Omar M Knio

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
  • Adjunct Professor in the Department of Mechanical Engineering and Materials Science

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

Research Interests

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.

Representative Publications

  • Attada, R; Dasari, HP; Chowdary, JS; Yadav, RK; Knio, O; Hoteit, I, Surface air temperature variability over the Arabian Peninsula and its links to circulation patterns, International Journal of Climatology, vol 39 no. 1 (2019), pp. 445-464 [10.1002/joc.5821] [abs].
  • Attada, R; Dasari, HP; Chowdary, JS; Yadav, RK; Knio, O; Hoteit, I, Surface air temperature variability over the Arabian Peninsula and its links to circulation patterns, International Journal of Climatology, vol 39 no. 1 (2019), pp. 445-464 [10.1002/joc.5821] [abs].
  • Wang, T; Lima, RM; Giraldi, L; Knio, OM, Trajectory planning for autonomous underwater vehicles in the presence of obstacles and a nonlinear flow field using mixed integer nonlinear programming, Computers & Operations Research, vol 101 (2019), pp. 55-75 [10.1016/j.cor.2018.08.008] [abs].
  • Navarro, M; Le MaĆ®tre, OP; Hoteit, I; George, DL; Mandli, KT; Knio, OM, Surrogate-based parameter inference in debris flow model, Computational Geosciences, vol 22 no. 6 (2018), pp. 1447-1463 [10.1007/s10596-018-9765-1] [abs].
  • Mohtar, SE; Hoteit, I; Knio, O; Issa, L; Lakkis, I, Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea, Ocean Modelling, vol 131 (2018), pp. 1-14 [10.1016/j.ocemod.2018.08.008] [abs].