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Thematische Bibliographien / Multi-objective topology optimization / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Multi-objective topology optimization“

Autor: Grafiati

Veröffentlicht am 30. Juni 2021

Zuletzt aktualisiert am 7. Februar 2022

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1

Lee, Chen Jian Ken, und Hirohisa Noguchi. „515 Multi-objective topology optimization involving 3D surfaces“. Proceedings of The Computational Mechanics Conference 2008.21 (2008): 233–34. http://dx.doi.org/10.1299/jsmecmd.2008.21.233.

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2

Kunakote, Tawatchai, und Sujin Bureerat. „Multi-objective topology optimization using evolutionary algorithms“. Engineering Optimization 43, Nr. 5 (Mai 2011): 541–57. http://dx.doi.org/10.1080/0305215x.2010.502935.

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3

Gong, Yunyi, Yoshitsugu Otomo und Hajime Igarashi. „Multi-objective topology optimization of magnetic couplers for wireless power transfer“. International Journal of Applied Electromagnetics and Mechanics 64, Nr. 1-4 (10.12.2020): 325–33. http://dx.doi.org/10.3233/jae-209337.

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In this paper, the multi-objective topology optimizations of wireless power transfer (WPT) devices with two different coil geometries are proposed for obtaining the designs with good balance between transfer efficiency and safety. For this purpose, the proposed method adopts the normalized Gaussian network (NGnet) and Non-dominated Sorting Genetic Algorithm II (NSGA-II). In addition, the optimization under the different constraint on ferrite volume is carried out to verify its influence on optimization results. It has been shown that the proposed method successfully provides the Pareto solution to the design problem of the WPT device.

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4

Guo, Weian, Ming Chen, Lei Wang und Qidi Wu. „Hyper multi-objective evolutionary algorithm for multi-objective optimization problems“. Soft Computing 21, Nr. 20 (24.05.2016): 5883–91. http://dx.doi.org/10.1007/s00500-016-2163-5.

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5

Bian, Xiang, Zong De Fang, Kun Qin, Lifei Lian und Bao Yu Zhang. „Multi-Objective Topology Optimization for Bevel Gear and Geometrical Reconstruction“. Applied Mechanics and Materials 278-280 (Januar 2013): 139–42. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.139.

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Usually the gear modification is a main measure to reduce the vibration and noise of the gears, but in view of the complexity of the gear modification, topology optimization method was used to optimize the structure of the gear. The minimum volume was set as the direct optimization goal. To achieve the target of reducing contact stress, tooth root bending stress and improving flexibility, the upper bound of the stress and lower bound of the flexibility were set appropriately, thus realizing multi-objective optimization indirectly. A method for converting topology result into parametric CAD model which can be modified was presented, by fitting the topology result with simple straight lines and arcs, the model can be smoothed automatically, after further regulating, the geometry reconstruction was finished. After topology optimization, the resulting structure and properties of the gear are consistent with cavity gear. While reducing the weight of the gear, the noise can be reduced and its life would be extended through increasing flexibility and reducing tooth root stress.

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6

Zuliani, João Batista Queiroz, Miri Weiss Cohen, Lucas de Souza Batista und Frederico Gadelha Guimarães. „Multi-objective Topology Optimization with Ant Colony Optimization and Genetic Algorithms“. Computer-Aided Design and Applications 12, Nr. 6 (29.04.2015): 674–82. http://dx.doi.org/10.1080/16864360.2015.1033328.

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7

Queiroz Zuliani, João Batista, Miri Weiss Cohen, Frederico Gadelha Guimarães und Carlos Alberto Severiano Junior. „A multi-objective approach for multi-material topology and shape optimization“. Engineering Optimization 51, Nr. 6 (25.09.2018): 915–40. http://dx.doi.org/10.1080/0305215x.2018.1514501.

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8

LI, Dongmei. „Multi-objective Topology Optimization of Thermo-mechanical Compliant Mechanisms“. Chinese Journal of Mechanical Engineering 24, Nr. 06 (2011): 1123. http://dx.doi.org/10.3901/cjme.2011.06.1123.

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9

Borovinšek, Matej, Nejc Novak, Matej Vesenjak, Zoran Ren und Miran Ulbin. „Designing 2D auxetic structures using multi-objective topology optimization“. Materials Science and Engineering: A 795 (September 2020): 139914. http://dx.doi.org/10.1016/j.msea.2020.139914.

