A systematic approach to numerical analysis and validation for industrial oven design and optimization – A case study

Öz

The findings of this research not only provide valuable insights into industrial oven design but also demonstrate the broader importance of adopting systematic approaches and incorporating numerical analysis techniques to achieve clean energy goals. By leveraging such approaches across various industrial sectors, we can pave the way for a greener future, where energy efficiency, environmental sustainability, and economic growth can harmoniously coexist. In today's rapidly evolving world, where the need for sustainable practices and clean energy solutions is more critical than ever, research plays a pivotal role in driving innovation and addressing environmental challenges. The study presented in this article aligns with this overarching goal by focusing on the optimization of industrial oven design, aiming to achieve energy efficiency and high-quality product outcomes. Efficient oven design and optimization hold significant implications for energy conservation, reducing greenhouse gas emissions, and minimizing environmental footprints. By precisely controlling heat distribution and velocity within industrial ovens, such as the one investigated in this study, resource consumption can be minimized, resulting in reduced energy usage and improved operational efficiency. Moreover, the enhanced uniformity in temperature and airflow distribution ensures optimal product quality, reducing waste and promoting sustainable production practices. A systematic approach to numerical analysis and validation for industrial oven design and optimization is developed. Computational fluid dynamics (CFD) and the Taguchi design of experiment methods were employed to determine the influential design variables. The 3D CFD model was then compared with experimental results to validate its accuracy. An experimental oven design was developed based on optimal signal-to-noise (S/N) ratios, and the numerical findings were corroborated through experimental measurements, demonstrating a strong agreement. The proposed approach, encompassing the design, manufacturing, and analysis stages, can be applied to diverse industrial oven designs.

Anahtar Kelimeler

• Taguchi DOE
• design of experiments
• orthogonal arrays
• computational fluid dynamics (CFD)
• optimization
• furnace
• forced convection
• heat transfer
• optimization
• CFD

Proje Numarası

7160496

Endüstriyel fırın tasarımı ve optimizasyonuna yönelik sayısal analiz ve doğrulamaya sistematik bir yaklaşım – Bir örnek olay çalışması

Öz

Bu araştırmanın bulguları yalnızca endüstriyel fırın tasarımına dair değerli bilgiler sağlamakla kalmıyor, aynı zamanda temiz enerji hedeflerine ulaşmak için sistematik yaklaşımları benimsemenin ve sayısal analiz tekniklerini birleştirmenin büyük önemini de gösteriyor. Çeşitli endüstriyel sektörlerde bu tür yaklaşımlardan yararlanarak enerji verimliliğinin, çevresel sürdürülebilirliğin ve ekonomik büyümenin uyumlu bir şekilde bir arada var olabileceği daha yeşil bir geleceğin yolu açılabilir. Verimli fırın tasarımı ve en iyileştirilmesi, enerji tasarrufu, sera gazı emisyonlarının azaltılması ve çevresel ayak izlerinin en aza indirilmesi gibi önemli etkilere sahiptir. Bu çalışmada endüstriyel fırın tasarımı ve en iyileştirilmesine yönelik sayısal analiz ve doğrulamaya yönelik sistematik bir yaklaşım geliştirilmiştir. Etkili tasarım değişkenlerini belirlemek için hesaplamalı akışkanlar dinamiği (HAD) ve Taguchi deney tasarım yöntemleri kullanılmıştır. 3 boyutlu HAD modellerinden çıkan sonuçlara bağlı olarak, sinyal-gürültü (S/N) oranları belirlenmiş, en yüksek verimlilik için, tasarım değişkenlerinin değerleri tespit edilmiş ve bu değerlere bağlı olarak deneysel bir fırın tasarımı geliştirilmiştir. HAD analizlerinden elde edilen sayısal değerler ile deneysel ölçümlerden elde edilen değerler arasında güçlü bir uyum görülmüştür. Tasarım, üretim ve analiz aşamalarını kapsayan önerilen yaklaşım, çeşitli endüstriyel fırın tasarımlarına uygulanabilir.

