Eklemeli imal edilmiş gözenekli topolojilerin ısıl performansı üzerine deneysel incelemeler

Öz

Eklemeli üretim, araştırmacıların tasarım kompaktlığı, gelişmiş verimlilik ve düşük maliyeti sağlayan benzersiz ve sıra dışı topolojiler oluşturmasına imkân verir. Eklemeli üretimin getirdiği tasarım özgürlüğü, topoloji optimizasyon yaklaşımını ısıl sistemlere uygulama fikrini ortaya çıkarmaktadır. Bu çalışmada, üç farklı tip topoloji için ısıl performansındaki değişimi deneysel olarak araştırılmaktadır: gyroid, bal peteği ve doğrusal. Ek olarak, çalışmanın etkisini artırmak için her topolojinin gözeneklilik seviyesi %25, %50 ve %75 arasında değiştirilmektedir. Deneysel sonuçlar, jiroid yapıların diğer topolojilere kıyasla ısıl yönden daha verimli (%15.6’ya kadar)olduğunu göstermektedir. Ayrıca, %25 poroziteye sahip doğrusal ve jiroid topolojilerin termal yayınımları uç noktalar olarak ölçülmüştür ve bu yapıların altıgen yapıya göre 1.1 kat daha fazla ısı yaydığı tespit edilmiştir.

Anahtar Kelimeler

• Topoloji optimizasyonu
• Gözenekli yapı
• Etkin ısıl iletkenlik
• Isıl yayılım

Experimental investigations on the thermal performance of additively manufactured porous topologies

Öz

Additive manufacturing enables researchers to form unique and unconventional topologies satisfying design compactness, improved efficiency, and lower cost. Design freedom introduced by the additive manufacturing reveals the idea of implementing the topology optimization approach into thermal systems. In this study, changes in thermal performance of three types of topologies: gyroid, hexagon (honeycomb), and rectilinear are experimentally investigated. In addition, porosity level of each topology is varied in between 25%, 50% and 75% to improve the impact of the study. The experimental results indicate that gyroid structures are thermally more efficient (up to 15.6%) than the remaining topologies. Furthermore, thermal diffusivities of the rectilinear and gyroid topologies with 25% porosity level are measured as the extremes, and it is detected that these structures propagate heat 1.1 times greater than the hexagon structure.

Anahtar Kelimeler

• Topology optimization
• Porous media
• Effective thermal conductivity
• Thermal diffusivity

Kaynakça

1. [1] Rong, Y., Zhao, Z.L., Feng, X.Q., Xie Y.M. 2022. Structural topology optimization with an adaptive design domain. Computer Methods in Applied Mechanics and Engineering. Volume 389, 114382. https://doi.org/10.1016/j.cma.2021.114382
2. [2] Prathyusha, A.L.R., Babu, G.R. 2022. A review on additive manufacturing and topology optimization process for weight reduction studies in various industrial applications. Materials Today Proceedings. Volume 62, pp. 109-117. https://doi.org/10.1016/j.matpr.2022.02.604
3. [3] Fawaz, A., Hua, Y., Le Corre, S., Fan, Y., Luo, L. 2022. Topology optimization of heat exchangers: A review. Energy, Volume 252, 124053. https://doi.org/10.1016/j.energy.2022.124053
4. [4] Lopes, H.N., Cunha, D.C., Pavanello, R., Mahfoud, J. 2022. Numerical and experimental investigation on topology optimization of an elongated dynamic system. Mechanical Systems and Signal Processing. Volume 165, 108356. https://doi.org/10.1016/j.ymssp.2021.108356
5. [5] Sun, Z., Wang, Y., Liu, P., Luo, Y. 2022. Topological dimensionality reduction-based machine learning for efficient gradient-free 3D topology optimization. Materials & Design. Volume 220, 110885. https://doi.org/10.1016/j.matdes.2022.110885
6. [6] Bujny, M., Olhofer, M., Aulig, N., Duddeck, F. 2021. Topology Optimization of 3D-printed joints under crash loads using Evolutionary Algorithms. Structural and Multidisciplinary Optimization. Volume 64, pp. 4181–4206. https://doi.org/10.1007/s00158-021-03053-4
7. [7] Siegkas, P. 2022. Generating 3D porous structures using machine learning and additive manufacturing. Materials & Design. Volume 220, 110858. https://doi.org/10.1016/j.matdes.2022.110858
8. [8] Shuaib, M., Haleem, A., Kumar, S., Javaid, M. 2021. Impact of 3D Printing on the environment: A literature-based study. Sustainable Operations and Computers. Volume 2, pp. 57-63. https://doi.org/10.1016/j.susoc.2021.04.001

