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The Study On The Method Of Structural Optimization Design On The Complicated Component Of The Large Mechanical System

Posted on:2003-09-20Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y J WangFull Text:PDF
GTID:1102360062995710Subject:Mechanical design and theory
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The optimization of a large complicated mechanical system (LCMS) can be realized satisfactorily, lies on the two factories: the one is to set up a reasonable optimization model; the other is to select a effective optimal algorithm fit for this model. The LCMS has large numbers of component parts, complicated correlations and lots of the questions brought on by some unsure factories. The model can also include different-characteristic functions, so that it is very difficulty to find the feasible optimization methods. In this thesis a solution scheme for solving the problem of whole optimization of the General Layout Spreader (GLS) used in mine is given. The scheme includes the two aspects: the study on the whole optimization and the space trusses optimization.In the whole optimization, the GLS whole system is divided into some subsystems by systemic parameters and their functions. The key technique is parameters classify. First, by the information in existence, such as engineering drawings and lists, the master variables, local variables and activate variables are fixed out automatically. And then, by expert databases, it is modified to the dividing results and eventually the comprehensive describing on the subsystems and the relevant objective functions are obtained. The whole strategy must ensure that its dividing result is correct under the precondition of low dimension and simple function.In trusses structural optimization, the characteristics of the section, shape and topology optimal algorithm of continuous variables and discrete variables are carefully studied, and the two new optimal algorithms to resolve continuous and discrete problems are brought forward. For the optimization of the continuous variables, the author combines the weaken idea, the DFP and the gradient projection method to form a modified Goldfarb method by which the optimal problems of the trusses can be solved. The examples indicate that the algorithm has strong pertinence and high efficiency, hi the discrete variable optimization, the problem is solved in the relative quotient method On the base of analyzing the relative quotient method, the conjugate gradient direction is used to modify the old search directions, the iterative matrix of the algorithm, and the method to resolve the discrete variable optimization, the relative conjugate difference quotient algorithm (RCDQ) is presented. The modified Goldfarb method and the RCDQ absorb the modified idea of Professor Sui Yunkang and the optimal idea of Professor Goldfarb and resolve the problems on relevant constrains and capacity.The above optimal algorithm remarkably reduced the iterative times under the precondition, which uses a lot of EMS memory, and its computing time cannot be remarkably reduced. The most of the computing time is consumed by the structurere-analysis and the accurate constraint functions set up before every optimal step. The most effective method to resolve the problem is that utilizes the approaching capability of the neural network, and overlap the time of the structural re-analysis and optimization by the parallel algorithm. In this thesis a neural network model to approach the trusses is established, and trained by the given precision. The results indicate that the method is feasible and reduce the time used into the structural re-analysis in the optimization process very largely.
Keywords/Search Tags:LCMS, whole optimization strategy, trusses, modified Goldfrab method, RCDQ, the neural network
PDF Full Text Request
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