PITA Fiscal Year 2009 Projects - Product and Process Design and Optimization

Efficient simulation strategies for strongly nonlinear coupled thermal-structural phenomena

Principal Investigators: Amit Acharya

Robust computational techniques tailored for coupled thermal-structural applications are essential to effective integration in industrial environments. At present, computational resources for models describing coupled phenomena often limit their use and effectiveness in engineering practice. This work will seek to develop a technique to address these limitations and focus on a reduction in solution time. Emerging considerations in industries impacted by coupled field solutions are motivating engineers to improve the current simulation technology. Specifically, industries involving weld-based fabrication methods would benefit significantly from efficient transient coupled thermal-structural algorithms. These industries include nuclear power generation, automotive, civil structures and naval shipbuilding. A primary concern of welding engineers is the impact of weld artifacts on product quality and service life. Issues such as distortional control and fatigue life are prime candidates for predictive simulation tools. However, current algorithm limitations present barriers to effective integration of these techniques into practical design and analysis environments. Engineers are looking to simulate the relevant coupled-field physics within a timeframe compatible with product development cycles. To this end, theory for adaptive hybrid time-stepping schemes for highly non-linear strongly coupled problems, like thermo-elastoplasticity, will be considered, based on a combination of fully implicit monolithic schemes and schemes based on the method of fractional steps. Such hybrid schemes are expected to maintain the balance between accuracy and computational efficiency. Strategies developed in this work will be leveraged by efforts to develop comprehensive computational tools for coupled thermalstructural applications.