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Building a Credible, Open-source High-fidelity Computational Fluid Dynamics Tool Suitable for Renewable Wave Energy Applications

Event Type: 
Date and Time: 
Friday, December 2, 2022 - 16:15
Building 300 Room 300
Event Sponsor: 
Parviz Moin, Director of Center for Turbulence Research
Dr. Stefan P. Domino, Computational Thermal & Fluid Mechanics Department, Sandia National Laboratory; Institute for Computational & Mathematical Engineering, Stanford

In this presentation, an unstructured, low-Mach, balanced-force, volume of fluid numerical methodology is overviewed whose prime objective is to target the modeling of wave-based renewable energy devices using high-fidelity computational fluid dynamics approaches. A control volume finite element numerical discretization, which includes novel residual-based stabilization for the volume of fluid equation, is established. Although WEC mod/sim requirements lack typical multiphysics complexities, other technical challenges exist, such as ensuring non-diffusive fluid transport in the presence of mesh modification and modeling floating devices that are free to move in a non-prescribed trajectory. The presentation outlines three critical components of a WEC mod/sim tool including 1) stable and accurate unstructured low-Mach fluid mechanics discretizations, 2) low-dissipation volume of fluid transport in the presence of PDE-based sharpening, and 3) mesh motion methodologies that encompass mesh deformation, sliding mesh, and overset approaches. Credibility of this numerical approach is established in the open-source Nalu simulation tool by deploying a code verification and model validation hierarchy across the intersection of the three critical components. A formal buoy validation case, with and without mooring, is presented, in addition to validation benchmark cases that reside in the high-displacement regime. These validation cases showcase an implicit overset unstructured mesh construct that allows a wave energy converter (WEC) geometry to freely move about a background domain, thereby establishing the efficacy of the approach in this challenging multiphase flow application.


Dr. Stefan Domino’s research interest rests within low-Mach fluid mechanics methods development for complex systems that drive the coupling of mass, momentum, species and energy transport. His core research resides within the intersection of physics model development, numerical methods research, V&V techniques exploration, and high-performance computing and coding methods for low-Mach turbulent flow applications. In support of his Adjunct Professor appointment within the Institute for Computational and Mathematical Engineering, Stefan also supports the co-teaching of ME469, Computational Methods in Fluid Mechanics, while continuing his primary career at Sandia National Laboratories (NM) as a Distinguished Member of the Technical Staff. Stefan earned his Ph.D. in Chemical Engineering (2000) from the University of Utah, where he also supported the technical objectives of the ASCI Alliance Center, C-SAFE, under his advisor, Professor Philip Smith. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525