OPTIMIZATION TECHNOLOGIES, INC. — Department of Defense SBIR Phase I: N202-139

OPTIMIZATION TECHNOLOGIES, INC. — SBIR Phase I award from Department of Defense.

Amount
$239,998
Agency
Department of Defense · Navy
Program / Phase
SBIR · Phase I
Topic
N202-139
Solicitation
20.2
NAICS
Place of performance
CO
Period
2020-10-13 → 2022-02-14

Description

As the U.S. Navy works to rapidly develop and field hypersonic weapons, a robust Modeling and Simulation (M&S) capability is necessary to measure the effectiveness of these new systems under different performance and design choices and mission scenarios. M&S of hypersonic systems, along with supporting blue and red force systems will allow analysts to explore and understand how hypersonic systems will contribute to future military engagements. While the ability to accurately model these new systems and their interactions in the battlespace is a critical capability, it is not enough. The number of potential variations of new hypersonic system performance and design choices and the number of potential scenarios involving different blue and red forces is immense, and the complex interactions between these variable factors make it impossible for the human mind to effectively explore the myriad possibilities. Combining M&S with an automated optimization and sensitivity analysis capability will enable effective investigation of the nearly unbounded set of possibilities in a limited timeframe. This optimization capability will make it possible to identify the best design and employment choices for new hypersonic systems that will quantifiably improve the key system metric probability of kill (Pk) which is derived directly from the probability of arrival (Pa) and the probability of damage (Pd). As part of an end-to-end M&S concept for hypersonic systems, OptTek and Infoscitex will demonstrate configurable simulation models for hypersonic systems at varying levels of fidelity along with software that automates optimization of key system performance measures. The software will also perform sensitivity analysis to identify which model inputs are key drivers of performance and to find robust design points.