MULTIPLE LINEAR REGRESSION MODELLING FOR THE COMPACTION CHARACTERISTICS OF SEDIMENTARY SOIL MIXED BENTONITE AS COMPACTED LINER

• Published in: Jurnal Teknologi
• Main Author: Khalid N.; Mukri M.; Zain N.M.; Razak Z.; Jais I.M.
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174921160&doi=10.11113%2fjurnalteknologi.v85.20161&partnerID=40&md5=bf90be1c3cf5fd75a9952143d8e05e96

This paper attempts to develop a prediction model for compaction characteristics such as maximum dry density (MDD) and optimum moisture content (OMC) of sedimentary residual soil mixed with bentonite as compacted liner. This prediction model was based on the laboratories testing data such as compaction testing and Atterberg limit testing of residual soil mixed with bentonite. Meanwhile, compaction testing was conducted at the different compaction energies. The Multiple Linear Regression (MLR) analysis method was selected to develop a model in determining the maximum dry density (MDD) and optimum moisture content (OMC). The predicted compaction model developed in this study was validated in accordance with the statistical validation steps and conditions. It was found from the modelling analysis, the significant relationship between the compaction energies (E) and OMC for MDD model. Meanwhile, it shows the significant relationship between liquid limit (LL), plastic limit (PL), percentage bentonite (B) and compaction energies (E) for OMC model. The fitted regression model shows the reasonably good regression coefficient for MDD model is (R2 = 78.5%) and for OMC model is (R2 = 71.9%). The models were validated by comparing between the predicted model with measured model data from published study data. It was found, the determination coefficient and mean square error (MSE) for validated model between the predicted model and the measured models gave a value of R2 = 88.7% with MSE = 0.12% for MDD model and R2 = 88% with MSE = 4.3% for OMC model. In conclusion, the models developed in this study present a good prediction for MDD and OMC. © 2023, Penerbit UTM Press. All rights reserved.