Pitt | Swanson Engineering
Senocak, Inanc
Mechanical Engineering & Materials Science
Senocak, Inanc
Associate Professor
Office: 636 Benedum Hall
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University of Florida, Gainesville, Aerospace Engineering, PhD, 2002                             

Middle East Technical University, Ankara, Turkey. Mechanical Engineering, BS, 1998

Computational fluid dynamics, wind forecasting, parallel computing, turbulence modeling, cavitating flows, and atmospheric dispersion.

  • National Science Foundation, CAREER Award, 2011
  • Postdoctoral Research Fellow, 2003, Center for Turbulence Research, Stanford University & NASA Ames Research Center

Book Chapter

  1. I. Senocak and H. Jin. “Chapter 16: Parallel Computing with Accelerators.” In F. Willmore, E. Jankowski, and C. Colina (Eds.), Introduction to Scientific and Technical Computing, Taylor and Francis, 2016.

Refereed Journal Articles

  1. J. Hasbestan, I. Senocak, “A short note on the use of the red-black tree in Cartesian adaptive mesh refinement algorithms,” J. Comput. Phys. 351, 473–477 (2017)
  2. C. Umphrey*, R. DeLeon*, I. Senocak, “Direct numerical simulation of turbulent katabatic slope flows with an immersed boundary method,” Boundary-layer Meteorol. 164, 367-382 (2017)
  3. T. Phillips*, R. DeLeon*, I. Senocak, “Dynamic rating of overhead transmission lines over complex terrain using a large-eddy simulation paradigm,” Renewable Energy, 108, 380-389 (2017)
  4. I. Senocak, M. Sandusky, R. DeLeon*, D. Wade, K. Felzien, and M. Budnikova, “An immersed boundary geometric preprocessor for arbitrarily complex terrain and geometry,” J. Atmos. Oceanic Technol. 32(11), 2075-2087 (2015)
  5. J. D. Eldredge, I. Senocak, P. Dawson, J. Canino, W. W. Liou, R. LeBeau, D. L. Hitt, M. P. Rumpfkeil, R. M. Cummings, “A best practices guide to CFD education in the undergraduate curriculum,” International Journal of Aerodynamics, 4 (3-4), 200-236 (2014)
  6. D. Wade and I. Senocak, “Stochastic reconstruction of atmospheric contaminant dispersion from multiple sources,” Atmospheric Environment, 74:45–51 (2013)
  7. F.P. Santos*, I. Senocak, J.L. Favero, and P.L.C. Lage “Solution of the population balance equation using parallel adaptive cubature on GPUs,” Computers and Chemical Engineering, 55:61-70 (2013)
  8. D. A. Jacobsen* and I. Senocak, “Multi-level parallelism for incompressible flow computations on GPU clusters,” Parallel Computing, 39: 1–20 (2013)
  9. R. Deleon*, D. A. Jacobsen* and I. Senocak, “Large-eddy simulations of turbulent incompressible flows on GPU clusters,” Computing in Science and Engineering, 15 (1): 26–33 (2013)
  10. J. Thibault*, I. Senocak, Accelerating incompressible flow computations with a Pthreads-CUDA implementation on small-footprint multi-GPU platforms, The Journal of Supercomputing, 59: 693-719 (2012)
  11. A. Gowardhan*, E. R. Pardyjak, I. Senocak, M.J. Brown, A CFD-based wind solver for an urban fast response transport and dispersion model, Environmental Fluid Mechanics, 11:439-464, (2011)
  12. I. Senocak, N. W. Hengartner, M. Short, B. Daniel, Stochastic event reconstruction of atmospheric contaminant dispersion using Bayesian inference, Atmospheric Environment, 42:7718–7727 (2008)
  13. I. Senocak, A. S. Ackerman, M. P. Kirkpatrick, D. E. Stevens, N. N. Mansour, Study of near-surface models in large-eddy simulations of neutrally stratified atmospheric boundary layer, Boundary Layer Meteorology, 124:405–424 (2007)
  14. I. Senocak, W. Shyy, S. T. Johansen, “Statistical characteristics of unsteady Reynolds-averaged Navier-Stokes computations,” Numerical Heat Transfer Part  B-Fundamentals, 47:1–18 (2005)
  15. I. Senocak, W. Shyy, Interfacial dynamics-based modeling of turbulent cavitating flows, Part-1: Model development and steady-state computations, International Journal of Numerical Methods in Fluids, 44:975–995, (2004)
  16. I. Senocak, W. Shyy, Interfacial dynamics-based modeling of turbulent cavitating flows, Part-2: Time-dependent computations, International Journal of Numerical Methods in Fluids, 44:997–1016 (2004)
  17. R. Vaidyanathan, I. Senocak, J. Wu, W. Shyy, Sensitivity evaluation of a transport-based turbulent cavitation model, Journal of Fluids Engineering, 125:447–458 (2003)
  18. J. Wu, I. Senocak, G. Wang, Y. Wu, and W. Shyy, Three-dimensional simulation of turbulent cavitating flows in a hollow-jet valve, Computer Modeling in Engineering and Sciences, 4:679–689 (2003)
  19. I. Senocak, W. Shyy, A pressure-based method for turbulent cavitating flow computations, Journal of Computational Physics, 176:363–383 (2002)
  20. G. Wang, I. Senocak, W. Shyy, T. Ikohagi. S. Cao, Dynamics of attached turbulent cavitating flows, Progress in Aerospace Sciences, 37:551–581 (2001)
  21. X. He, I. Senocak, W. Shyy, S. N. Gangadharan, S. Thakur, Evaluation of laminar-turbulent transition and equilibrium near wall turbulence models, Numerical Heat Transfer Part  A:Applications, 37:101–112 (2000)



  1. A Massively Parallel Computational Framework for Grid Integration of Wind Energy over Complex Terrain, Washington State University, Pullman, WA, April 21, 2016.
  2. Computational Methods for Forward and Inverse Modeling of Atmospheric Transport and Dispersion, National Weather Center Seminars and Colloquium, University of Oklahoma, Norman, OK, October 28, 2014
  3. Microscale modeling of winds over complex terrain using an immersed boundary method on GPU clusters, Workshop on Microscale Modeling of Complex Terrain Flows, University of Notre Dame, September 25, 2014
  4. Accelerating Wind Simulations over Arbitrarily Complex Terrain using a GPU computing paradigm, 6th International Symposium on Computational Wind Engineering, Hamburg, Germany, June 11, 2014. (Keynote Lecture)
  5. GPU-accelerated Cartesian Wind Simulations over Arbitrarily Complex Terrain, , ASE-12, Special Invited Session on Numerical Weather Modeling, AIAA Aviation and Aeronautics Forum (AVIATION 2014) June 18, 2014.
  6. Multi-GPU Accelerated Fine-Scale Wind Simulations over Complex Terrain, National Wind Technology Center, National Renewable Energy Laboratory, Boulder, CO, May 23, 2013.
  7. Multi-GPU Accelerated Fine-Scale Wind Simulations over Complex Terrain, Department of Geosciences, Boise State University, May 5, 2013.
  8. Multi-GPU Accelerated Fine-Scale Wind Simulations over Complex Terrain, National Oceanic and Atmospheric Administration, Sustainable Energy and Atmospheric Sciences Seminar Series, Boulder, CO, February 21, 2013.
  9. Advanced Computing for Wind Energy and Environmental Applications, Department Mechanical and Industrial Engineering, New Jersey Institute of Technology, February 15, 2013.