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Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第11期15卷 3010-3038页

作者： Jitendra Khatti Kamaldeep Singh Grover Department of Civil Engineering Rajasthan Technical UniversityKota324010RajasthanIndia

A comparison between deep learning and standalone models in predicting the compaction parameters of soil is presented in this *** hundred and ninety and fifty-three soil samples were randomly picked up from two hundred and forty-three soil samples to create training and validation datasets,*** performance and accuracy of the models were measured by root mean square error(RMSE),coefficient of determination(R2),Pearson product-moment correlation coefficient(r),mean absolute error(MAE),variance accounted for(VAF),mean absolute percentage error(MAPE),weighted mean absolute percentage error(WMAPE),a20-index,index of scatter(IOS),and index of agreement(IOA).Comparisons between standalone models demonstrate that the model MD 29 in Gaussian process regression(GPR)and model MD 101 in support vector machine(SVM)can achieve over 96%of accuracy in predicting the optimum moisture content(OMC)and maximum dry density(MDD)of soil,and outperformed other standalone *** comparison between deep learning models shows that the models MD 46 and MD 146 in long short-term memory(LSTM)predict OMC and MDD with higher accuracy than ANN ***,the LSTM models outperformed the GPR models in predicting the compaction *** sensitivity analysis illustrates that fine content(FC),specific gravity(SG),and liquid limit(LL)highly influence the prediction of compaction parameters.

关键词： Artificial intelligence(AI) Anderson-darling(AD)test Compaction parameters fine-grained soil Soft computing Score analysis

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Drainage performance and capillary rise restraint effect of wicking geotextile

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Journal of Central South University 2021年第10期28卷 3260-3267页

作者： BAI Mei LIU Zhi-bin ZHANG Shu-jian LIU Feng LEI Song-lin Department of Underground Engineering School of TransportationSoutheast UniversityNanjing 211189China Jilin Provincial High-Class Highway Construction Bureau Changchun 130028China

Wicking geotextile(WG)is considered as a possible countermeasure to reduce water content in unsaturated *** this research,rainfall tests were carried out to verify the drainage performance of *** capillary rise tests were conducted to study the effect of WG on the prevention of capillary *** results indicated that WG with good drainage performance could drain gravitational and capillary water out of kaolinite *** kaolinite soil column with water content of 12%and compaction degree of 90%,the whole process of capillary rise in soil column with a layer of WG was a typical two-stage mode,and the maximum capillary height was about 380 mm,which provided that the WG could work as a barrier to prevent capillary rise *** addition,the total vertical influential regions of WG in kaolinite soil above and below the WG layer were 400 and 100 mm,respectively.

关键词： geosynthetics wicking geotextile fine-grained soil drainage performance capillary rise soil column test

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