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Paper Citation Record · LEDGER

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2501.14699.

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pith.paper-citation-record.v1
2501.14699 v1

Coverage vector

measured 31 of 31 reference resolution

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measured 31 of 31 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

31 of 31 outbound references displayed

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Outbound references

Observation 684125b3-3f5c-4ca6-bc10-b70f0e65af9f · outbound

This paper cites Computational fluid dynamics: the basics with applications.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Computational fluid dynamics: the basics with applications

Reference 1

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Observation 040fbce3-f6d9-4175-96db-e9f7485cbccc · outbound

This paper cites Best practices for reduction of uncertainty in CFD results.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Best practices for reduction of uncertainty in CFD results

Reference 2

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Observation 50f0617b-2f0f-4422-a47c-2a48714401b6 · outbound

This paper cites Verification and Validation in Scientific Computing.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Verification and Validation in Scientific Computing

Reference 3

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Observation 0614187d-2ed9-4be5-9f04-55dee1deed79 · outbound

This paper cites Convolutional Neural Networks for Steady Flow Approxi- mation.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Convolutional Neural Networks for Steady Flow Approxi- mation

Reference 4

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Observation 4bfcd786-1824-4eb7-95b5-2a71a2739bb5 · outbound

This paper cites On the role and challenges of CFD in the aerospace industry.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models On the role and challenges of CFD in the aerospace industry

Reference 5

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Observation 2b7a9204-2b85-4c47-ac41-5c74310fe435 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 6

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Observation 538a3460-559a-43e9-bdca-dfb784f0d5d0 · outbound

This paper cites State-of-the-art in aerodynamic shape optimisation methods.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models State-of-the-art in aerodynamic shape optimisation methods

Reference 7

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Observation 76a1cd5e-7754-4e41-8687-8e4190b19023 · outbound

This paper cites Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks

Reference 8

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Observation 82fe5c01-dd8a-4cae-b7e0-6ac3862adc29 · outbound

This paper cites NN-SVG: Publication-Ready Neural Network Architecture Schematics.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models NN-SVG: Publication-Ready Neural Network Architecture Schematics

Reference 9

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Observation 307e1c49-f1aa-4f42-8f0f-e3406f30dcb0 · outbound

This paper cites Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction

Reference 10

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Observation 009814dc-36f2-4add-86e3-478f9bd0deeb · outbound

This paper cites CFDNet: A Deep Learning-Based Accelerator for Fluid Simulations.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models CFDNet: A Deep Learning-Based Accelerator for Fluid Simulations

Reference 11

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Observation e55def70-a1a3-4f64-957f-b0b596089131 · outbound

This paper cites Generalizability of Convolutional Encoder–Decoder Networks for Aerodynamic Flow-Field Prediction Across Geometric and Physical- Fluidic Variations.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Generalizability of Convolutional Encoder–Decoder Networks for Aerodynamic Flow-Field Prediction Across Geometric and Physical- Fluidic Variations

Reference 12

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Observation bf26e5bc-4b44-4157-ab59-c76edacb61f3 · outbound

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

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Deep Learning Methods for Reynolds-Averaged Navier-Stokes Simulations of Airfoil Flows

Reference 13

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Observation d89c8893-7b04-4b6a-882d-5662f92ea1e6 · outbound

This paper cites Physics-informed neural networks (PINNs) for fluid mechanics: a review.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Physics-informed neural networks (PINNs) for fluid mechanics: a review

Reference 14

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Observation 49fed7fa-2536-4906-a52c-6e636e3342c5 · outbound

This paper cites NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incom- pressible Navier-Stokes equations.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incom- pressible Navier-Stokes equations

Reference 15

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Observation 80c1ffad-f0d9-4108-9ce4-d69fa0f1b51f · outbound

This paper cites A point-cloud deep learning framework for prediction of fluid flow fields on irregular geometries.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models A point-cloud deep learning framework for prediction of fluid flow fields on irregular geometries

Reference 16

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Observation dee48d0f-1a78-4f1f-a849-5c71025153e6 · outbound

This paper cites SURFNet: Super-Resolution of Turbulent Flows with Transfer Learning us- ing Small Datasets.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models SURFNet: Super-Resolution of Turbulent Flows with Transfer Learning us- ing Small Datasets

Reference 17

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Observation fc24bc75-31dd-4448-b86a-f8adf03402a7 · outbound

This paper cites Experience report of physics-informed neural networks in fluid simulations: pitfalls and frustration.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Experience report of physics-informed neural networks in fluid simulations: pitfalls and frustration

Reference 18

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Observation 155b55ce-4cb9-4b45-9947-2d4951f674d3 · outbound

This paper cites Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations

Reference 19

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Observation 066de7be-3d8c-4c04-bee7-4437f5dd0e11 · outbound

This paper cites Multi-Fidelity Machine Learning Applied to Steady Fluid Flows.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Multi-Fidelity Machine Learning Applied to Steady Fluid Flows

Reference 20

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Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Unresolved cited work

Reference 21

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Observation 47c34e1c-b3b6-4a94-995c-7c978dec5849 · outbound

This paper cites Towards high-accuracy deep learning inference of compressible flows over aerofoils.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Towards high-accuracy deep learning inference of compressible flows over aerofoils

Reference 22

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Observation d9d68e75-b76c-4c62-8d21-df59f857c892 · outbound

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Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Can Physics-Informed Neural Networks beat the Finite Element Method?

Reference 23

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This paper cites Fourth AIAA High-Lift Prediction Workshop: Fixed-Grid Reynolds-Averaged Navier–Stokes Summary.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Fourth AIAA High-Lift Prediction Workshop: Fixed-Grid Reynolds-Averaged Navier–Stokes Summary

Reference 24

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Observation 01dca32b-1b44-402d-9da9-05e57951d0fc · outbound

This paper cites Evolutionary Multi-Objective Aerodynamic Design Optimization Using CFD Simulation Incorporating Deep Neural Network.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Evolutionary Multi-Objective Aerodynamic Design Optimization Using CFD Simulation Incorporating Deep Neural Network

Reference 25

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Observation f9b2da16-07b1-47f2-9799-56717264bfc0 · outbound

This paper cites Fast simulation of airfoil flow field via deep neural network.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Fast simulation of airfoil flow field via deep neural network

Reference 26

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Observation 9bb14add-7647-4e05-a62e-492673d53955 · outbound

This paper cites 2D NACA 0012 Airfoil Validation Case.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models 2D NACA 0012 Airfoil Validation Case

Reference 27

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Observation 66760d21-05ca-4f25-959f-b3645f78e980 · outbound

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Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Accuracy Improvement Technique of DNN for Accelerating CFD Simulator

Reference 28

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Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models Neural operator-based super-fidelity: A warm-start approach for accelerating steady- state simulations

Reference 29

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This paper cites url: https://aip.scitation.org/doi/abs/10.1063/5.0033376.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models url: https://aip.scitation.org/doi/abs/10.1063/5.0033376

Reference 6631

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Observation f1e21252-6661-4fb5-b2bd-5184b1fe5c65 · outbound

This paper cites url: https://doi.org/10.2514/1.C037184.

Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models url: https://doi.org/10.2514/1.C037184

Reference 8669

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