Results 61 to 70 of about 25,726 (266)

Wear prediction of micro-grinding tool based on GA-BP neural network

Jin'gangshi yu moliao moju gongcheng
An intelligent tool wear prediction model has been proposed for the micro-grinding tool, optimized using a genetic algorithm (GA) based BP neural network.
Miao TIAN, Kangning YU, Yinghui REN, Chengxi SHE, Luan YI   +4 more
doaj   +1 more source

Designing Polymer Nanocomposites for X‐Ray Shielding: Mechanisms, Architectures, and Scalable Processing

Advanced Engineering Materials, EarlyView.
This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele, Hossein Ipakchi, Tizazu H. Mekonnen   +2 more
wiley   +1 more source

Liner Wear Prediction Using Bayesian Regression Models and Clustering

International Journal of Prognostics and Health Management
Chutes, bins, and hoppers are critical assets in bulk commodity handling. Sacrificial wear liners are employed to protect these assets from abrasive wear. An essential maintenance challenge is optimising the timing of liner replacements.
Jacob Van Den Broek, Melinda Hodkiewicz, Adriano Polpo   +2 more
doaj   +1 more source

Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure

Advanced Engineering Materials, EarlyView.
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari, Supharoek Sornsomrit, Muhammad Ayaz Akbar, Stephan Rudykh   +3 more
wiley   +1 more source

Influence of Si Content and Milling Duration on the Microstructure and Mechanical–Tribological Properties of AlCoCrFeNiSi High‐Entropy Alloys

Advanced Engineering Materials, EarlyView.
Si‐doped AlCoCrFeNi high‐entropy alloys are synthesized by mechanical alloying to reveal the effect of Si content and milling time on phase evolution, microstructural refinement, and tribological behavior. A transition from FCC to BCC structure, significant grain refinement, and enhanced hardness and wear resistance are achieved, with the 4 at% Si ...
Mustafa Okumuş, Mehmet Emin Demir, Sercan Özpınar   +2 more
wiley   +1 more source

Electrified Damage in Motion Systems

Advanced Engineering Materials, EarlyView.
The electrified damage in motion systems is a fundamental framework presenting the degradation pathway arising from the coupling of electrical energy transport with mechanical contact and interfacial chemistry. The framework positions electrified damage as a distinct degradation regime with unique characteristic surface morphologies and failures of ...
M. Humaun Kabir, Angelina Nguyen, Hong Liang   +2 more
wiley   +1 more source

Stretching the Printability Metric in Direct‐Ink Writing with Highly Extensible Yield‐Stress Fluids

Advanced Functional Materials, EarlyView.
This study introduces “drawability” as a new metric for assessing printability in direct‐ink writing, focusing on gap‐spanning performance and speed robustness. By designing yield‐stress fluids with high extensibility, we demonstrate that extensional strain‐to‐break significantly enhances printability.
Chaimongkol Saengow, Samya Sen, Joaquin Yus, Eliza E. Lovrich, Amanda G. Hoika, Kelly M. Chang, Arielle A. Pfeil, Nellie Haug, Amy J. Wagoner Johnson, Randy H. Ewoldt   +9 more
wiley   +1 more source

Mechanical Behavior and Fracture Mechanisms of MXene/PVDF Nanocomponsites: In Situ Characterization and Multiscale Analysis

Advanced Functional Materials, EarlyView.
Multiscale experiments and modeling reveal how Ti3C2Tx MXene nanosheets reinforce PVDF nanocomposites. An optimal MXene loading (∼1 wt.%) nearly doubles tensile strength through efficient stress transfer, flake alignment, and crack‐deflection mechanisms, transforming ductile polymer behavior into a controlled multi‐stage fracture pathway which aligns ...
Bita Soltan Mohammadlou, James FitzPatrick, Li Meng, Kateryna Shevchuk, Ahmad Najafi, Yury Gogotsi   +5 more
wiley   +1 more source

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source

Prediction of Rail Wear Under Different Railway Track Geometries Using Artificial Neural Networks

Infrastructures
The geometry of the railway track affects rail wear significantly. If the rail wear can be predicted and considered during the alignment design phase, the problems it causes can be mitigated at the source by optimizing the values and combinations of ...
Hong Zhang, Weichen Shuai, Linya Liu, Pengfei Zhang, Kejun Zhang, Hongsong Lin, Yuke Zhang, Wei Li   +7 more
doaj   +1 more source