Aakash Jain

My research develops adjoint methods for hybrid particle-continuum solvers used in hypersonic computational fluid dynamics (CFD). Current high-fidelity hypersonic simulations couple continuum fluid solvers with particle-based Direct Simulation Monte Carlo (DSMC) methods to accurately model flow across all altitude regimes, but no framework exists to efficiently compute gradients for these systems. By formulating an adjoint method for this hybrid solver — and implementing it on GPU-accelerated hardware — the work will enable gradient-based optimization of hypersonic vehicles at a fraction of the cost of traditional approaches, opening the door to high-fidelity multidisciplinary design optimization across the full hypersonic flight envelope for the first time.