Multi-island Genetic Algorithm Research Articles

Research on Noise Reduction of Water Hydraulic Throttle Valve Based on RBF Neural Network and Multi-Island Genetic Algorithm

Excessive pressure drop within the internal flow channel of the water hydraulic throttle valve will generate severe noise. In order to reduce the noise of the throttle valve, in this paper, the model of the throttle valve was established, and the flow characteristics and acoustic characteristics of the valve were simulated. The simulation results showed that the parameters of the throat structure, such as the half angle, throat inlet angle and throat length, have a significant effect on the noise of the valve. Then, the three main structural parameters were used as optimization variables, and radial basis function (RBF) neural networks and multi-island genetic algorithms (MIGA) were used to reduce the noise of the valve. The approximate model of the relationship between the structural parameters of the valve and noise was established by RBF neural networks, and MIGA was used to optimize the approximate model. Finally, the optimal valve model was established based on the obtained optimal parameters, and its noise was analyzed through simulation and experiment. The research results indicated that the optimization method, which combines RBF Neural Network and MIGA, can effectively reduce the noise of hydraulic throttle valves.

Effect of parameter optimization on the flow characteristics of venturi-self-excited oscillation mixer based on response surface model and multi-island genetic algorithm

Effect of parameter optimization on the flow characteristics of venturi-self-excited oscillation mixer based on response surface model and multi-island genetic algorithm

Parametric optimization of rearview mirror structure based on a multi-island genetic algorithm

To quickly find the structural parameters of a particular mirror that produces the least amount of aerodynamic noise, the rearview mirror of a passenger car is taken as the research object and an optimization platform is established based on Isight software in this paper. The mirror structure is parameterized in Sculptor, and several sample models are constructed using the optimal Latin hypercube design (OLHD). Then, by simulating each sample model, the sound pressure level of the Curle source at the side window surface monitoring point was obtained. The relationship between the mirror structure and the wind noise at the point is fitted using the Kriging approximation model after the calculation is completed. Finally, the values at each point decreased when the changes at positions 1, 2, 3, and 4 were 2.5 mm, 3.91 mm, 4.5 mm, and 3.6 mm, and the sound pressure level at monitoring point 4 decreased the most, with a reduction of 3.76 dB in wind noise compared with the original model.

Numerical prediction and optimization of aerodynamic noise of straw crushers by considering the straw-crushing process

Straw crops are struck and broken into soft filaments by the high-speed rotating hammers of straw crushers, which disturb the internal airflow field and generate much noise during the operation of straw crushers. To accurately estimate and reduce the aerodynamic noise of straw crushers at the design stage, in this study, first, the coupling method of the discrete element method, bonded-particle model, and computational fluid dynamics were used to obtain the acoustics source data. Next, the Ffowcs Williams–Hawkins theory and the indirect boundary element method were used to predict the aerodynamic noise generated during the straw crushing process. The multi-island genetic algorithm was used to optimize the aerodynamic noise of straw crushers. The results indicate that the simulated and measured total sound pressure levels (TSPLs) at the outlet and inlet differed by 1.43 and 2.12 dB(A), respectively. Additionally, aerodynamic noise at the inlet appears to be primarily influenced by the sound pressure level at the excitation fundamental frequency, while noise at the outlet is primarily influenced by the sound pressure level at the double frequency. Higher sound pressure levels were mainly concentrated at the fundamental frequency and its lower harmonic frequencies, and the sound pressure level gradually decreased with the increase in the frequency. After optimization, the aerodynamic noise TSPL at the inlet decreased from 100.87 to 88.58 dB(A) and at the outlet decreased from 102.26 to 89.62 dB(A). This study provides a methodological reference for aerodynamic noise prediction and the design of low-noise straw crushers.

Inverse parameter identification framework for cohesive zone models based on multi-island genetic algorithm

Composite interfaces are commonly simulated by cohesive zone models with the key challenge being the calibration of interfacial parameters. A novel inverse identification framework is presented in this paper to determine the interface parameters of cohesive zone models. This approach employs the multi-island genetic algorithm to obtain the key parameters of cohesive zone model which can reproduce the experimental observations. Utilizing two independent metrics, namely the load-displacement response and the debonding length history, an objective function is formulated to give the framework inherent robustness. The interface debonding length is used to uniquely determine the debonding properties of the specimen. To demonstrate the feasibility of the proposed framework, the strength-based cohesive zone model is taken as an example. The inverse algorithm is adopted to identify the interface parameters of both the double cantilever beam (DCB) experiments and the fixed-ratio mixed-mode (FRMM) tests. The robustness, accuracy and sensitivity of the framework are validated through the double cantilever beam test. The findings indicate that the numerical results align closely with the experimental data, confirming that the interface parameters identified by the proposed framework can reproduce the experimental results.

