Abstract

Tension-stiffening effects can significantly influence the flexural performance of cracked reinforced concrete specimens. Such effect is amplified for fiber-reinforced concrete, given the fact that fibers can bridge the cracks. The objective of this study was to develop a model to predict the deflection of cracked reinforced ultra-high performance concrete (R-UHPC) beam elements. The modeling approach characterized the average bending moment of inertia by combining the existing model used for conventional reinforced concrete and the analytical model of stress distribution of UHPC along the cross-section. The finite element analysis (FEA) was employed to evaluate the flexural deflection based on the average bending moment of inertia. The calculated load-deflection relationships have been compared to experimental results. The results indicated that the relative errors of deflection between predicted and experimental results can be controlled within 15%, compared to values ranging from 5% to 50% calculated by neglecting the tensile properties of cracked UHPC and values ranging from 5% to 30% calculated by effective inertia of bending moment of ACI code. Therefore, the developed model can be used in practice because it can secure the accuracy of deflection prediction of the R-UHPC beams. Such a simplified model also has higher sustainability compared to FEA using solid elements since it is easier and time-saving to be established and calculated.

Department(s)

Civil, Architectural and Environmental Engineering

Comments

This project was sponsored by the Program for Changjiang Scholars and Innovative Research Team in University (IRT15R29), Young Elite Scientist Sponsorship Program by CAST, lzjtu EP support (201606), collaborative innovation team of science and technology for colleges and universities in the Gansu Province (2017C-08) and the Long Yuan Youth Innovative Talents Support Programs.

Keywords and Phrases

Cracked beam; Flexural strength; Inertia of bending moment; Tension stiffening; UHPC

International Standard Serial Number (ISSN)

2071-1050

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2022 The Authors, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Publication Date

01 Jan 2022

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