Inverse methods in computational modeling of welding processes

该项目的目标是继续开发先进的工程工具，将优化理论与工业焊接中复杂、多物理过程的数学和计算建模的最新进展相结合。我们将应用并进一步阐述在早期项目中取得的进展。特别是，我们打算开发一套改进的计算工具，使研究工程师能够(i)为金属惰性气体（MIG）焊接工艺创建最佳的输入工艺参数时间表（速度，电流，功率等）；这些时间表还将确保最小的热输入，从而最小的材料变形，（ii）根据实验测量对模型的某些未知参数（例如，依赖于溶液的材料属性）进行估计；材料属性的实际值通常难以获得，因此适当地进行参数估计可能会提高计算建模的保真度。这个跨学科的研究项目将由麦克马斯特大学的Protas博士小组和加拿大通用汽车公司（GM）共同进行，前者将带来数学和计算方面的专业知识，后者将提供工程方面的专业知识。我们还将与澳大利亚联邦科学与工业研究组织（CSIRO）的物理学家密切互动，他们将在一个相关问题上与通用汽车合作。在项目过程中，我们将为一名研究生和一名博士后提供跨学科的培训，包括应用和计算数学以及物理和应用工程科学的元素，这些研究生和博士后将被招募到这个项目中全职工作。该项目的成果可能具有改善制造业各个部门使用的连接技术的一般效果，因此可能对加拿大经济产生积极影响。例如，在这个项目中开发的优化方法可以被通用汽车公司用于改进其在安大略省奥沙瓦的通用汽车工厂组装的车辆的连接技术。这个项目也将为普罗塔斯博士的团队在学术研究的前沿做出贡献创造机会。

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.