Results 261 to 270 of about 2,251,696 (313)

Electrospinning Technology, Machine Learning, and Control Approaches: A Review

open access: yesAdvanced Engineering Materials, Volume 27, Issue 7, April 2025.
Electrospinning produces micro‐ and nanoscale fibers, holding great promise in biomedical engineering. Industrial adoption faces challenges in controlling fiber properties, reproducibility, and scalability. This review explores electrospinning techniques, modeling, and machine learning for process optimization.
Arya Shabani   +5 more
wiley   +1 more source

Observation of oral actions using digital image processing system.

open access: bronze, 1990
Tetsuo Ichikawa   +5 more
openalex   +2 more sources

An Ontology‐Augmented Digital Twin for Fiber‐Reinforced Polymer Structures at the Example of Wind Turbine Rotor Blades

open access: yesAdvanced Engineering Materials, Volume 27, Issue 8, April 2025.
A methodology for establishing an ontology‐augmented structural digital twin for fiber‐reinforced polymer structures dedicated to individual lifetime prediction, in this case, a wind turbine rotor blade, is introduced. The methodology resembles the manufacturing as well as the operation of the structure.
Marc Luger   +6 more
wiley   +1 more source

Semantic Orchestration and Exploitation of Material Data: A Dataspace Solution Demonstrated on Steel and Copper Applications

open access: yesAdvanced Engineering Materials, Volume 27, Issue 8, April 2025.
This article introduces the Dataspace Management System (DSMS), a methodological framework realized in software, designed as a technology stack to power dataspaces with a focus on advanced knowledge management in materials science and manufacturing. DSMS leverages heterogeneous data through semantic integration, linkage, and visualization, aligned with
Yoav Nahshon   +7 more
wiley   +1 more source

Seamless Science: Lifting Experimental Mechanical Testing Lab Data to an Interoperable Semantic Representation

open access: yesAdvanced Engineering Materials, Volume 27, Issue 8, April 2025.
In pursuit of modern data management techniques, this study presents an in‐lab pipeline combining electronic laboratory notebooks (eLabFTW) and Python scripts for creating semantically enriched, interoperable, machine‐actionable data. Automating data mapping enhances usability, collaboration, and unified knowledge representation.
Markus Schilling   +7 more
wiley   +1 more source

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