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A metamodeling with CFD method for hydrodynamic optimisations of deflectors on a multi-wing trawl door

OCEAN ENGINEERING 2021年 232卷 109045-109045页

作者： Wang, Gang Huang, Liuyi Wang, Lei Zhao, Fenfang Li, Yuyan Wan, Rong Ocean Univ China Coll Fisheries Qingdao 266003 Peoples R China East China Sea Fisheries Res Inst Shanghai 200090 Peoples R China Natl Engn Res Ctr Ocean Fisheries Shanghai 201306 Peoples R China Shanghai Ocean Univ Coll Marine Sci Shanghai 201306 Peoples R China

In the present work, a metamodeling with Computational Fluid Dynamics (CFD) method for the hydrodynamic optimisations of deflectors on the multi-wing trawl door is introduced. Then a comparative analysis of Kriging and Artificial Neural Networks metamodeling methods is carried out, using the effects of relative camber, thickness and the installed angles of deflectors on the hydrodynamics as a case study for optimisations. Based on CFD simulations (verified by the wind tunnel experiment), a strict procedure including metamodeling and multi-objective genetic algorithm is established. Efficiency and accuracy between the two methods are discussed. Finally, this study studied the flow patterns of the optimal otter board in the higher working efficiency state. The results showed that Kriging performs better than Artificial Neural Networks methods in 2-factor metamodeling. However, in the 3-factor investigation, Artificial Neural Networks has more advantages in the prediction of drag, while Kriging is better in the lift component of hydrodynamics. The relative camber has the considerable impacts on the hydrodynamics of the trawl door, whereas the thickness of deflectors shows the prominent influence on the resistances, followed by lift forces. The effect of installed angles on the hydrodynamic loadings is more remarkable than that of thickness and relative camber. In flow visualisation, the disappearance of the vortex on the deflector suction side indicates the rationality of the newly-proposed procedure used for optimisations.

关键词： Metamodeling Artificial Neural Networks Kriging multi-objective genetic algorithm Trawl door Hydrodynamics

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Feasibility of micro-hole machining in fiber laser trepan drilling of 2.5D Cf/SiC composite: Experimental investigation and optimization

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OPTIK 2021年 242卷 167186-167186页

作者： Liu, Chang Zhang, Xianze Gao, Lei Jiang, Xiaogeng Li, Cheng Yang, Tao Tiangong Univ Tianjin Key Lab Adv Mechatron Equipment Technol Sch Mech Engn Tianjin 300387 Peoples R China

The special structure characteristics make 2.5D C-f/SiC composite a key material in high-temperature parts of aerospace field. However, the micro-hole machining based on fiber laser has been a challenge due to effect of taper and heat affected zone. This paper proposed the feasibility on high-quality micro-hole machining of the 2.5D C-f/SiC composite by using fiber laser trepan drilling, including experimental investigation and optimization analysis for the first time. The key laser parameters, such as scanning speed, pulse frequency, pulse width, defocus amount, and energy percentage are introduced as the optimization parameters, and taper and average thickness of heat affected zone (HAZ(a)) are chosen as objectives. A comprehensive analysis method including Taguchi L-16(4(5)) orthogonal array, analysis of variance (ANOVA), regression modeling, and multi-objective genetic algorithm (MOGA-II) is presented on fiber laser trepan drilling to minimize the taper and the HAZ(a). The importance and interaction of the laser parameters on the taper and HAZ(a) are obtained. The results show that the fiber laser trepan drilling integrated with the proposed experimental and optimization analysis can achieve the high-quality micro-hole machining of 2.5D C-f/SiC composite. The presented methodology can be also used in high-quality machining of other fields.

