Finite Element Modeling of Partially Composite Light-Gage Steel Tube Beam with Lightweight Concrete Deck Slab
Bibliographic record
Abstract
For the time being, the steel-concrete composite floors are commonly used in residential, office, and commercial buildings.A traditional composite floor is often constructed with hot-rolled steel.The utilization of hot-rolled steel sections in small and medium-sized buildings is not cost-efficient.Because of the material, cutting process, and labor costs.In addition, the common usage of light-gage cold-formed members, which are often utilized in a non-composite manner, has led to the employment of bigger section sizes.Consequently, the replacement of hot-rolled steel sections with light-gage steel ones to act compositely is a cost-efficient solution.Therefore, this study uses FE modeling with ABAQUS software to investigate the structural behavior of the partially composite light-gage tube beam with a lightweight concrete deck slab.Results of the analysis show that changing the concrete type has a minor influence on strength and stiffness.Changing the concrete type from lightweight to normal weight increases the strength by 3.5%, and increasing the yield stress has a major contribution to the strength.Increasing the yield stress of the beam from 355 MPa to 700 MPa increases the strength by 35.8%.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".