Date of Award
Master of Science
We created a new methodology to perform conceptual design analysis on aircraft, using off-the-shelf, high-fidelity software tools to explore the project design space, including important preliminary design factors and thereby producing a more robust result which is less subject to compromise at later design stages. We claim that this analysis can be performed in one hour with commonly available computation resources, and therefore is applicable to conceptual design. We used the case study of a supersonic transport jet to develop these methods. For this application, we used Solidworks to create a parameterized three-dimensional CAD solid to define the exterior geometry of the aircraft, and create populations of design candidates. We used STAR-CCM+ to perform an automated fluid flow analysis of these candidates, using three-dimensional, viscous, turbulent finite volume analysis and incorporating internal engine performance characteristics. We then used MATLAB to collect the data produced by these analyses, compute additional results of interest, and quantify the design space represented by a population of candidates. We heavily automated the steps of this process, to allow large studies or optimization frameworks to be implemented. Our results show that the method produces a data set which is much more rich than conventional conceptual design techniques. The method captures many interactions between aircraft systems which are normally not quantified until later phases of design: aerodynamic interactions between external lifting surfaces and between the external body and internal engine performance, and how structural constraints affect wing performance. We also produce detailed information about the aircraft static stability. Further, the method is able to produce these results with commonly available computer hardware within the one-hour timeframe we allow for a conceptual design analysis.
John Thomas Watson
Watson, John Thomas, "A high-fidelity approach to conceptual design" (2016). Graduate Theses and Dissertations. 15183.