Empirical modeling of the compaction curve of cohesive soils

Abstract

Compaction curves (or density–moisture relationships) of cohesive soils are essential components for establishing practical and reliable criteria for effective control of field compaction. In this paper, modules built from empirical models for simulating the compaction curves of cohesive soils based on easily measured basic soil properties and compaction energy were developed using both statistical regression and artificial neural networks (ANNs) techniques. A large number of compaction curves pertaining to a wide variety of fine-grained soils were collected and used in modeling. The developed modules were able to predict compaction curves of soils with good accuracy, with the ANN-based module outperforming the statistical-based analog. The compaction modules were utilized to inquire about the compactibility behavior of fine-grained soils in relation to their properties and the compaction energy used. Besides their use as independent compaction curve predictors, the compaction modules can be used as supplementary units in numerical models for solving geotechnical engineering problems and as tools useful in preliminary design phases and feasibility studies.Key words: cohesive soils, compaction curve, modeling, neural networks, regression.