Details
| Original language | English |
|---|---|
| Article number | 117085 |
| Number of pages | 24 |
| Journal | Computer Methods in Applied Mechanics and Engineering |
| Volume | 428 |
| Early online date | 28 May 2024 |
| Publication status | E-pub ahead of print - 28 May 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.
Keywords
- High stochastic dimensions, Random geometry, Stochastic finite element method, Stochastic homogenization, Stochastic multiscale analysis
ASJC Scopus subject areas
- Engineering(all)
- Computational Mechanics
- Engineering(all)
- Mechanics of Materials
- Engineering(all)
- Mechanical Engineering
- Physics and Astronomy(all)
- Computer Science(all)
- Computer Science Applications
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In: Computer Methods in Applied Mechanics and Engineering, Vol. 428, 117085, 01.08.2024.
Research output: Contribution to journal › Article › Research › 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 -