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人工制备有机质固化土力学特性试验研究 被引量:28

Experimental study on mechanical properties of stabilized artificial organic soil
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摘要 为了探讨有机质对水泥固化土物理力学特性的影响以及固化剂XGL2005的固化效果,在软土中添加腐植酸配制得到了不同有机质含量的人工有机质土,并进行了液塑限试验;另外,对单掺水泥固化与水泥添加固化剂XGL2005复合固化有机质土进行了无侧限抗压强度对比试验.试验结果表明,人工有机质土的液限以指数形式增长,塑限则呈线性形式增加;随着固化土中有机质质量分数的增加,固化土的强度呈对数形式下降;而随着固化剂XGL2005掺量的增加,固化土的强度呈幂函数形式增长;固化剂XGL2005可有效消除有机质的不利影响,显著增强水泥固化有机质土的效果.在分析水泥质量分数、固化剂掺量(质量分数)和龄期对强度影响规律的基础上,通过回归分析建立了既可考虑有机质质量分数对强度削减的影响,又能考虑水泥质量分数、固化剂掺量(质量分数)和龄期对强度增强影响的预测模型. In order to study the influence of organic matter on the physical and mechanical properties of stabilized soil, and the effect of XGL2005 on stabilizing organic soil, artificial organic soil was obtained by adding humie acid into soft soil, and liquid-plastic limit tests were conducted on the artificial organic soil with different content of humic acid. Unconfined compressive strength tests were carried out on cement stabilized soil and cement admixed with XGL2005 stabilized soil respectively. Test results indicated that the liquid limit of artificial organic soil increased exponentially, whose plastic limit increased of linearly with the humic acid content; the strength of stabilized soil decreased logarithmetically with increase organic matter content. On the contrary, the strength of stabilized soil increased in the form of power function as stabilization agent content increased. The strength of cement stabilized organic soil was reinforced greatly by adding the stabilizer XGL2005to reduce the adverse effect of organic matter. Based on the law obtained from the test, a prediction model was established by regression analysis. The model considers not only the positive influence of the curing time, the content of the cement and stabilization agent, but also the adverse influence of organic matter on the strength of stabilized soil.
出处 《浙江大学学报(工学版)》 EI CAS CSCD 北大核心 2007年第1期109-113,共5页 Journal of Zhejiang University:Engineering Science
基金 国家自然科学基金资助项目(50678158)
关键词 固化土 龄期 无侧限抗压强度 预测模型 有机质 stabilized soil curing time unconfined compressive strength prediction model organic matter
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