Results 81 to 90 of about 33,561,195 (290)

Microstructural Evolution and Vacancy Defect Formation in Mn–Mo–Ni RPV Steel Under Low Cycle Fatigue: Insights From EBSD and PALS

open access: yesAdvanced Engineering Materials, EarlyView.
Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar   +2 more
wiley   +1 more source

Multimodal Data‐Driven Microstructure Characterization

open access: yesAdvanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang   +4 more
wiley   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

open access: yesAdvanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang   +2 more
wiley   +1 more source

Convergence Order of the Reproducing Kernel Method for Solving Boundary Value Problems

open access: yes, 2016
In this paper, convergence rate of the reproducing kernel method for solving boundary value problems is studied. The equivalence of two reproducing kernel spaces and some results of adjoint operator are proved.
Zhihong Zhao, Yingzhen Lin, J. Niu
semanticscholar   +1 more source

Creep‐Induced Microstructural Evolution in an A2‐B2 Superalloy

open access: yesAdvanced Engineering Materials, EarlyView.
A 27.3Ta‐27.3Mo‐27.3Ti‐8Cr‐10Al (at.%) refractory high‐entropy alloy with precipitation‐strengthened A2‐B2 microstructure was studied by creep tests at 1030°C, which demonstrate a transition in deformation mechanisms in the range of 100–150 MPa applied stress. This is associated with changes in dislocation–precipitate interactions. Relevant deformation
Liu Yang   +10 more
wiley   +1 more source

Influence of Test Temperature and Test Frequency on Fatigue Life of Aluminum Alloy EN AW‐2618A

open access: yesAdvanced Engineering Materials, EarlyView.
The influence of test temperature and test frequency on the fatigue life of EN AW‐2618A is investigated. High‐cycle fatigue tests are performed at different test temperatures and frequencies on the 1000 h/230°C overaged state. Both test parameters reduce fatigue life due to time‐dependent damage mechanisms.
Ying Han   +5 more
wiley   +1 more source

Single Target Tracking Algorithm Based on Multi-Fuzzy Kernel Fusion

open access: yesJisuanji kexue yu tansuo, 2020
For the problem how to accurately and quickly locate targets in the current target tracking field, the core content of most popular trackers is to combine a kernel method to train a discriminative classifier to distinguish the target from the surrounding
CHEN Chen, DENG Zhaohong, GAO Yanli, WANG Shitong
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

open access: yesAdvanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran   +6 more
wiley   +1 more source

Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels [PDF]

open access: yesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
In this paper, we develop an approach to exploiting kernel methods with manifold-valued data. In many computer vision problems, the data can be naturally represented as points on a Riemannian manifold. Due to the non-Euclidean geometry of Riemannian manifolds, usual Euclidean computer vision and machine learning algorithms yield inferior results on ...
Sadeep Jayasumana   +4 more
openaire   +3 more sources

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

open access: yesAdvanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle   +5 more
wiley   +1 more source

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