الفهرس 
CHAPTER 1INTRODUCTION 1Only 14 pages are availabe for public view
 |  | from | 266 |  |  |
| | | from | 266 | | |
Abstract
Many coastal areas have soft clay soils, characterized by high compressibility and low bearing capacity. There are several methods for improving soil characteristics, one of which is stone columns technique. This method can reduce the possibility for liquefaction, speed the consolidation effect, strengthen the soil, and lessen the compressibility of soft, loose, and fine-graded soils. In this study, unit cell stone columns with 50 and 75mm diameters and the length of stone column to the depth of the soft clay (L/H) of 1 and 0.75, were subjected to laboratory experiments on soft clay soil. Crushed asphalt, crushed concrete, crushed ceramic, and treated concrete were tested as sustainable recycled filler materials, with dolomite used as a natural aggregate in the stone columns. In addition, tests were conducted on both uncased and geogrid encased stone columns. The main objective is to identify the most effective sustainable filler material that improves in load-bearing capacity and minimizes the settlement. The behavior of stone columns was assessed by load-settlement behavior, varying stress concentration ratio (n) and the load improvement factor (LIF). The results indicate that all the materials used in this study improved the bearing capacity and reduced the settlement. It is observed that treated concrete yielded the best results in improvement, while crushed asphalt is considered the most economical option compared to the other materials used. Additionally, PLAXIS 3D Software was utilized to investigate the behavior of a strip footing suited over soft clay soil reinforced with stone columns. Various machine learning techniques, such as SVM, MLR, GPR, and ANN, are employed to evaluate their effectiveness in analyzing the performance of sustainable recycled materials within stone columns.