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Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates
This study intends to predict the long-term skid resistance of steel slag asphalt mixture (SSAM) from the mineral composition of the aggregates. The polished stone value (PSV) and mineral composition of the aggregates were assessed using the accelerated polishing test and X-ray diffraction, respecti...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9966793/ https://www.ncbi.nlm.nih.gov/pubmed/36850091 http://dx.doi.org/10.3390/polym15040807 |
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author | Ji, Kuo Shi, Changchun Jiang, Jing Tian, Yaogang Zhou, Xiaowei Xiong, Rui |
author_facet | Ji, Kuo Shi, Changchun Jiang, Jing Tian, Yaogang Zhou, Xiaowei Xiong, Rui |
author_sort | Ji, Kuo |
collection | PubMed |
description | This study intends to predict the long-term skid resistance of steel slag asphalt mixture (SSAM) from the mineral composition of the aggregates. The polished stone value (PSV) and mineral composition of the aggregates were assessed using the accelerated polishing test and X-ray diffraction, respectively. The hardness (H) and surface texture richness (STR) of the aggregates were calculated from the mineral composition of the aggregates, and then a multivariate linear model was established between PSV and H and STR. The British pendulum number (BPN) and three-dimensional morphology of the SSAM were then evaluated using a British pendulum and a pavement laser scanner, respectively. Finally, an exponential relationship was established between BPN, aggregate PSV, and various aggregate amounts of SSAM. The results show that steel slag with H, STR, and PSV was better than natural aggregates and can significantly improve the skid resistance of pavement, but the relationship between steel slag content and long-term skid resistance of SSAM was not linear, and SSAM with 50% steel slag content had the best skid resistance. The mathematical model developed can predict the long-term skid resistance of SSAM from the mineral composition of the aggregates. The model can be used by designers to predict the long-term skid resistance of steel slag asphalt pavements at the design stage and thus better determine the proportion of steel slag to other aggregates. |
format | Online Article Text |
id | pubmed-9966793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99667932023-02-26 Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates Ji, Kuo Shi, Changchun Jiang, Jing Tian, Yaogang Zhou, Xiaowei Xiong, Rui Polymers (Basel) Article This study intends to predict the long-term skid resistance of steel slag asphalt mixture (SSAM) from the mineral composition of the aggregates. The polished stone value (PSV) and mineral composition of the aggregates were assessed using the accelerated polishing test and X-ray diffraction, respectively. The hardness (H) and surface texture richness (STR) of the aggregates were calculated from the mineral composition of the aggregates, and then a multivariate linear model was established between PSV and H and STR. The British pendulum number (BPN) and three-dimensional morphology of the SSAM were then evaluated using a British pendulum and a pavement laser scanner, respectively. Finally, an exponential relationship was established between BPN, aggregate PSV, and various aggregate amounts of SSAM. The results show that steel slag with H, STR, and PSV was better than natural aggregates and can significantly improve the skid resistance of pavement, but the relationship between steel slag content and long-term skid resistance of SSAM was not linear, and SSAM with 50% steel slag content had the best skid resistance. The mathematical model developed can predict the long-term skid resistance of SSAM from the mineral composition of the aggregates. The model can be used by designers to predict the long-term skid resistance of steel slag asphalt pavements at the design stage and thus better determine the proportion of steel slag to other aggregates. MDPI 2023-02-06 /pmc/articles/PMC9966793/ /pubmed/36850091 http://dx.doi.org/10.3390/polym15040807 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ji, Kuo Shi, Changchun Jiang, Jing Tian, Yaogang Zhou, Xiaowei Xiong, Rui Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates |
title | Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates |
title_full | Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates |
title_fullStr | Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates |
title_full_unstemmed | Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates |
title_short | Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates |
title_sort | determining the long-term skid resistance of steel slag asphalt mixture based on the mineral composition of aggregates |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9966793/ https://www.ncbi.nlm.nih.gov/pubmed/36850091 http://dx.doi.org/10.3390/polym15040807 |
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