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Exploring the Emerging Evolution Trends of Probabilistic Service Life Prediction of Reinforced Concrete Structures in the Chloride Environment by Scientometric Analysis

Author(s): ORCID
ORCID
ORCID
ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2021
Page(s): 1-14
DOI: 10.1155/2021/8883142
Abstract:

To reveal the global picture and emerging evolution trends with sufficiently large literature data of RC structure’s service life prediction, especially the time to corrosion initiation, the scientometric analysis on the corresponding evolution trends was performed by using visualization software CiteSpace and VOSviewer in this paper. First, the application of CiteSpace and VOSviewer and retrieval strategy for data collection were described. And then, information visualization analysis was carried out based on the papers related to RC structure’s service life evaluation from publications number evolution, journal distribution, and authors’ contribution. Finally, document cocitation network, cooccurring keywords network, and timeline view of keywords network were conducted to discuss the research hotspots on time to corrosion initiation evaluation of reinforcement. Research results reveal that the number of publications on RC structure’s service life evaluation reached its peak in 2011. Besides, Structural Safety is the journal that makes the most significant contributions, and Professor Li CQ is the author with the most contribution score. Moreover, the knowledge body of the time to corrosion initiation prediction consists of six clusters; the high-citation articles in this field mainly focus on the multiple-parameters model and probabilistic reliability method.

Copyright: © Junzhi Zhang 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
    10646720
  • Published on:
    10/01/2022
  • Last updated on:
    17/02/2022
 
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