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Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting Genetic Algorithm

The use of steel slag powder instead of filler to prepare asphalt mortar was beneficial to realize the effective utilization of steel slag and improve the performance of asphalt concrete. Nevertheless, the anti-aging properties of steel-slag powder–asphalt mortar need to be further enhanced. This st...

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Autores principales: Lv, Yang, Wu, Shaopeng, Cui, Peide, Amirkhanian, Serji, Xu, Haiqin, Zou, Yingxue, Yang, Xinkui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9143452/
https://www.ncbi.nlm.nih.gov/pubmed/35629660
http://dx.doi.org/10.3390/ma15103635
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author Lv, Yang
Wu, Shaopeng
Cui, Peide
Amirkhanian, Serji
Xu, Haiqin
Zou, Yingxue
Yang, Xinkui
author_facet Lv, Yang
Wu, Shaopeng
Cui, Peide
Amirkhanian, Serji
Xu, Haiqin
Zou, Yingxue
Yang, Xinkui
author_sort Lv, Yang
collection PubMed
description The use of steel slag powder instead of filler to prepare asphalt mortar was beneficial to realize the effective utilization of steel slag and improve the performance of asphalt concrete. Nevertheless, the anti-aging properties of steel-slag powder–asphalt mortar need to be further enhanced. This study used antioxidants and UV absorbers in steel-slag powder–asphalt mortar to simultaneously improve its thermal-oxidation and UV-aging properties. The dosage of modifier was optimized by second-generation non-inferior sorting genetic algorithm. Fourier-Transform Infrared Spectroscopy, a dynamic shear rheometer and the heavy-metal-ion-leaching test were used to evaluate the characteristic functional groups, rheological properties and heavy-metal-toxicity characteristics of the steel-slag-powder-modified asphalt mortar, respectively. The results showed that there was a significant correlation between the amount of modifier and G*, δ, and the softening point. When the first peak appeared for G*, δ, and the softening point, the corresponding dosages of x(1) were 2.15%, 1.0%, and 1.1%, respectively, while the corresponding dosage of x(2) were 0.25%, 0.76%, and 0.38%, respectively. The optimal value of the modifier dosage x(1) was 1.2% and x(2) was 0.5% after weighing by the NSGA-II algorithm. The asphalt had a certain physical solid-sealing effect on the release of heavy-metal ions in the steel-slag powder. In addition, the asphalt structure was changed under the synergistic effect of oxygen and ultraviolet rays. Therefore, the risk of leaching heavy-metal ions was increased with the inferior asphalt-coating performance on the steel-slag powder.
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spelling pubmed-91434522022-05-29 Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting Genetic Algorithm Lv, Yang Wu, Shaopeng Cui, Peide Amirkhanian, Serji Xu, Haiqin Zou, Yingxue Yang, Xinkui Materials (Basel) Article The use of steel slag powder instead of filler to prepare asphalt mortar was beneficial to realize the effective utilization of steel slag and improve the performance of asphalt concrete. Nevertheless, the anti-aging properties of steel-slag powder–asphalt mortar need to be further enhanced. This study used antioxidants and UV absorbers in steel-slag powder–asphalt mortar to simultaneously improve its thermal-oxidation and UV-aging properties. The dosage of modifier was optimized by second-generation non-inferior sorting genetic algorithm. Fourier-Transform Infrared Spectroscopy, a dynamic shear rheometer and the heavy-metal-ion-leaching test were used to evaluate the characteristic functional groups, rheological properties and heavy-metal-toxicity characteristics of the steel-slag-powder-modified asphalt mortar, respectively. The results showed that there was a significant correlation between the amount of modifier and G*, δ, and the softening point. When the first peak appeared for G*, δ, and the softening point, the corresponding dosages of x(1) were 2.15%, 1.0%, and 1.1%, respectively, while the corresponding dosage of x(2) were 0.25%, 0.76%, and 0.38%, respectively. The optimal value of the modifier dosage x(1) was 1.2% and x(2) was 0.5% after weighing by the NSGA-II algorithm. The asphalt had a certain physical solid-sealing effect on the release of heavy-metal ions in the steel-slag powder. In addition, the asphalt structure was changed under the synergistic effect of oxygen and ultraviolet rays. Therefore, the risk of leaching heavy-metal ions was increased with the inferior asphalt-coating performance on the steel-slag powder. MDPI 2022-05-19 /pmc/articles/PMC9143452/ /pubmed/35629660 http://dx.doi.org/10.3390/ma15103635 Text en © 2022 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
Lv, Yang
Wu, Shaopeng
Cui, Peide
Amirkhanian, Serji
Xu, Haiqin
Zou, Yingxue
Yang, Xinkui
Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting Genetic Algorithm
title Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting Genetic Algorithm
title_full Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting Genetic Algorithm
title_fullStr Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting Genetic Algorithm
title_full_unstemmed Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting Genetic Algorithm
title_short Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting Genetic Algorithm
title_sort optimization of asphalt-mortar-aging-resistance-modifier dosage based on second-generation non-inferior sorting genetic algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9143452/
https://www.ncbi.nlm.nih.gov/pubmed/35629660
http://dx.doi.org/10.3390/ma15103635
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