Computational Engineering & Simulations using Python: FEM & FVM

Computational Engineering & Simulations using Python: FEM & FVM
(In Association with iHUB Divyasampark IIT Roorkee)

About this Course:

This course provides a hands-on & application-oriented knowledge on computational engineering and numerical simulations covering core techniques- Finite Element Method (FEM) and Finite Volume Method (FVM) for solving Engineering problems. This course begins with Python fundamentals with a strong focus on its libraries like NumPy & Matplotlib. It then covers numerical schemes and iterative solvers used in Computational Engineering and progressively moves on to introduce FEM formulation, element modelling, boundary conditions, and post-processing for both 1D and 2D problems, with a strong focus on implementation, physical interpretation of results, error and convergence analysis through practical, industry-relevant case studies. Finally, it introduces FVM and discusses how to develop stable and accurate solvers for diffusion, advection–diffusion, and 2D fluid flow problems with FVM using Python programming.

Course Objectives:
•   Build a strong foundation in Python programming for numerical computing and scientific visualization.
•   Implement and analyse iterative linear solvers (Jacobi, Gauss–Seidel and SOR) and understand their convergence behaviour.
•   Apply key Numerical discretization schemes and evaluate their relative accuracy and stability.
•   Formulate and implement finite element method (FEM) solutions for 1D and 2D engineering problems in structural analysis.
•   Perform error estimation and mesh-convergence studies to assess numerical accuracy and solution reliability in FEM.

• Build and validate finite volume method (FVM) solvers for 1D and 2D diffusion and fluid-flow problems using Python.

Batch Details:
Class Timings: 7:00 pm – 9:00 pm (Monday-Wednesday-Friday) Start Date: 01st June 2026
Duration: 64 Hours End Date: 14th Aug 2026
Mode: Online Certification: iHUB Divyasampark IIT Roorkee
Last Date to Register: 31st May 2026

Course Fee: Rs. 7000/- (Amount inclusive of GST)

Course Highlights:
• Industry-Relevant Skills in computational Engineering & Numerical Techniques.
• Essential Skills to fit into the roles of CFD Analytst, FE Analyst etc.
• Globally accepted certification from iHUB Divyasampark IIT Roorkee
• Full-time access to recorded lectures/PPTs/PDFs/Study Materials.

Course Overview:

Module 1: Python Programming Fundamentals

Installation of Anaconda Environment, working with Jupyter notebook.
Basics of Python Language; Python objects with details of shell/numbers/variables etc.
Introduction to NumPy Library.
Arithmetic and Numerical operations using NumPy
Data Visualization and plotting using Matplotlib.

Module 2: Numerical Schemes and Solver

Forward, backward and central schemes, order of accuracy.
Assessment of various schemes through python coding.
Introduction to Iterative Solvers.
Implementation of Jacobi, Gauss-Seidel and SOR solvers using Python and study on their convergence behavior.

Module 3: Finite Element Method Fundamentals

Governing equations, Strong vs weak form
Galerkin formulation; Boundary conditions (Dirichlet and Neumann)
Element types: 1D linear & quadratic.
Shape functions and interpolation error, Isoparametric mapping, Gaussian quadrature and integration accuracy.
Python implementation: Axial bar under static load, 1D Heat conduction.

Module 4: Finite Element Methods for two-dimensional problems

2D triangular elements.
Poisson equation formulation.
Stress and flux computation; post-processing and visualization.
Python implementation: Plane stress plate with hole, 2D heat conduction (welding: moving heat source).

Module 5: Error Analysis & Convergence in FEM

Sources of FEM error, error norms.
Mesh convergence studies (h-convergence).
Patch test & consistency check.
Python implementation in the Stress convergence in bar problems.

Module 6: Finite Volume Methods Fundamentals

Introduction to FVM, its formulation and basic theoretical concepts.
1D steady and unsteady heat conduction, stability conditions.
Developing python implementations of 1D steady & unsteady heat conduction equations.
1D Advection- Diffusion: Stability, upwinding & concepts of Numerical Diffusion.
Developing python implementations of 1D Advection-diffusion Equations.

Module 7: Finite volume Methods for two-dimensional problems

2D diffusion equation.
Python implementation on 2D Diffusion equation and insights.
Fluid flow in 2D- Stream Function-Vorticity Approach.
Implementing Lid driven cavity flow problem using Python.
Visualization & Insights.

Prerequisites and eligibility:

No coding experience in any programming language required. We’ll start from scratch.
This course can be taken up by any undergraduate/postgraduate student of Basic & Applied Sciences, Engineering, Management and Computer Applications and also by Research Scholars/Faculties/Working Professionals who want to upskill themselves.
Participants need to have a laptop/PC (with a minimum of 4 GB RAM, 100 GB HDD, Intel i3 processor) and proper internet/Wi-Fi connection.

Contact Person: Dr. Subrat Kotoky

Email: [email protected] / [email protected]

Phone: 9085317465 / 8473874389

Expert Profile:

Dr. Manash Pratim Borthakur

Ph.D. in Mechanical Engineering (IIT Guwahati).
Worked in prestigious global institutions, like, KTH Royal Institute of Technology, Sweden and National Research Council, Italy.
CFD consultant for an Italian R&D firm Medlea S.r.l.s.
Expert in computational engineering and numerical methods for diverse fluid dynamics configurations.
Research & Teaching Experience: 5+ Years

Dr. Chaitanya Vundru

Ph.D. in Mechanical Engineering, IIT Bombay-Monash University.
Worked in General Electric.
Expert in Nonlinear Finite Element Analysis (FEA) with strong integration of programming and advanced manufacturing research.
Vast experience in Python, C/C++, and FORTRAN with teaching excellence in FEM, mentoring students in computational modelling and simulation-based design.

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