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...

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Main Authors: Kuo Ji, Changchun Shi, Jing Jiang, Yaogang Tian, Xiaowei Zhou, Rui Xiong
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Polymers
Subjects:
Online Access:https://www.mdpi.com/2073-4360/15/4/807
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author Kuo Ji
Changchun Shi
Jing Jiang
Yaogang Tian
Xiaowei Zhou
Rui Xiong
author_facet Kuo Ji
Changchun Shi
Jing Jiang
Yaogang Tian
Xiaowei Zhou
Rui Xiong
author_sort Kuo Ji
collection DOAJ
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.
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spelling doaj.art-e74de147cccd46a68b8cad7dace750762023-11-16T22:50:13ZengMDPI AGPolymers2073-43602023-02-0115480710.3390/polym15040807Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of AggregatesKuo Ji0Changchun Shi1Jing Jiang2Yaogang Tian3Xiaowei Zhou4Rui Xiong5School of Materials Science and Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Materials Science and Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Materials Science and Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Materials Science and Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Materials Science and Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Materials Science and Engineering, Chang’an University, Xi’an 710064, ChinaThis 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.https://www.mdpi.com/2073-4360/15/4/807steel slagsteel slag asphalt mixtureaggregate mineral compositionlong-term skid resistancedifferential polishingsurface texture richness
spellingShingle Kuo Ji
Changchun Shi
Jing Jiang
Yaogang Tian
Xiaowei Zhou
Rui Xiong
Determining the Long-Term Skid Resistance of Steel Slag Asphalt Mixture Based on the Mineral Composition of Aggregates
Polymers
steel slag
steel slag asphalt mixture
aggregate mineral composition
long-term skid resistance
differential polishing
surface texture richness
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 steel slag
steel slag asphalt mixture
aggregate mineral composition
long-term skid resistance
differential polishing
surface texture richness
url https://www.mdpi.com/2073-4360/15/4/807
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