Omar Mohamad Knio

Image of Omar Mohamad Knio

Edmund T. Pratt Jr. School Professor of Mechanical Engineering and Materials Science

My research interests encompass computational fluid mechanics, oceanic and atmospheric flows, turbulent flow, physical acoustics, chemically-reactive flow, energetic materials, microfluidic devices, dynamical systems, numerical methods, and asymptotic and stochastic techniques.

Appointments and Affiliations
  • Edmund T. Pratt Jr. School Professor of Mechanical Engineering and Materials Science
  • Professor in the Department of Mechanical Engineering and Materials Science
  • Professor in the Department of Civil and Environmental Engineering
Contact Information:
  • Office Location: 144 Hudson Hall, Box 90300, Durham, NC 27708
  • Office Phone: (919) 660-5344
  • Email Address: omar.knio@duke.edu
Education:

  • Ph.D. Massachusetts Institute of Technology, 1990

Specialties:

Computational Mechanics
Fluid Mechanics
Acoustics

Awards, Honors, and Distinctions:

  • Associated Western Universities Faculty Fellowship Award, Associated Western Universities, June 1996
  • Distinguished Alumnus Award, American University of Beirut, May 2005
  • Friedrich Wilhelm Bessel Award, Humboldt Foundation, 2003
  • Penrose Award, American University of Beirut, July 1984
  • R&D 100 Award for "Nanofoil Product", R&D Magazine, 2005

Courses Taught:
  • ME 221L: Structure and Properties of Solids
  • ME 555: Advanced Topics in Mechanical Engineering

Representative Publications: (More Publications)
    • Sraj, I; Iskandarani, M; Thacker, WC; Srinivasan, A; Knio, OM, Drag Parameter Estimation Using Gradients and Hessian from a Polynomial Chaos Model Surrogate, Monthly Weather Review, vol 142 no. 2 (2014), pp. 933-941 [10.1175/MWR-D-13-00087.1] [abs].
    • Sraj, I; Specht, PE; Thadhani, NN; Weihs, TP; Knio, OM, Numerical simulation of shock initiation of Ni/Al multilayered composites, Journal of Applied Physics, vol 115 no. 2 (2014), pp. 023515-023515 [10.1063/1.4861402] [abs].
    • Alexanderian, A; Rizzi, F; Rathinam, M; Le Maître, OP; Knio, OM, Preconditioned Bayesian regression for stochastic chemical kinetics, Journal of Scientific Computing, vol 58 no. 3 (2014), pp. 592-626 [abs].
    • Rizzi, F; Jones, RE; Debusschere, BJ; Knio, OM, Uncertainty quantification in MD simulations of concentration driven ionic flow through a silica nanopore. II. Uncertain potential parameters., Journal of Chemical Physics, vol 138 no. 19 (2013) [10.1063/1.4804669] [abs].
    • Rizzi, F; Jones, RE; Debusschere, BJ; Knio, OM, Uncertainty quantification in MD simulations of concentration driven ionic flow through a silica nanopore. I. Sensitivity to physical parameters of the pore., Journal of Chemical Physics, vol 138 no. 19 (2013) [10.1063/1.4804666] [abs].