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Record W1968274565 · doi:10.1139/l01-009

Composite reliability model for local scour around cylindrical bridge piers

2001· article· en· W1968274565 on OpenAlexvenueno aff
A. Melih Yanmaz, Ozgur Cicekdag

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPierFroude numberStructural engineeringAbutmentEngineeringLog-normal distributionReliability (semiconductor)Geotechnical engineeringBridge (graph theory)Flow (mathematics)MathematicsStatistics

Abstract

fetched live from OpenAlex

Bridge scour is an extremely complex phenomenon because of the random characteristics of sediment laden flow in close proximity to piers and abutments. This occurrence leads to high uncertainties and unavoidable risk in bridge pier and abutment design. In this study, a composite reliability model is developed for the reliability assessment of bridge pier scour using static resistance – loading interference. Based on the physical interpretation of the phenomenon and a statistical analysis of the available information, the relative maximum scour depth (corresponding to the minimum required relative pier footing elevation) and the linear combination of the relative approach flow depth and flow Froude number are defined as the system resistance and external loading, respectively. By examining a set of laboratory and field data, a two-parameter bivariate lognormal distribution is found to represent the joint probability density function of resistance and loading. Reliability expressions are developed in terms of resistance. Use of the model is illustrated in a practical application in which a relationship is obtained between the reliability and safety factors under various return periods. This information is of importance in decision making.Key words: reliability, bridge pier, scour, resistance, loading, safety factor, return 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.594
Threshold uncertainty score0.980

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 head0.011
GPT teacher head0.201
Teacher spread0.190 · 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

Citations26
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicHydrology and Sediment Transport ProcessesFrench-language works237,207