检索结果-内蒙古大学图书馆

Research on multi-objective optimization design of the nuclear island cold chain system in HPR1000 based on a new hybrid genetic algorithm

引用

PROGRESS IN NUCLEAR ENERGY 2025年 180卷

作者： Zhao, Weiguang Yu, Pei Zeng, Xiaobo Fan, Guangming Meng, Zhaoming Yan, Changqi Harbin Engn Univ Coll Nucl Sci & Technol Harbin 150001 Peoples R China Harbin Engn Univ Fundamental Sci Nucl Safety & Simulat Technol Lab Harbin 150001 Peoples R China China Nucl Power Engn Co Ltd Beijing 100870 Peoples R China

Currently, the design of the cold chain system for the HPR1000 nuclear island does not take a unified approach and largely relies on the design experience of the respective designers. The various subsystems contain numerous devices, and the cumulative design margins often result in many unreasonable parameters in the original design scheme of the cold chain system. To address this issue, this paper establishes a mathematical model for the cold chain system to assist in its design. Based on genetic algorithms and the simplex algorithm, adaptive relaxation constraint dominance relations and two improved NSGA-II multi-objective handling methods are introduced, leading to the development of a new hybrid multi-objective genetic algorithm. The performance of this algorithm is verified using optimized benchmark testing functions, thus allowing for the scientific optimization of the cold chain system design scheme. A sensitivity analysis is conducted on the design parameters of the ventilation system, refrigeration system, component cooling system, and seawater system within the cold chain system to explore the impact of these parameters on performance indicators. optimization design calculations for the cold chain system are performed under safe and feasible conditions, resulting in an optimization scheme. The results indicate that the developed algorithm is effective in addressing the complex optimization problems of the cold chain system, and the optimized cold chain system can reduce weight by up to 18.4 %, volume by up to 18.6 %, investment costs by up to 5.7%, and system energy consumption by up to 7.5 %.

关键词： HPR1000 optimization algorithm Nuclear island cold chain system (NICCS) multi-objective optimization design Performance evaluation model

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design of injection molding process parameters based on the improved efficient global optimization algorithm and non-dominated sorting-based genetic algorithm

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2015年第9-12期78卷 1813-1826页

作者： Zhao, Jian Cheng, Gengdong Ruan, Shilun Li, Zheng Dalian Univ Technol Dept Engn Mech State Key Lab Struct Anal Ind Equipment Dalian 116024 Peoples R China

This paper develops a framework that tackles the Pareto optimum of injection process parameters for multi-objective optimization of the quality of plastic part. The processing parameters such as injection time, melt temperature, packing time, packing pressure, cooling temperature, and cooling time are studied as model variables. The quality of plastic part is measured by warp, volumetric shrinkage, and sink marks, which is to be minimized. The two-stage optimization system is proposed in this study. In the first stage, an improved efficient global optimization (IEGO) algorithm is adopted to approximate the nonlinear relationship between processing parameters and the measures of the part quality. In the second stage, non-dominated sorting-based genetic algorithm II (NSGA-II) is used to find a much better spread of design solutions and better convergence near the true Pareto optimal front. A cover of liquid crystal display part is optimized to show the method. The results show that the Pareto fronts obtained by NSGA-II are distributed uniformly, and this algorithm has good convergence and robustness. The pair-wise Pareto frontiers show that there is a significant trade-off between warpage and volumetric shrinkage, and there is no significant trade-off between sink marks and volumetric shrinkage and between sink marks and warpage.

