Optimization of compounding ratio of fume-suppressing asphalt and evaluation of its effect of fume suppression

doi:10.16085/j.issn.1000-6613.2023-0613

Abstract

Abstract:

In order to suppress the generation of asphalt fumes at high temperatures and reduce the level of environmental pollution and the health impact of operators, the optimization study of the compounding ratio of fume-suppressing asphalt was carried out. Based on the needle penetration, ductility and softening point of single-doped fume-suppressing asphalt and the fume production test results of the asphalt under the self-research device, the optimization of the ratio of fume-suppressing asphalt was carried out by combining entropy weight method and genetic algorithm, and analysis of the dispersion uniformity and storage stability of the optimized fume suppressant in asphalt and its effect on the characteristic functional groups of asphalt. The high, medium and low temperature performance tests of fume-suppressing asphalt based on the optimized compounding ratio were carried out, and the effect of fume suppression was evaluated to verify the effectiveness of the optimized compounding ratio method. The main conclusions were as follows. The fume suppressant was uniformly dispersed in the asphalt and did not change the characteristic functional groups of asphalt. The optimized compounded fume-suppressing asphalt met the storage stability requirements. The optimized compounding of fume suppressant improved high and low temperature performance of asphalt and enhanced the medium temperature fatigue performance of asphalt. The color change of the filter tube before and after the asphalt fume collection indicated that the asphalt fume enrichment method was highly reliable. The optimized compounding fume-suppressing asphalt had a significant effect of fume suppression and the maximum fume suppression rate was 99.7%. The small difference between the predicted and measured values of the indicators proved the reliability of the optimized compounding ratio method.

Key words: fume-suppressing asphalt, entropy weight method, genetic algorithm, effect of fume suppression

摘要：

为抑制沥青在高温下烟气的产生，降低环境污染及对作业人员健康的影响程度，本文进行了抑烟沥青复掺配比优化研究。基于单掺抑烟沥青的针入度、延度及软化点及自制沥青烟生成富集装置的沥青产烟结果，结合熵权法与遗传算法进行抑烟沥青复掺配比优化，并分析优化复掺抑烟剂在沥青中的分散均匀性、储存稳定性及其对沥青特征官能团的影响；基于优化复掺配比的抑烟沥青高、中、低温性能测试，并对其抑烟效果进行评价，验证优化复掺配比方法的有效性。研究表明：抑烟剂均匀分散于沥青中，且未对沥青特征官能团产生改变，优化复掺抑烟沥青满足储存稳定性要求。优化复掺抑烟剂对沥青高、低温性能具有改善作用，并提升了沥青中温抗疲劳性能。沥青烟收集前后滤管颜色变化表明该沥青烟富集方式具有较高的可靠性，且优化复掺抑烟沥青具有显著抑烟效果，最大抑烟率为99.7%。优化复掺配比下的指标预测值与实测值差异较小，证明了该优化复掺配比方法的可靠性。

关键词: 抑烟沥青, 熵权法, 遗传算法, 抑烟效果

CLC Number:

TU535

LI Ping, CHEN Xiule, ZHANG Qiang, NIAN Tengfei, WANG Yuxing, WANG Meng. Optimization of compounding ratio of fume-suppressing asphalt and evaluation of its effect of fume suppression[J]. Chemical Industry and Engineering Progress, 2024, 43(4): 1923-1933.

李萍, 陈修乐, 张强, 念腾飞, 王育兴, 王盟. 抑烟沥青复掺配比优化及抑烟效果评价[J]. 化工进展, 2024, 43(4): 1923-1933.

