• Title/Summary/Keyword: size and shape optimization

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A Study on the Size and the Shape Optimization of Cross Beam for Electric Vehicle using GENESIS 7.0 (GENESIS 7.0을 이용한 전동차용 크로스 빔의 치수와 형상 최적화에 관한 연구)

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    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.11
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    • pp.129-136
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    • 2002
  • Electric vehicle body has to be subjected to uniform load and demand auxiliary equipment such as air pipe, electric wire pipe and gas pipe. Especially, lightweight vehicle body is salutary to save operating costs and fuel consumption. Cross beam supports the weight of passenger and electrical equipments and account for the most of weight of vehicle body. Therefore this study performs the size and the shape optimization of crossbeam for electric vehicle using GENESIS 7.0 and presents the effect of mass reduction and the shape of hole in cross beam.

Shape & Topology Optimum Design of Truss Structures Using Genetic Algorithms (유전자 알고리즘에 의한 평면 및 입체 트러스의 형상 및 위상최적설계)

  • Yuh, Baeg-Youh;Park, Choon-Wook;Kang, Moon-Myung
    • Journal of Korean Association for Spatial Structures
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    • v.2 no.3 s.5
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    • pp.93-102
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    • 2002
  • The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

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Shape Optimal Design to Minimize the Weight of the Pedal Arm of an Automotive Clutch (자동차 클러치 페달 암의 무게 최소화를 위한 형상 최적설계)

  • Lee, Boo-Youn;Lee, Hyun-Woo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.2 s.257
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    • pp.269-276
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    • 2007
  • Optimal thickness and shape of the pedal arm of an automotive clutch is determined, using the numerical optimization technique, by solving the size and shape optimization problems to minimize its weight. For the optimization problems, two cases of stress and displacement constraints are considered: one from the vertical, and the other from the transverse stiffness test condition. The result of the transverse case is shown to be more conservative than that from the vertical case, being determined as the final optimum.

Topology, shape, and size optimization of truss structures using modified teaching-learning based optimization

  • Tejani, Ghanshyam G.;Savsani, Vimal J.;Patel, Vivek K.;Bureerat, Sujin
    • Advances in Computational Design
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    • v.2 no.4
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    • pp.313-331
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    • 2017
  • In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

Optimum Design of the Spatial Structures using the TABU Algorithm (TABU 알고리즘을 이용한 대공간 구조물의 최적설계)

  • Cho, Yong-Won;Lee, Sang-Ju;Han, Sang-Eul
    • Proceeding of KASS Symposium
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    • 2005.05a
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    • pp.246-253
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    • 2005
  • The design of structural engineering optimization is to minimize the cost. This problem has many objective functions formulating section and shape as a function of the included discrete variables. simulated annealing, genetic algerian and TABU algorithm are searching methods for optimum values. The object of this reserch is comparing the result of TABU algorithm, and verifying the efficiency of TABU algorithm in structural optimization design field. For the purpose, this study used a solid truss of 25 elements having 10 nodes, and size optimization for each constraint and load condition of Geodesic one, and shape optimization of Cable Dome for verifying spatial structures by the application of TABU algorithm

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The Optimized Design Method of Vehicle for Weight-Reduction (무게절감을 위한 차량 최적 설계 기법)

  • Lee, Jeong-Ick
    • Korean Journal of Computational Design and Engineering
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    • v.12 no.5
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    • pp.376-381
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    • 2007
  • The geometric configuration in the weight-reduced structure is very required to be started from the conceptual design with low cost, high performance and quality. In this point, a structural-topological shape concerned with conceptual design of structure is important. The method used in this paper combines three optimization techniques, where the shape and physical dimensions of the structure and material distribution are hierachically optimized, with the maximum rigidity of structure and lightweight.

