New paper: “Nonlinear electro-elastic finite element analysis with neural network constitutive models”

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New paper published in CMAME under the project “Multiphysics-Informed Design of Tunable Smart Materials”.  The present work, the applicability of physics-augmented neural network (PANN) constitutive models for complex electro-elastic finite element analysis is demonstrated. For the investigations, PANN models for electro-elastic material behavior at finite deformations are calibrated to different synthetically generated datasets describing the … Read more

Applicants for a Marie Skłodowska-Curie Actions Postdoctoral Fellowships (MSCA-PF-2024)

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In MultiSimO Lab. we are seeking Applicants for a Marie Skłodowska-Curie Actions Postdoctoral Fellowships (MSCA-PF-2024).  We are seeking a good candidate with strong background and proven track record in computational mechanics to apply for a MSCA Postdoc fellowship. The ideal applicant should graduated a PhD in Computational Mechanics or Applied Mathematics. A strong experience in … Read more

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DeepONet: a deep-learning-based framework for approximating linear and nonlinear operators

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Delighted to convene the inaugural meeting of the research team for the coordinated POTENTIAL project in Cartagena. Our discussions on electromechanics, optimal control, and deep-learning algorithms were exceptionally fruitful, fostering an atmosphere of collaboration and innovation. Excited to witness the promising developments that will emerge as we continue to work together towards our shared objectives.Grant … Read more

New paper: “Gradient enhanced gaussian process regression for constitutive modelling in finite strain hyperelasticity”

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New paper published in CMAME under the project “Multiphysics-Informed Design of Tunable Smart Materials”. This paper introduces a metamodelling technique that leverages gradient-enhanced Gaussian process regression (also known as gradient-enhanced Kriging), effectively emulating the response of diverse hyperelastic strain energy densities. The approach adopted incorporates principal invariants as inputs for the surrogate of the strain energy density. This integration enables … Read more

New paper: “Learning nonlinear constitutive models in finite strain electromechanics with Gaussian process predictors” 

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The first paper authored by our PhD student, Alberto Pérez Escolar, under the project “Multiphysics-Informed Design of Tunable Smart Materials” has been published in CM. This paper introduces a gradient-enhanced Gaussian process metamodel designed to emulate homogenized nonlinear electromechanical constitutive models. The methodology, implemented entirely using Julia, incorporates principal invariants as inputs for the surrogate … Read more

Rogelio Ortigosa receives the Juan Carlos Simó Award.

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Dr. Rogelio Ortigosa, has been awarded by the Spanish Society of Computational Mechanics and Engineering with the Juan Carlos Simó Award, in recognition of his career as a researcher. The evaluating committee highlights his ‘solid and coherent trajectory of this young researcher, who presents a remarkable scientific output in the field of electroactive materials.’ Likewise, … Read more

Dr. Jesús Martínez Frutos invited speaker at Workshop “Journées Optimisation de Formes et Applications (JOFA 4)”

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Dr.  Jesús Martínez Frutos will be giving a talk at the Workshop Journées Optimisation de Formes et Applications (JOFA 4) to be held in  L’École polytechnique, Paris 28th October 2019 to 29th October 2019.  In this workshop Jesús Martínez Frutos will be talking about  the latest developments developed together with researchers from the MC3 group and Ecole Polytechnique  in the field … Read more

Dr. Jesús Martínez Frutos invited speaker at Workshop on New trends and challenges in the mathematics of optimal design

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Dr.  Jesús Martínez Frutos will be giving a talk at the Workshop on New trends and challenges in the mathematics of optimal design to be held in Cambridge, UK 10th June 2019 to 14th June 2019.  In this workshop Jesús Martínez Frutos will be talking about  the latest developments developed together with researchers from the MultiSimO Lab and Ecole … Read more