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Marine shaft optimization using surrogate models and multi-objective optimization

STRUCTURES 2024年 63卷

作者： Nickabadi, Saeid Hosseini, Seyed Mohammadreza Bathaee, Hasan Alirezaeipour, Saeid Univ Imam Khomeini Marine Sci Fac Mech Engn Nowshahr Iran Univ Tehran Fac Mech Engn Tehran Iran Univ Tarbiat Modares Fac Mech Engn Tehran Iran

This paper aims to obtain an application software using Ansys software in which a static, dynamic, and modal analysis for the power transmission of ships is presented. The objective functions of this research are maximum static stress, maximum dynamic stress, shaft mass, and modal shaft frequency analysis. A complete, comprehensive, and generalizable model for metal shaft types is presented. Then, using the kriging response surface and multi-objective genetic algorithm (NSGA II), these goals are optimized simultaneously. In this research, the optimization parameters are geometric parameters of the shaft design, including the position of the supports and the inner and outer diameters of the shaft. As a result of this optimization, the shaft's maximum static and dynamic stresses are reduced by 36% and 42%, respectively. The shaft's mass, which is one of the most critical factors during the shaft and its vibrations, is reduced by about 9%. In this regard, the first natural frequency of the optimized shaft increased by about 28.5% compared to the initial shaft.

关键词： Ship propulsion shaft Metal shaft Static and dynamic analysis Modal analysis Optimization Kriging response level multi-objective genetic algorithm

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Cost-effective sensor placement optimization for large-scale urban sewage surveillance

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SUSTAINABLE CITIES AND SOCIETY 2024年 103卷

作者： Wang, Sunyu Xu, Ke Zhou, Yulun Univ Hong Kong Dept Urban Planning & Design Hong Kong Peoples R China Univ Calif Los Angeles Samueli Sch Engn Los Angeles CA 90095 USA Univ Hong Kong Musketeers Fdn Inst Data Sci Hong Kong Peoples R China

Early pandemic outbreak detection in cities is a crucial but challenging task. Complementary to the costly massive individual testing, urban sewage surveillance offers a rare, cost-effective solution for large-scale monitoring of pandemic spread in cities with minimal interference to people's lives. One emerging question is how to derive a cost-effective sensor placement plan in city -scale sewage networks having complicated topologies. Inspired by remote sensing, we first provide a general multi -objective formulation of the optimal sensor placement problem on directed networks. Then, we introduce a connectivity -based objective evaluation approach and embed it into an NSGA-II algorithm to enable efficient optimization on large-scale directed graphs. The effectiveness of the proposed method is verified on a real -world sewage network in Hong Kong serving more than 500,000 urban residents. Results show that the proposed method efficiently generated optimal sensor placement plans on city -scale networks. Optimized sensor placement plans outperformed human placement heuristics by a significant margin of 102%, highlighting the necessity for data -driven decision support for large-scale urban sensing. Methodologically, this study provides a benchmark problem and datasets for network -based spatial optimization studies. Codes and datasets developed in this study are open -sourced to support future research in a real -world scenario.

关键词： Optimal sensor placement Network-based spatial optimization multi-objective genetic algorithm Sewage surveillance Pandemic control

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Optimization Research on the Impact of Charging Load and Energy Efficiency of Pure Electric Vehicles

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PROCESSES 2024年第11期12卷 2599页

作者： Xin, Huajian Li, Zhejun Jiang, Feng Mo, Qinglie Hu, Jie Zhou, Junming Guangxi Vocat & Tech Inst Ind Sch Intelligent Mfg Coll Nanning 530001 Peoples R China Guangxi Univ Sci & Technol Sch Mech & Automot Engn Liuzhou 545616 Peoples R China

In this paper, the negative impact of the charging load generated by the disorderly charging scheme of large-scale pure electric vehicles on the operation performance of the power grid system and the problem of reducing its charging energy efficiency are studied and analyzed. First, based on Matlab 2022a simulation software and the Monte Carlo random sampling method, the probability density model of the factors affecting the charging load is constructed, and the total charging load of different quantities is simulated. Second, the IEEE33-node distribution network model is introduced to simulate the influence of charging load on the grid under different permeability schemes. Finally, the multi-objective genetic algorithm is used to optimize the charging cost and battery life. Taking the 20% permeability scheme as an example, the research results show that, compared with the disorderly charging scheme, the multi-objective optimization scheme reduces the peaking valley difference rate by 24.34%, the charging load power generation cost by 29.5%, and the charging cost by 23.9%. The power grid profit increased by 45.8%, and the research conclusion has practical significance for the energy efficiency optimization of pure electric vehicles.

