Research on Prediction of Subgrade Freezing and Thawing Characteristics in Alpine Meadow Area Based on BP Neural Network
Based on the reconstruction and expansion project of Gongjue-Mangkang Highway in Chang-du,Tibet,the indoor freeze-thaw test of subgrade soil was designed and made according to the grada-tion composition of subgrade soil.Based on the data obtained from laboratory tests,a neural network model for predicting the freezing-thawing deformation of subgrade soil was established.The frost heave and thaw settlement deformation of subgrade soil were predicted by using this model,and the gradation range of subgrade filler needed in practical engineering was obtained.The results show that,when the moisture content of the initial test is 9％,the subgrade soil samples with fine-grained components in the range of 11％～16％and 17％～18％show"weak frost heaving of Grade Ⅱ"and"frost heaving of Grade Ⅲ".The soil samples with the content of fine-grained components in the range of 11％～18％show"Grade Ⅱ weak thawing settlement".Considering the influence of fine par-ticle content on frost heave deformation,thaw settlement deformation and compaction effect of sub-grade soil,it is suggested that the fine particle content in subgrade filler should be controlled within 16％,and the proportion of fine particle content at 13％can be considered as the best gradation.
highway engineeringhighway subgradefreezing and thawing characteristicslaboratory testBP neural network
万方数据
维普
