Mr. Nathan See is a Research Staff Member in the Thermal Hydraulics group under the Nuclear Energy and Fuel Cycle Division at the Oak Ridge National Laboratory. He received his BS (2006) in aerospace engineering from Iowa State University and did masters level work at Syracuse University in Aerospace Engineering (2007-2008). Prior to joining ORNL, he spent 13 years in industry focusing on coupling CFD and physical testing, including wind tunnel and on-track testing; and everything from supersonic business jets to ballistics, and ground vehicles to race cars. Nathan is highly experienced in large scale HPC computing, utilizing some of the fastest machines over the last decade (Jaguar, JaguarPF, Kraken, EOS, Titan, and Summit).
At ORNL, Nathan’s focus is on large complicated geometries for HPC utilization and impactful research utilizing design optimization. This includes the Transformational Challenge Reactor (TCR), where work is being done to leverage the advancements in additive manufacturing to 3D-print a next-generation nuclear reactor; and projects within the Consortium for Advanced Simulation of Light Water Reactors (CASL).
Technical Skills
- Experienced CFD professional with specific focus on leveraging design optimization and advanced multi-physics software and technology for high-fidelity modeling and simulation of nuclear, aerospace and ground vehicle systems.
- Expert in industry leading computational fluid dynamics technologies including Siemens’ STAR-CCM+, Siemens’ HEEDS, NASA’s FUN3D, Pointwise, and TecPlot360.
- Expert in large scale HPC computing and resource management.
- Expert in experimental test design, setup, and execution along with test facility management.
- Expert in coupling computational and physical testing programs.
- Experience with other engineering tools and packages, including SolidWorks, SpaceClaim, FORTRAN90/95, bash scripting, python, Scilab, NASA’s USM3D, Mississippi State’s Solidmesh/ALFR3, NASA’s TetrUSS.
Publications
News
October 26, 2023
3 MIN READ
ORNL projects receive $8M from DOE Technology Commercialization Fund in FY23