Electrical Circuit Research Articles

J-A Approach to Simulations of HTS Tapes: How to Couple With Electric Circuits

J-A Approach to Simulations of HTS Tapes: How to Couple With Electric Circuits

Increase the operational reliability of the electric drive of the weaving machine

The main purpose of this research work is to analyze malfunctions, power consumption, engine overheating and vibrations based on the loadings of electrical circuits through artificial neural networks. The reliability of artificial intelligence systems was proven on the basis of a model-based system depending on the task, and the obtained values were experimentally compared in the electrical operation of existing equipment in general industrial enterprises. An imitation model of the real object was developed. A concept of increasing productivity was set up to identify malfunctions, in contrast to the existing annular method. The article developed an algorithm for increasing the operational reliability of the electrical operation of the weaving machine on the basis of integrated indicators of excitation to determine the probability of failure of electrical operation. The article proposes the possibility of directly processing the diagnostic energy parameters through artificial neural networks. An experimental combination of signals resulted in a model based on input power and torque, and was based on an asynchronous motorized electrical circuit. It has been proven that intellectual reliability can be increased by 3-5% compared to operational reliability in traditional methods.

Development of stability charts for double salience reluctance machine modeled using hill’s equation

The paper presents a novel algorithm for the development of stability charts. The second-order differential homogeneous equation describing a double salient reluctance machine with a capacitance connected to its stator winding is transformed into hill’s equation. The circuit components are the stator coil time-varying inductance of a double salient reluctance machine, capacitance and resistance. All these are modeled by hill’s equation. The double salient reluctance machine acts as an energy conversion system. The maximum and minimum inductance of the energy conversion system is measured in laboratory by inductance, capacitance, and resistance (LCR) meter. These values help to determine the inductance modulation index. The inductance modulation indetx, the characteristic constant and the characteristic parameter obtained from modeling equations are used in the MATLAB/Simulink model. The MATLAB/Simulink simulations generate stable and unstable oscillations to form stability charts. The proposed stability charts are in good agreement with the Ince-Stritt stability chart, which is widely applied in physics, mechanics and in electrical engineering, especially where the state of stability of a system or an electric oscillatory circuit is to be determined.

3D Hybrid modeling for the ultrasonic phased array inspection of porosity in heavy plates: Simulation and experimental validation

Quantitative NDT modeling and simulation tools are important in design and fabrication of ultrasonic phased array probes with optimum characteristics and reduce the number of experimental efforts and development time. In order to achieve high accuracy (Amplitude deviation < 1 dB) with a low computational time in the simulation, the modeling tools require not only the high-frequency approximation of the ultrasonic wave propagation but also the high-precision electro-acoustic coupling model. This paper describes a computationally efficient 3D time-dependent hybrid model for the simulation of ultrasonic phased array inspection of porosity in heavy plates. This method combines the results of both 3D finite element analysis (PZFLex-FEA) and the semi-analytical ultrasonic simulation “Ray-Tracing”. As a first step, we demonstrate the FEA modeling of an ultrasonic phased array probe, which includes the full 1-3 piezocomposite design with the arrangement of array elements, conducting electrodes, multi-phase backing material, acoustical matching layer and electrical circuit of a 50 Ohm coaxial cable. In the current FEA simulation, we considered the acoustical and electrical cross-talk between the adjacent elements of an ultrasonic array sensor. In the second step, the FEA-simulated ultrasonic pulse-echo signal and its frequency spectrum of an array element in the farfield region are further used as the reference input signal in the CIVA-UT software to simulate the imaging of porosity in heavy plates, quantitatively. The design of the 3D wedge-geometry of the application specific array sensor is modeled and optimized using the CIVA raytracing and multi-phase backing models. The real excitation pulse of the industrial ultrasonic testing equipment “ROMIS (ROSEN Modular Inspection System)” is also included in the simulation to achieve high accuracy in the current hybrid modeling. The dependency of the detectability of the porosity on the frequency of the array sensor and the active element group so-called “Virtual Probe” are quantitatively analyzed. Finally, the 3D hybrid model simulated Time Corrected Gain (TCG) curves of the porosity like defects in the reference steel plates are compared with the real experiments and a good quantitative agreement is achieved.

Electric vehicle and photovoltaic advanced roles in enhancing the financial performance of a manufacturing and commercial setup

Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network.

