Frames made of polymer composites are increasingly used in the aerospace, automotive, and agricultural industries. A frequently used technology in the production line of composite frames is winding rovings onto a non-load-bearing frame to form the structure using an industrial robot and a winding head, which is solidified through a subsequent heat-treatment pressure process. In this technology, the most difficult procedure is the winding of the curved parts of a composite frame. The primary concern is to ensure the proper winding angles, minimize the gaps and overlaps, and ensure the homogeneity of the wound layers. In practice, the curved frame parts very often geometrically form sections of a torus. In this work, the difficulty of achieving a uniform winding of toroidal parts is described and quantified. It is shown that attaining the required winding quality depends significantly on the geometrical parameters of the torus in question. A mathematical model with a detailed procedure describing how to determine the number of rovings of a given width on toroidal parts is presented. The results of this work are illustrated with practical examples of today's industrial problems.
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http://dx.doi.org/10.3390/polym15153227 | DOI Listing |
Front Oncol
October 2024
Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, United States.
Purpose: This paper discusses an advanced version of our audiovisual-assisted therapeutic ambience in radiotherapy (AVATAR) radiolucent display systems designed for pediatric radiotherapy, enabling anesthesia-free treatments, video communication, and biofeedback. The scope of the AVATAR system is expanded here in two major ways: (i) through alternative mounting systems to accommodate a broader range of radiotherapy machines (specifically to fit robotic-arm and toroidal geometry photon radiotherapy and proton radiotherapy systems) and (ii) through additional hardware to provide video-calling, optimized audio for clear communication, and combined video inputs for biofeedback, translation, and other advanced functionalities.
Methods And Materials: Because robustness requires strong parts and radio-transparency requires thin, light parts, three-dimensional printing was used to rapidly prototype hollow structures and to iteratively improve robustness.
Polymers (Basel)
July 2023
Department of Mathematics, Faculty of Science, Humanities and Education, Technical University of Liberec, Studentská 2, 461 17 Liberec, Czech Republic.
Sci Rep
June 2023
Japan Atomic Energy Agency, Tokai, 319-1195, Japan.
Magnetic components are key parts of energy conversion systems, such as electric generators, motors, power electric devices, and magnetic refrigerators. Toroidal inductors with magnetic ring cores can be found inside such electric devices that are used daily. For such inductors, magnetization vector M is believed to circulate with/without distribution inside magnetic cores as electric power was used in the late nineteenth century.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
February 2023
Southwestern Institute of Physics, Chengdu 610041,People's Republic of China.
We study the dynamics of turbulence transport subject to a constraint on the profile formation and relaxation, dominated by the ion temperature gradient modes, within the framework of adiabatic electron response using a flux-driven global gyro-kinetic toroidal code, GKNET. We observe exponentially constrained profiles, with two different scale lengths, that are spatially constant in each region in higher input power regimes. The profiles are smoothly connected in the knee region located at [Formula: see text] of the minor radius, outside which the gradient is steepened and shows a weak confinement improvement.
View Article and Find Full Text PDFExperimental observations assisted by 2-D imaging diagnostics on the KSTAR tokamak show that a solitary perturbation (SP) emerges prior to a boundary burst of magnetized toroidal plasmas, which puts forward SP as a potential candidate for the burst trigger. We have constructed a machine learning (ML) model based on a convolutional deep neural network architecture for a statistical study to identify the SP as a boundary burst trigger. The ML model takes sequential signals detected from 19 toroidal Mirnov coils as input and predicts whether each temporal frame corresponds to an SP.
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