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Free-shape modeling and optimization for cold plates with tree-like channels

INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES 2023年第1期245卷

作者： Tian, Xi -Wei Wang, Wei Li, Peng Sun, Chen Wang, Cong-Si Qian, Si-Hao Wang, Meng Xidian Univ Key Lab Elect Equipment Struct Design Minist Educ Xian 710071 Peoples R China Xidian Univ Shaanxi Key Lab Space Solar Power Stn Syst Xian 710071 Peoples R China Yellow River Shaanxi Grp Co Ltd Xian 710073 Peoples R China

The use of cold plates is often considered a preferred cooling strategy to quickly remove detained heat from inside the system, which is widely used in engineering applications such as battery thermal management systems (BTMSs). Structural designs are essential to cold plate designs and serve as the foundation for other subsequent designs. This study introduces a free-shape modeling method for the structural design of cold plates with tree-like channels. The geometric characteristics include tree-like features (branching angles, lengths, numbers, and levels), passage patterns, elliptical cross-section sizes and shapes, and channel twists. They can all be freely revised by adjusting the related control parameters. A case of Cold Plates with Tree-like and Straight Channels (CPTSC), which is frequently found in BTMSs, is designed to verify the universality and effectiveness of the proposed free-shape modeling method. After that, the optimization technology based on the nsga-ii evolu-tionary algorithm is used to minimize the average temperature (overall thermal performance) and root mean square temperature (temperature uniformity) of top and bottom surfaces. The generalized minimum residual (GMRES) method is utilized for the numerical analyzes, and the numerical results indicate that the resulting designs can reduce the average temperature and root mean square temperature by up to 5.91 K (1.75%) and 2.06 K (23.54%), respectively, for Re=1000 and a total power of 600 W. The numerical and experimental results show that the structure of the best compromised solution reduces both thermal indicators by 5.79 K (1.72%) and 1.88 K (21.49%), respectively. This work provides a guideline for the design of tree-like structures that can be used not only in flat-panel cold plates but also in disk-shaped cold plates, heat sink with fins, and heat sink filled with phase change materials.

关键词： Free-shape modeling Tree-like channels nsga-ii algorithm Shape optimization Cooling enhancement Flat-panel cold plates

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Multi-objective optimization control for tunnel boring machine performance improvement under uncertainty

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AUTOMATION IN CONSTRUCTION 2022年 139卷 1页

作者： Liu, Wenli Li, Ang Liu, Congjian Huazhong Univ Sci & Technol Sch Civil & Hydraul Engn Dept Construct Management Wuhan 430074 Hubei Peoples R China

The tunnel boring machine (TBM) is an important and common construction method for urban subways, and it requires a detailed and rational control strategy to ensure the safety and efficiency of TBM excavation. Multiple objectives are required for shield tunneling;however, the control of TBM parameters is a complex and difficult problem under frequently encountered unforeseen geological conditions. Hence, a multi-objective optimization framework has been proposed to provide suggested TBM operational parameters for decision making under uncertainty. A Grey Wolf Optimizer-Generalized Regression Neural Network (GWO-GRNN) model has been developed to predict the TBM performance under different TBM operating parameters and geological conditions. Then, the nondominated sorting genetic algorithm (nsga-ii) is introduced to solve the multi-objective optimization problem and obtain the final decision-making solutions. To indicate the applicability of the proposed multi-objective optimization (MOO) framework, the Wuhan San-Yang Road Highway-Rail Tunnel Shield Project was adopted as an example. Results show that the GWO-GRNN model is in good agreement with the experimental measurements to predict the advance speed and ground settlement, with R-2 values of 0.97 and 0.91, respectively. Additionally, the results of nsga-ii optimization show that the proposed framework can realize the optimization of multiple objectives under different geological conditions. The results of this research are able to generate the optimal solutions for TBM operators, which can improve decision making when conflicting TBM excavation objectives exist.

