Experimental and Numerical Investigations of Laced Built-Up Lightweight Concrete Encased Columns Subjected to Cyclic Axial Load
Bibliographic record
Abstract
The steel-concrete composite column comprises a steel core and surrounding concrete. The purpose of the system is to provide analysis and design techniques for a newly invented class of laced steel-concrete composite short columns for cyclic axial loads. To minimize the increasing density issues associated with nominal strength concrete and in consideration of the depletion of natural resources required to produce concrete, factory-obtained lightweight sintered fly ash aggregates with and without basalt fiber are employed. The normal-weight concrete containing basalt fiber is shown to be more ductile than any other column. The axial deformation of columns LNA and LSA at failure was found to be 3.5 mm, whereas columns LNAF and LSAF reached an axial shortening of 4.5 mm at failure. The column LSAF was found to have 5.3% more energy absorption than the LSA and 11.5% less than the column LNAF. It was observed that the rigidity of these fabricated components had been enhanced. It was found that the section configuration with a lacing system had improved confinement effects and ductility. Comparing the finite element analysis to the experimental data revealed a strong connection with numerical modeling, with a variance of around 8.77%.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".