Methodology for Obtaining Optimal Sleeve Friction and Friction Ratio Estimates from CPT Data

Abstract

Cone penetration testing (CPT) is a cost effective and popular tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic penetrometer into penetrable soils and recording cone bearing ( q c ), sleeve friction ( f c ) and dynamic pore pressure ( u ) with depth. The measured q c , f s and u values are utilized to estimate soil type and associated soil properties. A popular method to estimate soil type from CPT measurements is the Soil Behavior Type (SBT) chart. The SBT plots cone resistance vs friction ratio, R f [where: R f = ( f s / q c )100%]. There are distortions in the CPT measurements which can result in erroneous SBT plots. Cone bearing measurements at a specific depth are blurred or averaged due to q c values being strongly influenced by soils within 10 to 30 cone diameters from the cone tip. The q c HMM algorithm was developed to address the q c blurring / averaging limitation. This paper describes the distortions which occur when obtaining sleeve friction measurements which can in association with q c blurring result in significant errors in the calculated R f values. This paper outlines a novel and highly effective algorithm for obtaining accurate sleeve friction and friction ratio estimates. The f c optimal filter estimation technique is referred to as the OSFE-IFM algorithm. The mathematical details of the OSFE-IFM algorithm are outlined in this paper along with the results from a challenging test bed simulation. The test bed simulation demonstrates that the OSFE-IFM algorithm derives accurate estimates of sleeve friction from measured values. Optimal estimates of cone bearing and sleeve friction result in accurate R f values and subsequent accurate estimates of soil behavior type.