Seismic performance of interior beam‐column joints using reinforced slag‐based geopolymer concrete
Bibliographic record
Abstract
Abstract Although geopolymer concrete (GC) is recognized as a green and low‐carbon material, GC structural members, particularly beam‐column joints, have been rarely studied. In the present study, eight reinforced GC joints and three reinforced concrete (RC) interior beam‐column joints were tested under cyclic loading. The test parameters were the concrete type, joint shear demand‐to‐capacity ratio, and axial‐compression ratio. The structural performance, including the failure mode, crack development, cyclic behavior of reinforced GC beam‐column joints, was evaluated. The test results showed that the cyclic behavior and crack development of the reinforced GC beam‐column joints differed from those of RC beam‐column joints. The increase of axial compression ratio improved the seismic performance of reinforced GC beam‐column joints with the joint shear demand‐to‐capacity ratio of 0.96–1.01. When the joint shear demand‐to‐capacity ratio was 1.54–1.61, the increase of axial compression ratio (0.1–0.3) improved the seismic performance, while the axial compression ratio of 0.5 was unfavorable because of significant joint shear damage. The applicability of the control conditions in the current design codes to the reinforced GC joints was evaluated. The control conditions of ACI 318–19 were applicable to the seismic design of reinforced GC beam‐column joints. On the other hand, the control conditions of GB50010‐2010 were not applicable because of the overestimated upper limit value of the joint shear demand‐to‐capacity ratio and axial compression ratio.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".