Parallel approach of a Galerkin-based methodology for predicting the compressive strength of the lightweight aggregate concrete

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Title: Parallel approach of a Galerkin-based methodology for predicting the compressive strength of the lightweight aggregate concrete
Authors: Migallón, Violeta | Navarro González, Francisco José | Penadés, Jose | Villacampa, Yolanda
Research Group/s: Computación de Altas Prestaciones y Paralelismo (gCAPyP) | Modelización Matemática de Sistemas
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial | Universidad de Alicante. Departamento de Matemática Aplicada
Keywords: Galerkin | Modelling | Parallel algorithms | Compressive strength prediction | Concrete
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial | Matemática Aplicada
Issue Date: 20-Sep-2019
Publisher: Elsevier
Citation: Construction and Building Materials. 2019, 219: 56-68. doi:10.1016/j.conbuildmat.2019.05.160
Abstract: A methodology based on the Galerkin formulation of the finite element method has been analyzed for predicting the compressive strength of the lightweight aggregate concrete using ultrasonic pulse velocity. Due to both the memory requirements and the computational cost of this technique, its parallelization becomes necessary for solving this problem. For this purpose a mixed MPI/OpenMP parallel algorithm has been designed and different approaches and data distributions analyzed. On the other hand, this Galerkin methodology has been compared with multiple linear regression models, regression trees and artificial neural networks. Based on different measures of goodness of fit, the effectiveness of the Galerkin methodology, compared with these statistical techniques for data mining, is shown.
Sponsor: This research was supported by the Spanish Ministry of Science, Innovation and Universities Grant RTI2018-098156-B-C54, co-financed by the European Commission (FEDER funds).
URI: http://hdl.handle.net/10045/92732
ISSN: 0950-0618 (Print) | 1879-0526 (Online)
DOI: 10.1016/j.conbuildmat.2019.05.160
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2019 Elsevier Ltd.
Peer Review: si
Publisher version: https://doi.org/10.1016/j.conbuildmat.2019.05.160
Appears in Collections:INV - gCAPyP - Artículos de Revistas
INV - MMS - Artículos de Revistas

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