Paper Citation Record · LEDGER

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration

As of 18 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2512.24757.

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

pith.paper-citation-record.v1
2512.24757 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T13:20:55.604360Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

26 of 26 outbound references displayed

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External citation measurements

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Outbound references

Observation a3770f35-2524-4b4c-b206-89f563903411 · outbound

This paper cites Pulsatile pipe flow transition: Flow waveform effects.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Pulsatile pipe flow transition: Flow waveform effects

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:53.055490Z

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Observation 4c69aa44-9214-4a89-a7af-9cc22b32e072 · outbound

This paper cites Highly Energy-Conservative Finite Difference Method for the Cylindrical Coordinate System.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Highly Energy-Conservative Finite Difference Method for the Cylindrical Coordinate System

Reference 2

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Observation 0035c53e-73f1-4607-b157-57c53e16a3fe · outbound

This paper cites Synthetic Turbulent Inflow Generator Using Machine Learning.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Synthetic Turbulent Inflow Generator Using Machine Learning

Reference 3

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Observation 53c9a7ab-45cb-481b-b8a9-c05ba8b44601 · outbound

This paper cites Direct Numerical Sim- ulation for Drag Reduction by Pulsating Turbulent Pipe Flow.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Direct Numerical Sim- ulation for Drag Reduction by Pulsating Turbulent Pipe Flow

Reference 4

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Observation a12f4709-60f8-476f-8b99-7029c6d2b9de · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Adam: A Method for Stochastic Optimization

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:53.579574Z

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Observation f2fee1ed-9a64-4ed3-9b1c-d664c3cf20e5 · outbound

This paper cites Prediction of the Drag Reduction Effect of Pulsating Pipe Flow Based on Machine Learning.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Prediction of the Drag Reduction Effect of Pulsating Pipe Flow Based on Machine Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:53.699974Z

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Observation 1bab850c-f5bd-4a27-90e7-69c1feb05f85 · outbound

This paper cites Turbulent Com- bined Oscillatory Flow and Current in a Pipe.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Turbulent Com- bined Oscillatory Flow and Current in a Pipe

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:53.830836Z

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Observation 69e779f8-755b-4d79-88fc-569b1f392bc3 · outbound

This paper cites Spectral Dynamics of Pulsating Tur- bulent Pipe Flow.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Spectral Dynamics of Pulsating Tur- bulent Pipe Flow

Reference 8

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Observation df852ef3-4478-4d62-ab88-b8a91b199008 · outbound

This paper cites Studies of the wall shear stress in a turbulent pulsating pipe flow.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Studies of the wall shear stress in a turbulent pulsating pipe flow

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.163824Z

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Observation a78c6f80-ff5a-452c-b042-9414f529d4da · outbound

This paper cites Influence of Large-Amplitude Os- cillations on Turbulent Drag.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Influence of Large-Amplitude Os- cillations on Turbulent Drag

Reference 10

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Observation 175005f1-f6c4-4135-81bc-5f99e58caf9f · outbound

This paper cites Pre- diction of pulsating turbulent pipe flow by deep learning with general- ization capability.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Pre- diction of pulsating turbulent pipe flow by deep learning with general- ization capability

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.326397Z

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Observation 2092dd83-cc7b-44f6-a14f-8a2391f23b25 · outbound

This paper cites Compressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Compressed Convolutional LSTM: An Efficient Deep Learning framework to Model High Fidelity 3D Turbulence

Reference 12

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Observation 60b09df1-00ce-4323-bd11-28bce331038e · outbound

This paper cites Gener- alization techniques of neural networks for fluid flow estimation.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Gener- alization techniques of neural networks for fluid flow estimation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.446535Z

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Observation c114a2c9-cc98-4776-91d6-a63590aa45de · outbound

This paper cites Effect of waveform on turbulence transition in pulsatile pipe flow.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Effect of waveform on turbulence transition in pulsatile pipe flow

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.514136Z

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Observation 19e741fd-0c08-4042-a2e1-9c2aba1df385 · outbound

This paper cites Critical assessment of turbulent drag reduction through spanwise wall oscillations.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Critical assessment of turbulent drag reduction through spanwise wall oscillations

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.605506Z

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Observation 9e374143-a8ec-46e2-9203-a5deefad9c7f · outbound

This paper cites Physics- informed neural networks: A deep learning framework for solving for- ward and inverse problems involving nonlinear partial differential equa- tions.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Physics- informed neural networks: A deep learning framework for solving for- ward and inverse problems involving nonlinear partial differential equa- tions

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.641638Z

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Observation 88b98469-d92d-48ba-b146-c9c9e4c953b7 · outbound

This paper cites Ex- perimental study on drag-reduction effect due to sinusoidal riblets in turbulent channel flow.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Ex- perimental study on drag-reduction effect due to sinusoidal riblets in turbulent channel flow

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.706264Z

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Observation 8e14ba6c-bbc1-4b96-b9da-2f17419f25e6 · outbound

This paper cites Boundary-Layer Theory.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Boundary-Layer Theory

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.749936Z

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Observation bbc8e56f-c14e-488b-805a-125fee38c76c · outbound

This paper cites Numerical Simulation of Pulsating Turbulent Channel Flow.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Numerical Simulation of Pulsating Turbulent Channel Flow

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.824109Z

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Observation f3a85f7b-679a-4250-b1ef-b4574f22419c · outbound

This paper cites Experimental Inves- tigation of Pump Control for Drag Reduction in Pulsating Turbulent Pipe Flow.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Experimental Inves- tigation of Pump Control for Drag Reduction in Pulsating Turbulent Pipe Flow

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.904517Z

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Observation 716c3484-0a38-4676-9cd2-d1c23ee3cc62 · outbound

This paper cites Machine learning in fluid dynamics: A critical assessment.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Machine learning in fluid dynamics: A critical assessment

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:54.992449Z

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Observation a7578f08-ba46-4022-87a0-4003b3e6e8db · outbound

This paper cites Turbulent-turbulent transient concept in pulsating flows.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Turbulent-turbulent transient concept in pulsating flows

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:55.036059Z

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Observation a04efd05-a321-46eb-be12-9c60c4dfe86e · outbound

This paper cites Towards physics-informed deep learning for turbulent flow prediction.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Towards physics-informed deep learning for turbulent flow prediction

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:55.117593Z

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Observation 1f125146-338a-4312-b562-3a4a4493cdac · outbound

This paper cites Physics-guided deep learning for generating turbulent inflow conditions.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Physics-guided deep learning for generating turbulent inflow conditions

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:55.256246Z

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Observation 3fa5f2c7-b886-4bc6-9389-ba4a815d6694 · outbound

This paper cites A transformer-based synthetic-inflow generator for spatially develop- ing turbulent boundary layers.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration A transformer-based synthetic-inflow generator for spatially develop- ing turbulent boundary layers

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:55.488679Z

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Observation 48e824bd-e220-423b-bf64-81b1c3467590 · outbound

This paper cites Data-centric artificial intelligence: A survey.

Generalization Capability of Deep Learning for Predicting Drag Reduction in Pulsating Turbulent Pipe Flow with Arbitrary Acceleration and Deceleration Data-centric artificial intelligence: A survey

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T13:20:55.604360Z

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Pith citing papers

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