Details
| Originalsprache | Englisch |
|---|---|
| Seitenumfang | 8 |
| Publikationsstatus | Veröffentlicht - 2019 |
| Veranstaltung | 13th International Conference on Applications of Statistics and Probability in Civil Engineering - Seoul, South Korea, Seoul, Südkorea Dauer: 26 Mai 2019 → 30 Mai 2019 Konferenznummer: 13 |
Konferenz
| Konferenz | 13th International Conference on Applications of Statistics and Probability in Civil Engineering |
|---|---|
| Kurztitel | ICASP13 |
| Land/Gebiet | Südkorea |
| Ort | Seoul |
| Zeitraum | 26 Mai 2019 → 30 Mai 2019 |
Abstract
Considering an uncertain correlation length of the input random fields described by a Karhunen-Loève expansion leads to a probability-box approach for the stochastic finite element computation. But, these computations are highly costly. Then, a stochastic collocation method using sparse grids within a Smolyak algorithm is proposed to reduce the computational cost, particularly in the context of non-linear computations. The interest and the development of the Smolyak algorithm for stochastic model with non-linear finite element methods regarding mixed, aleatory and epistemic, uncertain inputs are here introduced. The limitations of Smolyak algorithm are critically discussed and suggestions for improvement are made.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Tief- und Ingenieurbau
- Mathematik (insg.)
- Statistik und Wahrscheinlichkeit
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2019. Beitrag in 13th International Conference on Applications of Statistics and Probability in Civil Engineering, Seoul, Südkorea.
Publikation: Konferenzbeitrag › Paper › Forschung › Peer-Review
}
TY - CONF
T1 - A collocation scheme for deep uncertainty treatment
AU - Dannert, Mona M.
AU - Fau, Amelie
AU - N. Fleury, Rodolfo M.
AU - Broggi, Matteo
AU - Nackenhorst, Udo
AU - Beer, Michael
N1 - Conference code: 13
PY - 2019
Y1 - 2019
N2 - Considering an uncertain correlation length of the input random fields described by a Karhunen-Loève expansion leads to a probability-box approach for the stochastic finite element computation. But, these computations are highly costly. Then, a stochastic collocation method using sparse grids within a Smolyak algorithm is proposed to reduce the computational cost, particularly in the context of non-linear computations. The interest and the development of the Smolyak algorithm for stochastic model with non-linear finite element methods regarding mixed, aleatory and epistemic, uncertain inputs are here introduced. The limitations of Smolyak algorithm are critically discussed and suggestions for improvement are made.
AB - Considering an uncertain correlation length of the input random fields described by a Karhunen-Loève expansion leads to a probability-box approach for the stochastic finite element computation. But, these computations are highly costly. Then, a stochastic collocation method using sparse grids within a Smolyak algorithm is proposed to reduce the computational cost, particularly in the context of non-linear computations. The interest and the development of the Smolyak algorithm for stochastic model with non-linear finite element methods regarding mixed, aleatory and epistemic, uncertain inputs are here introduced. The limitations of Smolyak algorithm are critically discussed and suggestions for improvement are made.
UR - http://www.scopus.com/inward/record.url?scp=85126502983&partnerID=8YFLogxK
U2 - 10.22725/ICASP13.179
DO - 10.22725/ICASP13.179
M3 - Paper
AN - SCOPUS:85126502983
T2 - 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019
Y2 - 26 May 2019 through 30 May 2019
ER -