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H2020Doctoral network2018–2023

DyVirt · Dynamic virtualisation: modelling performance of engineering structures

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2018-02-01 → 2023-03-31
EU contribution
€3,588,403
Participants
8
Scheme
MSCA-ITN

Lines connect the coordinator with its partners.

Results in brief

Dynamic virtualisation: modelling performance of engineering structures

The aim of this innovative training network is to enable a new generation of early-stage researchers (ESRs) 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 of the ESRs who receive training through this network will (i) obtain a PhD from an internationally-recognised university, (ii) gain crucial skills in developing accurate models of dynamic structures much needed in industry, (iii) gain experience of applying their research skills in non-academic organisations, and (iv) receive training in transferable skills such as commercialisation and communication.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). Verification is concerned with the numerical accuracy of the virtual model. It addresses both the elimination of coding errors and estimation of the numerical errors that necessarily arise through discretisation of physical laws. Validation assesses the extent to which the virtual model accurately represents the system/structure being modelled, and thus the degree of trust that can be given to its predictions of real-world events. Successful development of dynamic virtualisation processes will be underpinned by the development and adoption of rigorous and appropriate V&V methodologies within industry. These 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 uncertainty. 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-focussed relationship. All this will result in a training network where ESRs 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.

Data: CORDIS, © European Union

Project 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.

Original text from CORDIS.

Participants

  • THE UNIVERSITY OF SHEFFIELD · SHEFFIELDCoordinatorUnited Kingdom
  • AKADEMIA GORNICZO-HUTNICZA IM. STANISLAWA STASZICA W KRAKOWIE · KrakowPoland
  • EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH · ZuerichSwitzerland
  • GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER · HannoverGermany
  • PANEPISTIMIO THESSALIAS · VOLOSGreece
  • SIEMENS GAMESA RENEWABLE ENERGY AS · BrandeDenmark
  • SIEMENS INDUSTRY SOFTWARE NV · LeuvenBelgium
  • THE UNIVERSITY OF LIVERPOOL · LIVERPOOLUnited Kingdom

Links

Data: CORDIS, © European Union