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multi-objective optimization design of double resilient groove metal seat for ball valve in liquid hydrogen receiving stations

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JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING 2024年第1期46卷 1-16页

作者： Li, Shuxun Zheng, Mingxing Wang, Yixue Yang, Lingxia Ma, Tingqian Lanzhou Univ Technol Sch Petrochem Technol Lanzhou 730050 Peoples R China Machinery Ind Pump & Special Valve Engn Res Ctr Lanzhou 730050 Peoples R China Sichuan Jiuzhou Elect Grp Co LTD Mianyang 621000 Peoples R China

For the liquid hydrogen receiving station ball valve seat in ultra-low temperature working conditions the cold shrinkage deformation is easy to lead to valve seal failure. Design a dual-elastic groove metal valve seat and a preliminary assessment of its performance. The seat performance is optimized based on the radial basis function (RBF) approximation model combined with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm. The Spearman method is used for sensitivity analysis, and the final multi-objective optimization design variables of the parameters that have a greater impact on the optimization objectives are selected. Based on the maximum equivalent stress Smax, maximum deformation Dmax, minimum fatigue life Lmin, and mass M as the optimized goal, different design variables have different effects on the four optimization objectives. The optimal Latin superposition method samples the valve seat structure parameters, and the establishment of High-precision RBF proxy model combined with the NSGA-II algorithm to find excellent Pareto cutting-edge solutions, comprehensively considering the performance requirements of valve seats to determine the optimal structural parameters of the valve seat. The maximum stress of the valve seat after the optimization decreased by 43.45%, the maximum deformation decreased by 45.33%, the quality was reduced by 22.49%, and the life expectancy increased by 114.11%. The finite element analysis of the seal verifies that the optimized seat has an excellent compensation effect under the ultra-low temperature conditions of liquid hydrogen.

关键词： Valve seat innovation design Liquid hydrogen receiving station ball valve Elastic compensation multi-objective optimization Sensitivity analysis

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multi-objective optimization design of shock-focusing detonation initiator

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ACTA ASTRONAUTICA 2024年 214卷 240-252页

作者： Liu, Xinyuan Yang, Qingzhen Hu, Hongbo Shi, Yongqiang Yang, Haoqi Northwestern Polytech Univ Sch Power & Energy Xian 710129 Shaanxi Peoples R China Xian Aerosp Prop Inst Sci & Technol Liquid Rocket Engine Lab Xian 710100 Shaanxi Peoples R China

Shock-focusing induced detonation is an efficient technique that has the potential to simplify detonation-based engines. However, the generation of high energy regions relies on an extremely strong shock, and the design of the initiator plays a crucial role in minimizing the threshold of incident shock strength. In this study, a multi-objective optimization design of the shock-focusing initiator was conducted using Computational Fluid Dynamics (CFD). Firstly, the accuracy of the numerical method and the reliability of the optimization platform were validated through a series of experimental data. Subsequently, the Axial Ratio (AR) of the elliptical reflector and the angle of the incident shock were optimized, considering the objectives of focusing pressure and focusing delay time. Three typical focusing patterns were identified from the samples, with pattern C generally exhibiting higher focusing pressure but longer focusing delay time. Four optimization cases were tested and demonstrated good agreement with the predicted results. case 1 corresponded to pattern A but failed to detonate, while the others followed pattern C and successfully detonation. Although pattern C was also observed in the original initiator, it failed to detonate because the focusing region was too distant from the bottom of the cavity. Finally, a best initiator was selected and compared to the original initiator. The results showed that the threshold of the incident shock Mach number M-in was reduced by 24.9%, the pressure of the corresponding driver gas was reduced by 68%, and the focusing delay time shortened by 7.2%.

