Inverse methods in computational modeling of welding processes

点击翻译按钮获取中文摘要

The goal of this project is to continue the development of advanced engineering tools integrating the Optimization Theory with recent progress in mathematical and computational modeling of complex, multi-physics processes involved in industrial welding. We will apply and further elaborate the advances made during an earlier project. In particular, we intend to develop an improved suite of computational tools that will allow research engineers to (i) create optimal input process parameter schedules (speed, current, power, etc.) for the Metal Inert Gas (MIG) welding process; these schedules will also ensure minimal heat input and, consequently, minimal material distortion, (ii) perform estimation of certain unknown parameters of the model (e.g., solution-dependent material properties) based on experimental measurements; actual values of material properties are often difficult to obtain, hence suitably performed parameter estimation will likely improve fidelity of computational modelling. This interdisciplinary research project will be carried out jointly by Dr. Protas' group at McMaster University, which will bring mathematical and computational expertise, and General Motors of Canada (GM) which will contribute engineering expertise. We will also closely interact with physicists from the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia who will be working with GM on a related problem. During the course of the project we will provide interdisciplinary training, involving elements of applied and computational mathematics as well as physics and applied engineering science, to a graduate student and a post-doctoral fellow to be recruited to work full-time on this project. The results of this project may have the generic effect of improving the joining technology used in various sectors of the manufacturing industry and may therefore exert a positive influence on the Canadian economy. For example, the optimization methodology developed in this project could be used by GM to improve the joining technology of its vehicles assembled at the GM plant in Oshawa, ON. This project will also create opportunities for Dr. Protas' group to make contributions at the forefront of academic research.