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Improved And Application Of Bi-directional Evolutionary Structural Topology Optimization Method

Posted on:2013-03-12Degree:MasterType:Thesis
Country:ChinaCandidate:L PengFull Text:PDF
GTID:2232330395986014Subject:Mechanical design and theory
Abstract/Summary:PDF Full Text Request
Topology optimization used in design initial step gives the expression of innovation andhad been accepted more and more widely, which made the structure topology optimizationbecome the hot research topics in structure optimization design field. Compared with sizeoptimization, shape optimization and another kind of optimize method, structure topologyoptimization could give a concept design at the beginning of the structure design, whichdoesn’t need any engineering experience, and more attractive for design engineers. There areso many methods to build mathematical model in continuum structure topology optimization,and involve more variables but also own advantages and disadvantages, lead to engineeringapplication of topology optimization failed to popularity. The bi-directional evolutionarystructural optimization (BESO) method what have been researched in this paper, that has theadvantages of simply algorithm and easy combination with finite element analysis program,so be used more and more widely in structure topology optimization. In order to improve therationality, generality and engineering application ability, the BESO method and it’sapplication based on continuum structure had been researched and discussed in this paper.This paper firstly aims to current stage of BESO method, summarizing the various kindsof common problems and its settle method. Through the analysis of the advantages anddisadvantages of these methods, the improvement method had been proposed based on thegenetic algorithm idea combining with the grid filtering technology, avoid the“checkerboard”, grid dependence and into the local optimal solution phenomenon occur inthe topology optimization. Structure strength topology optimization of compliant for targetfunction and structure modal topology optimization of modal frequency maximize based onthe modal sensitivity sort method both had been established,witch from the point view ofimproving the material utilization. The improvement of BESO method had been realized bythe Matlab programming, with the classical cantilever beam and “Michell” structure provedthe validity of the improved method put forward in this paper. At the same time, by the wayof comparing with the current popular topology optimization to prove the advantages of thisBESO method and improvement effect.In the second place, engineering practice often needs to consider the strength, stiffness, stability, modal and so on many kinds of requirements. Therefore, consider the stress andmodal problem with multi displacement constraints had been studied in this paper. By usingLagrange multiplier method, respectively to compliance uniformity and modal frequencymaximize be objective function, establish the mathematic model of the corresponding multiconstraint element sensitivity values.Thirdly, by the high performance finite element analysis application HyperWorks as aplatform, combined with TCL and C language to carry through the secondary development.So the improvement BESO method had been realized in HyperWorks by the modularprogramming operation, which including the pre-processing, iterative curve displayed, curveeditor and post processing, therefore, the generality of this BESO method had beenimprovement.Finally, based on structure damping adhesion technology to reduce vibration, combinedwith BESO method, the method of determine the position where adhesion the damp materialwas put forward, which apply to damping vibration reducing for ship plate structure. And theproposed method had been verified by a simple plate structure with both ends constraints, andalso could be promoted in engineering practice.
Keywords/Search Tags:topology optimization, bi-directional evolutionary structural optimization method, multi-objective optimization, damping vibration reducing
PDF Full Text Request
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