关键词： Shock-focusing Detonation multi-objective optimization Direct initiation NSGA-II

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multi-objective optimization of a Lower Limb Prosthesis for Metabolically Efficient Walking Assistance

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年 22卷 4606-4621页

作者： Li, Guoxin Wang, Jiandong Li, Zhijun Yen, Gary G. Qi, Qi Xing, Jinqiu Tongji Univ Shanghai Yangzhi Rehabil Hosp Shanghai Sunshine Rehabil Ctr Sch Mech Engn Shanghai 201804 Peoples R China Tongji Univ Shanghai Yangzhi Rehabil Hosp Translat Res Ctr Shanghai Sunshine Rehabil Ctr Shanghai 201804 Peoples R China Univ Sci & Technol China Inst Adv Technol Hefei 230031 Peoples R China Oklahoma State Univ Sch Elect & Comp Engn Stillwater OK 74078 USA Tongji Univ Shanghai Yangzhi Rehabil Hosp Shanghai Sunshine Rehabil Ctr Shanghai 201804 Peoples R China Tongji Univ Dept Rehabil Shanghai 201804 Peoples R China Guangzhou Yikang Med Equipment Ind Co Ltd Guangzhou 511447 Peoples R China

Enhancing energy efficiency is pivotal for advancing robotic lower limb prostheses. However, the conventional control strategy in powered prostheses displays notable variance in energy economy across terrains during walking. This challenge could be managed by developing control optimization methods to effectively reduce the subject's metabolic cost and the device's energy expenditure, thereby improving the walking economy in diverse environments. In this study, we investigate a multi-objective optimization problem (MOP) for controlling above-knee prostheses, intending to reduce prosthetic power consumption and the subject's metabolic costs during walking activities. To bolster real-time performance in the optimization loop, we introduce a knee-guided evolutionary algorithm (KGEA) for MOP, which efficiently reduces exploration space and time complexity, thus enabling the practical implementation of a limited number of solutions in each iteration. The effectiveness of the proposed optimization-based strategy was evaluated through experiments involving two lower limb amputees engaging in slope, stair, and flat walking. Our results demonstrated that the optimization-based strategy significantly reduced the subjects' metabolic consumption, with an average reduction of 16.53% for subject 1 and 10.23% for subject 2 across different terrains, compared to using the prosthesis without the optimization strategy. This promising outcome marks a substantial advancement in the development of energy-efficient, multi-degree-of-freedom power prostheses.

关键词： Prosthetics Legged locomotion optimization Motors Costs Robots Muscles multi-objective optimization knee-guided evolutionary algorithm lower limb prosthesis metabolically efficient walking

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multi-objective optimization of distributed green infrastructure for effective stormwater management in space-constrained highly urbanized areas

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JOURNAL OF HYDROLOGY 2024年 644卷

作者： Zhou, Hong Gao, Cheng Luan, Qinghua Shi, Liming Lu, Zhengsheng Liu, Jun Hohai Univ Coll Hydrol & Water Resources Nanjing 210098 Peoples R China Hohai Univ Natl Key Lab Water Disaster Prevent Nanjing 210098 Peoples R China Hohai Univ Coll Agr Sci & Engn Nanjing 211100 Peoples R China

Green infrastructure (GI) is essential for stormwater management, but its implementation in highly urbanized areas is challenging due to the limited space available for GI retrofitting. There is a lack of comprehensive evaluations that assess the spatial adaptability, functionality, and cost-benefit of various GI measures, and optimize their placement to achieve the maximum reduction rate of total runoff (RTR) and reduction rate of pollution load (RPL) while minimizing life cycle cost (LCC) in space-constrained highly urbanized areas (SCHUA). To address this issue, a novel concept of infiltration, retention, and storage integrated GI (IRS-GI) for SCHUA was proposed, and a framework coupling the Storm Water Management Model (SWMM) with multi- objective optimization algorithms was developed to determine the optimal IRS-GI layout, focusing on the objectives of RTR, RPL, and LCC. The impacts of different GI type, size, and location, rainfall return periods, and algorithms (NSGA-II and NSGA-III) were then examined. The results showed that IRS-GI could achieve satisfactory RTR and RPL results while single-type GI may struggle to meet requirements. optimization outcomes were significantly influenced by rainfall return periods, with cost-benefit decreasing as return periods increasing. Besides, the optimization results of NSGA-II and NSGA-III showed differences, and the comprehensive Pareto frontier obtained by reapplying non-dominated sorting could achieve more comprehensive results for determining the optimal IRS-GI configuration. Under the urban drainage design standard, the optimal IRS-GI layout, covering 32.97 % of the green spaces, 38.57 % of the rooftop, and 60.98 % of the ordinary roads and squares, respectively, could achieve a RTR of 50.09 %, RPL of 57.00 %, and LCC of 0.79 x 10(8) CNY/yr. Additionally, the optimal configuration suggested that a higher proportion of GI downstream of drainage system may contribute to better cost-benefit, emphasizing the need for lo

