EVALUATION OF NONLINEAR SEISMIC DEMANDS OF LOW-RISE CLT BUILDINGS USING SIMPLIFIED ANALYSIS METHODS
Bibliographic record
Abstract
For the seismic performance evaluation of both new and existing low-rise buildings, practicing engineers are often interested in using first-mode based nonlinear static analysis procedures as prescribed in various guidelines and standards. These procedures not only require significantly less computational time and modelling effort compared to the detailed dynamic analysis but also can provide insight into the complex nonlinear response and behaviour of buildings (e.g., progression of inelastic action, energy dissipation, strength degradation, etc.). This paper aims to evaluate the inelastic seismic demands and performance of cross-laminated timber (CLT) shear wall buildings designed according to the capacity design approach and the applicable Canadian standard (CSA-O86). For this purpose, detailed inelastic models of several case study CLT shear wall buildings (with typical plan configurations, storey heights, and connection types) are developed and subjected to the monotonic pushover analysis to understand the key characteristics of their lateral response. The inelastic seismic demands of case study buildings are then determined using two nonlinear static analysis procedures, i.e., the FEMA 440 Capacity Spectrum Method (CSM) and the ASCE 41-17 Displacement Coefficient Method (DCM). The results indicate that the seismic performance of case study buildings (as determined using these methods) is acceptable and is in alignment with design assumptions recommended by CSA-O86. The yielding hierarchy in connections is consistent with the intended design criteria. At the design level earthquake, numerous spline connections have yielded, while the response of hold-downs remained in the elastic range indicating their reserve strength and stiffness. The study also demonstrates that both the CSM and DCM methods can be effectively used to predict the inelastic seismic demands of low-rise CLT shear wall buildings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".