Original Research

Optimization of window opening, its position and heat source position to obtain maximum air exchange efficiency and heat transfer for a generic cross-ventilated room

Abstract

Introduction: Today, the natural ventilation is emphasized to minimize the energy consumption. It also helps to decrease interior temperatures and maintain internal humidity. In this work, the effect of the rear window opening (factor-1), its position (factor-2) and also the effect of the position of a heat source (factor-3) on Air Exchange Efficiency (AEE) and Heat Source Surface Temperature (HSST) is evaluated.
Materials and methods: The Taguchi Design of Experiment (DOE) is applied to shortlist nine simulations with different combinations of the levels for three factors. Then Computational Fluid Dynamics (CFD) simulations were performed and the responses (AEE & HSST) were recorded. The Signal-toNoise (S/N) ratio values are evaluated separately for the responses and the rank table is prepared to see the impact of various factors for the best response value. Analysis of Variance (ANOVA) analysis is performed to evaluate the impact percentage of the factors to obtain the best responses.
Results: From the mean S/N plots, the best and the worst combinations of levels of the factors for both responses are identified and then simulated. From the study, it is observed that the rear window opening and the window position has the highest and the lowest impact respectively to obtain the highest AEE. Similarly, the window position and the window opening have almost equal impact on lowering the HSST.
Conclusion: The study concludes that proper positioning of window and its opening can be evaluated to get the best AEE and to transfer the maximum heat from the heat source in the room.

1. Yin W, Zhang G, Yang W, Wang X. Natural ventilation potential model considering solution multiplicity, window opening percentage, air velocity and humidity in China. J Building Environment. 2010;45(2):338-44.
2. Costanzo V, Yao R, Xu T, Xiong J, Zhang Q, Li B. Natural ventilation potential for residential buildings in a densely built-up and highly polluted environment. A case study. J Renewable Energy. 2019;138:340-53.
3. Escombe AR, Oeser CC, Gilman RH, Navincopa M, Ticona E, Pan W, et al. Natural ventilation for the prevention of airborne contagion. J PLoS medicine. 2007;4(2):e68.
4. Kalia S, Mishra N, Ghose P. Indoor air quality assessment of an existing apartment located in Indian tropical city, Bhubaneswar. J Journal of Air Pollution Health. 2024.
5. Zhai ZJ, Johnson M-H, Krarti M. Assessment of natural and hybrid ventilation models in whole-building energy simulations. J Energy Buildings. 2011;43(9):2251-61.
6. Szokolay S, Koenigsberger O. Manual of tropical housing and building. 1973.
7. Xie H, Zhang TJJoAP, Health. Impact of roof shape on indoor gaseous pollutant level for natural ventilation buildings in a street canyon: Numerical simulation. 2023;8(3):339-60.
8. Wu J, Long F, Deng B, Health. Numerical simulation of VOCs emission from building materials: A comparison of different material shapes. J Journal of Air Pollution Health. 2022;7(2):109-20.
9. Pathirana S, Rodrigo A, Halwatura R. Effect of building shape, orientation, window to wall ratios and zones on energy efficiency and thermal comfort of naturally ventilated houses in tropical climate. J International Journal of Energy Environmental Engineering. 2019;10(1):107-20.
10. Aldawoud A. Windows design for maximum cross-ventilation in buildings. J Advances in building energy research. 2017;11(1):67-86.
11. Sacht H, Lukiantchuki MA. Windows size and the performance of natural ventilation. J Procedia Engineering. 2017;196:972-9.
12. Abdullah HK, Alibaba HZ. Window design of naturally ventilated offices in the mediterranean climate in terms of CO2 and thermal comfort performance. J Sustainability. 2020;12(2):473.
13. Kalia S, Mishra N, Ghose P. Impact of Internal Wall Barriers on Airflow Pattern in Natural Cross-Ventilation of the Common Houses in Bhubaneswar City, India. J Jordan Journal of Mechanical Industrial Engineering. 2023;17(1).
14. Zhang Z-Y, Yin W, Wang T-W, O’Donovan A. Effect of cross-ventilation channel in classrooms with interior corridor estimated by computational fluid dynamics. J Indoor Built Environment. 2022;31(4):1047-65.
15. Yuce BE, Nielsen PV, Wargocki P. The use of Taguchi, ANOVA, and GRA methods to optimize CFD analyses of ventilation performance in buildings. J Building Environment. 2022;225:109587.
16. Yin X, Muhieldeen MW, Razman R, Ee JYC. Multi-objective optimization of window configuration and furniture arrangement for the natural ventilation of office buildings using Taguchi-based grey relational analysis. J Energy Buildings. 2023;296:113385.
17. Lenin V, Sivalakshmi S, Raja M. Optimization of window type and vent parameters on single-sided natural ventilation buildings. J Journal of Thermal Analysis Calorimetry. 2019;136(1):367-79.
18. Chandra AS, Reddy PN, Harish R. Natural ventilation in a lege space with heat source: CFD visualization and taguchi optimization. J Journal of Thermal Engineering. 2022;8(5):642-55.
19. Buratti C, Mariani R, Moretti E. Mean age of air in a naturally ventilated office: Experimental data and simulations. J Energy Buildings. 2011;43(8):2021-7.
20. Hang J, Sandberg M, Li Y. Age of air and air exchange efficiency in idealized city models. J Building Environment. 2009;44(8):1714-23.
21. Hormigos-Jimenez S, Padilla-Marcos MA, Meiss A, Gonzalez-Lezcano RA, Feijó-MuÑoz J. Experimental validation of the age-of-the-air CFD analysis: A case study. J Science Technology for the Built Environment. 2018;24(9):994-1003.
22. Ning M, Mengjie S, Mingyin C, Dongmei P, Shiming D. Computational fluid dynamics (CFD) modelling of air flow field, mean age of air and CO2 distributions inside a bedroom with different heights of conditioned air supply outlet. J Applied energy. 2016;164:906-15.
23. Yazarlou T, Barzkar E. Louver and window position effect on cross-ventilation in a generic isolated building: A CFD approach. J Indoor Built Environment. 2022;31(6):1511-29.
24. Bademlioglu A, Canbolat A, Yamankaradeniz N, Kaynakli O. Investigation of parameters affecting Organic Rankine Cycle efficiency by using Taguchi and ANOVA methods. J Applied Thermal Engineering. 2018;145:221-8.
Files
IssueVol 10 No 3 (2025): Summer 2025 QRcode
SectionOriginal Research
DOI https://doi.org/10.18502/japh.v10i3.19593
Keywords
Ventilation; Computational fluid dynamics (CFD); Air exchange efficiency; Taguchi; Analysis of variance
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
1.
Kalia S, Mishra N, Ghose P, Mishra VK. Optimization of window opening, its position and heat source position to obtain maximum air exchange efficiency and heat transfer for a generic cross-ventilated room. JAPH. 2025;10(3):311-328.