages while routing the clock signal from one sink to other sink. These blockages like RAM, ROM, PLL etc. are fixed during the placement process. The work is carried out mainly in three steps- first is Generation of 3D Clock tree avoiding the blockages, then Buffering and Embedding and finally validating the results by SPICE simulation. The experimental result shows that our CTS approach results in significant 9% reduction in power as compare to the existing work.

With the rapid development of MEMS (Micro-electro-mechanical Systems) fabrication technologies, manifolds microelectrodes with various structures and functions have been designed and fabricated for applications in biomedical research, diagnosis and treatment through electrical stimulation and electrophysiological signal recording. The flexible MEMS microelectrodes exhibit multi-aspect excellent characteristics beyond stiff microelectrodes based on silicon or SU-8, which comprising: lighter weight, smaller volume, better conforming to neural tissue and lower fabrication cost. In this paper, we mainly reviewed key technologies on flexible MEMS microelectrodes for neural interface in recent years, including: design and fabrication technology, flexible MEMS microelectrodes with fluidic channels and electrode-tissue interface modification technology for performance improvement. Furthermore, the future directions of flexible MEMS microelectrodes for neural interface were described including transparent and stretchable microelectrodes integrated with multi-aspect functions and next-generation electrode-tissue interface modifications facilitated electrode efficacy and safety during implantation. Finally, the combinations among micro fabrication techniques with biomedical engineering and nanotechnology represented by flexible MEMS microelectrodes for neural interface will open a new gate to human lives and understanding of the world.

Dump design and scheduling are critical elements to effective mine planning, especially if several of them are required in large-scale open pit mines. Infrastructure capital and transportation costs are considerable from an early stage in the mining project, and through the life-of-mine as these dumps gradually become immense structures. Delivered mining rates, as well as certain spatial and physical constraints, provide a set of parameters of mathematical and economic relationship that creates opportunities for modelling and thus facilitates the measuring and optimization of ultimate dump design by using programming and empirical techniques while achieving economic objectives. This paper presents a methodology to model and optimize the design of a mine dump by minimizing the total haulage costs. The proposed methodology consists on: (i) Formulation of a dump model based on a system of equations relying on multiple relevant parameters; (ii) Solves by minimizing the total cost using linear programming and determines a ‘preliminary’ dump design; (iii) Through a series of iterations, modifies the ‘preliminary’ footprint by projecting it to the topography and creates the ultimate dump design. Finally, an example application for a waste rock dump illustrates this methodology.

Impact characterization of linear resonant actuator (LRA) is studied experimentally by newly developed drop tester, which can control various experimental uncertainty such as rotational moment, air resistance, secondary impact and so on. The feasibility of this test apparatus was verified by comparison with free fall test. By utilizing a high-speed camera and measuring the vibrational displacement of spring material, the impact behavior was captured and the damping ratio of the system was defined. Based on the above processes, the finite element model was established and the experimental and analytical results were successfully correlated. Finally, the damage of the system from impact loading can be expected by developed model and as a result, this research can improve the impact reliability of LRA.

Electricity sector is among the main carbon emissions contributors. This sector has the potential to reduce its carbon emissions through producing electric energy from zero emitting facilities and through the optimization of the consumption in a way to better accommodate low carbon emissions. Hydrogen society per se combined with smart grids, as this is analyzed in this manuscript, can present substantial contribution towards climate change mitigation.

The technologies influencing alternative ways of transportation are augmenting in recent years as the need for transportation is increasing rapidly due to urbanization and motorization. In this paper, a solar powered electric auto-rickshaw (SPEA) is designed and developed for Indian conditions. The developed vehicle is comprehensively analyzed techno-economically for its viability in the Indian market. The performance analysis of SPEA results in an optimal charging rate of 2 kWh per day with an average solar irradiance of 325 W/m2. The discharging characteristics are studied based on different loading conditions. The vehicle achieved a maximum speed of 21.69 km/h with battery discharge rate of 296W at 90kg load and also reached a maximum discharge rate of 540W at 390kg loading with a maximum speed of 12.11 km/h. The environmental analysis of SPEA displayed yearly CO2 emissions of 1,777 kg, 1,987 kg and 1,938 kg using Compressed Natural Gas, Liquefied Petroleum Gas and gasoline engines respectively can be mitigated using SPEA. The results of financial analysis of SPEA were welcoming as the investor gets 24.44% lesser payback duration compared to gasoline run vehicle. Socio-Economic analysis of SPEA discussed its significant advantages and showed 18.73% and 3.9% increase in yearly income over gasoline driven and battery driven vehicles.

Errors during manufacture of high value components are not acceptable nowadays in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power manufacture complex and accurate components that demand close measurements and fast feedback into manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They shall provide the possibility to measure the workpiece during or after the manufacturing process, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable for process control or product validation. Due to the similarity between a coordinate measuring machine and a machine tool, some of the methods applied for a correct assessment of uncertainty in coordinate measuring machines are adapted to the challenges of a machine tool. The scientific objective is to determine the uncertainty on a machine tool measurement and, in this way, convert it into a machine integrated traceable measuring process. This paper reviews the fundamentals of machine tool metrology.

