Abstract

V.HOHN, Amanda et al. Empirical Models to Predict Compaction Parameters for Soils in the State of Ceará, Northeastern Brazil. Ing. Investig. [online]. 2022, vol.42, n.1, e104.  Epub Oct 22, 2021. ISSN 0120-5609.  https://doi.org/10.15446/ing.investig.v42n1.86328.

This work developed prediction models for maximum dry unit weight (γd, max) and optimum moisture content (OMC) for compacted soils in Ceará, Brazil, based on index and physical properties and physical properties. The methodology included data from soils used in the construction of 15 dams in Ceará, with available information regarding laboratory tests of interest. Correlations were developed using non-linear regression, from 169 laboratory results (83 for training and 86 for validating the models), which presented a R2 of 0,763 for MoPesm (prediction model for γd, max) and 0,761 for MoTuo (model for OMC). A posteriori, the same physical indexes used to train and validate MoPesm and MoTuo were used as inputs of other prediction models available in the literature, whose outputs differed considerably from laboratory results for the evaluated soils. MoPesm and MoTuo were able to satisfactorily predict compaction parameters, with outputs close to those obtained in laboratory for tested soil samples. Their performance justifies their use for predicting compaction parameters in geotechnical structures that use employ soils when there are financial restraints, short timeframes, or unavailability of test equipment, particularly in early design stages and preliminary studies, before appropriate soil sampling and field investigation can be conducted, thus saving substantial time and financial resources.

Keywords : predicting models; compacted soils; maximum dry unit weight; optimum moisture content.

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