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Sensitivity analysis of corrosion rate prediction models utilized for reinforced concrete affected by chloride
journal contribution
posted on 2013-01-01, 00:00 authored by Frank CollinsFrank Collins, K Siamphukdee, R ZouChloride-induced reinforcement corrosion is one of the major causes of premature deterioration in reinforced concrete (RC) structures. Given the high maintenance and replacement costs, accurate modeling of RC deterioration is indispensable for ensuring the optimal allocation of limited economic resources. Since corrosion rate is one of the major factors influencing the rate of deterioration, many predictive models exist.
However, because the existing models use very different sets of input parameters, the choice of model for RC deterioration is made difficult. Although the factors affecting corrosion rate are frequently reported in
the literature, there is no published quantitative study on the sensitivity of predicted corrosion rate to the various input parameters. This paper presents the results of the sensitivity analysis of the input parameters
for nine selected corrosion rate prediction models. Three different methods of analysis are used to determine and compare the sensitivity of corrosion rate to various input parameters: (i) univariate regression analysis, (ii) multivariate regression analysis, and (iii) sensitivity index. The results from the analysis have quantitatively verified that the corrosion rate of steel reinforcement bars in RC structures is highly sensitive to corrosion duration time, concrete resistivity, and concrete chloride content. These important findings establish that future empirical models for predicting corrosion rate of RC should carefully consider and
incorporate these input parameters.
However, because the existing models use very different sets of input parameters, the choice of model for RC deterioration is made difficult. Although the factors affecting corrosion rate are frequently reported in
the literature, there is no published quantitative study on the sensitivity of predicted corrosion rate to the various input parameters. This paper presents the results of the sensitivity analysis of the input parameters
for nine selected corrosion rate prediction models. Three different methods of analysis are used to determine and compare the sensitivity of corrosion rate to various input parameters: (i) univariate regression analysis, (ii) multivariate regression analysis, and (iii) sensitivity index. The results from the analysis have quantitatively verified that the corrosion rate of steel reinforcement bars in RC structures is highly sensitive to corrosion duration time, concrete resistivity, and concrete chloride content. These important findings establish that future empirical models for predicting corrosion rate of RC should carefully consider and
incorporate these input parameters.
History
Journal
Journal of Materials Engineering and PerformanceVolume
22Issue
6Pagination
1530 - 1540Publisher
SpringerLocation
Amsterdam, The NetherlandsPublisher DOI
ISSN
1059-9495Language
engNotes
Cited By :1 Export Date: 15 September 2015Publication classification
C1.1 Refereed article in a scholarly journalCopyright notice
ASM International 2013Usage metrics
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No categories selectedKeywords
chloride-induced corrosioncorrosion damage modelingreinforced concretesensitivity analysisScience & TechnologyTechnologyMaterials Science, MultidisciplinaryMaterials ScienceCOVER-CRACKINGSTEEL REINFORCEMENTSERVICE LIFEREBAR CORROSIONRC STRUCTURESPROPAGATIONTEMPERATUREDETERIORATIONRESISTIVITYSATURATION
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