Uncertainty-Driven Optimization Framework for Tamped Direct Laser Impulse Experiments

We propose prototyping and feasibility study efforts to address the Phase-1 SBIR call DTRA243-004: Predictive Methodology for Tamped Direct Laser Impulse Parameter Optimization.áWe propose the development of a fast-running software to optimize tamped Direct Laser Impulse (DLI) parameters for achieving a specified impulse on target materials. We will evaluate the combination of hydro codes, analytic approximations, and surrogate models to calculate necessary laser and tamper parameters backward from the desired impulse. Bayesian optimization is employed to explore the parameter space efficiently, while uncertainty quantification addresses both computational and experimental variabilities. Linearized models will be constructed around optimal points to extract parameter domain space to identify acceptable operating ranges. The tool will provide robust insights for experimental design and will be validated through comparisons with data from National Ignition Facility (NIF) DLI experiments and diagnostic tools such as Photon Doppler Velocimetry (PDV). This methodology offers a faster and more reliable framework for experimental planning, reducing trial and error in impulse optimization for defense-related applications.