Results 151 to 160 of about 19,693 (247)

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

open access: yesAdvanced 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   +9 more
wiley   +1 more source

Modeling Dislocation Cutting of γ′ Precipitates in Ni‐Base Superalloys: Linking Atomistic and Dislocation Dynamics Simulations

open access: yesAdvanced Engineering Materials, EarlyView.
Dislocation cutting of γ′ precipitates in Ni‐based superalloys is investigated by linking atomistic simulations with discrete dislocation dynamics. The critical cutting stress is shown to be governed by the antiphase boundary energy, while line tension effects promote edge‐preferred cutting.
Frédéric Houllé   +9 more
wiley   +1 more source

Experimental performance comparison of fixed and single-axis subfields in a large-scale outdoor photovoltaic power plant. [PDF]

open access: yesSci Rep
Abderraouf B   +7 more
europepmc   +1 more source

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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

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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