Optimal System Parameters Research Articles

Parameter Optimization of the Power and Energy System of Unmanned Electric Drive Chassis Based on Improved Genetic Algorithms of the KOHONEN Network

For unmanned electric drive chassis parameter optimization problems, an unmanned electric drive chassis model containing power systems and energy systems was built using CRUISE, and as the traditional genetic algorithm is prone to falling into the local optima, an improved isolation niche genetic algorithm based on KOHONEN network clustering (KIGA) is proposed. The simulation results show that the proposed KIGA can reasonably divide the initial niche populations. Compared with the traditional genetic algorithm (GA) and the isolation niche genetic algorithm (IGA), KIGA can achieve faster convergence and a better global search ability. The comprehensive performance of the unmanned electric drive chassis in terms of power and economy was increased by 8.26% with a set of better solutions. The results show that simultaneous power system and energy system parameter optimization can enhance unmanned electric drive chassis performance and that KIGA is an efficient method for optimizing the parameters of unmanned electric drive chassis.

Multi-objective optimization of MQL system parameters for the roller burnishing operation for energy saving, product quality and air pollution

Multi-objective optimization of MQL system parameters for the roller burnishing operation for energy saving, product quality and air pollution

Relevance of Robustness and Uncertainties Analysis in the Optimal Design of Wave Energy Converters

The optimisation design of Wave Energy Converters (WEC) to reduce the cost of energy of the technology is a widely investigated topic. In literature classical optimisation strategies have been presented and applied to identify the optimal system parameters of WECs to optimise specific techno-economic metrics. The performance of the optimal identified devices relies on these nominal parameters and it can be strongly affected by construction and modelling uncertainties. In this context, the concept of robustness of the optimal solution plays a relevant role in the identification of a device whose performance is affected as little as possible by uncertainties of various kinds. In the first part of this paper different declinations of robustness concept are derived from other fields of application and described. The identified robustness indexes are then applied to optimal solutions obtained via classical optimisation to evaluate its importance in the design process of WECs.
 Strictly related to this kind of methodology is the Sensitivity Analysis (SA) technique, it aims to investigate how the input variation (due to uncertainties or external noise or additional environmental parameters) influences the output results of a defined numerical model and highlight the relative input parameters relevance. Sensitivity Analysis, therefore, can be a valuable tool applicable in the uncertainty set estimation to identify the variables most subject to such uncertainties and their prominence.
 The main objective of the work is to underline the importance of introduce the robustness evaluation of WECs during the optimisation process since classical optimisation techniques can lead to solutions that are affected by uncertainties.

Multi‐Objective Optimization Design of Vacuum Interrupter Structure Based on Improved Artificial Jellyfish Search Algorithm

An improved multi‐objective optimization method based on artificial jellyfish search algorithm is proposed to solve the multivariable and multi‐objective optimization problem of vacuum interrupter with mutual coupling of structural parameters and mutual restriction of performance indexes. The finite element model of 40.5 kV/31.5kA vacuum interrupter is established. The structural parameters of seven important parts such as contact diameter and contact sheet thickness in vacuum interrupter are taken as optimization variables. The optimization objective is to maximize the longitudinal magnetic field strength and minimize the conductor resistance at the peak breaking short‐circuit current of vacuum interrupter. The artificial jellyfish search algorithm is improved on the population position initialization strategy and the population mutation cross‐update strategy. The Pareto front solution of the structural parameters of the vacuum interrupter is obtained by the joint simulation of finite element analysis and numerical calculation software. Finally, the multi‐parameter and multi‐objective optimization design of vacuum interrupter structure is realized. The comprehensive performance index is introduced into the optimal parameter group of jellyfish on the Pareto front. Under the constraint of weight variables, the optimal structural parameters of contact system are obtained. The axial magnetic induction intensity of the optimized vacuum interrupter contact is increased by 13.2%, and the conductor resistance is reduced by 25.4%. The comprehensive performance of vacuum interrupter is improved by 17.8%, and the stability and reliability of the power system are further improved. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Mitigating jacket offshore platform vibration under wave loadings utilising nonlinear energy sinks

