|
| A polynomial dimensional decomposition method for analyzing statistical characteristics of structural random vibration responses in the time-domain |
| Received:May 25, 2023 Revised:July 20, 2023 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20230525003 |
| KeyWord:random vibration polynomial dimensional decomposition trigonometric series superposition PDD expansion model |
| Author | Institution |
| 刘凡 |
中南林业科技大学 土木工程学院, 长沙 ;大连理工大学 工程力学系, 大连 |
| 肖进 |
北京宇航系统工程研究所, 北京 |
| 韩波 |
大连理工大学 工程力学系, 大连 |
| 赵岩 |
大连理工大学 工程力学系, 大连 ;大连理工大学宁波研究院, 宁波 |
|
| Hits: 464 |
| Download times: 349 |
| Abstract: |
| This paper aims at the statistical characteristics analysis of the dynamic response of structures under random excitation,proposes a polynomial dimensional decomposition (PDD) method for the time-domain response analysis of structural stationary and non-stationary random vibration and effectively calculates the statistical moments and probability density of the structural random vibration response.Firstly,the trigonometric series superposition method is used to simulate the random excitation,the random phases in the method are taken as the random input of the structural system,and the random vibration response in the time-domain of the structure is regarded as a function of the random phases.Secondly,the structural response function is decomposed by component functions,and the component functions are expanded by the Fourier polynomials,then the PDD expansion model for the prediction of structural responses is constructed.Finally,in order to solve the problem of high-dimensional integration when constructing the PDD expansion model,the dimension reduction integration method is introduced to reduce the integration dimension and significantly improves the computational efficiency.In the numerical examples,the random vibration response analyses in the time-domain of a single-degree-of-freedom system and twenty-story frame structure are carried out,and the results calculated by the proposed method are compared with the results of Monte Carlo simulation to verify the accuracy and efficiency of the proposed method. |
|
|
|