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Comparative study has been performed to investigate the behavior of dredged fills on rigid (Model 1) and flexible (Model 2) containers. The study was focused on the sedimentation of soil fills and the development of total stresses. Model 1 is made of an acrylic cylinder and Model two is a scale-size geotextile tube. Results indicate that for rigid containers, significant decrease of the sediment height is apparent during the dewatering process. On the other hand, because the geotextile is permeable, the water is gradually dissipated during the filling process on flexible containers. Hence, significant loss in the tube height is not apparent during the duration of the test. Pressure spikes are apparent on rigid containers during the filling process which can be attributed to the confining effect due to hydrostatic pressure. For the flexible containers, the pressure readings gradually increases with time during the filling process and normalize at the end on the filling stage. No pressure spikes were apparent due to the gradual dissipation of pore water pressure.

Analytical solutions for modeling geotextile tubes during the filling process and approximation method to determine the densified tube shape are reviewed. The geotextile tube filling analysis is based on Plaut & Suherman\'s two-dimensional solution for geotextile tubes having a weightless and frictionless inextensible membrane resting on a rigid horizontal foundation subjected to internal and external hydrostatic pressures. The approximation for the densified tube shape developed by Leshchinsky et al. was adopted. A modified method for approximating the densified tube shape based on an areal-strain deformation analysis is introduced. Design diagrams useful for approximating geotextile tube measurements in the design process are provided.

Geotextile tubes are basically a huge sack filled with sand or dredged soil. Geotextile tubes are made of permeable woven or non-woven synthetic fibers (i.e., polyester or PET and polypropylene or PP). The geotextile tubes' performances in strength, dewatering, retaining solid particles and stacked stability have been studied extensively in the past. However, only little research has been done in the observation of the deformation behavior of geotextile tubes. In this paper, a large-scale apparatus for geotextile tube experiment is introduced. The apparatus is equipped with a slurry mixing station, pumping and delivery station, an observation station and a data station. For this study the large-scale apparatus was utilized in the studies regarding the stresses on the geotextile and the deformation behavior of the geotextile tube. Model tests were conducted using a custom-made woven geotextile tubes. Load cells placed at the inner belly of the geotextile tube to monitor the total soil pressure. Strain gauges were also placed on the outer skin of the tube to measure the geotextile strain. The pressure and strain sensors are attached to a data logger that sends the collected data to a desktop computer. The experiment results showed that the maximum geotextile strain occurs at the sides of the tube and the soil pressure distribution varies at each geotextile tube section.

The typical design of ground improvement with prefabricated vertical drains (PVD) and surcharge preloading involves a series of deterministic analyses using averaged or mean soil properties for the various combination of the PVD spacing and surcharge preloading height that would meet the criteria for minimum consolidation time and required degree of consolidation. The optimum design combination is then selected in which the total cost of ground improvement is a minimum. Considering the variability and uncertainties of the soil consolidation parameters, as well as considering the effects of soil disturbance (smear zone) and drain resistance in the analysis, this study presents a stochastic cost optimization of ground improvement with PVD and surcharge preloading. Direct Monte Carlo (MC) simulation and importance sampling (IS) technique is used in the stochastic analysis by limiting the sampled random soil parameters within the range from a minimum to maximum value while considering their statistical distribution. The method has been verified in a case study of PVD improved ground with preloading, in which average results of the stochastic analysis showed a good agreement with field monitoring data.