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Detection and Quantification of Cracking in Concrete Aggregate through Virtual Data Fusion of X-ray Computed Tomography Images

  • In this work, which is part of a larger research program, a framework called “virtual data fusion“ was developed to provide an automated and consistent crack detection method that allows for the cross-comparison of results from large quantities of X-ray Computed Tomography (CT) data. A partial implementation of this method in a custom program was developed for use in research focused on crack quantification in Alkali-Silica Reaction (ASR)-sensitive concrete aggregates. During the CT image processing, a series of image analyses tailored for detecting specific, individual crack-like characteristics were completed. The results of these analyses were then “fused” in order to identify crack-like objects within the images with much higher accuracy than that yielded by any individual image analysis procedure. The results of this strategy demonstrated the success of the program in effectively identifying crack-like structures and quantifying characteristics, such as surface area and volume.In this work, which is part of a larger research program, a framework called “virtual data fusion“ was developed to provide an automated and consistent crack detection method that allows for the cross-comparison of results from large quantities of X-ray Computed Tomography (CT) data. A partial implementation of this method in a custom program was developed for use in research focused on crack quantification in Alkali-Silica Reaction (ASR)-sensitive concrete aggregates. During the CT image processing, a series of image analyses tailored for detecting specific, individual crack-like characteristics were completed. The results of these analyses were then “fused” in order to identify crack-like objects within the images with much higher accuracy than that yielded by any individual image analysis procedure. The results of this strategy demonstrated the success of the program in effectively identifying crack-like structures and quantifying characteristics, such as surface area and volume. The results demonstrated that the source of aggregate has a very significant impact on the amount of internal cracking, even when the mineralogical characteristics remain very similar. River gravels, for instance, were found to contain significantly higher levels of internal cracking than quarried stone aggregates of the same mineralogical type.zeige mehrzeige weniger

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Metadaten
Autor*innen:Tyler OeschORCiD, Frank WeiseORCiD, Giovanni BrunoORCiD
Dokumenttyp:Zeitschriftenartikel
Veröffentlichungsform:Verlagsliteratur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):Materials
Jahr der Erstveröffentlichung:2020
Organisationseinheit der BAM:7 Bauwerkssicherheit
7 Bauwerkssicherheit / 7.1 Baustoffe
8 Zerstörungsfreie Prüfung
8 Zerstörungsfreie Prüfung / 8.5 Röntgenbildgebung
Veröffentlichende Institution:Bundesanstalt für Materialforschung und -prüfung (BAM)
Verlag:MDPI
Verlagsort:Basel, Switzerland
Jahrgang/Band:13
Ausgabe/Heft:18
Erste Seite:Paper 3921
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurbau
Freie Schlagwörter:ASR-Sensitive Aggregate; Alkali-Silica Reaction (ASR); Crack Detection; Damage Quantification; X-ray Computed Tomography (CT)
Themenfelder/Aktivitätsfelder der BAM:Chemie und Prozesstechnik
Infrastruktur
DOI:10.3390/ma13183921
URN:urn:nbn:de:kobv:b43-512170
Verfügbarkeit des Dokuments:Datei für die Öffentlichkeit verfügbar ("Open Access")
Lizenz (Deutsch):License LogoCreative Commons - CC BY - Namensnennung 4.0 International
Datum der Freischaltung:14.09.2020
Referierte Publikation:Ja
Datum der Eintragung als referierte Publikation:14.09.2020
Schriftenreihen ohne Nummerierung:Wissenschaftliche Artikel der BAM
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