Mohsen Zayernouri receives a prestigious AFOSR 2017 Young Investigator Program Award

  • Oct 11, 2016
  • News

Mohsen Zayernouri has won a highly prestigious and selective 2017 Young Investigator Program (YIP) Award from the U.S. Air Force Office of Scientific Research (AFOSR), which will award $20.8 million in three-year grants to 58 scientists and engineers. YIP is open to early-career scientists and engineers who show exceptional ability and promise for conducting basic research. Zayernouri is an assistant professor of Computational Mathematics, Science, & Engineering (CMSE) and Mechanical Engineering. He is also the director of the Fractional Mathematics for Anomalous Transport and Hydromechanics (FMATH) group at MSU. View:http://bit.ly/2dOjdTe

College of Engineering news website story: http://www.egr.msu.edu/news/2016/10/13/young-investigator-award

 

Title: Data-Infused Fractional PDE Modelling and Simulation of Anomalous Transport

The proposed research will break a new ground with long-term impact for data-infused and realistic simulations of the complex phenomena of twenty-first century. The overarching goal is to develop a robust computational-mathematical modelling framework for predictive simulation of challenging multi-physics and multi-scale problems e.g., anomalous (wave-to-diffusion) transport and ageing complex materials, where the corresponding fractional PDE models can be obtained from available data from small-to-big scales.

The novelty of approach is to employ emerging and generalizing mathematical models, namely fractional PDEs, where the derivative orders in space and time can be fixed, variable, and distributed orders. In addition, a robust and efficient framework has been proposed to construct the fractional orders from observable data, taking into account the corresponding inherent data uncertainties. The proposed approach will open up new attractive possibilities for modelling multi-scale sub-to-super diffusion processes, in addition to multi-physics problems such as wave-to-diffusion dynamics, occurring in ageing complex soft matter and ageing visco-elasto-plastic materials. Such anomalous transport phenomena hence cannot be successfully modeled by the existing PDE models. The proposed linear and nonlinear fractional PDEs can rigorously code the underlying memory effects, nonlocal interaction, self-similar structures, and power-law distributions. If successful, the proposed research can lead to more reliable life prediction of the US Air Force fleet, in addition to improve the conceptual design and capability of lightweight fighters. Moreover, the proposed research potentially leads to much more
efficient and more reliable models for the prediction of turbulent combustion.