The overall thermal performance of a solar water heating (SWH) system is significantly affected by the mismatch between the temporal distribution of solar radiation and the heating load. Therefore, a favorable correlation between the collector and storage size should be generated based on the dynamic characteristics of the system. This study focuses on the optimal matching of solar collector area with storage volume for an SWH system (with short-term heat storage capability) for a space heating application. A simplified model of an SWH system based on hourly energy flow is established. System control strategy is integrated into the model in a simple manner without sacrificing computing speed. Based on this model, the combined effect of collector area and storage volume on system thermal performance and economy is analyzed, and a simple procedure for determining the optimal system size is illustrated. A case study showed that for an SWH system utilized for space heating application, the optimized ratio between storage volume and collector area is dependent on the total collector area of the system, and is dominated by the requirement of overheating prevention. The minimum storage volume for a specific collector area that can prevent the storage tank from being overheated can be adopted as the optimum storage volume for that collector area. The optimum ratio between storage volume and collector area increases as the collector area increases. Therefore, a trade-off between heat collection and heat loss has to be made while attempting to increase solar fraction by improving collector area.

Person to person droplets/particles or contaminant cross transmission is an important issue in ventilated environment, especially in the unidirectional ventilated protective isolation room (UVPIR) where the patient’s immune system is extremely low and easily infected. We simulated the dispersion process of the droplets with initial diameter of 100 μm, 10 μm and gaseous contaminant in unidirectional ventilated protective isolation room and studied the droplets dispersion and cross transmission with different sizes. The droplets with initial size of 100 μm settle out of the coughing jet quickly after coming out from mouth and cannot be carried by the coughing jet to the human thermal plume affecting (HTPA) zone of the susceptible manikin. Hence, the larger droplets disperse mainly in the HTPA zone of the source manikin, and the droplets cross transmission between source manikin and susceptible manikin is very small. The droplets with initial size of 10 μm and gaseous contaminant have similar dispersion but different removal process in the UVPIR. Part of the droplets with initial size of 10 μm and gaseous contaminant that are carried by the higher velocity coughing airflow can enter the HTPA zone of the susceptible manikin and disperse around it. The other part cannot spread to the susceptible manikin’s HTPA zone and mainly spread in the source manikin’s HTPA zone. The results from this study would be useful for UVPIR usage and operation in order to minimize the risk of cross infection.

Infection is a major cause of death for the immunocompromised patients whose immune mechanisms are deficient. The most effective way of protecting these patients is the total environment protection such as protective isolation room (PIR). Unidirectional airflow ventilation is usually used in PIR. The supply air velocity in PIR can affect not only the cleanliness level of the room and total environment protection effects to the patients, but also the energy consumption and initial equipment investment of the room. Computational fluid dynamics (CFD) program is used to simulate the airflow field and the concentration distribution of the particles from human body and breathing. Three scenarios when the manikin is standing, sitting and lying are investigated in this study. The intensities of supply airflow with different velocities and the upward airflow induced by thermal plume with different postures are compared. The qualitative and quantitative analysis of the simulation results show that the required supply air velocity to control the thermal plume and particle dispersion from human body and breathing is at least 0.25 m/s when the manikin is standing or sitting, and 0.2 m/s when the manikin is lying.

High volatile organic compound (VOC) concentrations following building decoration have been observed frequently. In reality, however, residents do not know the indoor VOC concentration levels until the buildings are tested, which seldom provides a preventive measure. While several indoor air quality (IAQ) simulation programs have been developed to predict indoor contaminant levels, case studies in the literature are scarce regarding the predictability of indoor VOC concentrations as well as how such predictions could be performed in real buildings. In this paper, we intended to conduct a proof-of-concept study whether simulations can help to reveal some of the key features of VOC concentrations during indoor decoration process. We conducted a case study, simulated and measured the VOC concentrations of a residential unit during the room decoration process. Results show that while certain agreement was achieved between the measurement and simulation, application of IAQ models to real buildings is challenging under the best of circumstances—single zone spaces with very few emission materials inside.

Ventilation is a main method to control the contaminant dispersion within clean wards. In this paper, we investigated the effects of various ventilation designs of the bathroom in an ISO Class 5 clean ward. Specifically, the contaminant dispersion and particle concentrations corresponding to three different ventilation design schemes were characterized and compared using computational fluid dynamics (CFD) analysis. For each design, we examined airflow and particle concentrations for contaminant sources located at two places (i.e., at the toilet seat and on the floor), respectively. Field test was conducted to compare the measured and simulated air velocities and particle concentrations in a hospital clean ward. The implemented CFD modeling of ventilation effects of various designs in this study has proven to accurately characterize airflow and contaminant control in the ventilated space, and has led to optimizing ventilation for the bathroom in an ISO Class 5 clean ward.