Figures/Tables 22

References 24

1	《中国公路学报》编辑部. 中国路面工程学术研究综述·2020[J]. 中国公路学报, 2020, 33(10): 1-66.
	Editorial Department of China Journal of Highway and Transport. Review on China’s pavement engineering Research·2020[J]. China Journal of Highway and Transport, 2020, 33(10): 1-66.
2	LIANG Yafeng, TANG Xuejiao, ZHU Qing, et al. A review: Application of tourmaline in environmental fields[J]. Chemosphere, 2021, 281: 130780.
3	YANG Jun, LI Zuyuan, XU Xinquan. Preparation and evaluation of cooling asphalt concrete modified with SBS and tourmaline anion powder[J]. Journal of Cleaner Production, 2021, 289: 125135.
4	THIVES Liseane Padilha, GHISI Enedir. Asphalt mixtures emission and energy consumption: A review[J]. Renewable and Sustainable Energy Reviews, 2017, 72: 473-484.
5	杨小龙, 申爱琴, 蒋宜馨, 等. 基于阻燃抑烟的纳米黏土改性沥青综述[J]. 交通运输工程学报, 2021, 21(5): 42-61.
	YANG Xiaolong, SHEN Aiqin, JIANG Yixin, et al. Review on nano clay modified asphalt based on flame retardant and smoke suppression[J]. Journal of Traffic and Transportation Engineering, 2021, 21(5): 42-61.
6	王朝辉, 李彦伟, 葛娟, 等. Tourmaline改性沥青及其混合料热拌减排性能[J]. 中国公路学报, 2014, 27(11): 17-24.
	WANG Chaohui, LI Yanwei, GE Juan, et al. Emission reduction effect of tourmaline modified asphalt and its mixtures under condition of hot-mix[J]. China Journal of Highway and Transport, 2014, 27(11): 17-24.
7	YANG Xiaolong, SHEN A, JIANG Yixin, et al. Properties and mechanism of flame retardance and smoke suppression in asphalt binder containing organic montmorillonite[J]. Construction and Building Materials, 2021, 302: 124148.
8	ABDULLAH Mohd Ezree, HAININ Mohd Rosli, YUSOFF Nur Izzi MD, et al. Laboratory evaluation on the characteristics and pollutant emissions of nanoclay and chemical warm mix asphalt modified binders[J]. Construction and Building Materials, 2016, 113: 488-497.
9	XU Tao, WANG Yang, XIA Wenjing, et al. Effects of flame retardants on thermal decomposition of SARA fractions separated from asphalt binder[J]. Construction and Building Materials, 2018, 173: 209-219.
10	PEI Jianzhong, WEN Yong, LI Yanwei, et al. Flame-retarding effects and combustion properties of asphalt binder blended with organo montmorillonite and alumina trihydrate[J]. Construction and Building Materials, 2014, 72: 41-47.
11	郭寅川, 王涵, 申爱琴, 等. ATH/OMMT复合改性沥青阻燃抑烟性能与机理分析[J]. 硅酸盐通报, 2020, 39(6): 1989-1997.
	GUO Yinchuan, WANG Han, SHEN Aiqin, et al. Analysis of flame-retarding and smoke suppressing performance and mechanism of ATH/OMMT modified asphalt[J]. Bulletin of the Chinese Ceramic Society, 2020, 39(6): 1989-1997.
12	ZHAO H, LI H P, LIAO K J. Study on properties of flame retardant asphalt for tunnel[J]. Petroleum Science and Technology, 2010, 28(11): 1096-1107.
13	金雷, 魏建国, 付其林, 等. DBDPE复合阻燃剂对SBS沥青性能的影响[J]. 长安大学学报(自然科学版), 2020, 40(2): 47-55, 65.
