Reliability Analysis of a Reinforced Concrete Slab-Column Connection without Shear Reinforcement
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Bibliographic record
Abstract
Punching shear design is a topic of international interest because it is critical for reinforced concrete slab-column connections, based on the fact that this type of connection can fail in a brittle way and without warning. Punching shear strength depends on many variables which may have some degree of uncertainty due to geometry, material properties, manufacturing processes, etc. In this study, reliability analysis will be performed by applying Monte Carlo Simulation due to random input parameters for current design codes (ACI 318-11, EC2-2004) and for an analytical punching shear model, such as Critical Shear Crack Theory, which was incorporated in the new fib Model Code (2010), so as to be compared and useful conclusions to be derived. For sensitivity analysis, valuable results will be derived on how specific parameters influence the output response (i.e., punching shear resistance). The sensitivity analysis will show how the uncertainty associated with the model's input parameters impacts the resultant uncertainty of its output, and which input parameters affect (most and least) the punching shear strength. Moreover, simulation results will give us an idea on which parameters are most important and which are the consequences of changing these parameters, regarding the punching shear strength of a slab-column connection, so as to improve punching shear design.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it