关键词： Tunnel boring machine Multi-objective optimization GWO-GRNN model nsga-ii algorithm Pareto optimal solutions

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Aerodynamic Shape Optimization of a Square Cylinder with Multi-Parameter Corner Recession Modifications

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ATMOSPHERE 2022年第11期13卷 1782-1782页

作者： Wang, Zhaoyong Zheng, Chaorong Mulyanto, Joshua Adriel Wu, Yue Harbin Inst Technol Sch Civil Engn Harbin 150090 Peoples R China Harbin Inst Technol Minist Educ Key Lab Struct Dynam Behav & Control Harbin 150090 Peoples R China

Corner modifications can reduce wind loads acting on supertall buildings and modify the corresponding flow structures. The present study investigated the aerodynamic shape optimization of the corner recession square cylinders with multiple geometric parameters in a large design space via the GA-GRNN surrogate model updating-based multi-objective optimization framework. Six typical optimal aerodynamic shape sections M1 similar to M6 were selected from the Pareto optimal front, and the effects of multiple geometric parameters of these sections on the aerodynamic performance and flow field were analyzed. The results showed that the present multi-objective optimization framework can significantly reduce the computational load and time cost, and significantly improve the optimization efficiency in solving complex engineering problems. The optimal corner recession sections can obviously reduce the mean drag coefficient C-D and root mean square lift coefficient C-sigma L while significantly increasing the Strouhal number St of the square cylinder, and it is concluded that the aerodynamic shape optimization can significantly improve the aerodynamic performance of square-sectional supertall buildings. When compared with the benchmark section, the C-D and C-sigma L of the optimal section M1 can be reduced up to 45.7% and 84.5%, respectively. Based on the analysis of the flow structures around the optimal sections, the flow mechanism can be attributed to the fact that the corner recession modifications postpone the flow separation, and deflect the separated shear layer towards the side surfaces and suppress the development of vortex shedding in the wake, which leads to significant elongation of the wake length and reduction of the width of the recirculation region. The proposed multi-objective optimization framework in this study can provide an important reference for the aerodynamic shape optimization of building structures and relevant studies.

关键词： aerodynamic shape optimization square cylinder corner recession modification GA-GRNN surrogate model nsga-ii algorithm wind load flow mechanism

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An approach to optimize bed sill design using multi-objective evolutionary algorithms

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ENVIRONMENTAL EARTH SCIENCES 2021年第15期80卷 480-480页

作者： Tabatabai, Mohammad Reza Majdzadeh Adineh, Saeedeh Alimohammadi, Saeed Ghoreishi, Seyed Hosein Shahid Beheshti Univ Fac Civil Water & Environm Engn Tehran Iran

Bed sills are a kind of grade control structure built at the same level as the river bed to protect it against erosion and to reduce the longitudinal slope of the channel. The aim of the present research was to determine the optimal dimensions of the structure by devising a new methodology to minimize cost and maximize stability, based on the optimization model of the multi-objective non-dominated sorting genetic algorithm (nsga-ii). This is achieved by calculating the width, height and distance between bed sills with these stability and cost objectives in mind. The nsga-ii algorithm is applied to solve the problem, and a set of Pareto points is obtained. The results are verified by considering the bed sills of the River Madarsoo in Iran and the River Plima in Italy, and comparing the results with those obtained using the Branch-and-Bound (B-and-B) algorithm. The results indicate that the cost and stability could respectively be improved by up to 18 and 20% in the River Madarsoo, and up to 18 and 26% in the River Plima, if the nsga-ii algorithm is used.

关键词： Multi-objective optimization nsga-ii algorithm Pareto front Bed sill River Madarsoo River Plima

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Nondominated sorting genetic algorithm-ii with Q-learning for the distributed permutation flowshop rescheduling problem

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KNOWLEDGE-BASED SYSTEMS 2023年第1期278卷

作者： Tao, Xin-Rui Pan, Quan-Ke Sang, Hong-Yan Gao, Liang Yang, Ao-Lei Rong, Miao Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Liaocheng Univ Sch Comp Sci Liaocheng 252000 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

The distributed permutation flowshop problem (DPFSP) has been extensively studied in recent years. However, most of the research has overlooked the disturbance factors in the processing environment, such as the arrival of new jobs. To address this issue, a nondominated sorting genetic algorithm-ii (nsga-ii) with Q-learning has been developed. First, an iterated greedy algorithm (IG) is proposed to generate an initial solution for the first stage. Then, the nsga-ii algorithm is designed to optimize dual-objective problems in the second stage, and the Q-learning algorithm is used to adjust the algorithm parameters. Next, two local search strategies based on key factories are adopted, including critical factory-based insert and swap operations. Finally, a comprehensive experiment of the proposed algorithm against other advanced multiobjective algorithms is conducted. The results confirm that the proposed algorithm can solve the distributed permutation flowshop rescheduling problem with high efficiency.& COPY;2023 Elsevier B.V. All rights reserved.

