We were honored to have Deepak Kumar from Oak Ridge National Laboratory present at the SIMULIA Americas Users Conference, May 3-4, 2023 in Novi, Michigan.
Abstract: The development of virtual models that accurately captures underlying physics across multiple scales and physical phenomena are of increasing interest to evaluate and improve end-to-end industrial processes. In this work, the capabilities of SIMULIA for a variety of industrial processes such as simulating novel manufacturing techniques, designing automotive components and large-scale molds, and analyzing deployable space structures are illustrated. SIMULIA’s capability to accurately predict the 8 deformations and mechanical responses in nonlinear regime for static and dynamic loadings is illustrated through design of polymer composite lattice structures and an automotive bumper, including experimental validations. The Abaqus ability of topology optimization through Tosca and simulating multibody structural assemblies are illustrated by designing door armrest and automotive seatback frame. The use of Python scripting within SIMULIA to automate all sort of tasks allows creation of workflows for analyzing large parametric design domains. Such a capability is demonstrated through the analysis and design of novel bistable mechanical metamaterials for deployable space structures. In addition, the predictive capability of Additive Manufacturing Modeler plug-in for thermomechanical process simulations is illustrated through an experimental validation via a large-scale material extrusion additive manufacturing of composite parts. Overall, SIMULIA enables multidisciplinary-multiscale simulations for end-to-end industry processes as summarized through various applications.
Bio: Dr. Deepak Pokkalla is a postdoctoral research associate in applied mechanics, composites manufacturing, and machine learning at the Oak Ridge National Laboratory. Dr. Deepak holds a Ph.D. in Applied Mechanics from National University of Singapore (NUS) and a bachelor’s degree in Civil Engineering from Indian Institute of Technology (IIT), Varanasi. Prior to joining Oak Ridge, he worked on deployable multi-stable mechanical metamaterials as a postdoctoral researcher at McGill University. His expertise is in employing finite element methods, structural optimization, and machine learning techniques to design novel material systems and manufacturing processes. He is currently working on accelerating design and manufacturing of automotive composite parts through simulations and machine learning. Dr. Deepak published several papers in peer-reviewed journals and received several accolades including 'Best Paper Award' from Engineering Mechanics.
