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Record W4367553915 · doi:10.1061/9780784484777.010

Multi-Hazard Resilience Assessment of Base-Isolated Bridges

2023· article· en· W4367553915 on OpenAlexaff
Vahid Aghaeidoost, A. H. M. Muntasir Billah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBase isolationResilience (materials science)Bridge (graph theory)EngineeringStructural engineeringHazardForensic engineeringNatural hazardReliability engineeringEnvironmental scienceComputer scienceMaterials scienceGeologyTelecommunications

Abstract

fetched live from OpenAlex

Damage to bridges during natural hazards can cause major difficulties in post-event emergency activities. In addition, the deterioration of bridges over their lifespan significantly impacts the life-cycle performance of bridges. This study intends to evaluate the overall life-cycle resilience performance and post-hazard loss analysis of isolated bridges equipped with different isolation systems, including lead rubber bearings and friction pendulum bearings. For the lifetime resilience and vulnerability assessment of a curved base-isolated bridge, bridge deterioration resulting from rebar corrosion and suites of ground motions representing possible seismic hazards at the bridge site are considered. The comparative resilience assessment and loss analysis results represent the base-isolation technique's comparative adequacy, resiliency, and cost-effectiveness. Statistical analysis is conducted to identify the parameters affecting base-isolated bridges' resiliency and life-cycle cost. The results demonstrate that the resilience, loss, and cost analysis results are highly sensitive to the type of isolation bearings.

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.

How this classification was reachedexpand

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.364

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 head0.026
GPT teacher head0.289
Teacher spread0.263 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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