Análisis de aceros AHSS en el nuevo simulador de deformación plástica HSMFS

El presente documento muestra las capacidades del nuevo simulador de deformación plástica, de reciente construcción, y capaz de realizar ensayos en cualquier tipo de material, hasta una fuerza de 10 kN. Además, se exponen otras líneas de investigación del grupo.Sellés Cantó, MÁ.; Sanchez-Caballero, S.; Pla-Ferrando, R.; Reig Pérez, MJ.; Segui Llinares, VJ.; Eixerés Tomás, B.; Pérez Bernabeu, E. (2013). Análisis de aceros AHSS en el nuevo simulador de deformación plástica HSMFS. Compobell, S.L. http://hdl.handle.net/10251/73772

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

An open source HPC-enabled model of cardiac defibrillation of the human heart

Sudden cardiac death following cardiac arrest is a major killer in the industrialised world. The leading cause of sudden cardiac death are disturbances in the normal electrical activation of cardiac tissue, known as cardiac arrhythmia, which severely compromise the ability of the heart to fulfill the body's demand of oxygen. Ventricular fibrillation (VF) is the most deadly form of cardiac arrhythmia. Furthermore, electrical defibrillation through the application of strong electric shocks to the heart is the only effective therapy against VF. Over the past decades, a large body of research has dealt with the study of the mechanisms underpinning the success or failure of defibrillation shocks. The main mechanism of shock failure involves shocks terminating VF but leaving the appropriate electrical substrate for new VF episodes to rapidly follow (i.e. shock-induced arrhythmogenesis).A large number of models have been developed for the in silico study of shock-induced arrhythmogenesis, ranging from single cell models to three-dimensional ventricular models of small mammalian species. However, no extrapolation of the results obtained in the aforementioned studies has been done in human models of ventricular electrophysiology. The main reason is the large computational requirements associated with the solution of the bidomain equations of cardiac electrophysiology over large anatomically-accurate geometrical models including representation of fibre orientation and transmembrane kinetics.In this Thesis we develop simulation technology for the study of cardiac defibrillation in the human heart in the framework of the open source simulation environment Chaste. The advances include the development of novel computational and numerical techniques for the solution of the bidomain equations in large-scale high performance computing resources. More specifically, we have considered the implementation of effective domain decomposition, the development of new numerical techniques for the reduction of communication in Chaste's finite element method (FEM) solver, and the development of mesh-independent preconditioners for the solution of the linear system arising from the FEM discretisation of the bidomain equations.The developments presented in this Thesis have brought Chaste to the level of performance and functionality required to perform bidomain simulations with large three-dimensional cardiac geometries made of tens of millions of nodes and including accurate representation of fibre orientation and membrane kinetics. This advances have enabled the in silico study of shock-induced arrhythmogenesis for the first time in the human heart, therefore bridging an important gap in the field of cardiac defibrillation research.</p

Computación Paralela Heterogénea y Homogénea para la Resolución de Problemas Estructurados de Álgebra Lineal Numércia

En el presente trabajo se han aplicado técnicas de computación paralela en la resolución de problemas de álgebra lineal numérica. El principal problema estudiado ha sido el de cálculo de valores propios de matrices estructuradas. Se ha estudiado el caso de las matrices tridiagonales (Capítulo 4), el de las matrices Toeplitz simétricas (Capítulo 6) y un caso de estudio particular proveniente de un problema de ingeniería (Capítulo 3). Se han aplicado técnicas de computación paralela tanto homogénea como heterogénea. Con el fin de disponer de una plataforma donde ejecutar nuestros algoritmos heterogéneos, se ha diseñado, ensamblado y configurado un clúster de computadores heterogéneos. El Capítulo 2 documenta dicha experiencia.Bernabeu Llinares, MO. (2008). Computación Paralela Heterogénea y Homogénea para la Resolución de Problemas Estructurados de Álgebra Lineal Numércia. http://hdl.handle.net/10251/13059Archivo delegad

