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Details of Grant 

EPSRC Reference: EP/N508500/1
Title: SWEPT 2
Principal Investigator: Allan, Dr RJ
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Scientific Computing Department
Organisation: STFC Laboratories (Grouped)
Scheme: Technology Programme
Starts: 10 June 2015 Ends: 09 June 2018 Value (£): 99,857
EPSRC Research Topic Classifications:
Fluid Dynamics Wind Power
EPSRC Industrial Sector Classifications:
Energy
Related Grants:
EP/N508512/1 EP/N508524/1 EP/N508536/1 EP/N508548/1
Panel History:  
Summary on Grant Application Form
The tasks associated with STFC are broken down in further detail below:

3.1.2 Wind Tunnel Test Case

STFC will be taking the output from this test case for use in 3.3.4.

3.3.1 Analysis of CFD and LIDAR output data formats

In order for the comparison between CFD and experimental data to be performed, the format of these data must be known

in order to facilitate transformations to a common format. STFC will liaise with zCFD and LIDAR manufacturers to obtain

sample data for study.

3.3.2 Numerical tools for SWEPT Data Comparison

STFC will leverage our existing big data software to create a validation tool for CFD against LIDAR data. The figure below

demonstrates how this software will fit into the workflow; LIDAR and CFD output will be input into the software and

MapReduce algorithms will be used to transform the data into a common format, perform comparisons and summarise the

results. The comparisons will be modifiable to produce different outputs depending on the requirements of the user.

3.3.3 Numerical tools for SWEPT Data Comparison Report

A report on the reliability, performance and scope of possible data comparison and analysis will be produced.

3.3.4 Big Data for Windtunnel/CFD Validation

The tool developed in 3.3.2 will be used to validate the wind tunnel simulations from 3.1 against the experimental results

from 3.2.

3.3.5 Big Data for LIDAR/CFD Validation

The tool developed in 3.3.2 will be used to validate simulations from 3.1 against the LIDAR data gathered in 3.2 for a

variety of test cases.

3.3.6 Big Data for Validation Report

The findings of 3.3.4 and 3.3.5 will be reported, detailing results from several MapReduce algorithms and presenting these

results in such a manner that they can be used to manipulate future CFD simulations to improve their accuracy.

3.3.7 Automated Data Comparison

The potential for automated feedback from the results of CFD validation into the parameters of future CFD simulations will

be explored, beginning with the identification of areas of the simulation requiring a higher level of resolution. Such feedback

would add another level of innovation to the project.

3.3.8 Automated Data Comparison Report

The findings of 3.3.7 will be presented and recommendations made on how automated feedback could form part of future

projects.
Key Findings
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Potential use in non-academic contexts
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Summary
Date Materialised
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