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Implementation of a Simplified Method in Design of Hysteretic Dampers for Isolated Highway Bridges

2016· article· en· W2548497895 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Bridge Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsIsolatorStructural engineeringDamperBase isolationEngineeringVibration isolationNonlinear systemSubstructureVibrationMechanical engineering

Abstract

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Using seismic isolation systems for highway bridges modifies the structure’s principal vibration modes and effectively reduces the seismic base shear conveyed from the superstructure to the substructure. However, for some low-damping rubber isolation bearings, large displacements can be a problem. Supplemental hysteretic dampers can be introduced into the base-isolated bridge, which might nevertheless increase the structure base shear, and the merit of adding dampers has to be evaluated properly. In this paper, a simplified method was implemented for the design of a low-cost hysteretic damper, and the resulting isolator-damper system was tested experimentally. The design method used is based on an equivalent linearization approach. A full-scale elastomeric isolation bearing was characterized and used in the design of a hysteretic damper. Both the isolator and the damper went through cyclic testing and real-time dynamic substructuring (RTDS) methods to verify the capacity of the method to design base isolation-damping systems. The study was further extended to extreme seismic loading by nonlinear time-history analysis. The results reveal that the simplified method is adequate for use in the performance optimization of isolated-damped bridges.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.569
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.276
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it