Algorithmic Advances to Increase the Fidelity of Conceptual Hypersonic Mission Design

Harish Saranathan, Purdue University

Abstract

The contributions of this dissertation increase the fidelity of conceptual hypersonic mission design through the following innovations: 1) the introduction of coupling between the effects of ablation of the thermal protection system (TPS) and flight dynamics, 2) the introduction of rigid body dynamics into trajectory design, and 3) simplifying the design of hypersonic missions that involve multiple phases of flight. These contributions are combined into a unified conceptual mission design framework, which is in turn applicable to slender hypersonic vehicles with ablative TPS. Such vehicles are employed in military applications, wherein speed and terminal energy are of critical importance. The fundamental observation that results from these contributions is the substantial reduction in the maximum terminal energy that is achievable when compared to the state-of-the art conceptual design process. Additionally, the control history that is required to follow the maximum terminal energy trajectory is also significantly altered, which will in turn bear consequence on the design of the control actuators. The other important accomplishment of this dissertation is the demonstration of the ability to solve these class of problems using indirect methods. Despite being built on a strong foundation of the calculus of variations, the state-of-the-art entirely neglects indirect methods because of the challenge associated with solving the resulting boundary value problem (BVP) in a system of differential-algebraic equations (DAEs). Instead, it employs direct methods, wherein the optimality of the calculated trajectory is not guaranteed. The ability to employ indirect methods to solve for optimal trajectories that are comprised of multiple phases of flight while also accounting for the effects of ablation of the TPS and rigid body dynamics is a substantial advancement in the state-of-the-art.

Degree

Ph.D.

Advisors

Grant, Purdue University.

Subject Area

Applied Mathematics|Aerospace engineering|Systems science

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