Structural control benchmark problem: Phase II-Nonlinear smart base-isolated building subjected to near-fault earthquakes
Bibliographic record
Abstract
Many branches of engineering, mathematics, and sciences, have relied on benchmark problems as a standard means to compare different solution techniques. Since 1996, the ASCE Structural Control and Monitoring Committee and Task Group on Benchmark Problems, the U.S. Panel on structural control, and IASCM have developed a series of benchmark control problems that offer a set of carefully modeled real-world structures in which different control strategies can be implemented, evaluated, and compared using a common set of performance indices. First-, second- and third-generation benchmark problems focusing on the response control of seismic and wind-excited buildings, and seismically excited long-span cable-stayed bridges have been developed and evaluated. The U.S. Panel on structural control and monitoring (currently chaired by Professor Satish Nagarajaiah, Rice University, Houston, TX), IASCM, and the ASCE structural control and monitoring committee have developed a new benchmark study to compare control strategies designed for a base-isolated building subjected to strong near-fault pulse-like ground motions. The special issue on phase I smart base-isolated building benchmark problem with a linear isolation system was successfully completed and published. This special issue focuses on the phase II smart base-isolated building benchmark problem with nonlinear isolation systems—friction or elastomeric system. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".