Anahtar Kelimeler

• Taguchi DOE
• deney tasarımı
• ortogonal diziler
• hesaplamalı akışkanlar dinamiği (HAD)
• optimizasyon
• fırın
• zorlanmış konveksiyon
• ısı transferi
• en iyileştirme
• CFD

Destekleyen Kurum

The Scientific and Technological Research Council of Turkey (TUBİTAK)

Proje Numarası

7160496

Kaynakça

1. Amadane, Y., Mounir, H., Marjani, A., Ettouhami, M., & Atifi, A. (n.d.). Using CFD Simulation and Taguchi Approach to Optimize the Parameters Influencing the Performance of PEM Fuel Cell with the Serpentine Flow Field. Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2019). AI2SD 2019. Lecture Notes in Electrical Engineering(624). https://doi.org/10.1007/978-3-030-36475-5_29
2. Aydın, A., Yaşar, H., Engin, T., & Büyükkaya, E. (2022). Optimization and CFD analysis of a shell-and-tube heat exchanger with a multi segmental baffle. Thermal Science, 1(26), pp. 1-12. https://doi.org/10.2298/TSCI200111293A
3. Biçer, N., Engin, T., Yasar, H., Büyükkaya, E., Aydın, A., & Topuz, A. (2020). Design optimization of a shell-and-tube heat exchanger with novel three-zonal baffle by using CFD and taguchi method. International Journal of Thermal Sciences, 155. https://doi.org/10.1016/j.ijthermalsci.2020.106417.
4. Boulet, M., Marcos, B., Dostie, M., & Moresoli, C. (2010). CFD modeling of heat transfer and flow field in a bakery pilot oven. Journal of Food Engineering, 97(3), pp. 393-402. https://doi.org/10.1016/j.jfoodeng.2009.10.034
5. Chandra, A. S., Reddy, P. N., & R, H. (2022). ArticleNatural ventilation in a lege space with heat source: CFD visualization and taguchi optimization. Journal of Thermal Engineering(8), pp. 642-655. https://doi.org/10.18186/thermal.1190545
6. Demir, U., & Aküner, M. C. (2018). Elektrikli bir araç için tekerlek içi asenkron motorun tasarım ve optimizasyonu. Journal of the Faculty of Engineering and Architecture of Gazi University, 33(4), pp. 1517-1530. https://doi.org/10.17341/gazimmfd.416448
7. Durbin, P. (1996). On the k-3 stagnation point anomaly. International Journal of Heat and Fluid Flow, 17(1), pp. 89-90. https://doi.org/10.1016/0142-727X(95)00073-Y
8. Fahey, M., Wakes, S. J., & Shaw, C. T. (2008). Use of computational fluid dynamics in domestic oven design. Int. Jnl. of Multiphysics, 2(1). https://doi.org/10.1260/175095408784300216

