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A Bayesian adaptive sampling method is developed for highly coupled multidisciplinary design problems. The method addresses a major challenge in aerospace design: exploration of a design space with computationally expensive analysis tools such as computational fluid dynamics (CFD) or finite element analysis. With a limited analysis budget, it is often impossible to optimize directly or to explore a design space with off-line design of experiments (DoE) and surrogate models. This difficulty is magnified in multidisciplinary problems with feedbacks between disciplines because each design point may require iterative analyses to converge on a compatible solution between different disciplines. Bayesian Collaborative Sampling (BCS) is a bi-level architecture for adaptive sampling that simulataneously - concentrates disciplinary analyses in regions of a design space that are favorable to a system-level objective - guides analyses to regions where interdisciplinary coupling variables are probably compatible BCS uses Bayesian models and sequential sampling techniques along with elements of the collaborative optimization (CO) architecture for multidisciplinary optimization. The method is tested with the aero-structural design of a glider wing and the aero-propulsion design of a turbojet engine nacelle.

New helicopter rotor designs are desired that offer increased efficiency, reduced vibration, and reduced noise. This problem is multidisciplinary, requiring knowledge of structural dynamics, aerodynamics, and aeroacoustics. Rotor optimization requires achieving multiple, often conflicting objectives. There is no longer a single optimum but rather an optimal trade-off space, the Pareto Frontier. Rotor Designers in industry need methods that allow the most accurate simulation tools available to search for Pareto designs. Computer simulation and optimization of rotors have been advanced by the development of "comprehensive" rotorcraft analysis tools. These tools perform aeroelastic analysis using Computational Structural Dynamics (CSD). Though useful in optimization, these tools lack built-in high fidelity aerodynamic models. The most accurate rotor simulations utilize Computational Fluid Dynamics (CFD) coupled to the CSD of a comprehensive code, but are generally considered too time consuming where numerous simulations are required like rotor optimization. An approach is needed where high fidelity CFD/CSD simulation can be routinely used in design optimization. This thesis documents the development of physics based rotor simulation frameworks. A low fidelity model uses a comprehensive code with simplified aerodynamics. A high fidelity model uses a parallel processor capable CFD/CSD methodology. Both frameworks include an aeroacoustic simulation for prediction of noise. A synergistic process is developed that uses both frameworks together to build approximate models of important high fidelity metrics as functions of certain design variables. To test this process, a 4-bladed hingeless rotor model is used as a baseline. The design variables investigated include tip geometry and spanwise twist. Approximation models are built for high fidelity metrics related to rotor efficiency and vibration. Optimization using the approximation models found the designs having maximum rotor efficiency and minimum vibration. Various Pareto generation methods are used to find frontier designs between these two anchor designs. The Pareto anchors are tested in the high fidelity simulation and shown to be good designs, providing evidence that the process has merit. Ultimately, this process can be utilized by industry rotor designers with their existing tools to bring high fidelity analysis into the preliminary design stage of rotors.

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<p dir="ltr">This thesis details the development of a multidisciplinary design analysis (MDA) framework intended to evaluate a rocket-powered, reusable hypersonic vehicle. In particular, the analysis framework computes the design closure of a coupled system resembling Stratolaunch Systems’ Talon-A reusable hypersonic test vehicle. The resulting analysis framework differs from available literature due to its focus upon payload-related design considerations. The presented framework, too, avoids the use of proprietary technical information and/or export-controlled analysis tools. The framework’s geometric analysis, for example, employs a reverse-engineered geometry resembling Talon-A. An open-source aerothermal package, too, was selected to evaluate the vehicle’s aerothermodynamic characteristics. Quick-to-implement methods were prioritized to expedite the development of the MDA framework. Notably, a regression-based structural analysis model was used, as well as an interpolative thermal protection system (TPS) sizing procedure. A quasi-steady trajectory model, too, was implemented within the MDA framework, to determine the vehicle’s mission performance. The resulting analysis takes the form of a six-discipline MDA framework that can calculate, among other parameters, the vehicle’s cruise duration. Initial design closure results for a vehicle resembling Talon-A, using an assumed TPS size, are currently available. These results report an estimated total vehicle mass within thirty percent of Talon-A’s true gross mass, as well as a cruise duration of approximately 445 seconds. These design closure results were also evaluated under a perturbed specific impulse of ±10%, with a resulting change in cruise duration of ±12.3%. Results for a cruise-condition design exploration procedure were also obtained within a simplified, sequential analysis chain. These design exploration results report a maximum cruise lift-to-drag ratio of approximately four. Future work has been identified, too, including the integration of more rigorous analysis tools for use within future iterations of the MDA framework. Notably, these tools include an open-source optimal control library, as well as a physics-based TPS sizing tool</p>