Efficacy of Several Design Methods for Predicting the Axial Compressive Capacity of Piles

Author:

Ozturk Baturalp1ORCID,Kodsy Antonio1ORCID,Bazi Youssef1ORCID,Iskander Magued G.1ORCID

Affiliation:

1. NYU Tandon School of Engineering, Brooklyn, NY

Abstract

A variety of design methods for determining piles’ axial compressive load capacity are routinely employed in current practice. These range from methods specified in building codes to proprietary methods developed and employed by an assortment of engineering firms. In this study, the performance of eight commonly used design methods was evaluated using a database of 505 load tests and associated geotechnical design parameters compiled from Professor Olson’s database and that of the Iowa State Department of Transportation. The methods investigated included standard penetration test (SPT)-based methods, such as those recommended by the Federal Highway Administration (FHWA), U.S. Army Corps of Engineers, American Petroleum Institute, and Revised Lambda; and cone penetration test (CPT)-based methods such as those recommended by the Norwegian Geotechnical Institute, Imperial College, Fugro, and University of Western Australia. Pile capacities were calculated using APILE software and were compared with the measured capacities interpreted using the standard Davisson criterion and stored in the databases. The performance of all design methods was evaluated in relation to accuracy, precision, effect of soil type, diameter, and length. Both SPT and CPT methods exhibited similar accuracies, however, CPT-based design methods exhibited significantly better precision compared with SPT-based methods. All methods had shortcomings and appeared to work best under certain conditions, which are documented in this paper. The authors believe that this evaluation will permit practicing engineers and regulating bodies to better understand the efficacy of various design approaches in common use.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Use of Machine Learning for Automated Classification of Sand Type;Transportation Research Record: Journal of the Transportation Research Board;2024-07-25

2. Forecasting the Bearing Capacity of Open-Ended Pipe Piles Using Machine Learning Ensemble Methods;IFCEE 2024;2024-05-03

3. Using Machine Learning to Predict Axial Pile Capacity;Transportation Research Record: Journal of the Transportation Research Board;2024-04-30

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3