Project description
A novel framework supports the design of tomorrow’s greener multistage turbomachinery
Turbomachinery is equipment that transfers energy through the expansion or compression of a continuously moving fluid via rotating blades, and it includes turbines and compressors. Multistage turbomachinery harnesses several cycles of such expansion or compression in a series to achieve a very high pressure difference from inlet to outlet. With the support of the Marie Skłodowska-Curie Actions programme, the MENTOR project is developing a deep neural network framework that will model uncertainty effects on multistage turbomachinery performance in the advanced phases of multistage turbomachinery design. Optimised turbines and compressors with greater efficiencies will support Europe’s carbon-neutrality and sustainability goals.
Objective
"This fellowship aims to train a talented early career researcher and to contribute to the EU scientific excellence by developing an innovative Multi-fidelity dEep neural Network uncerTainty quantificatiOn and Robust optimization design (MENTOR) framework in order to handle the high dimensionality (HD) uncertain problems in the advanced multistage turbomachinery design process. The applicant is a highly dedicated and motivated young researcher and has been stimulated to propose this novel idea. He has been successively honoured with several prestigious awards including the National Scholarship for PhD Candidate, Excellent PhD Graduates of Beijing, Excellent Doctoral Dissertations Award of Beijing and ASME Young Engineer Turbo Expo Travel Award attributed to his excellent research achievement in cost-efficient uncertainty quantification (UQ) studies.
The traditional UQ methods can hardly control the computation cost for predicting the higher-order moments of multistage turbomachinery performance considering HD input uncertainties. The deep learning technology is a promising approximator in predicting the HD function. Integration of multi-fidelity (MF) methodology with deep neural network (DNN) can further combine their complementary merits. Thus, the novel MF-DNN method is proposed here and its effectiveness in handling a 60-dimensional test function has been preliminarily validated in the Incoming Researcher's recent work. Through this research fellowship, an affordable MENTOR framework will be finally established to investigate the multi-source uncertainty effects on multistage turbomachinery performance. This project has been carefully designed to match the applicant's profile with the strength of Imperial's UQ Lab, and thus will facilitate excellent two-way knowledge transfer and training activities. Successful completion of this fellowship will contribute to achieving the goal of the EU's ""Green Deal"" and will benefit the applicant's academic career prospect."
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
SW7 2AZ London
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.