RBF-Based Integrated Optimization Method of Structural and Turning Parameters for Low-Floor Axle Bridge

The axle bridge plays a crucial role in the bogie of low-floor light rail vehicles, impacting operational efficiency and fuel economy. To minimize the total cost of the structure and turning of axle bridges, an optimization model of structural and turning parameters was built, with the fatigue life, maximum stress, maximum deformation, and maximum main cutting force as constraints. Through orthogonal experiments and multivariate variance analysis, the key design variables which have a significant impact on optimization objectives and constraints (performance responses) were identified. Then the optimal Latin hypercube design and finite element simulation was used to build a Radial Basis Function (RBF) model to approximate the implicit relationship between design variables and performance responses. Finally, a multi-island genetic algorithm was applied to solve the integrated optimization model, resulting in an 8.457% and 1.1% reduction in total cost compared with the original parameters and parameters of sequential optimization, proving the effectiveness of the proposed method.

Optimization design on cooling structure of High-Temperature magnetic fluid dynamic seal device

In order to better sealing performance of magnetic fluid at high temperature, structural optimization design of cooling component in magnetic fluid dynamic sealing device at high temperature is studied in this paper. The magnetic field model of magnetic fluid sealing device at high-temperature is established to analyze the influence of temperature on the sealing performance of magnetic fluid, and magnetic field strength distribution is obtained. The simulated results show both magnetic induction strength difference and theoretical sealing pressure decrease gradually with the increase of the operating temperature. To reduce the temperature having great influence on sealing performance of magnetic fluid dynamic seal device, the temperature field model is constructed. Based on the Latin hypercube sampling method, the design matrix between cooling structural parameters and temperature is determined. In consideration of the neural network approach, the approximate agent model is built to analyze the correlation relationship between cooling structure parameters and cooling performance. The multi-island genetic algorithm is conducted on searching the optimal cooling structural parameters under global design space. The optimized results show that the average temperature of the permanent magnet is decreased by 27 °C, and the average temperature of the seal gap is reduced by 28 °C. The theoretical sealing differential pressure of the high-temperature magnetic fluid is improved by 49 KPa.

Research on Mode Switching and Energy Management of Hybrid Electric Vehicle

Aiming at the optimization of mode switching control and energy management strategy for parallel hybrid electric vehicles, a mode switching control method and A-ECMS steady-state energy management strategy is proposed. Firstly, in order to effectively suppress the impact caused by mode switching, and a fuzzy controller is designed for clutch engagement displacement. Then, on the basis of ensuring the smoothness of mode switching, A-ECMS control strategy based on SOC feedback is established. Finally, Isight and Cruise are used to build a co-simulation platform, and multi-island genetic algorithm is used to study the influence of initial value selection of equivalent factor on the controller. The results show that the proposed mode switching control and energy management control strategy, combined with A-ECMS strategy, can effectively improve the vehicle fuel economy on the basis of ensuring the mode switching smoothness.

Optimizing and designing upper-stage separation spring of lifting-body rocket

Because the upper-stage separation of a lifting-body rocket is difficult under the low-altitude and high-speed flight environments, an upper-stage separation scheme based on the separation spring is proposed. The integration of ADAMS and MATLAB realizes the multi-body dynamics simulation analysis of upper-stage separation. The experimental design method is used to carry out the target simulation and calculation of the upper-stage separation process, with the separation condition deviation and the separation spring deviation considered at the same time, thus ensuring the reliability of the separation scheme. In order to further optimize the separation scheme, an upper-stage separation optimization model is established with the Isight software, and the mass of separation spring is optimized with the multi-island genetic algorithm and significantly reduced by 48.87% under the condition that the upper-stage separation process satisfies all constraints, thereby effectively improving the performance of the lifting-body rocket.