关键词： Injection molding Kriging surrogate model IEGO multi-objective optimization design NSGA-II

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design method for the machine tool's structural parts based on computer-aided engineering

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2015年第5-8期78卷 1053-1065页

作者： Liu, Shihao Hainan Univ Coll Mech & Elect Engn Haikou 570228 Hainan Peoples R China

In order to improve the static and dynamic performance of the machine tool's structural parts and achieve lightweight design at the same time, a multi-objective optimization design method is proposed. The orthogonal experimental design method and response surface method are adapted to establish the optimization model, while a modified particle swarm optimization algorithm and grey relational analysis method are adapted to solve the model. The proposed method was used to conduct multi-objective optimization design for a gantry machine tool's slide-seat. Based on the computer-aided engineering analysis, the response surface optimization model was established. After verifying the accuracy of response surface optimization model, five groups of non-inferior solutions are obtained by using the particle swarm optimization algorithm. The optimal design scheme was selected from the non-inferior solution set through using the grey relational analysis method, which reduces slide-seat's mass and improves its static and dynamic performance considerably. After conducting static and dynamic experimental study on the slide-seats before and after multi-objective optimization design, the rationality and feasibility of the multi-objective optimization design method for the machine tool's structural parts were verified.

关键词： Machine tool Structural parts multi-objective optimization design Computer-aided engineering

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design of Inset-surface Permanent Magnet Machine Considering Deterministic and Robust Performances

引用

Chinese Journal of Electrical Engineering 2021年第3期7卷 73-87页

作者： Gaohong Xu Zexin Jia Wenxiang Zhao Qian Chen Guohai Liu School of Electrical and Information Engineering Jiangsu UniversityZhenjiang 212013China

The inset-surface permanent magnet(ISPM)machine can achieve the desired electromagnetic performance according to the traditional deterministic ***,the reliability and quality of the machine may be affected by the essential manufacturing tolerances and unavoidable noise factors in mass *** address this weakness,a comprehensive multi-objective optimization design method is proposed,in which robust optimization is performed after the deterministic *** response surface method is first adopted to establish the optimization objective ***,the sample points are obtained via Monte Carlo simulation considering the design-variable *** design for Six Sigma approach is adopted to ensure the robustness of the design ***,the barebones multi-objective particle swarm optimization algorithm is used to obtain a compromise solution.A prototype is manufactured to evaluate the effectiveness of the proposed *** to the finite-element analysis and experimental tests,the electromagnetic performance and reliability of the machine are significantly enhanced with the proposed method.

关键词： multi-objective optimization design robust design design for Six Sigma Monte Carlo simulation barebones multi-objective particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design of Hybrid Excitation Double Stator Permanent Magnet Synchronous Machine

引用

IEEE TRANSACTIONS ON ENERGY CONVERSION 2023年第4期38卷 2364-2375页

作者： Chu, Jinlong Cheng, He Sun, Junhang Peng, Cheng Hu, Yihua China Univ Min & Technol Sch Elect Engn Xuzhou 221116 Peoples R China China Univ Min & Technol Xuzhou 221116 Peoples R China China Univ Min & Technol Xuzhou Campus Xuzhou 221000 Peoples R China Univ York Dept Elect Engn York YO10 5DD England

In this article, a novel hybrid excitation double stator permanent magnet synchronous machine (HEDS-PMSM) is designed. The permanent magnets and field windings work together to provide air gap magnetic field, and different currents are applied to the field windings to enhance or weaken the air gap magnetic field to achieve a wide speed regulation range. Considering the complex structure of double-stator machine, the multi-objective optimization method is proposed to optimize the machine parameters. To optimize the machine accurately and efficiently, the sensitivity analysis of the main design variables of the machine is carried out, and the design variables with high sensitivity are selected. Then, the kriging response surface model is used to analyze the high sensitivity design variables of the machine. In order to obtain the optimal design variables, Non-Dominated Sorted Genetic Algorithm-II (NSGA-II) algorithm is used to optimize the HEDS-PMSM iteratively. Based on the finite element simulation software, the output torque, torque ripple, core loss and other electromagnetic performance of the machine are analyzed. A prototype is made for experimental verification. The experimental results show that the multi-objective optimization design method for the proposed HEDS-PMSM is reasonable and effective.

