Spatial Analysis of Gradation of Gravel Formations with Application to No-Dig Engineering

• Main Authors: Chang-Yi Jiang, 江長億
• Other Authors: Keh-Jian Shou
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/71773846821184301495

碩士 === 國立中興大學 === 土木工程學系所 === 100 === Taichung area is covered by the gravel formations, therefore, the No-Dig construction often confronts gravel strata with various size of cobbles. This geologic condition makes the construction equipment easy to wear and with various sizes of cobbles. Serious wear of the cutter can be experienced such that the cobbles cannot be broken to the size of inlet. And the extra shaft has to be excavated to remove the obstacles and repair the cutter head, which results in the increase in construction cost and delay of duration. Therefore, if we can understand the particle size distribution of gravel in order to provide the reference for design and construction, a better decision can be made for the length of excavation, the design of cutter head, and the parameters for the facilities before No-Dig construction. In this paper, the pipejacking cases in Taichung City were adopted for the analyses through spatial statistical analysis to simulate the area gravel particle size distribution, and the results can be used to estimate the particle size distribution. In addition, according to the No-Dig cases, gravel characteristics and advancing rate data were also analyzed by linear regression and quadratic polynomial regression. The regression analysis shows that uniaxial compressive strength multiplying cumulative percentage of 60% of the particle size and the advancing rate possesses a higher value of the square of correlation coefficient (R2). Therefore, this study apply the uniaxial compressive strength, cumulative percentage of 60% of the particle size to estimate the advancing rate and obtain a advancing rate predition formula. A typical case in Taichung area is also analyzed in details for other parameters, such as viscosity and sand content of the driving fluids; The results of regression analysis of advancing rate shows that the lower the viscosity or the higher sand content, the better in the advancing rate. In addition, according to the spatial statistical analysis of the data obtained from the shafts (the particle size percentage of greater than 20cm, between 2cm to 20cm, less than 2cm). The results were applied to the T-PROGS geostatistic analysis to building a 3D geological model. We can then obtain the particle size distribution parameters along the pipe-jacking alignment and further applied for the regression analysis with average daily advance rate. The results show that the change of gravel particles larger than 20 cm is highly correlated with average daily advancing rate.