Prediction of the displacement mechanism of the cracked soil using NXFEM and Artificial Neural Networks

Namdar, Abdoullah and Mehran, Karimpour-Fard and Filippo, Berto and Nurmunira, Muhammad (2023) Prediction of the displacement mechanism of the cracked soil using NXFEM and Artificial Neural Networks. Procedia Structural Integrity, 47. pp. 636-645. ISSN 2452-3216. (Published)

[img]
Preview
Pdf
1-s2.0-S2452321623004687-main.pdf

Download (16MB) | Preview

Abstract

The stiffness and strength of the soil foundation govern the seismic safety of the structure. Estimating the influence of the soil crack on the nonlinear displacement of the soil foundation needs to be investigated in detail. In the present study, the cracked soil foundation subjected to the seismic load has been simulated. The nonlinear extended finite element method (NXFEM) was applied for the prediction of the crack path on the soil foundation considering the mechanical properties of the soil as the main parameters. In addition, the impact of the crack morphology on the differential displacement of the soil model was investigated. To examine the validity and prediction of the displacement range of the cracked soil foundation, Artificial Neural Networks (ANNs) were employed by using MATLAB. Considering the results of the numerical simulation and ANNs were observed that there is a direct relationship between the morphology of the soil crack with the soil with displacement mechanism. The morphology of the soil crack has a considerable impact on the vibration mechanism of the soil mass subjecting to the seismic loading. The novelty of the present study is related to the prediction impact of crack morphology on cracked soil foundation differential displacement. The prediction crack morphology of the soil significantly supports geotechnical earthquake engineering design.

Item Type: Article
Uncontrolled Keywords: Soil crack; crack morphology; seismic loading; ANNs; NXFEM; displacement
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Civil Engineering Technology
Depositing User: Ts. Dr. Nurmunira Muhammad
Date Deposited: 30 Aug 2023 00:49
Last Modified: 30 Aug 2023 00:49
URI: http://umpir.ump.edu.my/id/eprint/38343
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item