Donald L. Brown, Ph.D.

Senior Researcher II

Years of Experience: 6

Educations and Licenses:

 

  • Ph.D., Applied Mathematics, 2012, Texas A&M University, College Station, TX
  • B.A., Mathematical Sciences, 2008, University of Cincinnati, Cincinnati, OH

 

Areas of Specialization:

 

  • Scientific computation, computational science and engineering, numerical methods
  • Multiscale modeling and simulation of porous media and heterogeneous materials
  • Geomechanics, thermomechanics, and fluid-solid interaction
  • Complex fluid simulations, Lattice Boltzmann methods, phase field modeling of interfaces
  • Multiscale methods and stability in high-frequency wave propagation and vibration

 

Overview

 

Dr. Brown’s prior research focus is on multiscale modelling and simulation of porous and heterogenous materials and developing applicable mathematical tools and techniques. The research has wide ranging applications in the modeling of subsurface flows for oil and gas, Lithium-Ion batteries, composites, thermomechanical behavior, and corrosion. Many complex materials processes have significant multiscale and multi-physical characteristics. This multiscale nature of this media often makes solving the full problem intractable, and alternative techniques must be employed to bridge these scales. Dr. Brown’s research is to develop computational tools and analysis techniques to deal with fundamental problems in multiscale processes of the complex physics.

 

Dr. Brown has an interest in homogenization theory of flow and mechanics to obtain effective physical models, multilevel upscaling with complex nonlinearities and uncertainty, and development and analysis of multiscale methods for heterogeneous materials. Dr. Brown’s recent interest includes application of these methods to real world problems faced at E2G. Dr. Brown has a strong desire to move in a direction of more data (big or small) integration into these models and connect the vast amounts of information with these simulations. Whether this is done in a Bayesian framework or model reduction setting, the aim is to integrate the information into the physical description, ultimately giving the clients of E2G a coherent description and understanding of the challenges they face.