Abstract
Moisture content of subgrade materials is an essential factor affecting frost heave deformation of high‐speed railway subgrade in a seasonally frozen region. Modeling and predicting moisture transport play an important role in analyzing the subgrade thermal and hydraulic conditions in cold regions. In this study, a long short‐term memory (LSTM) model was proposed based on subgrade material moisture in two sections during one winter and spring cycle from 2015 to 2016. The reliability of the model was verified by comparing the monitoring data with the model results. The results demonstrate that the LSTM model can be effectively used to forecast the dynamic characteristics of the moisture of subgrade materials. The data of simulated moisture content of subgrade materials have a root mean square error ranging from 0.17 to 0.47 in the training phase and from 0.20 to 10.5 in the testing phase. The proposed model provides a novel method for long‐term moisture prediction in subgrade materials of high‐speed railways in cold regions.
Highlights
Frozen ground is mainly distributed in highlatitude areas such as northeast China, north China, and northwest China, accounting for 53.5% of China’s total land area [1, 2]
The gradient descent algorithm was applied to update the weight of the model. e adaptive moment (Adam) estimation was selected as the optimization algorithm for the training process of the model
In comparison with other optimization algorithms, the Adam algorithm is more efficient in terms of calculation and it has a better effect in practical applications [31]
Summary
Frozen ground is mainly distributed in highlatitude areas such as northeast China, north China, and northwest China, accounting for 53.5% of China’s total land area [1, 2]. Rough field monitoring and laboratory tests, it was found that soil properties, temperature, and moisture content were the main factors affecting the frost heave of the subgrade [6,7,8,9,10,11,12,13]. Several experiments and numerical models have focused on one or two controlling factors that may affect moisture transport. They are time-consuming and sometimes cannot predict the long-term dynamics of moisture content, for instance, Khoury et al [20] found that a change in the subgrade moisture content affected the performance of pavement materials. Few studies have simulated and predicted the moisture variation in high-speed railway subgrades in cold regions
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