Numerical Evaluation of Structural Behavior of the Simply Supported FRP-RC Beams
Bibliographic record
Abstract
The main problem of steel-reinforced concrete structures is corrosion of steel reinforcements which leads to premature failure of concrete structures. This problem costs a lot annually to rehabilitate and repair concrete structures. In order to improve the long-term performance of reinforced concrete structures and for preventing this corrosion problem, conventional steel bars in concrete can be substituted by Fiber Reinforced Polymer (FRP) bars. In this study the structural behavior and performance of the simply supported concrete beams reinforced with the FRP bars are numerically evaluated and compared with the conventionally steel-reinforced concrete beams. The commercial Finite Element program, ABAQUS, was used for this purpose and the ability of the Concrete Damage Plasticity constitutive model for concrete was investigated for modeling the non-linear behavior and fracture of the concrete material. Two different cases were considered for evaluating the structural behavior of FRP-reinforced concrete beams; case (a) effect of different types and ratios of reinforcements, and case (b) effect of different concrete qualities. For the first case, different reinforcement types (i.e., CFRP, GFRP, AFRP and steel bars) and various reinforcement ratios were considered and the concrete material assumed to be of normal strength quality (NSC). For the second case, it was assumed that the concrete for all the FE models has high strength quality (HSC) and hence, for comparing the results of the HSC and NSC models, the mechanical properties of the reinforcements were considered to be identical as the first case. The results of modeling are presented in terms of; moment vs. mid-span deflection curves, compressive strain in the outer fiber of concrete, tensile strain in the lower tensile reinforcement, cracking and ultimate moments, service and ultimate deflections, deformability factor and mode of failure. Finally, the results of simulations are compared with predictions of several design models including ISIS Canada Model, ACI 440-H and CSA S806-02 standards.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".