Dr. Inanc Senocak is an Associate Professor with the Department of Mechanical and
Biomedical Engineering. Before joining Boise State in 2007, Dr. Senocak served for two
years as a postdoctoral research associate at the Los Alamos National Laboratory where he
worked in the area of stochastic source inversion of atmospheric plumes. Prior to that
appointment he worked as a postdoctoral fellow at the Center for Turbulence Research,
which is jointly operated by Stanford University and NASA. In addition to teaching and
advising students, Dr. Senocak conducts research in such areas as computational fluid
dynamics (CFD), wind power forecasting, parallel computing, cavitation and multiphase
flows, turbulence modeling, atmospheric transport and dispersion. 

Articles and Conference Proceedings

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Solution of the Population Balance Equation Using Parallel Adaptive Cubature on GPUs (with Fabio P. Santos, Jovani L. Favero, and Paulo L. C. Lage), Computers & Chemical Engineering (2013)

The Dual Quadrature Method of Generalized Moments (DuQMoGeM) is an accurate moment method for solving...

 

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Stochastic Reconstruction of Multiple Source Atmospheric Contaminant Dispersion Events (with Derek Wade), Atmospheric Environment (2013)

Reconstruction of intentional or accidental release of contaminants into the atmosphere using concentration measurements from...

 

The Search for Strategies to Prevent Persistent Misconceptions (with Dazhi Yang), 120th ASEE Annual Conference and Exposition, June 23, 2013 - June 26, 2013, Atlanta, GA, United States (2013)

Research shows that it may be too late to repair misconceptions of fundamental science and...

 

The Search for Strategies to Prevent Persistent Misconceptions (with Dazhi Yang), 120th ASEE Annual Conference and Exposition (2013)

Research shows that it may be too late to repair misconceptions of fundamental science and...

 

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Large Eddy Simulations of Turbulent Incompressible Flows on GPU Clusters (with Rey DeLeon and Dana Jacobsen), Computing in Science & Engineering (2013)

Graphics processing unit (GPU) and clusters of GPUs have emerged as cost-effective general-purpose scientific computing...