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Applied Mathematics

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Applied Mathematics

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Research Frontiers in Computational Fluid Dynamics Modeling

Numerical methods and simulations for solving Navier-Stokes equations with applications to aerodynamics and environmental flows.

Turbulence Closure Models at Extreme Reynolds Numbers
Machine Learning Surrogates for Multiphase Flow Dynamics
Lattice Boltzmann Methods in Non-Newtonian Fluids
Data-Driven Reduced-Order Models for Complex Geometries
Adaptive Mesh Refinement in Shock-Dominated Regimes
Physics-Informed Neural Networks for Inverse Flow Problems
Multiscale Coupling Between Molecular and Continuum Scales
Uncertainty Quantification in High-Dimensional Parameter Spaces
Vortex Dynamics and Coherent Structure Evolution
Hydrodynamic Instabilities in Stratified and Rotating Flows

All Applied Mathematics PhD categories