Martin’s research involves development of advanced methods for high fidelity analysis of nuclear reactors, with both Monte Carlo methods and deterministic methods. The methods utilize a high-dimensional phase space (7 independent variables) with large data structures that depend nonlinearly on the solution and are big enough to require domain decomposition. Hybrid techniques combining Monte Carlo and deterministic methods yield huge sparse matrices that require innovative storage and inversion algorithms.
Research AreasData; Statistics and Stochastic Methods
High Performance Computing
Numerical Analysis; Statistics and Stochastic Methods and Theories