Projet ADDOPTML (Horizon 2020, appel à projets 2020)
Action : Staff Exchanges
Panel : Information Science and Engineering
Statut du projet : SIGNED

Additive Manufacturing (AM) has attracted the interest of industry due to its potential for flexible and automated production of complex geometry objects, combined with minimizing the time required to develop new products. According to recent analysis, the market for AM products is projected to grow annually by 18%. Although AM technologies are an integral part of digitized industrial production and of the 4th industrial revolution, Architectural, Engineering & Construction Industry (AECI) is reluctant to adopt them in design and construction. While AECI has been a pillar industry since 80's, its scale and impact on the global economy expands continuously. This development is also associated with important drawbacks, including large contribution to waste production, huge energy consumption and severe environmental pollution. The recent Green New Deal for Europe sets as primary objective the reform of heavy industry, including AECI, which accounts for 40% of the energy consumed on the continent. The main tools for achieving this objective are to minimize both materials used and amount of AECI waste. The principal aim of ADDOPTML network is to create and validate a holistic machine learning aided, optimum design-manufacturing process of civil structures by developing strong synergies among a multi-disciplinary team of academic experts and SMEs from Belgium, Cyprus, Germany, Greece, Italy, Jordan, Netherlands and Spain. This will be achieved taking advantage of ongoing progress in AM technologies including recycled consumables, thus contributing to the European challenge to become the world's first climate-neutral bloc by 2050. As a primary application, an integrated structural design framework based on AM optimized structural elements for transitional structures will be developed, to address the shortage of hospital units faced by many countries as coronavirus pandemic continues to sweep the World and to develop novel human shelter structure for post-disaster housing.

Mots clés : additive manufacturing, topology optimization, nonlinear finite element analyses experimental verification, generative design, deployable structures, humanitarian crises, human shelter structures

Participants :
- Vrije Universiteit Brussel (Belgique) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 92000.0 €
- Jordan University of Science and Technology (Jordanie) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Space Applications Services (Belgium) (Belgique) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 23000.0 €
- National Technical University of Athens (Grèce) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 1113200.0 €
- European Welding Federation (Belgique) — Partner, beneficiary, Autres, subvention : 46000.0 €
- Tsakalis kai sia oe (Grèce) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 230000.0 €
- Polytechnic University of Turin (Italie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 184000.0 €
- RISA Sicherheitsanalysen (Allemagne) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 230000.0 €
- University of Cyprus (Chypre) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 73600.0 €
- Kataskeves & esthitires idiotiki kefalaiouxiki etaireia (Grèce) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 230000.0 €
- University of Stuttgart (Allemagne) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 46000.0 €
- Idea75 srl (Italie) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 50600.0 €
- Fundación Prodintec (Espagne) — Partner, beneficiary, Recherche, subvention : 46000.0 €
- Mx3d bv (Pays-Bas) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 46000.0 €