Results 101 to 110 of about 5,846,901 (309)

The Influence of C(sp3)H–Selenium Interactions on the 77Se NMR Quantification of the π‐Accepting Properties of Carbenes

open access: green, 2020
Glen P. Junor   +5 more
openalex   +2 more sources

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

Current Tracking Adaptive Control of Brushless DC Motors

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
In this paper, the current tracking for Brushless Direct Current motors is approached considering uncertainty in the parameters of the motor's model. An adaptive control scheme to compensate electrical parameters uncertainty is proposed without requiring any knowledge of the mechanical parameters.
Fernanda Ramos‐García   +3 more
wiley   +1 more source

Dynamic Precipitation during High‐Pressure Torsion of a Magnesium–Manganese Alloy

open access: yesAdvanced Engineering Materials, EarlyView.
An ultrafine‐grained alloy is produced by high‐pressure torsion of solutionized Mg–1.35 wt% Mn. Precipitation of nanometer‐scale Mn particles during deformation provides pinning sites. This prevents the formation of a bimodal grain structure and results in a finer grain size than for pure Mg.
Julian M. Rosalie, Anton Hohenwarter
wiley   +1 more source

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

open access: yesAdvanced 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   +8 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

open access: yesAdvanced 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   +2 more
wiley   +1 more source

Multimodal Mechanical Testing of Additively Manufactured Ti6Al4V Lattice Structures: Compression, Bending, and Fatigue

open access: yesAdvanced Engineering Materials, EarlyView.
In this experimental study, the mechanical properties of additively manufactured Ti‐6Al‐4V lattice structures of different geometries are characterized using compression, four point bending and fatigue testing. While TPMS designs show superior fatigue resistance, SplitP and Honeycomb lattice structures combine high stiffness and strength. The resulting
Klaus Burkart   +3 more
wiley   +1 more source

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