Bridge bearing fuse systems for regions with high-magnitude earthquakes at long recurrence intervals
Bibliographic record
Abstract
This paper describes an ongoing experimental and computational program investigating bridge bearing assemblies common in mid-America, to ascertain their effectiveness as seismic fuses and to characterize their component behavior during large displacements of the superstructure. The bearing assemblies considered in the testing program are intended to address seismic risk for regions where the hazard is dictated by infrequent, but large magnitude, seismic events such as may occur in the New Madrid seismic zone near southern Illinois. Test specimens include low-profile fixed bearings, as well as steel-reinforced elastomeric bearings. The elastomeric bearings, some of which include a Teflonon-steel sliding surface, have stiffened L-shaped retainer brackets to restrain transverse response at service load levels. The bearing components being studied are intended to ensure predictable, elastic response for service loading, including small seismic events. However, for larger seismic events, mechanical response of these bridge bearings will transition through highly nonlinear mechanisms that require a refined behavioral understanding, including post-yield deformations and fracture of selected steel components in the fixed bearings, high shear strain response in the elastomer, and sliding along predetermined interfaces. The experimental program is evaluating potential fuse mechanisms and component behavior that will then be implemented in computational models of complete bridges to assess global system response. The research will develop comprehensive test data upon which to base bridge design guidelines for proportioning fuse components to provide reliable service performance, as well as a passive, quasi-isolated global response during a major seismic event. This design dichotomy of bridge response ensures seismic safety (i.e., prevention of span loss) while maintaining appropriate fiscal responsibility consistent with the nature of seismic risk in regions where major earthquakes are expected to occur only at long recurrence intervals. 1 Graduate Research Assistant, Dept. of Civil and Environmental Engineering, University of Illinois at UrbanaChampaign, Urbana, IL 61801 2 Professor, Dept. of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 3 Associate Professor, Dept. of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 4 Assistant Professor, Dept. of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801 Proceedings of the 9th U.S. National and 10th Canadian Conference on Earthquake Engineering Compte Rendu de la 9ieme Conference Nationale Americaine et 10ieme Conference Canadienne de Genie Parasismique July 25-29, 2010, Toronto, Ontario, Canada • Paper No
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".