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Record W4403709840 · doi:10.1139/cjce-2024-0145

Comparative analysis of hydrodynamic loads on bridge piers: assessing standards through numerical modeling

2024· article· en· W4403709840 on OpenAlexaffvenue
Seyed Mohammad Hadi Moosavian, Shooka Karimpour, S. J. Pantazopoulou

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsYork University
Fundersnot available
KeywordsStructural engineeringBridge (graph theory)EngineeringPierGeotechnical engineeringMarine engineeringCivil engineering

Abstract

fetched live from OpenAlex

Currently, there is an alarming difference in the estimated actions on piers resulting from flash-floods and tsunamis as prescribed by international structural design codes. Previous studies have explored the interaction between surge waves and piers from a fluid-dynamics perspective, but there is no assessment about the relevance of the methods used in Structural Design to determine the hydrodynamic pressure resultants. To determine the degree of conservatism embedded in design, results from the different approaches are compared against validated numerical simulations. Three-dimensional numerical analyses were conducted using the OpenFOAM platform, employing the Large Eddy Simulation turbulence modeling approach to simulate the dam-break wave impacting the pier. The findings revealed that the maximum force was not necessarily caused by the stream’s first strike and could be sustained over time. The hydrodynamic pressure center consistently occurred at two-thirds of the stream depth, significantly impacting the overturning moments experienced by the pier. Identified inconsistencies between Codes underscore the need for revision of nonconservative approaches in predicting the design forces.

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 score0.601
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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