A new method for rapidly capturing the strength and full nonlinear response of partially interacting steel–concrete composite beams
Bibliographic record
Abstract
A semi-analytical procedure is presented for predicting the complete flexural response of partially interacting steel-concrete composite beams up to failure. The governing equation of the Euler-Bernoulli beam theory is solved wherein concrete, steel and the shear connectors joining the concrete slab to the steel beam are assumed to have nonlinear stress-deformation relationships. The adopted constitutive relationship for the connectors allows for partial or full composite action. The solution is applicable to beams and one-way slabs subjected to concentrated or uniform load and/or their combination. The governing equation is numerically solved by satisfying the equilibrium and compatibility requirements along the member. For the reinforced concrete part of the composite beam, a nonlinear moment-curvature relationship is developed that accounts for concrete nonlinearity in compression and for cracking and tension-stiffening in tension as well as for steel reinforcement nonlinearity. The steel profile is assumed to have a bilinear elasto-plastic strain-hardening moment-curvature relationship. Comparison of the proposed model results with the corresponding experimental load-deflection curves and interfacial shear-slip curves of several beams tested by others shows good agreement. The relative simplicity, efficiency and easy application of the present solution make it possible to accurately predict the failure load, interfacial slip and full nonlinear response of partially interacting composite beams.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".