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10

Aguilar Madeira, J. F., H. Rodrigues und Heitor Pina. „Multi-objective optimization of structures topology by genetic algorithms“. Advances in Engineering Software 36, Nr. 1 (Januar 2005): 21–28. http://dx.doi.org/10.1016/j.advengsoft.2003.07.001.

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11

Simonetti, Hélio Luiz, Valério S. Almeida, Francisco de Assis das Neves und Marcelo Greco. „Multi-objective topology optimization using the Boundary Element Method“. Structures 19 (Juni 2019): 84–95. http://dx.doi.org/10.1016/j.istruc.2018.12.002.

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12

Wei, Chao, Shui Guang Tong, Zhong Xiu Fei und Xue Mei Lin. „Multi-Objective Topology Optimization Design of a Large Marine Gearbox“. Applied Mechanics and Materials 201-202 (Oktober 2012): 325–28. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.325.

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Multi-objective topology optimization was studied for layout and structural optimization of a large marine gear-box to minimize its weight, while guaranteeing its strength and rigidity. After determining design domain and multiple load cases, static structure stiffness and the first order natural frequency was defined as optimization objectives. Based on SIMP(solid isotropic material with penalization) method, the topology optimization model of the box structure was set up. Furthermore, by taking into account of manufacturability, the optimal structure was obtained. Comparing to the original design, the optimized box has 7.8% weight reduction, while its structure is more reasonable, indicating the method has certain theoretical and engineering values.

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13

Liu, Zhi Jun, Wei Gang Zheng und Xiao Le Li. „Multi-Objective Frame Optimization Design of Steering Pump Bracket“. Advanced Materials Research 971-973 (Juni 2014): 584–87. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.584.

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By analyzing stress contours and deformation contours of the primary bracket, we can know that bracket material is more, contours proves too safe for bracket strength and stiffness. To improve the material utilization rate, topology optimization for bracket is carried by using topology module (DOE) of finite element analysis software workbench14.0. the main design parameter was set up, accordingly to accomplish analysis about the relationship between design parameter with quality. on the basis of analysis results, we improved primary structure that made the bracket quality reduced by 10% and executes verification, we obtained the reasonable structure finally.

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14

Xu, Weikai, Jinying Ning, Zibin Lin, Wuchao Qi, Hongliang Liu und Wei Wang. „Multi-objective topology optimization of two-dimensional multi-phase microstructure phononic crystals“. Materials Today Communications 22 (März 2020): 100801. http://dx.doi.org/10.1016/j.mtcomm.2019.100801.

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15

Nebro, Antonio J., Enrique Alba und Francisco Luna. „Multi-Objective Optimization using Grid Computing“. Soft Computing 11, Nr. 6 (03.05.2006): 531–40. http://dx.doi.org/10.1007/s00500-006-0096-0.

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16

Doi, Shuhei, Hidenori Sasaki und Hajime Igarashi. „Multi-Objective Topology Optimization of Rotating Machines Using Deep Learning“. IEEE Transactions on Magnetics 55, Nr. 6 (Juni 2019): 1–5. http://dx.doi.org/10.1109/tmag.2019.2899934.

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17

Xu, Xian, Yafeng Wang und Yaozhi Luo. „An improved multi-objective topology optimization approach for tensegrity structures“. Advances in Structural Engineering 21, Nr. 1 (06.07.2017): 59–70. http://dx.doi.org/10.1177/1369433217706780.

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18

Zhong, Wei, Ruiyi Su, Liangjin Gui und Zijie Fan. „Multi-objective topology and sizing optimization of bus body frame“. Structural and Multidisciplinary Optimization 54, Nr. 3 (06.04.2016): 701–14. http://dx.doi.org/10.1007/s00158-016-1431-4.

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19

Xiao, Denghong, Hai Zhang, Xiandong Liu, Tian He und Yingchun Shan. „Novel steel wheel design based on multi-objective topology optimization“. Journal of Mechanical Science and Technology 28, Nr. 3 (März 2014): 1007–16. http://dx.doi.org/10.1007/s12206-013-1174-8.

