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Record W4385764795 · doi:10.1080/19942060.2023.2244028

Numerical simulation of planing motion and hydrodynamic performance of a seaplane in calm water and waves

2023· article· en· W4385764795 on OpenAlexfundno aff
Zhijie Song, Rui Deng, Tiecheng Wu, Xupeng Duan, Hang Ren

Bibliographic record

VenueEngineering Applications of Computational Fluid Mechanics · 2023
Typearticle
Languageen
FieldEngineering
TopicShip Hydrodynamics and Maneuverability
Canadian institutionsnot available
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceChina Postdoctoral Science FoundationNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of ChinaMinistry of Natural Resources
KeywordsVolume of fluid methodFuselageAerodynamicsMechanicsAir entrainmentTurbulenceSuctionEntrainment (biomusicology)Computational fluid dynamicsOffshore geotechnical engineeringComputer simulationFree surfaceReynolds-averaged Navier–Stokes equationsGeologyMarine engineeringFlow (mathematics)EngineeringPhysicsAerospace engineeringMeteorologyGeotechnical engineeringAcoustics

Abstract

fetched live from OpenAlex

The high-speed motion of a seaplane involves the coupled hydrodynamic and aerodynamic effects. The suction force, pressure, free surface and motion of the seaplane model were numerically investigated to understand the characteristics of the seaplane's planing motion. The study utilized the SST-DDES turbulence model to analyse the coupled hydrodynamic and aerodynamic effects. Overset mesh method and rigid body motion were employed to simulate the high-speed and substantial motion of seaplane. The volume of fluid method (VOF) was used to capture and sharpen the interface between water and air. First, verification and validation (V&V) were performed by comparing the results with those of the towing tank experiments. Second, the air-water entrainment in calm water and free surfaces were presented, and the pressure distribution on the seaplane was analysed and discussed. Numerical simulations were performed while considering the wave parameters of different velocities, wavelengths, and wave heights. The accelerations of the fore, aft, and centre of gravity of the seaplane demonstrated the presence of the suction effect. The evolution of the air-water entrainment at the bottom of the fuselage was observed. The investigation of suction characteristics revealed that the aerodynamic force in waves plays a substantial role in influencing motions of the seaplane.Highlights The study of hydrodynamics and aerodynamics of seaplanes is interdisciplinary. The numerical schemes, including a SST-DDES turbulent model, overset mesh method, and volume of fluid (VOF) method, have proven to be effective and accurate for simulating the motion of the seaplane and flow field characteristics.The greater the speed and wave height, the faster is the motion of the seaplane and the greater are peak and trough values of the pitch. As the wavelength increased, the peak value of the motion decreased gradually.The accelerations of the aft, fore, and centre of gravity of the seaplane in the waves exhibited significant periodicity. The peak value of the acceleration at the aft was the largest, whereas that at the centre of gravity was mild, and the peak value of the acceleration at the centre of gravity was greater than that at the fore. The acceleration indicates that suction at the aft of the seaplane hinders the takeoff during the planing motion.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.201
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

Citations13
Published2023
Admission routes1
Has abstractyes

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