关键词： pure electric vehicles Monte Carlo method IEEE model multi-objective genetic algorithm

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multi-condition stability analysis and lightweight research of mining wide-body dump truck compartment

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MEASUREMENT SCIENCE AND TECHNOLOGY 2024年第4期35卷 045603-045603页

作者： Liu, Zhihai Liu, Dongyang Tian, Shaolu Han, Wenyu Zhao, Xieguang Shandong Univ Sci & Technol Coll Transportat Qingdao 266590 Peoples R China Shandong Univ Sci & Technol Coll Mech & Elect Engn Qingdao 266590 Peoples R China Shandong Univ Sci & Technol Coll Intelligent Equipment Tai An 271001 Peoples R China

This paper proposes a multi-condition optimization method based on single condition optimization and weight. This method analyzes and discusses various working states of the wide-body dump truck and optimize its structure. Firstly, the modal shape and natural frequency of the carriage under modal conditions are analyzed using the finite element method. Combined with the mechanic's theory, the carriage's force, deformation, and stress are studied under the turning and partial load conditions. This part provides a basis for subsequent stability analysis and lightweight research. According to the filtering white noise method and differential equation method, the f-class road model and the vehicle system dynamics model are established in MATLAB to study the influence of road vibration on the stability of the dump truck during operation. The carriage vibration data prove that the road vibration causes the low order resonance of the carriage and affects the stability of the dump truck. This part provides a basis for the subsequent stability optimization. Based on the above analysis, a multi-objective genetic algorithm based on the response surface is used to optimize the structural parameters of the carriage under partial load conditions, turning conditions and modal conditions, to realize the optimization of stability, mass, stress and deformation of the carriage. Finally, the entropy weight method is used to fuse the optimization results of the three working conditions. The correctness of the comprehensive optimization results is verified, and the wide-body dump truck carriage optimization is realized, proving the feasibility of the proposed method.

关键词： lightweight excitation frequency response surface optimization multi-objective genetic algorithm weighting

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Performance enhancement of segmented annular thermoelectric generator based on multi-parameter and multi-objective optimization

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THERMAL SCIENCE AND ENGINEERING PROGRESS 2024年 47卷

作者： Sun, Yajing Zhai, Pengcheng Wang, Shuhao Duan, Bo Li, Guodong Chen, Gang Wuhan Univ Technol Hubei Key Lab Theory & Applicat Adv Mat Mech Wuhan 430070 Peoples R China Wuhan Univ Technol State Key Lab Adv Technol Mat Synth & Proc Wuhan 430070 Peoples R China Natl Univ Singapore Dept Mech Engn Singapore 119077 Singapore

The excellent performance of annular thermoelectric generator (ATEG) is crucial for its commercial application, and it has been validated that the segment configuration can effectively enhance the ATEG performance. Nevertheless, owing to the limitations in conventional optimization methods which fail to simultaneously consider the co-influence of multiple parameters, further exploration is required for achieving optimal design of segmented annular thermoelectric generator (SATEG). In this study, we present a novel approach combining multi-objective genetic algorithm (MOGA) with finite element method to implement the multi-parameter and multi-objective optimization of SATEG. This approach not only reduces the computational cost but also ensures precise control on SATEG temperature below its maximum acceptable operation temperature. Furthermore, the optimization results highlight the importance of emphasizing diversity between p- and n- type TE legs as well as recognizing the different optimal geometrical structures for two types of TE legs, which have been always overlooked in previous researches. By adopting the optimal geometrical structure at a hot end temperature of 600 K, significant improvements in output power of 32.839 % and efficiency of 61.915 % are achieved for SATEG.