ABSTRACT The random vibrations of jacket offshore platforms caused by wave loadings can reduce the service life and fatigue failure of the offshore platforms. The nonlinear energy sink (NES) has great application potential because of its lightweight, high robustness and wide frequency band of vibration attenuation. The NES is introduced to mitigate the vibrations of the jacket offshore platform as a passive control device under wave loadings. The dynamic model of jacket platforms is developed with the NES system. The optimal parameters of the NES system are obtained by exhaustive search method. The results show that the NES system can effectively mitigate the responses of the deck level of jacket platforms under different wave states. The NES system could reduce the response under various deck's mass and stiffness of jacket platforms. The present study proves the feasibility of the NES system in the application of vibration control for marine structures.

Multi-Parameter and Multi-Objective Optimization of Occupant Restraint System in Frontal Collision

To solve the constraints of multi-objective optimization of the driver system and high nonlinear problems, according to the relevant dimensions of a car, we build a simulation model with Hybrid III 50th dummy driver constraint system. The comparison of the driver mechanics index of the experimental data with the simulation data in the frontal crash shows that the accuracy of simulation model meets the requirements. The optimal Latin test design is adopted, and the global sensitivity analysis of the design parameters is carried out based on the Kriging model. The four most sensitive parameters are selected, and the parameters are solved by a multi-island genetic algorithm. And then the nonlinear programming quadratic line (NLPQL) algorithm is used to search for accurate optimization. The optimal parameters of the occupant restraint system are determined: the limiting force value of force limiter 2 985.603 N, belt extension 12.684%, airbag point explosion time 27.585 ms, and airbag vent diameter 27.338 mm, with the weighted injury criterion (WIC) decreased by 12.97%, the head injury decreased by 22.60%, and the chest compression decreased by 7.29%. The results show that the system integration of passive safety devices such as seat belts and airbags can effectively protect the driver.

Stability analysis and control parameter optimization of multi-VSG parallel grid-connected system

The virtual synchronous generator (VSG) is emerging as an attractive solution for controlling the grid-connected inverter when the renewable energy has a high penetration level into the grid. This study delves into the stability analysis and parameter optimization of multi-VSG parallel grid-connected systems. Consequently, a small-signal model (SSM) for the multi-VSG parallel grid-connected system is developed to facilitate system analysis. Utilizing this model, the feasible parameter regions are determined by applying the Routh-Hurwitz criterion, enabling the identification of key factors contributing to the system's oscillation mode. Subsequently, a time-domain model is employed to ascertain the dynamic feasible region index, which aids in delineating the scope of parameter optimization. Furthermore, the impact of deviation angle, damping, and eigenvalues on system stability is incorporated into the construction of the objective function. To optimize system parameters within the feasible region, the simulated annealing-particle swarm optimization algorithm (SA-PSO) is utilized. The effectiveness of the theoretical analysis and the proposed parameter optimization method is demonstrated through simulations.

Peroxydisulfate activation using magnetic graphite intercalation compounds: A promising system for pharmaceuticals removal in treated wastewater matrix

The release of contaminants of emerging concern (CECs) from the effluents of municipal wastewater treatment plants (MWWTPs) into the environment is a major problem because of its influence on both the environment and human health. The Fenton system has been demonstrated to remove CECs from different aqueous matrices effectively. However, the Fenton system has been considered to be efficient at acidic pH, which hinders its application in MWWTPs. Herein, the Fenton-like oxidation catalyzed by iron species intercalated between carbon layers of graphite (as a recyclable catalyst) was studied to remove amoxicillin, as a model pharmaceutical, from effluents of MWWTPs. Response surface methodology (RSM) was used to optimize system parameters, including catalyst loading, peroxydisulfate (PDS) dosage, and reaction time. Amoxicillin removal in the proposed system reached more than 99% by utilizing a catalyst dosage of 2 g/L and 5 mM of PDS at neutral pH. Sensitivity analysis of model parameters indicated that the amoxicillin removal was highly sensitive to the dosage of the catalyst, while the model is less sensitive to PDS dosage and reaction time. The results indicated that the PDS activation employing magnetic graphite intercalation compounds could be used as a promising system for pharmaceutical removal from MWWTP effluents.