9. [9] Maleki, E., Bagherifard, S., Bandini, M., Guagliano, M. 2021. Surface post-treatments for metal additive manufacturing: Progress, challenges, and opportunities. Additive Manufacturing. Volume 37, 101619. https://doi.org/10.1016/j.addma.2020.101619
10. [10] Lu, J., Dong, P., Zhao, Y., Zhao, Y., Zeng, Y., 2021. 3D printing of TPMS structural ZnO ceramics with good mechanical properties. Ceramics International. Volume 47, 12897-12905. https://doi.org/10.1016/j.ceramint.2021.01.152
11. [11] Kushwaha, B., Dwivedi, K., Ambekar, R.S., Pal, V., Jena, D.P., Mahapatra, D.R., Tiwary, C.S. 2020. Mechanical and acoustic behavior of 3D-printed hierarchical mathematical fractal menger sponge. Advance Engineering Materials. Volume 23, 2001471. https://doi.org/10.1002/adem.202001471
12. [12] Rouf, S., Rina, A., Haq, M.I.U., Naveed, N., Jeganmohan, S., Kichloo, A.F. 2022. 3D printed parts and mechanical properties: Influencing parameters, sustainability aspects, global market scenario, challenges, and applications. Advanced Industrial and Engineering Polymer Research. Volume 5, 143-158. https://doi.org/10.1016/j.aiepr.2022.02.001
13. [13] Afrose, M.F., Masood, S.H., Iovenitti, P., Nikzad, M., Sbarski, I. 2016. Effects of part build orientations on fatigue behaviour of FDM-processed PLA material. Progress in Additive Manufacturing. Volume 1, 21–28. https://doi.org/10.1007/s40964-015-0002-3.
14. [14] Ma, L., Zhang, Q., Jia, Z., Liu, C., Deng, Z., Zhang, Y. 2022. Effect of drying environment on mechanical properties, internal RH and pore structure of 3D printed concrete. Construction and Building Materials. Volume 315, 125731. https://doi.org/10.1016/j.conbuildmat.2021.125731
15. [15] Heever, M., Plessis, A., Kruger, J., Zijl, G. 2022. Evaluation the effects of porosity on mechanical properties of extrusion-based 3D printed concrete. Cement and Concrete Research. Volume 153, 106695. https://doi.org/10.1016/j.cemconres.2021.106695
16. [16] Rimasauskas, M., Jasiuniene, E., Kuncius, T., Rimasauskiene, R., Cicenas, V. 2022. Investigation of influence of printing parameters on the quality of 3D printed composite structures. Composite Structures. Volume 281, 115061. https://doi.org/10.1016/j.compstruct.2021.115061
17. [17] Zhang, Y., Hsieh, M.T., Valdevit, L. 2021. Mechanical performance of 3D printed interpenetrating phase composites with spinodal topologies. Composite Structures. Volume 263, 113693. https://doi.org/10.1016/j.compstruct.2021.113693
18. [18] Indres, A.I., Constantinescu, D.M., Mocian, O.A. 2021. Bending behavior of 3D printed sandwich beams with different core topologies. Wiley Material Design & Processing Communications. Volume 3, e252. https://doi.org/10.1002/mdp2.252
19. [19] Jeong, D.G., Seo, H.S. 2021. Study on mechanical performance of 3D printed composite material with topology shape using finite element method. Functional Composites and Structures. Volume 3, 035003. https://doi.org/10.1088/2631-6331/ac1914
20. [20] Hmeidat, N.S., Brown, B., Jia, X., Vermaak, N., Compton, B. 2021. Effects of infill patterns on the strength and stiffness of 3D printed topologically optimized geometries. Rapid Prototyping Journal, Volume 27, pp. 1467-1479. https://doi.org/10.1108/RPJ-11-2019-0290