关键词： Segmented annular thermoelectric generator multi-parameter and multi-objective optimiza-tion multi-objective genetic algorithm Segment ratio Performance enhancement

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Hybrid modeling and optimization of fiber laser hole cutting of austenitic stainless-steel sheets using response surface

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LASER PHYSICS 2024年第4期34卷 045602-045602页

作者： Niu, Zhenhua Dehkordi, Mohammad Hossein Razavi Ghazi, Mohammadreza Akbari, Mohammad Coll Electromech Engn Anyang Vocat & Tech Coll Anyang 455000 Peoples R China Islamic Azad Univ Dept Mech Engn Najafabad Branch Najafabad Iran Islamic Azad Univ Aerosp & Energy Convers Res Ctr Najafabad Branch Najafabad Iran

In this study, an efficient approach was proposed to systematically model and optimize the laser small hole cutting process parameters using a hybrid approach for the design of experiment and multi-objective genetic algorithm optimization. The central composite design and response surface methodology were used to effectively model the impact of four main factors: cutting speed, laser power, gas pressure and focal distance on the responses. The responses considered were hole diameter circularity tolerance, spattering and cut kerf width, which were used to evaluate the quality of the laser hole cutting. The regression equations were used to model the effect of process parameters and their interactions on the responses. These regression models were then used as objective functions for optimization. The results show that the focal distance and laser power have had a significant influence on the hole diameter circularity tolerance and the variation in size of the cut kerf. In particular, the melted material spattering rate increased threefold when the focal distance increased from 0.4 to 0.8 mm. The optimization results highlighted that the best outcomes in terms of minimum deviation, spatter, and the cut-kerf width were achieved at low power (between 605 and 685 W) and low speeds (in the range of 11.1-12.7 m min-1). The optimal focal distance for all solutions was found to be 0 mm for the gas pressure (between 6.5 and 8 bars) to minimize the objective functions.

关键词： laser hole cutting response surface methodology multi-objective genetic algorithm dimensional tolerances optimization

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multi-objective Optimization of Underwater Towed System during CourseKeeping Motion

Multi-Objective Optimization of Underwater Towed System duri...

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International Conference on Mechanical Design and Simulation (MDS)

作者： Cheng, Yanyan Li, Yunzhou Yang, Chong Kunming Ship Borne Equipment Res & Test Ctr Res Off 1 Kunming Peoples R China

ISBN: (纸本)9781510655263;9781510655256

In this paper, the underwater towed system during the course-keeping motion was taken as the research object, in addition, the governing equation of motion was given as well. By the means of the experimental data obtained by the design of experiment, the second-order polynomial response surface models reflecting the steady-state motion characteristics of the towrope were established. Apart from mentioned above, the tail drag depth and the head tension were taken as objective functions, and the optimal solution set of Pareto was obtained by using the multi-objective optimization algorithm. The results shown that the approximate models were used to optimize the towrope when the parameters of the towrope were within a certain range, which can quickly and accurately analyzed the influences of each parameter on the steady-state motion characteristics of the towrope.

关键词： underwater towed system course-keeping motion optimal Latin hypercube design response surface method multi-objective genetic algorithm

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Optimal design of micro-dimples on crankpin bearing surface for improving engine's lubrication and friction

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INDUSTRIAL LUBRICATION AND TRIBOLOGY 2021年第1期73卷 52-59页

作者： Jiao, Renqiang Nguyen, Vanliem Le, Vanquynh Bui, Vancuong Hubei Polytech Univ Sch Mech & Elect Engn Huangshi Hubei Peoples R China Thai Nguyen Univ Technol Fac Automot & Power Machinery Engn Thai Nguyen Vietnam

Purpose The purpose of this paper is to investigate the optimal design of micro-dimples on the bearing surface of the crankpin bearing (CB) to ameliorate the engine's lubrication and friction (ELF). Design/methodology/approach A hydrodynamic model of the CB considering the influence of the asperity contact is built under the impact of the dynamic loading of the slider-crank-mechanism. The micro-dimples on non-slip surface of the bearing are designed and optimized based on the lubrication model and multi-objective genetic algorithm. The performance of optimal micro-dimples on ameliorating the ELF is analyzed and compared with that of optimal CB dimensions via the reduction of the solid contact force, friction force and friction coefficient between the crankpin and bearing surfaces;and the increase of the oil film pressure. Findings The optimal design of micro-dimples on the bearing surface may not only greatly ameliorate the ELF but also make the rotation of the crankpin inside the bearing more stable in comparison with the optimization of CB dimensions. Originality/value This study results not only clearly ameliorates the ELF but also can be applied to the slip/non-slip surface pairs of other journal bearings to enhance their lubrication performance.

