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    Postdoctoral Appointee – Low-Carbon Fuel Sprays and Engine Combustion Modeling - Lemont, United States - Argonne National Laboratory

    Argonne National Laboratory
    Argonne National Laboratory Lemont, United States

    6 days ago

    Default job background
    Full time
    Description

    The Multiphysics Computation Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee. The successful candidate's research will involve synergistic collaborations with a multidisciplinary team comprised of fellow postdoctoral appointees and staff scientists with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with the goal to enhance predictive capability and scalability of multi-scale and multi-physics simulation codes.

    The prospective postdoctoral appointee will perform multi-physics and multi-scale CFD simulations of complex systems involving modeling of multi-phase flows, turbulent combustion, heat transfer, combustion, and emissions of low-carbon propulsion systems by further developing commercial/in-house codes and high-performance computing (HPC).

  • Develop accurate and computationally efficient CFD models to simulate the chain of physics and chemistry involved with fuel injection, fuel-air mixing, turbulent combustion, and emissions of propulsion systems.
  • Perform simulations of turbulent combustion in combustion engines involving fuel sprays, spray-wall interaction, fuel-air mixing, combustion, and emission modeling.
  • Perform high-fidelity reacting simulations that involve both conventional and low-carbon fuels, with emphasis on alcohol-based, bio-, and renewable fuels.
  • Improve the computational efficiency and accuracy of physics-based and data-driven models for liquid fuel injection and spray-wall interaction and integrate them in simulations of direct injection engines.
  • Work as a part of a multidisciplinary team involving experimentalists, CFD experts, and computational scientists to enable cutting-edge CFD modeling & simulations on the next generation supercomputing architectures.
  • Position Requirements

  • Ph.D. in mechanical/aerospace engineering, applied mathematics, chemical engineering, or a related discipline earned no more than three years ago is required.
  • Experience in modeling and simulation of three-dimensional multiphase turbulent reacting flow applications using 3-D CFD codes (e.g., CONVERGE, OpenFOAM, Ansys Fluent, etc.).
  • Excellent understanding of sprays, spray-wall interaction, turbulence, chemical kinetics, reacting flow physics, and turbulent combustion modeling.
  • Extensive knowledge of fuel properties and their effects on fluid behavior in reacting and non-reacting flow applications.
  • Understanding of combustion engine theory and modeling.
  • The candidate must demonstrate good collaborative skills, including the ability to work well with other divisions, laboratories, and universities.
  • Skilled in communication at all levels of the organization.
  • The successful candidate is expected to present and publish results in peer reviewed society technical reports and journal articles.
  • A successful candidate must have the ability to model Argonne's Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
  • Preferred Qualifications:

  • Knowledge of and experience with modeling alcohol-based, bio-, and renewable fuels.
  • Experience in geometry manipulation with computer-aided design software.
  • Experience with coupling CFD and FEA codes.
  • Knowledge of multi-dimensional code development (in C++/C/Fortran) for two-phase/multiphase flow and turbulent combustion applications, as well as parallel scientific computing.
  • Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and analysis of large datasets, and parallel scientific computing.
  • Experience in carrying out research tasks with industry partners.
  • Experience in interdisciplinary collaborative research.
  • Job Family

    Postdoctoral Family

    Job Profile

    Postdoctoral Appointee

    Worker Type

    Long-Term (Fixed Term)

    Time Type

    Full time


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