Results 191 to 200 of about 1,044,738 (264)

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
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, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Image Filtering to Improve Maize Tassel Detection Accuracy Using Machine Learning Algorithms. [PDF]

Sensors (Basel)
Rodene E, Fernando GD, Piyush V, Ge Y, Schnable JC, Ghosh S, Yang J.   +6 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
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, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Enhancing Prostate Cancer Detection Accuracy in Magnetic Resonance Imaging-targeted Prostate Biopsy: Optimizing the Number of Cores Taken. [PDF]

Eur Urol Open Sci
Zattoni F, Fasulo V, Kasivisvanathan V, Kesch C, Marra G, Martini A, Falagario U, Soeterik T, van den Bergh R, Rajwa P, Gandaglia G, EAU-YAU Prostate Cancer Working Party (PCa-WP).   +11 more
europepmc   +1 more source

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

Deep learning-based image quality assessment: impact on detection accuracy of prostate cancer extraprostatic extension on MRI. [PDF]

Abdom Radiol (NY)
Lin Y, Belue MJ, Yilmaz EC, Law YM, Merriman KM, Phelps TE, Gelikman DG, Ozyoruk KB, Lay NS, Merino MJ, Wood BJ, Gurram S, Choyke PL, Harmon SA, Pinto PA, Turkbey B.   +15 more
europepmc   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source

A Simplified Laminar Flow Model for the Pultrusion of Glass Fiber/Polyethylene Terephthalate Commingled Yarns

Advanced Engineering Materials, EarlyView.
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares, Nadège Bouchonneau, Christian Jochum, Donald Radford   +3 more
wiley   +1 more source

Enhancing reginal wall abnormality detection accuracy: Integrating machine learning, optical flow algorithms, and temporal convolutional networks in multi-view echocardiography. [PDF]

PLoS One
Kasim S, Tang J, Malek S, Ibrahim KS, Shariff RER, Chima JK.   +5 more
europepmc   +1 more source

Flexural Behavior of 3D‐Printed Porous Bouligand‐Structured Polymers: Influence of Pitch Angle and Porosity

Advanced Engineering Materials, EarlyView.
This study examines how helicoidal architectures with different porosities respond to bending. Adjusting layer angle and spacing in 3D‐printed polymers reveals clear tradeoffs between stiffness, strength, and energy absorption. Experiments and simulations highlight designs that distribute stress effectively, offering pathways for optimizing lightweight
Praveenkumar Subhash Patil, Edward D. McCarthy, Parvez Alam   +2 more
wiley   +1 more source