Abstract
ABSTRACTThis application paper describes a novel, cluster-based, semi-automatic, stream surface placement strategy for structured and unstructured computational fluid dynamics (CFD) data, tailored towards a specific application: The BLOODHOUND jet and rocket propelled land speed record vehicle. An existing automatic stream surface placement algorithm(8), is extensively modified to cater for large unstructured CFD simulation data. The existing algorithm uses hierarchical clustering of velocity and distance vectors to find potential stream surface seeding locations. This work replaces the hierarchical clustering algorithm, designed to work with small regular grids, with a K-means clustering approach suitable for large unstructured grids. Modifications are made to the seeding curve construction algorithm, improving the smoothness and distribution of the discretised curve in complex cases. A new distance function is described which allows the user to target particular characteristics of simulation data. The proposed algorithm reduces the required memory footprint and computational requirement compared to previous work(8). The performance and effectiveness of the proposed algorithm is demonstrated, and CFD domain expert evaluation is provided describing the value of this approach.
Highlights
1.1 Background and motivationIn recent decades, aerodynamic designers, and design engineers more generally, have increasingly relied on computational modelling, and in particular computational fluid dynamics (CFD) to simulate the aerodynamic response of motorsport[20] and aerospace vehicles
A typical multi-disciplinary aerospace design cycle is shown in Fig. 1, and it is evident that CFD analysis and CFD post-processing lie at the heart of the design cycle’s ‘inner loop’
The techniques and applications presented in this paper are the results of work undertaken to improve on the effectiveness of flow visualisation in the context of the typical aerodynamic design cycle
Summary
Aerodynamic designers, and design engineers more generally, have increasingly relied on computational modelling, and in particular computational fluid dynamics (CFD) to simulate the aerodynamic response of motorsport[20] and aerospace vehicles. The BLOODHOUND vehicle has four wheels and will be under full control of its driver during record attempts set to take place in 2015 and 2016 It has a slender body of approximately 13 m length with two front wheels within the body and two rear wheels mounted externally within wheel fairings. The effect of airbrake deployment can clearly be seen during the deceleration phase of the run profile This application was deemed to be a perfect test case for the visualisation technique detailed in this paper due to the vehicle’s geometrical complexity and, due to unique aerodynamic challenge of taking a land vehicle faster than the speed of sound, the designers’ lack of prior knowledge of likely aerodynamic performance and anticipated aerodynamic performance. It was hoped that the approach developed for this project would significantly improve the aerodynamic designers’ understanding of the phenomena that would determine the car’s performance and, in turn, success in its record breaking attempt
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