Cavitation performance analysis and optimal design of the portable electric-driven axial flow pump

Based on the ISIGHT optimization platform, the impeller parameterization modeling and simulation process of the portable axial flow pump is carried out through CFturbo, ICEM and CFX software, and the impeller is optimized with the help of multi-island genetic algorithm to target the two optimization objectives of efficiency and head. The optimization results show that the hydraulic efficiency increased by 6.3% under design conditions. At the same time, compared with the original solution, the optimized cavitation performance is significantly improved. Additionally, overall entropy production is significantly reduced. Field test results show that the head deviation is 1.42% and the efficiency deviation is 4.52% under design conditions, proving that the optimization results are reliable.

Parameters collaborative optimization design and innovation verification approach for fuel cell distributed drive electric tractor

Fuel cell distributed drive electric tractors (FCDET) are one of the necessary means to achieve truly green agriculture. However, low traction efficiency, poor control coordination, and excessive energy consumption are the main reasons hindering the industrialization of FCDET. This paper proposed a parametric collaborative optimization design method and innovative verification system that considers the drive system and energy system. Based on the tractor plowing operating conditions, a 7-DOF coupled dynamics model of the distributed drive system and a tire-soil interaction model were established, and the key component selection and parameter matching were completed. On the drive system optimization level, the front and rear wheelside transmission ratios are optimized based on a multi-island genetic algorithm (MIGA). On the energy system optimization level, the globally optimal power distribution ratio is found based on the dynamic programming algorithm (DP). A complete experimental prototype verification system is constructed based on the MATLAB/Simulink-NI PXI joint simulation platform, physical prototype test bench, and real vehicle multi-index test platform. The results show that the average efficiencies of the optimized drive and energy system are increased by 0.38 % and 3.82 %, the total energy consumption (total hydrogen consumption) is reduced by 25.40 % and 15.39 %, respectively. The maximum fault-free operating time is 5.5h, the average traction power is 21.07 kW, and the average traction force is 10610 N in the all-wheel drive mode. The experimental results fully demonstrate that the electric tractor with the fuel cell distributed drive system as the core can meet the verification of multiple indicators. This study can provide a new theoretical basis and technical verification method for the optimal design and system control of fuel cell distributed drive electric tractors.

Collaborative optimization on cooling channel flow resistance and winding temperature for integrated cooling of motor and controller

The efficiency and working performance of the motor and controller system in micro-electric vehicles depends mainly on its thermal performance, which is contingent upon effective and active cooling. The working temperature of the motor and controller may be too high during operation, which properly causes motor power reduction or motor breakdowns. Therefore, it is crucial to design a good cooling channel for better cooling the integrated motor and controller system. This work proposes an integrated cooling channel of motor and controller, and the fluid-solid coupling analysis is applied for analyzing the velocity, pressure distributions of the cooling channel, and temperature distributions of motor solid components. Meanwhile, the collaborative optimization method based on the multi-island genetic algorithm (MIGA) is used to attain optimal design parameters of the integrated cooling channel of the motor and controller for obtaining a better cooling channel design with lower flow resistance and lower winding temperatures. Results show that the original cooling channel’s flow resistance and maximum winding temperature are 31.87 kPa and 120.04°C, respectively. The flow resistance and winding temperature are pretty significant. After optimization, the local vortex flow and zero velocity area in optimal cooling channel design are improved, the coolant flow velocity becomes more uniform, and the flow resistance is significantly reduced. The flow resistance and maximum winding temperature of the optimal cooling channel design are 12.5 kPa and 116.76°C, respectively, which are decreased compared with the original cooling channel structure, with a decrease of 39.4% and 2.7%, respectively. The research findings in this work can provide theoretical reference for solid components temperature evaluation of motor and give valuable data to cooling performance evaluation and optimization of integrated cooling channel for motor and controller system.

Optimization design and experiment study on a water hydraulic flexible actuator integrating flexible inner skeleton and soft external skin used for underwater flexible gripper

A water hydraulic flexible gripper with three flexible actuators is proposed, which integrates a soft external skin and a flexible inner skeleton to enhance resistance against water pressure. To investigate the deformation characteristics of the water hydraulic flexible actuator, a mathematical model is established to describe the relationship between water pressure and actuator deformation. The effects of different materials, structural sizes, and inlet pressure are analyzed through simulation. A Kriging model is utilized to fit the simulation results, while a multi-island genetic algorithm is employed to obtain an optimal solution for the structure of the flexible actuator. Finally, the deformation of the flexible actuator under various inlet pressures is quantified through experimental measurements, and the obtained results exhibit degree of consistency with the simulation outcomes. After completing static experiments at a simulated sea depth of 1000 m, the tip forces of flexible actuators were tested, and then land and underwater grasping experiments were conducted. The water-hydraulic flexible actuator developed in this study has great potential for handling fragile or deformable objects during deep-sea. This promotes the application of water-hydraulic flexible manipulators in the field of underwater robotics, providing higher flexibility and adaptability compared to traditional rigid manipulators.

