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Appropriate Method of Determination of Coefficient of Consolidation for Municipal Solid Waste

机译:确定城市固体废物固结系数的适当方法

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To predict the rate of settlement of municipal solid waste specimens (MSW), it is essential to estimate the value of the coefficient of consolidation (Cv) using laboratory consolidation test results. Literature suggests that the various empirical curve-fitting methods used for assessing Cv are Casagrande's logarithm of time fitting method and Taylor's square root of time fitting method for the same test data. Both methods are derived from the time factor and degree of consolidation (T-U) relationship and corresponding laboratory time-compression (T-delta) relationship. For different types of wastes and loading conditions, the shapes of curves vary considerably, and the validity of these approaches is not established. In all these cases, the estimation of the Cv poses a serious problem. To overcome the above difficulties, the rectangular hyperbola method is used, in this article, to determine the Cv by U-T or t versus delta relationship. Earlier, this method was used for different coefficient of consolidation values of time for completion of different percentages of consolidation. It is found that the calculated values of Cv are found to be more reliable when the time for 60% of consolidation is taken. The estimated Cv values from the rectangular hyperbola method lie between the existing standard methods of Casagrande's and Taylor's. The rectangular hyperbola method is simple and can be used for all shapes of time-compression curves, and the specific advantage of this method is that the initial compression need not be known and is devised to separate the initial, primary, and secondary compression for any load increment.
机译:要预测城市固体废物标本(MSW)的沉降速率,必须使用实验室固结测试结果估算固结系数(Cv)的值。文献表明,用于评估Cv的各种经验曲线拟合方法是Casagrande的时间拟合方法的对数和Taylor的时间拟合方法的平方根。两种方法均来自时间因素和巩固程度(T-U)关系以及相应的实验室时间压缩(T-delta)关系。对于不同类型的废物和装载条件,曲线的形状变化很大,并且这些方法的有效性尚未确立。在所有这些情况下,Cv的估计都会带来严重的问题。为了克服上述困难,本文使用矩形双曲线方法通过U-T或t与增量关系确定Cv。以前,此方法用于完成时间的不同合并系数值,以完成不同百分比的合并。可以发现,当花费60%的固结时间时,Cv的计算值更加可靠。矩形双曲线法的估计Cv值介于卡萨格兰德和泰勒的现有标准方法之间。矩形双曲线方法很简单,可用于所有形状的时间压缩曲线,该方法的特殊优点是不需要知道初始压缩,并且可以将任意类型的初始,主次压缩分开负载增量。

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