Curriculum
- 4 Sections
- 26 Lessons
- 3 Days
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- Fundamentals of FEA and Its Applications in Railway Equipment9
- 1.1Fundamentals: Basic principles, equations, and numerical modeling.
- 1.2Key concepts: Meshing, boundary conditions, material properties, and element types.
- 1.3Advantages of FEA in engineering design and structural analysis.
- 1.4Role of FEA in designing bogies, axles, couplers, and other railway components.
- 1.5Ensuring compliance with international standards (EN 13749, UIC codes).
- 1.6Identifying and mitigating fatigue and stress concentrations in railway systems.
- 1.7Case Study: Using FEA for crash simulations and safety analysis in rolling stock.
- 1.8Case Study: Optimizing component weight and strength for cost efficiency.
- 1.9Hands-on session: Setting up a basic FEA model for a railway component using industry-standard software (e.g., ANSYS, Abaqus).
- Advanced FEA Techniques and Problem-Solving9
- 2.1Non-linear analysis: Material and geometric non-linearity.
- 2.2Modal analysis: Vibration modes and frequency response for railway systems.
- 2.3Dynamic analysis: Simulating transient and impact scenarios.
- 2.4Addressing common issues: Poor convergence, inaccurate results, and mesh dependency.
- 2.5Strategies for optimizing mesh quality and solver performance.
- 2.6Managing large assemblies and multi-body simulations.
- 2.7Case study: Failure analysis of railway components under cyclic loading.
- 2.8Discussion: Reducing noise and vibration in high-speed rail systems.
- 2.9Interactive activity: Simulating and interpreting results for a critical railway component under load conditions.
- Validation, Optimization, and Emerging Trends7
- 3.1Techniques for validating FEA results against experimental data.
- 3.2Ensuring accuracy through sensitivity analysis and error estimation.
- 3.3Design optimization: Minimizing weight while maintaining performance.
- 3.4Simulation-driven design: Iterative improvement of railway equipment.
- 3.5Integration of FEA with machine learning and artificial intelligence.
- 3.6Use of cloud computing and high-performance computing (HPC) for large-scale simulations.
- 3.7Advanced materials modeling (e.g., composites and lightweight alloys).
- Capstone Project: Real-Life Simulation1