Research Article | Open Access | Download PDF
Volume 73 | Issue 11 | Year 2025 | Article Id. IJETT-V73I11P126 | DOI : https://doi.org/10.14445/22315381/IJETT-V73I11P126Examining Thermal Properties of Cross-Ventilation in Multizone Buildings: Machine Learning Appraisal of Modelling Methods and Architectural Ingenuities
Soumyajit Koley
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 21 Oct 2025 | 10 Nov 2025 | 17 Nov 2025 | 25 Nov 2025 |
Citation :
Soumyajit Koley, "Examining Thermal Properties of Cross-Ventilation in Multizone Buildings: Machine Learning Appraisal of Modelling Methods and Architectural Ingenuities," International Journal of Engineering Trends and Technology (IJETT), vol. 73, no. 11, pp. 364-416, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I11P126
Abstract
Pervasive challenges within the built environment, namely, escalating carbon dioxide emissions and the imperative for energy conservation, underscore a significant unresolved dilemma in thermal regulation strategies. Although the benefits of passive air movement are empirically substantiated, its systematic integration into contemporary architectural schemas remains infrequent, primarily because of the stringent demands for elevated air exchange rates and an intrinsic institutional bias towards fully mechanised ventilation systems. This comprehensive study addresses this knowledge deficit by rigorously investigating the thermal efficacy of transverse airflow dynamics within heterogeneous spatial configurations, while concurrently deploying advanced machine learning paradigms to refine and validate the associated simulation methodologies. A novel hybrid model synthesising computational fluid dynamics outputs with sophisticated neural network architectures has been developed and validated against extensive field datasets. The findings demonstrate that the optimised analytical methodology yields a prediction accuracy enhancement of 93.72%, facilitating a robust comparative assessment of various architectural design parameters. Critically, the utilisation of cross–flow convection elevates the internal air quality index by 14.88 units and concurrently decreases the necessary auxiliary cooling load by 21.19%, significantly surpassing single–sided aeration techniques across numerous multizone edifices. The resultant methodology provides a definitive blueprint for formulating future integrated environmental conditioning systems, which judiciously balance energy efficiency targets with the critical requirement of superior internal air quality and enhanced occupant thermal amenity.
Keywords
Computational Fluid Dynamics, HVAC systems, Indoor air quality, Thermal comfort, Mechanical ventilation system, Wind–induced ventilation, Radiative cooling, Eddy Diffusion, Building information modelling.
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