Abstract

Artificial intelligence is one of the most widely and extensively researched topics in the world today. In recent times , AI and machine learning are finding applications in several fields. This paper explores the application of artificial intelligence for pre and post processing , in crash simulations. Abstract: The focus of Artificial Intelligence in Computer Aided Engineering ( CAE ) has largely been on optimization , and prediction methods to replace traditional physics based approaches. While such applications provide a huge advantage with prediction time , they are not suitable for highly non linear behaviour observed in scenarios such as full car crash due to limitations with data , algorithms , computer infrastructure and most of all , since they do not utilize the existing knowledge of physics. Instead of applying Artificial Intelligence in solving , this study aims to improve efficiency by using Artificial Intelligence for pre - and post processing. This paper describes an AI based assistant that uses deep learning, natural language processing ( NLP ) and computer vision ( CV ) to assist with pre- and post processing in Finite Element simulations. In addition to saving the engineer's time on performing repetitive tasks and reducing manual errors , using such an assistant proved to leverage the simplicity of simple human natural language instead of having to train engineers on interfaces of different Computer Aided Engineering tools. Keywords: Artificial Intelligence , AI , Deep Learning , Machine Learning , ML , crash simulations , FEA , FEM , Finite Element , CAE, Computer Aided Engineering , Non linear FEM , Finite Element Method , NLP , Natural Language Processing , Simulation Assistant , Computer Aided Engineering , car crash, vehicle crash , intent classification , named entity recognition , NER , simulation support , preprocessing , postprocessing