Experimental Simulation of Decay Heat of Corium at the Lava-B Test-Bench

During the development of a severe accident at a nuclear power plant (NPP), corium is formed—a melt of core materials. A distinctive feature of corium, due to the content of fuel elements in its composition, is the presence of decay heat, which makes a significant contribution to the nature of the interaction of the corium melt with the structural materials of the reactor plant. In this regard, the decay heat should be taken into account when conducting computational studies and physical experiments. For this reason, certain requirements are imposed on the methods of simulating decay heat in the corium prototype, which relate to both the uniformity of the volume distribution and its intensity. This paper presents the results of calibration experiments to substantiate the operability of the induction heating system of the Lava-B test bench, which is used to simulate decay heat in the study of processes occurring during an accident with the NPP core meltdown. So, in order to obtain optimal characteristics of the heating system, a series of experiments was conducted on heating the graphite block in the experimental section of the Lava-B test bench. In the experiments, the capacitance of the used oscillating circuit capacitor banks and the electrical power on the inductor varied. As a result of the analysis of the data obtained, the most optimal parameters of the inductor-load simulator system were determined. In general, the performed experiments confirmed the operability of the induction heater and the possibility of its use in experimental studies of the interaction of corium with the various structural elements of the NPP reactor core at the Lava-B test bench.

Joint resource and trajectory optimization for secure UAV-based relay NOMA system

In this paper, we propose and analyze the maximal secrecy capability of an unmanned aerial vehicle (UAV)-based relay non-orthogonal multiple access system. In this system, a UAV acts as an aerial relay station to assist transmission from a source to two users in the presence of a terrestrial eavesdropper and a friendly jamming UAV. The minimum achievable secrecy rate (MASR) of two users is derived as a metric indicator to quantify the security of the system under the assumption that the location of the eavesdropper is imprecise. In order to maximize MASR, an efficient iterative algorithm is proposed to optimize system parameters, i.e., the trajectory of UAVs, transmit and jamming powers, as well as power allocation factors. Since the objective function and constraints of the total problem are non-convex, the successive convex approximation and block coordinate descent techniques are applied to find efficient approximate solutions. Simulation results demonstrate that the proposed algorithm significantly enhances the MASR of the system compared to benchmark schemes.

Optimisation of transport and technological system parameters of an agricultural enterprise in conditions of partial uncertainty

DOWNLOAD ARTICLE Optimisation of transport and technological system parameters of an agricultural enterprise in conditions of partial uncertainty Viacheslav Matsiuk, Viktoriia Opalko, Liliya Savchenko, Oleg Zagurskiy, Nadiia Matsiuk Received 07.04.2023, Revised 17.07.2023, Accepted 11.08.2023 Abstract At the stage of production of a wide range of agricultural products, to ensure the smooth operation of agricultural enterprises, it is necessary to solve the problems of fast and efficient delivery of relevant equipment, spare parts, and consumables with the rational use of available production resources. The research aims to improve the transport and technological system for the supply of orders in the form of consignments to meet the needs of the production activities of an agricultural enterprise. For this purpose, an agent-based simulation model was developed in the AnyLogic 8.7 environment using the Java compiler, since this toolkit allows simultaneously combining discrete-event and agent-based approaches. The model was implemented on the example of an enterprise of a separate subdivision of the National University of Life and Environmental Sciences of Ukraine “Agronomic Research Station”. As a result, a comprehensive, optimisation mathematical model of the supply of goods on an extensive network of road routes using the agricultural enterprise’s fleet of vehicles under conditions of partial uncertainty was obtained. In the course of experiments and calculations based on the real process of an agricultural enterprise, a range of values of the size of the truck fleet that meets the optimisation conditions has been found. It has been determined that the range of values close to the optimal size of the unloading truck fleet varies from 9 to 14 units. It has been established that the values of the optimisation criterion describing the average delivery time from the beginning of the need for an order to the moment of its delivery vary from 9.96 to 12.78 hours. The limit level of load of the transport and technological system is determined, at which the limit level of technological fault tolerance is ensured. It is 135 or more orders per year for each supplier with an estimated fleet of 12 trucks. The results of the study, such as the use of analytical tools and algorithms to optimise routes and allocate resources, can be used to improve transport efficiency, and help companies choose the most profitable and environmentally friendly routes for transportation

