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Record W649711308 · doi:10.3329/jname.v2i1.2026

Prediction of transient loading on a propeller from an approaching ice block

2005· article· en· W649711308 on OpenAlexafffund
Pengxuan Liu, Bruce Colbourne, Chin Shin

Bibliographic record

VenueNational Research Council Canada (Government of Canada) · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsNational Research Council Canada
FundersNational Research Council Canada
KeywordsPropellerBlock (permutation group theory)SuctionMechanicsGeologyInertial frame of referenceStructural engineeringMarine engineeringEngineeringGeometryPhysicsMathematicsMechanical engineeringClassical mechanics

Abstract

fetched live from OpenAlex

An unsteady 3D surface panel method has been developed to predict hydrodynamic load fluctuations on an ice class propeller induced by continuous variation of proximity to an ice block. The low order, time domain, combined doublet and source panel method approximates the doublet and source distribution uniformly over each panel on the propeller blades. For non-lifting bodies, i.e., the hub and ice block, only sources are distributed over the body surfaces. The simulations model is contrived in such a manner that the ice block and surrounding fluid remain stationary; and at each time step, the propeller rotates and advances forward in the inertial reference frame. This numerical model is validated with previous fixed-proximity experimental measurements and good agreement is obtained. Prediction of the fluctuating hydrodynamic load is carried out as a full dynamic interaction between the ice block and the propeller. Results for this study are compared with previous fixed-proximity numerical models and experiments. The new dynamic model establishes a basis for analysis of a more realistic fluid-structure interaction, which could, in the future, include ice block acceleration due to suction force and ice block impact loading on the propeller blade and shaft.

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)0.007
metaresearch head score (Gemma)0.004
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 score0.514
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
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 head0.073
GPT teacher head0.237
Teacher spread0.164 · 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
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueNational Research Council Canada (Government of Canada)Same topicArctic and Antarctic ice dynamicsFrench-language works237,207