کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
499260 | 863035 | 2008 | 13 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A computational procedure for response statistics-based optimization of stochastic non-linear FE-models A computational procedure for response statistics-based optimization of stochastic non-linear FE-models](/preview/png/499260.png)
An approach for an efficient solution of response statistics-based optimization problems of non-linear FE systems under stochastic loading is presented. A sequential approximate optimization approach, where approximate stochastic analyses are used during portions of the optimization process, is implemented in the proposed formulation. In this approach, analytical approximations of the performance functions in terms of the design variables are considered during the optimization process. The analytical approximations are constructed by combining a mixed linearization approach with a stochastic response sensitivity analysis. The state of the system is defined in terms of the statistical second-moment characteristics of the structural response. The stochastic loading and the response of the system are represented by an orthogonal series expansion of the corresponding covariance matrices. In particular, a truncated Karhunen–Loève (K–L) expansion is applied. The system of non-linear equations is replaced by a statistical equivalent linear system. The evaluation of the K–L vectors is carried out by an efficient procedure that combines local linearization, modal analysis and static response of higher structural modes. An illustrative example is presented that shows the efficiency of the proposed methodology: it considers a building finite element model enforced with non-linear hysteretic devices and subject to a stochastic ground acceleration. Two types of problems are considered: a minimum structural weight design problem and an optimal non-linear device design problem.
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 198, Issue 1, 15 November 2008, Pages 125–137