Flexural Behavior of Steel Fiber Reinforced Concrete

• Published in: Journal of materials in civil engineering Vol. 10; no. 2; pp. 86 - 97
• Main Authors: Lok, Tat-Seng, Pei, Jin-Song
• Format: Journal Article
• Language: English
• Published: Reston, VA American Society of Civil Engineers 01-05-1998
• Subjects: Applied sciences; Buildings. Public works; Concretes. Mortars. Grouts; Exact sciences and technology; Fibre reinforced concrete (including asbestos cement); Materials; TECHNICAL PAPERS; Constitutive equation; Parameter estimation; Strain softening; Fiber reinforced concrete; Bending; Steel fiber; Numerical method; Tension
• DOI: 10.1061/(ASCE)0899-1561(1998)10:2(86)
• EISSN: 1943-5533
• ISSN: 0899-1561

A constitutive model for steel fiber reinforced (SFR) concrete is proposed, in which the tensile behavior incorporates a bilinear strain softening feature. Composite material properties (fcu, ft), fiber volume concentration (Vf), fiber aspect ratio (L d), and fiber-concrete matrix bond stress ( d) are used to define the model. The model may also exhibit strain hardening characteristic depending on the magnitude of the variables. Based on the constitutive model, the full history of the flexural moment-curvature relationship for SFR concrete is calculated. Predicted curves are superimposed onto and compared with published experimental data. The results show good overall agreement; the post-cracking softening and post-cracking strengthening response were predicted. In order to facilitate the rapid assessment of the ultimate flexural behavior of SFR concrete, a secondary tensile model is derived from the proposed model. A strain softening parameter ( ) is defined for the secondary model and used to evaluate the performance and efficiency of steel fiber reinforcement. The predictive technique using this parameter can be applied to SFR concrete containing various concrete strengths, types of fibers, and fiber concentrations. Charts are presented to assist with fiber selection for flexural design of SFR concrete. Predictions based on the charts are compared with published experimental data.