10.14489/vkit.2024.09.pp.003-010

DOI: 10.14489/vkit.2024.09.pp.003-010

Вяткин С. И., Долговесов Б. С.
МЕТОД ПОДГОТОВКИ ФУНКЦИОНАЛЬНО ЗАДАННЫХ МОДЕЛЕЙ ДЛЯ 3D-ПЕЧАТИ
(c. 3-10)

Аннотация. Предложен метод синтеза объектов, созданных из сложных разнородных материалов, со множеством материалов для 3D-печати. Метод поддерживает процедурную оценку геометрических деталей и состава материала. Функционально заданные модели обеспечивают компактное хранение баз данных. В методе только небольшая часть конечного объема сохраняется в памяти, а выходные данные небольшими порциями передаются на выход.

Ключевые слова: функциональная модель; вокселизация; 3D-печать.

Vyatkin S. I., Dolgovesov B. S.
A METHOD FOR PREPARING FUNCTIONALLY SPECIFIED MODELS FOR 3D PRINTING
(pp. 3-10)

Abstract. 3D printing is widely used in industry, architecture, aerospace, crafts, art, etc. 3D printing based on a variety of materials allows you to create objects from complex heterogeneous materials. However, there are huge computational difficulties. The problem of 3D printing is still open for research. We propose a method for synthesizing objects with a variety of materials for 3D printing. The method supports the procedural evaluation of geometric details and the composition of the material. Functionally defined models provide compact database storage. In the method, only a small part of the final volume is stored in memory, and the output data is transmitted to the output in small portions. The purpose of the proposed work is to create a method for preparing functionally specified models for 3D printing. Additive manufacturing from many materials is becoming available for an increasing number of applications. When developing the proposed method, the following was taken into account. The method provides continuous definition of the material, scalability for printing large volumes and a minimum of preliminary calculations. A method for describing the complex optical and mechanical logic of materials has been developed. The composition of the material and geometric details are calculated procedurally, taking into account the separation of material and geometry. Templates are defined independently of the geometry and are reused in different models. The procedural synthesis of surface and volume detail ensures resolution independence at different image sizes and resolution.

Keywords: Functional model; Voxelization; 3D printing.

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С. И. Вяткин, Б. С. Долговесов (Институт автоматики и электрометрии Сибирского отделения Российской академии наук, Новосибирск, Россия) E-mail: Этот e-mail адрес защищен от спам-ботов, для его просмотра у Вас должен быть включен Javascript

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S. I. Vyatkin, B. S. Dolgovesov (Institute of Automation and Electrometry of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia) E-mail: Этот e-mail адрес защищен от спам-ботов, для его просмотра у Вас должен быть включен Javascript

