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Details of Grant 

EPSRC Reference: EP/N015398/1
Title: Extracting coherent structures and low-order modelling using Optimal Mode Decomposition
Principal Investigator: Wynn, Dr A
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Aeronautics
Organisation: Imperial College London
Scheme: First Grant - Revised 2009
Starts: 30 April 2016 Ends: 29 April 2017 Value (£): 96,940
EPSRC Research Topic Classifications:
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine
Related Grants:
Panel History:
Panel DatePanel NameOutcome
25 Nov 2015 Engineering Prioritisation Panel Meeting 25th and 26th November 2015 Announced
Summary on Grant Application Form
Since nearly 25% of UK emissions are generated by transport, improving the energy efficiency of aviation and road vehicles is vital if the UK is to meet legally binding targets to significantly reduce greenhouse gas emissions by 2050. One promising approach to achieving this aim is to improve the aerodynamic performance of ground and air vehicles using active flow control. In active flow control, measurements are taken from the flow in real time and, in response to those measurements, action is taken to positively modify the flow. For example, movable surfaces on an aircraft's wing or on the rear of a road vehicle may be dynamically adjusted to reduce aerodynamic drag and hence decrease fuel consumption.

To implement an active control strategy typically requires an approximating flow model, which allows a beneficial control action to be computed from a given flow measurement. However, a significant challenge is that flows of practical interest have highly complicated and intricate dynamics, while computational and theoretical restrictions mean that the approximating models must be simple, or low-dimensional. One method of bridging this gap is to identify coherent structures in a flow, that is, spatial features which are of dynamical importance to its evolution and performance. If a small set of representative coherent structures can be identified, they can be used as the building blocks for a flow model and therefore facilitate a successful flow control strategy.

The aim of this project is to develop the Optimal Mode Decomposition (OMD) algorithm, a method which systematically extracts dynamically important coherent structures from ensembles of experimental or numerical fluid flow data. The systematic nature of the data extraction is important since it provides a tractable method of analysing the increasing large-scale sets of fluid flow data that are now available. The proposed research will thoroughly benchmark the performance of the OMD algorithm across a range of fundamental and challenging fluid flows, assess the suitability of the extracted structures to be used for flow modelling and estimation and, finally, undertake a theoretical study to explain any observed behaviour. This research will therefore develop a methodology to underpin the application of flow control for improved energy efficiency and consequently addresses a current and fundamentally important environmental and economic issue.

Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.imperial.ac.uk