Applications of Modeling and Machine Learning in Additive Manufacturing

This Special Issue reprint includes thirteen articles on the applications of modeling and machine learning for the novel design of additively manufactured products, additive manufacturing processes, alloy design, tailoring microstructures, customized mechanical and chemical properties, improved cree...

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Format:	Online
Idioma:	anglès
Publicat:	MDPI - Multidisciplinary Digital Publishing Institute 2025
Matèries:	unsupervised machine learning K-means clustering additive manufacturing nickel plating hardness scratch test machine learning random forest quality inspection laser powder bed fusion process monitoring optical tomography computerized tomography gas pores lack of fusion tensile properties in situ monitoring Gaussian Process Regression directed energy deposition single track geometry uncertainty quantification user-centric decision making expert knowledge keyhole deep learning image segmentation WAAM neural networks temperature history finite element method 3D printing convective flow buoyancy Stokes law gas porosity index stainless steel 316 Ti-6Al-4V Inconel 718 AlSi10Mg physics-informed neural networks metal additive manufacturing online learning real-time modeling temperature field prediction laser direct energy deposition surface repair aluminum alloy multiscale simulation molten pool thermal stress surrogate model recurrent neural network melt pool characterization thermal history direct energy deposition principal component analysis self-organizing maps linear mixed-effects models monitoring modeling statistics n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Accés en línia:	ONIX_20250812T110751_9783725837465_160
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Sumari:	This Special Issue reprint includes thirteen articles on the applications of modeling and machine learning for the novel design of additively manufactured products, additive manufacturing processes, alloy design, tailoring microstructures, customized mechanical and chemical properties, improved creep resistance, fatigue life, serviceability, and reducing defects and residual stresses and distortion.

Applications of Modeling and Machine Learning in Additive Manufacturing

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