Abstract

ABSTRACT The importance of engineering simulation is increasing day by day with the increase of computing power. The finite element analysis method is one of the widely used approaches for this purpose. To achieve optimum simulation, there is no alternative to take complete control over the code which proprietary commercial codes fail to offer. This paper focuses on the review of the development of a finite element analysis framework using freely available python libraries and wrapping legacy C/C++ or Fortran libraries around python; and its verification as a viable finite element solution with an example of concrete tensile strength test simulation. Keywords that, Finite Element Analysis, Numerical Modeling, Engineering Simulation, Scientific Computing, Sparse Matrix, Python. 1. INTRODUCTION The finite element analysis is a computer based numerical technique which gives near accurate result in modeling complex engineering phenomena with very small error margin [1]. Major applications for FEA include static, dynamic and thermal characterizations of mechanical phenomena occuring in nature and in real life [2] [3]. FEA is also being used as a tool to model biological phenomena occuring in human body [4] and to optimize smart characteristics of advanced materials & devices [5]. Advances in computer hardware have made FEA easier and very efficient for solving complex engineering problems on desktop computers. To achieve optimum simulation, there is no alternative to take complete control over the code which proprietary commercial codes fail to offer. Moreover, To avoid input errors and increase the simulation reliability, the user must have the access to the source code level. This paper discusess the present numerical modeling practice and suggests an optimum numerical modeling framework from both the performance and accessibility point of view.

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