Prediction of soil thermal resistivity based on multivariate distribution models
WANG Caijin1，WU Meng1，CAI Guojun1，2，ZHAO Zening1，LIU Songyu1
(1. Institute of Geotechnical Engineering，Southeast University，Nanjing，Jiangsu 211189，China；2. School of Civil
Engineering，Anhui Jianzhu University，Hefei，Anhui 230601，China)
Abstract：The soil thermal resistivity is an important parameter to determine the thermal properties of geotechnical materials. In order to accurately predict the soil thermal resistivity，a prediction model of soil thermal resistivity is established based on the multivariate distribution model. The prediction model is verified，analyzed，and compared with the traditional empirical model to clarify the performance of the proposed model. The results show that the established multivariate distribution model can accurately predict the soil thermal resistivity. With the increase of input parameters，the prediction accuracy of multivariate distribution model is significantly improved，the is increased from 0.719 5 to 0.899 5，the value is reduced from 1.077 8 to 1.037，and the value is reduced from 0.367 5 to 0.212 1. The model has the best prediction accuracy. The prediction accuracy of multivariate distribution model is obviously better than that of traditional empirical model. For the prediction of thermal resistivity of different soil types with significant differences in engineering properties and complex sedimentary environment，it is suggested to select different types of multivariate distribution models according to the data to evaluate the thermal resistivity.
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2023, Vol. 42 
