The use of CPT for calculating axial capacity of drilled shafts
type: CreativeWork
description: The use of drilled shafts has increased significantly in the last two decades due to their ability to carry large loads economically. Current methods for calculating axial capacity of drilled shafts rely heavily on static methods. The cone penetration test is a simple, fast, and economical test that provides a continuous measurement of in-situ soil resistance with depth. The objectives of this thesis are (1) to evaluate the cone penetrometer as an alternative for calculating axial capacity of drilled shafts, (2) to evaluate available CPT methods, and (3) to develop procedures that rely on CPT resistance to calculate side and tip capacity of drilled shafts. A database of 95 full-scale drilled shaft load tests has been collected for this study. The database consists of 48 load tests in cohesionless soils, 16 load tests in cohesive soils, and 31 load tests in mixed soils. Five cone methods are evaluated: Schmertmann method, modified Schmertmann method, LPC method, Meyerhof method, and Gwizdala method. The Reese and O'Neill method is also evaluated for shafts in cohesive soils (using current database), for shafts in cohesionless soils (using q$\sb{\rm c}$/N conversions), and in mixed soils (using Reese and O'Neill database). The influence of geometry (L/B ratio, diameter, length, expanded base), construction procedure, type of bearing layer, and cone type on predicted capacity has been assessed. The study resulted in improved CPT design procedures that correlate q$\sb{\rm c}$ of the cone to q$\sb{\rm b}$ and f$\sb{\rm s}$ of a drilled shaft. Design curves are given for mechanical and electric cones. The database was used to evaluate the proposed method and other design procedures studied. The average ratio of predicted to measured capacity Q$\sb{\rm p}$/Q$\sb{\rm m}$ for the proposed method was approximately equal to one for all soil categories. The scatter exhibited in prediction results was lower than that in other CPT methods analyzed. The proposed method predicted c…
abstract: The use of drilled shafts has increased significantly in the last two decades due to their ability to carry large loads economically. Current methods for calculating axial capacity of drilled shafts rely heavily on static methods. The cone penetration test is a simple, fast, and economical test that provides a continuous measurement of in-situ soil resistance with depth. The objectives of this thesis are (1) to evaluate the cone penetrometer as an alternative for calculating axial capacity of drilled shafts, (2) to evaluate available CPT methods, and (3) to develop procedures that rely on CPT resistance to calculate side and tip capacity of drilled shafts. A database of 95 full-scale drilled shaft load tests has been collected for this study. The database consists of 48 load tests in cohesionless soils, 16 load tests in cohesive soils, and 31 load tests in mixed soils. Five cone methods are evaluated: Schmertmann method, modified Schmertmann method, LPC method, Meyerhof method, and Gwizdala method. The Reese and O'Neill method is also evaluated for shafts in cohesive soils (using current database), for shafts in cohesionless soils (using q$\sb{\rm c}$/N conversions), and in mixed soils (using Reese and O'Neill database). The influence of geometry (L/B ratio, diameter, length, expanded base), construction procedure, type of bearing layer, and cone type on predicted capacity has been assessed. The study resulted in improved CPT design procedures that correlate q$\sb{\rm c}$ of the cone to q$\sb{\rm b}$ and f$\sb{\rm s}$ of a drilled shaft. Design curves are given for mechanical and electric cones. The database was used to evaluate the proposed method and other design procedures studied. The average ratio of predicted to measured capacity Q$\sb{\rm p}$/Q$\sb{\rm m}$ for the proposed method was approximately equal to one for all soil categories. The scatter exhibited in prediction results was lower than that in other CPT methods analyzed. The proposed method predicted c…
author: Alsamman, Omar Mohammed
language: eng
keywords: Engineering, Civil
date published: 2011-05-07T13:26:57Z
date modified: 2026-07-22T22:25:19Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2142/22037