Effect of Exchange-Correlation Functional on the Structural, Mechanical, and Optoelectronic Properties of Orthorhombic RbSrBr3 Perovskite

In the present study, the effect of the exchange-correlation functional on the structural, mechanical, and optoelectronic properties of orthorhombic RbSrBr3 perovskite has been investigated using various functionals in Density Functional Theory (DFT) with the CASTEP code. The optimized lattice parameters are quite similar for all the functionals. The electronic properties have shown that RbSrBr3 perovskite is a wide direct band gap compound with a band gap energy ranging from 4.296 eV to 4.494 eV for all the functionals. The mechanical parameters like elastic constants, Young’s modulus, Shear modulus, Poisson’s ratio, Pugh’s ratio, and an anisotropic factor reveal that the RbSrBr3 perovskite has ductile behavior and an anisotropic nature which signifies the mechanical stability of the compound. The Debye temperature might withstand lattice vibration heat. High absorption coefficient (>104 cm−1), high optical conductivity, and very low reflectivity have been found in the RbSrBr3 perovskite for all functions. The computed findings on the RbSrBr3 perovskite suggested that the presented studied material is potentially applicable for photodetector and optoelectronic devices.

Enhanced Fuzzy Logic Control Model and Sliding Mode Based on Field Oriented Control of Induction Motor

In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.

Optimal Operation of Distributed Generations Considering Demand Response in a Microgrid Using GWO Algorithm

The widespread penetration of distributed energy sources and the use of load response programs,especially in a microgrid,have caused many power system issues,such as control and operation of these networks,to be affected.The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid.In this paper,the optimum operation of distributed generation resources and heat and power storage in a microgrid,was performed based on real-time pricing through the proposed gray wolf optimization(GWO)algorithm to reduce the energy supply cost with the microgrid.Distributed generation resources such as solar panels,diesel generators with battery storage,and boiler thermal resources with thermal storage were used in the studied microgrid.Also,a combined heat and power(CHP)unit was used to produce thermal and electrical energy simultaneously.In the simulations,in addition to the gray wolf algorithm,some optimization algorithms have also been used.Then the results of 20 runs for each algorithm confirmed the high accuracy of the proposed GWO algorithm.The results of the simulations indicated that the CHP energy resources must be managed to have a minimum cost of energy supply in the microgrid,considering the demand response program.

Modeling, Analysis and Simulation of a High-Efficiency Battery Control System

This paper explains step-by-step modeling and simulation of the full circuits of a battery control system and connected together starting from the AC input source to the battery control and storage system.The three-phase half-controlled rectifier has been designed to control and convert the AC power into DC power.In addition,two types of direct current converters have been used in this paper which are a buck and bidirectional DC/DC converters.These systems adjust the output voltage to be lower or higher than the input voltage.In the buck converters,the main switch operates in conduction or cut-off mode and is triggered by a Pulse-Width Modulated(PWM)signal.The output and input voltage levels ratio are used to calculate thePWMsignal’s duty cycle.Therefore,the duty cycle indicates the operation mode of the converter in steady-state operation.In this study,we analyze and control of a buck converter with the PWM signal.Besides,the bidirectional DC/DC converter has been achieved and optimized by PI control methods to control the battery charging and discharging modes.The simulation has been applied via the Matlab/Simulink environment.The results show the activity of each part of the designed circuits starting from the converters and the battery control system in charge and discharge modes.

Frilled Lizard Optimization: A Novel Bio-Inspired Optimizer for Solving Engineering Applications

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.

Modelling of Wideband Concentric Ring Frequency Selective Surface for 5G Devices

Frequency selective surfaces(FSSs)play an important role in wireless systems as these can be used as filters,in isolating the unwanted radiation,in microstrip patch antennas for improving the performance of these antennas and in other 5G applications.The analysis and design of the double concentric ring frequency selective surface(DCRFSS)is presented in this research.In the sub-6 GHz 5G FR1 spectrum,a computational synthesis technique for creating DCRFSS based spatial filters is proposed.The analytical tools presented in this study can be used to gain a better understanding of filtering processes and for constructing the spatial filters.Variation of the loop sizes,angles of incidence,and polarization of the concentric rings are the factors which influence the transmission coefficient as per the thorough investigation performed in this paper.A novel synthesis approach based on mathematical equations that may be used to determine the physical parameters ofDCRFSSbased spatial filters is presented.The proposed synthesis technique is validated by comparing results from high frequency structure simulator(HFSS),Ansys electronic desktop circuit editor,and an experimental setup.Furthermore,the findings acquired from a unit cell are expanded to a 2×2 array,which shows identical performance and therefore proves its stability.

