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Dive into the research topics where Francisco Chinesta is active.

Publication


Featured researches published by Francisco Chinesta.


PLOS ONE | 2018

Reduced-order modeling of soft robots

Jean Chenevier; David González; J. Vicente Aguado; Francisco Chinesta; Elías Cueto

We present a general strategy for the modeling and simulation-based control of soft robots. Although the presented methodology is completely general, we restrict ourselves to the analysis of a model robot made of hyperelastic materials and actuated by cables or tendons. To comply with the stringent real-time constraints imposed by control algorithms, a reduced-order modeling strategy is proposed that allows to minimize the amount of online CPU cost. Instead, an offline training procedure is proposed that allows to determine a sort of response surface that characterizes the response of the robot. Contrarily to existing strategies, the proposed methodology allows for a fully non-linear modeling of the soft material in a hyperelastic setting as well as a fully non-linear kinematic description of the movement without any restriction nor simplifying assumption. Examples of different configurations of the robot were analyzed that show the appeal of the method.


Archive | 2018

Consistent data-driven computational mechanics

David González; Francisco Chinesta; Elías Cueto

We present a novel method, within the realm of data-driven computational mechanics, to obtain reliable and thermodynamically sound simulation from experimental data. We thus avoid the need to fit any phenomenological model in the construction of the simulation model. This kind of techniques opens unprecedented possibilities in the framework of data-driven application systems and, particularly, in the paradigm of industry 4.0.We present a novel method, within the realm of data-driven computational mechanics, to obtain reliable and thermodynamically sound simulation from experimental data. We thus avoid the need to fit any phenomenological model in the construction of the simulation model. This kind of techniques opens unprecedented possibilities in the framework of data-driven application systems and, particularly, in the paradigm of industry 4.0.


Archive | 2018

Simulation of the microwave heating of a thin multilayered composite material: A parameter analysis

Hermine Tertrais; Anaïs Barasinski; Francisco Chinesta

Microwave (MW) technology relies on volumetric heating. Thermal energy is transferred to the material that can absorb it at specific frequencies. The complex physics involved in this process is far from being understood and that is why a simulation tool has been developed in order to solve the electromagnetic and thermal equations in such a complex material as a multilayered composite part. The code is based on the in-plane-out-of-plane separated representation within the Proper Generalized Decomposition framework. To improve the knowledge on the process, a parameter study in carried out in this paper.


Archives of Computational Methods in Engineering | 2018

A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity

Ruben Ibañez; Emmanuelle Abisset-Chavanne; Jose Vicente Aguado; David González; Elías Cueto; Francisco Chinesta


Archives of Computational Methods in Engineering | 2018

kPCA-Based Parametric Solutions Within the PGD Framework

David González; Jose Vicente Aguado; Elías Cueto; Emmanuelle Abisset-Chavanne; Francisco Chinesta


Archives of Computational Methods in Engineering | 2018

A Manifold Learning Approach for Integrated Computational Materials Engineering

Elena Lopez; David González; Jose Vicente Aguado; Emmanuelle Abisset-Chavanne; Elías Cueto; Christophe Binetruy; Francisco Chinesta


Computational Mechanics | 2017

Data-driven non-linear elasticity: constitutive manifold construction and problem discretization

Ruben Ibañez; Domenico Borzacchiello; Jose Vicente Aguado; Emmanuelle Abisset-Chavanne; Elías Cueto; Pierre Ladevèze; Francisco Chinesta


Computer Methods in Applied Mechanics and Engineering | 2017

Model order reduction for real-time data assimilation through Extended Kalman Filters

David González; Alberto Badías; I. Alfaro; Francisco Chinesta; Elías Cueto


International Journal of Material Forming | 2017

About the origins of residual stresses in in situ consolidated thermoplastic composite rings

Cyril Dedieu; Anaïs Barasinski; Francisco Chinesta; Jean-Marc Dupillier


International Journal for Numerical Methods in Engineering | 2018

Proper generalized decomposition solutions within a domain decomposition strategy: PGD solutions within a DD strategy

Antonio Huerta; Enrique Nadal Soriano; Francisco Chinesta

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Roland Keunings

Université catholique de Louvain

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Adrien Scheuer

Université catholique de Louvain

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Antonio Huerta

Polytechnic University of Catalonia

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