Modeling Excitable Cells with Memristors

This paper presents an in-depth analysis of an excitable membrane of a biological system by proposing a novel approach that the cells of the excitable membrane can be modeled as the networks of memristors. We provide compelling evidence from the Chay neuron model that the state-independent mixed ion channel is a nonlinear resistor, while the state-dependent voltage-sensitive potassium ion channel and calcium-sensitive potassium ion channel function as generic memristors from the perspective of electrical circuit theory. The mechanisms that give rise to periodic oscillation, aperiodic (chaotic) oscillation, spikes, and bursting in an excitable cell are also analyzed via a small-signal model, a pole-zero diagram of admittance functions, local activity, the edge of chaos, and the Hopf bifurcation theorem. It is also proved that the zeros of the admittance functions are equivalent to the eigen values of the Jacobian matrix, and the presence of the positive real parts of the eigen values between the two bifurcation points lead to the generation of complicated electrical signals in an excitable membrane. The innovative concepts outlined in this paper pave the way for a deeper understanding of the dynamic behavior of excitable cells, offering potent tools for simulating and exploring the fundamental characteristics of biological neurons.

FEM-Circuit co-simulation of superconducting synchronous wind generators connected to a DC network using the homogenized J–A formulation of the Maxwell equations

High-temperature superconductors (HTS) are greatly appealing for the development of high efficient, and high energy density power devices. They are particularly relevant for applications requiring light and compact machines such as wind power generation. In this context, to ensure the proper design of the superconducting machines and their reliable operation in power systems, it is then important to develop models that can accurately include their physics but also can describe properly their interaction with the system. To achieve such a goal, one approach is the co-simulation. This numerical technique can bring fine geometrical and physical details of the machines through a finite element model (FEM) meanwhile dealing with the operation of the whole system that incorporates the machine and a subset of the power grid represented by an external electrical circuit. The goal of the present work is to put to use this numerical technique when superconducting components are involved. Here, a case study is proposed involving a 15 MW hybrid superconducting synchronous generator (HTS rotor and conventional stator) coupled to a direct current network via a rectifier and its associated filter. The case study related to wind power application allows grasping the technical issues when employing co-simulation dealing with HTS machines. The FEM of the generator is done in the commercial software COMSOL Multiphysics, which interacts with the circuit simulator Simulink through the built-in Functional Mock-up Unit. For the present study, a new version of the latest J–A formulation combined with homogenization technique is introduced allowing an even faster computation time compared to the T–A formulation. Distributed variables and global variables such as current density, magnetic flux density, and local losses for the former and voltage, current, electromagnetic torque, and power quality for the latter are estimated and compared for both formulations. The idea is to find the best-suited combination FEM-circuit under criteria of computational speed, accuracy, and numerical stability. Thus, it is shown that all formulations generate an error of less than 5% on the machine parameters and that the J–A formulation with first order elements stands out with a significant 4-fold reduction in computational costs.

Enhancing grid resiliency in distributed energy systems through a comprehensive review and comparative analysis of islanding detection methods

Reduction of fossil fuel usage, clean energy supply, and dependability are all major benefits of integrating distributed energy resources (DER) with electrical utility grid (UG). Nevertheless, there are difficulties with this integration, most notably accidental islanding that puts worker and equipment safety at risk. Islanding detection methods (IDMs) play a critical role in resolving this problem. All IDMs are thoroughly evaluated in this work, which divides them into two categories: local approaches that rely on distributed generation (DG) side monitoring and remote approaches that make use of communication infrastructure. The study offers a comparative evaluation to help choose the most efficient and applicable IDM, supporting well-informed decision-making for the safe and dependable operation of distributed energy systems within electrical distribution networks. IDMs are evaluated based on NDZ outcomes, detection duration, power quality impact, multi-DG operation, suitability, X/R ratio reliance, and efficient functioning.

Influence of proteins on the dielectric characteristics of 5CB and 8CB liquid crystals

