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Multidisciplinary Flexible Design Decisions Approach Based On Hybrid-Game Theory

Posted on:2017-08-20Degree:MasterType:Thesis
Country:ChinaCandidate:L P LiFull Text:PDF
GTID:2322330512476272Subject:Mechanical design and theory
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The current engineering product design decisions covers knowledge of multiple disciplines and fields.It is considered an engineering product design decisions is a multi-disciplinary design decisions problem.Multidisciplinary design decisions through fully explore and use the synergistic effect arising from the interaction between the various disciplines to get the best overall performance of the engineering product design.Its distinguishing feature is multidisciplinary and coupling,causing large amount of calculation,design repeatedly and other issues.Due to product design is not achieved overnight,there are various uncertainties in the actual design process,so product design is more complicated and varied.To solve these problems,this paper established hybrid game frameworks based on game theory to express interactions between disciplines of multidisciplinary design optimization,and introduced the concept of flexibility to establish flexible mathematical model,to make the design flexible,to reduce the influence of the uncertainty in the design of products.First of all,according to the characteristics of complex product design,involving multiple disciplines and containing multiple design objectives in each disciplines,according to the relationship between disciplines,respectively established three mixed game frameworks to show the interaction relationship between the various disciplines.Secondly,this paper using the game theory to solve the multidisciplinary design problem.The parametric design based on game theory and the game multidisciplinary design based on numerical simulation is proposed.The parametric design based on game theory firstly uses relevant empirical formula,statistical formulas to create mathematical models of various disciplines;secondly uses design structure matrix to determine interactions between disciplines,and uses fuzzy set theory to divide strategy set of each player;then choose a mixed game framework based on interaction relationship between disciplines to game optimization.The the game multidisciplinary design based on numerical simulation is proposed for those product design problem that difficult to use empirical or statistical formulas or other analytical methods to analyze.Firstly,using Solidworks software to establish the three-dimensional model of product,and then analyzing the product model in the Ansys software,finally integrating Solidworks software and Ansys software together through Isight software,and establishing the game framework in Isight software to optimize.Again,given the impact of the uncertainty,the flexible concept is introduced and put forward a flexible design model based on probability theory.We use the reference function of performance level as flexible expression of design requirements.The sought the flexible range of design variables replace the point solution of fixed value for increasing the flexibility of design process and design scheme.The flexible range of solution is in the feasible design space,to make each disciplinary performance at a satisfactory level and be close to the expected value,which has good stability.Probability distribution is used to build the model of corresponding performance change.Design preference index is introduced to evaluate the flexible design.Based on compromise decision support problem to establish multidisciplinary flexible design decision model and give the solving algorithm.Then,based on the above research,gives a multi-disciplinary flexible design decisions approach based on mix game,it reduces the coupling between disciplines and increases product design flexibility.Finally,the design and analysis of ship is used to verify the feasibility and effectiveness of the method.
Keywords/Search Tags:Multidisciplinary optimization, hybrid game, Design decisions, flexible design, Probability theory
PDF Full Text Request
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