Efficiency of the Alternative Load Path Method to Evaluate the Progressive Collapse Potential of 3D Building under Blast Load
Bibliographic record
Abstract
the work in the progressive collapse of three-dimensional composite buildings quite limited due to the cost and difficulties of the full-scale experimental tests and the complexity of the modelling technique.Researchers and design engineers are following The Alternative Load Path method (ALP) recommended by GSA and DoD guidelines to mitigate the progressive collapse potential.The commonly used ALP method, which considers as a threat-independent methodology, taking into account single column removal scenarios only regardless of the threat load type.This paper investigates the efficiency of the ALP to determine the progressive collapse potential of 3D composite building when subjected to 500 kg of TNT.Two-stage nonlinear dynamic analysis of 3D composite 9-story building with top and seat double web angle connection is carried out.In the first stage of analysis the axial load carried by the columns under gravity load is calculated.The second stage devotes to find out the number of columns likely to be involved in the progressive collapse using the damage index criteria through three-step of loading.A precise analysis is implemented to find out the effect of column location in the remaining capacity of the column.The influence of the boundary condition on the column response under blast load is highlighted.The results show that the ALP methodology is not usually conservative and may be more than one column wiped out under 500 kg of TNT which may be carried by a small vehicle.The commonly used damage criteria (stability, yielding and fracture) cannot capture the realistic damage of axial load bearing column, and the damage index which is related to its global behaviour has to be used.The structure response drastically increased when two columns removed at a time under blast load compared to the single column removal recommended by ALP of the DoD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".