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Predicting the Ultimate Bearing Capacity of Bolts with an Optimized Function Model

Author(s):



Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2020
Page(s): 1-9
DOI: 10.1155/2020/4934260
Abstract:

Bolts are widely employed as an effective ground reinforcement element to secure the underground workplaces. Due to their inherent accessibility, low cost, and easy implementation, rebar bolts are the most popular and commonly used reinforcement in ground support systems. However, it is expensive to obtain failure stage data from in situ pullout tests to study the ultimate bearing capacity of rebar bolts. In this paper, several function models that are commonly used for predicting the ultimate bearing capacity of bolts are presented. Based on these models, a general function model is constructed to replicate the relationship between the load and displacement of a rebar bolt in a pullout test. In addition, the value ranges of relevant parameters in the function model are also assessed. By analysing the general function model, an improved exponential and power function model, which is essential to bolt design, is presented to simulate the load-displacement curve and predict the ultimate bearing capacities of bolts. Comparisons between the improved exponential and power function model and other regular models show that the former has a higher calculation accuracy and good stability. Moreover, a comparison of the predicted ultimate bearing capacity and the test results indicates the reliability of the improved exponential and power function model. The improved exponential and power function model can provide theoretical guidance for the design of rebar bolts applied in reinforcement engineering.

Copyright: © Bin Zheng et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10444088
  • Published on:
    05/10/2020
  • Last updated on:
    02/06/2021
 
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