Baskar Ganapathysubramanian

Assistant Professor

Office: 2100 Black Engineering Phone: 515 294-7442 Email: baskarg@iastate.edu

Department(s): Mechanical Engineering, Electrical and Computer Engineering (Courtesy).

Research Interests: Computational transport mechanics, scientific computing, multi-scale modeling, uncertainty quantification and data-driven analysis.

Current Research: Our work in wind energy is in the broad area of incorporating uncertainty quantification in wind energy analysis. Our recent efforts have focused on two related areas. (a) We are developing data-driven mathematical techniques that assimilate large-scale meteorology data to construct a low-dimensional yet realistic stochastic wind flow model. Since the framework is data-driven, this model is location-, and terrain-aware and accurately captures spatial and temporal correlations (like diurnal patterns, transition from stable to unstable flows). This framework enables integrating meteorology data with farm-scale and turbine-scale analysis. (b) Rigorously incorporating wind-, material- and operational uncertainties into both simplified wind-turbine models (like FAST) and full-fidelity turbine simulations. We seek to construct distributional (or probabilistic) forecasts of turbine performance under these stochastic conditions.

Recent Publications:

Guo, Qiang, Daniel Rajewski, Eugene Takle, and Baskar Ganapathysubramanian: Constructing low-dimensional stochastic wind models through temporal and spatial decomposition. Wind Energy.

Guo, Qiang, Yuri Bazilevs, M.-C. Hsu, and Baskar Ganapathysubramanian: Investigating ply material uncertainty on wind turbine blade performance: A stochastic-isogeometric approach. Computational Mechanics.

Amini, Hamed, Elodie Sollier, Mahdokht Masaeli, Yu Xie, Baskar Ganapathysubramanian, Howard A. Stone, and Dino Di Carlo, 2013: Engineering fluid flow using sequenced microstructures. Nature Communications, 4. (doi:10.1038/ncomms2841).

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