Effect of base connection rotational stiffness on seismic performance of steel moment resisting frames
Bibliographic record
Abstract
Exposed column base plate (CBP) connections play a pivotal role on the seismic performance of steel moment-resisting frames (SMRFs) by transmitting axial loads, shear forces, and bending moments from the superstructure to the foundation. Traditional analyses typically idealize these connections as either pinned or fixed, neglecting their inherent semi-rigid rotational stiffness, which can result in erroneous predictions of interstory drifts, base shear demands, floor accelerations, and collapse capacities. This study incorporates finite element method (FEM) derived rotational stiffness values, quantified as multiples of the column's flexural rigidity (EI/H), into nonlinear analyses of a five-story SMRF designed according to CSA S16-19 and NBCC 2020 for a Site Class D location in Vancouver, British Columbia, Canada. Elastic rotational springs, representing different base stiffness, ranging from pinned to fixed are considered. Modal analyses indicate that higher base stiffness reduces fundamental periods and redistributes modal mass participation toward higher modes. Nonlinear pushover analyses reveal that models with increased base stiffness exhibit enhanced lateral strength, delayed yielding, and preferred beam-hinge mechanisms, in contrast to the soft-story failure observed in the pinned base model. Nonlinear time-history analyses of stiffer base models, employing 20 ground motions scaled to the NBCC 2020 spectrum, demonstrate reduced peak interstory drifts but amplified floor accelerations, underscoring a trade-off between displacement control and inertial demands. Fragility curves developed through incremental dynamic analyses yield elevated median capacities for damage states and collapse margin ratios, affirming lower vulnerability in semi-rigid and fixed configurations. The results emphasize the critical need for accurate semi-rigid modeling, particularly accounting for bi-directional effects, to achieve balanced seismic resilience in SMRFs.
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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) | 0.001 | 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".