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石灰改良红黏土导热系数影响因素及模型预测 被引量:6

Influence Factors and Model Prediction of Thermal Conductivity of Lime-modified Red Clay
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摘要 导热系数是研究温度场的重要参数,基于石灰与红黏土酸碱互损随时间的演化,利用瞬态热线法导热系数仪,研究含水率、干密度以及龄期对石灰改良红黏土导热系数的影响,并建立经验函数和反向传播(back propagation,BP)神经网络预测模型。结果表明:石灰改良红黏土的导热系数随含水率的增加呈指数增长,随干密度的增加呈线性增长;在15%~27%含水率范围内,其导热系数平均增长53.87%;在1.25~1.65 g/cm^(3)干密度范围内,其导热系数平均增长87.06%;改良土导热系数随龄期的增加呈指数降低,降低速率逐渐减小,最终趋于稳定的趋势,在龄期90 d范围内,导热系数平均降低16.6%。经验证分析,两种模型的整体误差均小于10%;可以很好地描述石灰改良红黏土的导热系数随影响因素的变化情况。该规律以及模型可以为相同土样进行石灰改良提供参考。 Thermal conductivity is an important parameter in the study of temperature field.Based on the evolution of acid-base mutual loss between lime and red clay over time,the influence of water content,dry density and age on thermal conductivity of lime-modified red clay was studied by using transient hot-wire thermal conductivity instrument,and the empirical model and back propagation(BP)neural network prediction model were established.The results show that the thermal conductivity of lime-modified red clay increases exponentially with the increase of water content and linearly with the increase of dry density.In the range of 15%~27% moisture content,its thermal conductivity increases by 53.87% on average.In the dry density range of 1.25~1.65 g/cm^(3),the thermal conductivity increases by 87.06% on average.The thermal conductivity of improved soil decreases exponentially with the increase of age,and the decreasing rate gradually decreases and finally tends to be stable.Within 90 days of age,the thermal conductivity decreases by 16.6% on average.Empirical analysis shows that the overall errors of the two models are less than 10%.The thermal conductivity of lime modified red clay can be well described with the change of influence factors.The law and model can provide reference for lime improvement of the same soil samples.
作者 王红旗 李栋伟 钟石明 贾志文 王泽成 陈鑫 秦子鹏 WANG Hong-qi;LI Dong-wei;ZHONG Shi-ming;JIA Zhi-wen;WANG Ze-cheng;CHEN Xin;QIN Zi-peng(School of Civil and Architectural Engineering,East China University of Technology,Nanchang 330013,China;Key Laboratory for Technology in Rural Water Management of Zhejiang Province,Zhejiang University of Water Resources and Electric Power,Hangzhou 310018,China)
出处 《科学技术与工程》 北大核心 2023年第5期2084-2092,共9页 Science Technology and Engineering
基金 国家自然科学基金(42061011,41977236) 新疆兵团科技计划基金(2020AB003) 东华理工大学博士启动基金(DHBK2019233)。
关键词 石灰改良 红黏土 导热系数 预测模型 BP神经网络 lime improvement red clay thermal conductivity prediction model BP neural network
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