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Behavioral Study of Raft Reinforced with Geogrid and Geocell Through Experiments and Neural Models | ||
| Civil Engineering Infrastructures Journal | ||
| دوره 56، شماره 2، اسفند 2023، صفحه 321-332 اصل مقاله (767.44 K) | ||
| نوع مقاله: Research Papers | ||
| شناسه دیجیتال (DOI): 10.22059/ceij.2023.343951.1847 | ||
| نویسندگان | ||
| Vikas Kumar* 1؛ Akash Priyadarshee2؛ Sunayana Chandra3؛ A. Jindal4؛ D. Rana5 | ||
| 1Assistant Professor, Department of Civil Engineering, SoET Block, Central University of Haryana, Mahendergarh, India. | ||
| 2Assistant Professor, Department of Civil Engineering, MIT Muzaffarpur, Bihar, India. | ||
| 3Ph.D. Candidate, Scientist, CSIR-NEERI, Delhi Zonal Centre, India. | ||
| 4Assistant Professor, Department of Civil Engineering, School of Engineering and Technology, Central University of Haryana, India | ||
| 5Assistant Professor, Department of Civil Engineering, School of Engineering and Technology, Central University of Haryana, India. | ||
| چکیده | ||
| The stability of a structure could be achieved either by adopting strong foundation or by improving the strength of the soil. This study is an attempt to investigate the behavior of a raft foundation (U-RF) upon reinforcing with geogrid (RF-R-Gr) and reinforcing with geocell (RF-R-Gc). The results of the study showed that optimal depth for placement of geogrid was found to be 0.3B (B is width of raft) while optimal depth for geocell varied from 0.1B to 0.15B. It was also found that the Bearing Capacity Ratio (BCR) for RF-R-Gr was typically six times higher than U-RF, while for RF-R-Gc it was eleven times higher than U-RF. Further, the outcomes of experimental study were modeled using Artificial Neural Networks (ANN) to predict the settlements. It was found that ANN models predicted settlement with higher values of correlation coefficient (r) as 0.9996 for RF-R-Gr and 0.9995 for RF-R-G. | ||
| کلیدواژهها | ||
| ANN؛ BCR؛ Geocell؛ Geogrid؛ Raft | ||
| مراجع | ||
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