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Numerical Design and Optimisation of Self-Compacting High Early-Strength Cement-Based Mortars

2023Journal article Open access
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dc.contributor.authorCangussu, Nara
dc.contributor.authorMatos, Ana Mafalda
dc.contributor.authorMilheiro-Oliveira, Paula
dc.contributor.authorMaia, Lino
dc.date.accessioned2024-02-02T14:44:14Z
dc.date.available2024-02-02T14:44:14Z
dc.date.issued2023
dc.description.abstractThe use of SCC in Europe began in the 1990s and was mainly promoted by the precast industry. Precast companies generally prefer high early-strength concrete mixtures to accelerate their production rate, reducing the demoulding time. From a materials science point of view, self-compacting and high early-strength concrete mixes may be challenging because they present contradicting mixture design requirements. For example, a low water/binder ratio (w/b) is key to achieving high early strength. However, it may impact the self-compacting ability, which is very sensitive to Vw/Vp. As such, the mixture design can be complex. The design of the experimental approach is a powerful tool for designing, predicting, and optimising advanced cement-based materials when several constituent materials are employed and multi-performance requirements are targeted. The current work aimed at fitting models to mathematically describe the flow ability, viscosity, and mechanical strength properties of high-performance self-compacting cement-based mortars based on a central composite design. The statistical fitted models revealed that Vs/Vm exhibited the strongest (negative) effect on the slump-flow diameter and T-funnel time. Vw/Vp showed the most significant effect on mechanical strength. Models were then used for mortar optimisation. The proposed optimal mixture represents the best compromise between self-compacting ability—a flow diameter of 250 mm and funnel time equal to 10 s—and compressive strength higher than 50 MPa at 24 h without any special curing treatment.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCangussu, N.; Matos, A.M.; Milheiro-Oliveira, P.; Maia, L. Numerical Design and Optimisation of Self-Compacting High Early-Strength Cement-Based Mortars. Appl. Sci. 2023, 13, 4142. https://doi.org/10.3390/ app13074142pt_PT
dc.identifier.doi10.3390/app13074142pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/5521
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationInstitute of R&D in Structures and Construction
dc.relationNot Available
dc.relationCement-based composites shift to Industry 4.0: performance-based mix design methodology, assessment and quality control
dc.relationCentre of Mathematics of the University of Porto
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectSelf-compacting concretept_PT
dc.subjectHigh early strengthpt_PT
dc.subjectMixture designpt_PT
dc.subjectDesign of experimentspt_PT
dc.subjectResponse modelpt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.titleNumerical Design and Optimisation of Self-Compacting High Early-Strength Cement-Based Mortarspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleInstitute of R&D in Structures and Construction
oaire.awardTitleNot Available
oaire.awardTitleCement-based composites shift to Industry 4.0: performance-based mix design methodology, assessment and quality control
oaire.awardTitleCentre of Mathematics of the University of Porto
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04708%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC INST 2018/CEECINST%2F00049%2F2018%2FCP1524%2FCT0001/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/CEEC IND4ed/2021.01765.CEECIND%2FCP1679%2FCT0004/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00144%2F2020/PT
oaire.citation.issue7pt_PT
oaire.citation.startPage4142pt_PT
oaire.citation.titleApplied Sciencespt_PT
oaire.citation.volume13pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamCEEC INST 2018
oaire.fundingStreamCEEC IND4ed
oaire.fundingStream6817 - DCRRNI ID
person.familyNameSerra Maia
person.givenNameLino Manuel
person.identifierR-000-97W
person.identifier.ciencia-idB711-823E-18C5
person.identifier.orcid0000-0002-6371-0179
person.identifier.scopus-author-id37051068400
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscovery3843bbca-e366-4c2f-ba3a-1b950a201d4b
relation.isProjectOfPublicationabd7f324-6515-4266-9436-ffcb0514f942
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