Omar M Knio

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
  • 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.

Specialties

Computational Mechanics
Fluid Mechanics
Acoustics

Representative Publications

  • Ahmed, A; Hantouche, M; Khurshid, M; Mohamed, SY; Nasir, EF; Farooq, A; Roberts, WL; Knio, OM; Sarathy, SM, Impact of thermodynamic properties and heat loss on ignition of transportation fuels in rapid compression machines, Fuel, vol 218 (2018), pp. 203-212 [10.1016/j.fuel.2018.01.030] [abs].
  • Kumar Jain, P; Mandli, K; Hoteit, I; Knio, O; Dawson, C, Dynamically adaptive data-driven simulation of extreme hydrological flows, Ocean Modelling (2018) [10.1016/j.ocemod.2017.12.004] [abs].
  • Saad, BM; Alexanderian, A; Prudhomme, S; Knio, OM, Probabilistic modeling and global sensitivity analysis for CO 2 storage in geological formations: a spectral approach, Applied Mathematical Modelling, vol 53 (2018), pp. 584-601 [10.1016/j.apm.2017.09.016] [abs].
  • Vohra, M; Huan, X; Weihs, TP; Knio, OM, Design analysis for optimal calibration of diffusivity in reactive multilayers, Combustion Theory & Modelling, vol 21 no. 6 (2017), pp. 1023-1049 [10.1080/13647830.2017.1329938] [abs].
  • Kim, D; El Gharamti, I; Hantouche, M; Elwardany, AE; Farooq, A; Bisetti, F; Knio, O, A hierarchical method for Bayesian inference of rate parameters from shock tube data: Application to the study of the reaction of hydroxyl with 2-methylfuran, Combustion and Flame, vol 184 (2017), pp. 55-67 [10.1016/j.combustflame.2017.06.002] [abs].