Finite-element modeling of early-age concrete behavior under high level of tensile stress View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Yalin Liu, Anton K. Schindler

ABSTRACT

Thermal cracking in concrete at early ages may influence the long-term durability of a structure. A finite-element method to predict early-age stress development is developed to consider temperature effects, modulus of elasticity, creep or stress relaxation, shrinkage, and coefficient of thermal expansion. Most models consider elastic and time-dependent behavior at normal stress levels in which the effect of cracking or the level of tensile stress is not considered. However, high-stress nonlinearity coupled with creep is of paramount importance when determining the cracking risk of concrete. Nonlinear behavior at high tensile stresses is present in concrete subjected to early-age thermal loading and should be considered to obtain an accurate thermal stress analysis. Therefore, the high-stress nonlinearity was considered in this study by correcting the model with a reduced effective modulus when the tensile stress is above 70% of its tensile strength. The experimental results of 22 concrete mixtures subjected to restraint to volume change tests were used to verify the accuracy of the proposed finite-element model from initial setting to the age of cracking. Statistical analysis results show that the coefficient of determination for all stress data points above a concrete tensile strength of 70% increased from 0.39 to 0.81 when using the predictions from the proposed model compared to the original linear-elastic model. The proposed model that accounts for creep and high-stress nonlinearity has a coefficient of determination of 0.97 for all the data points from 22 concretes, and provides a feasible prediction of early-age concrete stresses from initial setting to cracking. More... »

PAGES

30

References to SciGraph publications

Journal

TITLE

Materials and Structures

ISSUE

2

VOLUME

52

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1617/s11527-019-1328-y

DOI

http://dx.doi.org/10.1617/s11527-019-1328-y

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https://app.dimensions.ai/details/publication/pub.1112318561


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