Results 81 to 90 of about 44,794 (286)

Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading

Advanced Engineering Materials, EarlyView.
The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
wiley   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced 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, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer

Scientific Reports
Fault diagnosis for gearbox by robust variational mode decomposition (RVMD) and twin extreme learning machine (TELM) with composite chaotic grey wolf optimizer (CCGWO) is proposed in this study. Robust variational mode decomposition is an advanced signal
Xuebin Huang, Anfeng Xu, Hongbing Liu, Bingcheng Ye   +3 more
doaj   +1 more source

Novel Fault Detection Method for Rolling Bearings Based on Improved Variational Modal Decomposition Method

IEEE Access
To enhance the precision of rolling bearing fault detection and lessen the likelihood of safety mishaps, this paper proposes a fault detection method grounded in improved variational mode decomposition. This technique initially employs the Northern Eagle
Xiaoli Huang, Haifeng Xu, Junying Cui
doaj   +1 more source

Toward Knowledge‐Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties

Advanced Engineering Materials, EarlyView.
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán, Hoang‐Thien Luu, Sarath Menon, Tilmann Hickel, Nina Merkert, Stefan Sandfeld   +5 more
wiley   +1 more source

On the stability of bubble functions and a stabilized mixed finite element formulation for the Stokes problem

, 2008
In this paper we investigate the relationship between stabilized and enriched finite element formulations for the Stokes problem. We also present a new stabilized mixed formulation for which the stability parameter is derived purely by the method of ...
Arnold, Bai, Baiocchi, Brezzi, Brezzi, Brezzi, Brooks, De Mulder, Donea, Douglas, Franca, Graham, Gresho, Griffiths, Hughes, Hughes, Hughes, Hughes, Malkus, Masud, Masud, Nakshatrala, Nakshatrala, Russo, Sani   +24 more
core   +2 more sources

Two-dimensional compact variational mode decomposition

, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zosso, Dominique, Dragomiretskiy, Konstantin, Bertozzi, Andrea L, Weiss, Paul S   +3 more
openaire   +3 more sources

Ideal Molecular Sieving with a Dense MOF for Helium Upgrading with Highly Diffusion Selective Mixed Matrix Membranes

Advanced Functional Materials, EarlyView.
The separation of Helium gas from natural gas is challenging but highly important. MIL‐116(Ga), a “non‐porous” metal–organic framework is used as a molecular sieve to separate He from CH4. Druse‐like MIL‐116(Ga) particles are integrated into polysulfone mixed matrix membranes.
Ayisha Komal, Laura Calderón‐Rodríguez, Oksana Smirnova, Eren Grossmann, Aparna Binu Varghese, Karen Marlenne Garcia Alvarez, Andreas Schneemann, Thomas Hoyer, Ralf Wyrwa, Felix Helmut Schacher, Alexander Knebel   +10 more
wiley   +1 more source

The Data-Driven Optimization Method and Its Application in Feature Extraction of Ship-Radiated Noise with Sample Entropy

Energies, 2019
The data-driven method is an important tool in the field of underwater acoustic signal processing. In order to realize the feature extraction of ship-radiated noise (S-RN), we proposed a data-driven optimization method called improved variational mode ...
Yuxing Li, Xiao Chen, Jing Yu, Xiaohui Yang, Huijun Yang   +4 more
doaj   +1 more source

Resonance-based sparse adaptive variational mode decomposition and its application to the feature extraction of planetary gearboxes.

PLoS ONE, 2020
Due to the assumption that the VMD technique is essentially a set of adaptive Wiener filter banks and its performance depends to a large extent on the preset parameter K (the number of decomposition).
Jing Zhu, Aidong Deng, Jing Li, Minqiang Deng, Wenqing Sun, Qiang Cheng, Yang Liu   +6 more
doaj   +1 more source