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Paper Citation Record · LEDGER

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

As of 19 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2506.22662.

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

pith.paper-citation-record.v1
2506.22662 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:05:08.152540Z

measured 29 of 29 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

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External citation measurements

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Outbound references

Observation e6706095-d282-4fca-b7a9-5877971e6dc8 · outbound

This paper cites Brian Spalding.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Brian Spalding

Reference 1

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Observation 62f03018-8dff-4a96-84ef-b288324397a0 · outbound

This paper cites View-dependent refinement of progressive meshes.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks View-dependent refinement of progressive meshes

Reference 2

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Observation 471f9eb8-ce1a-4bb3-9220-7ba435afcb40 · outbound

This paper cites UCNN: A Convolutional Strategy on Unstructured Mesh.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks UCNN: A Convolutional Strategy on Unstructured Mesh

Reference 3

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Observation 9437d33e-df36-45dd-8fad-294d9da62e59 · outbound

This paper cites Tucker, and Shahrokh Shahpar.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Tucker, and Shahrokh Shahpar

Reference 4

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Observation f7477685-b02e-40fc-ab92-e5afc97b6c84 · outbound

This paper cites Chawner and Nigel J.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Chawner and Nigel J

Reference 5

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Observation 8a660ee8-8032-440b-a49b-f8bddaf1f24c · outbound

This paper cites Low Reynolds Number Airfoil Design Lecture Notes.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Low Reynolds Number Airfoil Design Lecture Notes

Reference 6

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Observation 7b2a33b5-d898-4a09-91fe-4b70e01bf01b · outbound

This paper cites Computational and experimental study on the aerodynamic performance of NACA 4412 airfoil with slot and groove.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Computational and experimental study on the aerodynamic performance of NACA 4412 airfoil with slot and groove

Reference 7

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Observation 4560e87a-1807-4003-830c-a521c3f36630 · outbound

This paper cites Deep learning in the finite element method.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Deep learning in the finite element method

Reference 8

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Observation bc4faf11-59f4-415e-896a-e596328ae7bf · outbound

This paper cites CFDNet: A deep learning-based accelerator for fluid simula- tions.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks CFDNet: A deep learning-based accelerator for fluid simula- tions

Reference 9

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Observation 61fede7b-0edf-4fcf-8b77-b0fb9008449a · outbound

This paper cites Deep learning to replace, improve, or aid CFD analysis in built environment applications: A review.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Deep learning to replace, improve, or aid CFD analysis in built environment applications: A review

Reference 10

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Observation 9016d885-aeb6-4c73-9248-ddc5afd6a61e · outbound

This paper cites Mesh Generation for Flow Analysis by using Deep Reinforcement Learning.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Mesh Generation for Flow Analysis by using Deep Reinforcement Learning

Reference 11

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Observation e9ecc796-b6b1-4fc1-aa30-7ac7f3f6afe5 · outbound

This paper cites A mesh optimization method using machine learning technique and variational mesh adaptation.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks A mesh optimization method using machine learning technique and variational mesh adaptation

Reference 12

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Observation 7e291697-a24a-497a-8f49-e7835635c57f · outbound

This paper cites Machine Learning-Based Optimal Mesh Generation in Computational Fluid Dynamics.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Machine Learning-Based Optimal Mesh Generation in Computational Fluid Dynamics

Reference 13

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Observation cb2fee80-759f-4e9f-b46b-a9b3a6088010 · outbound

This paper cites A data augmentation-based technique for deep learning applied to CFD simulations.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks A data augmentation-based technique for deep learning applied to CFD simulations

Reference 14

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Observation 88860ff6-b94e-4fb9-8f04-d0b86408b09c · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

Reference 15

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Observation 4678e523-f622-481b-8420-493064e5f8d5 · outbound

This paper cites Machine Learning for Fluid Mechanics.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Machine Learning for Fluid Mechanics

Reference 16

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Observation d65f9eb7-e39b-448f-b7af-5574d27e8bfa · outbound

This paper cites CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences

Reference 17

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

This paper cites Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows.

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

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Observation 965bf752-e767-41e4-906c-0134b172e61f · outbound

This paper cites DGM: A deep learning algorithm for solving partial differential equations.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks DGM: A deep learning algorithm for solving partial differential equations

Reference 19

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Observation 5eb7e14f-0663-4ace-8236-6743a794ca05 · outbound

This paper cites Mesh Optimization.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Mesh Optimization

Reference 20

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This paper cites A parallel parameterized level set topology opti- mization framework for large-scale structures with unstructured meshes.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks A parallel parameterized level set topology opti- mization framework for large-scale structures with unstructured meshes

Reference 21

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Observation 0ab0db99-b65f-4f06-8217-e66c6ca95796 · outbound

This paper cites Geometric parameters in the target matrix mesh optimization paradigm.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Geometric parameters in the target matrix mesh optimization paradigm

Reference 22

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AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Ahmed et al

Reference 23

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This paper cites MeshCNN: A Network with an Edge.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks MeshCNN: A Network with an Edge

Reference 24

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This paper cites Qi et al.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Qi et al

Reference 25

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Observation 515b78ea-e078-49b9-a57d-cfbeb6932b79 · outbound

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AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks MeshCNN Fundamentals: Geometric Learning through a Reconstructable Representation

Reference 26

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This paper cites GWCNN: A Metric Alignment Layer for Deep Shape Analysis.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks GWCNN: A Metric Alignment Layer for Deep Shape Analysis

Reference 27

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Source-reported events for the cited work

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Observation 8386de1e-33b4-4bde-82f0-4cb3d8abbfbd · outbound

This paper cites PointCNN: Convolution On $\mathcal{X}$-Transformed Points.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks PointCNN: Convolution On $\mathcal{X}$-Transformed Points

Reference 28

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AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks Unresolved cited work

Reference 29

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