Details
| Original language | English |
|---|---|
| Pages (from-to) | 4471-4477 |
| Number of pages | 7 |
| Journal | AIAA journal |
| Volume | 60 |
| Issue number | 7 |
| Early online date | 8 Apr 2022 |
| Publication status | Published - 10 Apr 2022 |
Abstract
A study focuses on the generalized global non-intrusive imprecise stochastic simulation (NISS) method, as it can propagate both the imprecise probability models and nonprobabilistic models at the same time. The staircase distributions are theoretically ready to be used in this method by constructing parametric p-boxes defining their hyper parameters as interval values. The feasibility of the proposed method is demonstrated by solving the reliability analysis subproblem of the NASA uncertainty quantification (UQ) challenge problem 2019. The Gaussian distribution-based p-box naturally contains Gaussian distributions, whereas the staircase distribution-based p-box contains a broad range of distributions, including skewed and bimodal distributions. A hybrid NISS method is developed, where the staircase distribution-based p-boxes are propagated by the local NISS method to significantly suppress the computational cost to estimate the component functions over the hyperparameters.
ASJC Scopus subject areas
- Engineering(all)
- Aerospace Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: AIAA journal, Vol. 60, No. 7, 10.04.2022, p. 4471-4477.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - A Distributionally Robust Approach for Mixed Aleatory and Epistemic Uncertainties Propagation
AU - Kitahara, Masaru
AU - Song, Jingwen
AU - Wei, Pengfei
AU - Broggi, Matteo
AU - Beer, Michael
PY - 2022/4/10
Y1 - 2022/4/10
N2 - A study focuses on the generalized global non-intrusive imprecise stochastic simulation (NISS) method, as it can propagate both the imprecise probability models and nonprobabilistic models at the same time. The staircase distributions are theoretically ready to be used in this method by constructing parametric p-boxes defining their hyper parameters as interval values. The feasibility of the proposed method is demonstrated by solving the reliability analysis subproblem of the NASA uncertainty quantification (UQ) challenge problem 2019. The Gaussian distribution-based p-box naturally contains Gaussian distributions, whereas the staircase distribution-based p-box contains a broad range of distributions, including skewed and bimodal distributions. A hybrid NISS method is developed, where the staircase distribution-based p-boxes are propagated by the local NISS method to significantly suppress the computational cost to estimate the component functions over the hyperparameters.
AB - A study focuses on the generalized global non-intrusive imprecise stochastic simulation (NISS) method, as it can propagate both the imprecise probability models and nonprobabilistic models at the same time. The staircase distributions are theoretically ready to be used in this method by constructing parametric p-boxes defining their hyper parameters as interval values. The feasibility of the proposed method is demonstrated by solving the reliability analysis subproblem of the NASA uncertainty quantification (UQ) challenge problem 2019. The Gaussian distribution-based p-box naturally contains Gaussian distributions, whereas the staircase distribution-based p-box contains a broad range of distributions, including skewed and bimodal distributions. A hybrid NISS method is developed, where the staircase distribution-based p-boxes are propagated by the local NISS method to significantly suppress the computational cost to estimate the component functions over the hyperparameters.
UR - http://www.scopus.com/inward/record.url?scp=85133692622&partnerID=8YFLogxK
U2 - 10.2514/1.J061394
DO - 10.2514/1.J061394
M3 - Article
AN - SCOPUS:85133692622
VL - 60
SP - 4471
EP - 4477
JO - AIAA journal
JF - AIAA journal
SN - 0001-1452
IS - 7
ER -