EPSRC Reference: |
EP/J501736/1 |
Title: |
Coupling of Real-World Data and Fast Response Algorithms to Improve Simulation Correlations and Optimise Construction |
Principal Investigator: |
Kraft, Professor M |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Chemical Engineering and Biotechnology |
Organisation: |
University of Cambridge |
Scheme: |
Technology Programme |
Starts: |
01 March 2012 |
Ends: |
31 January 2015 |
Value (£): |
169,228
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EPSRC Research Topic Classifications: |
Information & Knowledge Mgmt |
Manufact. Enterprise Ops& Mgmt |
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EPSRC Industrial Sector Classifications: |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
The project will develop and deploy MODSUITE within the Caterpillar UK Engines Company Ltd. (CAT). MODSUITE is a
novel data analysis and optimisation tool and will be applied to analyse engine and machine test data against predictive
physics-based models of the processes occurring within the engine. The tool will apply novel optimisation and fastresponse
algorithms to systematically refine and quantify the uncertainty within the models. This will enable CAT to use the
make more effective use of the data and use the models to help optimise engine performance, including gaseous and
particulate (soot) emissions.
The project is split between four main partners. The Computational Modelling (CoMo) Group at the University of Cambridge
will perform the fundamental research and development required to apply MODSUITE to the applications presented by
CAT. Cambridge Computational Modelling Ltd. (CMCL), an engineering software and services company, will focus on
developing a user interface and testing the application of the software. CAT and BorgWarner Ltd. (see
www.borgwarner.com) will provide experimental data and models for real applications to support the software testing.
Federal Mogul Ltd. (see www.federalmogul.com) will act as a subcontractor to CAT for some of the model development.
The software will be developed and tested using three demonstration applications, at increasing levels of system
complexity. The initial phase of the project will be performed at CMCL facilities in Cambridge. Following successful
completion of the initial testing, the software will be deployed at CAT via an internet based user interface. This will enable
the software to be run at CMCL whilst it is still in development, whereas the application models will be run at CAT using
distributed computing technology, allowing CAT to harness the large computing resource at their disposal and maintain
control over the models and data. The web-based interface and distributed computing design offer a simple, but powerful
solution.
The CoMo Group will initially contribute to the project by investigating optimisation methods that are not currently
implemented within MODSUITE. The ones that are most relevant to the applications presented by CAT will be identified
and added. The group will extend MODSUITE so that it can automatically read and process the large quantities of
experimental data made available by CAT, facilitating the creation of data driven models. A wider range of different
response surface methods and an automated response generation and selection method will be investigated and
implemented. This will increase the versatility of the tool such that suitable response surfaces can be generated for each
specific test application. These improvements will facilitate the ability to generate suitable data driven models as well as
fast surrogate models. Advanced optimisation methods will be developed with a focus on self-calibration and robustness to
provide consistent and reliable results without the need for expert knowledge of the specific algorithms. These advanced
algorithms will be combined with uncertainty propagation and analysis tools to quantify the uncertainties in the model. The
MODSUITE code will be adapted to allow it to run over a distributed computing system.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.cam.ac.uk |