Details
| Original language | English |
|---|---|
| Title of host publication | OPT-i 2014 - 1st International Conference on Engineering and Applied Sciences Optimization, Proceedings |
| Editors | N. D. Lagaros, Matthew G. Karlaftis, M. Papadrakakis |
| Pages | 2213-2233 |
| Number of pages | 21 |
| ISBN (electronic) | 9789609999465 |
| Publication status | Published - 2014 |
| Externally published | Yes |
| Event | 1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014 - Kos Island, Greece Duration: 4 Jun 2014 → 6 Jun 2014 |
Abstract
A novel methodology for optimal structural system design considering life cycle seismic loss estimation is developed. Specifically, a performance-based multi-objective design optimization framework is proposed for nonlinear/hysteretic multi-degree-of-freedom (MDOF) structural systems under evolutionary stochastic earthquake excitations. The core of the proposed framework is a recently developed efficient approximate analytical system response determination technique which can readily handle cases of nonlinear/hysteretic systems and of non-stationary stochastic excitations of arbitrary evolutionary power spectrum forms. Thus, the non-stationary response amplitude probability density functions (PDFs) of the inter-storey drift ratios (IDRs) are efficiently determined, circumventing computationally intensive Monte Carlo simulations. Note that the proposed framework allows for making explicit the relationship between the stochastic earthquake excitations, the non-stationary response amplitude PDFs of the IDRs, and the expected value of the life cycle seismic losses. In this regard, an efficient determination of Pareto optimal solutions is implemented. Further, the multi-objective optimization problem is solved by employing a Genetic Algorithm based approach to determine Pareto optimal solutions, which is specifically tailored to meet the characteristics of the problem under consideration. Hence, various possible solutions including the design that best represents the outcome that the designer considers potentially satisfactory are obtained. An illustrative numerical example, comprising the versatile Bouc-Wen (hysteretic) model is considered to demonstrate the efficiency and robustness of the proposed methodology.
Keywords
- Evolutionary stochastic excitations, Hysteretic systems, Life-cycle loss estimation, Multi-objective optimization, Statistical linearization, Stochastic dynamics
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Computer Science(all)
- Software
- Engineering(all)
- General Engineering
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OPT-i 2014 - 1st International Conference on Engineering and Applied Sciences Optimization, Proceedings. ed. / N. D. Lagaros; Matthew G. Karlaftis; M. Papadrakakis. 2014. p. 2213-2233.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Optimal design of nonlinear structures under evolutionary stochastic earthquake excitations
AU - Mitseas, Ioannis P.
AU - Kougioumtzoglou, Ioannis A.
AU - Beer, Michael
PY - 2014
Y1 - 2014
N2 - A novel methodology for optimal structural system design considering life cycle seismic loss estimation is developed. Specifically, a performance-based multi-objective design optimization framework is proposed for nonlinear/hysteretic multi-degree-of-freedom (MDOF) structural systems under evolutionary stochastic earthquake excitations. The core of the proposed framework is a recently developed efficient approximate analytical system response determination technique which can readily handle cases of nonlinear/hysteretic systems and of non-stationary stochastic excitations of arbitrary evolutionary power spectrum forms. Thus, the non-stationary response amplitude probability density functions (PDFs) of the inter-storey drift ratios (IDRs) are efficiently determined, circumventing computationally intensive Monte Carlo simulations. Note that the proposed framework allows for making explicit the relationship between the stochastic earthquake excitations, the non-stationary response amplitude PDFs of the IDRs, and the expected value of the life cycle seismic losses. In this regard, an efficient determination of Pareto optimal solutions is implemented. Further, the multi-objective optimization problem is solved by employing a Genetic Algorithm based approach to determine Pareto optimal solutions, which is specifically tailored to meet the characteristics of the problem under consideration. Hence, various possible solutions including the design that best represents the outcome that the designer considers potentially satisfactory are obtained. An illustrative numerical example, comprising the versatile Bouc-Wen (hysteretic) model is considered to demonstrate the efficiency and robustness of the proposed methodology.
AB - A novel methodology for optimal structural system design considering life cycle seismic loss estimation is developed. Specifically, a performance-based multi-objective design optimization framework is proposed for nonlinear/hysteretic multi-degree-of-freedom (MDOF) structural systems under evolutionary stochastic earthquake excitations. The core of the proposed framework is a recently developed efficient approximate analytical system response determination technique which can readily handle cases of nonlinear/hysteretic systems and of non-stationary stochastic excitations of arbitrary evolutionary power spectrum forms. Thus, the non-stationary response amplitude probability density functions (PDFs) of the inter-storey drift ratios (IDRs) are efficiently determined, circumventing computationally intensive Monte Carlo simulations. Note that the proposed framework allows for making explicit the relationship between the stochastic earthquake excitations, the non-stationary response amplitude PDFs of the IDRs, and the expected value of the life cycle seismic losses. In this regard, an efficient determination of Pareto optimal solutions is implemented. Further, the multi-objective optimization problem is solved by employing a Genetic Algorithm based approach to determine Pareto optimal solutions, which is specifically tailored to meet the characteristics of the problem under consideration. Hence, various possible solutions including the design that best represents the outcome that the designer considers potentially satisfactory are obtained. An illustrative numerical example, comprising the versatile Bouc-Wen (hysteretic) model is considered to demonstrate the efficiency and robustness of the proposed methodology.
KW - Evolutionary stochastic excitations
KW - Hysteretic systems
KW - Life-cycle loss estimation
KW - Multi-objective optimization
KW - Statistical linearization
KW - Stochastic dynamics
UR - http://www.scopus.com/inward/record.url?scp=84911904134&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84911904134
SP - 2213
EP - 2233
BT - OPT-i 2014 - 1st International Conference on Engineering and Applied Sciences Optimization, Proceedings
A2 - Lagaros, N. D.
A2 - Karlaftis, Matthew G.
A2 - Papadrakakis, M.
T2 - 1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014
Y2 - 4 June 2014 through 6 June 2014
ER -