ABSTRACT In this paper, we study the influence of the protein Bovine Serum Albumin (BSA) on the dielectric properties of liquid crystals (LCs) such as 4-cyano-4-pentyl biphenyl (5CB) and Octyl-4-biphenylcarbonitrile (8CB). Studying the effect of proteins on the dielectric properties of LC is essential for both fundamental research and practical applications in material science, biomedical engineering, biotechnology, and optoelectronic devices. It helps understand the protein behaviour on the surface of LCs, which offers an opportunity to develop novel sensing platforms. A polarising optical microscope (POM) was used to examine the correlation between textures formed by LCs interacting with different concentrations of BSA. In the dielectric studies, dielectric parameters such as impedance (Z), real (Z’) and imaginary (Z’’) parts of the impedance, and the tangential loss (tan δ) were measured. The investigation involved analysing relaxation times using the collected data, revealing distinct behaviours between 5CB and 8CB liquid crystals. Bode and Nyquist’s plots were constructed and analysed to investigate the changes LCs undergo while interacting with BSA. An equivalent electrical circuit (EEC) was constructed using Bode and Nyquist data, from which circuit element values were successfully extracted. The results obtained from the POM studies and the interferences drawn from the EIS can help enhance the performance of protein-based liquid crystal devices.

Prioritising SCADA (Supervisory et al.) Integration at key points Using Fuzzy AHP and TOPSIS Methods (Study Case at PLN UP2D Makassar)

PLN UP2D Makassar regulates the 20 kV electrical distribution network in South Sulawesi, Southeast Sulawesi, and West Sulawesi. PLN UP2D Makassar holds a management contract, which is SCADA integration. Based on the Network Database Book, in 2023, there were 128 key points (LBS and reclosers) that were not yet integrated with SCADA or not online with the Master SCADA. The current issue identified in making decisions on SCADA integration to critical points in PLN UP2D Makassar is using the crucial point ratio Value per PLN UP3 criteria. The weakness of this method is that SCADA integration at key points does not consider the benefits and impacts of SCADA integration, such as the improvement of SAIDI and ENS. This study aims to create guidelines for decision-making on SCADA integration at critical points. This research involves five experts in PLN UP2D Makassar. A total of 6 criteria were established and processed using the Fuzzy AHP TOPSIS method to rank the 128 key points that will be integrated with SCADA. The Fuzzy AHP TOPSIS calculation results have been validated with a consistency ratio of -0.008 (consistent) and sensitivity analysis (10% increase/decrease in criteria weight). This means that the proposed six criteria can be used to rank alternative vital points that will be integrated with SCADA.

Influence of the magnetic flux on the dynamics of a self-sustaining system: analytical, numerical and analogical investigations

This paper investigates the nonlinear dynamics of a ferroelectric enzyme-substrate reaction modeled by the birhythmic van der Pol oscillator coupled to the magnetic flux. We derive the equilibrium points and study their stability. We analyze some bifurcation structures and the variation of the Lyapunov exponents. The phenomena of symmetric attractors and the anti-monotonicity are observed. By increasing the magnetic flux, we find that the equilibrium points are stable, tends to control chaotic regimes, and affects regular and quasi-regular ones. As the magnetic flux increases, the amplitude of the oscillations around the equilibrium points decreases and the amplitude of the limit cycles at the Hopf bifurcation tends to disappear. Further increasing the magnetic flux gives rise to chaotic dynamics. The electrical circuit and analogical simulations are derived using the PSpice software. The agreement between analogical and numerical results is acceptable.

Zirconia Dental Implants Surface Electric Stimulation Impact on Staphylococcus aureus

Tooth loss during the lifetime of an individual is common. A strategy to treat partial or complete edentulous patients is the placement of dental implants. However, dental implants are subject to bacterial colonization and biofilm formation, which cause an infection named peri-implantitis. The existing long-term treatments for peri-implantitis are generally inefficient. Thus, an electrical circuit was produced with zirconia (Zr) samples using a hot-pressing technique to impregnate silver (Ag) through channels and holes to create a path by LASER texturing. The obtained specimens were characterized according to vitro cytotoxicity, to ensure ZrAg non-toxicity. Furthermore, samples were inoculated with Staphylococcus aureus using 6.5 mA of alternating current (AC). The current was delivered using a potentiostat and the influence on the bacterial concentration was assessed. Using AC, the specimens displayed no bacterial adhesion (Log 7 reduction). The in vitro results presented in this study suggest that this kind of treatment can be an alternative and promising strategy to treat and overcome bacterial adhesion around dental implants that can evolve to biofilm.

SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards.

