Results 71 to 80 of about 296,188 (298)

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 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

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

Creep‐Induced Microstructural Evolution in an A2‐B2 Superalloy

Advanced 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, Aparajita Pramanik, Sandipan Sen, Shubhashis Dixit, Marcel Muench, R. J. Vikram, Daniel Schliephake, Yolita M. Eggeler, Ankur Chauhan, Martin Heilmaier, Alexander Kauffmann   +10 more
wiley   +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

Experimental Characterization and Constitutive Modeling of the Effect of Prior Inelastic Strain on the Viscoplastic Behavior of AD730 at 700 °C

Advanced Engineering Materials, EarlyView.
This study shows that superalloys used in aircraft engine disks become much more prone to deformation at high temperatures if they have been strained during manufacturing. This effect increases with the level of prior strain but eventually reaches a limit.
Fabio Machado Alves da Fonseca, Patrick Villechaise, Malik Durand, Arnaud Longuet, Florent Coudon, Loïc Signor, Julien De Jaeger, Dominique Eyidi, Nathalie Bozzolo, Jonathan Cormier   +9 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

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced 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, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

Noise reduction and deflection of pipe tunnel data via intelligent optimization and modal decomposition

Discover Applied Sciences
Urban underground engineering construction widely uses pipe jacking tunnels due to their trenchless characteristics. However, environmental noise easily affects the monitoring data, making it difficult to extract deflection data.
Deyi Yu, Qiuhan Zhao, Gang Qiao, Nan Yu, Yong Wen, Ling Luo   +5 more
doaj   +1 more source