	JIN Lei, WEI Jianguo, FU Qilin, et al. Effect of DBDPE composite flame retardant on the performance of SBS asphalt[J]. Journal of Chang’an University (Natural Science Edition), 2020, 40(2): 47-55, 65.
14	颜可珍, 刘沛, 王晓亮. 基于GEP算法的沥青混合料动模量预测[J]. 建筑材料学报, 2015, 18(6): 1106-1110.
	YAN Kezhen, LIU Pei, WANG Xiaoliang. Prediction of dynamic modulus of asphalt mixture based on gene expression programming algorithm[J]. Journal of Building Materials, 2015, 18(6): 1106-1110.
15	童申家, 谢祥兵, 赵大勇, 等. 紫外光老化后沥青混合料路用性能非线性预测[J]. 建筑材料学报, 2016, 19(1): 105-110.
	TONG Shenjia, XIE Xiangbing, ZHAO Dayong, et al. Nonlinear prediction of road performance of asphalt mixture after ultraviolet aging[J]. Journal of Building Materials, 2016, 19(1): 105-110.
16	赵永祯, 李梦, 王选仓, 等. 基于聚类分析改性沥青混合料性能分级研究[J]. 建筑材料学报, 2014, 17(3): 437-445.
	ZHAO Yongzhen, LI Meng, WANG Xuancang, et al. Research on performance classification of modified asphalt mixture based on clustering algorithm[J]. Journal of Building Materials, 2014, 17(3): 437-445.
17	NIAN Tengfei, LI Jinggao, LI Ping, et al. Method to predict the interlayer shear strength of asphalt pavement based on improved back propagation neural network[J]. Construction and Building Materials, 2022, 351: 128969.
18	OMAR Hend ALI, YUSOFF Nur Izzi Md, CEYLAN Halil, et al. Determining the water damage resistance of nano-clay modified bitumens using the indirect tensile strength and surface free energy methods[J]. Construction and Building Materials, 2018, 167: 391-402.
19	YANG Xiaolong, SHEN Aiqin, SU Yuxuan, et al. Effects of alumina trihydrate (ATH) and organic montmorillonite (OMMT) on asphalt fume emission and flame retardancy properties of SBS-modified asphalt[J]. Construction and Building Materials, 2020, 236(6): 117576.
20	YE Qunshan, DONG Wenzhuo, WANG Shipei, et al. Research on the rheological characteristics and aging resistance of asphalt modified with tourmaline[J]. Materials, 2019, 13(1): 69.
21	CHEN Qian, WANG Chaohui, QIAO Zhi, et al. Graphene/tourmaline composites as a filler of hot mix asphalt mixture: Preparation and properties[J]. Construction and Building Materials, 2020, 239: 117859.
22	ZHANG Xiaorui, ZHOU Xinxing, XU Xinquan, et al. Enhancing the functional and environmental properties of asphalt binders and asphalt mixtures using tourmaline anion powder modification[J]. Coatings, 2021, 11(5): 550.
23	LI Ping, WANG Meng, NIAN Tengfei, et al. Asphalt fume generation-enrichment device development and fume production estimation model[J]. Advances in Civil Engineering Materials, 2021, 10(1): 453-467.
24	张喜军, 仝配配, 蔺习雄, 等. 基于线性振幅扫描试验评价硬质沥青的疲劳性能[J]. 材料导报, 2021, 35(18): 18083-18089.
	ZHANG Xijun, TONG Peipei, LIN Xixiong, et al. Fatigue characterization of hard petroleum asphalt based on the linear amplitude sweep test[J]. Materials Reports, 2021, 35(18): 18083-18089.