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20

Yang, Shu Yi, Hong Li und Yang Bin Ou. „Topology Optimization of Suspension of the Hard Disk Drive Based on SIMP Method“. Advanced Materials Research 819 (September 2013): 356–61. http://dx.doi.org/10.4028/www.scientific.net/amr.819.356.

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in order to guarantee the reliability of the hard disk drive data read/write and slider positioning accuracy, the suspension first order bending frequency, first order torsional frequency, first order sway frequency single objective topology optimization model which were based on solid isotropic elastic material penalty (SIMP) method were put forward, and the suspension multi-objective topology optimization model was defined by using the weighted method. Through the topology optimization design the hard disk drive suspension new topological structure was obtained. The results show that hard disk drive suspension single objective and multi-objective topology optimization design objective frequency are large promote than that of the initial design.

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21

ZHANG, Zhifei. „Research on Multi-objective Topology Optimization of Vehicle Suspension Control Arm“. Journal of Mechanical Engineering 53, Nr. 04 (2017): 114. http://dx.doi.org/10.3901/jme.2017.04.114.

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22

Lim, Jarad, Chao You und Iman Dayyani. „Multi-objective topology optimization and structural analysis of periodic spaceframe structures“. Materials & Design 190 (Mai 2020): 108552. http://dx.doi.org/10.1016/j.matdes.2020.108552.

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23

Cheng, Dandan, Xi Lu und Xiaojuan Sun. „Multi-objective topology optimization of column structure for vertical machining center“. Procedia CIRP 78 (2018): 279–84. http://dx.doi.org/10.1016/j.procir.2018.08.305.

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24

Stanford, Bret, und Peter Ifju. „Multi-Objective Topology Optimization of Wing Skeletons for Aeroelastic Membrane Structures“. International Journal of Micro Air Vehicles 1, Nr. 1 (März 2009): 51–69. http://dx.doi.org/10.1260/1756-8293.1.1.51.

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25

Cardillo, Alessandro, Gaetano Cascini, Francesco Saverio Frillici und Federico Rotini. „Multi-objective topology optimization through GA-based hybridization of partial solutions“. Engineering with Computers 29, Nr. 3 (07.07.2012): 287–306. http://dx.doi.org/10.1007/s00366-012-0272-z.

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26

Alfouneh, Mahmoud, und Liyong Tong. „Maximizing modal damping in layered structures via multi-objective topology optimization“. Engineering Structures 132 (Februar 2017): 637–47. http://dx.doi.org/10.1016/j.engstruct.2016.11.058.

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27

Wang, Kai, De Sheng Yang und Da Wei Ma. „Multi-Objective Structure Optimization Design of a Car Lower Control Arm“. Advanced Materials Research 774-776 (September 2013): 420–27. http://dx.doi.org/10.4028/www.scientific.net/amr.774-776.420.

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A multi-objective structure optimization design of a car lower control arm was operated in order to improve both compliance and eigenfrequencies effectively. Based on SIMP (solid isotropic material penalization) method, compromise programming method was adopted to define multi-objective topology optimization. The topological structure of lower control arm was obtained through the optimization, and further, the new structure design. Results verified by FEA show that the new design can simultaneously satisfy the compliance and eigenfrequencies objective, and can meet yield stress requirements.

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28

Wang, Ping, Zhou Lan und Xiao Yang Shen. „Weight Reduction Design of Gear Drive Based on Parameter and Structural Optimization“. Advanced Materials Research 139-141 (Oktober 2010): 1406–10. http://dx.doi.org/10.4028/www.scientific.net/amr.139-141.1406.

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. For a medium or large-sized gear drive, in order to achieve the optimum weight reduction effect, an approach of weight reduction design is proposed that multi-objective optimization of gear parameters is carried out firstly, and then structural optimization is adopted to design the gear former. The rational design parameters of a gear drive are determined by the multi-objective optimization with minimizing the sum of gear volumes and the equivalent moment of inertia of input shaft (EMI) synchronously. Conceptual design of the former is given by structural topology optimization of the gear, and the reasonability of topology optimization can be demonstrated by static and dynamic analysis. The results indicate that for a double-reduction gearbox of 500KW co-rotating twin screw pulping extruder, the EMI of the gear drive reduces by 20.88% through the multi-objective optimization of gear parameters, and the moment of inertia of a bull gear reduces by 38.86% through structural topology optimization.