关键词： Hybrid excitation permanent magnet synchronous machine parameter sensitivity analysis kriging response surface model multi-objective optimization design

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design of post-soil system for enhanced W-beam guardrail containment performance

引用

INTERNATIONAL JOURNAL OF CRASHWORTHINESS 2023年第1期28卷 116-126页

作者： Lu Jijian Lei Zhengbao Changsha Univ Sci & Technol Large Scale Struct Impact Lab Changsha Peoples R China

In the W-beam guardrail system, the post can provide sufficient lateral force through interaction with the subgrade and can create the necessary containment function by connecting with the W-beam rail panel. The purpose of this study is to evaluate the best embedment depth and section size of two different posts in the same subgrade from the perspectives of maximum lateral force and occupant ridedown acceleration for enhanced the containment performance of guardrail protection system in China. An accurate lateral force measurement method is used for the inertia effect in collision problems. And the exact finite element model of post-soil interaction is built by combining dynamic impact test with detailed finite element study. Then the Genetic algorithm (GA) was used to determine the optimum value of spread and then the GA-RBF was applied to construct the surrogate models of the analytical objective, which increased the accuracy of fitting. Finally, the embedment depth and structure size were obtained using multi-objective genetic algorithm. Full-scale crash test results show that the optimum design results meet the requirements. Through optimization design, W-beam guardrail has been greatly improved, which improves the crash safety of corrugated beam guardrail.

关键词： multi-objective optimization design guardrail post post embedment depth structure size GA-radial basis function (GA-RBF) genetic algorithm (GA)

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design of a centrifugal impeller considering both aerodynamic efficiency and structural machinability

引用

ENGINEERING COMPUTATIONS 2021年第6期38卷 2755-2780页

作者： Xie, Xing Li, Zhenlin Zhu, Baoshan Wang, Hong China Univ Petr Coll Mech & Transportat Engn Beijing Key Lab Proc Fluid Filtrat & Separat Beijing Peoples R China Tsinghua Univ Dept Energy & Power Engn Beijing Key Lab CO2 Utilizat & Reduct Technol Beijing Peoples R China Tsinghua Univ Inst Nucl & New Energy Technol Beijing Peoples R China

Purpose This study aims to complete the optimization design of a centrifugal impeller with both high aerodynamic efficiency and good structural machinability. design/methodology/approach First, the design parameters were derived from the blade loading distribution and the meridional geometry in the impeller three-dimensional (3D) inverse design. The blade wrap angle at the middle span surface and the spanwise averaged blade angle at the blade leading edge obtained from inverse design were chosen as the machinability objectives. The aerodynamic efficiency obtained by computational fluid dynamics was selected as the aerodynamic performance objective. Then, using multi-objective optimization with the optimal Latin hypercube method, quadratic response surface methodology and the non-dominated sorting genetic algorithm, the trade-off optimum impellers with small blade wrap angles, large blade angles and high aerodynamic efficiency were obtained. Finally, computational fluid dynamics and computer-aided manufacturing were performed to verify the aerodynamic performance and structural machinability of the optimum impellers. Findings Providing the fore maximum blade loading distribution at both the hub and shroud for the 3D inverse design helped to promote the structural machinability of the designed impeller. A straighter hub coupled with a more curved shroud also facilitated improvement of the impeller's structural machinability. The preferred impeller was designed by providing both the fore maximum blade loading distribution at a relatively straight hub and a curved shroud for 3D inverse design. Originality/value The machining difficulties of the designed high-efficiency impeller can be reduced by reducing blade wrap angle and enlarging blade angle at the beginning of impeller design. It is of practical value in engineering by avoiding the follow-up failure for the machining of the designed impeller.

