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Why CAE?

Our Courses

Upcoming Events

Our Approach

We provide training in the field of Computer Aided Engineering (CAE) for working professionals and students. Finite element analysis (FEA) and Computational Fluid Dynamics (CFD) are our expertise. Our courses are specially designed to develop a conceptual and practical understanding. We use various open source tools like Salome, Code-Saturne, OpenFoam, Code-Aster, Elmer, Python, Scilab, Octave for CFD & FEA simulations.

Learning CAE is much more than learning a particular

commercial software !!!

 Many a time, learning such wonderful and versatile techniques are confused with handling of certain commercial software. While any software with well-designed and attractive user interface creates an euphoria about its capability and sophistication, but many end up using them like a black-box. Even people with good experience and expertise in certain software, end-up following a trial and error approach due to lack of understanding of the basics of the technique. So, it is important for any practising (as well as aspiring) engineers and researchers to have a complete end to end understanding of the methods.

This includes the following

• Pre-processing: This includes all the steps involved in transforming the actual governing equation of the problem to a numerical formulation and applying them over a discretized domain (meshing) along with appropriate boundary and initial conditions. The problem over the continuous domain is mapped to finite number points.

 

Solving: This involves finding the solution of the numerical formulation with desired accuracy level in an iterative manner by using appropriate solving technique. For example, solving techniques for linear and non-linear problem ought to be different. So understanding the mathematical model always helps in choosing appropriate solver.

• Post-processing: In this step the solution obtained at finite number of points is further processed and interpolated to get the approximate solution over the entire domain.

So the objective of learning CAE techniques needs to be learning the problem solving approach rather than particular software. Someone with good idea of the basics of methods, can always adapt any software quickly, as irrespective of how the user interface looks in different software the core remains same.

Our courses are designed with the following objectives.

 • Help engineering graduates to acquire more practical knowledge of Design and Analysis.

• Provide In depth knowledge in FEM/FEA/CFD practices.

• To spread R&D activities at academic institutes.

Why CAE?

To solve any real life engineering problem, there are basically two steps:

I. Mathematical Modelling: The aim of this step is to develop the governing equation(s) for the problem. This gives rise to a set of algebraic/ differential/ integral or combinations of such equations. For example, the motion of a mass particle can be modelled by a second order Differential Equation, popularly known as Newton’s 2nd second law of motion.

II. Solution of Governing Equations: If the governing equations are simple, then they can be solved by using appropriate analytical methods. For example, some ordinary differential equations (ODEs) and partial differential equations (PDEs) can be solved by using analytical methods e.g. variable separable method. If analytical solution is not available, numerical method is used to find an approximate solution for the problem.

What is Computer Aided Engineering (CAE) and why it is required?

With the emergence of sophisticated and powerful computers, there has been a growing use of computers for solving various engineering problems. All such problem solving approaches, where there is extensive use of computers, can be classified as CAE. To solve the problems using computer various numerical methods/ schemes have been developed.

 

 

 

How numerical methods solve the problem?

Numerical solving techniques are approximate methods, where the domain is divided into smaller & simpler segments; this is known as discretization. Then, an approximate solution of governing equations are achieved in these smaller domains. For example, an approximate solution of a set of PDEs over a complex plane area can be obtained, by first dividing the domain into quadrangles/ triangles and then converting the PDEs into a set of algebraic equations by using Taylor’s expansion. Subsequently an approximate solution is obtained , by solving the algebraic equations over the discretized domain with help the boundary conditions and initial conditions.

Major Numerical Solving techniques:

As the mathematical modelling of most engineering problems give rise to ordinary or partial differential equations, so most of the times, when we talk of such techniques, they mean some method to solve the differential equations. Out of many approaches, finite element analysis/methods (FEA/FEM), finite volume methods (FVM), finite difference methods (FDM) and boundary element methods (BEM) are some popular techniques and extensively used .