<p>Wax precipitation is a critical factor affecting the durability of wax-based WMA. To address the issues of high subjectivity and significant error associated with the conventional viscosity method for determining the WPT, this study proposes an enhanced WPT determination algorithm and systematically investigates the influence of warm-mix additive type, dosage, and external conditions on wax precipitation behavior. The algorithm integrates the viscous flow activation energy method with adaptive error range determination, leveraging the Arrhenius equation to significantly improve the accuracy and stability of WPT detection. Experiments were conducted using two SHRP asphalts and four wax-based warm-mix additives (PW, FW, AW, MW). Results indicate that the WMA mixed with PW exhibited the highest WPT due to its high content of high-carbon alkanes, whereas the WPT of FW WMA was the lowest. Additionally, WPT increased with a higher dosage of the warm-mix additive. Aging led to an increase in WPT, attributed to the reduction in light components. Both cooling rate and shear rate showed a negative correlation with WPT, as rapid cooling hindered effective heat exchange and the shear-thinning effect suppressed wax crystal formation. This study elucidates the relationship between wax precipitation rates and the chemical composition of the warm-mix additives, revealing that additives with a higher proportion of high-carbon alkanes result in a steeper slope of the viscosity-temperature curve and accelerate wax precipitation. The refined algorithm proposed herein offers a more reliable approach for analyzing asphalt wax precipitation characteristics, while the findings provide valuable insights for optimizing WMA formulations and processes.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Characterization of wax precipitation behavior in Warm-Mix asphalt

  • Yan Li,
  • Jiawei Huang

摘要

Wax precipitation is a critical factor affecting the durability of wax-based WMA. To address the issues of high subjectivity and significant error associated with the conventional viscosity method for determining the WPT, this study proposes an enhanced WPT determination algorithm and systematically investigates the influence of warm-mix additive type, dosage, and external conditions on wax precipitation behavior. The algorithm integrates the viscous flow activation energy method with adaptive error range determination, leveraging the Arrhenius equation to significantly improve the accuracy and stability of WPT detection. Experiments were conducted using two SHRP asphalts and four wax-based warm-mix additives (PW, FW, AW, MW). Results indicate that the WMA mixed with PW exhibited the highest WPT due to its high content of high-carbon alkanes, whereas the WPT of FW WMA was the lowest. Additionally, WPT increased with a higher dosage of the warm-mix additive. Aging led to an increase in WPT, attributed to the reduction in light components. Both cooling rate and shear rate showed a negative correlation with WPT, as rapid cooling hindered effective heat exchange and the shear-thinning effect suppressed wax crystal formation. This study elucidates the relationship between wax precipitation rates and the chemical composition of the warm-mix additives, revealing that additives with a higher proportion of high-carbon alkanes result in a steeper slope of the viscosity-temperature curve and accelerate wax precipitation. The refined algorithm proposed herein offers a more reliable approach for analyzing asphalt wax precipitation characteristics, while the findings provide valuable insights for optimizing WMA formulations and processes.