Postdoctoral Appointee – Gas Turbine Modeling

The Multi-Physics Computations group at Argonne National Laboratory is seeking to hire a postdoctoral appointee for performing multi-physics and multi-scale CFD simulations of gas turbine engines. The candidate will be a part of the Transportation and Power Systems Division within the Advanced Energy Technologies Directorate at Argonne. The successful candidate’s research will involve collaborations with a multidisciplinary team involving computational fluid dynamics experts, gas turbine modelers and experimentalists to enhance the predictive capability of gas turbine modeling codes for stationary power generation and propulsion applications.

The candidate will perform multi-fidelity CFD simulations of gas turbines using alternate fuels including hydrogen and hydrogen carriers by further developing in-house and commercial codes, leveraging high-performance computing (HPC) and develop Reduced-Order Models for predicting rare events such as flame flashback, and blow out.

• Perform high-fidelity simulations of gas turbine combustors with gaseous fuels for stationary power generation applications. Focus on de-carbonization of this sector via the use of Carbon-less and low-Carbon fuels.

• Develop machine learning based reduced-order models for predicting rare events including flame flashback.

• Work as a part of a multidisciplinary team involving experimentalists, Computational Fluid Dynamics (CFD) experts and computational scientists to run the simulations using the next generation supercomputing architectures.

• Present and publish results in peer reviewed society technical reports, journal articles, and meetings with key stakeholders.

Position Requirements

• Ph.D. in Mechanical/Aerospace engineering, chemical engineering, applied mathematics, or a related discipline and should be 0 – 3 years post Ph.D.

• Knowledge of gas turbine combustion theory of operation.

• Knowledge of liquid and gaseous fuels for gas turbine applications.

• Experience in the use of ML softwares (TensorFlow, PyTorch, Julia, etc.) for reduced-order modeling and simulations, CFD, management and analysis of big data, and parallel scientific computing.

• Ability to collaborate and work well with other divisions, laboratories, universities, and industry.

• Skilled verbal and written communication skills at all levels of the organization.

• A successful candidate must have the ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. 

Preferred Qualifications:

• Understanding of turbulence, chemical kinetics, reacting flow physics, and combustion modeling.

• Experience in simulation of turbulent reacting flows in gas turbine combustors using CFD codes (e.g., CONVERGE, OpenFOAM, CharLES etc.).

• Experience with high-order CFD methods and solvers.

Job Family

Postdoctoral Family

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

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