Consolidated-drained triaxial compression tests were conducted to compare the stress-strain and volume change response of sands and clayey sands reinforced with discrete randomly distributed poly-propylene fibers. The influence of various test parameters such as fiber content (0.0%, 0.5% and 1.0% by weight), clay content (0%, 10% and 20% by weight), relative density (50% and 90%) and confining pressure (100 kPa, 200 kPa and 300 kPa) were investigated. It has been observed that addition of clay particles to the sands decreased the shear strength of samples. Also, increase in clay content reduced dilation and increased compressibility of the mixed soil. Addition of the fiber to both sands and clayey sands samples improved the shear strength and increased ductility and axial strain at failure point.
Backfill name | UR-S | GR-S | UR-W | GR-W |
Maximum stress (kPa) | 416 | 725 | 520 | 960 |
Settlement at failure (mm) | 4.6 | 9.0 | 15.5 | 14.9 |
Plastic settlement (mm) | 3.5 | 7.0 | 12.5 | 12.0 |
Number of load cycles | 10 | 20 | 20 | 30 |
Bearing capacity ratio (BCR) | 1 | 1.74 | 1.25 | 2.32 |
Performance rating | 4 | 2 | 3 | 1 |
This paper presents a feed-forward back-propagation neural network model to predict the retained tensile strength and design chart to estimate the strength reduction factors of nonwoven geotextiles due to the installation process. A database of 34 full-scale field tests was utilized to train, validate and test the developed neural network and regression model. The results show that the predicted retained tensile strength using the trained neural network is in good agreement with the results of the test. The predictions obtained from the neural network are much better than the regression model as the maximum percentage of error for training data is less than 0.87% and 18.92%, for neural network and regression model, respectively. Based on the developed neural network, a design chart has been established. As a whole, installation damage reduction factors of the geotextile increases in the aftermath of the compaction process under lower as-received grab tensile strength, higher imposed stress over the geotextiles, larger particle size of the backfill, higher relative density of the backfill and weaker subgrades.
A series of reduced scale plate load tests was conducted to evaluate the bearing capacity of a strip footing resting on granular slopes. The effect of three factors including geocell burial depth, geocell length and spacing of geocell layers were discussed and evaluated. In this regard, 18 tests were performed to investigate the behavior of one and two layers geocell-reinforced slope as well as the unreinforced slope and plain condition.The results suggest that in the single-layered geocell-reinforced slope, the optimum burial depth of the first layer of geocell reinforcement is 0.1 times of the strip footing width, whereas at greater depth beneficial effect of the geocell reduces. In addition, expanding the reinforcement length up to approximately three times the foundation width could effectively increase the bearing capacity, whereas extending the length beyond that does not lead to any significant improvement. Furthermore, use of two geocell layers by considering an optimum geocell space of 0.2 times of the foundation width could enhance the bearing capacity up to 226% in comparison with the unreinforced slope, and up to 79% of the plane condition for settlement ratio of 15%. Finally, the results indicate that the efficiency of the geocell reinforcements in lessening the gap between slope and plane conditions increases as the settlement of the footing rises due to the better mobilization of dilation characteristics of granular backfill material and better lateral confinement of coarse aggregates by geocell in greater strains. |
Page 1 from 1 |
© 2025 CC BY-NC 4.0 | Journal of Engineering Geology
Designed & Developed by : Yektaweb