响应面法-灰关联分析优化活化胶粉/SBR复合改性沥青掺量研究

何东坡1, 潘志强1*, 王宏光1,2, 杜文鑫2

化工新型材料 ›› 2022, Vol. 50 ›› Issue (1) : 187 -191.

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化工新型材料 ›› 2022, Vol. 50 ›› Issue (1) : 187-191. DOI: 10.19817/j.cnki.issn1006-3536.2022.01.038
科学研究

响应面法-灰关联分析优化活化胶粉/SBR复合改性沥青掺量研究

    何东坡1, 潘志强1*, 王宏光1,2, 杜文鑫2
作者信息 +

Optimizing the content of activated crumb rubber and SBR composite modified asphalt by response surface methodology-grey relation analysis

  • He Dongpo1, Pan Zhiqiang1, Wang Hongguang1,2, Du Wenxin2
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文章历史 +
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摘要

为提升沥青的综合性能,采用废食用油对废胶粉进行活化处理,复配丁苯橡胶(SBR)制备复合改性沥青。采用响应面法中的Box-Behnken设计方法,分别对不同掺量废食用油、废胶粉、SBR制备的复合改性沥青进行三大指标和135℃旋转黏度性能测试,利用灰关联分析对沥青的性能进行综合评价,建立关联度的响应面数学模型,得出各改性剂的最优掺量。结果表明,选用响应面法-灰关联分析可以很好地对沥青改性剂的掺量进行优化;当废食用油掺量为10%、废胶粉掺量为10%、SBR掺量为5%时,制得的复合改性沥青综合性能最优,且关联度的预测值与实际值相对误差仅为2.45%,拟合程度较高。

Abstract

In order to improve the comprehensive performance of asphalt,waste cooking oil was used to activate the waste crumb rubber and compounded with butadiene styrene rubber(SBR) to prepare composite modified asphalt.The Box-Behnken design method in the response surface methodology was selected to test and analyzed the three major indicators of asphalt and the rotational viscosity at 135°C.The correlation degree in the grey relation analysis was used to comprehensively evaluate the performance of the asphalt to establish a response surface with correlation degree mathematical model,thereby obtaining the optimal dosage of each modifier.The results showed that the selection of response surface methodology-grey relation analysis could optimize the content of asphalt modifiers.The optimal content of modifiers for the asphalt were:10% waste cooking oil,10% waste crumb rubber,5% SBR,the relative error between the predicted value and the actual value of the correlation degree was 2.45%,which showed a high degree of fit.

关键词

活化胶粉 / 丁苯橡胶 / 响应面法 / 灰关联分析 / 复合改性沥青 / 改性剂掺量

Key words

activated crumb rubber / SBR / response surface methodology / grey relation analysis / composite modified asphalt / modifier content

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响应面法-灰关联分析优化活化胶粉/SBR复合改性沥青掺量研究[J]. 化工新型材料, 2022, 50(1): 187-191 DOI:10.19817/j.cnki.issn1006-3536.2022.01.038

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基金资助

国家自然科学基金(51708092);中国博士后科学基金资助项目(2018M631894)

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