关键词： Fiber laser 2.5D c(f)/SiC composite Micro-hole machining Feasibility analysis multi-objective genetic algorithm

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Spatial Geometry Design of a Low Earth Orbit Constellation for Iranian Regional Navigation Satellite System

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JOURNAL OF AEROSPACE TECHNOLOGY AND MANAGEMENT 2021年 13卷

作者： Zardashti, Reza Emami, Shiva Malek Ashtar Univ Technol Fac Aerosp Tehran Iran

The regional navigation satellite system (RNSS) is recently used in some countries to cover or enhance their local navigation. The most important satellite navigation systems to date are in the Earth medium orbit (MEO) and Earth synchronous Earth orbit (GEO), which are characterized by big satellites, and high launch, construction, and operation costs. In contrast, low Earth orbit (LEO) small-satellite constellations have recently become attractive because of their advantages, such as a significant reduction in system cost, an increase in communication volume, and a reduction in latency. Therefore, in this study, the spatial geometry of a LEO constellation is designed for Iran to increase the required regional navigation performance. For this purpose, the optimal constellation configuration is obtained through a multi-objective genetic algorithm (MOGA) utilizing a cost function with a combination of the geometry dilution of precision (GDOP), the number of satellites, and orbital height in the form of a design procedure. Moreover, reducing the feasible region of longitude of the ascending nodes of orbit planes is applied in the design process to reduce the search space. The simulation results indicate the constellation designed performance.

关键词： Regional navigation satellite system Satellite constellation multi-objective genetic algorithm Geometry dilution of precision Low Earth orbit

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A system-of-systems meta-architecting approach for seru production system design 15

A system-of-systems meta-architecting approach for seru prod...

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IEEE 15th International Conference of System of Systems Engineering (SoSE)

作者： Vanfossan, Samuel Dagli, Cihan H. Kwasa, Benjamin Missouri Univ Sci & Technol Engn Management & Syst Engn Rolla MO 65409 USA

ISBN: (纸本)9781728180502

Sponsored by expedient technologic innovation, consumers frequently expect manufacturer offerings to exhibit extensive product variety and regular product advancement. These expectations have rendered many traditional production practices less applicable. Chiefly impacted is the notion of mass-produced, low-variety artifacts via massive assembly lines. These operations have difficulty meeting the high-customization, short-lifecycle requirements imposed by contemporary demand. Many industries and organizations have begun the transformation from these rigid assembly mechanisms to a more versatile, cellular production strategy known as seru production. To facilitate this transition, methods are needed to aid manufacturers in appropriately selecting and arranging seru system components, a critical step in seru system design. Herein, a generalized model is proposed utilizing a system-of-systems architecting approach to determine the component assembly best suiting the needs of the manufacturing entity. Candidate architectures are generated and evaluated using a multi-objective genetic algorithm from which a preferred alternative is selected through a fuzzy inference system. Directing this genetic algorithm, domain-independent objectives are presented, maintaining applications to most seru production design scenarios. The proposed method is then applied to a camera production example, culminating in the identification of a well-performing architecture. The presented method should find increased use as organizations further adopt this flexible production methodology.

关键词： Seru production system meta-architecture generation multi-objective genetic algorithm fuzzy inference system system-of-systems architecting

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A growing complex network design method with an adaptive multi-objective genetic algorithm and an inner link restructuring method

A growing complex network design method with an adaptive Mul...

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Annual Conference of the Society-of-Instrument-and-Control-Engineers (SICE)

作者： Mizuno, Haruki Okamoto, Takashi Koakutsu, Seiichi Hirata, Hironori Chiba Univ Grad Sch Engn Chiba Japan

ISBN: (纸本)9784907764401

Many systems that can be modeled using network structures appear in various fields such as informatics, social science, economics, ecology, biology, and engineering. If these systems can be modeled as complex network systems, a complex network design method that finds a desired network structure can become one of strong tools in large-scale system designs. Conventional complex network design methods generally tackle static networks. On the other hand, a growing complex network design method has been proposed. In this method, the network is grown with determining the link structure of the newly-added node in order to obtain a desired network. In this design method, it is expected that characteristics of the optimization problem solved in the algorithm vary along with growth of the network. However, parameters of the optimization method are fixed;hence, its search process may be inefficient. In the design method, connection targets of a new node are only determined, and the structure of the existing network is not changed. Therefore, if the initial network has a large number of nodes, the desired network may not be obtained by using the design method. In this study, we propose to introduce an inner link restructuring method and an adaptive MOGA, that is, an adaptive SPEA2 into the growing complex network design method to deal with foregoing issues. Then, we confirm the effectiveness of the proposed method through numerical experiments.

