Seismic evaluation of friction spring‐based self‐centering braced frames based on life‐cycle cost
Bibliographic record
Abstract
Abstract In recent decades, a variety of self‐centering braces (SCBs) have been developed to address the limitations of conventional frames by decreasing residual drift due to earthquakes. However, the initial construction cost of self‐centering (SC) structures is expected to be higher and the study about its cost‐effectiveness over the life‐cycle span is limited. This paper presents a seismic life‐cycle cost evaluation of emerging friction spring‐based self‐centering braced frames (SCB‐Fs) compared with traditional buckling restrained braced frames (BRB‐Fs) when an existing structure is upgraded. Particular focus is on the effect of residual deformation, initial construction cost, and high fatigue performance of the SCB. Following the performance‐based design of the SCB‐F and BRB‐F, system‐level analyses are conducted. Numerical results of case‐study buildings indicate that the total expected annual loss (EAL) of the BRB‐F increases by approximately three times when the effect of residual deformation is considered, while its effect on the total EAL of the SCB‐F is negligible. Besides, the superior performance of the SCB‐F compared to BRB‐F is highlighted by a substantial reduction in EAL induced by earthquakes. In addition, the acceleration‐related seismic losses of SCB‐F constitute approximately 44% of the total EAL. Its contribution is significantly larger in the case of the SCB‐F compared to the BRB‐F. From the perspective of economic benefit, increasing the structural life‐cycle span is beneficial to the SCB‐F compared to the BRB‐F. The high fatigue performance of the SCB is favorable to increase the economic benefit of the SCB‐F, especially when the reduction of repair time is considered. The economic benefit of the SCB‐F compared to the BRB‐F is highly related to the initial construction cost. Taking the 100 years as an expected life‐cycle span, the high initial construction cost of the SCB‐F would not be paid off when the unit cost of the SCB is about 2.1 times that of the BRB.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".