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29

Ge, Wenjie, und Xin Kou. „Topology Optimization of Multi-Materials Compliant Mechanisms“. Applied Sciences 11, Nr. 9 (23.04.2021): 3828. http://dx.doi.org/10.3390/app11093828.

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In this article, a design method of multi-material compliant mechanism is studied. Material distribution with different elastic modulus is used to meet the rigid and flexible requirements of compliant mechanism at the same time. The solid isotropic material with penalization (SIMP) model is used to parameterize the design domain. The expressions for the stiffness matrix and equivalent elastic modulus under multi-material conditions are proposed. The least square error (LSE) between the deformed and target displacement of the control points is defined as the objective function, and the topology optimization design model of multi-material compliant mechanism is established. The oversaturation problem in the volume constraint is solved by pre-setting the priority of each material, and the globally convergent method of moving asymptotes (GCMMA) is used to solve the problem. Widely studied numerical examples are conducted, which demonstrate the effectiveness of the proposed method.

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30

NAKAYAMA, Hirotaka, und Masatoshi SHIMODA. „Simultaneous shape and topology optimization for multi-objective design of a multi-layered shell“. Proceedings of The Computational Mechanics Conference 2016.29 (2016): 4_286. http://dx.doi.org/10.1299/jsmecmd.2016.29.4_286.

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31

Qu, Yanjun, Yanru Jiang, Liangjie Feng, Xupeng Li, Bei Liu und Wei Wang. „Lightweight Design of Multi-Objective Topology for a Large-Aperture Space Mirror“. Applied Sciences 8, Nr. 11 (15.11.2018): 2259. http://dx.doi.org/10.3390/app8112259.

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For a large-aperture space telescope, one of the key techniques is the method for designing the lightweight primary mirror assembly (PMA). In order to minimize the mirror surface error under axial gravity, lateral gravity, and polishing pressure at the same time, a method for topology optimization with multi-objective function combined with parametric optimization is introduced in this paper. The weighted compliance minimum is selected as the objective function to maximum the mirror structural stiffness. Then sensitivity analysis method and size optimization are used to determine the mirror structure parameters. Compared with two types of commonly used lightweight configurations, the new configuration design shows obvious superiority. In addition, the surface figure root mean square (RMS) of the mirror mounted by given bipod flexure (BF) under 1 g lateral gravity is minimized only with a value of 3.58 nm, which proves the effectiveness of the design method proposed in this paper.

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32

Khalilpourazari, Soheyl, Bahman Naderi und Saman Khalilpourazary. „Multi-Objective Stochastic Fractal Search: a powerful algorithm for solving complex multi-objective optimization problems“. Soft Computing 24, Nr. 4 (21.05.2019): 3037–66. http://dx.doi.org/10.1007/s00500-019-04080-6.

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33

Shin, Hyunjin, Akira Todoroki und Yoshiyasu Hirano. „Elite-initial population for efficient topology optimization using multi-objective genetic algorithms“. International Journal of Aeronautical and Space Sciences 14, Nr. 4 (30.12.2013): 324–33. http://dx.doi.org/10.5139/ijass.2013.14.4.324.

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34

Xia, Meng, Qiang Zhou, Jan Sykulski, Shiyou Yang und Yanhong Ma. „A Multi-Objective Topology Optimization Methodology Based on Pareto Optimal Min-Cut“. IEEE Transactions on Magnetics 56, Nr. 3 (März 2020): 1–5. http://dx.doi.org/10.1109/tmag.2019.2955386.

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35

Peng, Q., X. Ni, F. Han, K. Rhaman, C. Ulianov und X. Fang. „Research on connection structure of aluminumbody bus using multi-objective topology optimization“. IOP Conference Series: Materials Science and Engineering 292 (Januar 2018): 012056. http://dx.doi.org/10.1088/1757-899x/292/1/012056.

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36

Luo, Z., L. Chen, J. Yang, Y. Zhang und K. Abdel-Malek. „Compliant mechanism design using multi-objective topology optimization scheme of continuum structures“. Structural and Multidisciplinary Optimization 30, Nr. 2 (18.03.2005): 142–54. http://dx.doi.org/10.1007/s00158-004-0512-y.

