Introduction

In modern engineering, computational heat transfer plays a crucial role in optimizing thermal management across industries such as aerospace, automotive, energy systems, manufacturing, and electronics. This course provides a deep dive into numerical techniques for solving heat transfer problems, with a strong emphasis on finite difference methods (FDM), finite element methods (FEM), and computational fluid dynamics (CFD). Participants will gain hands-on experience in simulating conduction, convection, radiation, and phase-change heat transfer using advanced software tools.

Objectives

By the end of this course, participants will:

1. Understand the fundamentals of heat transfer and its computational modeling approaches.
2. Learn to apply finite difference (FDM), finite element (FEM), and finite volume (FVM) methods for numerical solutions.
3. Develop skills in discretizing partial differential equations (PDEs) for thermal problems.
4. Use Computational Fluid Dynamics (CFD) software (such as ANSYS Fluent, OpenFOAM, or COMSOL) for heat transfer simulations.
5. Analyze steady-state and transient heat conduction in complex geometries.
6. Model convective heat transfer in fluid flows, including turbulence and multi-phase interactions.
7. Understand radiative heat transfer and its impact on thermal system design.
8. Gain hands-on experience in simulating heat exchangers, cooling systems, and thermal energy storage.
9. Explore advanced topics such as nanofluids, micro-scale heat transfer, and AI-assisted thermal simulations.

Who Should Attend?

This course is designed for:

• Mechanical, Aerospace, and Automotive Engineers working on thermal system design.
• Energy and Power Engineers focusing on heat exchangers, renewable energy systems, and HVAC applications.
• Computational Scientists involved in CFD simulations for thermal engineering.
• R&D Engineers working on thermal optimization in electronics, combustion, and material processing.
• Graduate Students & Researchers in heat transfer, fluid mechanics, and thermal management.

Course Outline

Day 1: Fundamentals of Heat Transfer and Computational Methods

• Morning Session:

  1. Introduction to Heat Transfer Mechanisms: Conduction, convection, and radiation.
  2. Mathematical Formulation of Heat Transfer Problems: Governing equations and boundary conditions.
  3. Introduction to Computational Methods: Overview of FDM, FEM, and FVM approaches.
  4. Discretization of Heat Transfer Equations: Stability, accuracy, and numerical errors.

• Afternoon Session:

  1. Finite Difference Methods (FDM) for Heat Conduction: Explicit and implicit schemes.
  2. Hands-on Exercise: Writing Python/Matlab code for solving 1D heat conduction.
  3. Introduction to CFD for Heat Transfer Problems: Basic concepts and workflow.
  4. Software Setup and Interface Walkthrough: Overview of ANSYS Fluent/OpenFOAM/COMSOL.

Day 2: Conduction Heat Transfer Modeling

• Morning Session:

  1. Steady-State and Transient Heat Conduction: 1D, 2D, and 3D problems.
  2. Handling Complex Geometries in FEM and FVM: Mesh generation strategies.
  3. Multi-Layered and Composite Material Analysis: Thermal conductivity variations.

• Afternoon Session:

  1. Solving 2D and 3D Heat Conduction Problems in CFD Software.
  2. Practical Case Study: Heat conduction in a heat sink.
  3. Error Analysis and Convergence Criteria in Numerical Simulations.
  4. Hands-on Exercise: Model validation against analytical solutions.

Day 3: Convective Heat Transfer and CFD Modeling

• Morning Session:

  1. Forced and Natural Convection: Governing equations and boundary layer theory.
  2. Turbulence Modeling in Heat Transfer Problems: RANS, LES, and DNS methods.
  3. Mesh Dependence and Grid Refinement for Accurate Solutions.
  4. Coupling Heat Transfer with Fluid Flow in CFD Simulations.

• Afternoon Session:

  1. Software Demonstration: Solving a convective heat transfer problem in CFD.
  2. Hands-on Simulation: Cooling of an electronic component using forced convection.
  3. Optimization of Heat Transfer Coefficients in Practical Applications.
  4. Error Reduction and Mesh Adaptation Techniques.

Day 4: Radiative Heat Transfer and Advanced Applications

• Morning Session:

  1. Radiation Heat Transfer Principles: Blackbody radiation, view factors, and emissivity.
  2. Modeling Radiation in Complex Systems: Surface-to-surface and participating media.
  3. Radiation in High-Temperature Applications: Aerospace and combustion simulations.

• Afternoon Session:

  1. Simulating Radiative Heat Transfer in CFD Software.
  2. Practical Case Study: Radiation heat loss in a solar thermal collector.
  3. Multiphysics Simulations: Coupling conduction, convection, and radiation.
  4. Hands-on Exercise: Implementing a radiation model in CFD.

Day 5: Special Topics and Industry Applications

• Morning Session:

  1. Phase Change Heat Transfer: Boiling, condensation, and melting phenomena.
  2. Heat Exchanger Simulation and Optimization: Shell-and-tube, plate, and compact designs.
  3. Thermal Management in Electronics and Battery Cooling.
  4. Nanofluids and Micro-Scale Heat Transfer: Emerging trends and applications.

• Afternoon Session:

  1. AI and Machine Learning in Heat Transfer Modeling.
  2. Case Study on Thermal Optimization in an Automotive Engine Cooling System.
  3. Final Project and Review of Simulation Techniques.
  4. Assessment and Certification Ceremony.

Certification

Upon successful completion of the course, participants will receive a Certificate of Completion in Computational Heat Transfer. This certification demonstrates expertise in using numerical methods and CFD tools for solving complex heat transfer problems across various industries.

Key Benefits of the Course:

✔ Hands-on training with industry-standard CFD software.
✔ Exposure to cutting-edge techniques in thermal modeling and simulation.
✔ Practical case studies from automotive, aerospace, and renewable energy sectors.
✔ Expert guidance from experienced professionals in heat transfer modeling.