Transmission line earthing system; Advanced design diagram for safety compliance

An electrical high-voltage power system is essential to support everyday electrical demands. Due to the increase in electrical loads, a more rigid design is required to ensure system compliance with standards and policies. High-voltage safety is the number one priority when it comes to the design, installation, commissioning, and operation of the electrical power system network. Safety compliance is getting more complex due to the joining infrastructure between residential and high-voltage projects. Nowadays, high-voltage infrastructure, including substations and transmission lines, is constructed near residential properties. This neighboring setup increased the safety concerns of high voltage systems, especially under fault or system malfunction situations. Safety concerns are addressed during the design stage and verified during the commissioning stages.The paper discusses the minimum transmission line earthing system requirements. This document provides a clear and consistent approach to assess transmission line earthing system design. The work contents comply with current IEEE standards including rigid author research outcomes. The works reduce the complexity of the assessment and explain the critical role of different sectors within the transmission line network. The work introduces the boundaries when the fault current analysis should include the earth grid resistance. A case study is also included.

Application of Improved Ant Colony Algorithm in Optimizing the Charging Path of Electric Vehicles

In current traffic congestion scenarios, electric vehicles (EVs) have the problem of reduced battery life and continuous decline in endurance. Therefore, this study proposes an optimization method for electric vehicle charging scheduling based onthe ant colony optimization algorithm with adaptive dynamic search (ADS-ACO), and conducts experimental verification on it. The experiment revealed that in the four benchmark functions, the research algorithm has the fastest convergence speed and can achieve convergence in most of them. In the validation of effectiveness, the optimal solution for vehicle time consumption under the ADS-ACO algorithm in the output of the algorithm with a stationary period and a remaining battery energy of 15 kW·h was 2.146 h in the regular road network. In the initial results of 15 kW·h under changes in road conditions from peak to peak periods, the total energy consumption of vehicles under the research algorithm was 4.678 kW·h and 4.656 kW·h under regular and irregular road networks, respectively. The change results were 4.509 kW·h and 4.656 kW·h, respectively. The initial results of 10 kW·h were 4.755 kW·h and 4.873 kW·h, respectively. The change results were 4.461 kW·h and 4.656 kW·h, respectively, which are lower than the comparison algorithm. In stability verification, research algorithms can find the optimal path under any conditions. The algorithm proposed in the study has been demonstrated to be highly effective and stable in electric vehicle charging path planning. It represents a novel solution for electric vehicle charging management and is expected to significantly enhance the range of electric vehicles in practical applications.

Design of Approximate Tree Multiplier Using Approximate Compressor for Image Processing Applications

Approximate computing enables high performance and efficiency of execution by using the overhead on compute units of a processor to give high speed. The speed and system delay are inversely proportional, necessitating massive parallel processes with massive hardware and power dissipation. Energy and area-efficient systems can be realized by reducing system accuracy and dependability. Approximate computing techniques can be used to reduce the number of computing resources needed for a given task and improve the performance of a system. This can be accomplished by lowering a computational model's accuracy and decreasing complexity, reducing power consumption, latency, and area requirements. This study examines an electrical circuit that performs multiplication of two equal integers and it proposes the use of a carry-in adder with two approximation compressors to reduce the size, latency, and power consumption while maintaining the same level of accuracy as current designs. The suggested algorithms were implemented in Xilinx Vivado and their effectiveness was evaluated using numerical performance metrics, including error rate, power consumption, delay, and power delay product in output result. The compressors suggested are used to implement 8 × 8 and 16 × 16 Dadda multipliers that perform comparably to state-of-the-art approximation multipliers.

A hybrid optimization approach for strategically placing electric vehicle charging stations in a radial distribution IEEE-33 bus system

Abstract The main objective of this study is to demonstrate the effectiveness of using Hybrid Particle Swarm Optimization (HPSO), a unique methodology, to optimize an IEEE-33 bus system for optimal placement of electric vehicles. This methodology has been specifically designed to effectively regulate voltage fluctuations while reducing power dissipation. The exploration capabilities of PSO and the exploitation capabilities of SA make HPSO a robust algorithm for a specific objective function. HPSO has shown superior performance compared to current traditional methods after careful study. Simulation results illustrate power loss reductions ranging from 1.01% to 8.21% compared to various metaheuristic methodologies. The inclusion of this approach demonstrates that combining the capabilities of PSO and SA facilitates the development of a highly efficient optimization framework by combining their stochastic search and fast convergence capabilities. This methodology not only sets innovative benchmarks for power system development, but also represents a significant paradigm shift in managing and improving durable and efficient electrical networks.

Assembled MXene-Liquid Metal Cages on Silicon Microparticles as Self-Healing Battery Anodes.

