Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 117085 |
| Seitenumfang | 24 |
| Fachzeitschrift | Computer Methods in Applied Mechanics and Engineering |
| Jahrgang | 428 |
| Frühes Online-Datum | 28 Mai 2024 |
| Publikationsstatus | Elektronisch veröffentlicht (E-Pub) - 28 Mai 2024 |
Abstract
This article develops an efficient uncertainty propagation framework for stochastic multiscale linear elasticity. Stochastic microscale problems are solved on the RVE with random material properties and random geometries. A stochastic homogenization approach is then used to calculate equivalent macroscale random material properties. According to different spatial correlations at the macroscale, random variables, random fields and high-dimensional random inputs are generated to model macroscale randomness. Stochastic finite element equations at both micro and macro scales are solved by using a unified and efficient numerical algorithm, which relies on a unified stochastic solution construction and an efficient iterative algorithm. It is efficient and accurate even for very high-dimensional problems due to its insensitivity to stochastic dimensions. Numerical results demonstrate the promising performance of the proposed framework, especially its high efficiency without loss of accuracy.
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- Ingenieurwesen (insg.)
- Numerische Mechanik
- Ingenieurwesen (insg.)
- Werkstoffmechanik
- Ingenieurwesen (insg.)
- Maschinenbau
- Physik und Astronomie (insg.)
- Informatik (insg.)
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in: Computer Methods in Applied Mechanics and Engineering, Jahrgang 428, 117085, 01.08.2024.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Efficient uncertainty propagation for stochastic multiscale linear elasticity
AU - Zheng, Zhibao
AU - Nackenhorst, Udo
N1 - Publisher Copyright: © 2024 The Author(s)
PY - 2024/5/28
Y1 - 2024/5/28
N2 - This article develops an efficient uncertainty propagation framework for stochastic multiscale linear elasticity. Stochastic microscale problems are solved on the RVE with random material properties and random geometries. A stochastic homogenization approach is then used to calculate equivalent macroscale random material properties. According to different spatial correlations at the macroscale, random variables, random fields and high-dimensional random inputs are generated to model macroscale randomness. Stochastic finite element equations at both micro and macro scales are solved by using a unified and efficient numerical algorithm, which relies on a unified stochastic solution construction and an efficient iterative algorithm. It is efficient and accurate even for very high-dimensional problems due to its insensitivity to stochastic dimensions. Numerical results demonstrate the promising performance of the proposed framework, especially its high efficiency without loss of accuracy.
AB - This article develops an efficient uncertainty propagation framework for stochastic multiscale linear elasticity. Stochastic microscale problems are solved on the RVE with random material properties and random geometries. A stochastic homogenization approach is then used to calculate equivalent macroscale random material properties. According to different spatial correlations at the macroscale, random variables, random fields and high-dimensional random inputs are generated to model macroscale randomness. Stochastic finite element equations at both micro and macro scales are solved by using a unified and efficient numerical algorithm, which relies on a unified stochastic solution construction and an efficient iterative algorithm. It is efficient and accurate even for very high-dimensional problems due to its insensitivity to stochastic dimensions. Numerical results demonstrate the promising performance of the proposed framework, especially its high efficiency without loss of accuracy.
KW - High stochastic dimensions
KW - Random geometry
KW - Stochastic finite element method
KW - Stochastic homogenization
KW - Stochastic multiscale analysis
UR - http://www.scopus.com/inward/record.url?scp=85194157999&partnerID=8YFLogxK
U2 - 10.1016/j.cma.2024.117085
DO - 10.1016/j.cma.2024.117085
M3 - Article
AN - SCOPUS:85194157999
VL - 428
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
SN - 0045-7825
M1 - 117085
ER -