Design optimization for ventilation shafts of naturally-ventilated underground shelters for improvement of ventilation rate and thermal comfort. (January 2018)

• Record Type: Journal Article
• Authors: Mukhtar, A.; Ng, K.C.; Yusoff, M.Z.
• Is Part Of: Renewable energy. Volume 115(2018)
• Page Start: 183
• Page End: 198
• Publication Date: 2018-01
• Subjects: Computational fluid dynamics (CFD) -- Design of experiments (DOE) -- Response surface methodology (RSM) -- Desirability function -- Ventilation rate -- Thermal comfort index; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2017.08.051
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: A good ventilation system is essential for an underground shelter to provide a comfortable environment with better indoor air quality. Ventilation shafts are widely used for ventilation purpose in an underground shelter. In the current work, the position of the ventilation shaft is optimized by employing the Response Surface Methodology (RSM). Two RSMs are constructed. The first RSM is constructed by 32 CFD models via Fractional Factorial Design (FFD) and the second model is constructed by 53 CFD models via Central Composite Rotatable Design (CCRD). The first and the second models are subsequently analysed by using the linear and quadratic models, respectively. The result indicates that both models lead to similar predictions on the inputs (factors) that strongly affect the response. Moreover, the response surface values agree well with the CFD values. Based on desirability functions, the optimized design improves the ventilation system by 24.5% as compared to the actual design. Also, the optimized design meets the comfort temperature and design criteria recommended for a naturally-ventilated underground shelter. Overall, this study finds that statistical analysis is a useful tool for the improvements of ventilation rate and thermal comfort. Highlights: Determine the positions of the ventilation shaft to have adequate ventilation rate is a crucial task during the design stage. Fractional Factorial Design and Central Composite Rotatable Design agreed on the factors that are strongly affected the response (output). The function of ventilation rate is obtained by least square regression analysis. Optimized design improves 24.5% of the output response compare to the actual design. Thermal Comfort Index was driven by the modified of de Dear and Brager adaptive comfort standard.