Lifelines such as highways, pipelines, telecommunication lines, and powerlines provide communities with vital services, and their functionality is dependent upon the foundation soil that supports them. However, when designing the infrastructure, it can be difficult to know where to test the soil in order to give spatially representative sampling, particularly for long, lifeline structures. Finding this distance requires knowledge of the spatial correlation and/or the spatial variability of the soil parameter (stiffness, cohesion, etc.). But this correlation distance is not typically found in practice because it requires large amounts of data and the costs of retrieving that data can be high. Lack of representative sampling can lead to an overly conservative design and too much sampling can create an overly expensive sampling program. In this study, multiple tests using the geophysical method of spatial autocorrelation (SPAC) were conducted to find the soil stiffness along a 310 meter long profile. SPAC records passive surface waves which sample the underlying soil, and these surface waves can be used to create a shear wave velocity profile of the site. The spatial continuity of the stiffness (the soil velocity values) was then found using geostatistics. The geostastical tool primarily used in this study was the (semi-)variogram, but the covariance function and the correlogram are also shown. By using these tools, the spatial correlation/variability can give an estimate of the how far apart to test the foundation soil so that the data is spatially representative. In other words, finding the distance that the soil parameter is minimally correlated with itself. This study found the distance (the range of the semi-variogram) to be 70 meters for 5 meters depth, 100 meters for 10 to 15 meters depth, and 90 meters for 30 meters depth.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-2647 |
| Date | 01 December 2015 |
| Creators | Wagstaffe, Daniel Raymond |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
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