Results 231 to 240 of about 1,118,651 (312)

PID control algorithm based on multistrategy enhanced dung beetle optimizer and back propagation neural network for DC motor control. [PDF]

Sci Rep
Kong W, Zhang H, Yang X, Yao Z, Wang R, Yang W, Zhang J.   +6 more
europepmc   +1 more source

Enhancing Bubble Removal in Geometry‐Optimized Electrodes

Advanced Engineering Materials, EarlyView.
3D‐printed lattice electrodes outperform stochastic foams in alkaline water electrolysis despite 20%–25% lower surface area. Straight flow channels generate Venturi‐like bubble entrainment, suppressing gas accumulation that renders foam interiors electrochemically inactive.
Florian Wiesner, Peter Förster, Alexander Limper, Anselm Brodersen, Matthias Wessling, John Linkhorst   +5 more
wiley   +1 more source

Directive transportation in smart cities with line connectivity at distinctive points using mode control algorithm. [PDF]

Sci Rep
Selvarajan S, Manoharan H, Khadidos AO, Khadidos AO, Hasanin T.   +4 more
europepmc   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Lateral Evasive Maneuver with Shared Control Algorithm: A Simulator Study. [PDF]

Sensors (Basel)
Sarabia J, Marcano M, Díaz S, Zubizarreta A, Pérez J.   +4 more
europepmc   +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

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

Advanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi, Hadi Moutablaleh, Ignatius A. Setiawan, Mehrshad Mehrpouya   +3 more
wiley   +1 more source

Compatibility of Methacrylate Based Resins Controls Interfacial Failure and Toughness in 3D‐Printed Multimaterial Composites

Advanced Engineering Materials, EarlyView.
This work shows that the mechanical performance of multimaterial digital light processing (DLP) printed thermoset composites is governed by resin compatibility and interfacial design rather than spatial patterning alone. Brittle and ductile resin combinations produced premature interfacial failure, while graded interfaces and mechanically compatible ...
Ahmed M. H. Ibrahim, Li Meng, Ahmad R. Najafi, Nicolas J. Alvarez   +3 more
wiley   +1 more source

A Novel IDS with a Dynamic Access Control Algorithm to Detect and Defend Intrusion at IoT Nodes. [PDF]

Sensors (Basel)
Alazab M, Awajan A, Alazzam H, Wedyan M, Alshawi B, Alturki R.   +5 more
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source