摘要
【目的】针对季节冻土地区渠道冻融破坏,分析微胶囊相变材料(microencapsulated phase change materials,mPCM)改良粉砂土层渠基的温度场,对改良粉砂土的导热系数进行研究。【方法】以mPCM为改良剂,掺入渠基粉砂土形成mPCM改良粉砂土;对mPCM改良粉砂土进行导热系数实验和内部结构表征;采用多元线性回归和支持向量机(support vector machine,SVM)方法分别建立mPCM改良粉砂土的导热系数预测模型。【结果】mPCM改良粉砂土导热系数与含水率、干密度、mPCM掺量有关,且受冰水相对含量、冰水相变潜热、mPCM相变潜热和mPCM填充密实作用的影响,具有明显的温度效应;mPCM改良粉砂土导热系数的变化与实验温度和mPCM相变温度有关,可分为快速降低、缓慢降低和逐步上升3个阶段;多元线性回归和SVM模型均能较好地拟合预测mPCM改良粉砂土的导热系数,但SVM模型更适用于表征mPCM改良粉砂土导热系数各影响因素间的非线性关系。【结论】mPCM改良粉砂土的导热系数提高能够有效调控渠基土温度场,减轻渠道冻害,且SVM模型能更加准确地进行导热系数预测。
Objective In regions with seasonal frozen ground,frost damage in channels is a common issue due to significant temperature fluc⁃tuations affecting the foundation soil.To address this challenge,phase change materials(PCMs)are being integrated into founda⁃tion soil to regulate soil temperature dynamics and mitigate frost damage.Understanding the thermal conductivity of PCMmodified soil is crucial for accurately analyzing temperature distribution.Experimental studies have highlighted several factors influencing soil thermal conductivity,including temperature,moisture content,dry density,salt content,mineral composition,and fine particle content.The sensitivity of these factors varies depending on whether the soil is frozen or thawed.Due to the complex interplay of these factors,developing accurate predictive models is essential to assess their impact on thermal conductivity.Empirical models employing artificial intelligence algorithms are gaining traction due to their high accuracy and adaptability,par⁃ticularly in thermal conductivity prediction.However,significant progress has been made in analyzing and predicting thermal con⁃ductivity in typical geological materials.Despite advances in thermal conductivity analysis for standard soils,research on atypical soils like PCM-modified soils remains relatively limited.To bridge this gap,studies are investigating microencapsulated phase change materials(mPCM)as amendments for sandy soil foundations in Ningxia.They are examining how factors such as mPCM content,moisture,temperature,and dry density affect thermal conductivity,supplemented by scanning electron microscopy(SEM)to analyze internal pore structures.To accurately assess the temperature distribution in the drainage base of pulverized sandy soil improved by microencapsulated phase change materials(mPCM),it is essential to study the thermal conductivity of this modified soil and establish a reliable prediction model.This research will provide crucial references for the application of PCMmodified soils in engi
作者
唐少容
殷磊
杨强
柯德秀
TANG Shaorong;YIN Lei;YANG Qiang;KE Dexiu(College of Civil and Hydraulic Engineering,Ningxia University,Yinchuan 750021,China;Ningxia Research Center of Technology on Water-saving Irrigation and Water Resources Regulation,Ningxia University,Yinchuan 750021,China;Engineering Research Center for Efficient Utilization of Water Resources in Modern Agriculture in Arid Regions,Ningxia University,Yinchuan 750021,China)
出处
《中国粉体技术》
CAS
CSCD
2024年第3期112-123,共12页
China Powder Science and Technology
基金
国家自然科学基金项目,编号:52368050
宁夏回族自治区重点研发计划项目,编号:2021BEG03023
宁夏高等学校一流学科建设项目,编号:NXYLXK2021A03
宁夏大学学生创新创业训练项目,编号:202310749586。
关键词
微胶囊相变材料
粉砂土
导热系数
预测模型
多元线性回归
支持向量机
microencapsulated phase change material
silty sand
thermal conductivity
predictive modeling
multiple linear regression
support vector machine
