Results 141 to 150 of about 16,482,147 (331)

Comparative Wear and Friction Analysis of Sliding Surface Materials for Hydrostatic Bearing under Oil Supply Failure Conditions

open access: yesAdvanced Engineering Materials, EarlyView.
Hydrostatic bearings excel in high‐precision applications, but their performance hinges on a continuous external supply. This study evaluates various material combinations for sliding surfaces to mitigate damage during supply failures or misalignment and to discover the most effective materials identified for enhancing the reliability and efficiency of
Michal Michalec   +6 more
wiley   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

Joint design and compression of convolutional neural networks as a Bi-level optimization problem. [PDF]

open access: yesNeural Comput Appl, 2022
Louati H   +4 more
europepmc   +1 more source

Bistable Mechanisms 3D Printing for Mechanically Programmable Vibration Control

open access: yesAdvanced Engineering Materials, EarlyView.
This work introduces a 3D‐printed bistable mechanism integrated into tuned mass dampers (TMDs) for mechanically adaptive passive vibration suppression. Through optimized geometry, the bistable design provides adaptable vibration reduction across a broad range of scenarios, achieving effective vibration mitigation without complex controls or external ...
Ali Zolfagharian   +4 more
wiley   +1 more source

Machine Learning Applied to High Entropy Alloys under Irradiation

open access: yesAdvanced Engineering Materials, EarlyView.
Designing alloys for extreme environments demands fast, trustworthy prediction. This review charts how machine learning—especially machine‐learned interatomic potentials and predictive models based on experiment‐informed datasets—captures the complexity of high‐entropy alloys in extreme environments, predicts phase formation, mechanical properties, and
Amin Esfandiarpour   +8 more
wiley   +1 more source

Mechanical Behavior and Microstructural Changes Associated with Tensile Deformation above the Martensite Start Temperature during Quenching and Subsequent Partitioning of a Low‐Alloy 37SiB6 Steel

open access: yesAdvanced Engineering Materials, EarlyView.
A new experimental setup, incorporating digital image correlation and infrared thermography in combination with inductive‐conductive heating for precise temperature control, is used to analyze the mechanical behavior and microstructural changes of sheet metal under complex thermomechanical test conditions that represent quench and partitioning ...
Christian Illgen   +4 more
wiley   +1 more source

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