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37

Lin, Jiangzi, Zhen Luo und Liyong Tong. „A new multi-objective programming scheme for topology optimization of compliant mechanisms“. Structural and Multidisciplinary Optimization 40, Nr. 1-6 (30.01.2009): 241–55. http://dx.doi.org/10.1007/s00158-008-0355-z.

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38

Cho, K. H., J. Y. Park, S. P. Ryu, J. Y. Park und S. Y. Han. „Reliability-based topology optimization based on bidirectional evolutionary structural optimization using multi-objective sensitivity numbers“. International Journal of Automotive Technology 12, Nr. 6 (24.11.2011): 849–56. http://dx.doi.org/10.1007/s12239-011-0097-6.

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39

Rosyid, Abdur, Bashar El-Khasawneh und Anas Alazzam. „Genetic and hybrid algorithms for optimization of non-singular 3PRR planar parallel kinematics mechanism for machining application“. Robotica 36, Nr. 6 (22.02.2018): 839–64. http://dx.doi.org/10.1017/s0263574718000152.

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SUMMARYThis paper proposes a special non-symmetric topology of a 3PRR planar parallel kinematics mechanism, which naturally avoids singularity within the workspace and can be utilized for hybrid kinematics machine tools. Subsequently, single-objective and multi-objective optimizations are conducted to improve the performance. The workspace area and minimum eigenvalue, as well as the condition number of the homogenized Cartesian stiffness matrix across the workspace, have been chosen as the objectives in the optimization based on their relevance to the machining application. The single-objective optimization is conducted by using a single-objective genetic algorithm and a hybrid algorithm, whereas the multi-objective optimization is conducted by using a multi-objective genetic algorithm, a weighted sum single-objective genetic algorithm, and a weighted sum hybrid algorithm. It is shown that the single-objective optimization gives superior value in the optimized objective, while sacrificing the other objectives, whereas the multi-objective optimization compromises the improvement of all objectives by providing non-dominated values. In terms of the algorithms, it is shown that a hybrid algorithm can either verify or refine the optimal value obtained by a genetic algorithm.

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40

Winyangkul, Seksan, Kittinan Wansaseub, Suwin Sleesongsom, Natee Panagant, Sumit Kumar, Sujin Bureerat und Nantiwat Pholdee. „Ground Structures-Based Topology Optimization of a Morphing Wing Using a Metaheuristic Algorithm“. Metals 11, Nr. 8 (19.08.2021): 1311. http://dx.doi.org/10.3390/met11081311.

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This paper presents multi-objective topology and sizing optimization of a morphing wing structure. The purpose of this paper is to design a new aircraft wing structure with a tapered shape for ribs, spars, and skins including a torsion beam for external actuating torques, which is anticipated to modify the aeroelastic characteristic of the aircraft wing using multi-objective optimization. Two multi-objective topology optimization problems are proposed employing ground element structures with high- and low-grid resolutions. The design problem is to minimize mass, maximize difference of lift effectiveness, and maximize the buckling factor of an aircraft wing subject to aeroelastic and structural constraints including lift effectiveness, critical speed, and buckling factors. The design variables include aircraft wing structure dimensions and thickness distribution. The proposed optimization problems are solved by an efficient multi-objective metaheuristic algorithm while the results are compared and discussed. The Pareto optimal fronts obtained for all tests were compared based on a hypervolume metric. The objective function values for Case I and Case II at 10 selected optimal solutions exhibit a range of structural mass as 115.3216–411.6250 kg, 125.0137–440.5869 kg, lift effectiveness as 1.0514–1.1451, 1.0834–1.1639 and bucking factor as 38.895–1133.1864 Hz, 158.1264–1844.4355 Hz, respectively. The best results reveal unconventional aircraft wing structures that can be manufactured using additive manufacturing. This research is expected to serve as a foundation for future research into multi-objective topology optimization of morphing wing structures based on the ground element framework.

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Wang, Kai, und Da Wei Ma. „Multi-Objective Structure Optimization Design on the Upper Carriage of a Naval Gun“. Applied Mechanics and Materials 541-542 (März 2014): 669–73. http://dx.doi.org/10.4028/www.scientific.net/amm.541-542.669.

