学术报告第201551期

题   目：Introduction to A Posteriori Error Estimation  Techniques for Computer Simulations
主 讲 人：Zhiqiang Cai  (Purdue  University)
时     间：2015年12月22日下午16：00

地     点：南一楼中311

Professor  Zhiqiang Cai

Brief  Biography:

1982  B.S. Computer Science, HUST

1985  M.S. Applied Mathematics, HUST

1990  Ph.D. Applied Mathematics, University of Colorado, USA

1990  Postdoc at Brookhaven National Lab, USA

1990-1991  Postdoc at Courant Institute, New York University, USA

1991-1996  Assistant Professor, Department of Mathematics, Southern University of  California, USA

1996-present,  Associate Professor, Full Professor, Department of Mathematics, Purdue  University, USA

 Research  interests: Numerical Solution of Partial Differential Equations (Finite  Element, Finite Volume, and Least-Squares methods), Iterative Techniques  (Multilevel and Domain Decomposition Methods)，Computational  Electromagnetics, A Posteriori Error Estimation and Adaptive  Methods.

        Abstract:  Adaptive mesh refinement (AMR) algorithms are one of two necessary tools for  grand challenging problems in scientific computing. Reliability of computer  simulations is responsible for accurate computer predictions/designs. Efficient  and reliable a posteriori error estimation are, respectively, the key for  success of AMR algorithms and the reliability of computer predictions/designs  Since Babˇuska’s pioneering work in 1976, the a posteriori error  estimation has been extensively studied, and impressive progress has been made  during the past four decades. However, due to its extreme difficulty, this  important research field of computational science and engineering remains wide  open. In this talk, I will describe basic principles of the a posteriori  error estimation techniques for finite element approximations to partial  differential equations.