Hydrodynamic and Structural Optimization of a Truss-Floating Aquaculture Vessel

A truss-floating aquaculture vessel is an innovative addition to the aquaculture industry, characterized by its large, porous, ship-shaped structure. It differs from traditional ships, offshore structures, and individual net cages. Due to its distinctive features, a large-scale truss-floating aquaculture vessel requires dedicated hydrodynamic and structural analysis, which is the primary focus of this paper. Our study starts with the calculation of wave loads acting on the vessel using the equivalent design wave method. Subsequently, it delves into the analysis of structural characteristics and stress distribution of the truss-floating aquaculture vessel, upon which structural optimization is performed. To determine the optimal design variables, a sensitivity analysis of the truss members is carried out using a parametric research method. Finally, the structure with multiple objectives is optimized using two distinct approaches: the adaptive simulated annealing algorithm (ASA) and the multi-island genetic algorithm (MIGA). The results reveal that prior to optimization, there is a risk of buckling and yielding damage occurring at various connections within the vessel structure. After optimization, the structural strength is significantly improved, accompanied by a reduction in the total weight of the vessel. This study offers a valuable reference for the design and structural safety assessment of this innovative truss-floating tank-type aquaculture vessel.

Time-history performance optimization of flapping wing motion using a deep learning based prediction model

Flapping Wing Micro Aerial Vehicles (FWMAVs) have caused great concern in various fields because of their high efficiency and maneuverability. Flapping wing motion is a very important factor that affects the performance of the aircraft, and previous works have always focused on the time-averaged performance optimization. However, the time-history performance is equally important in the design of motion mechanism and flight control system. In this paper, a time-history performance optimization framework based on deep learning and multi-island genetic algorithm is presented, which is designed in order to obtain the optimal two-dimensional flapping wing motion. Firstly, the training dataset for deep learning neural network is constructed based on a validated computational fluid dynamics method. The aerodynamic surrogate model for flapping wing is obtained after the convergence of training. The surrogate model is tested and proved to be able to accurately and quickly predict the time-history curves of lift, thrust and moment. Secondly, the optimization framework is used to optimize the flapping wing motion in two specific cases, in which the optimized propulsive efficiencies have been improved by over 40% compared with the baselines. Thirdly, a dimensionless parameter Cvariation is proposed to describe the variation of the time-history characteristics, and it is found that Cvariation of lift varies significantly even under close time-averaged performances. Considering the importance of time-history performance in practical applications, the optimization that integrates the propulsion efficiency as well as Cvariation is carried out. The final optimal flapping wing motion balances good time-averaged and time-history performance.

Optimal design and research for nozzle governing turbine of compressed air energy storage system

The air storage pressure of the compressed air energy storage system gradually decreases during the energy release process. In order to make the turbine work efficiently in non-design conditions, it is necessary to adopt a reasonable air distribution method for the turbine. In this paper, the orthogonal experimental design is carried out on the inlet pressure of the nozzle under different base pressure. Based on the response surface method, the optimal nozzle governing method corresponding to different base pressure under required output work conditions is obtained by multi-island genetic algorithm. The optimal NG method can improve the w by up to 9.2 % compared with throttle governing. To meet the output work requirement, an optimal NG method should have as few nozzles as possible and more nozzles with the same inlet pressure as the BP.

Study on the vibration reduction characteristics of shock absorber throttle orifice in tractor suspension

The hydraulic shock absorber of a certain tractor suspension system is analyzed to determine the influence of the cross-sectional area ratio of the throttling holes of the restoration valve and the compression valve on the vibration damping performance of the whole vehicle, using a new method of machine-hydraulic co-simulation. First, the AMESim model of the hydraulic shock absorber is established, and the Kriging model is used to approximate the parameters of the AMESim hydraulic shock absorber model; the multi-island genetic algorithm and the gradient descent algorithm are used to obtain the three scenarios in which the cross-sectional area ratios of the throttle orifices of the same equivalent damping coefficients are greater than, equal to, or less than one. Then, a co-simulation model of 1/4 vehicle Recurdyn/AMESim and a co-simulation model of the whole vehicle with 162 degrees of freedom were established. The result show that, compared with the traditional method, this machine-hydraulic co-simulation method improves the calculation accuracy, calculation speed, and co-simulation model parameter accuracy. For low-speed conditions, when the throttle orifice area ratio equals 0.32, the minimum vehicle body center acceleration (root mean square value equal to 1.78 m/s2) is achieved. For high-speed driving conditions, when the throttle orifice area ratio is approximately 3.1, the minimum vehicle body center acceleration (root mean square value equal to 3.52 m/s2) is achieved.

