Transient numerical study on injecting PCM in buildings along with extra comfort ventilation: Use of artificial neural network to decline energy utilization. (October 2022)

• Record Type: Journal Article
• Authors: Alnaqi, Abdulwahab A.; Alsarraf, Jalal; Al-Rashed, Abdullah A.A.A.
• Is Part Of: Engineering analysis with boundary elements. Volume 143(2022)
• Page Start: 559
• Page End: 567
• Publication Date: 2022-10
• Subjects: PCM -- Ventilation -- Building -- Energy consumption -- ANN -- Photovoltaic cells; Boundary element methods -- Periodicals; Engineering mathematics -- Periodicals; Équations intégrales de frontière, Méthodes des -- Périodiques; Mathématiques de l'ingénieur -- Périodiques; Boundary element methods; Engineering mathematics; Periodicals; 620.00151
• DOI: 10.1016/j.enganabound.2022.07.005
• Languages: English
• ISSNs: 0955-7997

Abstract

Abstract: Strict standards in medical complexes forced the air conditioning designers to approve a system that adjusts temperature and CO2 levels. In this study, medical complex energy analysis was discussed by introducing two cases, i.e., internal and external improvers. Using numerical approaches the energy analysis was performed and consequently using CFD-based approaches, the internal temoerature distribution was simulated. Monthly analysis showed that PCM has a positive effect each month. The heating zone and cooling zone for the medical complex with PCM were 15751 and 129923 kBtu per hour less than the normal medical complex. In the external improver section, a program was developed to adjust the building's ventilation in three scenarios: part-load, full-load, and extra load. Although in the first and second scenarios, the goal of ventilation was to create comfortable conditions, in the third scenario, the goal of extra ventilation was to reduce energy consumption. Excessive ventilation kept the room in comfortable conditions by distributing fresh air at the desired temperature. Owing to injecting extra ventilated fresh air, the changes in the heating zone were not significant while the cooling zone parameter decreased by 2639 kBtu per hour. To forecast the thermal behavior of the medical complex with PCM, the neural network was implemented.