Results 241 to 250 of about 156,992 (308)

A new drag and lift correlation for spherocylinders from fully resolved Immersed Boundary Method

open access: yesAIChE Journal, EarlyView.
Abstract Many industrial processes deal with non‐spherical particles, e.g., mineral mining and biomass conversion. It is crucial to understand the particles' hydrodynamics to control and optimize these processes. To extend the current state‐of‐the‐art from arrays of spherical particles to spherocylindrical particles, we performed extensive particle ...
A. H. Huijgen   +4 more
wiley   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas   +4 more
wiley   +1 more source

Evolution of Physical Intelligence Across Scales

open access: yesAdvanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu   +7 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

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