A Machine Learning-Accelerated Framework for Lethality Assessment of Directed Energy Engagements of Hypersonic Threats

ATA Engineering, Inc., (ATA) proposes a Phase I Small Business Innovation Research program to develop a modular framework for rapid assessment of the lethality of directed energy (DE) engagements against hypersonic threat systems. The developed framework will couple existing tools in the lethality and DE communities with state-of-the-art physics-based solvers for modeling the threatÆs aerothermal condition, material effects, and associated aerodynamic performance degradation. Physics-based methods will be accelerated using a variety of machine learning approaches to generate reduced-order models and enable rapid lethality assessments and trade studies by software end users. The Phase I effort will focus on assessing the methods and tools available for each element of the lethality workflow, and development of plans for subsequent Phase II software development, integration, verification, and validation. Approved for Public Release | 24-MDA-11906 (16 Sep 24)