Flesh Machine - Vision Machine - War Machine [PDF]
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In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi +4 more
wiley +1 more source
Flow Field Simulation and Experimental Study of Electrode-Assisted Oscillating Electrical Discharge Machining in the C<sub>f</sub>-ZrB<sub>2</sub>-SiC Micro-Blind Hole. [PDF]
Ge C +5 more
europepmc +1 more source
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Sustainable machining and optimization of machining parameters utilizing different dielectrics in EDM machining of Waspaloy. [PDF]
Priyanka P +3 more
europepmc +1 more source
Description of the U.S. Coast and Geodetic Survey tide-predicting machine, no. 2
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THE AUTOMATIC WEIGHING MACHINE CO. <italic>V.</italic> THE COMBINED WEIGHING MACHINE CO., <italic>AND</italic> THE COMBINED WEIGHING MACHINE CO. <italic>V.</italic> THE AUTOMATIC WEIGHING MACHINE CO. [PDF]
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Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
Editorial for Special Issue on Ultra-Precision Machining of Difficult-to-Machine Materials. [PDF]
Li C.
europepmc +1 more source

