TY - GEN
T1 - Developed Predictive Design Equations for Drilled Shaft Capacities for Various Rock Formations by Conducting Site Investigation and Load Test
AU - Salman, Hosam
AU - Puppala, Anand J.
AU - Chittoori, Bhaskar C.S.
N1 - Publisher Copyright:
© 2024 American Society of Civil Engineers (ASCE). All rights reserved.
PY - 2024
Y1 - 2024
N2 - 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 (Qun) 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, Qun, skin friction, and end bearing for various geologic formations.
AB - 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 (Qun) 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, Qun, skin friction, and end bearing for various geologic formations.
KW - and Texas.
KW - Bi-Directional Load Cell Testing
KW - Correlations
KW - Database
KW - Drilled Shafts
KW - Intermediate Geomaterials (IGM)
KW - Limestone; Sandstone
KW - Osterberg load test
KW - Regressions
KW - Rock
KW - Shale
KW - Site Investigation
KW - Statnamic
KW - Texas Cone Penetrometer (TCP)
UR - http://www.scopus.com/inward/record.url?scp=85192989478&partnerID=8YFLogxK
U2 - 10.1061/9780784485408.005
DO - 10.1061/9780784485408.005
M3 - Conference contribution
AN - SCOPUS:85192989478
T3 - Geotechnical Special Publication
SP - 35
EP - 50
BT - Geotechnical Special Publication
A2 - Moug, Diane M.
T2 - 2024 International Foundations Congress and Equipment Expo: Drilled and Driven Foundations and Innovative and Emerging Approaches for Foundation Engineering, IFCEE 2024
Y2 - 7 May 2024 through 10 May 2024
ER -