Analysis and design of laterally unsupported portal frames for out-of-plane stability
Bibliographic record
Abstract
A methodology for the analysis and design of laterally unsupported portal frames is proposed. A finite element model is developed to predict the elastic critical load and associated buckling mode. Regression analysis is then conducted to find lateral displacement and rotation field expressions that closely approximate the buckled configurations predicted by the finite element analysis. The obtained functions are then substituted into the total potential energy expression, and the stationarity conditions are evoked. The resulting eigen-value problem is solved for the out-of-plane buckling loads that are then compared with those based on the finite element model. The agreement between the two solutions provides an indication of the accuracy of the simplified energy solution. The member destabilizing effects induced by axial forces are separated from those induced by strong axis bending. The separation of these two effects is subsequently exploited in a two-step eigen-value procedure, aimed at determining the key member resistances defined in the interaction check of the standard CSA-S16-01, while accurately modeling the boundary conditions of the member. These are (i) compressive resistance of the member in the absence of bending effects and (ii) flexural resistance of the member in the absence of axial force effects.Key words: portal frames, lateral buckling, finite element analysis, wide flange sections, frame design, principle of stationary potential energy.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".