In pursuit of higher energy density in lithium-ion batteries, silicon (Si) has been recognized as a promising candidate to replace commercial graphite due to its high theoretical capacity. However, the pulverization issue of Si microparticles during lithiation/delithiation results in electrical contact loss and increased side reactions, significantly limiting its practical applications. Herein, we propose to utilize liquid metal (LM) particles as the bridging agent, which assemble conductive MXene (Ti3C2Tx) sheets via coordination chemistry, forming cage-like structures encapsulating mSi particles as self-healing high-energy anodes. Due to the integration of robust Ti3C2Tx sheets and deformable LM particles as conductive buffering cages, simultaneously high-rate capability and cyclability can be realized. Post-mortem analysis revealed the cage structural integrity and the maintained electrical percolating network after cycling. This work introduces an effective approach to accommodate structural change via a resilient encapsulating cage and offers useful interface design considerations for versatile battery electrodes.

#2795 In-silico assessment of arteriovenous fistula maturation with patient-specific computational hemodynamic models

Abstract Background and Aims Native arteriovenous fistula (nAVF) is the preferred access for haemodialysis (HD) treatment. Both the quality and complications of the haemodialysis technique are closely related to vascular access. nAVF maturation process includes several morphological changes affecting haemodynamics, with previous studies suggesting that it is highly related to AVF failure. Computational Fluid Dynamics (CFD) simulations by using idealized morphologies or the analysis of one patient-specific geometry have been proposed to understand the pathophysiology of maturation failure. However, it is difficult to correlate with clinical practice and therefore limits its use. The aim is to develop a patient-specific modelling time pipeline, incorporating the haemodynamics of the blood flow to real anatomical and morphological characteristics. Method Design: prospective computational simulation analysis of nAVF in 3 patients at 3 different stages: after fistula creation, (1 week), maturation (1 month) and post-maturation (6 months). Analysis: morphological and haemodynamic. Inclusion criteria: >18 years and end-stage chronic kidney disease. Variables and data: Once morphology was extracted from nAVF magnetic resonance imaging, generated meshes were refined and compiled to obtain a volumetric mesh. The boundary conditions of the model were defined and extracted using ultrasound nAFV data. Data were analyzed at the 3 stages. Models: A 3-element Windkessel model was used to simulate the pressure waveform to feed the vein of the system. In this model, clinical data were also considered to classify the patient as normotensive or hypertensive to estimate waveform parameters. The Windkessel model estimates wall shear stress (WSS), velocity and flow for all the points located in the mesh by making an analogy from an electric circuit resistance model. As validation, the flow obtained from the Windkessel model was compared with the one obtained from the ultrasound scan of the patient. Results Different temporal points were analyzed for each nAVF. Results from the simulations in Fig. 1, illustrating the evolution over time and development. The geometrical characteristics were found to significantly impact on flow dynamics. The area most affected by flow was the juxta-anastomotic section which showed higher magnitude distribution of WSS and velocity for all time-points. According to the analysis of the simulations, a perpendicular junction between the vein and the artery potentially resulted in less damage in this area (in WSS terms), being important to mitigate the AVF failure. At maturation stage (1 month) the analysis shows WSS distribution mainly located in the juxta-anastomotic section and decreased in magnitude regarding one week; therefore, this can be marked as the stabilization point for nAFV maturation. Conclusion

Path Optimisation of Electric Vehicles for Collection and Delivery based on Intelligent Waste Bins

This paper proposes a dynamic electric vehicle path optimization method for intelligent garbage collection and transportation systems to address the increasing uncertainty of urban household waste and the carbon emissions caused by vehicles in traditional garbage collection and transportation processes. With the goal of minimizing total cost and maximizing garbage collection and transportation, adjust the soft time window in a timely manner based on whether the amount of garbage generated by the intelligent garbage bin reaches the collection and transportation threshold. Taking into account the position of the garbage bin to be cleared, the position of the garbage collection and transportation vehicle, the amount of electricity, and the loading capacity, dynamically adjust the vehicle path. Due to the fact that genetic algorithms require a long time to converge to an acceptable solution, this paper uses greedy genetic algorithms to comprehensively utilize their advantages in local search and global search capabilities to achieve faster convergence solutions. The research results indicate that compared with traditional static garbage collection and transportation modes, dynamic garbage collection and transportation schemes can reduce total costs and increase garbage collection and transportation volume, and reasonable planning of the path of electric collection and transportation vehicles can effectively reduce carbon emissions. Finally, the effectiveness and efficiency of the algorithm were verified through comparative analysis of numerical examples.