||Fort Sam Houston, TX 78234
Research has shown that laser-material interactions deviate from the predictions given by traditional mathematical models for short laser exposure times. For example, it was found that in general, a shorter exposure time often results in a stronger deviation from established theory. Alternative theories and methods are being formulated in an attempt to describe these phenomena from a first principles point of view. Some of these methods include generalizing current models by recasting them as fractional order differential equations which have resulted in expressions that show high agreement with experimental observation regardless of exposure duration. Others involve coupled multi-physics analytical/numerical simulations that combine electromagnetics, mechanics, and heat transfer at a variety of temporal and spatial scales and sometimes in dynamic geometries. The goal of this project is to analyze these new theories and numerical methods and use them to predict material damage at varying radiofrequency and/or optical wavelengths as well as modifying, extending, and/or developing new/existing models where appropriate/as needed. The opportunity involves creating numerical toolboxes for novel mathematical methods for high-performance computing (HPC) environments and rigorous problem and solution definition in meta-language forms to enable language-agnostic solvers
Parker, James E., Charles W. Beason, Stephen P. Sturgeon, William B. Voorhees, Samuel S. Johnson, Kaitlin S. Nelson, Leland R. Johnson, and Jeffrey N. Whitmore. "Revisiting 35 and 94 GHZ Millimeter Wave Exposure to the Non-Human Primate Eye." Health Physics 119, no. 2 (2020): 206-215.
Zollars, Byron G., Gabriel J. Elpers, Austin L. Goodwin, Edward A. Early, Nicholas J. Gamez, Robert J. Thomas, and Optical Radiation Bioeffects Branch. "AFRL-RH-FS-TR-2019-0016." (2019).
Wharmby, Andrew W. "Fractional lumped capacitance." Fractional Calculus and Applied Analysis 21, no. 4 (2018): 1104-1119.
numerical methods; laser material interaction; differential equations; high performance computing