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Method, Software And Application Of Structural Fatigue Life Optimization Based On Metamodels

Posted on:2011-04-29Degree:MasterType:Thesis
Country:ChinaCandidate:Y Q DengFull Text:PDF
GTID:2132330338976696Subject:Aircraft design
Abstract/Summary:PDF Full Text Request
The fatigue failure may do great harm to flight safety, so it has important practical significance to carry out the research about improving fatigue life. Structural fatigue life optimization is practical methodology to deal with this issue, but the fatigue life analysis in optimization cycles is a time-consuming procedure. To overcome this disadcantage, a method of structural fatigue life optimization based on metamodels is proposed. Based on this method, a optimization software was developed, and it is applied to the structural optimization of a nose landing gear.A metamodel-based theoretical framework of structural fatigue life optimization was proposed. The fatigue life analysis of the whole structure was carried out to figure out the critical component with the lowest fatigue life, then the load-time history of this component was obtained by dynamics simulation analysis. After that, the metamodels on fatigue and weight of the critical component were constructed, and then its fatigue life was optimized.Three kinds of metamodels and two kinds of design of experiments was analized systematically. It is found that the radial basis functions constructed by Latin Hypercube design is the best metamodel for the fatigue life. This is because that it is not only a good model with a higher fitting efficiency, but also has a better adaptability.The"Optimal Information"was introduced into the partical swarm optimization to deal with the problem that convergence speed was slowed down significantly in the end due to all of the particals converge to the minimum. Then structural fatigue life optimization software was developed using Java, and this optimization software can carryout the design of experiments, construct the metamodels and provide the modified partical swarm optimization.Taking a nose gear as an example, the critical component:forward strut was figure out by fatigue life analysis of the nose gear, then the load-time history of forward strut was obtained by dynamics simulation. Based on parametric finite element model of forward strut established by PCL, the metamodel on fatigue life and weight of forward strut was constructed. Finally, the fatigue life of forward strut was optimized, and the fatigue life of the forward strut was improved significantly, from 1.51E5 cycles to 7.24E5 cycles.
Keywords/Search Tags:aircraft landing gear, fatigue life optimization, Latin Hypercube design, radial basis functions, partical swarm optimization
PDF Full Text Request
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