关键词： Crankpin bearing Micro-dimples Slip non-slip surfaces Lubrication and friction multi-objective genetic algorithm

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Tribological performance evaluation on brake friction material by using multi-objective optimization methods

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INDUSTRIAL LUBRICATION AND TRIBOLOGY 2021年第4期73卷 599-605页

作者： Oktem, Hasan Shinde, Dinesh Kocaeli Univ Hereke Asim Vocat Sch Div Machine & Met Technol Kocaeli Turkey Gujarat Technol Univ Ahmadabad Gujarat India

Purpose The purpose of this study is to present a novel approach for the evaluation of tribological properties of brake friction materials (BFM). Design/methodology/approach In this study, a BFM was newly formulated with 16 different ingredients and produced using an industrial hot compression molding process. Experimentation was carried out on the brake tester, which was developed for this purpose according to SAE J661 standards. The braking applications, sliding speed and braking pressure were considered as performance parameters, whereas coefficient of friction (CoF) and wear rate as output parameters. The influence of the performance parameters on the output was studied using response surface plots. Analysis of variance and regression analysis was accomplished for post-experimental evaluation of results. multi-criteria decision-making (MCDM) and multi-objective genetic algorithm (MOGA) were applied for estimating the most critical performance parameter combination to evaluate the BFM. Findings The present experimental model was significant and effectively used to predict the performance. MCDM generates the optimal values for the parameters braking applications, braking pressure (Bar) and sliding speed (rpm) as 1000, 30 and 915, whereas MOGA as 1008, 10.503 and 462.8202, respectively. Originality/value An efficient model for performance evaluation of the BFM considering maximum CoF and minimum wear rate was experimentally presented and statistically verified. Also, the two multi-objective optimization methodologies were implemented and compared. A comparison between the results of MCDM and MOGA reveals that MOGA yields 30% better results than MCDM.

关键词： Optimization multi-objective genetic algorithm Coefficient of friction multi-criteria decision-making Brake friction materials Wear rate

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Simultaneous multi-objective Optimization of Semi-active Intermediate Isolation System and Building Structure

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INTERNATIONAL JOURNAL OF STEEL STRUCTURES 2021年第2期21卷 604-612页

作者： Kim, Hyun-Su Kang, Joo-Won Sunmoon Univ Div Architecture Asan South Korea Yeungnam Univ Sch Architecture Gyongsan South Korea

Recently, to reduce seismic responses, dozens of high-rise buildings in Japan and Korea have adopted the intermediate isolation system (IIS). These applications have shown successful response reduction performance for tall buildings. The important dynamic responses of building structures with the IIS are the peak intermediate isolator drift (IID), and the peak inter-story drift (ISD). The semi-active intermediate isolation system (SAIIS) was developed to more effectively reduce these seismic responses. In previous study, the authors showed that the SAIIS using magnetorheological dampers successfully reduced both the IID and the ISD. However, the optimal design of the SAIIS only was conducted, without considering the building structure. If both the SAIIS and the building structure properties are considered in the optimal design procedure, more effective optimal design for both the SAIIS and the building structure can be achieved. In this research, a simultaneous multi-objective optimization (MOO) method of the SAIIS and the building structure is proposed to achieve this. genetic algorithm was selected for simultaneous MOO of the SAIIS and the building structure. The fuzzy inference controller was selected as a control algorithm. The authors show that in comparison to the sequential optimization procedure that practical applications generally use, the simultaneous MOO method can provide much better control capacity and structural design process.

关键词： Semi-active intermediate isolation system multi-objective genetic algorithm Simultaneous structural optimization Seismic response reduction

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