关键词： Green Infrastructure Stormwater management multi-objective optimization Highly urbanized area SWMM

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multi-objective optimization of chemical reaction characteristics of selective catalytic reduction in denitrification of diesel engine using ELM-MOPSO methodology

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ENERGY 2024年 311卷

作者： Zhang, Zhiqing Zhao, Ziheng Tan, Dongli Zhang, Bin Yin, Zibin Cui, Shuwan Li, Junming Guangxi Univ Sci & Technol Sch Mech & Automot Engn Liuzhou 545000 Peoples R China Hunan Inst Engn Sch Elect & Informat Engn Xiangtan 411104 Peoples R China Jimei Univ Sch Marine Engn Xiamen 361021 Peoples R China

This study systematically investigated the effects of structural parameters in a two-stage selective catalytic reduction (SCR) catalyst on ammonia storage, NO conversion efficiency, and ammonia slip using computational fluid dynamics (CFD) simulations. The rank ordering of the correlations between structural parameters and performance metrics was determined by gray relational analysis (GRA). Both the catalyst diameter and the upstream catalyst porosity had correlations exceeding 0.9, making them key parameters affecting SCR performance. An extreme learning machine (ELM) prediction model was trained using data obtained from CFD simulations. The prediction performance of this ELM model was then evaluated using statistical metrics. Finally, the optimized Pareto frontier diagram was obtained through the multi-objective particle swarm optimization (MOPSO) algorithm, and the optimal results were selected for further CFD modeling analysis. The results showed that the upstream NO conversion efficiency of the SCR system was improved by 7.7 %, the downstream NO conversion efficiency was improved by 18.67 %, the ammonia slip was reduced by 71.97 %, and the upstream ammonia storage capacity was improved by 6.83 % compared with the original model.

关键词： Selective catalytic reduction multi-objective optimization NO conversion efficiency Ammonia slip Ammonia storage

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multi-objective optimization method of injection molding process parameters based on hierarchical sampling and comprehensive entropy weights

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2024年第3-4期133卷 1481-1499页

作者： Zeng, Wei Yi, Guodong Zhang, Shuyou Wang, Zili Zhejiang Univ State Key Lab Fluid Power & Mechat Syst Hangzhou Peoples R China

The key of the multi-objective optimization of injection molding processes lies in achieving a balance between the accuracy of the surrogate model and the multiple objectives while taking the diversity and interdependence of process parameters into consideration. However, the sampling process for building high-precision surrogate models requires a large number of sample points, resulting in high modeling costs for other regions. Moreover, the selection of Pareto fronts often relies solely on the magnitudes of objective values, without considering the uncertainties associated with the information. To address these issues, this research proposes a novel multi-objective optimization method for injection molding process parameters, using hierarchical sampling and integrated entropy weighting. The method introduces a unique hierarchical sampling approach to enhance the accuracy of the surrogate model in injection molding, with a specific focus on critical components. Additionally, our method incorporates entropy calculations for multiple objective defect value parameters during the multi-objective optimization process, enhancing the rationality of the optimization process. The proposed method is utilized to optimize the injection molding parameters of a thin-walled propeller blade. The result shows that our surrogate model fits well and exhibits superior performance compared to the response surface method in optimizing multiple objectives.

