Towards Accelerated Flight Testing via Sequential Design of Experiments

As the capabilities of hypersonics vehicles have become the forefront domain of contention, each nation is seeking to mobilize the ability to rapidly develop hypersonic vehicles. However, the high degree of cost and challenges of the flight regime have slowed down the flight test cycle for new hypersonic vehicle designs. With improvements to computational modeling and integration of digital engineering, such as NASA's Configuration Based Aerodynamics (CBAERO) tool, the ability to supplement the design and testing phase of the flight test cycle becomes possible. However, it is still vital to efficiently test designs to maximize system knowledge using a systematic approach to investigate the design space. The use of a sequential design of experiments (DOE) allows for the model complexity and fidelity to grow by block, efficiently arriving at accurate conclusions without wasted test points. With the combination of a power analysis and iterative model analysis, the sequential strategy enables accelerated learning, statistically accurate modeling, and robustness to help reduce risk for testing. Two analyses of alternative design cases of hypersonic geometries were used with computational simulation of sequential DOE. The CBAERO results for both cases demonstrated efficient and accurate modeling of flight characteristic metrics, including a factor-response model with less than 6% normalized root mean squared error, optimal geometry design, and model uncertainty validation. Despite limitations from being a lower fidelity analysis than typical ground testing, the benefits gained from being time efficient and cost-effective open up possibilities to accelerate the flight test cycle using computational modeling. This methodology may also provide insight into risk reduction analysis and improvements in digital engineering with higher fidelity data from ground testing and even flight testing.