Assessing the Performance of a Speech Recognition System Embedded in Low-Cost Devices

The main purpose of this research is to investigate how an Amazigh speech recognition system can be integrated into a low-cost minicomputer, specifically the Raspberry Pi, in order to improve the system's automatic speech recognition capabilities. The study focuses on optimizing system parameters to achieve a balance between performance and limited system resources. To achieve this, the system employs a combination of Hidden Markov Models (HMMs), Gaussian Mixture Models (GMMs), and Mel Frequency Spectral Coefficients (MFCCs) with a speaker-independent approach. The system has been developed to recognize 20 Amazigh words, comprising of 10 commands and the first ten Amazigh digits. The results indicate that the recognition rate achieved on the Raspberry Pi system is 89.16% using 3 HMMs, 16 GMMs, and 39 MFCC coefficients. These findings demonstrate that it is feasible to create effective embedded Amazigh speech recognition systems using a low-cost minicomputer such as the Raspberry Pi. Furthermore, Amazigh linguistic analysis has been implemented to ensure the accuracy of the designed embedded speech system.

A Hybrid Mode Membrane Computing Based Algorithm with Applications for Proton Exchange Membrane Fuel Cells

Membrane computing is a branch of natural computing which has been extended to solve various optimization problems. A hybrid mode membrane-computing-based algorithm (HMMCA) is proposed in this paper to solve complex unconstrained optimization problems with continuous variables. The algorithmic framework of HMMCA translates from its distributed cell-like membrane structure and communication rule. A non-deterministic evolutionary programming method and two computational rules are applied to enhance the computational performance. In a numerical simulation, 12 benchmark test functions with different variables are used to verify the algorithmic performance. The test results and comparison with three other algorithms illustrate its effectiveness and superiority. Moreover, a case study on a proton exchange membrane fuel cell (PEMFC) system parameter optimization problem is applied to validate its practicability. The results of the simulation and comparison with seven other algorithms demonstrate its practicability.

Set of mathematical models for Bessel-Gauss beams coupling into the parabolic-index fiber under the influence of atmospheric turbulence and random jitter.

The expression of efficiency for Bessel-Gauss (BG) beams coupling into the parabolic fibers (PF) after passing through the Cassegrain antenna system is first derived. The effects of atmospheric turbulence and random jitter of the coupling lens on the efficiency are also taken into account to improve the practical applicability of our model. This article use a BG beam with a wavelength of 1550 mm and fiber with a core radius RF of 50 μm and a relative refractive index difference ζ of 0.01 for simulation testing. The optimal parameters of the antenna system are determined: the radius of the primary mirror and the secondary mirror is 8.33 cm and 1.25 cm, respectively. The coupling efficiency of BG beams of different orders reaches above 94% simultaneously when the lens's focal length is 7.8 cm. After taking into account the transmission efficiency of the antenna system, the system's total efficiency for BG beams of different orders averages 76.33%, when the transmission distance is 1 km. The results show that the same degree of turbulence and random jitter have different influences on the coupling efficiency of BG beams of different orders, and lower-order BG beams have better resistance to turbulence and jitter during propagation and coupling. Moreover, the effect of the guided mode field on the coupling efficiency and the resistance to turbulence varies for different values of mode radial index in the fiber p. The guided mode with p = 0 not only enables the BG beams of different orders to achieve the highest transmission efficiency in the coupling system almost simultaneously but also the random jitter and turbulence have less influence on the coupling efficiency of this mode. It means that the BG beams can have higher efficiency when coupled to the mode with p = 0 after long-distance transmission. This property of the fiber mode at p = 0 provides conditions for the simultaneous propagation of multiple BG beams in a parabolic fiber, which provides a theoretical basis for higher transmission capacity. This research work provides a theoretical model for the theoretical study of vortex beams and optical communication, which is beneficial for the design and application of vortex beams and has instructive meaning for practical engineering design.

