Abstract

Compaction is the process of artificially improving the mechanical properties of soil. However, determination of compaction characteristics in laboratory using Proctor compaction test is time consuming and expensive. Hence, there is a need of correlating compaction characteristics with other physical properties of bottom ash which can be obtained easily. This paper describes an innovative solution to predict the compaction properties of coal bottom ash for the preliminary assessment prior to geotechnical engineering related field applications. The data for required parameters of bottom ash for the model development were collected through a literature survey representing different parts of the world. After stepwise regression analysis, specific gravity and uniformity coefficient were found to be the most significant input parameters to predict the compaction characteristics of bottom ash. These parameters were then used to develop the models to predict maximum dry density and optimum moisture content of bottom ash using multiple regression analysis. The developed models were accurate with a prediction accuracy less than ±3% for both maximum dry density and optimum moisture content models. These empirical models were also presented graphically. According to those predictive curves, maximum dry density increases with increasing uniformity coefficient and specific gravity while optimum moisture content reduced.

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