关键词： Hierarchical sampling Model refinement Gaussian interpolation Comprehensive entropy weight multi-objective optimization NSGA-III

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multi-objective optimization of Liquid-Cooled Power Unit With multiple Pumps in Parallel Under Variable Operating Conditions

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IEEE ACCESS 2024年 12卷 168825-168836页

作者： Hu, Hao Liu, Yang Ma, Xiqiang Li, Wenju Yue, Lingyun Yang, Fang Henan Univ Sci & Technol Sch Mech & Elect Engn Luoyang 471000 Henan Peoples R China Xinxiang Aviat Ind Grp Co LTD Xinxiang 453000 Henan Peoples R China Henan Univ Sci & Technol Key Lab Mech Design & Transmiss Syst Luoyang 471000 Henan Peoples R China

Advanced airborne equipment liquid cooling system presents the development trend of multiple pumps in parallel, centralised heat dissipation and high efficiency circulation, but this type of system has the characteristics of many variable parameters and strong non-linearity, which makes the system operation and control become extraordinarily complex, posing a serious challenge to the system performance. Although some progress has been made in the current optimization of liquid cooling system performance, there are still gaps such as insufficient consideration of the multi-objective optimization problem and limited optimization effect. To fill this research gap, this study takes minimum specific energy consumption, minimum flow deviation and minimum impeller load as the optimization objectives, establishment of multi-objective optimization model for liquid-cooled power unit, the optimal solution set of the Pareto model is solved using the multi-objective grey wolf optimization algorithm (MOGWO), and the optimal solution set is substituted for the optimal solution, and the evaluation indexes are designed in combination with the actual working conditions to obtain the optimal schedule. By example analysis, the optimized system under variable operating conditions, the impeller load and specific energy consumption decreased by 16.88% and 3.64% respectively, while the rise in flow deviation was controlled within 0.76%. The newly established optimisation model effectively mitigates potential safety hazards during system operation. Finally, by combining all the indicators, three scheduling options are provided under variable operating conditions, focusing on reliability and economy, overall balance and high-precision flow, respectively, in order to adapt to the diversified requirements of different operating environments.

关键词： Impellers Pumps optimization Energy consumption Reliability optimization models Valves Liquids Systems operation Load modeling Impeller load liquid-cooled power unit multi-objective optimization Pareto optimal solution set specific energy consumption

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multi-objective optimization for an irreversible Braysson cycle

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JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY 2024年第8期149卷 3471-3485页

作者： Liu, Xu Ge, Yanlin Chen, Lingen Shi, Shuangshuang Feng, Huijun Wuhan Inst Technol Inst Thermal Sci & Power Engn Wuhan 430205 Peoples R China Hubei Prov Engn Technol Res Ctr Green Chem Equipme Wuhan 430205 Peoples R China Wuhan Inst Technol Sch Mech & Elect Engn Wuhan 430205 Peoples R China

Based on the irreversible closed Braysson cycle model constructed by predecessors which included the heat leakage loss, internal irreversibility loss and thermal resistance loss and finite-time thermodynamics, NSGA-II algorithm is applied to conduct multi-objective optimization for the dimensionless ecological function (E over bar \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{E}$$\end{document}), efficiency (eta\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\eta$$\end{document}), dimensionless power density (P over bar d\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{P}_{{\text{d}}}$$\end{document}) and dimensionless power output (P over bar \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{P}$$\end{document}) of different objective combinations with logarithmic temperature ratio (x\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$x$$\end{document}) of working fluid and heat conductance distribution (u\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage

关键词： multi-objective optimization Heat conductance distribution Logarithmic temperature ratio Finite time thermodynamics Irreversible Braysson cycle NSGA-II algorithm

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multi-objective optimization for snap-through response of spherical shell panels

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APPLIED MATHEMATICAL MODELLING 2024年 127卷 711-729页

作者： Abo-bakr, Rasha M. Mohamed, Nazira Eltaher, M. A. Emam, Samir Zagazig Univ Fac Sci Math Dept Zagazig Egypt Zagazig Univ Fac Engn Engn Math Dept Zagazig Egypt King Abdulaziz Univ Fac Engn Mech Engn Dept Jeddah Saudi Arabia Amer Univ Sharjah Mech Engn Dept Sharjah U Arab Emirates Zagazig Univ Fac Engn Mech Design & Prod Dept Zagazig Egypt

