A Method for Predicting Pile Capacity Using Cone Penetration Test Data

سال انتشار: 1398
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 213

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شناسه ملی سند علمی:

JR_CIVLJ-7-2_008

تاریخ نمایه سازی: 23 شهریور 1403

چکیده مقاله:

The massive construction in poor lands has encouraged engineers to use deep foundations in order to transfer superstructure loads to the subsoil. Since soil excavation, sampling, and laboratory testing as a part of site investigation are relatively difficult, in-situ tests such as cone penetration test (CPT) as a very informative test may be recommended. The CPT has been widely used in engineering as a part of site investigation, and its data has been used to determine the axial capacity of piles. In this paper, the prediction capability of three empirical widely famous old methods used to predict the axial pile capacity based on CPT data is evaluated by using field data obtained from direct field pile loading tests. In this evaluation, the direct pile load test results are used as measured data. Three popular famous statistical evaluation methods namely the best-fitted line, geometric mean, and geometric standard deviation have been used. The evaluation results indicate that generally although predicting methods based on CPT data have been widely used to determine the axial bearing capacity of piles, they need to be upgraded for the economic and relatively accurate design of piles. According to the statistical studies carried out in the current research, among three old empirical methods, although the Nottingham and Schmertmann Method (۱۹۷۵, ۱۹۷۸) (NSM) [۷, ۸] has the best agreement with test results, it is felt that the method needs to be upgraded. The modification of NSM has been done in the current paper using a comprehensive database.

کلیدواژه ها:

Cone Penetration Test (CPT) ، Static Pile Load Test ، Axial pile capacity ، Statistical methods

نویسندگان

Parisa Heidari

Graduate student, Dept of Civil Engineering, K N Toosi University of Technology, Tehran, Iran

Mahmoud Ghazavi

Civil Engineering Department, K.N. Toosi University of Technology

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