Assessment and enhancement of soil freezing characteristic curve estimation models

Abstract

The soil freezing characteristic curve (SFCC) represents a vital parameter in cold regions. Special instruments and highly trained personnel must measure the SFCC experimentally, a process that is both cumbersome and labor-intensive. Consequently, several estimation models have emerged to indirectly gauge the SFCC, yet the effectiveness of these models has rarely been examined. This study scrutinized three SFCC estimation models and enhanced them by employing a one-point measurement method. A total of 65 fine-grained soils and 25 coarse-grained soils were used to evaluate six SFCC estimation models. Findings reveal that the one-point measurement method markedly enhances the efficiency of the SFCC estimation models. In addition, when compared with three traditional SFCC estimation models, the extended SFCC estimation models were assessed, revealing that the extended Xin et al. SFCC estimation model ranks highest in performance among the SFCC estimation models considered. The research contributes a novel approach to developing SFCC estimation models in cold regions.