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Paper Citation Record · LEDGER

Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1810.08217.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1810.08217 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:26:49.536798Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T16:46:20.156732Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f52dfaf9-98cd-44c8-88a0-1b01df580e84 · inbound

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development cites this paper.

Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-14T11:26:49.536798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:26:49.536798Z digest=sha256:f0ad40efa50321e136ee84cbd9510cbd49759220d7238c8a216218ca0229b595

Observation fa256077-7bb5-4028-a6b5-9f656dc8a4f1 · inbound

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks cites this paper.

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T20:24:33.552111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:24:33.552111Z digest=sha256:0725530b7c23c27a61fe211986b6d8223d848c90a39305637bbf48e6e4551164

Observation 3fa2b1bb-94b1-423b-8052-3571b98da272 · inbound

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks cites this paper.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:07.287052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:07.287052Z digest=sha256:4f7ee92f6903dfff920311080c0ee59ded5f9abf879a7c11a8607ccf725084f4

Observation 72c1cbd0-91ee-4ca4-94a6-3289b15f0013 · inbound

Loop2Net: Data-Driven Generation and Optimization of Airfoil CFD Meshes from Sparse Boundary Coordinates cites this paper.

Loop2Net: Data-Driven Generation and Optimization of Airfoil CFD Meshes from Sparse Boundary Coordinates Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T21:59:15.533768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:59:15.533768Z digest=sha256:0317c8be883362c5251d1a993800b40d8a02e11b21f6e80615c33a2a5953fb5d

Observation 642436c7-4d53-45c7-9ffc-9dd6bdd65473 · inbound

Mesh Based Simulations with Spatial and Temporal awareness cites this paper.

Mesh Based Simulations with Spatial and Temporal awareness Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:46:20.295132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-09T15:00:51.468683Z digest=sha256:e5683a38690e9a46290c1202a3ffe8f10794aab64714dde07ad7201f71fda16c