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Record W2911751326 · doi:10.9753/icce.v36.structures.4

LOADING ON PIPELINES DUE TO EXTREME HYDRODYNAMIC CONDITIONS

2018· article· en· W2911751326 on OpenAlexaff
Behnaz Ghodoosipour, Jacob Stolle, Ioan Nistor, Abdolmajid Mohammadian, Adrian Raul Simpalean

Bibliographic record

VenueCoastal Engineering Proceedings · 2018
Typearticle
Languageen
FieldEngineering
TopicEarthquake and Tsunami Effects
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPipeline transportStorm surgeEnvironmental scienceStormEngineeringMarine engineeringGeotechnical engineeringPetroleum engineeringGeologyCivil engineeringEnvironmental engineeringOceanography

Abstract

fetched live from OpenAlex

Proper design of pipelines used for oil, gas, water and wastewater transmission is of great importance. This is even more critical when pipelines are located in nearshore, coastal areas that are exposed to extreme hydrodynamic events, such as tsunami and storm surges. The American Society of Civil Engineers (ASCE)), in its ASCE7 Chapter 6: Tsunami Loads and Effects, the new standard for tsunami impacts and loading stresses the necessity to study tsunami loads on pipelines. Understanding the hydrodynamic forces acting on the pipelines is vital in ensuring their safe operation and avoiding potential damage to the environment. To address these issues, the following study is the first of its kind to investigate loading on pipelines due to tsunami-like bores.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

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