A Systematic Review of Thermoelectric Peltier Devices: Applications and Limitations

Conventional refrigeration processes release ammonia and freon into the atmosphere,which results in global warming.These problems may be overcome by using thermoelectric modules because of the absence of coolants or refrigerants in these systems.However,the cooling performances of such modules are relatively small in comparison to those of conventional refrigerators.In this paper,the working principles of thermoelectric modules are discussed together with a review of different relevant aspects,namely:the thermoelectric materials,and their mechanical properties used to build thermoelectric devices,different types of thermoelectric devices available on the market,mathematical modeling of thermoelectric materials,and various applications of thermoelectric materials in different fields.

Design and Development of an Intelligent Energy Management System for a Smart Grid to Enhance the Power Quality

MigroGrid(MG)has emerged to resolve the growing demand for energy.But because of its inconsistent output,it can result in various power quality(PQ)issues.PQ is a problem that is becoming more and more important for the reliability of power systems that use renewable energy sources.Similarly,the employment of nonlinear loads will introduce harmonics into the system and,as a result,cause distortions in the current and voltage waveforms as well as low power quality issues in the supply system.Thus,this research focuses on power quality enhancement in the MG using hybrid shunt filters.However,the performance of the filter mainly depends upon the design,and stability of the controller.The efficiency of the proposed filter is enhanced by incorporating an enhanced adaptive fuzzy neural network(AFNN)controller.The performance of the proposed topology is examined in a MATLAB/Simulink environment,and experimental findings are provided to validate the effectiveness of this approach.Further,the results of the proposed controller are compared with Adaptive Fuzzy Back-Stepping(AFBS)and Adaptive Fuzzy Sliding(AFS)to prove its superiority over power quality improvement in MG.From the analysis,it can be observed that the proposed system reduces the total harmonic distortion by about 1.8%,which is less than the acceptable limit standard.

Modeling and Simulation of DVR and D-STATCOM in Presence of Wind Energy System

The present study suggests that series voltage injection is more effective than parallel current injection to improve voltage quality on the load side.The line voltage can be accurately symmetrized at the connection point by creating and controlling a series voltage component in each phase.This is more reliable and effective than parallel current injection.A dynamic voltage restorer(DVR)and a distribution static synchronous compensator(DSTATCOM)were utilized to provide the required power.The DVR is an effective andmodern device utilized in parallel within the grid and can protect sensitive loads from voltage problems in the grid by injecting voltage.The DVR and D-STATCOM were used to improve voltage stability in faults.A standard 13-bus system was studied in the presence of a wind farm.The simulation results demonstrated that single and three-phase overloads dramatically altered the voltage of the system,making it necessary to use compensators to improve voltage stability.The DVR and D-STATCOM showed similar performance under normal conditions and somewhat improved grid voltage unbalance.However,the DVR outperformed D-STATCOM under asymmetric faults conditions and led to lower voltage variations.

Availability Capacity Evaluation and Reliability Assessment of Integrated Systems Using Metaheuristic Algorithm

Contemporarily,the development of distributed generations(DGs)technologies is fetching more,and their deployment in power systems is becom-ing broad and diverse.Consequently,several glitches are found in the recent studies due to the inappropriate/inadequate penetrations.This work aims to improve the reliable operation of the power system employing reliability indices using a metaheuristic-based algorithm before and after DGs penetration with feeder system.The assessment procedure is carried out using MATLAB software and Mod-ified Salp Swarm Algorithm(MSSA)that helps assess the Reliability indices of the proposed integrated IEEE RTS79 system for seven different configurations.This algorithm modifies two control parameters of the actual SSA algorithm and offers a perfect balance between the exploration and exploitation.Further,the effectiveness of the proposed schemes is assessed using various reliability indices.Also,the available capacity of the extended system is computed for the best configuration of the considered system.The results confirm the level of reli-able operation of the extended DGs along with the standard RTS system.Speci-fically,the overall reliability of the system displays superior performance when the tie lines 1 and 2 of the DG connected with buses 9 and 10,respectively.The reliability indices of this case namely SAIFI,SAIDI,CAIDI,ASAI,AUSI,EUE,and AEUE shows enhancement about 12.5%,4.32%,7.28%,1.09%,4.53%,12.00%,and 0.19%,respectively.Also,a probability of available capacity at the low voltage bus side is accomplished a good scale about 212.07 times/year.