关键词： Centrifugal Impeller Aerodynamic Efficiency multi-objective optimization design Structural machinability

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design of shaftless rim-driven thruster

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART M-JOURNAL OF ENGINEERING FOR THE MARITIME ENVIRONMENT 2024年第3期238卷 633-639页

作者： Tao, Bian Liangliang, Liu Wenhao, Cai Wen, Jiang Zhiwen, Liu Jianghan Univ Sch Intelligent Mfg Wuhan Hubei Peoples R China Guangdong HUST Ind Technol Res Inst Dongguan Peoples R China Jianghan Univ Sch Intelligent Mfg Shanjiaohu St 8 Wuhan 430056 Hubei Peoples R China

This paper proposes a multi-objective optimization design method for shaftless rim-driven thruster (RDT) based on the ISIGHT platform. The pitch ratio, the blade area ratio and the advance coefficient of RDT were considered as the design optimization variables, the thrust and efficiency of the RDT were the optimization objectives. The multi-objective optimization design method was based on the surrogate module and the optimization module in the ISIGHT platform. Two analytical methods (response surface methodology (RSM) and radial basis function Model (RBF)) were used to build the surrogate model. The Muti-Island GA optimization algorithm was adopted in the optimization module. The paper indicates that both RSM model and RBF model are feasible to build the surrogate model, the RBF model has better accuracy and reliability than RSM model. The blade obtained by RBF method has larger thrust and smaller torque than that of the blade obtained by RSM method. For the large advance coefficient (J > 0.6), the efficiency of the blade obtained by RBF method is slightly higher than that of the blade obtained by RSM method.

关键词： Shaftless rim-driven thruster multi-objective optimization design ISIGHT platform

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design of a battery pack system for crashworthiness and lightweight based on a submodel and hybrid weighting method

引用

ENGINEERING optimization 2024年

作者： Lian, Fengmin Wang, Dengfeng Xu, Wenchao Zhang, Xiaopeng Kong, Dewen Huang, Lina Jilin Univ Coll Automot Engn Changchun Nanling Campus Changchun Peoples R China

The research focuses on optimizing battery pack systems (BPSs) for crashworthiness and lightweight design in electric vehicles. Traditional methods have high computing costs and do not account for the battery cell's failure criterion. This study uses a submodel and hybrid weighting for multi-objective design. It starts with the finite element model of a single cell, validates it and then builds a BPS model with a submodel for key areas. The optimal Latin hypercube sampling technique is used to sample the design space, and a kriging surrogate model and multi-objective particle swarm algorithm are used to find the Pareto solution. The compromise solution is selected using the analytic hierarchy process-Entropy-VIKOR method, considering the maximum principal strain of the cell. This approach cuts the computation time by 56.2% and offers a practical solution for BPS design by utilizing the load-bearing ability of the BPS.

关键词： Submodel hybrid weighting method battery pack system crashworthiness multi-objective optimization design

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization design of Bearingless Permanent Magnet Synchronous Generator

引用

IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY 2020年第4期30卷 1-5页

作者： Hua, Yizhou Zhu, Huangqiu Xu, Ying Jiangsu Univ Sch Elect & Informat Engn Zhenjiang 212013 Jiangsu Peoples R China

In order to realize the design objectives of high power generation performance and stable suspension capability, a multi-objective optimization method based on a response surface (RS) model and an improved multi-objective particle swarm optimization (MOPSO) algorithm is proposed and utilized to the multi-objective optimization design of a bearingless permanent magnet synchronous generator (BPMSG). Firstly, the operating principle and the mathematical model of the BPMSG are introduced. Secondly, the design variables and the design objectives are determined and the design space is reduced by the sensitivity analysis. Thirdly, the RS models of design objectives are constructed and the improved MOPSO algorithm is applied to get the Pareto optimal sets. Finally, the initial generator and the optimal generator are compared using the finite element analysis software. Compared with the initial generator, the average suspension force of the optimal generator is increased by 21% and the suspension force ripple is decreased by 52%.

关键词： Bearingless permanent magnet synchronous generator multi-objective optimization design multi-objective particle swarm optimization algorithm response surface model

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：