指标	测试结果		技术要求
指标	SK	ZH	技术要求
针入度（25℃）/0.1mm	83	84	80~100
延度（10℃）/cm	56	58	≥35
软化点/℃	47.9	46.8	42~52
RTFOT后残留物
质量损失/%	-0.03	-0.53	≤±0.4
残留针入度比/%	60.8	65.2	≥57
残留延度/cm	11.8	12	≥8

指标	测试结果		技术要求
指标	SK	ZH	技术要求
针入度（25℃）/0.1mm	83	84	80~100
延度（10℃）/cm	56	58	≥35
软化点/℃	47.9	46.8	42~52
RTFOT后残留物
质量损失/%	-0.03	-0.53	≤±0.4
残留针入度比/%	60.8	65.2	≥57
残留延度/cm	11.8	12	≥8

运算参数	数值
初始种群数	100
交叉概率	0.4
变异概率	0.05
最大迭代次数	200

运算参数	数值
初始种群数	100
交叉概率	0.4
变异概率	0.05
最大迭代次数	200

抑烟沥青种类	针入度/0.1mm	延度（10℃）/cm	软化点/℃	抑烟率/%
电气石（325目）-12%	75.3	37.4	46.9	25.5
电气石（325目）-14%	73.6	35.7	47.1	26.2
电气石（325目）-16%	72.7	33.4	47.3	38.5
电气石（325目）-18%	71.0	30.5	47.5	34.4
电气石（800目）-12%	73.7	34.8	45.8	46.7
电气石（800目）-14%	72.5	32.8	46.7	61.1
电气石（800目）-16%	70.8	29.1	47.1	78.1
电气石（800目）-18%	68.4	26.8	47.4	71.8
电气石（1250目）-12%	73.3	33.0	45.0	29.3
电气石（1250目）-14%	71.3	31.2	45.5	32.3
电气石（1250目）-16%	69.2	28.0	46.6	84.6
电气石（1250目）-18%	67.8	26.2	47.0	76.8
电气石（2000目）-12%	76.9	35.2	46.9	58.3
电气石（2000目）-14%	76.2	33.9	47.1	59.5
电气石（2000目）-16%	75.4	32.4	47.4	91.3
电气石（2000目）-18%	73.4	29.9	48.1	86.2
电气石（5000目）-12%	83.2	36.0	47.7	63.7
电气石（5000目）-14%	82.6	34.8	47.8	72.3
电气石（5000目）-16%	80.9	33.6	47.9	86.2
电气石（5000目）-18%	76.5	31.2	48.3	58.5
电气石（10000目）-12%	71	34.9	46.4	40.3
电气石（10000目）-14%	71.2	33.6	46.9	63.7
电气石（10000目）-16%	69.1	29.5	47.8	90.2
电气石（10000目）-18%	67.6	28.7	48.4	88.7
有机蒙脱土-6%	81.8	39.3	49.1	84.9
有机蒙脱土-8%	83.9	37.7	52.0	86.4
有机蒙脱土-10%	86.3	37.3	55.6	97.6
有机蒙脱土-12%	88.5	35.2	62.2	88.2
无机蒙脱土-6%	83.7	40.0	49.1	41.6
无机蒙脱土-8%	82.2	42.1	47.7	57.3
无机蒙脱土-10%	79.8	37.9	48.2	85.6
无机蒙脱土-12%	78.9	35.4	48.7	58.2
聚丙烯-1%	53.9	27.1	48.8	48.6
聚丙烯-2%	58.2	27.9	48.1	31.8
聚丙烯-3%	61.0	31.2	48.1	24.9
聚丙烯-4%	59.3	31.6	48.8	35.7
聚苯乙烯-1%	80.7	76.0	46.2	70.4
聚苯乙烯-2%	73.9	27.7	47.1	40.5
聚苯乙烯-3%	69.2	17.5	47.6	43.1
聚苯乙烯-4%	47.7	9.9	50.4	79.4
Mg(OH)₂-6%	70.5	32.8	49.2	53.1
Mg(OH)₂-8%	73.7	27.9	51.1	66.2
Mg(OH)₂-10%	68.3	24.6	52.8	88.7
Mg(OH)₂-12%	66.3	24.0	54.1	47.8
Al(OH)₃-6%	76.8	35.0	46.2	33.8
Al(OH)₃-8%	75.2	25.7	47.1	38.0
Al(OH)₃-10%	73.1	23.5	47.6	75.7
Al(OH)₃-12%	72.7	20.8	50.4	71.9
C-1%	68.1	36.0	45.6	83.4
C-2%	58.6	27.7	47.1	29.4
C-3%	61.2	17.5	47.6	83.0
C-4%	56.8	9.9	50.4	72.6
三聚氰胺-1%	80.9	26.0	46.2	53.6
三聚氰胺-2%	79.9	17.7	48.9	45.3
三聚氰胺-3%	81.8	15.5	49.7	15.7
三聚氰胺-4%	83.6	11.9	50.4	87.8