Shear Strength of Sandwich Panel Walls
Bibliographic record
Abstract
Cast in situ sandwich panel walls construction systems become a real competitor to the traditional systems especially in low rise buildings. The energy efficiency of this type of buildings and its ease of manufacturing and construction give the opportunity of popularity of that system in many regions. The bearing walls in the sandwich panel systems are responsible for resisting both gravity and lateral loads. However, sandwich panels structural systems do not have their own code design provisions yet. Thus the designers depend on the experimental results or the simulated provisions of reinforced concrete codes or standards. In this study, eight squat sandwich panel walls are tested under both constant axial and quasi-static seismic loads. The tests parameters included boundary element type, aspect ratio, horizontal reinforcement ratio, concrete compressive strength and level of axial load. Due to the complexity of the experimental tests and the need for simple shear strength prediction methods, the feasibility of utilization of the published conventional reinforced concrete walls equations in predicting the peak shear strength of sandwich panels squat walls is discussed. The experimental shear strength results of current study and that in the literature are compared with the predictive equations published in design codes as well as those available in the literature. Eight prediction equations are selected and presented. Four equations were provided by building codes from USA, New Zealand and Canada. The other four equations were proposed in the literature. The predicted values by the New Zealand Code NZS 3101:2006 presents the best code prediction provisions and the equation proposed by Carrillo and Alcocer provides a conservative prediction with low results dispersion. The suggested modification factor on Sanchez-Alejandre and Alcocer equation gives the best shear strength prediction of sandwich panels 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 | 0.001 |
| 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) | 0.003 | 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".