Vibrations of blades and tower have important impact for wind turbine. This paper presents a active controller design to suppress blade edgewise vibrations under aerodynamic load and gravitational load.Treating the sum of aerodynamic load input in edgewise direction and gravitational load as unknown disturbance input,a stochastic disturbance accommodating control(SDAC) approach is proposed to design a controller which it utilizes a minimum-variance unbiased estimator(MVUE) to estimate both state and unknown input. The stability analysis proved that the proposed SDAC is bounded in mean square.In order to verify the performance of the minimum-variance unbiased estimator and the proposed SDAC, numerical simulations using Matlab/Simulink have been carried out for the National Renewable Energy Laboratory 5-MW wind turbine.Under the different circumstance which exists the random process and measure noise and noise free. It is shown that the estimation value by MVUE can tracking the real state and unknown input. The results are also compared to the traditional linear quadratic regulator(LQR) and show that the proposed stochastic disturbance accommodating control scheme can further reduce displacement in edgewise vibrations direction and the control strategy is more effective than the LQR.

The biophenol integral extraction protocol from vegetation water developed in the early 2000s for the three-phase olive mill was adapted to a large two-phase mill operating in Sicily during the 2016/2017 season. The new set-up allows extensive recovery of olive phenolics, transforming previous waste into a source of revenues for the milling company and of valued bioproducts for its bioeconomy partner, while eliminating a source of potential pollution altogether.

The fault diagnosis of wind farms has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of a wind park benchmark model, and it considers viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves data-driven approaches, as they can represent effective tools for coping with poor analytical knowledge of the system dynamics, noise, uncertainty and disturbances. In particular, the proposed data-driven solutions rely on fuzzy models and neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen architectures rely on nonlinear autoregressive with exogenous input models, as they can represent the dynamic evolution of the system along time. The developed fault diagnosis schemes are tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind farm installation. The achieved performances are also compared with those of a model-based approach relying on nonlinear differential geometry tools. Finally, a Monte-Carlo analysis validates the robustness and the reliability of the proposed solutions against typical parameter uncertainties and disturbances.

In this paper, the methods and their analysis for estimating the location of three dimension (3-D) single source buried in lossy medium are presented with uniform circular array (UCA). The mathematical model of the signal in the lossy medium is proposed. Using location information in the covariance matrix obtained by sensors’ output, the equations of the source location (azimuth angle, elevation angle and range) are obtained. The phase and amplitude of the covariance matrix function are used to process these equations respectively. Then, the phase and amplitude of the covariance matrix function are used to process the source localization in the conductive medium together. By analyzing the characteristics of the proposed methods and MUSIC method, the computational complexity and the valid range of these methods are given. From the results, whether the loss is known, we can choose the appropriate method to process the issues (localization in lossless medium or lossy medium).

Identification of costs drivers and their influence level on building development costs play a key role in the development of construction models and improve the efficiency and effectiveness of any project. Forty-five indicators influencing building development costs in New Zealand are explored by literature review and pilot interviews. These indicators are grouped into seven categories. The determination and ranking of the cost drivers are carried out by a questionnaire survey distributed to key professionals working in New Zealand’s construction industry. Structural equation modeling (SEM) software was employed for analysis of the collected data. One of the key advantages of this powerful software is to provide the p-value according to the structure of the research model. Findings of this study indicate that the property market and construction industry factor, statutory and regulatory factor, and socio-economic factor are major factors affecting building development costs in New Zealand.

The paper presents the design stages of a single-phase Silicon Carbide bidirectional DC-AC converter. This includes the LCL filter design responsible to meet grid connection requirements. A 3kW laboratory prototype of the power converter is built employing a low-cost phase locked loop and its results are presented. The design of the low-cost phase locked loop and its implementation are depicted in some detail.

The switched inertance hydraulic system (SIHS) is a novel high-bandwidth and energy-efficient digital device which can adjust or control flow and pressure by a means that does not rely on throttling the flow and dissipation of power. An SIHS can provide an efficient step-up or step-down of pressure or flow rate by using a digital control signal. In this article, analytical models of an SIHS in a four-port high-speed switching valve configuration are proposed, and the system dynamics and performance are investigated theoretically and experimentally. The flow responses, system characteristics and power consumption can be predicted effectively and accurately by using the proposed models, which were validated by comparing with experiments and with numerical simulation. The four-port configuration is compared with the three-port configuration, and it is concluded that the former one is less efficient for valves of the same size, but provides a bi-direction control capability. As bi-direction control is a common requirement, this constitutes an important contribution to the development of efficient digital hydraulics.

