中文版 | English

在结果中检索

CSpace

浏览/检索结果: 共5条，第1-5条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Stochastic higher-order three-scale strength prediction model for composite structures with micromechanical analysis 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2022, 卷号: 465, 页码: 30
作者:  Dong, Hao;  Yang, Zihao;  Guan, Xiaofei;  Cui, Junzhi
收藏  |  浏览/下载：75/0  |  提交时间：2023/02/07
Composite structures  Multiscale random configurations  SHTSP model  Multilevel strategy  Strength prediction  
Optimal design for kernel interpolation: Applications to uncertainty quantification 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2021, 卷号: 430, 页码: 19
作者:  Narayan, Akil;  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：138/0  |  提交时间：2021/04/26
Kernel interpolation  Fekete points  Cholesky decomposition with pivoting  Hermite interpolation  Uncertainty quantification  
A second-order and nonuniform time-stepping maximum-principle preserving scheme for time-fractional Allen-Cahn equations 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2020, 卷号: 414, 页码: 16
作者:  Liao, Hong-lin;  Tang, Tao;  Zhou, Tao
收藏  |  浏览/下载：159/0  |  提交时间：2020/06/30
Time-fractional Allen-Cahn equation  Alikhanov formula  Adaptive time-stepping strategy  Discrete maximum principle  Sharp error estimate  
Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2019, 卷号: 381, 页码: 110-128
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：166/0  |  提交时间：2019/03/11
Bayesian inverse problems  Multi-fidelity polynomial chaos  Surrogate modeling  Markov chain Monte Carlo  
Data-driven polynomial chaos expansions: A weighted least-square approximation 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2019, 卷号: 381, 页码: 129-145
作者:  Guo, Ling;  Liu, Yongle;  Zhou, Tao
收藏  |  浏览/下载：161/0  |  提交时间：2019/03/11
Uncertainty quantification  Data-driven polynomial chaos expansions  Weighted least-squares  Equilibrium measure