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A multi-objective structure optimization design onthe upper carriage of a naval gun was operated in order to improve both compliance and eigenfrequencies effectively. Based on SIMP (solid isotropic material penalization) method, compromise programming method was adopted to define multi-objective topology optimization. The topological structure of upper carriage was obtained through the optimization, and further, the new structure design. Results verified by FEA show that the new design can simultaneously satisfy the compliance and eigenfrequencies objective, and meanwhile candecrease mass and stress.

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42

Li, Zhao Kun, Hua Mei Bian, Li Juan Shi und Xiao Tie Niu. „Reliability-Based Topology Optimization of Compliant Mechanisms with Geometrically Nonlinearity“. Applied Mechanics and Materials 556-562 (Mai 2014): 4422–34. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4422.

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A new reliability-based topology optimization method for compliant mechanisms with geometrical nonlinearity is presented. The aim of this paper is to integrate reliability and geometrical nonlinear analysis into the topology optimization problems. Firstly, geometrical nonlinear response analysis method of the compliant mechanisms is developed based on the Total-Lagrange finite element formulation, the incremental scheme and the Newton-Raphson iteration method. Secondly, a multi-objective topology optimal model of compliant mechanisms considering the uncertainties of the applied loads and the geometry descriptions is established. The objective function is defined by minimum the compliance and maximum the geometric advantage to meet both the stiffness and the flexibility requirements, and the reliabilities of the compliant mechanisms are evaluated by using the first order reliability method. Thirdly, the computation of the sensitivities is developed with the adjoint method and the optimization problem is solved by using the Method of Moving Asymptotes. Finally, through numerical calculations, reliability-based topology designs with geometric nonlinearity of a typical compliant micro-gripper and a multi-input and multi-output compliant sage are obtained. The importance of considering uncertainties and geometric nonlinearity is then demonstrated by comparing the results obtained by the proposed method with deterministic optimal designs, which shows that the reliability-based topology optimization yields mechanisms that are more reliable than those produced by deterministic topology optimization.

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Li, Yongxin, Quanwei Yang, Tao Chang, Tao Qin und Fenghe Wu. „Multi-load cases topological optimization by weighted sum method based on load case severity degree and ideality“. Advances in Mechanical Engineering 12, Nr. 8 (August 2020): 168781402094751. http://dx.doi.org/10.1177/1687814020947510.

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Mechanical structures always bear multiple loads under working conditions. Topology optimization in multi-load cases is always treated as a multi-objective optimization problem, which is solved by the weighted sum method. However, different weight factor allocation strategies have led to discrepant optimization results, and when ill loading case problems appear, some unreasonable results are obtained by those alternatives. Moreover, many multi-objective optimization problems have certain optimization objective, and an evaluation formula to measure Pareto solution in the multi-objective optimization problem area is lacking. Regarding these two problems, a new method for calculating the weight factor is proposed based on the definition of load case severity degree. Additionally, an amplified load increment is derived and suggested in the minimum compliance with a volume constraint problem. Ideality is formulized from Pareto front to the ideal solution to evaluate the different optimization results. Benchmark topology optimization examples are solved and discussed. The results show that the load case severity degree is less affected by the different weighted sum functions and can avoid ill loading case phenomena, and the ideality of optimization result obtained by the load case severity degree is the best.

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Wang, Yi Qing, Xu Chen, Bin Wang, Xin Bin Kuang und Xiao Geng Tian. „Multi-Objective Optimization for the Section Structure of Sandwich Plate Applied in the High-Speed Train Compartments“. Applied Mechanics and Materials 597 (Juli 2014): 535–39. http://dx.doi.org/10.4028/www.scientific.net/amm.597.535.

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In order to obtain the side walls section structures of high speed train applicable to different running speeds and conditions, a multi-objective optimization design is made based on the structure of topology optimization. In this optimization formulation, the weight of sandwich plate, static compliance and maximum deformation are used as the objective functions; the thickness of face panels and cores in five parts of the side wall are variables; and the air pressure gradient in compartments is the constraint function. Surrogate model techniques are adopted for constructing the response surfaces based on the optimization. Finally, a multi-objective optimization is performed using the NSGA-II algorithm and the optimization generates a Pareto solution set. The structure performance in Pareto set is greatly improved by 8.21% -33.58% than that of topology structure. In addition, the Pareto solution set provides engineers with many alternative Pareto-optimal solutions for optimization design of the sandwich plate section applied in the high-speed train.

