4 papers
An efficient solver based on low-rank approximation and Neumann matrix series for unsteady diffusion-type partial differential equations with random coefficients
Yujun Zhu, Min Li, Yulan Ning +1
In this paper, we develop an efficient numerical solver for unsteady diffusion-type partial differential equations with random coefficients. A major computational challenge in such…
A low-rank solver for the Stokes-Darcy model with random hydraulic conductivity and Beavers-Joseph condition
Yujun Zhu, Yulan Ning, Zhipeng Yang +2
This paper proposes, analyzes, and demonstrates an efficient low-rank solver for the stochastic Stokes-Darcy interface model with a random hydraulic conductivity both in the porous…
Splitting Method for Stochastic Navier-Stokes Equations
Jie Zhu, Yujun Zhu, Ju Ming +1
This paper investigates the two-dimensional stochastic steady-state Navier-Stokes(NS) equations with additive random noise. We introduce an innovative splitting method that decompo…
Clustering-based Low Rank Approximation Method
Yujun Zhu, Jie Zhu, Hizba Arshad +2
We propose a clustering-based generalized low rank approximation method, which takes advantage of appealing features from both the generalized low rank approximation of matrices (G…