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Local scour and hydrodynamics around river crossing pipelines under ice-covered flow conditions

2025· article· en· W4411313800 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOcean Engineering · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPipeline transportFlow (mathematics)OceanographyEnvironmental scienceGeologyMarine engineeringEngineeringMechanicsPhysics

Abstract

fetched live from OpenAlex

Local scour around submarine pipelines is a critical concern in cold-region hydraulics, where ice cover alters flow dynamics. This study experimentally investigates scour behavior under varying flow conditions, pipe configurations (single, tandem, and triple), and ice scenarios (open-channel, smooth ice, and rough ice). Flume tests were conducted using PVC pipes with diameters of 0.04 m, 0.05 m, and 0.06 m. Results show that ice cover increases equilibrium scour depth and reduces the time to reach the equilibrium state, with rough ice producing the deepest scour due to enhanced near-bed turbulence and flow confinement. In contrast, multi-pipe layouts reduce maximum scour depth but accelerate scour onset. Velocity field measurements from Acoustic Doppler Velocimetry (ADV) revealed intensified reverse flows and elevated turbulent kinetic energy near the bed under ice-covered conditions, consistent with observed scour patterns. This work extends existing scour models by incorporating the combined effects of ice roughness and multiple-pipe interference, offering empirical tools tailored for cold-region pipeline design.

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: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.527

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 head0.004
GPT teacher head0.206
Teacher spread0.202 · 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