Postdoctoral Appointee - Gas Turbine Modeling

Argonne National Laboratory

Lemont, IL

Job posting number: #7085366

Posted: September 15, 2021

Application Deadline: Open Until Filled

Job Description

Perform Multi-Physics and Multi-Scale simulations for gas turbines by further developing in-house and commercial codes, leveraging high-performance computing (HPC). Develop Machine Learning (ML) based frameworks for developing surrogate models and reduced-order modeling of gas turbines.

The successful candidate’s research will involve synergetic collaborations with a multidisciplinary team involving computational fluid dynamics experts, gas turbine modelers and experimentalists, and computational scientists to enhance the predictive capability of gas turbine modeling codes for aviation and stationary power generation applications.

Job Description:

Perform high-fidelity simulations of gas turbine combustors with liquid fuels for propulsion applications. Focus on improving simulation capabilities for sustainable aviation fuels.

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 (ML) frameworks for multi-objective surrogate model development for gas turbine systems using high performance computing (HPC) tools.

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 and journal articles.

Position Requirements:

Candidates should have a Ph.D. in Mechanical/Aerospace engineering, chemical engineering, applied mathematics, or a related discipline.

Knowledge of gas turbine combustion theory of operation. Extensive knowledge of liquid and gaseous fuels for gas turbine applications. Good understanding of turbulence, chemical kinetics, reacting flow physics, and combustion modeling is desired.

Experience in simulation of turbulent reacting flows in gas turbine combustors using CFD codes (e.g., CONVERGE, OpenFOAM, etc.) is desired. Experience with high-order CFD methods and solvers is a plus.

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.

Strong 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.

Position Requirements

Candidates should have a Ph.D. in Mechanical/Aerospace engineering, chemical engineering, applied mathematics, or a related discipline.

Knowledge of gas turbine combustion theory of operation. Extensive knowledge of liquid and gaseous fuels for gas turbine applications. Good understanding of turbulence, chemical kinetics, reacting flow physics, and combustion modeling is desired.

Experience in simulation of turbulent reacting flows in gas turbine combustors using CFD codes (e.g., CONVERGE, OpenFOAM, etc.) is desired. Experience with high-order CFD methods and solvers is a plus.

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.

Strong 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.

Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.


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