Optimal probability‐based partial mass isolation of elevated coal scuttle in thermal power plant building
Why this work is in the frame
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Bibliographic record
Abstract
Summary Partial mass isolation (PMI) system is a practical strategy to mitigate seismic response of the main structure. Many studies provide various formulas to estimate an optimum design solution for the structure under simplified excitation models. But the efficiency of these optimization methods under actual ground motion records requires investigation. This paper proposes a new optimization design framework, which considers the randomness of ground motions. To describe the vibration depression effects of the PMI under various records, several theoretical distributions were assumed and tested. A Weibull distribution was selected because of its best performance in the chi‐squared tests among the several theoretical distributions. A sensitivity study on the number of records was performed to ensure the accuracy of estimated parameters with a relatively small sample size. This framework was adopted in the design of a PMI system for a large‐scale thermal power plant building through both single‐objective and multiobjective optimization procedures. Optimal design results from the single‐objective optimization procedure were compared with those from traditional formulas. Additionally, with the relative displacement limitation, the Pareto optimum set was obtained from the multiobjective optimization procedure. The final design was compared with the single‐objective optimization result.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it