Behaviour of double skin profiled composite shear wall system under in-plane monotonic, cyclic and impact loadings
Bibliographic record
Abstract
This research investigated the behaviour of a new form of composite shear wall system consisting of two skins of profiled steel sheeting and an infill of concrete under in-plane monotonic, cyclic and impact loading. The extensive experimental, analytical and numerical investigations of composite shear walls provided information on strength, stiffness, load-deformation response, steel sheet-concrete interaction, stress-strain characteristics and failure modes.Eight composite wall specimens with overall dimensions of 1626 mm (height) x 720 mm (width) were tested under monotonic, cyclic and impact loading. Steel sheet-concrete connections were provided by intermediate fasteners to generate composite action. Two types of steel sheets classified based on strength as mild and high strength and also, two types of concrete-infill namely Self-Consolidating Concrete (SCC) and Engineered Cementitious Composites (ECC) were used to construct the walls. An analytical model for shear resistance of the composite wall was developed based on existing models taking into account the shear capacity of the steel sheets, concrete core and steel-concrete interaction. Moreover, two non-linear finite element models for the composite wall under monotonic/cyclic and impact loading were developed using proprietary ABAQUS/CAE software. The performance of developed numerical models was validated against experimental results and then the models were utilized to carry out an extensive parametric study to understand the influence of material and steel-concrete interaction on the structural behaviour of the walls.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".