Results 221 to 230 of about 281,198 (279)
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Numerical Analyses of Entropy Production and Thermodynamics Exergy on a Hydrogen-Fueled Micro Combustor Featuring a Diamond-Shaped Bifurcated Inner-Tube Structure for Thermophotovoltaic Applications. [PDF]
Almutairi F.
europepmc +1 more source
Powder metal processing provides scalable advantages in nanoporous (np) metal development. Mechanical alloying is used to produce unique precursors for hybrid nanopore formation by oxide reduction and dealloying. As demonstrated in np Ag, this approach improves process efficiency while promoting smaller ligaments and larger pores, both of which are ...
Mark A. Atwater, Oliver A. Fowler
wiley +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo +3 more
wiley +1 more source
Entropy production associated with magnetohydrodynamics (MHD) thermo-solutal natural convection of non-Newtonian MWCNT-SiO2-EG hybrid nano-coolant. [PDF]
Mahmud T, Chowdhury T, Nag P, Molla MM.
europepmc +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
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 +2 more
wiley +1 more source
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 +5 more
wiley +1 more source
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 +3 more
wiley +1 more source

