Advanced Finite Element Simulations Using Abaqus

• Create advanced finite element models in Abaqus
• Apply theoretical concepts to analyze finite element simulations
• Apply the effects of nonlinear material models and evaluate the results
• Create models consisting of orthotropic materials and analyse its influence
• Create models discretizing fiber composite structures and analyse the layups and critical ply stresses and strains based on first and last ply failure criteria
• Create and evaluate crack tips models and analyse their prediction accuracy.
• Create crack growth using models cohesive material laws in a finite element model and evaluate the impact of different modelling parameters
• Create Python scripts and apply these for pre- and post-processing steps
• Apply AI-tools (Large-Language Models e.g. like ChatGPT/CoPilot) to generate scripts and input files in order to interact with Abaqus and to evaluate/post-process results.
• Create simple user-defined subroutines in Abaqus
• Understand the navigation in Abaqus’ User Manual and apply your knowledge to find relevant information.
• Analyse and evaluate critically finite elements simulations (plausible check, physical meaningful, mesh convergence study, comparison with tests/analytical results).

The workload in the course will focus on studying a range of nonlinear problems, including formulating, solving, and evaluating solutions for realistic finite element problems. Throughout the finite element exercises, key aspects of using a commercial finite element code will be addressed. Cases involving isotropic elastic, anisotropic elastic, and elastic-plastic material laws will be analyzed. Additionally, user-defined subroutines and Python scripting will be utilized.

• 6 – 20 (Thurs 13-17)

41501/41502/41812/41525/41526, or other courses covering strength of materials and an introduction to the finite element method or other courses covering composite materials and fracture mechanics

The course is structured as a problem-based, problem-solving learning experience. This means that the knowledge gained from lectures and tutorials must be transferred and applied to similar examples to solve given problems. The emphasis is on deep understanding and conclusive post-processing, where analytical solutions and experimental results are often compared and discussed.