An open source HPC-enabled model of cardiac defibrillation of the human heart

Sudden cardiac death following cardiac arrest is a major killer in the industrialised world. The leading cause of sudden cardiac death are disturbances in the normal electrical activation of cardiac tissue, known as cardiac arrhythmia, which severely compromise the ability of the heart to fulfill the body's demand of oxygen. Ventricular fibrillation (VF) is the most deadly form of cardiac arrhythmia. Furthermore, electrical defibrillation through the application of strong electric shocks to the heart is the only effective therapy against VF. Over the past decades, a large body of research has dealt with the study of the mechanisms underpinning the success or failure of defibrillation shocks. The main mechanism of shock failure involves shocks terminating VF but leaving the appropriate electrical substrate for new VF episodes to rapidly follow (i.e. shock-induced arrhythmogenesis). A large number of models have been developed for the in silico study of shock-induced arrhythmogenesis, ranging from single cell models to three-dimensional ventricular models of small mammalian species. However, no extrapolation of the results obtained in the aforementioned studies has been done in human models of ventricular electrophysiology. The main reason is the large computational requirements associated with the solution of the bidomain equations of cardiac electrophysiology over large anatomically-accurate geometrical models including representation of fibre orientation and transmembrane kinetics. In this Thesis we develop simulation technology for the study of cardiac defibrillation in the human heart in the framework of the open source simulation environment Chaste. The advances include the development of novel computational and numerical techniques for the solution of the bidomain equations in large-scale high performance computing resources. More specifically, we have considered the implementation of effective domain decomposition, the development of new numerical techniques for the reduction of communication in Chaste's finite element method (FEM) solver, and the development of mesh-independent preconditioners for the solution of the linear system arising from the FEM discretisation of the bidomain equations. The developments presented in this Thesis have brought Chaste to the level of performance and functionality required to perform bidomain simulations with large three-dimensional cardiac geometries made of tens of millions of nodes and including accurate representation of fibre orientation and membrane kinetics. This advances have enabled the in silico study of shock-induced arrhythmogenesis for the first time in the human heart, therefore bridging an important gap in the field of cardiac defibrillation research.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Theoretical model of a multi-layered polymer coated steel-strip ironing process using a neural network

An alternative to the traditional can manufacturing process is to use plastic laminated rolled steels as base stocks. This material consist of pre-heated steel coils that are sandwiched between one or two sheets of polymer. The heated sheets are then immediately quenched, which yields a strong bond between the layers. Such polymer-coated steels were investigated by Jaworski [1,2] and Sellés [3], and found to be suitable for ironing with carefully controlled conditions. A novel multi-layer polymer coated steel has been developed for container applications. This material presents an interesting extension to previous research on polymer laminated steel in ironing, and offers several advantages over the previous material (Sellés [3]). This document shows a modelization for the ironing process (the most crucial step in can manufacturing) done by using a neural network. © (2012) Trans Tech Publications.This work was supported by the “Universitat Politècnica de València” [grant number PAID-06-10-003-305]Sellés Cantó, MÁ.; Schmid, SR.; Sanchez-Caballero, S.; Pérez Bernabeu, E.; Reig Pérez, MJ.; Segui Llinares, VJ. (2012). Theoretical model of a multi-layered polymer coated steel-strip ironing process using a neural network. Trans Tech Publications. https://doi.org/10.4028/www.scientific.net/MSF.713.139J.A. Jaworski and S.R. Schmid: Trib. Trans. Vol. 42 (1999), pp.32-38.J.A. Jaworski, S.R. Schmid and J.E. Wang: J. Manuf. Sci. and Eng. Vol. 121 (1999), pp.232-237.M.A. Sellés, S.R. Schmid, V.J. Seguí: J. of Mat. Process. Tech. Vol. 202 (2008), pp.7-14