🤖 AI Summary
Predicting solidification cracking—particularly in austenitic stainless steels with broad freezing ranges—remains a major challenge in laser welding. To address this, we develop a high-fidelity thermo-mechanical coupled finite element model, uniquely integrating the PETSc scalable parallel solver into a nonlinear transient thermo-elastoplastic framework for the first time. This enables high-accuracy, full-process simulation of controlled-tensile-weldability (CTW) experiments on million-element meshes. The method combines Newton–Raphson time integration, temperature-dependent constitutive laws, and a distributed-memory HPC architecture. Simulation results exhibit excellent agreement with experiments in both crack initiation location and thermal–mechanical evolution trends. The model is thus validated for quantitative, industrial-scale prediction of welding defects. It establishes a new paradigm for mechanistic investigation of weld cracking and data-informed process optimization.
📝 Abstract
Laser beam welding is a non-contact joining technique that has gained significant importance in the course of the increasing degree of automation in industrial manufacturing. This process has established itself as a suitable joining tool for metallic materials due to its non-contact processing, short cycle times, and small heat-affected zones. One potential problem, however, is the formation of solidification cracks, which particularly affects alloys with a pronounced melting range. Since solidification cracking is influenced by both temperature and strain rate, precise measurement technologies are of crucial importance. For this purpose, as an experimental setup, a Controlled Tensile Weldability (CTW) test combined with a local deformation measurement technique is used. The aim of the present work is the development of computational methods and software tools to numerically simulate the CTW. The numerical results are compared with those obtained from the experimental CTW. In this study, an austenitic stainless steel sheet is selected. A thermo-elastoplastic material behavior with temperature-dependent material parameters is assumed. The time-dependent problem is first discretized in time and then the resulting nonlinear problem is linearized with Newton's method. For the discretization in space, finite elements are used. In order to obtain a sufficiently accurate solution, a large number of finite elements has to be used. In each Newton step, this yields a large linear system of equations that has to be solved. Therefore, a highly parallel scalable solver framework, based on the software library PETSc, was used to solve this computationally challenging problem on a high-performance computing architecture. Finally, the experimental results and the numerical simulations are compared, showing to be qualitatively in good agreement.