0000000000800600

AUTHOR

Humberto Varum

0000-0003-0215-8701

showing 2 related works from this author

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

2019

A methodology aiming to predict the vulnerability of masonry structures under seismic action is presented herein. Masonry structures, among which many are cultural heritage assets, present high vulnerability under earthquake. Reliable simulations of their response to seismic stresses are exceedingly difficult because of the complexity of the structural system and the anisotropic and brittle behavior of the masonry materials. Furthermore, the majority of the parameters involved in the problem such as the masonry material mechanical characteristics and earthquake loading characteristics have a stochastic-probabilistic nature. Within this framework, a detailed analytical methodological approac…

Artificial Neural Networkfailure criteriaComputer scienceRestoration mortarStructural system0211 other engineering and technologiesVulnerability020101 civil engineering02 engineering and technologylcsh:Technology0201 civil engineeringlcsh:Chemistryfragility analysisFragilitySeismic assessmentVulnerability assessmentForensic engineeringGeneral Materials ScienceMasonry structurelcsh:QH301-705.5InstrumentationArtificial Neural NetworksmonumentsFluid Flow and Transfer Processes021110 strategic defence & security studieslcsh:Tbusiness.industryProcess Chemistry and TechnologyGeneral EngineeringProbabilistic logicMonumentMasonrylcsh:QC1-999Computer Science ApplicationsCultural heritageSettore ICAR/09 - Tecnica Delle Costruzionilcsh:Biology (General)lcsh:QD1-999restoration mortarslcsh:TA1-2040Fragility analysiseismic assessmentlcsh:Engineering (General). Civil engineering (General)businessdamage indexlcsh:Physicsmasonry structuresstochastic modelingApplied Sciences
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Masonry Compressive Strength Prediction Using Artificial Neural Networks

2019

The masonry is not only included among the oldest building materials, but it is also the most widely used material due to its simple construction and low cost compared to the other modern building materials. Nevertheless, there is not yet a robust quantitative method, available in the literature, which can reliably predict its strength, based on the geometrical and mechanical characteristics of its components. This limitation is due to the highly nonlinear relation between the compressive strength of masonry and the geometrical and mechanical properties of the components of the masonry. In this paper, the application of artificial neural networks for predicting the compressive strength of m…

Computer science0211 other engineering and technologiesSocial SciencesCompressive strength020101 civil engineering02 engineering and technology0201 civil engineeringEngenharia e Tecnologia::Engenharia CivilBack-Propagation Neural Networks (BPNNs)11. Sustainability021105 building & constructionMasonryArtificial Neural Networks (ANNs)Science & TechnologyArtificial neural networkbusiness.industryMasonry unitArts & HumanitiesStructural engineeringMasonryMortarSettore ICAR/09 - Tecnica Delle CostruzioniNonlinear systemSoft-computing techniquesCompressive strengthBuilding materialsBuilding materialMortarbusiness
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