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Listar por autor "Chinesta Soria, Francisco"

Mostrando ítems 1-12 de 12

A Physically-Based Fractional Diffusion Model for Semi-Dilute Suspensions of Rods in a Newtonian Fluid

Nadal, Enrique; Aguado-López, Jose Vicente; Abisset-Chavanne, E.; Chinesta Soria, Francisco Jose; Keunings, R.; Cueto, E. (Elsevier, 2017)

[EN] The rheological behaviour of suspensions involving interacting (functionalized) rods remains nowadays incompletely understood, in particular with regard to the evolution of the elastic modulus with the ...
Allying topology and shape optimization through machine learning algorithms

Muñoz-Pellicer, David; Nadal, Enrique; Albelda Vitoria, José; CHINESTA SORIA, FRANCISCO JOSE; Ródenas, Juan José (Elsevier, 2022-07-01)

[EN] Structural optimization is part of the mechanical engineering field and, in most cases, tries to minimize the overall weight of a given design domain, subjected to functionality constraints given in terms of stresses ...
An efficient solver of the saturation equation in liquid composite molding processes

García Manrique, Juan Antonio; Gascón Martínez, María Llanos; Chinesta, F.; Ruiz, E.; Trochu, F. (Springer-Verlag, 2010-09)

[EN] A major issue in Liquid Composite Molding Process (LCM) concerns the reduction of voids formed during the resin filling process. Reducing the void content increases the quality of the composite and improves its ...
Induction machine model with finite element accuracy for condition monitoring running in real time using hardware in the loop system

Sapena-Bano, Angel; CHINESTA SORIA, FRANCISCO JOSE; Pineda-Sanchez, Manuel; Aguado-López, Jose Vicente; Borzacchiello, D.; Puche-Panadero, Rubén (Elsevier, 2019-10)

[EN] Most industrial processes are run by induction machines (IMs). Condition monitoring of IM assures their continuity of service, and it may avoid highly costly breakdowns. Among the methods for condition monitoring, ...
Low-Rank Approximation in Neuronal Networks

Dolz Martínez, Vicent (Universitat Politècnica de València, 2020-10-13)

[EN] Artificial intelligence algorithms have experienced a dramatic improvement in the last decade generating very precise models in all fields of study. This has led us to a new problematic of mass data storage and ...
Manifold learning for coherent design interpolation based on geometrical and topological descriptors

Muñoz-Pellicer, David; Allix, O.; CHINESTA SORIA, FRANCISCO JOSE; Ródenas, Juan José; Nadal, Enrique (Elsevier, 2023-02-15)

[EN] In the context of intellectual property in the manufacturing industry, know-how is referred to practical knowledge on how to accomplish a specific task. This know-how is often difficult to be synthesised in a set of ...
Model reduction based on sparse identification techniques for induction machines: Towards the real time and accuracy-guaranteed simulation of faulty induction machines

Sapena-Bano, Angel; Chinesta, F.; Puche-Panadero, Rubén; Martinez-Roman, Javier; Pineda-Sanchez, Manuel (Elsevier, 2021-02)

[EN] The development of condition monitoring (CM) systems of induction machines (IMs) is essential for the industry because the early fault detection would help engineers to optimise maintenance plans. However, the use of ...
On the physical interpretation of fractional diffusion

Nadal, Enrique; Abisset-Chavanne, E.; Cueto, E.; Chinesta Soria, Francisco Jose (Elsevier, 2018)

[EN] Even if the diffusion equation has been widely used in physics and engineering, and its physical content is well understood, some variants of it escape fully physical understanding. In particular, anormal diffusion ...
Proper Generalized Decomposition solutions within a Domain Decomposition strategy

Huerta, Antonio; Nadal, Enrique; Chinesta Soria, Francisco Jose (John Wiley & Sons, 2018-03-30)

[EN] Domain decomposition strategies and proper generalized decomposition are efficiently combined to obtain a fast evaluation of the solution approximation in parameterized elliptic problems with complex geometries. The ...
Real time parameter identification and solution reconstruction from experimental data using the Proper Generalized Decomposition

Nadal Soriano, Enrique; Chinesta Soria, Francisco José; Díez Mejia, Pedro; Fuenmayor Fernández, Francisco Javier; Denia Guzmán, Francisco David (Elsevier, 2015-11-01)

Some industrial processes are modelled by parametric partial differential equations. Integrating computational modelling and data assimilation into the control process requires obtaining a solution of the numerical model ...
Real-Time Path Planning Based on Harmonic Functions undera Proper Generalized Decomposition-Based Framework

Montés Sánchez, Nicolás; Chinesta Soria, Francisco José; Mora Aguilar, Marta Covadonga; Falcó, Antonio; Hilario Pérez, Lucía; Rosillo Guerrero, Nuria; Nadal, Enrique (MDPI AG, 2021-06)

[EN] This paper presents a real-time global path planning method for mobile robots using harmonic functions, such as the Poisson equation, based on the Proper Generalized Decomposition (PGD) of these functions. The main ...
Simultaneous roots for vectorial problems

Chinesta, Francisco; Cordero Barbero, Alicia; Garrido-Saez, Neus; Torregrosa Sánchez, Juan Ramón; Triguero-Navarro, Paula (Springer-Verlag, 2023-07)

[EN] In this manuscript, we design an iterative step that can be added to any numerical process for solving systems of nonlinear equations. By means of this addition, the resulting iterative scheme obtains, simultaneously, ...