A state-space method for real-time transient simulation of indoor airflow. (December 2017)

• Record Type: Journal Article
• Authors: Wang, Qiujian; Pan, Yiqun; Zhu, Mingya; Huang, Zhizhong; Tian, Wei; Zuo, Wangda; Han, Xu; Xu, Peng
• Is Part Of: Building and environment. Volume 126(2017)
• Page Start: 184
• Page End: 194
• Publication Date: 2017-12
• Subjects: CFD -- FFD -- State-space fluid dynamics (SFD) -- Transient air flow simulation -- Real-time simulation; Buildings -- Environmental engineering -- Periodicals; Building -- Research -- Periodicals; Constructions -- Technique de l'environnement -- Périodiques; Electronic journals; 696
• DOI: 10.1016/j.buildenv.2017.09.032
• Languages: English
• ISSNs: 0360-1323

Abstract

Abstract: Inhomogeneous airflow distribution is common in air-conditioned rooms, especially the large open spaces. To evaluate the thermal comfort of such space, or the control performance of the Heating, Ventilation, and Air Conditioning (HVAC) systems in an efficient way, one will need a fast prediction method to simulate the airflow and temperature distribution. This paper proposes a discrete state-space method, called state-space fluid dynamics (SFD), for the fast indoor airflow simulation. To handle time-varying velocity and temperature field, SFD converts all the governing equations of fluid dynamics into the form of a state-space model. Four typical cases are selected to evaluate both the accuracy and speed of SFD, compared with fast fluid dynamics (FFD), which is another fast airflow simulation program. Results show that SFD is capable of achieving faster-than-real-time airflow simulation with an accuracy similar to FFD. The computing time of SFD is longer than FFD when the time step size is the same. However, SFD can generally produce better results than FFD when the time step size is larger, which allows SFD run faster than FFD. Highlights: SFD can handle the time-varying airflow field by converting all the governing equations into state-space model. For studied cases, the current SFD code can achieve real-time or faster-than-real-time simulation. SFD can obtain stable numerical and reasonably accurate solutions when using relatively large time step size.