关键词： Distributed flowshop Rescheduling Multiobjective nsga-ii algorithm Q-learning

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Integrated optimization of process planning and scheduling problems based on complex networks

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JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION 2023年 36卷

作者： Guo, Kai Liang, Yan Niu, Muqing Tan, Wenan Henan Univ Sci & Technol Business Sch Luoyang 471023 Henan Peoples R China Henan Collaborat Innovat Ctr Nonferrous Met Luoyang 471023 Henan Peoples R China Henan Univ Sci & Technol Affiliated Hosp 1 Luoyang 471023 Henan Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol 29 Jiangjun Ave Nanjing 211106 Peoples R China Shanghai Polytech Univ Sch Comp & Informat Engn Shanghai 201209 Peoples R China

Industrial information integration can promote modern manufacturing enterprises to achieve efficient information processing and data integration in manufacturing systems, providing a good framework for solving process planning and workshop scheduling integration problems. To explore optimization issues in an intelligent manufacturing environment, find a better way to solve the integration of process planning and scheduling, and analyze basic features of manufacturing task-driven workshop scheduling network. The paper constructs a multiprocess relational network model based on processes and machines in accordance with the complex network theory. Moreover, this paper proposes a multi-objective integrated model that minimizes maximum makespan, minimum machine load, and minimum machine energy consumption with the constraints of the workpiece, process, and machine. This paper uses the nsga-ii algorithm strategy to analyze the proposed model and issue. The feasibility of the model and algorithm proposed is demonstrated by solving various optimization objectives in actual workshop manufacturing tasks. Then, it analyses and evaluates the network structure characteristic index of the production and manufacturing scheduling process, which provides a decision basis for the task processing process design and scheduling planning in the intelligent manufacturing.

关键词： Complex network nsga-ii algorithm Network characteristics Multi -objective optimization

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Nickel-based polycrystalline superalloy composition design framework based on non-dominated sorting genetic algorithm ii

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COMPUTATIONAL MATERIALS SCIENCE 2023年第1期220卷

作者： Liu, Yaxi Xu, Bin Huangfu, Wei Yin, Haiqing Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China Univ Sci & Technol Beijing Beijing Adv Innovat Ctr Mat Genome Engn Beijing Engn & Technol Res Ctr Convergence Network Sch Comp & Commun Engn Beijing 100083 Peoples R China Univ Sci & Technol Beijing Collaborat Innovat Ctr Steel Technol Beijing 100083 Peoples R China Univ Sci & Technol Beijing Shunde Grad Sch Shunde 528399 Peoples R China Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China

Nickel-based superalloy composition design problem has always been a fundamental task for growing demands in intended applications. In this paper, we establish a nickel-based polycrystalline superalloy composition design framework to excavate novel alloys with superior properties efficiently and comprehensively. First, we establish a model of creep resistance with respect to composition proportions with little data knowledge and computational effort based on the Gaussian process regression. Then, we solve the constrained multi -objective nickel-based superalloy composition design problem, aiming at maximizing the creep resistance while minimizing the alloy cost, by meta-heuristic non-dominated sorting genetic algorithm ii efficiently, which enables fast searching rather than simply ranking in large-scale solution space. Pareto fronts containing optimal candidate alloys where the trade-off between creep resistance and alloy cost is fully considered are obtained. Finally, we filter the unqualified candidate alloys that dissatisfy the phase fraction of superalloy on several Pareto fronts based on some screening indicators computed by JMatPro software, and a set of well-performed alloys with high creep resistance and low alloy cost is obtained.

关键词： Composition design Nickel-based superalloy Creep resistance prediction Gaussian process regression nsga-ii algorithm

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Credit evaluation method of generating companies considering the market behavior in China electricity market

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ENERGY SCIENCE & ENGINEERING 2021年第9期9卷 1554-1567页

作者： Xie, Jingdong Wang, Shiyao Zhou, Xuemei Sun, Bo Sun, Xin Shanghai Univ Elect Power Shanghai 200090 Peoples R China

Since the reformation of the electricity market of China is increasing and the modernization of the national governance system is being promoted, the electricity market management system needs to be gradually improved. Credit evaluation is an essential part of the electricity market management system. Therefore, a complete credit evaluation system plays a fundamental role in ensuring that the electricity market can operate safely, stably, efficiently, and reliably. The traditional credit evaluation methods focus on the financial situation and credit records of the generating companies. With the gradual development of the electricity market transactions, the market behavior needs to be included in the credit evaluation indicator system to standardize the behavior of the generating companies and reduce the risks of the market transactions. This study establishes a complete credit evaluation system from three perspectives: market behavior, financial situation, and social responsibility. In addition, to determine the weight of indicators in the credit evaluation, the analytic hierarchy process (AHP) algorithm, fuzzy theory, and the non-dominated sorted genetic algorithm ii (nsga-ii) algorithm are combined. The variance of the evaluation results and the deviation degree of the indicator weight are considered the objective functions of the nsga-ii algorithm to optimize the indicator weight. Finally, comparing as an example the results of the credit evaluation before and after the optimization of an electricity market shows that the credit evaluation method can effectively distinguish the generating companies that adopt different market behaviors and has a high practical significance.

