Technical and Economical Comparison of Steel Shear Wall and Steel Bracing Systems in Steel Structures
Bibliographic record
Abstract
Results of research conducted on the Steel Shear Walls in 2004 and 2005 years, obliged USA and Canada design provisions to present related rules of this system in their new editions of steel structures. Hence, in recent years, the use of Steel Shear Walls in the design of new structures and rehabilitation of existing buildings in different countries have been speared. Concentrically Braced Frame systems is one of the common resistant systems against lateral loads in Iran. Designers have put this system under consideration duo to reduction of consumption of steel weight and economic efficiency in comparison with other systems. For this purpose, in this research, in order to compare the Concentrically Braced Frame systems and Special Steel Shear Walls, three structures with different heights of these two systems were analyzed and designed by ETABS software. Also, strip model method presented in seismic design provisions of USA was used for the designing of Steel Shear Walls. To compare the performance of these two systems, introduced structures were analyzed under nonlinear static analysis (pushover) by SAP2000 software. The results of this study showed that in structures with high height, performance of Seel Shear Wall system is more appropriate than Special Concentrically Braced system and use of Steel Shear Wall systems is more affordable in high structures. At the end of this research to evaluate the actual behavior of Steel Shear Walls, one of the designed frames with this system was analyzed under Tabas, El Centro and Kobe earthquakes by finite element ABAQUS software. It was apparent that steel base shear curve versus time, is dependent on earthquake record.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".