Details
| Original language | English |
|---|---|
| Article number | 103368 |
| Journal | Probabilistic Engineering Mechanics |
| Volume | 70 |
| Early online date | 14 Sept 2022 |
| Publication status | Published - Oct 2022 |
Abstract
This contribution focuses on reliability-based design and optimum design sensitivity of linear dynamical structural systems subject to Gaussian excitation. Directional Importance Sampling (DIS) is implemented for reliability assessment, which allows to obtain first-order derivatives of the failure probabilities as a byproduct of the sampling process. Thus, gradient-based solution schemes can be adopted by virtue of this feature. In particular, a class of feasible-direction interior point algorithms are implemented to obtain optimum designs, while a direction-finding approach is considered to obtain optimum design sensitivity measures as a post-processing step of the optimization results. To show the usefulness of the approach, an example involving a building structure is studied. Overall, the reliability sensitivity analysis framework enabled by DIS provides a potentially useful tool to address a practical class of design optimization problems.
Keywords
- Directional Importance Sampling, First excursion probability, Gaussian loading, Interior point algorithm, Linear structures, Optimum design sensitivity, Structural design
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Statistical and Nonlinear Physics
- Engineering(all)
- Civil and Structural Engineering
- Energy(all)
- Nuclear Energy and Engineering
- Physics and Astronomy(all)
- Condensed Matter Physics
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Ocean Engineering
- Engineering(all)
- Mechanical Engineering
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In: Probabilistic Engineering Mechanics, Vol. 70, 103368, 10.2022.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - On the use of Directional Importance Sampling for reliability-based design and optimum design sensitivity of linear stochastic structures
AU - Jerez, Danko J.
AU - Jensen, Héctor A.
AU - Valdebenito, Marcos A.
AU - Misraji, Mauricio A.
AU - Mayorga, Franco
AU - Beer, Michael
N1 - Funding Information: This research is partially supported by ANID (National Agency for Research and Development, Chile) under its program FONDECYT, grant numbers 1200087 and 1180271 . Also, this research has been partially supported by ANID, Chile and DAAD (German Academic Exchange Service, Germany) under CONICYT-PFCHA/Doctorado Acuerdo Bilateral DAAD Becas Chile/ 2018-62180007 . These supports are gratefully acknowledged by the authors.
PY - 2022/10
Y1 - 2022/10
N2 - This contribution focuses on reliability-based design and optimum design sensitivity of linear dynamical structural systems subject to Gaussian excitation. Directional Importance Sampling (DIS) is implemented for reliability assessment, which allows to obtain first-order derivatives of the failure probabilities as a byproduct of the sampling process. Thus, gradient-based solution schemes can be adopted by virtue of this feature. In particular, a class of feasible-direction interior point algorithms are implemented to obtain optimum designs, while a direction-finding approach is considered to obtain optimum design sensitivity measures as a post-processing step of the optimization results. To show the usefulness of the approach, an example involving a building structure is studied. Overall, the reliability sensitivity analysis framework enabled by DIS provides a potentially useful tool to address a practical class of design optimization problems.
AB - This contribution focuses on reliability-based design and optimum design sensitivity of linear dynamical structural systems subject to Gaussian excitation. Directional Importance Sampling (DIS) is implemented for reliability assessment, which allows to obtain first-order derivatives of the failure probabilities as a byproduct of the sampling process. Thus, gradient-based solution schemes can be adopted by virtue of this feature. In particular, a class of feasible-direction interior point algorithms are implemented to obtain optimum designs, while a direction-finding approach is considered to obtain optimum design sensitivity measures as a post-processing step of the optimization results. To show the usefulness of the approach, an example involving a building structure is studied. Overall, the reliability sensitivity analysis framework enabled by DIS provides a potentially useful tool to address a practical class of design optimization problems.
KW - Directional Importance Sampling
KW - First excursion probability
KW - Gaussian loading
KW - Interior point algorithm
KW - Linear structures
KW - Optimum design sensitivity
KW - Structural design
UR - http://www.scopus.com/inward/record.url?scp=85139864510&partnerID=8YFLogxK
U2 - 10.1016/j.probengmech.2022.103368
DO - 10.1016/j.probengmech.2022.103368
M3 - Article
AN - SCOPUS:85139864510
VL - 70
JO - Probabilistic Engineering Mechanics
JF - Probabilistic Engineering Mechanics
SN - 0266-8920
M1 - 103368
ER -