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Laboratory Study of Soft Soil Improvement using Lime Mortar-(Well Graded) Soil Columns

机译:石灰砂浆(分级井)土柱改良软土的室内研究

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Stone columns and sand compaction piles represent the most known column-type technique for improving soft soils. In this study, more than 675 laboratory tests were carried out on composite specimens with lime mortar-well graded soil (lime-WS) column. These tests were conducted on specimens prepared as lime-WS using a mixture of lime and well graded soil poured into a local clay soil material with various proportions of lime and different curing times. The test programs were designed to investigate influences of variations in the moisture content on composite specimens. All tests were performed on specimens based on the classical California bearing ratio (CBR) testing procedure according to ASTM D1883-94. Test results were used to train an artificial neural network (ANN). ANN makes it possible to predict the behavior of these columns and their load bearing capacity as a function of changes in clay and lime content with different curing times. Tests results show that lime-WS columns, which contain 20 % lime and 22 % clay, increase the strength of soft fine grained soils to a noticeable amount.
机译:石柱和压实桩代表了改善软土的最著名的柱型技术。在这项研究中,使用石灰砂浆井分级的土壤(lime-WS)柱对复合标本进行了超过675个实验室测试。这些测试是在准备为石灰-WS的样品上进行的,使用的是将石灰和分级良好的土壤混合物倒入具有不同比例石灰和不同固化时间的当地粘土土壤材料中的方法。测试程序旨在调查含水量变化对复合材料样本的影响。所有测试均根据ASTM D1883-94的经典加利福尼亚轴承比(CBR)测试程序在标本上进行。测试结果用于训练人工神经网络(ANN)。人工神经网络可以预测这些柱的行为及其承载能力,这些变化是不同固化时间下粘土和石灰含量变化的函数。测试结果表明,石灰-WS色谱柱包含20%的石灰和22%的粘土,可将软细粒土的强度提高到显着水平。

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