Development of a second-order dynamic model for quantifying impact of thermal mass on indoor thermal environment. (October 2021)

• Record Type: Journal Article
• Authors: Lu, Yihang; Yang, Zili; Yu, Jia; Chen, Bin; Zhong, Ke
• Is Part Of: Journal of building engineering. Volume 42(2021)
• Publication Date: 2021-10
• Subjects: Thermal mass -- Effective thermal capacity -- Temperature elastic coefficient -- Database models -- Indoor thermal condition; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2021.102496
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Indoor thermal environment can be significantly influenced by thermal mass, which is not considered quantitatively in building thermal design due to the lack of a simple and accurate calculation model. For this reason, a temperature elastic coefficient (TEC) is proposed to characterize the dynamic heat transfer between inner surfaces of external walls (ISEW) and indoor air, and an effective thermal capacity (ETC) is used to characterize thermal mass. A second-order dynamic model is thus developed to efficiently evaluate the impact of thermal mass on indoor thermal environment by employing the TEC and ETC. The results show that both the TEC and the ETC are affected by the insulation position, wall thermal resistance, air change rate and window-wall ratio (WWR), but independent of the outdoor air temperature, indoor heat source intensity and solar radiation. Furthermore, the combination of the second-order dynamic model and the database models of ETC and the TEC are determined by using multiple nonlinear regression analysis, and can help policy makers and building thermal designers to estimate the impact of thermal mass on the indoor thermal environment quickly and accurately. Graphical abstract: Image 1 Highlights: Dynamic heat transfer is characterized by temperature elastic coefficient (TEC). A dynamic model is developed by using TEC and effective thermal capacity (ETC). The model can evaluate the impact of thermal mass on indoor thermal environment. Factors influencing the ETC and the TEC are analyzed and clarified. Database models for the ETC and TEC are obtained by using statistical analysis methods.