• Proceedings of the Korean Geotechical Society Conference
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• 1999.02a
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• pp.84-95
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• 1999

Laboratory experiments were performed to evaluate the strength characteristics of solidified sandy soils by portland cement with mixing conditions. Factors considered in the experiments were the fine content(<#200, %), cement content(%) and water-cement ratio and unconfined compressive strength tests were performed on samples at 7 and 28 cured day. Results of tests showed that for a low cement content(7%∼10%) the fine content was very important while for a high cement content the water-cement ratio was very important. For 7%∼10% cement content, the optimum fine content which gained maximum strength was about 30%. But for 13% cement content, low fine content and water-cement ratio were more useful than others. In the multi regression analysis, significant equation was gained.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.6
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• pp.135-142
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• 2001

Laboratory experiment was performed to evaluate the influence of mixing conditions to the strength of solidified sandy soils with cement. The major physical factors considered in this experiment were the fine particles content(<$\sharp200%$), cement content(%) and water-cement ratio, and unconfined compressive strength test was performed on the samples at 7 and 28 cured day. The results of tests shows that when the cement content is relatively low (7~10 percents) the fine content in the sandy soils is very important, but when cement content is high the water-cement ratio became more important. It was appeared that in the range of the cement content of 7~10 percents, about 20~30 percents of fine content to the total sample weight is the optimum condition to get the maximum strength. In the case of the cement content of 13 percents, the strength of sample was considerably affected by the water-cement ratio rather than the fine content. In this paper, empirical equations were also developed and evaluated to verify the relationship among three factors by the multi-regression analysis.