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Record W2807384738 · doi:10.1061/9780784481639.005

Nine-Year Field-Monitoring Data from an Integral-Abutment Bridge

2018· article· en· W2807384738 on OpenAlexaffabout
Shelley A. Huntley, Arun J. Valsangkar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsUniversity of New Brunswick
FundersU.S. Department of Transportation
KeywordsAbutmentBridge (graph theory)Term (time)Structural engineeringTorsion (gastropod)Geotechnical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

Many field studies of integral abutment bridges have focussed on construction and short-term behaviour, while the data on long-term performance are not abundant. In this paper, long-term field monitoring data from an instrumented integral abutment bridge in Fredericton, NB are presented. The primary objective is to add to the limited database of long-term monitoring so that the information might be used to calibrate numerical methods predicting long-term performance over the design life of a bridge. In this paper, data of abutment movements and earth pressures on the abutments over a 9-year monitoring period are presented. Field data indicate that the primary mode of movement for one abutment is translation and a combination of rotation and translation for the other abutment. Data also indicate that the abutments are tilting in opposite directions to one another, resulting in torsion of the bridge superstructure. Finally, of particular interest, is the concern of earth pressure ratcheting. Data do not conclusively show an increase in passive earth pressures behind the abutment over the 9-year monitoring period.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score0.436

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 head0.039
GPT teacher head0.287
Teacher spread0.248 · 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 designSimulation or modeling
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

Citations12
Published2018
Admission routes2
Has abstractyes

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