Suleyman Yasayanlar

Principal Interests: • Finite Element Analysis (FEA) • Solid Mechanics • Material Damage Modeling • Implicit & Explicit FEA • Computational Mechanics • Material Characterization • Deep Neural Network Models • Abaqus • HyperMesh • HyperWorks • Generating automation scripts for FEA packages. Abaqus Material Modeling, Abaqus Element Modelling • Evaluating linear, non-linear, implicit, or explicit analyses in Abaqus. • Contact Modeling, • Topology optimization. • Implementing User Materials (UMAT and VUMAT) subroutines to Abaqus. • Implementing mesh-independent solution algorithms into Abaqus through User Elements (UEL). • Modeling micro-mechanics-based problems using Python scripting interface. • Creating Python scripts to create models, post-process models, and creating analysis reports. • Combining Machine Learning frameworks (such as Keras, Tensorflow, PyTorch, etc.) and Abaqus to evaluate data-driven analysis. Machine Learning & Artificial Intelligence: • Creating data input pipelines, cleaning data for Deep Neural Network Models, • Creating Custom Deep Neural Network Models and fine-tuning model hyperparameters. • Combining Machine Learning Frameworks with Finite Element solution algorithms. Hence evaluate data-driven analysis