Coexisting Terahertz and RF Finite Wireless Networks: Coverage and Rate Analysis

Wireless communications over Terahertz (THz)-band frequencies are vital enablers of ultra-high rate applications and services in sixth-generation (6G) networks. However, THz communications suffer from poor coverage because of inherent THz features such as high penetration losses, significant molecular absorption, and severe path loss. To surmount these critical challenges and fully exploit the THz band, we explore a coexisting radio frequency (RF) and THz finite indoor network in which THz small cells are deployed to provide high data rates, and RF macrocells are deployed to satisfy coverage requirements. Using stochastic geometry tools, we assess the performance of coexisting RF and THz networks and derive tractable analytical expressions for the coverage probability and average achievable rate. The analytical results are validated with Monte-Carlo simulations. Several insights are devised for accurate tuning and optimization of THz system parameters, including the THz bias, and the fraction of THz access points (APs) to deploy. The obtained results recognize a clear coverage/rate trade-off where a high fraction of THz AP improves the rate significantly but may degrade the coverage performance. Furthermore, the location of a user in the finite area highly affects the fraction of THz APs that optimizes its quality of service.

Simulation and Error Analysis of Methane Detection Globally Using Spaceborne IPDA Lidar

Methane (CH4) is recognized as the second most important greenhouse gas. An accurate and precise monitoring of methane gas globally has a vital role in studying the carbon cycle and global warming. The spaceborne integrated path differential absorption (IPDA) lidar is one of the most effective payload for methane detection. The simulation and optimization of the lidar system parameters can create an important base for the development of spaceborne payloads. However, previous IPDA lidar simulations have mostly used standard atmospheric models at simulation conditions, and to the best of our knowledge, there is no literature yet which applies a wavelength optimization to the IPDA system. In this study, we have investigated the relationship between the IPDA lidar system, based on wavelength optimization, and error measurement for CH4 column-averaged concentration. By selecting the wavelengths with the lowest comprehensive error as on-line and off-line, the error has been minimized by 10 ppb approximately relative to before optimization. We have proposed an IPDA simulation model at real atmospheric conditions, combining with ERA-5 reanalysis data, to simulate methane concentration globally, and present the distribution of errors. Finally, after the optimization of the lidar system parameters, we have ensured that the maximum inversion error for CH4 measurement is less than 10 ppb, to provide a reference for designing spaceborne IPDA lidar systems for high-precision CH4 column-averaged concentration detection.

System level performance analysis and parameter optimization of hydrogen production based on solid oxide electrolytic cell

The high-temperature solid oxide electrolytic cell (SOEC) is expected to be widely used in large-scale energy storage, the chemical industry, distributed energy, and other fields due to its high efficiency and cleanliness. Moreover, selecting the operation point of the SOEC system with variable load under high-temperature conditions and striking a balance between safety and efficiency are difficult. Therefore, a 3 kW SOEC system model is built following the electrochemical reaction principle and the considered system layout. Based on this, the influence of operating parameters on stack voltage and power, stack outlet temperature, system H2 production, specific energy consumption, system efficiency, and the power consumption distribution of auxiliary equipment are analyzed. Finally, the operating current, temperature, air flow, and H2O utilization rate were taken as optimization variables, and the safe range of operating parameters was taken as the constraint condition to optimize system efficiency. The results show that under the given operating conditions and assumptions, the energy efficiency of the SOEC system can be adjusted from 60 % to 100 %, and the temperature difference can be controlled within 100 ℃. The durability of the system is improved by maximally reducing the temperature difference while ensuring the high efficiency of reactor operation.

