Results 191 to 200 of about 182,295 (268)

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Noise2Average: An iterative residual learning strategy for image denoising without clean data. [PDF]

Imaging Neurosci (Camb)
Li Z, Li Z, Bilgic B, Ying K, Salat DH, Polimeni JR, Liao H, Huang SY, Tian Q.   +8 more
europepmc   +1 more source

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

Current Practices and a Novel Operational Framework for Planning Research on Digital Health Promotion Interventions From Development to Implementation: Scoping Review. [PDF]

J Med Internet Res
Collin C, Alberti C, Martin P, Moore G, Eyraud C, Le Roux E.   +5 more
europepmc   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

Parameter Selection in Coupled Dynamical Systems for Tomographic Image Reconstruction. [PDF]

J Imaging
Kasai R, Al-Ola OMA, Yoshinaga T.
europepmc   +1 more source

A Thermodynamic 3D Model for the Simulation of Diffusion‐Controlled Alloying Processes in Heterogeneous Material Structures

Advanced Engineering Materials, EarlyView.
A numerical model resulting from irreversible thermodynamics for describing transport processes is introduced, focusing on thermodynamic activity gradients as the actual driving force for diffusion. Implemented in CUDA C++ and using CalPhaD methods for determining the necessary activity data, the model accurately simulates interdiffusion in aluminum ...
Ulrich Holländer, Leonhard Holländer, André Langohr, Hans Jürgen Maier   +3 more
wiley   +1 more source

Masting Breakdown in European Beech Reduces Fitness Benefits of Masting, Partly Explained by Climate Change. [PDF]

Ecol Evol
Jantzen CC, Burant JB, Gamelon M, Bakker ES, Visser ME.   +4 more
europepmc   +1 more source

Microstructural Evolution and Vacancy Defect Formation in Mn–Mo–Ni RPV Steel Under Low Cycle Fatigue: Insights From EBSD and PALS

Advanced Engineering Materials, EarlyView.
Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar, Dhanadeep Dutta, G. Bharat Reddy   +2 more
wiley   +1 more source

ChemScreener: an active learning enabled hit discovery workflow with WDR5 inhibitor case study. [PDF]

J Cheminform
Shen L, Fang J, Liu L, Wang R, Jenkins JL, Wang H.   +5 more
europepmc   +1 more source