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Misranked by Small Samples: Physics-Consistent Neural Operator Learning for Transient Gear-Tooth Contact Stress Fields

https://doi.org/10.2139/ssrn.7459657
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/aaai.70002openalex-snapshot
Reproducibility in machine‐learning‐based research: Overview, barriers, and drivers
inferredcites →https://doi.org/10.1002/nme.5135openalex-snapshot
Projection‐based model reduction for contact problems
inferredcites →https://doi.org/10.1002/nme.70041openalex-snapshot
Component‐Based Model‐Order Reduction With Mortar Tied Contact for Nonlinear Quasi‐Static Mechanical Problems
inferredcites →https://doi.org/10.1002/nme.70193openalex-snapshot
Physics‐Informed Graph Neural Networks to Reconstruct Local Fields Considering Finite Strain Hyperelasticity
inferredcites →https://doi.org/10.1007/s00354-024-00253-6openalex-snapshot
Improving the Efficiency of Training Physics-Informed Neural Networks Using Active Learning
inferredcites →https://doi.org/10.1007/s00466-023-02323-wopenalex-snapshot
Semi-reduced order stochastic finite element methods for solving contact problems with uncertainties
inferredcites →https://doi.org/10.1007/s00466-025-02604-6openalex-snapshot
Stress predictions in polycrystal plasticity using graph neural networks with subgraph training
inferredcites →https://doi.org/10.1007/s10010-023-00699-yopenalex-snapshot
Potentials and challenges in enhancing the gear transmission development with machine learning methods—a review
inferredcites →https://doi.org/10.1016/j.cma.2023.116671openalex-snapshot
A neural network finite element method for contact mechanics
inferredcites →https://doi.org/10.1016/j.cma.2025.117984openalex-snapshot
Predicting crack nucleation and propagation in brittle materials using Deep Operator Networks with diverse trunk architectures
inferredcites →https://doi.org/10.1016/j.compstruc.2025.107838openalex-snapshot
Efficient parametric model order reduction in contact mechanics
inferredcites →https://doi.org/10.1016/j.measurement.2015.12.046openalex-snapshot
Experimental measurement of strain and stress state at the contacting helical gear pairs
inferredcites →https://doi.org/10.1016/j.mechmachtheory.2016.03.010openalex-snapshot
Dynamic tooth root strains and experimental correlations in spur gear pairs
inferredcites →https://doi.org/10.1016/j.mechmachtheory.2017.01.006openalex-snapshot
External spur gear root bending stress: A comparison of ISO 6336:2006, AGMA 2101-D04, ANSYS finite element analysis and strain gauge techniques
inferredcites →https://doi.org/10.1016/j.neunet.2024.106826openalex-snapshot
Exactly conservative physics-informed neural networks and deep operator networks for dynamical systems
inferredcites →https://doi.org/10.1016/j.nexres.2025.100940openalex-snapshot
Machine learning surrogate models for Hertzian contact stress prediction in gear design: A comparative study of multiple approaches
inferredcites →https://doi.org/10.1016/j.patter.2023.100804openalex-snapshot
Leakage and the reproducibility crisis in machine-learning-based science
inferredcites →https://doi.org/10.1016/j.patter.2024.101046openalex-snapshot
Avoiding common machine learning pitfalls
inferredcites →https://doi.org/10.1016/j.ymssp.2022.109896openalex-snapshot
Digital twin-driven intelligent assessment of gear surface degradation
inferredcites →https://doi.org/10.1016/s0045-7949(05)80016-1openalex-snapshot
Static contact stress analysis of a spur gear tooth using the finite element method, including frictional effects
inferredcites →https://doi.org/10.1049/cim2.12064openalex-snapshot
State of the art on vibration signal processing towards data‐driven gear fault diagnosis
inferredcites →https://doi.org/10.1111/mice.13292openalex-snapshot
Physics‐informed neural operator solver and super‐resolution for solid mechanics
inferredcites →https://doi.org/10.1111/mice.13367openalex-snapshot
A branched Fourier neural operator for efficient calculation of vehicle–track spatially coupled dynamics
inferredcites →https://doi.org/10.1111/mice.13405openalex-snapshot
Geometry physics neural operator solver for solid mechanics
inferredcites →https://doi.org/10.1177/16878132241290948openalex-snapshot
Predictive residual stress analysis in gear units: an artificial intelligence approach based on finite element data
inferredcites →https://doi.org/10.3389/fmech.2022.1078134openalex-snapshot
Numerical and experimental research of helical gear contact stress considering the influence of friction
inferredcites →https://doi.org/10.3390/sym17081312openalex-snapshot
Neural Network-Based Estimation of Gear Safety Factors from ISO-Based Simulations
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