Results 151 to 160 of about 7,163,355 (354)

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

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

Quantum critical phenomena in a compressible displacive ferroelectric. [PDF]

open access: yesProc Natl Acad Sci U S A, 2020
Coak MJ   +5 more
europepmc   +1 more source

Robocasting of a Water‐Based Biopolymer/WO3 Nanopowder Paste as a Precursor to Tungsten Carbide Lattices

open access: yesAdvanced Engineering Materials, EarlyView.
This study demonstrates a novel, additive manufacturing approach to produce complex, porous tungsten carbide structures using water‐based direct ink writing/robocasting. Leveraging a modified commercial printer and heat treatment, the process yields lightweight, electrically conductive 3D architectures capable of supporting a mechanical load.
James Bentley Bevis   +3 more
wiley   +1 more source

Grassmann techniques applied to classical spin systems

open access: yesCondensed Matter Physics, 2009
We review problems involving the use of Grassmann techniques in the field of classical spin systems in two dimensions. These techniques are useful to perform exact correspondences between classical spin Hamiltonians and field-theory fermionic actions ...
M. Clusel, J.-Y. Fortin
doaj   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy