Results 161 to 170 of about 43,039 (317)

Optimization of Machining Parameters for Milling Zirconia Ceramics by Polycrystalline Diamond Tool. [PDF]

Materials (Basel), 2021
Yan X, Dong S, Li X, Zhao Z, Dong S, An L.   +5 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

Dimensions and cost prediction modelling of Nd:YVO₄laser internal micro-channel fabrication in PMMA [PDF]

, 2010
This paper presents the employment of Design of Experiments (DoE) as the prediction tool for the laser micro-machining process. Laser internal micro-channels machined using pulsed Nd:YVO4 laser in PMMA were studied.
Brabazon, Dermot, Karazi, Shadi, Ben Azouz, Aymen   +2 more
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Neural-Network-Based Approaches for Optimization of Machining Parameters Using Small Dataset. [PDF]

Materials (Basel), 2022
Kosarac A, Mladjenovic C, Zeljkovic M, Tabakovic S, Knezev M.   +4 more
europepmc   +1 more source

Variable Stiffness Flexure Structures Enabled by Phase‐Change Gallium and Adhesive Interfacial Locking for Soft Robotic Applications

Advanced Engineering Materials, EarlyView.
A flexure‐based variable stiffness structure is developed by integrating phase‐change modulation and adhesive interfacial locking of gallium. The design enables a wide stiffness variability, transitioning from soft, flexible behavior to rigid, load‐supporting performance.
Sungjin Kim, Sohee John Yoon, Yong‐Lae Park   +2 more
wiley   +1 more source

Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models. [PDF]

Materials (Basel), 2022
Rammohan S, Kumaran ST, Uthayakumar M, Korniejenko K, Nykiel M, Velayutham A.   +5 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

Teaching machines to optimizing machining parameters: using independent fuzzy logic controller and image data. [PDF]

SN Appl Sci, 2022
Mamledesai H, Zheng Y, Ahmad R.
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

Acoustic Emission Detection Signals in the Experimental Validation of Nanometric Machining Simulations [PDF]

, 2012
The molecular dynamics simulations of nanomachining processes have provided insight into process parameters, material removal and tool wear mechanisms.
Oluwajobi, Akinjide O., Chen, X.
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