Larsson, Johan | A. James Clark School of Engineering, University of Maryland

Faculty Directory

Larsson, Johan

Larsson, Johan

Associate Professor
Member, Applied Mathematics & Statistics, and Scientific Computation
Mechanical Engineering
3149 Glenn L. Martin Hall
Website(s):

EDUCATION

  • PhD, University of Waterloo, Canada  (2006)
  • MSc, Chalmers University of Technology, Sweden  (2002)
  • BSc, Lund Institute of Technology, Sweden  (1999)

HONORS AND AWARDS

  • E. Robert Kent Outstanding Teaching Award for Junior Faculty  (2019)
  • NSF CAREER Award  (2015)
  • Best MSc Thesis in the ME Department  (2015; to student Andrew Trettel)

PROFESSIONAL MEMBERSHIPS

  • American Physical Society
  • American Institute for Aeronautics and Astronautics
  • Associate Editor for AIAA Journal  (2017-2020)

 

Dr. Larsson has broad interests within the fields of fluid mechanics, turbulence, combustion and predictive computational science. His interests range from the very fundamental to the rather applied: his ideal research question is one which solves a highly applied problem through a rigorous and creative fundamental approach. Large-scale simulations on thousands of processors are an important tool in this research, enabling detailed turbulence simulations or quantification of simulation uncertainties. Current project topics include: enabling large eddy simulation to be applied at realistic (high) Reynolds numbers through approximate wall-modeling; developing grid-adaptation techniques for turbulence simulations; developing models for transcritical combustion; and developing physics-based uncertainty quantification approaches for complex multi-physics systems.

Burgers Program Features Topics in Turbulence

Graduate students from 30 universities and 7 countries come to College Park.

UMD Hosts the Premier Combustion Science Meeting in the U.S.

A record number of attendees made the 2017 meeting the most successful in its history.

Larsson Receives NSF CAREER Award

Larsson targets turbulent flows to improve future modeling capabilities.