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Record W6986220205

Optimization fo rock berms for pipeline stabilization subject to intense hydrodynamic forcing

2015· article· en· W6986220205 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueNPARC · 2015
Typearticle
Languageen
FieldEngineering
TopicWave and Wind Energy Systems
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBermPipeline transportForcing (mathematics)Pipeline (software)ArmourRange (aeronautics)Current (fluid)Physical modelling
DOInot available

Abstract

fetched live from OpenAlex

This article describes a comprehensive study in which 2D and 3D physical modelling at 1:40 scale was used to optimize the design and validate the performance of dynamically stable rock berms to be used for stabilizing several large pipelines traversing water depths from 5m to 65m and potentially exposed to large waves and strong currents generated by intense tropical cyclones. For added realism, all of the model rock berms were constructed using a scaled simulation of rock installation by fall pipe vessel to be used in the field. Special attention was also given to simulating the self-stability of the model pipeline segments, including special end constraints designed to mimic the behaviour of a continuous pipeline. A large data set concerning the behaviour of dynamically reshaping rock berms in a range of water depths under intense hydrodynamic forcing due to three-dimensional waves and currents was produced and used to develop efficient and costeffective rock berm designs for all depth zones.

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: none
Teacher disagreement score0.894
Threshold uncertainty score0.476

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 head0.018
GPT teacher head0.222
Teacher spread0.203 · 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