关键词： Complex Network multi-objective Optimization Growing Network Network Design multi-objective genetic algorithm

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Cost-effective retrofits of power grids based on critical cascading failure scenarios identified by multi-group non-dominated sorting genetic algorithm

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INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 2020年 49卷

作者： Choi, Eujeong Song, Junho Korea Atom Energy Res Inst Seoul South Korea Seoul Natl Univ Dept Civil & Environm Engn Seoul South Korea

Power supply network is one of the most critical infrastructure networks of urban communities, but prone to the risk of cascading failures. In efforts toward disaster risk reduction of urban communities, it is thus important to identify critical cascading failure scenarios of the power supply networks and prepare effective countermeasures based on the identified scenarios. While addressing these issues, previous research efforts focused on cascading failure scenarios induced by a single component although those induced by multiple components may occur under natural or man-made disaster events. A major challenge in this problem is high computational cost required for simulating cascading failure scenarios and solving large-size optimization problems. This paper first presents an effective method to identify multi-component failure combinations entailing critical cascading failures in the network by using the overload cascading model, the multi-group non-dominated sorting genetic algorithm (MG-NSGA), and the concept of critical zone. Based on the identified critical scenarios, cost-effective retrofit combinations against the risk of cascading failures are also identified using the proposed 'elite set updating' method. The proposed disaster risk reduction decision-making methods are demonstrated and tested by numerical examples of two complex power supply networks.

关键词： Power supply network Cascading failure scenarios Overload cascading failure multi-objective genetic algorithm Retrofit optimization

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Optimised Decision Making of Transportation Infrastructure Asset Management

Optimised Decision Making of Transportation Infrastructure A...

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世界交通运输工程技术论坛（WTC2021）

作者： Jiarong Li Chang'an University Department of Traffic Engineering

After more than 30 years of rapid development and construction,the transportation infrastructure achievements in China have attracted worldwide *** the other hand,the demand for Transportation Infrastructure Asset Management(TIAM)is growing quickly and strongly,and the rapid,safe and high-density traffic development trends have placed new demands on transportation infrastructure construction and *** the durable period of the pavement,it is still necessary to continue investing a large amount of funds to maintain and rebuild the pavement to keep their good performance,but the funds are not always available,so how to allocate the maintenance funds reasonably and keep the pavement in a good condition at the same time has become a hotpot,there are many decision-making methods to deal with it,but all of them have some deficiencies,this paper utilizes the inherent parallel mechanism and the characteristics of global optimization of genetic algorithm(GA),proposes a multi-objective genetic algorithm(MOGA)to simulate the problem of TIAM as a biological evolution problem,and by comparing the fitness of each generation of individuals to generate a new generation,in subsequent iterations,the generation is constantly replaced with a high fitness alternative to a low fitness value,so that after several generations,the best can be *** optimization result of a case study shows that the application of this algorithm in TIAM is successful and effective.

关键词： Transportation infrastructure asset management Optimised decision-making multi-objective genetic algorithm Large scale road network

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A multiobjective genetic algorithm for Analysis, Design and Optimization of Antipodal Vivaldi Antennas 9

A Multiobjective Genetic Algorithm for Analysis, Design and ...

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IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC)

作者： Antonio Pumallica-Paro, Marco Luis Arizaca-Cusicuna, Jorge Clemente-Arenas, Mark Univ Nacl San Antonio Abad Cusco Escuela Profes Ingn Elect Cuzco Peru Univ Nacl Ingn INICTEL UNI Inst Nacl Invest & Capacitac Telecomunicac DIDT Grp Radio Frecuencia Microondas & Opt G RFMO Av San Luis 1771 Lima 41 Peru

ISBN: (纸本)9781728105666

In the this contribution, a multi-objective genetic algorithm (MOGA) was implemented to analyze, design and optimize several Antipodal Vivaldi Antennas (AVA) that are being used on Ground Penetration Radars (GPR) applications. This algorithm was implemented and used as an optimization tool in a commercial available software. Directivity, lower cutoff frequency (LCF), bandwidth and cross-polarization were the objectives to be optimized. For the use of the MOGA, the 3D model of the antenna is built in the simulator. Some of its parameters are defined as variables, as the dimensions and shape of the antenna (Individual) depend on the value that its parameters (Genes) take. This work proves to be simple and time saving tool to optimize parameters in a geometry changing system as GPR.

