Coupling of Real-World Data and Fast Response Algorithms to Improve Simulation Correlations and Optimise Construction

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The project will develop and deploy MODSUITE within the Caterpillar UK Engines Company Ltd. (CAT). MODSUITE is anovel data analysis and optimisation tool and will be applied to analyse engine and machine test data against predictivephysics-based models of the processes occurring within the engine. The tool will apply novel optimisation and fastresponsealgorithms to systematically refine and quantify the uncertainty within the models. This will enable CAT to use themake more effective use of the data and use the models to help optimise engine performance, including gaseous andparticulate (soot) emissions.The project is split between four main partners. The Computational Modelling (CoMo) Group at the University of Cambridgewill perform the fundamental research and development required to apply MODSUITE to the applications presented byCAT. Cambridge Computational Modelling Ltd. (CMCL), an engineering software and services company, will focus ondeveloping a user interface and testing the application of the software. CAT and BorgWarner Ltd. (seewww.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 systemcomplexity. The initial phase of the project will be performed at CMCL facilities in Cambridge. Following successfulcompletion of the initial testing, the software will be deployed at CAT via an internet based user interface. This will enablethe software to be run at CMCL whilst it is still in development, whereas the application models will be run at CAT usingdistributed computing technology, allowing CAT to harness the large computing resource at their disposal and maintaincontrol over the models and data. The web-based interface and distributed computing design offer a simple, but powerfulsolution.The CoMo Group will initially contribute to the project by investigating optimisation methods that are not currentlyimplemented within MODSUITE. The ones that are most relevant to the applications presented by CAT will be identifiedand added. The group will extend MODSUITE so that it can automatically read and process the large quantities ofexperimental data made available by CAT, facilitating the creation of data driven models. A wider range of differentresponse surface methods and an automated response generation and selection method will be investigated andimplemented. This will increase the versatility of the tool such that suitable response surfaces can be generated for eachspecific test application. These improvements will facilitate the ability to generate suitable data driven models as well asfast surrogate models. Advanced optimisation methods will be developed with a focus on self-calibration and robustness toprovide consistent and reliable results without the need for expert knowledge of the specific algorithms. These advancedalgorithms will be combined with uncertainty propagation and analysis tools to quantify the uncertainties in the model. TheMODSUITE code will be adapted to allow it to run over a distributed computing system.