This paper address the development of a new technic in the sleep analysis domain. Sleep is defined as a periodic physiological state during which vigilance is suspended and reactivity to external stimulations diminished. We sleep on average between six and nine hours per night and our sleep is composed of four to six cycles of about 90-minutes each. Each of these cycles is composed of a succession of several stages of sleep, more or less deep. The analysis of sleep is usually done using a polysomnography. This examination consists of recording, among other things, electrical cerebral activity by electroencephalography (EEG), ocular movements by electrooculography (EOG) and chin muscle tone by electromyography (EMG). The recording is done mostly in a hospital, more specifically in a service for monitoring the pathologies related to sleep. The readings are then interpreted manually by an expert to generate a hypnogram, a curve showing the succession of sleep stages during the night in 30-second epochs. The proposed method is based on the follow-up of the thermal signature that makes it possible to classify the activity into three classes: "awakening", "calm sleep" and "agitated sleep". The contribution of this non-invasive method is part of the screening of sleep disorders, to be validated by a more complete analysis of the sleep. The measure provided by this new system, based on temperature monitoring (patient and ambient), aims to be integrated into the tele-medicine platform developed within the framework of the Smart-EEG project by the SYEL - SYstèmes ELectroniques team. Analysis of the data collected during the first surveys carried out with this method showed a correlation between thermal signature and activity during sleep. The advantage of this method lies in its simplicity and the possibility of carrying out measurements of activity during sleep and without direct contact with the patient at home or hospitals.

Saliency detection in synthetic aperture radar (SAR) image is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR image. Firstly, we extract four features of SAR image as the input of the MSD model, which include the intensity, orientation, uniqueness and global contrast. Then, the saliency map is generated by the multitask sparsity pursuit (MTSP) which integrates the multiple features collaboratively. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps of the source images, an image fusion method is proposed for the SAR and color optical image fusion. The experimental results of real data show the proposed image fusion method is superior to the presenting methods in terms of several universal quality evaluation indexes, as well as in the visual quality. The salient areas in the SAR image can be highlighted and the spatial and spectral details of color optical image can also be preserved in the fusion result.

In Ghana, about 73% of households rely on solid fuels for cooking. Over 13,000 annual deaths are attributed to exposure to indoor air pollution from inefficient combustion. In this study, assessment of thermal efficiency, emissions and total global warming impact of three cookstoves commonly used in Ghana was completed using IWA water boiling test (WBT) protocol. Statistical averages of three replicate tests for each cookstove were computed. Thermal efficiency results were: wood-burning cookstove 12.2% (Tier 0), traditional charcoal cookstove 23.3% (Tier 1-2) and improved charcoal cookstove 30% (Tier 2-3). The wood-burning cookstove emitted more CO, CO2 and PM2.5 than charcoal cookstove (coalpot) and improved cookstove. Emission factor for PM2.5 and emission rate for the wood-burning cookstove (Tier 0) were over four times higher than the traditional charcoal cookstove (Tier 3) and improved cookstove (Tier 2). On the basis of WBT, annual global warming impact potential for emissions are estimated at 4 tonnes of CO2e for the wood-burning cookstove, 1.5 tonnes of CO2e for charcoal cookstove (coalpot) and 1 tonne of CO2e for improved cookstove. We conclude that there is the need for awareness, policy and incentives to enable end-users switch to improved cookstoves for increased efficiency, reduced emissions/global warming impact.

The stability assessment of aged tunnel linings were mainly evaluated based on the visual inspection, and the Tunnel-lining Crack Index (TCI) is one of the most widely used tunnel lining health assessment indexes in Japan. However, the intersection and distribution of cracks, which can influence the stability of tunnel lining greatly, were not considered in the TCI. A new method was proposed for the health assessment of tunnel lining, which evaluate the lining states according to the fractal dimension of cracks. Based on the machine vision-based method, the crack image can be extracted efficiently. The fractal dimension of lining cracks in one span can be obtained in a few minutes. A series of comparative tests and field tests were conducted to evaluate the validity of this new method. The comparative tests confirmed that fractal dimension can characterize the density, width, and distribution of cracks. The results also certificated that the influence of crack width is larger than the crack density. The intersection of cracks, which will increase the risk of lining collapse, can also increase the fractal dimension, whereas the TCI keep constant. The fractal dimensions of tunnel lining cracks were obtained according to the digital inspection test of Hidake Tunnel in Japan for all the 65 spans. Moreover, the TCI was obtained through statistical methods. The correlation between fractal dimension and TCI of tunnel lining was studied. The significance of the new evaluation index is that it can identify some unusual spans of tunnel lining and provide a basis for further internal testing. As a complement to the conventional visual inspection method, the fractal dimension of the cracks is a promising health assessment index.

With the widespread use of electric machines there is a growing need to extract information from the machines to optimize their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of an squirrel cage induction motor rotor physical variables. The system comprises: circuit to acquire desirable rotor variable(s) value(s) and send it to the computer; a rectifier and power storage circuit that besides converting an alternating current in continuous also store energy for a certain amount of time to wait the motor engine shutdown; and magnetic generator that harvest energy from rotating field to power the circuits mentioned above. The embedded system is set on the rotor, making it difficult to power the system because it is rotating, problem solved with the construction of the magnetic generator eliminating the need of using batteries or collector rings and send data to the computer using a wireless NRF24L01 module. For the proposed system validation a temperature sensor (DS18b20) was used, variable known as the most important when identifying the need for maintenance and control systems. Tests were made getting satisfactory results proving the viability of using sensors on the rotor.