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Durability Evaluation of Concrete in Cold and Arid Regions Based on Grey Relational Theory

Author(s):
ORCID

ORCID

Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2022
Page(s): 1-10
DOI: 10.1155/2022/6287810
Abstract:

Aiming at the outstanding problem of concrete durability in cold and arid regions, the Datonghe-Qingwangchuan Diversion Project in Gansu Province, China, was used as a typical research area, and erosion products were determined by field sampling and laboratory XRD analysis. Three durability evaluation indices, namely, the mass loss rate, relative dynamic elastic modulus (RDEM), and compressive strength loss rate, were measured via indoor accelerated testing. Based on grey relational theory, a concrete durability evaluation model was constructed. The critical failure values of the three evaluation indices were introduced as a set of data to optimize the model and determine the grey relational degree of each group of concrete specimens under different working conditions. The results show that using the test results and the optimized grey relational analysis evaluation model, the concrete specimens mixed with an air-entraining agent have strong resistance to composite erosion. The durability of concrete specimens with an air-entraining agent content of 0.016% and fly ash content of 15% is better, and a high content (30%) of fly ash accelerates the damage of concrete specimens. The model calculations are consistent with the test results. This method can solve the problem of the durability of concrete specimens in the whole test cycle not being fully evaluated. The results of the study provide useful references for concrete mix proportion optimization and durability evaluation problems.

Copyright: © Li Gong et al. 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
    10698148
  • Published on:
    11/12/2022
  • Last updated on:
    15/02/2023
 
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