Digital Transformation Solution for Identification of Geotechnical Parameters Using Statistical Data Analysis | ||||
| ERJ. Engineering Research Journal | ||||
| Article 8, Volume 45, Issue 1, January 2022, Page 89-99 PDF (572.47 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erjm.2022.105847.1121 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Hesham Gaafar  1; Ahmed Dakhly2; Amr Elhakim2
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| 1Faculty of Engineering, Cairo Uni | ||||
| 2Department of Public Works, Faculty of Engineering, Cairo University, Giza, Egypt | ||||
| Abstract | ||||
| Currently, there is a large boom in the construction of new developments, infrastructure, and transportation projects in the Middle East. Geotechnical engineers are responsible to characterize the subsurface ground conditions, obtain design parameters and identify problematic subsurface ground conditions. Geospatial Information Systems combined with statistical algorithms can provide an efficient way for identifying soil parameters/hazards. GIS associates data with their location (coordinates). The spatial data analysis platform ArcGIS is used to determine soil parameters at unsampled locations. An automated workflow is developed to apply different interpolation algorithms providing engineers with an easy-to-use tool to determine the most accurate algorithm for use in a specific project. This technique is applied to assess the liquefaction potential in a project site in Dubai, United Arab Emirates. Four spatial data analysis algorithms: Inverse Distance Weighted (IDW), Natural Neighbour, Regularized Spline, and Tension Spline are applied to the measured data. The errors associated with the use of the different algorithms are computed and compared. The suitability of the use of different algorithms is discussed. | ||||
| Keywords | ||||
| Digital Transformation; Data Analysis; Liquefaction; GIS | ||||
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