A Techno-Economical Characterization of Solar PV Power Generation in Rwanda:The Role of Subsidies and Incentives

Standalone Solar PV systems have been vital in the improvement of access to energy in many countries.However,given the large cost of solar PV plants’components,in developing countries,there is a dear need for such components to be subsidised and incentivised for the consumers to afford the produced energy.Moreover,there is a need for optimal sizing of the solar PV plants taking into account the solar information,energy requirement for various activities,and economic conditions in the off-grid regions in Rwanda.This study aims to develop optimally sized solar PV plants suited to rural communities in Rwanda.Likewise,it aims at characterizing the impacts of subsidies and incentives on the profitability and affordability of solar PV plants’energy in Rwanda.In the study,we have developed a model on basis of which the plant power(peak power)and costs of energy can be predicted given the load requirements using PVSyst.The model was validated using data corrected at eight different sites.Our generalized predictive model’s results matched the results obtained using field measurement data as inputs.The models have been able to replicate with a by degree of accuracy the peak powers and the plants’costs for different loads and were used to evaluate the economic viability of solar PV plants in Rwanda.It was found that with incentives and subsidies of 20%,the solar PV systems’costs,the Levelised Cost of Energy would drop from a maximum of 0.098 Euro to a minimum of 0.072 Euro,the payback period was reduced from a maximum of 7.5 years to a minimum of 6.0 years while the return on investments was seen to vary between 425.72 and 615.32 per cent over the plants’lifetime of 25 years.Overall our findings underscore the importance of government subsidies and incentives for solar PV energy generation projects to be significantly profitable.

Automatic area estimation of algal blooms in water bodies from UAV images using texture analysis

Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human life.The adverse effects of harmful algal blooms(HABs)necessitate a convenient solution for detection and monitoring.Unmanned aerial vehicles(UAVs)have recently emerged as a tool for algal bloom detection,efficiently providing on-demand images at high spatiotemporal resolutions.This study developed an image processing method for algal bloom area estimation from the aerial images(obtained from the internet)captured using UAVs.As a remote sensing method of HAB detection,analysis,and monitoring,a combination of histogram and texture analyses was used to efficiently estimate the area of HABs.Statistical features like entropy(using the Kullback-Leibler method)were emphasized with the aid of a gray-level co-occurrence matrix.The results showed that the orthogonal images demonstrated fewer errors,and the morphological filter best detected algal blooms in real time,with a precision of 80%.This study provided efficient image processing approaches using on-board UAVs for HAB monitoring.

Application of Stork Optimization Algorithm for Solving Sustainable Lot Size Optimization

The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.

Application of Power Electronics and Control for Dual Battery Packs Management with Voltage Balancing and State of Charge Estimation

Energy storage, such as lead acid batteries, is necessary for renewable energy sources’ autonomy because of their intermittent nature, which makes them more frequently used than traditional energy sources to reduce operating costs. The battery storage system has to be monitored and managed to prevent serious problems such as battery overcharging, over-discharging, overheating, battery unbalancing, thermal runaway, and fire dangers. For voltage balancing between batteries in the pack throughout the charging period and the SOC estimate, a modified lossless switching mechanism is used in this research’s suggested battery management system. The OCV state of charge calculation, in the beginning, was used in conjunction with the coulomb counting approach to estimate the SOC. The results reveal that correlation factor K has an average value of 0.3 volts when VM ≥ 12 V and an average value of 0.825 when VM ≤ 12 V. The battery monitoring system revealed that voltage balancing was accomplished during the charging process in park one after 80 seconds with a SOC difference of 1.4% between Batteries 1 and 2. On the other hand, the system estimates the state of charge during the discharging process in two packs, with a maximum DOD of 10.8 V for all batteries. The project’s objectives were met since the BMS estimated SOC and achieved voltage balance.

Progress of Materials and Devices for Neuromorphic Vision Sensors

The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated components such as sensors,memory,and processing units.As a prime example,the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits,such as simpler circuitry,lower power consumption,and less data redundancy.(2)Swifter:Owing to the nature of physics,smaller and more integrated devices can detect,process,and react to input more quickly.In addition,the methods for sensing and processing optical information using various materials(such as oxide semiconductors)are evolving.(3)Smarter:Owing to these two main research directions,we can expect advanced applications such as adaptive vision sensors,collision sensors,and nociceptive sensors.This review mainly focuses on the recent progress,working mechanisms,image pre-processing techniques,and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.

Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines

As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification.For this purpose,a novel model-independent nonsingular terminal slidingmode control(MINTSMC)using the basic principles of the ultralocal model(ULM)and combined with the single input interval type-2 fuzzy logic control(SIT2-FLC)is developed for non-linear wind turbine pitch angle control.In the suggested control framework,the MINTSMC scheme is designed to regulate the wind turbine speed rotor,and a sliding-mode(SM)observer is adopted to estimate the unknown phenomena of the ULM.The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error.Extensive examinations and comparative analyses were made using a real-time softwarein-the-loop(RT-SiL)based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested modelindependent scheme in a real-time testbed.

Synthesis and characterization of boron-doped NiO thin films pro-duced by spray pyrolysis

Boron-doped NiO thin films were prepared on glass substrates at 400℃ by airbrush spraying method using a solution of nickel nitrate hexahydrate. Their physical properties were investigated as a function of dopant concentration. From X-ray diffraction patterns, it is observed that the films have cubic structure with lattice parameters varying with boron concentration. The morphologies of the films were examined by using scanning electron microscopy, and the grain sizes were measured to be around 30-50 nm. Optical measurements show that the band gap energies of the films first decrease then increase with increasing boron concentration. The resistivities of the films were determined by four point probe method, and the changes in resistivity with boron concentration were investigated.

A Study on Microstructural and Mechanical Properties of a Stir Cast Al(SiC-Mg-TiFe)Composite

Development of metal matrix composite is becoming widespread in most engineering applications where excellent mechanical properties are required.Mechanical and microstructural properties of aluminium reinforced with silicon carbide was investigated.Ingot of aluminium was melted in a furnace at temperature ranging between 650-700℃.Ferrotitanium and silicon carbide were preheated in a muffle furnace before addition to molten aluminium in a crucible furnace.Fixed proportions of magnesium,ferrotitanium and varying proportions of silicon carbide were utilized as reinforcements.Stirring was carried out manually for a minimum of 10 mins after the addition of each weight percent of silicon carbide.Resulting as-cast samples were sectioned for various mechanical and microstructural analysis.Microstructural studies from optical microscopy and scanning electron microscopy(SEM)showed the dispersion of reinforcements in the aluminium matrix.Mechanical properties which includes hardness and tensile strength of fabricated composites were observed to increase,while XRD analysis showed various phases formed from reaction between the matrix and reinforcements.

Analysis of Nonlinear Electrical Circuits Using Bernstein Polynomials

In electrical circuit analysis, it is often necessary to find the set of all direct current （d.c.） operating points （either voltages or currents） of nonlinear circuits. In general, these nonlinear equations are often represented as polynomial systems. In this paper, we address the problem of finding the solutions of nonlinear electrical circuits, which are modeled as systems of n polynomial equations contained in an n-dimensional box. Branch and Bound algorithms based on interval methods can give guaranteed enclosures for the solution. However, because of repeated evaluations of the function values, these methods tend to become slower. Branch and Bound algorithm based on Bernstein coefficients can be used to solve the systems of polynomial equations. This avoids the repeated evaluation of function values, but maintains more or less the same number of iterations as that of interval branch and bound methods. We propose an algorithm for obtaining the solution of polynomial systems, which includes a pruning step using Bernstein Krawczyk operator and a Bernstein Coefficient Contraction algorithm to obtain Bernstein coefficients of the new domain. We solved three circuit analysis problems using our proposed algorithm. We compared the performance of our proposed algorithm with INTLAB based solver and found that our proposed algorithm is more efficient and fast.

Investigation and Comparison of Two Models in Galvanic Coupling Intra-body Communications

Intra-body communication (IBC) is a new,emerging,short-range and human body based communication methodology.It is a technique to network various devices on human body,by utilizing the conducting properties of human tissues,suitable for currently fast developing Body area network (BAN)/Body sensor network (BSN).IBC is believed to have advantages in power consumption,electromagnetic radiation,interference from external electromagnetic noise,security,and restriction in spectrum resource.In this article,the authors develop two models,which are analytical and empirical approaches,for comparing the performance and accuracy of IBC on a human limb.Through in vivo experiment of five volunteers,both models basically match with the experimental result with equivalent circuit model superior than electromagnetic model in term of maximum error.