关键词： credit evaluation electricity market nsga-ii algorithm weight optimization

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A multi-objective optimization design method for underwater composite sandwich structures with high acoustic transmission and low vibration performance

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SHIPS AND OFFSHORE STRUCTURES 2024年

作者： Li, Yongzheng Kong, Dedong Zhang, Haihua Zhang, Yuyang Xia, Maolong Jiangsu Univ Sci & Technol Zhenjiang 212100 Peoples R China China Ship Sci Res Ctr Shanghai Branch Shanghai Peoples R China Taihu Lab Deepsea Technol Sci Lian Yun Gang Ctr Lianyungang Peoples R China

To address the issue of reduced structural integrity and optimality resulting from the conventional serial design of sonar dome structures, this paper establishes a multi-objective optimal design model for composite sandwich structures, utilising the Non-dominated Sorting Genetic algorithm-ii (nsga-ii). The model's stability and reliability are subsequently validated. Upon this model, a structural optimization design technique is postulated for composite sandwich structures within the realm of Fluid-Structure Interaction (FSI) multi-physics coupling. This approach aims to optimize the lightweight, high-rigidity composite sandwich structure, enhancing its acoustic transmission and minimizing vibration performance under turbulent pressure pulsations. The suggested method notably enhances the efficiency of structural design while ensuring precision. The proposed method effectively addresses the deficiency of serially designed sonar domes by neglecting the synergistic effects among multiple disciplines. In summary, this approach offers technical support and new research perspectives for the design of sonar domes under the coupling of multiple physical fields.

关键词： Composite sandwich structure nsga-ii algorithm fluid and structure interaction (FSI) sonar dome

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Comparative study on single-objective optimization and multi-objective optimization of convex textured friction couple performance

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SURFACE TOPOGRAPHY-METROLOGY AND PROPERTIES 2023年第1期11卷 015017-015017页

作者： Yu, Xiaodong Shi, Guangqiang Zhao, Feihu Feng, Yanan Gao, Weicheng Harbin Univ Sci & Technol Key Lab Adv Mfg & Intelligent Technol Minist Educ Harbin 150080 Peoples R China

To improve the friction property of the friction pair of the hydrostatic thrust bearing, the surface with convex textures is designed at the bottom of the oil cavity, and the effect of convex textures on the interstitial oil film performance is analyzed. The interstitial oil film in contact with convex textures is simulated and studied by the computational fluid dynamics method. The study shows that the oil cavity with the convex structures can significantly improve the friction characteristics of the gap oil film in the hydrostatic thrust bearing. In order to further study the effect of texture parameters (texture radius, texture spacing , texture quantity and texture area ratio ) on its performance, the method based on the full factor test is used for single objective optimization, and the methods based on the BBD response surface and the nsga-ii algorithm are used for multiple target collaborative optimization. The full factor test with the main effect shows that the best combination with the bearing capacity is 0.5 mm, 7 mm, 7 and 1.6%, and the best combination with the rigidity is 0.3 mm, 5 mm, 5 and 1.13%. The influence of textures on the maximum temperature of oil film is basically unchanged and the bearing capacity is in inverse proportion to the friction factor. When considering the interaction between texture parameters, the BBD response surface method is used for multi-objective optimization. The study shows that the texture radius is 0.7 mm, the texture spacing is 7 mm, the quantity of textures is 6.2, and the area ratio is 3.14%, the optimal response values can be obtained, which the bearing capacity is 8519.31 N and the rigidity is 1.31868 E + 12 N m(-1). The multi-objective optimization analysis of the nsga-ii algorithm based on the BBD response surface model shows that the algorithm can obtain a Pareto solution set. Each set of solutions obtained by the nsga-ii algorithm is the optimal solution. Both the BBD response surface method and the nsga-ii al

关键词： convex textures texture parameters friction performance full factor test BBD response surface analysis nsga-ii algorithm

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