Analytical identification of the unmanned aerial vehicles' surfaces for the implementation at a 3D printer
Journal Title: Восточно-Европейский журнал передовых технологий - Year 2019, Vol 1, Issue 2
Abstract
<p>Based on the R-functions theory, new approaches to analytical identification of drone surfaces for realization of 3D printing technology have been developed.</p><p>The R-functions theory allows one to describe geometric objects of a complex shape with a single analytical expression, that is, obtain a mathematical model of the object in a form of an equation. To derive such equations, we used both the well-known standard primitive (sphere, ellipsoid, cylinder, cone, pyramid, etc.) procedure and a new approach, blending on a frame, which enables derivation of multiparameter equations with specified properties. Multiparameter equations of surfaces of drones of various types and purposes have been derived and visualized. Adequacy of the results to the designed objects was confirmed by visualization, both in conditions of operation of the RFPreview program and by realization on a 3D printer. The use of literal parameters when specifying geometric information in an analytical form makes it possible to promptly change size and shape of the designed objects which helps reduce time required to build computational models. The proposed method can reduce labor input in operation of CAD systems by months in cases when it is necessary to view a large number of design variants in a search for an optimal solution. Having the object equation, one can easily obtain equation of any of its sections which is useful for numerical calculations, namely, when building computational meshes.</p><p>This can have a great effect on reducing complexity in construction of computational models for determining aero-gas-dynamic and strength characteristics. Characterization is also often associated with the need to account for changes in the aircraft shape. This leads to the fact that establishment of aerodynamic characteristics just because of the need to build a large number of computational models to account for this factor increases work duration by months. When specifying parameters, change of the rated operating conditions is made almost instantly.</p>
Authors and Affiliations
Tatyana Sheyko, Kirill Maksimenko-Sheyko, Vladimir Sirenko, Anna Morozova, Roksana Petrova
Keywords
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- EP ID EP666165
- DOI 10.15587/1729-4061.2019.155548
- Views 78
- Downloads 0
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