Abstract: In the context of the “carbon peaking and carbon neutrality” goals, the specific heat capacity of soil, as one of the important thermophysical parameters, plays an important role in many fields such as energy geo-structure, subway ventilation calculation, buried pipelines, nuclear waste disposal, artificial ground freezing, agricultural irrigation, etc. A specific heat capacity test was carried out on clay samples with different initial dry densities and initial water contents under different temperature conditions, and the variation patterns and mechanisms were investigated. The test results indicate that the specific heat capacity of clay increases linearly with the increase of initial dry density and initial water content, and is proportional to the third power of temperature. The mechanism of the variation of specific heat capacity is related to the variation of three-phase percentage, solid-phase lattice vibration, and water-ice phase transition. A model for predicting the specific heat capacity of clay considering multi-factors is established and cross-validated with back propagation artificial neural network (BP-ANN) model, simplified theoretical model and other empirical models. The comparison shows that the prediction model has better performance in terms of applicability and accuracy, which can provide a reliable reference for specific heat capacity determination in theoretical calculations, numerical simulations, and engineering practice.

Key words: clay, specific heat capacity, prediction model, multi-factors, thermophysical properties