Perform high-fidelity Computational Fluid Dynamics (CFD) simulations of Internal Combustion Engine (ICE) and Gas Turbine Engine flows using spectral element method (SEM). Develop tools to generate SEM grids for complex, moving domains in a seamless fashion. Implement submodels for turbulence, heat transfer, two-phase flow, ignition, and combustion into SEM codes. Perform scalability studies and port these simulations on leadership class supercomputing resources, identify and improve the bottlenecks in scaling the simulations.
The successful candidate’s research will involve synergetic collaborations with a multi-disciplinary team involving engine modelers and experimentalists, and computational scientists to enhance the predictive capability for next-generation engine modeling code.
Ph.D. in mechanical/aerospace engineering, applied mathematics, chemical engineering, or a related discipline.
Experience with Nek5000, NekRS or other comparable spectral element method codes is required.
Experience in running high-fidelity simulations on leadership class supercomputers is required.
Understanding of high-order methods for fluid flows is required.
Experience in performing simulations on hybrid computing architectures is desirable.
Knowledge of large scientific code management and optimization is desirable.
Knowledge of performing scalability studies to identify and improve bottlenecks in large codes is desirable.
Collaborative skills, including the ability to work well with other divisions, laboratories, and universities.
Good communication skills at all levels of the organization.
Experience in two-phase flow applications, turbulence modeling, combustion modeling, internal combustion/gas turbine engine theory and operation is desirable.
A successful candidate must have the ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
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