Shape Optimization of a Bogie frame for the Reduction of its Weight (고속 화차용 대차프레임의 경량화를 위한 최적설계)

  • Kim, Hyun-Su;Ahn, Chan-Woo;Choi, Kyung-Ho;Park, Jeong-Ho
    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.9
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    • pp.186-192
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    • 2002
  • As industry is developed, the faster transportation of freight train is demanded. The optimum design of a structure requires the determination of economical member size and shape of a structure which will satisfy the design conditions and the functions. In this study, it is attempted to minimize the dead weight of bogie frame. From the numerical results in the shape and size optimization of the bogie frame, it is known that the weight can be reduced up to 17.45% with the displacement, stress, first natural frequency and critical buckling-load constraints. The first natural frequency and the critical buckling load of the optimized model is larger than that of the lowest design value. Stress and displacement conditions are also satisfied within the design conditions. From the results, the optimal model is stable and useful for the improvement of railway carriages.

A new PSRO algorithm for frequency constraint truss shape and size optimization

  • Kaveh, A.;Zolghadr, A.
    • Structural Engineering and Mechanics
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    • v.52 no.3
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    • pp.445-468
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    • 2014
  • In this paper a new particle swarm ray optimization algorithm is proposed for truss shape and size optimization with natural frequency constraints. These problems are believed to represent nonlinear and non-convex search spaces with several local optima and therefore are suitable for examining the capabilities of new algorithms. The proposed algorithm can be viewed as a hybridization of Particle Swarm Optimization (PSO) and the recently proposed Ray Optimization (RO) algorithms. In fact the exploration capabilities of the PSO are tried to be promoted using some concepts of the RO. Five numerical examples are examined in order to inspect the viability of the proposed algorithm. The results are compared with those of the PSO and some other existing algorithms. It is shown that the proposed algorithm obtains lighter structures in comparison to other methods most of the time. As will be discussed, the algorithm's performance can be attributed to its appropriate exploration/exploitation balance.

Optimization to Control Buckling Temperature and Mode Shape through Continuous Thickness Variation of Composite Material (복합소재의 연속 두께 변화를 통한 좌굴온도 및 모드형상 최적화)

  • Lee, Kang Kuk;Lee, Hoo Min;Yoon, Gil Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.6
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    • pp.347-353
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    • 2021
  • In this study, we presented a novel size optimization framework to control the linear buckling temperature and several buckling modes of plates, by optimizing thickness values of composite structures for practical engineering applications. Predicting the buckling temperature and mode shape of structures is a vital research topic in engineering to achieve structural stability. However, optimizing designs of engineering structures through engineering intuition is challenging. To address this limitation, we proposed a method that combines finite element simulation and size optimization. Based on the idea that the structural buckling temperature and mode shape of a plate are affected by the thickness of the structure, the thickness values of the nodes of the target structure were set as the design variables in this optimization method; and the buckling temperature values, and buckling mode shapes were set as the objective functions. This size optimization method enabled the determination of optimal thickness distributions, to induce the desired buckling temperature values and mode shapes. The validity of the proposed method was verified in terms of their buckling temperature values and buckling mode shapes, using several numerical examples of rectangular composite structures.

Structural Shape Optimization under Static Loads Transformed from Dynamic Loads (동하중으로부터 변환된 등가정하중을 통한 구조물의 형상최적설계)

  • Park, Ki-Jong;Lee, Jong-Nam;Park, Gyung-Jin
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.1262-1269
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    • 2003
  • In structural optimization, static loads are generally utilized although real external forces are dynamic. Dynamic loads have been considered in only small-scale problems. Recently, an algorithm for dynamic response optimization using transformation of dynamic loads into equivalent static loads has been proposed. The transformation is conducted to match the displacement fields from dynamic and static analyses. The algorithm can be applied to large-scale problems. However, the application has been limited to size optimization. The present study applies the algorithm to shape optimization. Because the number of degrees of freedom of finite element models is usually very large in shape optimization, it is difficult to conduct dynamic response optimization with the conventional methods that directly threat dynamic response in the time domain. The optimization process is carried out via interfacing an optimization system and an analysis system for structural dynamics. Various examples are solved to verify the algorithm. The results are compared to the results from static loads. It is found that the algorithm using static loads transformed from dynamic loads based on displacement is valid even for very large-scale problems such as shape optimization.

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