Inversion of the Seepage Parameters of Earth/Rockfill Dams Considering the Coupling Effect of Seepage and Thermal Transfer

The estimation of inversion parameters for seepage models is very important for ensuring the safety of earth/rockfill dams. In most existing studies, only hydraulic characteristics have been determined based on seepage pressure or discharge observation information, which may result in inversion results that do not accurately characterize the true properties of dam materials. In this paper, an advanced parameter inversion method considering the coupling effect of seepage and thermal transfer is proposed. A seepage–thermal transfer coupled finite element model is established, and hydraulic head and temperature data of monitoring points are obtained through the forward simulation method. The entropy weight (EW) method is used to preprocess the hydraulic head and temperature data, and a universal kriging (UK) surrogate model is established to replace the time-consuming finite element simulations. The multi-island genetic algorithm (MIGA) is applied to find the optimal solution, thereby obtaining the inversion results. The effectiveness and accuracy of the proposed method are verified through laboratory tests involving seepage and thermal transfer monitoring of a core rockfill dam. Joint inversion based on temperature and hydraulic head observation information can result in improvement in the accuracy of the inversion results.

Study on the Optimal Design of a Shark-like Shape AUV Based on the CFD Method

In previous AUV designs, the thrusters were often placed outside the vehicle, resulting in their performance being significantly influenced by the shape of the vehicle. Additionally, this placement also leads to the generation of strong radiated noise that propagates in all directions, making noise reduction challenging. Taking inspiration from the shape of sharks, this paper proposes a slender, shark-inspired AUV. The model features a continuous passageway in the middle where a pump-jet thruster is installed to provide propulsion. The walls of the passageway are then covered with sound-absorbing materials to reduce radiated noise. To address the problem of low design efficiency caused by multiple design parameters, a multi-objective optimization method is proposed to optimize the shape of the AUV. The performance targets of speed, displacement, and energy consumption are determined as objective functions, and a multi-island genetic algorithm is used as the optimization algorithm to build the multi-objective optimization process. An automated optimization platform was then developed which integrates parametric modeling, mesh partitioning, the CFD calculation, and the optimized design. To enhance the efficiency of optimization, a surrogate model was developed to approximate the CFD calculation. Using the optimal Latin hypercube method, experimental factors were designed, and a surrogate model was constructed based on the radial basis function approach. Following optimization, the resistance was reduced by 9.1%, while the displacement volume was increased by 10.7% and energy consumption was decreased by 6.3%. By analyzing the velocity and entropy production distribution of the AUV, the effectiveness of the optimization method was verified.

Optimization of the chamber of OWC to improve hydrodynamic performance

Nearly 71% of Earth's surface area is occupied by the ocean, which is abundant in energy, with wave energy being one of its essential components. As a result, the investigation of wave energy generation devices is a crucial matter. This paper analyzes the performance of the oscillating water column (OWC) wave energy conversion device under the influence of unidirectional regular waves and optimizes the OWC device accordingly. The impact of different structural dimensions on the first-stage conversion efficiency of the OWC device is determined. Moreover, to evaluate the performance of the OWC device in real sea conditions, the wave climate at Sanmen Gorge is employed as the experimental parameter. The study examines the performance and characteristic response of the OWC device regarding the air chamber width, thickness of the front wall, and draught of the front wall. The findings reveal that the width of the OWC air chamber and the draught of the front wall significantly affect the OWC performance. Decreasing the width of the air chamber results in a stable horizontal plane, eliminating the occurrence of standing wave phenomena. As the draft of the front wall increases, the reflection coefficient of the air chamber gradually increases, and it becomes difficult for the wave to penetrate into the air chamber section. The Latin hypercube design experiment method was used to select experimental points and establish quadratic polynomial response functions. The OWC device was optimized based on multi-island genetic algorithm. The simulation and fault tolerant optimization methods presented in this paper can be widely used to improve system performance.