ZHANG Jian, YE Jian-shu, ZHOU Chu-wei. Powell’s Optimal Identification of Material Constants of Thin-Walled Box Girders Based on Fibonacci Series Search Method[J]. Applied Mathematics and Mechanics, 2011, 32(1): 93-102. doi: 10.3879/j.issn.1000-0887.2011.01.010
Citation: ZHANG Jian, YE Jian-shu, ZHOU Chu-wei. Powell’s Optimal Identification of Material Constants of Thin-Walled Box Girders Based on Fibonacci Series Search Method[J]. Applied Mathematics and Mechanics, 2011, 32(1): 93-102. doi: 10.3879/j.issn.1000-0887.2011.01.010

Powell’s Optimal Identification of Material Constants of Thin-Walled Box Girders Based on Fibonacci Series Search Method

doi: 10.3879/j.issn.1000-0887.2011.01.010
  • Received Date: 2010-08-29
  • Rev Recd Date: 2010-12-01
  • Publish Date: 2011-01-15
  • For thin-walled curve box girders,dynamic Bayesian error function of material constants of the structure was founded.Combined with one-dimensional Fibonacci series automatic search scheme of optimal step length,the Powell's optimization theory was utilized to perform the stochastic identification of material constants of thin-walled curve box.Then the steps of parameters'identification were presented in detail and the Powell's identification procedure of material constants of thin-walled curve box was compiled,in which the mechanical analysis of thin-walled curve box was completed based on finite curve strip element(FCSE)method.Through some classic examples,it is obtained that the Powell's identification of material constants of thin-walled curve box has numerical stability and convergence,which demonstrates that the present method and the compiled procedure are correct and reliable.And during parameters'iterative processes,the Powell's theory is irrelevant with the calculation of FCSE's partial differentiation, which proves high computation efficiency of the studied methods.The stochastic performances of systematic parameters and systematic responses are simultaneously deliberated in dynamic Bayesian error function. The one-dimensional optimization problem of the optimal step length is solved by adopting Fibonacci series search method and there is no need to determine the region in which the optimized step length lies.
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