Reassessing the Plastic Hinge Model for Energy Dissipation of Axially Loaded Columns
Bibliographic record
Abstract
This paper investigates the energy dissipation potential of axially loaded columns and evaluates the use of a plastic hinge model for analysis of hi-rise building column collapse under extreme loading conditions. The experimental program considered seven axially loaded H-shaped extruded aluminum structural section columns having slenderness ratios that would be typical of floor-to-ceiling heights in buildings. All seven test specimens initially experienced minor-axis overall buckling followed by formation of a plastic hinge at the mid-height region, leading to local buckling of the flanges on the compression side of the plastic hinge, and eventual folding of the compression flanges. The experimental energy absorption, based on load-displacement relations, was compared to the energy estimates based on section plastic moment resistance based on measured yield stress and based on measured hinge rotations. It was found that the theoretical plastic hinge model underestimates a column’s actual ability to absorb energy by a factor in the range of 3 to 4 below that obtained from tests. It was also noted that the realizable hinge rotation is less than 180° . The above observations are based, of course, on actual columns being able to sustain high tensile strains at hinge locations without fracturing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".