9. İç, Y. T., & Yıldırım, S. (2012). Çok kriterli karar verme yöntemleriyle birlikte taguchi yöntemini kullanarak bir ürünün tasariminin geliştirilmesi. Journal of the Faculty of Engineering and Architecture of Gazi University, 27(2), pp. 447-458.
10. Inc, A. (2009). ANSYS Fluent User Guide Release 12. Ansys Inc.
11. Inc, A. (2011). ANSYS CFX-Solver Theory Guide, Release 14. Canonsburg, PA: ANSYS Inc.
12. Inc., A. (2011). ANSYS CFX-Solver Modeling Guide, Rel. 14. 452-453.
13. Jegede, F., & Polley, G. (1992). Optimum Heat-Exchanger Design. Chemical Engineerıng Research & Design(70), pp. 133-141.
14. Kahraman, F., & Sugözü, B. (2019). An integrated approach based on the taguchi method and response surface methodology to optimize parameter design of asbestos-free brake pad material. Turkish Journal of Engineering, 3(3), pp. 127-132. https://doi.org/10.31127/tuje.479458
15. Kokolj, U., Škerget, L., & Ravnik, J. (2017). A numerical model of the shortbread baking process in a forced convection oven. Applied Thermal Engineering, 111, pp. 1304-1311. https://doi.org/10.1016/j.applthermaleng.2016.10.031.
16. Kokolj, U., Škerget, L., & Ravnik, J. (2017). The Validation of Numerical Methodology for Oven Design Optimization Using Numerical Simulations and Baking Experiments. Strojniški vestnik - Journal of Mechanical Engineering, 63(4), pp. 215-224. https://doi.org/10.5545/sv-jme.2016.4089
17. Marvin, J. G. (1988). Accuracy Requirements and Benchmark Experiments for CFD Validation. National Aeronautics and Space Administration.
18. Morris, A. S., & Langari, R. (2016). Measurement and Instrumentation (Second Edition). Elsevier Inc. https://doi.org/10.1016/C2013-0-15387-1
19. Norton, T., & Da-WenSun. (2006). Computational fluid dynamics (CFD) – an effective and efficient design and analysis tool for the food industry: A review. Trends in Food Science & Technology, 17(11), 600-620. https://doi.org/10.1016/j.tifs.2006.05.004
20. Obidowski, D., Stajuda, M., & Sobczak, K. (2021). Efficient Multi-Objective CFD-Based Optimization Method for a Scroll Distributor. Energies, 14(2-377). https://doi.org/10.3390/en14020377
21. Özer, M., Altınkaynak, A., Temiz, V., Mutlu, T., Dışpınar, T., Özgen, A. K., & Yücel, M. (2016). Önden yüklemeli bir çamaşır makinesinin sonlu elemanlar yöntemiyle dinamik olarak modellenmesi. Journal of the Faculty of Engineering and Architecture of Gazi University, 31(3), pp. 773-780. https://doi.org/10.17341/gummfd.78923
22. Rek, Z., Rudolf, M., & Zun, I. (2012). Application of CFD Simulation in the Development of a New Generation Heating Oven. Strojniški vestnik - Journal of Mechanical Engineering(58), pp. 134-144. https://doi.org/10.5545/sv-jme.2011.163
23. Shimpy, S., Kumar, M., & Kumar, A. (2024). Design and optimization of a domestic solar dryer: an analytical approach. Engineering Computations, 41(4), pp. 947-965. https://doi.org/10.1108/EC-12-2023-0916
24. Smolka, J., Bulinski, Z., & Nowak, A. J. (2013). The experimental validation of a CFD model for a heating oven with natural air circulation. Applied Thermal Engineering, pp. 387-398. http://dx.doi.org/10.1016/j.applthermaleng.2013.02.014
25. Stojanović, B., Babić, M., Veličković, S., & Blagojević, J. (2015). Optimization Of Wear Behaviour In Aluminium Hybrid Composites Using Taguchi Method. 14th International Conference on Tribology, SERBIATRIB ‘15. Belgrade, Serbia.
26. Tambolkar, P., Ponkshe, A., Mulay, V., & Bewoor, A. (2020). Use of Taguchi DOE for CFD Simulation to maximize the Reusability of Working Fluids of Centrifugal Filter. Procedia Manufacturing, 46, pp. 608-614. https://doi.org/10.1016/j.promfg.2020.03.087
27. Tank, A., Chhanwal, N., Indrani, D., & Anandharamakrishnan, C. (2014). Computational fluid dynamics modeling of bun baking process under different oven load conditions. J Food Sci Technol, 51(9), pp. 2030-2037. https://doi.org/10.1007/s13197-012-0736-6
28. Türkan, B. (2024). Elektrikli araçlarda optimum soğutucu tasarımı için TRIZ algoritmasının uygulanması ve Taguchi analizi. Journal of the Faculty of Engineering and Architecture of Gazi University, 39(1), pp. 521-534. https://doi.org/10.17341/gazimmfd.1072512
29. Ünverdi, M., & Küçük, H. (2019). Taguchi yöntemi ve hesaplamalı akışkanlar dinamiği kullanılarak tasarlanan levhalı ısı değiştiricilerin performanslarının karşılaştırılması. Pamukkale Univ Muh Bilim Derg, 25(4), pp. 373-386. https://doi.org/10.5505/pajes.2018.35493
30. Vizguerra-Morales, P., Va´zquez-Castillo, J. A., Romero-Toledo, R., Aguilera-Alvarado, A. F., & Ponce-Ortega, J. M. (2016). Optimization and CFD modeling of an improved rustic oven for producing bricks. Clean Techn Environ Policy(18), pp. 1599-1609. https://doi.org/10.1007/s10098-016-1139-6
31. Yia, Y., Salonitisa, K., Tsoutsanisb, P., Litos, L., & Patsavelas, J. (2017). Improving the curing cycle time through the numerical modeling of air flow in industrial continuous convection ovens. The 50th CIRP Conference on Manufacturing Systems. 63, pp. 499-504. Procedia CIRP. https://doi.org/10.1016/j.procir.2017.03.167
32. Yuce, B. E., Nielsen, P. V., & Wargocki, P. (2022). The use of Taguchi, ANOVA, and GRA methods to optimize CFD analyses of ventilation performance in buildings. Building and Environment(225). https://doi.org/10.1016/j.buildenv.2022.109587