关键词： multi-objective genetic algorithm Antipodal Vivaldi Antennas Ground Penetrating Radar

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An improved procedure to implement NSGA-III in coordinate waste management for urban agglomeration

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WASTE MANAGEMENT & RESEARCH 2019年第11期37卷 1161-1169页

作者： Qu, Lili Zhou, Zhihao Zhang, Tianzhu Zhang, Huanan Shi, Lei Tsinghua Univ Sch Environm State Key Joint Lab Environm Simulat & Pollut Con Beijing Peoples R China Columbia Univ Dept Earth & Environm Engn New York NY 10027 USA

With the growth of urbanization in countries globally, large cities have often formed clusters of urban agglomerations in metropolitan areas. The coordinated management of regional solid waste produced by such urban agglomeration poses a typical high-dimensional, multi-objective optimization issue. This paper aims to introduce a procedure to implement the third-generation genetic algorithm (NSGA-III), an established multi-objective genetic algorithm based on non-dominated sorting mechanisms, for the purpose of evaluating environmental and economic benefits simultaneously while seeking the optimal solutions for coordinated management among multiple recycling centres. In this study, two series of scenarios were abstracted from scrap tire recycling, representing linear calculation and nonlinear calculation cases separately. Several improvements were made to the originally published NSGA-III procedure that solve the problem of non-convergence for hypervolumes of the output. Through comparisons of calculation results, an improved procedure is suggested and shown to have improved performance.

关键词： Urban agglomeration waste management multi-objective genetic algorithm NSGA-III Jing-Jin-Ji

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multi-objective optimization of wavy microchannel heat sinks with symmetric configurations generated by interpolation curves

Results in Engineering

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Results in Engineering 2025年 26卷

作者： Zhen Li Haitao Han Xunqing Huang Jiarun Lou Qiancan He Haoran Zheng Xiangyao Xue Shuai Shao Changchun Institute of Optics Fine Mechanics and Physics (CIOMP) Chinese Academy of Sciences Changchun 130033 PR China University of Chinese Academy of Sciences Beijing 100039 PR China School of Mechanical Engineering Guizhou Institute of Technology Guiyang 550003 PR China Institute of laser manufacturing Henan Academy of Sciences Zhengzhou 450000 PR China

Microchannel heat sinks (MCHS) with symmetric configurations enhance fluid flow disturbances through expansion-contraction sections, improving heat transfer performance. This paper presents an optimal design for symmetrically curved MCHS generated by using interpolation curves. The multi-objective genetic algorithm based on decomposition (MOEA/D) is used to achieve the optimization of three design variables, and pumping power and thermal resistance are considered as the objective functions. Partial correlation analysis reveals that the design variables W 1 and W 3 describing the width of microchannels have the greatest influence on the two objective functions with different trends. The technique for order of preference by similarity to ideal solution (TOPSIS) is used to select the optimal compromise solution from the Pareto-optimal solutions. The channel first widens and then narrows in each unit of the TOPSIS solution and the solution with the minimum consumption of pumping power and maximum thermal resistance, which is opposite to the solution with the maximum consumption of pumping power and minimum thermal resistance. The widening position in TOPSIS solution is closer to the downstream and this configuration reduces the pressure drop while maintaining the fluid disturbance effect of the expansion-contraction sections. Compared to the straight channel, the optimal compromise solution selected by TOPSIS strategy reduces the consumption of pumping power by 10.0 % and the thermal resistance by 47.0 % concurrently. Therefore, the optimal MCHS with the TOPSIS solution and the optimization approach are highly applicable in practice.

关键词： Microchannel heat sinks Response surface multi-objective genetic algorithm multi-criteria decision-making Optimal compromise solution Heat transfer enhancement

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