@article{ajcea2016435,
author={{Joshaghani, Mohammad S. and Raheem, Aram M. and Mousavi, M.M. Reza},
title={Analytical Modeling of Large-Scale Testing of Axial Pipe-Soil Interaction in Ultra-Soft Soil},
journal={American Journal of Civil Engineering and Architecture},
volume={4},
number={3},
pages={98--105},
year={2016},
url={http://pubs.sciepub.com/ajcea/4/3/5},
issn={2328-3998},
abstract={In this study, large-scale model test with dimensions of 2.4 m*2.4 m*1.8 m has been designed to investigate the behavior of axial pipe-soil interaction on the simulated ultra-soft seabed. Large-scale tests were performed on plastic pipes by loading the pipe from the ends, placed on ultra-soft clayey soil with undrained shear strength ranged from 0.01 kPa to 0.1 kPa, to quantify the axial soil-pipe interaction. An accurate remote gridding system was developed for displacement measurement. Two new models were used to correlate the shear strength with the water content of the ultra-soft soil. The models were verified with data points reported in the literature and experimental tests performed in the laboratory. The shear strength was correlated strongly with water content of ultra-soft soil with coefficient of correlation (R<SUP>2</SUP>) up to 0.91. Moreover, new analytical models were established to predict the axial break-out resistance and large-displacement residual resistance in ultra-soft soil. The new models have taken into account the effects of vertical loads (W), normalized initial embedment (&#948;in), boundary length (&#955;), and the rate of axial loading (Vp). The new models have shown very good predictions for the experimental results with coefficient of correlation (R<SUP>2</SUP>) up to 0.87. Also, a new analytical model (p-q-m) was proposed to predict the force-displacement relationship for axial testing of pipe-soil interaction. This new model (p-q-m) has also shown a very good agreement with the experimental testing results for the full force-displacement response of pipe soil interaction. Detailed statistical procedure has been used to analyze the performance of both p-q and p-q-m models. The modified p-q model presents better estimation using any of the statistical methods.},
doi={10.12691/ajcea-4-3-5}
publisher={Science and Education Publishing}
}