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DRIVEN SIGNED

Increasing the scientific excellence and innovation capacity in Data-Driven Simulation of the University of Luxembourg

Total Cost €

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EC-Contrib. €

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Partnership

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Project "DRIVEN" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITE DU LUXEMBOURG 

Organization address
address: 2 AVENUE DE L'UNIVERSITE
city: ESCH-SUR-ALZETTE
postcode: 4365
website: http://wwwen.uni.lu

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Luxembourg [LU]
 Total cost 1˙157˙475 €
 EC max contribution 1˙000˙000 € (86%)
 Programme 1. H2020-EU.4.b. (Twinning of research institutions)
 Code Call H2020-WIDESPREAD-05-2017-Twinning
 Funding Scheme CSA
 Starting year 2018
 Duration (year-month-day) from 2018-10-01   to  2021-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITE DU LUXEMBOURG LU (ESCH-SUR-ALZETTE) coordinator 512˙550.00
2    UNIVERSITY OF LIMERICK IE (LIMERICK) participant 245˙000.00
3    INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE FR (LE CHESNAY CEDEX) participant 242˙450.00
4    THE UNIVERSITY OF TEXAS SYSTEM US (AUSTIN) participant 0.00

Map

 Project objective

The overall aim of the DRIVEN project is to boost the scientific excellence and technology-transfer capacity in data-driven simulation of the University of Luxembourg (UL) by creating a network with the high-quality Twinning partners: Institut National de Recherche en Informatique et en Automatique (Inria), University of Limerick (ULIM) and University of Texas at Austin (UT Austin). To achieve this aim, the 3 year project will build upon the existing strong research and innovation base of UL and its Twinning partners.

To boost their scientific excellence and technology transfer capacity in data-driven simulation, the partners will implement a research and innovation strategy focused on three sub-topics:

1. Mathematical foundations for data-driven simulations – UL with UT Austin, 2. Data-driven simulations for computer-assisted therapy – UL with Inria, and 3. Data-driven simulations for functional composite materials – UL with ULIM.

The research and innovation strategy takes into account the recent SWOT analysis of UL and has the following objectives:

• Objective 1: Strengthen UL’s research excellence in data-driven simulation • Objective 2: Enhance the research and innovation capacity of UL and the Twinning partners • Objective 3: Raise the research profile of UL and the Twinning Partners • Objective 4: Contribute to the SMART Specialisation Strategy of Luxembourg • Objective 5: Support research and innovation on a European level In order to achieve these objectives, the consortium partners will implement a comprehensive set of measures via the project’s work packages:

• Short term staff exchanges (WP1); • Training workshops, conferences and summer schools (WP2); • Dissemination and outreach (WP3).

 Deliverables

List of deliverables.
Project leaflet and poster Websites, patent fillings, videos etc. 2019-09-20 14:27:40

Take a look to the deliverables list in detail:  detailed list of DRIVEN deliverables.

 Publications

year authors and title journal last update
List of publications.
2018 H. Rappel, L.A.A. Beex, L. Noels, S.P.A. Bordas
Identifying elastoplastic parameters with Bayes’ theorem considering output error, input error and model uncertainty
published pages: , ISSN: 0266-8920, DOI: 10.1016/j.probengmech.2018.08.004
Probabilistic Engineering Mechanics 2019-05-19
2018 Paul Hauseux, Jack S. Hale, Stéphane Cotin, Stéphane P.A. Bordas
Quantifying the uncertainty in a hyperelastic soft tissue model with stochastic parameters
published pages: 86-102, ISSN: 0307-904X, DOI: 10.1016/j.apm.2018.04.021
Applied Mathematical Modelling 62 2019-05-19
2017 Paul Hauseux, Jack S. Hale, Stéphane P. A. Bordas
Calculating the Malliavin derivative of some stochastic mechanics problems
published pages: e0189994, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0189994
PLOS ONE 12/12 2019-05-19
2016 K.C. Hoang, P. Kerfriden, S.P.A. Bordas
A fast, certified and “tuning free” two-field reduced basis method for the metamodelling of affinely-parametrised elasticity problems
published pages: 121-158, ISSN: 0045-7825, DOI: 10.1016/j.cma.2015.08.016
Computer Methods in Applied Mechanics and Engineering 298 2019-05-19
2018 Hussein Rappel, Lars A. A. Beex, Stéphane P. A. Bordas
Bayesian inference to identify parameters in viscoelasticity
published pages: 221-258, ISSN: 1385-2000, DOI: 10.1007/s11043-017-9361-0
Mechanics of Time-Dependent Materials 22/2 2019-05-19
2017 Paul Hauseux, Jack S. Hale, Stéphane P.A. Bordas
Accelerating Monte Carlo estimation with derivatives of high-level finite element models
published pages: 917-936, ISSN: 0045-7825, DOI: 10.1016/j.cma.2017.01.041
Computer Methods in Applied Mechanics and Engineering 318 2019-05-19
2018 Huu Phuoc Bui, Satyendra Tomar, Hadrien Courtecuisse, Stephane Cotin, Stephane P. A. Bordas
Real-Time Error Control for Surgical Simulation
published pages: 596-607, ISSN: 0018-9294, DOI: 10.1109/tbme.2017.2695587
IEEE Transactions on Biomedical Engineering 65/3 2019-05-19
2016 Olivier Goury, David Amsallem, Stéphane Pierre Alain Bordas, Wing Kam Liu, Pierre Kerfriden
Automatised selection of load paths to construct reduced-order models in computational damage micromechanics: from dissipation-driven random selection to Bayesian optimization
published pages: 213-234, ISSN: 0178-7675, DOI: 10.1007/s00466-016-1290-2
Computational Mechanics 58/2 2019-05-19
2018 Tuan Nguyen, Alireza Kashani, Tuan Ngo, Stéphane Bordas
Deep neural network with high-order neuron for the prediction of foamed concrete strength
published pages: , ISSN: 1093-9687, DOI: 10.1111/mice.12422
Computer-Aided Civil and Infrastructure Engineering 2019-05-19

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