21. [21] Zhang, J., Yanagimoto, J. 2021. Density-based topology optimization integrated with genetic algorithm for optimizing formability and bending stiffness of 3D printed CFRP core sandwich sheets. Composites Part B: Engineering. Volume 225, 109248. https://doi.org/10.1016/j.compositesb.2021.109248
22. [22] Ozguc, S., Pan, L., Weibel, J.A. 2021. Topology optimization of microchannel heat sinks using a homogenization approach. International Journal of Heat and Mass Transfer, Volume 169,120896. https://doi.org/10.1016/j.ijheatmasstransfer.2020.120896.
23. [23] Dirker, J., Meyer, J.P. 2013. Topology Optimization for an Internal Heat-Conduction Cooling Scheme in a Square Domain for High Heat Flux Applications. Journal of Heat Transfer, ASME. Volume 135, 111010. https://doi.org/10.1115/1.4024615
24. [24] Donoso, A. 2006. Numerical Simulations in 3D Heat Conduction: Minimizing the Quadratic Mean Temperature Gradient by an Optimality Criteria Method. SIAM Journal on Scientific Computing, Volume 28, pp. 929-941. https://doi.org/10.1137/060650453
25. [25] Dbouk, T. 2017. A review about the engineering design of optimal heat transfer systems using topology optimization. Applied Thermal Engineering. Volume 112, 841-854. https://doi.org/10.1016/j.applthermaleng.2016.10.134.
26. [26] Li, H., Ding, H., Meng, F., Jing, D., Xiong, M. 2019. Optimal design and thermal modelling for liquid-cooled heat sink based on multi-objective topology optimization: An experimental and numerical study. International Journal of Heat and Mass Transfer. Volume 144, 118638. https://doi.org/10.1016/j.ijheatmasstransfer.2019.118638
27. [27] Taha, B., Patil, S., Dennis, B.H. 2021. Design and Manufacturing of Topology Optimized Heat Sinks Made of Copper Using 3D Printing. ASME Proceedings of the 16th International Manufacturing Science and Engineering Conference. Volume 1: Additive Manufacturing. June 21–25. https://doi.org/10.1115/MSEC2021-63877
28. [28] Tseng, P.H., Tsai, K.T., Chen, A.L., Wang, C.C. 2019. Performance of novel liquid-cooled porous heat sink via 3D laser additive manufacturing. International Journal of Heat and Mass Transfer. Volume 137, 558-564.https://doi.org/10.1016/j.ijheatmasstransfer.2019.03.116
29. [29] Bejan, A. 2013. Convection Heat Transfer. 4th Edition. WILEY, Hoboken, New Jersey.
30. [30] Cengel, Y.A. 2002. Heat Transfer: A Practical Approach. 2nd Edition. McGraw-Hill, New York.
31. [31] Incropera, F.P., Dewitt, D.P., Bergman, T.L., Lavine, A.S. 2020. Principles of Heat and Mass Transfer. Global Edition. WILEY, Hoboken, New Jersey.
32. [32] Oss. S. 2022. A simple model of thermal conduction in human skin: temperature perception and thermal effusivity. European Journal of Physics, Volume 43, 035101. https://doi.org/10.1088/1361-6404/ac4c8a
33. [33] Turhan, C., Ceter, A.E. 2021. A novel occupant detection-based ventilation control strategy for smart building applications. Mugla Journal of Science and Technology. Volume 7, pp. 24-35. https://doi.org/10.22531/muglajsci.928315
34. [34] Turhan, C. 2020. Comparison of indoor air temperature and operative temperature driven HVAC systems by means of thermal comfort and energy consumption. Mugla Journal of Science and Technology. Volume 6, pp. 156-163. https://doi.org/ 10.22531/muglajsci.679256