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Zheng, Li Ming, Qiang Wang, Sheng Xin Zhang und Shao Yong Zheng. „Population recombination strategies for multi-objective particle swarm optimization“. Soft Computing 21, Nr. 16 (18.02.2016): 4693–705. http://dx.doi.org/10.1007/s00500-016-2078-1.

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Wang, Shuai, Hu Zhang, Yi Zhang und Aimin Zhou. „Adaptive population structure learning in evolutionary multi-objective optimization“. Soft Computing 24, Nr. 13 (22.11.2019): 10025–42. http://dx.doi.org/10.1007/s00500-019-04518-x.

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47

Zhang, S., J. Yin, H. W. Zhang und B. S. Chen. „Multi-objective optimization of two-dimensional phoxonic crystals with multi-level substructure scheme“. International Journal of Modern Physics B 30, Nr. 09 (10.04.2016): 1650046. http://dx.doi.org/10.1142/s0217979216500466.

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Phoxonic crystal (PXC) is a promising artificial periodic material for optomechanical systems and acousto-optical devices. The multi-objective topology optimization of dual phononic and photonic max relative bandgaps in a kind of two-dimensional (2D) PXC is investigated to find the regular pattern of topological configurations. In order to improve the efficiency, a multi-level substructure scheme is proposed to analyze phononic and photonic band structures, which is stable, efficient and less memory-consuming. The efficient and reliable numerical algorithm provides a powerful tool to optimize and design crystal devices. The results show that with the reduction of the relative phononic bandgap (PTBG), the central dielectric scatterer becomes smaller and the dielectric veins of cross-connections between different dielectric scatterers turn into the horizontal and vertical shape gradually. These characteristics can be of great value to the design and synthesis of new materials with different topological configurations for applications of the PXC.

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A., Dr Sathesh. „OPTIMIZED MULTI-OBJECTIVE ROUTING FOR WIRELESS COMMUNICATION WITH LOAD BALANCING“. Journal of Trends in Computer Science and Smart Technology 2019, Nr. 02 (23.12.2019): 106–20. http://dx.doi.org/10.36548/jtcsst.2019.2.004.

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The rapid advancements in the wireless communication networks have increased the popularity of portable or mobile devices and the network framed with these mobile devices. These mobile networks framed using the volunteering portable devices are decentralized and have dynamic topologies experiencing sudden changes in the network structure. The main reason causing the topology changes are the limited energy availability of the device and their mobility. Improper trafficking of the tasks and improper selection of the portable devices causes maximum energy consumption resulting in the link failures and changes in the topology of the network. So the paper puts forward the hybridized optimization technique to handle the multi-objective problem faced by these decentralized networks. The proposed method is validated using the network simulator-2 to evince throughput, energy consumption and the network longevity achieved by the proposed method.

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Nan, Bo, Yikui Bai und Yue Wu. „Multi-Objective Optimization of Spatially Truss Structures Based on Node Movement“. Applied Sciences 10, Nr. 6 (13.03.2020): 1964. http://dx.doi.org/10.3390/app10061964.

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This paper discusses the solutions for topology optimization of spatially discrete structures. The optimization objects are the structural weight and the maximum displacement. The optimization variables include structural node coordinates, and the improved MOEA (Multi-objective Evolutionary Algorithm) method is used to optimize the structure. The innovation of this study is that it breaks through the shortage of constant node position in the optimization thought of traditionally discrete structure in the “Ground Structure Approach” and uses the coordinate of the node as the optimization variable for the optimization calculation. The result is not a single one but a set of optimal solutions through the evolution (i.e., Pareto optimal solutions); on this basis, the most suitable solution can be found according to the boundary conditions or other related requirements. Using the C# language to compile the calculation program, ANSYS finite element software is used to analyze the structure, and the Pareto front surface was automatically drawn to determine the optimal layout form of the discrete structure. The analysis results show that the improved MOEA method can provide an effective method to solve such optimization problems.

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ZHANG, Xianmin. „Multi-objective Topology Optimization of Multiple Materials Compliant Mechanisms Based on Parallel Strategy“. Journal of Mechanical Engineering 52, Nr. 19 (2016): 1. http://dx.doi.org/10.3901/jme.2016.19.001.

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