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This research paper presents a comprehensive analysis to develop an energy-efficient and net-zero-energy (NZE) model for a proposed hypothetical mosque model located in Riyadh, Saudi Arabia. The study employs a sequential optimization analysis using BEopt software (Building Energy Optimization Tool) to explore various energy conservation measures (ECMs) from three main categories: HVAC, lighting, and building envelope. The ECMs are evaluated based on energy savings and life-cycle cost, with the most cost-effective options selected for the proposed energy-efficient design package. Furthermore, a passive downdraught evaporative cooling (PDEC) system is introduced as a passive cooling strategy to further reduce the cooling energy consumption. Computational fluid dynamics (CFD) analysis is utilized to optimize the airflow around the building and PDEC tower, determining the optimal PDEC dimensions for enhanced ventilation performance. The PDEC system is found to contribute 12% to cooling energy savings, which further enhances the energy efficiency of the proposed mosque. A rooftop solar PV system is incorporated into the optimal energy-efficient design to achieve a NZE mosque. The results demonstrate that the NZE model achieves 80% energy savings, with the remaining 20% offset by the solar PV system. Moreover, life-cycle cost analysis reveals that the NZE model offers the lowest cost, making it the most cost-effective design option. This research provides valuable insights into designing sustainable mosques in hot and dry climates, such as Riyadh, offering a comprehensive solution to significantly reduce energy end-use and promote sustainable building practices. [ABSTRACT FROM AUTHOR]

This research study investigated the transient behavior of the convection–diffusion model for the infiltration heat recovery (IHR) and the influence of the building envelope heat capacity, along with other factors. A transient numerical model was developed and validated to analyze the IHR under various conditions. The results highlight the role of heat capacity, thermal conductivity, wall thickness, airflow rate, airflow direction, and wall porosity on the temperature distribution and the heat recovery factor within the wall. Higher-heat-capacity walls displayed a delayed temperature rise, while low-thermal-conductivity walls reduced the conduction heat transfer and increased the IHR factor. The impact of heat capacity diminished with very low thermal conductivity walls but became evident for high-thermal-conductivity walls, particularly at higher Peclet numbers. Thicker walls enhanced the heat retention and improved the IHR, with a reduced influence of airflow rate. Higher IHR factors were associated with thicker walls, lower Peclet numbers, and higher heat capacities. The analysis also showed that the wall porosity affected the IHR with less significance than the other factors. Incorporating these findings into building energy modeling tools could improve the prediction accuracy of the thermal behavior of buildings. Accordingly, this study contributes to building physics by understanding IHR dynamics and thermal mass interactions, as well as improving building energy modeling accuracy for performance prediction. Future research can explore the impacts of additional factors on IHR and investigate the effect of IHR on the overall energy consumption of buildings. [ABSTRACT FROM AUTHOR]

Ventilation systems are one of the most effective strategies to reduce the risk of viral infection transmission in buildings. However, insufficient ventilation rates in crowded spaces, such as schools, would lead to high risks of infection transmission. On the other hand, excessive ventilation rates might significantly increase cooling energy consumption. Therefore, energy-efficient control methods, such as Demand Control Ventilation systems (DCV), are typically considered to maintain acceptable indoor air quality. However, it is unclear if the DCV-based controls can supply adequate ventilation rates to minimize the probability of infection (POI) in indoor spaces. This paper investigates the benefits of optimized ventilation strategies, including conventional mechanical systems (MV) and DCV, in reducing the POI and cooling energy consumption through a detailed sensitivity analysis. The study also evaluates the impact of the ventilation rate, social distancing, and number of infectors on the performance of the ventilation systems. A coupling approach of a calibrated energy model of a school building in Jeddah, KSA, with a validated Wells–Riley model is implemented. Based on the findings of this study, proper adjustment of the DCV set point is necessary to supply adequate ventilation rates and reduce POI levels. Moreover, optimal values of 2 ACH for ventilation rate and 2 m for social distance are recommended to deliver acceptable POI levels, cooling energy use, and indoor CO2 concentration for the school building. Finally, this study confirms that increasing the ventilation rate is more effective than increasing social distancing in reducing the POI levels. However, this POI reduction is achieved at the cost of a higher increase in the cooling energy. [ABSTRACT FROM AUTHOR]