Developed Predictive Design Equations for Drilled Shaft Capacities for Various Rock Formations by Conducting Site Investigation and Load Test

Engineering strength properties of various rock formations vary significantly, and the data is typically scattered. Graphical and statistical measures are beneficial in summarizing and understanding such scatter and variation in strength properties. These techniques were used to predict rock engineering parameters, parameter distribution, and best-fit correlations among the parameters. The main objective of this study is to develop new design charts and prediction equations for various geologic formations to be used for drilled shaft design and rock strength property determination. In order to develop the regression equations, two databases were collected from 22 projects consisting of site investigation database and load test database. These projects included four geologic formations: shale, woodbine shale, woodbine sandstone, and limestone. Each geologic formation dataset was then subdivided into three types of classifications based on Federal Highway Administration (FHWA)'s rock classification system that uses unconfined compressive strength (Q(un)) and rock quality designation (RQD). After that, the database was subdivided further into sub-datasets, according to the level of weathering: hard or fresh, moderately weathered, or weathered. This paper discussed the statistical analyses and regressions for the field and laboratory parameters. Numerical and regression modelling of the rock properties and strength were considered to develop numerous equations for rock properties, strength, and drilled shaft bearing capacities, as well as equations for predicting TCP, Q(un), skin friction, and end bearing for various geologic formations.