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Self-adaptive physics-informed neural networks (SA-PINN) coupled with thermal network model (TNM) for cross-scale temperature field modeling of wet friction components

Jianpeng Wu, Peng Zhao, Wenya Shu, Jian Yang, Liyong Wang, Shuai Han

2025Tribology International14 citationsDOI

Topics & Concepts

Mean squared errorApproximation errorMean absolute percentage errorWeightingThermalCoupling (piping)Field (mathematics)Artificial neural networkHeat transferTransient (computer programming)Power (physics)Root mean squareControl theory (sociology)Temperature measurementSensitivity (control systems)EngineeringProcess (computing)Power transmissionMaterials scienceComputer scienceTransfer functionTransmission (telecommunications)Least mean squares filterNetwork modelThermal resistanceTransmission systemFinite element methodMechanicsModel Reduction and Neural NetworksNuclear Engineering Thermal-HydraulicsHydraulic and Pneumatic Systems
Self-adaptive physics-informed neural networks (SA-PINN) coupled with thermal network model (TNM) for cross-scale temperature field modeling of wet friction components | Litcius