The capital aim of this project is to develop novel computational models and numerical methods to genuinely and drastically advance simulation-based decision-making for cutting-edge industrial problems. It will confront existing knowledge gaps on fundamental approaches in reduced order model techniques for real-time, inverse and optimization problems, and it will deliver comprehensive understanding and tools for simulation in problems seen by industry as a major asset to increase performance and competitiveness. The ultimate goal is to set the basis for the next generation of simulation tools that will be used for industry related problems within Europe. In spite the international efforts in this area, these objectives represent a challenge beyond todays state-of-the-art both from the fundamental computational engineering/science perspective and from the applied engineering industrial standpoint. To achieve these objectives, InSilico is focused on three specific industrial problems (IP), namely, fast simulation supporting surgery; electric grids, including uncertainty quantification and decision making; and aerodynamical and mechanical simulation for shape design and optimization in the automotive industry. The project aims at providing tools to face the Social Challenge on Economy and Digital Society (#7 from the list of those identified by the Spanish RTD Strategy). The instruments for decision making provided by the methologies developed here are to be implemented in portable digital devices. The possibility of producing online real-time simulations with the computational capacity of a smart phone is creating a new paradigm in the social use of the simulation software for industrial design, for management and control of complex systems and for monitoring health technologies. Incidentally, making progress in the three IPs (Surgery, Electric grids and Automotion) is having impact in three other Social Challenges: Health, Demographical Change and Welfare (#1); Clean, Safe and Sustainable Energy (#3) and Integrated and Sustainable Smart Transport (#4). These three big problems, apparently dissimilar and unrelated, share one essential feature: the presence of many queries and the need for real-time response. By real time different things are meant depending on the context, but in general this relates to the need of a fast and reliable response provided in times much lower than those usual for everyday engineering simulation practice, and ranging from some milliseconds in virtual surgery to some minutes in shape optimisation. To efficiently solve these problems, it is envisaged that model order reduction techniques constitute nowadays the sole alternative to more traditional tools that, despite the generalization of supercomputing infrastructures, have not provided a satisfactory solution yet under these astringent requirements. Among the plethora of possible model order reduction techniques, Proper Generalized Decomposition techniques have demonstrated, despite their youth, an impressive capacity to provide real time response in a wide variety of problems. By stating the problem at hand into a parametric formulation, a sort of computational vademecum is obtained, that allows for real-time post-processing rather than real-time simulation. This computational vademecum approach opens unprecedented possibilities for real time and many query problems, as previous works of the applicants have already demonstrated.
Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016
Programa Estatal de I+D+i Orientada a los Retos de la Sociedad
Retos de Investigación: Proyectos de I+D+i
Gobierno De España. Ministerio De Economía Y Competitividad, Mineco
Serafin, K.; Magnain, B.; Florentin, E.; Pares, N.; Diez, P. International journal for numerical methods in engineering Vol. 110, num. 5, p. 440-466 DOI: 10.1002/nme.5363 Date of publication: 2017-05-04 Journal article