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1、AbstractAbstractGiventhenumericalinstabilitiesinevolutionarystructuraloptimizationoffiniteelementandtheimmaturestageofdevelopmentonEFGevolutionarystructuraloptimization,EFGevolutionarystructuraloptimizationalgorithmarediscussedinthispaper,basedonthehigh
2、precision,fastconvergence,goodstabilityofEFG,aswellasthesimpleprincipleofevolutionarystructuraloptimizationmethodandlessdesignvariables.Themainresearchcontentsareasfollows:StudyonEFGevolutionarystructuraloptimizationalgorithm.EFGevolutionarystructuralop
3、timizationmathematicalmodelswillbeestablishedinthefirstplace,aswellasthebasicflow,andthenfourtypesofmaterialremovealgorithmarebroughtup,aimedatthebasicflowoftheresearchobjectmaterialremovemodule,namely,GDGmaterialdeletionalgorithm,GDGNmaterialdeletional
4、gorithm,NDNmaterialdeletionalgorithm,BGDGNmaterialdeletionalgorithm.Thefeasibilityofthesefourmaterialdeletionalgorithmmethodsarealsoverified.Apartfromthis,differentmatrixassemblingwaysreferringtothestructuralanalysisofEFGaredemonstratedbyclassification,
5、andthecorrespondingMatlabcodeiswritten.ThefeasibilityandeffectivenessofthisBGDGNmethodareeventuallyverifiedbyanumericalexample.EngineeringapplicationofBGDGNmaterialdeletionalgorithm.Firstly,theMatlabcodeofBGDGNmethodisappliedinconcretetrussstructureandm
6、ultipleloadcasesstructure,thesmoothandneatresult,aswellasnocheckerboardphenomenon,closelyconsistenttotheexistingliteratureconclusion,whichshowsthatthealgorithmhasgoodductility.Then,inordertotestandverifythenumericalresultsofthismaterialremovedalgorithmh
7、asnothingtodowiththeparameters,twokindsofconfiguration,evenlydividedangularnodesandirregulararrangementnodes,arediscussed.AgoodcommonalityofBGDGNmethodisverified,throughatheoreticalsolutionofanumericalcase.StudyonEFGBi-directionalevolutionarystructureop
8、timizationmethod.ImplementationstepsofEFGBi-directionalevolutionarystructureoptimizationisfirstlydescribedindetail,followedbythebasicprocedure,andthenthecorrespondingMatlabprogramcodeareaccomplished.Finally,thefeasibilityandrelia
