Results 131 to 140 of about 18,411,452 (302)

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

open access: yesAdvanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle   +5 more
wiley   +1 more source

Reduction of nonlinear models for control applications

open access: yes, 2013
A systematic approach to the model reduction of high-fidelity fluid-structure-flight models and the subsequent flight control design for very flexible aircraft is considered. The test case is for an unmanned aerial vehicle.
Da Ronch, A.   +2 more
core   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

open access: yesAdvanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare   +5 more
wiley   +1 more source

Microstructure Modification of Additively Manufactured Mo–9Si–8B by Annealing and Its Effects on High‐Temperature Mechanical Properties

open access: yesAdvanced Engineering Materials, EarlyView.
Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt   +5 more
wiley   +1 more source

Design of a model following control system for nonlinear descriptor system in discrete time [PDF]

open access: yes, 2008
summary:A model following control system (MFCS) can output general signals following the desired ones. In this paper, a method of nonlinear MFCS will be extended to be a nonlinear descriptor system in discrete time.
Okubo, Shigenori   +2 more
core   +1 more source

An Explicit Constitutive Reconstruction Framework for Mechanical Characterization of Miniaturized 3D‐Printed Specimens

open access: yesAdvanced Engineering Materials, EarlyView.
An explicit constitutive reconstruction framework enables accurate tensile characterization of miniaturized additively manufactured specimens using only the grip‐to‐grip displacement measurements. Progressive validation through self‐consistency, analytical comparison, and inverse finite element method (iFEM) benchmarking demonstrates constitutive ...
Junqing Leng   +4 more
wiley   +1 more source

Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials

open access: yesAdvanced Engineering Materials, EarlyView.
Adaptive foam 3D printing, enabled by expandable microspheres, imparts cellular structures to thermoplastic and thermosetting polymers, manufactured through a variety of processes including fused filament fabrication, direct ink writing, digital light processing, and inkjet printing.
Nariman Rajabifar, Amir Ameli
wiley   +1 more source

Home - About - Disclaimer - Privacy