AbstractThe broad aim of the work carried out was to develop a Computational Fluid Dynamics (CFD) based Reduced Order Model (ROM) capable of the rapid modelling of an aircraft’s response to ‘1-cosine’ gusts; for use in identifying critical gust load cases early within the design process where computational resources are at a premium. The first stage of the work involved recreating an already existing Eigensystem Realisation Algorithm (ERA) based ROM; this acted as a baseline ROM method on which developments were made, and performances compared.
The ROM was initially developed and tested on a three-dimensional, inviscid, rigid wing model. As the baseline ROM method showed high accuracy levels (typically comparable to full order CFD results), the focus of development was on reducing the computational cost associated with building the ROM. This was achieved first through reducing the number of inputs needed to create the ROM to one; and then by minimising the computational cost associated with obtaining that single input. At the end of this portion of the ROM development, the final ROM required just 5.2% of the computational cost incurred by the base ROM.
Further developments and testing were carried out on more complex test cases. For the first of these, a generic wide-bodied aircraft which included the effects of viscosity, the ROM performed as well as it had previously. In the final test case, a simple inviscid, aircraft model which contained both aeroelastic effects and flight mechanics, a slight degradation in performance was noted but was relatively minor.
Finally, modifications were made to the ROM to extend its usefulness. This was achieved by successfully modifying the ROM so that it could be built at one altitude, and then used at another; as long as the Mach number remained constant. Additionally, the ROM was modified so that the surface pressures of the output gust could be constructed; the results of which were generally very good.
|Date of Award||23 Jan 2019|
|Supervisor||Dorian P Jones (Supervisor) & Ann L Gaitonde (Supervisor)|