Results 131 to 140 of about 6,382,755 (302)

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

Advanced 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, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

A Study on Accuracy in Hot Machining

Journal of the Japan Society of Precision Engineering, 1970
Ryoichi ICHIMIYA, Hideaki KAWAHARA
openaire   +3 more sources

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

Advanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi, Hadi Moutablaleh, Ignatius A. Setiawan, Mehrshad Mehrpouya   +3 more
wiley   +1 more source

Cathode Design and Flow Field Optimization in Electrochemical Machining of Square Holes. [PDF]

Micromachines (Basel)
Liu X, Guo Z, Du F, Su G, Chen H, Zhang C.   +5 more
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Modeling the accuracy of the manufacturing machine [PDF]

Proceedings of the 2nd EAI International Conference on Management of Manufacturing Systems, 2018
Jozef Svetlík, Juraj Kováč, Patrícia Dudová, Jozef Dobránsky, Michal Považan   +4 more
openaire   +1 more source

A data-driven approach for high-accuracy tool wear prediction in machining Hastelloy C276. [PDF]

Sci Rep
Abdullah M, Rao ACU, Ramachandran T, Biswal S, Chaudhary SP, Singh R, Mishra A, Mann VS, Bhowmik A, Abate L.   +9 more
europepmc   +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

Simulation and Experimental Research on Tooth Power Skiving Cutting of Double-circular-arc Internal Gears

Jixie chuandong
A method for machining double-circular-arc internal gears using power skiving technology is proposed to address the current problems of difficulty, poor accuracy, and low efficiency in machining double-circular-arc internal gears.
Wang Feng, Yang Shufeng, Xu Wenbo, Zhang Weijie, Yu Wentao   +4 more
doaj  

Intelligent machining error prediction and compensation system based on convolutional neural networks and improved genetic algorithm. [PDF]

Sci Rep
Bai W.
europepmc   +1 more source