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Physics-Informed Neural Networks for Missing Physics Estimation in Cumulative Damage Models: A Case Study in Corrosion Fatigue
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: We present a physics-informed neural network modeling approach for missing physics estimation in cumulative damage models. This hybrid approach is designed to merge physics-informed and data-driven layers within deep neural ...
A Nonstationary Uncertainty Model and Bayesian Calibration of Strain-Life Models
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The Coffin–Manson–Basquin–Haford (CMBH) model is a well-accepted strain-life relationship to model fatigue life as a function of applied strain. In this paper, we propose a nonstationary uncertainty model for the CMBH ...
Kriging Approach Dedicated to Represent Hydrodynamic Bearings
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The mathematical modeling of journal bearings has advanced significantly since the Reynolds equation was first proposed. Advances in the processing capacity of computers and numerical techniques led to multiphysical models ...
Kriging-Based Surrogate Controller for Robust Control of a Flexible Rotor Supported by Active Magnetic Bearings
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Vibration control in supercritical rotors is a challenging task due to the underlying complex dynamics that high-speed machinery undergoes. When taking into account both structural (e.g., structural integrity and material ...