Influence of Column Strength and Stiffness on the Inelastic Behavior of Strong-Column-Weak-Beam Frames
Bibliographic record
Abstract
The design philosophy of strong-column-weak-beam (SCWB) in which plastic deformation is predominantly allowed to occur in beams while columns remain essentially elastic is commonly adopted in seismic design codes for moment-resisting frames. Practical design of SCWB frames is employed by using the beam-to-column-joint ratio, which is mainly done to prevent formation of plastic hinges in columns without consideration of the global inelastic behavior of the SCWB frame. This paper investigates the inelastic behavior of SCWB frames with different distributions of beam and column plastic strengths at different ductility demand levels. Midrise 9-story steel frames were designed as SCWB frames with the same lateral strength but with different column strength and stiffness relative to those of the beams. Nonlinear static and dynamic analysis results indicate that the relative plastic flexural capacities of the beams and column bases have a significant effect on the structural deformation and seismic response of SCWB frames. The structural response and beam-to-column-joint demand strongly depend on the column strength and stiffness. The results indicate that a global parameter may be used in addition to the beam-to-column-joint ratio to control the inelastic response behavior of strong-column-weak-beam frames.
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) | 0.000 | 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".