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Dynamic virtualisation: modelling performance of engineering structures

Objective

The aim of this innovative training network is to train a new generation of early-stage researchers (ESR’s) to face the urgent challenge of how to model the performance of engineering structures that operate in dynamic environments. Building trusted virtual models for structures subject to high dynamic loads is a process we call “dynamic virtualisation”. All the ESR’s who receive training through this network will (i) obtain a PhD from an internationally recognised University, (ii) gain experience of applying their research skills in non-academic organisations, and (iii) receive training in transferable skills such commercialisation and communication. The network will be run as part of the Open Data Project giving maximum research impact through open access publications, data, software and public engagement. The research carried out through this network will go beyond the now ubiquitous process of creating computer based simulation models of structural dynamics. Obtaining a valuable virtual model is no longer a question of computing power, but now rests in the more difficult problem of developing trust in the model through the process of verification and validation (V & V). The challenges are perhaps most obvious in the renewable energy sector, where technology is developing at a very rapid pace, and more reliable models are required to cope with structures subjected to extreme loadings which lead to a high degree of nonlinearity, and uncertainties. Applying our research to such problems will be accelerated by close interaction with the industrial partners in the network, with whom we intend to maintain and enhance an innovation focused relationship. This will result in a training network where ESR’s are able to be creative, entrepreneurial and innovative whilst receiving state of the art training that will enable them to deal with future challenges in this important area of engineering.

Fields of science (EuroSciVoc)

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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Keywords

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.

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.

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.

MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-ITN-2017

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Coordinator

THE UNIVERSITY OF SHEFFIELD
Net EU contribution

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.

€ 546 575,76
Address
FIRTH COURT WESTERN BANK
S10 2TN SHEFFIELD
United Kingdom

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Region
Yorkshire and the Humber South Yorkshire Sheffield
Activity type
Higher or Secondary Education Establishments
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Total cost

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.

€ 546 575,76

Participants (7)

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