Modelling the capacity of micropiled-raft foundation rested on soft clayey soil using an artificial neural network approach. Issue 5 (28th May 2022)

• Record Type: Journal Article
• Authors: Borthakur, Nirmali; Das, Manita
• Is Part Of: International journal of geotechnical engineering. Volume 16:Issue 5(2022)
• Page Start: 558
• Page End: 573
• Publication Date: 2022-05-28
• Subjects: Micropiled-raft foundation -- clayey soil -- artificial neural network -- multi variable regression -- capacity -- algorithm; Geotechnical engineering -- Periodicals; Soil mechanics -- Periodicals; Rock mechanics -- Periodicals; 624.1513
• DOI: 10.1080/19386362.2021.1959138
• Languages: English
• ISSNs: 1938-6362

Abstract

ABSTRACT: Micropiled-raft foundation shows its ability to solve particular type of foundation problem i.e . building of medium height and weight structures over soft deep-seated clayey soil deposit. Potential of artificial neural network method was used in the study for the assessment of capacity of micropiled-raft foundation under a given settlement in soft clayey soil considering the complex non-linear load-settlement behaviour. Experiments were conducted on micropiled-raft foundation constructed with different variables within a soft clayey soil bed in the test pit in field and a database was prepared from load-settlement graphs those were utilized to develop different ANN models. It was observed from the study that Bayesian Regularization algorithm with 90–10% validation model performs the best. Sensitivity analysis was performed to determine the relative significance of different input variables and a neural interpretation diagram was prepared. An empirical equation was proposed with best fit ANN model and an example illustrated.