Optimization of Conceptual Design of Air Breathing Hypersonic Vehicle

Abstract

In the past few years, many countries have invested their time and efforts in research of hypersonic flight to realize commercial and research benefits. This has led to a rocketing development in the domain of Hypersonic flow. More research is being done on the complexities present exclusively in hypersonic flow. These flow complexities when faced by hypersonic vehicles makes it very important to have increased performance for ensuring sustained and economic flight. Based on this, the paper focuses on obtaining optimized models of forebody waverider integrated Hypersonic vehicles for Mach number 6 and Dynamic pressure of 47.8 kPa at an altitude of 27 km using conventional hypersonic theories. The models are parameterized with respect to inlet height, inlet width and equivalence ratio and are further evaluated to obtain Specific impulse (Isp) and Lift to Drag ratio (L/D) as objective parameters. To account for tradeoffs and computational cost, the multi-objective optimization process is performed using Non-dominated Sorting Genetic Algorithm (NSGA) with Artificial Neural Network (ANN) as a surrogate model. Subsequently, the optimized solutions are obtained in the form of pareto front and were later evaluated for stability and steady state conditions. The results obtained give optimized stabilized vehicles and the methodology followed can be used to design hypersonic vehicles for commercial or research purposes based on desired mission requirements.