• A data-driven learning method for constitutive modeling: application to vascular hyperelastic soft tissues 

      González Ibáñez, David; García González, Alberto; Chinesta Soria, Francisco; Cueto Prendes, Elias (Multidisciplinary Digital Publishing Institute (MDPI), 2020-05-01)
      Article
      Accés obert
      We address the problem of machine learning of constitutive laws when large experimental deviations are present. This is particularly important in soft living tissue modeling, for instance, where large patient-dependent ...
    • A local multiple proper generalized decomposition based on the partition of unity 

      Ibáñez Pinillo, Rubén; Abisset Chavanne, Emmanuelle; Chinesta Soria, Francisco; Huerta, Antonio; Cueto Prendes, Elias (John Wiley & sons, 2019-10-12)
      Article
      Accés obert
      It is well known that model order reduction techniques that project the solution of the problem at hand onto alow-dimensional subspace present difficulties when this solution lies on a non-linear manifold. To overcomethese ...
    • A multidimensional data-driven sparse identification technique: the sparse proper generalized decomposition 

      Ibáñez Pinillo, Rubén; Abisset Chavanne, Emmanuelle; Ammar, Amine; González Ibáñez, David; Cueto Prendes, Elias; Huerta, Antonio; Duval, Jean Louis; Chinesta Soria, Francisco (2018-01-01)
      Article
      Accés obert
      Sparse model identification by means of data is especially cumbersome if the sought dynamics live in a high dimensional space. This usually involves the need for large amount of data, unfeasible in such a high dimensional ...
    • Parametric electromagnetic analysis of radar-based Advanced Driver Assistant Systems 

      Vermiglio, Simona; Champaney, Victor; Sancarlos, Abel; Daim, Fatima; Kedzia, Jean Claude; Duval, Jean Louis; Díez, Pedro; Chinesta Soria, Francisco (Multidisciplinary Digital Publishing Institute (MDPI), 2020-10-05)
      Article
      Accés obert
      Efficient and optimal design of radar-based Advanced Driver Assistant Systems (ADAS) needs the evaluation of many different electromagnetic solutions for evaluating the impact of the radome on the electromagnetic wave ...
    • Radars in transport applications 

      Ibáñez Pinillo, Rubén; Chinesta Soria, Francisco; Abisset-Chavanne, Emmanuelle; Abenius, Erik; Huerta, Antonio (Springer, 2020-02-28)
      Capítol de llibre
      Accés restringit per política de l'editorial
      In the recent years, automotive car industry is evolving towards a new generation of autonomous vehicles, where decision making is not fully perform by the driver but it partially relies on the technology of the car itself. ...
    • Structural health monitoring by combining machine learning and dimensionality reduction techniques 

      Quaranta, Giacomo; López Tomás, Elena; Abisset-Chavanne, Emmanuelle; Duval, Jean Louis; Huerta, Antonio; Chinesta Soria, Francisco (2019-01-01)
      Article
      Accés obert
      Structural Health Monitoring is of major interest in many areas of structural mechanics. This paper presents a new approach based on the combination of dimensionality reduction and data-mining techniques able to differentiate ...
    • Tensor representation of non-linear models using cross approximations 

      Aguado, José Vicente; Borzacchiello, Domenico; Kollepara, Kiran Sagar; Chinesta Soria, Francisco; Huerta, Antonio (2019-10-01)
      Article
      Accés obert
      Tensor representations allow compact storage and efficient manipulation of multi-dimensional data. Based on these, tensor methods build low-rank subspaces for the solution of multi-dimensional and multi-parametric models. ...
    • Vademecum-based GFEM (V-GFEM): optimal enrichment for transient problems 

      Canales, Diego; Leygue, Adrien; Chinesta Soria, Francisco; González Ibáñez, David; Cueto Prendes, Elias; Feulvarch, Eric; Bergheau, Jean-Michel; Huerta, Antonio (2016-11)
      Article
      Accés obert
      This paper proposes a generalized finite element method based on the use of parametric solutions as enrichment functions. These parametric solutions are precomputed off-line and stored in memory in the form of a computational ...