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Characterizing the Self-Healing Asphalt Materials: A Neutron Imaging Study
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.ORCID iD: 0000-0002-1827-1517
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.ORCID iD: 0000-0001-8260-2723
Laboratory for Neutron Scattering and Imaging, Paul Scherrer Institute, 5232, Villigen, Switzerland.
Department of Engineering Sciences, EMPA Materials Science and Technology, 8600, Dübendorf, Switzerland.
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2024 (English)In: Advanced Engineering Materials, ISSN 1438-1656, E-ISSN 1527-2648, Vol. 26, no 21, article id 2400764Article in journal (Refereed) Published
Abstract [en]

Given the significant role of asphaltic pavement in surface transportation systems, even minor enhancements in asphalt materials hold the potential for cost savings and reduced environmental impacts. The healing properties of asphalt have drawn interest for sustainability, yet much remains unknown about the causes and influencing factors. To leverage self-healing for extending pavement life, understanding the mechanisms and conditions that stimulate microcrack healing is essential. This study aims to investigate the dynamic progress of microcrack closure in asphalt mastics. The time-series evolution of crack closure led by self-healing is tracked by neutron computed tomography, with image processing facilitating volumetric analysis over a 7 h period. The study examines the healing process in mastic samples with three different sand filler contents (10, 20, and 30%). Results show that for all the investigated samples, the healing rate declines exponentially over time, with 100% recovery not achieved after 7 h at room temperature. Filler content-influenced healing speed and 20% sand demonstrate the best performance. Meanwhile, the healing performance varies within the 10% and 30% groups, depending on initial crack size. Additionally, the study finds that initial crack size influences healing behavior in the samples.

Place, publisher, year, edition, pages
Wiley , 2024. Vol. 26, no 21, article id 2400764
Keywords [en]
asphalt materials, image processing, neutron tomographies, self-healing, sustainabilities
National Category
Infrastructure Engineering
Identifiers
URN: urn:nbn:se:kth:diva-366519DOI: 10.1002/adem.202400764ISI: 001318599500001Scopus ID: 2-s2.0-85204731419OAI: oai:DiVA.org:kth-366519DiVA, id: diva2:1982541
Note

QC 20250708

Available from: 2025-07-08 Created: 2025-07-08 Last updated: 2025-07-08Bibliographically approved

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Liu, ZhuhuanCavalli, Maria ChiaraKringos, Nicole

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