+ - Библиографический список (References) Click to collapse

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Eng

1. Vyatkin S. I., Dolgovesov B. S. (2022). Functionally defined models for additive manufacturing. Issledovaniya. Innovatsii. Praktika, 4(4), 16 – 25. [in Russian language] DOI: 10.18411/iip -08-2022-04
2. Elek O., Zhang R., Sumin D. et. al. (2021). Robust and Practical Measurement of Volume Transport Parameters in Solid Photo-polymer Materials for 3D Printing. Optics Express, 29(5), 7568 – 7588. DOI: 10.1364/OE.406095
3. Zhao M., Li X., Zhang D., Zhai W. (2022). TPMS-Based Interpenetrating Lattice Structures: Design, Mechanical Properties and Multiscale Optimization. In-ternational Journal of Mechanical Sciences, 244(45). DOI: 10.1016/j.ijmecsci.2022.108092
4. Morsy M., Morsy A., Brunton A., Urban P. (2022). Shape Dithering for 3D Printing. ACM Transac-tions on Graphics, 41(4), 1 – 12. DOI: 10.1145/3528223.3530129
5. Nagasawa K., Ono K., Arai W., Tsumura N. (2023). Perceptual Translucency in 3D Printing Using Surface Texture. Journal of Imaging, 9(5), 1 – 18. DOI: 10.3390/jimaging9050105
6. Nagasawa K., Ono K., Arai W., Tsumura N. (2022). Reproduction of Perceptual Translucency by Surface Texture in 3D Printing. Color and Imaging Conference, 30(1), 264 – 270. DOI: 10.2352/CIC.2022.30.1.46
7. Piovarci M., Foshey M., Babaei V. et. al. (2020). Towards Spatially Varying Gloss Reproduction for 3D Printing. ACM Transactions on Graphics, 39(6), 1 – 13. DOI: 10.1145/3414685.3417850
8. Urban P. (2020). Graphical 3D Printing: Challenges, Solutions and Applications. London Imaging Meeting, (1), 87 – 90. DOI: 10.2352/issn.2694-118X.2020.LIM-35
9. Zheng A., Zhu Z., Bian S. et. al. (2021). Optimized Unidirectional and Bidirectional Stiffened Objects for Minimum Material Consumption of 3D Printing. Mathematics, 21(9), 1 – 15. DOI: 10.3390/math9212835
10. Zheng A., Bian S., Chaudhry E. et. al. (2020). Minimizing Material Consumption of 3D Printing with Stress-Guided Optimization. Computational Science, 5, 588 – 603. DOI: 10.1007/978-3-030-50426-7_44
11. Miyoshi M., Punpongsanon P., Iwai D.,Sato K. (2021). SoftPrint: Investigating Haptic Softness Perception of 3D Printed Soft Object in FDM 3D Printers. Journal of Imaging Science and Technology, 65, 1 – 25. DOI: 10.2352/J.ImagingSci.Technol.2021.65.4.040406
12. Yang W., Calius E., Huang L., Singamneni S. Artificial Evolution and Design for Multi-Material Addi-tive Manufacturing. (2020). 3D Printing and Additive Manufacturing, 7(6), 326 – 337 DOI: 10.1089/3dp.2020.0114
13. Hashemi M. S., McCrary A., Kraus K. H., Sheidaei A. (2021). A Novel Design of Printable Tunable STiffness Metamaterial for Bone Healing. Journal of the Mechanical Behavior of Biomedical Materials, 116(2), 1 – 9. DOI: 10.1016/j.jmbbm.2021.104345
14. Zhang M., Zhao N., Yu Q. et. al. (2022). On the damage tolerance of 3-D printed Mg-Ti interpenetrating-phase composites with bioinspired architectures. Nature Communications, 13(1), 1 – 14. DOI: 10.1038/s41467-022-30873-9
15. Yang J., Chen X., Sun Y. et. al. (2023). Ra-tional Design and Additive Manufacturing of Grain Boundary-Inspired, Multi-Architecture Lattice Structures. Materials & Design, 235, 1 – 12. DOI: 10.1016/j.matdes.2023.112448
16. Jones A., Leary M., Bateman S., Easton M. A. (2023). Investigating Mechanical Properties of Additively Manufactured Multimaterial Gyroids: the Effect of Pro-portion, Scale and Shape. Additive Manufacturing, 76, 1 – 12. DOI: 10.1016/j.addma.2023.103784
17. Aghajani S., Wu C., Li Q., Fang J. (2023). Additively Manufactured Composite Lattices: A State-of-the-art Review on Fabrications, Architectures, Constituent Materials, Mechanical Properties, and Future Directions. Thin-Walled Structures, 197(9), 1 – 5. DOI: 10.1016/j.tws.2023.111539
18. Vyatkin S. I. (2007). Modeling complex surfaces using perturbation functions. Avtometriya, 43(3), 40 – 47. [in Russian language]
19. Vyatkin S. I. (2014). Transformations of functionally specified forms. Programmnye sistemy i vychislitel'nye metody, (4), 484 – 499. [in Russian language]
20. Vyatkin S. I., Dolgovesov B. S. (2018). Geo-metric data compression method using perturbation functions. Avtometriya, 54(4), 18 – 25. [in Russian language] DOI: 10.15372/AUT20180403
21. Katasonov A. V., Vyatkin S. I., Dolgovesov B. S. (2005). Voxelization of functional forms. Proceedings of the 15th Intertnational conference on computer graphics and its applications “Graphicon-2005”, 372 – 377. Novosibirsk: IVMMG SO RAN. [in Russian language]

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