Mitigating deepwater jacket offshore platform vibration under wave and earthquake loadings utilizing nonlinear energy sinks

The random vibrations of jacket offshore platforms under wave and earthquake actions can reduce the service life and exacerbate fatigue damage of the offshore platforms. Aiming to mitigate those unwanted vibrations, this paper introduces the nonlinear energy sinks (NES) to the deep-water jacket offshore platform as a passive control device. Its coupling dynamic model is built with assumed parameters of wave and earthquake loads, and the wave forces of the platform structure are calculated by Morison's equation. Further, the optimal parameters of the NES system are obtained by an exhaustive search algorithm under the objective function. The results show that the NES system can effectively contribute to mitigating the maximum, minimum, and root mean squares (RMS) of deck-level responses of the platform structure. What's more, despite various mass or stiffness of platform structure, the NES system not only greatly reduces the response peaks, but also demonstrates a more steady phenomenon, in which the robustness is presented clearly. In this way, it strongly proves the feasibility and robustness of the NES system under wave and earthquake loadings.

CONVEYOR-TYPE SMALL HYDROPOWER PLANT FOR SHALLOW RIVER WATERS

This paper deals with the development of a small conveyor-type hydropower plant intended for operation in shallow river waters without construction of a dam. The proposed design offers a closed-shaped flattened conveyor equipped with flat-shaped blades. The conveyor is oriented perpendicular to the fluid flow. Several identical flat blades interacting with fluid flow are mounted on conveyor belt and move together with the belt in one straight line direction. Then after turning in the reversing mechanism, blades move in the opposite direction. The conveyor system has a built-in energy generator which drive shaft is connected with one of the reversing ends of the plant. Conveyor belt system dynamics analysis is performed on the base of equivalent model with one degree of freedom. The interaction of a moving conveyor flat blade in translation motion with fluid flow is studied by computer simulation with program Mathcad using a superposition principle. In accordance with this approach, a fast-chaotic motion of fluid particles (Brownian motion) is separated from the slow-directed flow motion, with the given average velocity. Optimization of system parameters (blade orientation angle to fluid flow, interaction constants of the braking generator) is performed, using a generated power as criterion. Simulation results confirm the serviceability and operational efficiency of the proposed hydropower plant in shallow river waters.

Production of biohydrogen and green platform compound 2, 5-furandicarboxylic acid using rice straw hydrolysate

Lignocellulosic hydrolysate contains several inhibitors that hinder downstream biological processes. The immobilized strain Burkholderia sp. H-2 was used in this study to biodetoxify real rice straw hydrolysate and biotransform 5-hydroxymethylfurfural (5-HMF), an inhibitor, into 2, 5-furandicarboxylic acid (FDCA), a valuable platform compound. An electrodialysis with bipolar membranes (EDBM) system was applied to recover FDCA and perform secondary detoxification of the biodetoxified real rice straw hydrolysate. The rice straw hydrolysate after biodetoxification and EDBM treatment was used for anaerobic dark fermentative hydrogen production. The immobilized Burkholderia sp. H-2 could completely biotransform 1843 mg/L 5-HMF into 1532 mg/L FDCA within 24 h when the 2-fold diluted rice straw hydrolysate was used as the feedstock. The optimal EDBM system parameters to recover FDCA were a hydrolysate pH of 6, operated at a current density of 17.86 mA/cm2. The FDCA recovery efficiency was 44.6 %, when using the biodetoxified real rice straw hydrolysate as the EDBM feedstock. The rice straw hydrolysate after biodetoxification and EDBM treatment had better biohydrogen production performance than the undetoxified and biodetoxified rice straw hydrolysates.