Automated Interpretation and Evaluation of Spatial Variability and Model Uncertainty in Geotechnical Site Characterization

Spatial variability of subsurface conditions and uncertainty in implementing methods and models for geotechnical site characterization are critical factors that contribute to financial and safety risks in transportation construction projects. As advanced data-rich techniques and methodologies are developed and implemented for geotechnical site characterization, design, and analysis, new tools are needed to leverage these techniques. A web-based platform will be introduced to provide innovative ways to automate and optimize the process of geotechnical site characterization. Specifically, this platform allows engineers to interactively visualize and efficiently evaluate and interpret statistical features of geotechnical data to facilitate development of design models. This is accomplished by automated evaluating model uncertainty using statistical analysis techniques incorporated into the Federal Highway Administration’s (FHWA’s) Geotechnical Engineering Circular (GEC) No. 5. This web-based platform has been implemented in several large highway and bridge design and construction projects with the Louisiana Department of Transportation and Development (LADOTD). Prototype project case histories will be briefly introduced in the paper. This web-based platform can be extended to incorporate a deep foundation database from LADOTD to eventually facilitate calibrating site-specific resistance factors from the load and resistance factor design (LRFD) methods for deep foundation design.