研究生: |
Nophi Ian Delos Reyes Biton Nophi Ian Delos Reyes Biton |
---|---|
論文名稱: |
Reliability-based Design Optimization using Methods of Moments Reliability-based Design Optimization using Methods of Moments |
指導教授: |
廖國偉
Kuo-Wei Liao |
口試委員: |
卿建業
Jian-ye Ching 林柏廷 Po Ting Lin 陳瑞華 Rwey-Hua Cherng |
學位類別: |
碩士 Master |
系所名稱: |
工程學院 - 營建工程系 Department of Civil and Construction Engineering |
論文出版年: | 2017 |
畢業學年度: | 105 |
語文別: | 英文 |
論文頁數: | 148 |
中文關鍵詞: | Reliability 、Optimization 、RBDO 、PSO 、Methods of Moments |
外文關鍵詞: | Reliability, Optimization, RBDO, PSO, Methods of Moments |
相關次數: | 點閱:322 下載:4 |
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Reliability-based Design Optimization (RBDO) produces optimal design with minimal cost and ensures a more reliable performance of the structure by explicitly incorporating uncertainties in its optimization algorithm. Expensive computational cost, accuracy of reliability assessment, as well as nonlinearity and non-differentiability of performance function are the main challenges in performing RBDO in real engineering problems. The promising accuracy and efficiency of Methods of Moments such as simplified third-moment (3M), fourth-moment (4M) and Pearson’s Distribution System-based fourth-moment (4M-P) for probabilistic analysis in combination with a metaheuristic optimization algorithm (i.e. Particle Swarm Optimization, PSO) is explored for RBDO implementation. The proposed methodology was able to search for the optimal design having linear, highly nonlinear, and implicit performance functions considered in the probabilistic constraints which were demonstrated in several numerical examples. To emphasize the applicability of the proposed algorithm in practical engineering problems, a two bay three story steel structure were solved, in which an equivalent stick model was developed to further lessen the computational cost in nonlinear time history analyses. The results were validated and compared from gathered related literature. The limitation on the applicable range of the simplified Methods of Moments produced incorrect optimal design in the RBDO for highly nonlinear limit state functions and non-normal random variables. However, for normally distributed random variables, simplified Methods of Moments formulations showed improved accuracy in structural reliability at optimal design compared to other existing reliability methods. Also, by increasing the number of variates in dimension reduction method, more accurate estimation of the moments of the performance function was observed. Finally, the implications of the results and limitations of the methodology are discussed
Reliability-based Design Optimization (RBDO) produces optimal design with minimal cost and ensures a more reliable performance of the structure by explicitly incorporating uncertainties in its optimization algorithm. Expensive computational cost, accuracy of reliability assessment, as well as nonlinearity and non-differentiability of performance function are the main challenges in performing RBDO in real engineering problems. The promising accuracy and efficiency of Methods of Moments such as simplified third-moment (3M), fourth-moment (4M) and Pearson’s Distribution System-based fourth-moment (4M-P) for probabilistic analysis in combination with a metaheuristic optimization algorithm (i.e. Particle Swarm Optimization, PSO) is explored for RBDO implementation. The proposed methodology was able to search for the optimal design having linear, highly nonlinear, and implicit performance functions considered in the probabilistic constraints which were demonstrated in several numerical examples. To emphasize the applicability of the proposed algorithm in practical engineering problems, a two bay three story steel structure were solved, in which an equivalent stick model was developed to further lessen the computational cost in nonlinear time history analyses. The results were validated and compared from gathered related literature. The limitation on the applicable range of the simplified Methods of Moments produced incorrect optimal design in the RBDO for highly nonlinear limit state functions and non-normal random variables. However, for normally distributed random variables, simplified Methods of Moments formulations showed improved accuracy in structural reliability at optimal design compared to other existing reliability methods. Also, by increasing the number of variates in dimension reduction method, more accurate estimation of the moments of the performance function was observed. Finally, the implications of the results and limitations of the methodology are discussed
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