Results 101 to 110 of about 21,380 (265)

Creep Properties and Deformation Mechanism of Additively Manufactured NiAl‐CrMo Composites

open access: yesAdvanced Engineering Materials, EarlyView.
Additively manufactured NiAl‐CrMo composites contain numerous interfaces and cell boundaries that control their creep response. At 700°C under high applied stress, creep is dominated by dislocation‐controlled power‐law mechanisms. At 800°C–900°C and lower stresses, creep is primarily diffusion‐controlled along cell boundaries.
Jan Vollhüter   +9 more
wiley   +1 more source

Optimization of the Production of Rubber Compounds Using Mathematical Models

open access: yesAdvanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle   +7 more
wiley   +1 more source

Additions [PDF]

open access: yesDeutsches Ärzteblatt international, 2019
openaire   +2 more sources

Molecular Dynamics Studies of Shape Memory Polymers: From Bead–Spring Models to Atomistic Simulations

open access: yesAdvanced Engineering Materials, EarlyView.
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley   +1 more source

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

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

Precipitation Simulations of the O‐Phase in Ti2AlNb Alloys Processed by Laser Powder Bed Fusion

open access: yesAdvanced Engineering Materials, EarlyView.
Simulated and experimental evolution of the O‐phase volume fraction during postprocessing of a Ti‐21Al‐25Nb (at.%) alloy processed by laser powder bed fusion. With results of sensitivity to input parameters from a thorough and quantified analysis, the interfacial energy matrix/precipitate is the most relevant input parameter for the simulation of the O‐
Silvana Tumminello   +7 more
wiley   +1 more source

Ratio estimators and simultaneous regression estimators for biomass in mixed plantation of Pinus elliottii Engelm. and Pinus taeda L.

open access: yesForest Systems
Aim of study: To evaluate the performance and biological consistency of ratio estimators for estimating the biomass of Pinus elliottii Engelm. and Pinus taeda L.
Ornélio P. E. Nhaduco   +6 more
doaj   +1 more source

with notes and additions [PDF]

open access: yesThe American Journal of the Medical Sciences
n ...
openaire   +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

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