Self-sensing behavior of hot asphalt mixture with steel fiber-based additive

Abstract: Scientists and engineers are consistently working to enhance the performance attributes of asphalt concrete mixtures. Pavement condition monitors, despite their high cost and long-term inaccuracies, are utilized for assessing pavement conditions and determining the level of deterioration. Consequently, they provide crucial data for the design, cost estimations, and development of pavement maintenance programmers. In recent times, there have been significant technological advancements and the introduction of new characteristics, such as the self-sensing feature. This study utilized this feature to build hot asphalt mixtures with several functionalities. The incorporation of conductive elements into asphalt mixtures enhances their electrical and mechanical characteristics. The objective of this study is to develop a hot asphalt mixture with electrical conductivity capable of detecting applied loads through conducting experimental tests such as the Marshall and compression tests. The asphalt grade used was between 40 and 50, and the aggregates were in proportions that met the Iraqi requirement. The asphalt mixture contained 2.5% steel fibers by volume, which were added to investigate their impact on the functional performance of the asphalt mixtures. An analysis was conducted on the samples’ behavior during the tests, revealing a discernible alteration in the electrical resistance measurement. This alteration demonstrated that the asphalt mixture detected the weights exerted upon it. The findings also indicated a rise in the Marshall stability metric. The advanced asphalt mixtures and their novel features allow for the monitoring of pavement conditions. Through the resolution of monitoring device issues, they additionally offer superior performance and extended lifespan.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Self-sensing behavior of hot asphalt mixture with steel fiber-based additive ; volume:14 ; number:1 ; year:2024 ; extent:14 ; Open engineering ; 14, Heft 1 (2024) (gesamt 14)

Beteiligte, Orts- und Zeitangaben

• Urheber: Obaid, Ahmed Wasfi ; Al-Dahawi, Ali ; Kawther, Khawla K. ; Abduljabbar, Ahmed Subhi

Weitere Informationen

• DOI: 10.1515/eng-2022-0603
• URN: urn:nbn:de:101:1-2406011708418.507322990811
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 14.08.2025, 10:44 MESZ