Composite spherical shell panels are commonly used for the lightweight design of thin-walled structures in the structure, architecture, aerospace engineering. Depending on the shell panel length, thickness, curvature, and stacking sequence, the load-deflection response under lateral load can be either a completely stable equilibrium path or an unstable snap-through path. In this work, the response of simply supported cross-ply composite spherical shell panels subjected to lateral static loads is studied and optimized. The spherical shell exhibiting snap-through response is optimized to (a) maximize the load required to initiate snap-through and (b) minimize the unstable region. Meanwhile, the spherical shell exhibiting continuous response is optimized to (a) maximize the softening-hardening load and (b) minimize the shell weight. The decision variables for both constraint multi-objective optimization (CMOO) problems include layup sequence, thickness, and the radius of curvature to side length ratio. The nonlinear governing equations are derived based on Kirchhoff-Love hypotheses for thin shells and Hamilton's principle. A novel semi-analytical method is presented based on Bernstein polynomials combined with a fast iterative approach to compute the objective features of the responses. Benefiting from the high efficiency and robustness of the proposed approach, the CMOO problems are solved by the metaheuristic multi-objective Artificial Hummingbird Algorithm (MOAHA). Composite spherical shell panels with various geometry and lamination configurations are considered to validate the performance of the proposed method. The optimization of geometric parameters (shell curvature and thickness) in addition to the staking sequence provide a high degree of tailoring of the shell performance to meet various objectives. These parameters are taken as design variables that must be optimized to achieve some objectives and satisfy arbitrary nonlinear constraints.

关键词： Nonlinear analysis Snap-through instability Spherical shell panels Bernstein polynomial method multi-objective optimization

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multi-objective optimization and life cycle assessment of mass-integrated combined heat and power system

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SCIENCE OF THE TOTAL ENVIRONMENT 2024年 951卷 175811页

作者： Yang, Jiawen Li, Chengyun Teng, Junfeng Zhang, Yikun Wang, Yi Hou, Yan Xia, Li Sun, Xiaoyan Wang, Lili Xiang, Shuguang Qingdao Univ Sci & Technol Coll Chem Engn Qingdao 266042 Peoples R China Sinopec Engn Inc Beijing 100101 Peoples R China

As the effects of climate change become more widely recognized, technical innovation and green energy will promote the growth of combined heat and power systems. This study proposes a novel mass-integrated combined heat and power system and conducts energy analysis, exergy analysis, and techno-economic analysis for the system. The optimization strategy integrated polynomial regression and non-dominated sorting genetic algorithm III is established, with system thermal efficiency, exergy efficiency, and return on investment (ROI) as objective functions. The system's environmental consequences are then assessed throughout its life cycle using life cycle assessment (LCA) under ideal operating circumstances. The findings reveal that the waste heat recovery heat exchanger has the highest exergy destruction in the system, with a value of 674.61 kW. Furthermore, the intermediate heat exchanger 1 and intermediate heat exchanger 2 (IHX2) with lesser exergy efficiency have an exergy destruction of less than 32.00 kW. The IHX2 is the most expensive equipment in the system, costing $90,931.19, but it also provides the most potential for system improvement. The multi-objective optimization findings suggest that the thermal efficiency, exergy efficiency, and ROI for the system are 0.17, 0.97, and 0.30, respectively. The LCA demonstrates that the system has a negligible influence on global warming and ozone generation with corresponding LCA findings of less than 4.20. The construction and operation phases of the investigation system have the most significant environmental consequences. The correlation between the raw materials necessary for the construction of the equipment in the system and the reaction temperatures, conditions, and waste composition during the preparation of the working fluids is large, so it is necessary to take corresponding environmental protection measures during production and processing to reduce the system's environmental emissions from the source and prom

关键词： Combined heat and power system multi-objective optimization Mass-integrated Life cycle assessment

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