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RESEARCH

3D Virtual Reality

Our real-time solver is coupled to our virtual wind tunnel environment built in Unreal Engine 4. Our current research is exploring different mechanisms for visualising the flow field in 3D while maintaining user flexibility and performance. We have developed a custom module for UE4 to allow dynamic vector fields and particle visualisation of the flow physics. The user navigates and interacts with this world using the HTC Vive Virtual Reality headset.

Portable CFD

We also are actively exploring the use of mobile devices either individually or collectively for performing flow physics simulations. The latest developments involve an accelerated CFD solver running on a mobile the Tegra K1 processor from NVIDIA and we have a publication available which details the implementation.

We are also exploring the use of GLSL compute shaders for the purpose also as well as the use of custom processors built by colleagues in the School of Computer Science.

3D Object Capture

As part of a current research project we are developing a 3D scanning laboratory for fast capture of 3D geometries of up to 1.5m in length. The current setup uses 6 depth-sensing Microsoft Kinect cameras to acquire point cloud data. These data are then stitched together and processed to form a clean point cloud geometry which can be read into our current flow solver as well as the visualisation environment.

 

Undergraduate and Postgraduate projects are available to students of the University of Manchester if they wish to work on the development of this laboratory.

PhD Projects

The following PhD projects are now available. If you are interested in joining the research group to work on real-time, interactive engineering simulation then please PG admissions with your CV and covering letter stating why you would like to join the group along with details of the project for which you wish to apply.

Please note that PhD projects advertised here do not have prior funding agreed. If you are selected as a suitable candidate for the project, assistance will be provided to help apply for funding if eligible.

Accelerated aircraft noise prediction for trajectory optimisation

Aircraft noise in the vicinity of airports is both a nuisance and has significant implications for the health of residents. The noise generated by aircraft as they arrive at or depart from airports can be measured but available data is limited to points where measurement equipment can be placed. The distribution of noise over a wider region is almost impossible to measure but offers important data for trajectory optimisation and noise minimisation.

Fly-over noise may be modelled and simulated instead. In-house software called FLIGHT can be used to simulate fly-over noise for a given trajectory and aircraft/environment configuration. However, the process is slow due to the complexity of the models involved and the spatial resolution of the process. The faster-than-real-time generation of noise map data would enable real-time trajectory optimisation and hence the minimisation of noise for residents on a aircraft-by-aircraft basis.

This project explores the potential of GPU-accelerated simulation in the context of fly-over noise prediction. The project aims to develop software for GPU which accurately predicts aircraft fly-over noise measurement. The accelerated noise map data will then be used to perform automatic trajectory optimisation and confidence analysis.

Applicants should have a strong knowledge of geometrical and analytical acoustic prediction techniques. In particular, they should be familiar with ray-tracing. GPU-programming experience is desirable but not essential. Applicants should also have strong experience of fluid mechanics modelling.

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