Show simple item record

FTIR spectroscopy and multivariate discriminant analysis for classifying bituminous mastics: Exploring aging states and mastic composition

dc.date.accessioned2024-07-22T15:03:03Z
dc.date.available2024-07-22T15:03:03Z
dc.date.issued2024-07-02
dc.identifierdoi:10.17170/kobra-2024070910501
dc.identifier.urihttp://hdl.handle.net/123456789/15933
dc.description.sponsorshipGefördert im Rahmen des Projekts DEALger
dc.language.isoeng
dc.rightsNamensnennung 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectbituminous masticseng
dc.subjectFTIR spectroscopyeng
dc.subjectmultivariate discriminant analysiseng
dc.subjectmachine learningeng
dc.subjectdata miningeng
dc.subject.ddc500
dc.subject.ddc600
dc.titleFTIR spectroscopy and multivariate discriminant analysis for classifying bituminous mastics: Exploring aging states and mastic compositioneng
dc.typeAufsatz
dcterms.abstractThis study aimed to differentiate among various bituminous mastics through the analysis of FTIR spectroscopy data. The mastics, incorporating three filler types, a 50/70 penetration index binder, and foamed bitumen, underwent chemical examination via FTIR spectroscopy after exposure to various aging cycles. Employing different multivariate discriminant analysis approaches, the investigation identified an optimal method, i.e., PLSR-LDA, which achieved a prediction precision of 100 % in distinguishing between various types of mixtures. The governing wavenumbers in the classification were determined through PLSR-LDA analysis by calculating VIP scores. Next, integrals associated with the highlighted wavenumber regions served as input to the DT classifier, resulting in classification with the prediction precisions of 96 % and 88 % for mastic types and aging states, respectively. The subsequent analysis underscored the significance of the CaCo₃ absorption band in discriminating between different mastic types. Similarly, C-H stretching of CH₃ and carbonyl bands were identified as pivotal regions governing the classification based on aging states.eng
dcterms.accessRightsopen access
dcterms.creatorMotevalizadeh, Seyed Mohsen
dcterms.creatorMollenhauer, Konrad
dcterms.creatorWetekam, Jens
dc.relation.doidoi:10.1016/j.conbuildmat.2024.137188
dc.subject.swdFT-IR-Spektroskopieger
dc.subject.swdDiskriminanzanalyseger
dc.subject.swdMastixger
dc.subject.swdMaschinelles Lernenger
dc.subject.swdText Miningger
dc.subject.swdAlterungger
dc.type.versionpublishedVersion
dcterms.source.identifiereissn:1879-0526
dcterms.source.journalConstruction and Building Materialseng
dcterms.source.volumeVolume 438
kup.iskupfalse
dcterms.source.articlenumber137188


Files in this item

Thumbnail
Name:
license_rdf
Size:
908bytes
Format:
application/rdf+xml
View/Open
Thumbnail
Name:
1_s2_0_S0950061824023304_main.pdf
Size:
9.013Mb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record

Namensnennung 4.0 International
Except where otherwise noted, this item's license is described as Namensnennung 4.0 International