The behavior of self compacting concrete exterior beam-column joints with a variation of shear reinforcement against cyclic lateral loads
Bibliographic record
Abstract
The beam-column joints are designed to have sufficient capacity under earthquake loads. This requirement needs design details of reinforcement that fulfill the seismic criteria and adequate compaction of concrete. Using Self Compacting Concrete (SCC) material can solve the difficulty of compacting conventional concrete due to the close reinforcement distance. This study aimed to analyze the behavior of the Exterior Beam-column Joints (EBJ) using SCC as materials with a variation of shear reinforcements to withstand cyclic lateral loads. The analysis was carried out using the ANSYS software and the Finite Element Method. The analysis included hysteresis curves, stress contours, ductility, stiffness, and structural strength. The performance of an EBJ without shear reinforcement (EBJ-S1 model) was compared to other EBJs using horizontal (EBJ-S2 model) and diagonal (EBJ-S3 model) shear reinforcements in the joint zones. The results showed that horizontal and diagonal shear reinforcement in the joint zones affected the performance of the EBJs in resisting cyclic lateral loads as the representative of earthquake loads. The EBJ without shear reinforcement could withstand compressive stresses of 3.33 to 17.22 MPa, while both EBJs using horizontal and diagonal shear reinforcement achieved the same compressive stresses range of 3.33 to 20 MPa. The EBJ with diagonal reinforcement performed a wider compressive area of stress contour than the EBJ of horizontal reinforcement. The EBJ-S3 model achieved the highest ductility value of 4.733 with diagonal shear reinforcements because it achieved the highest ultimate displacement of the other EBJ models.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".