Simulation of Contaminant Distributions in a JFL Restroom

Simulation of Contaminant Distributions in a JFL Restroom: Modeling Stephanie Philippe, Todd Owen, Dr. Hector Medina School of Engineering Abstract Methods Background: Indoor Air Quality (IAQ) is defined as the air quality within buildings, especially related to the health and comfort of occupants. Managing the distribution and removal of pollutants and contaminants in public restrooms is a major area of concern, since they contain multiple sources of indoor pollutants, including human waste processes. Furthermore, the high traffic use of public restrooms exacerbates the restroom IAQ problem, making it imperative for building engineers to closely monitor contamination levels. Methods: A model of the restroom was created in CONTAM, with appropriate parameters characterizing temperature, contamination sources, ventilation system, etc. A CFD model of the zones was created using CFD 0 Editor. Transient simulations were conducted for both software. Particle distribution were obtained from CFD 0 and contaminant levels from CONTAM. Results: Contaminant levels remained constant in three of the five zones. Stall 2 experienced the largest increase in levels. Stall 1 experienced very slight increases, for some contaminants. Conclusions: There is an accumulation of contaminants in Stall 2, possibly due to the presence of incoming particles on their way to the exhaust vent above Stall 2. The CONTAM floor plan was modeled from building mechanical plans. Openings were placed along the walls corresponding to areas of airflow between zones. Zones were characterized by defining floor area, room temperature, and contaminants present. A simple air-handling system was used to model the restroom’s current ventilation system. Five species of contaminants were used as sources in each zone. After the CONTAM environment was properly defined, a transient airflow and transient contaminant simulation was executed. The results of the multi-zone simulation (i. e. airflows and pressure differences) were exported to CFD 0. A model of the CFD zone was created in the CFD 0 Editor. The location of contaminant sources and airflow inlets were defined. The wall boundaries were also defined for the CFD zones. A transient simulation was conducted using the CFD 0 software. The CFD 0 results were exported again to CONTAM. Using the new distributed results, a second transient simulation was executed in CONTAM. Figure 1. CONTAM floor plan modeled from mechanical plans The restroom was divided into 5 zones: the Main restroom area, Stall 1, Stall 2, Stall 3 and Stall 4. Zone temperature was set to 65°F. Five contaminant species were used: Acetic acid, Ammonia, Butyric acid, Hydrogen sulfide and Propanoic acid. A simple air handling system was used to model the exhaust system used for the restroom. Figure 5. CONTAM transient airflow results through bottom and top gaps of Stall 4 A B C D Figure 2. Graphical display of airflow and pressure differences in the zones Results and/or Conclusion E Figure 6. CONTAM transient results: contamination concentrations in kg contaminant/kg air This chart shows the levels of A) acetic acid B) ammonia C) butyric acid D) hydrogen sulfide and E) propanoic acid in all the zones. The most notable change occurs in Stall 2, in which all contaminant levels increase linearly. Introduction and/or Research Question Heating, ventilation and air conditioning (HVAC) systems provide thermal comfort and fresh air to building occupants. Unfortunately, HVAC systems can consume an average of 39% of a facility’s energy use [1]. While these systems are some of the largest contributors to energy waste in buildings, they also represent a huge potential for energy savings. The need for more energy-efficient solutions for buildings has required a revolution in ventilation strategies. As a result, push for a new generation of smart ventilation systems has developed. Smart ventilation strategies are defined as the use of controls to ventilate a building more when it would provide energy or indoor air quality (IAQ) advantage (or both) and less when it provides a disadvantage [2]. There is a need to develop more energy-efficient smart exhaust systems, especially for restroom and kitchen applications, that will yield more energy savings while maintaining or improving the building’s IAQ. Furthermore, there are currently no definitive IAQ metrics based on contaminant removal to date that can be used for building standards and codes. Instead, ventilation rate requirements are set based occupant comfort, not on health criteria. However, this approach assumes that ventilation is enough to remove both human odors and other contaminants. Currently, the minimum ventilation requirement prescribed by ASHRAE is 10 L/s person to account for both human odors and other contaminants, such as building materials and furnishings. However, no specific justification is stated for this requirement [2]. Thus, health-based metrics would be instrumental in accurately determining ventilation rates are sufficient to reduce contaminant transport and/or disease transmission, especially in restrooms. The goal of this study is to conduct computer simulations using CONTAM and CFD software with geometries and conditions based on a campus restroom facility. The results of these simulations will potentially depict the flow regimes and contamination transport in restroom facilities and provide insights for developing contaminant-based smart ventilation methods. Figure 3. 3 -D model of restroom facility The total floor area is 269 sq. ft. , the ceiling height is 9 ft, and the total zone volume is 2419 cu. ft. Not shown in the model are the supply vent, which is in the ceiling near the entry door, and the exhaust vent, which is located above Stall 2. A B The current contamination levels obtained by CONTAM show a surprising result. In the main restroom area, Stall 3 and Stall 4, contaminant concentrations remain constant. In Stall 1, there is a slight increase in levels for butyric acid, hydrogen sulfide and propanoic acid; however, these levels vary only by an order of tenthousandths. Stall 2 experienced the most increase in contaminant concentrations. All contamination levels increased linearly in Stall 2, despite its proximity to the exhaust vent. Conclusions Based on current findings from CONTAM results, there is an accumulation of contamination in Stall 2. Since this stall is directly beneath the exhaust vent, contaminants from other stalls may be entering Stall 2 on the path toward the exhaust. If the ventilation rate is insufficient to remove contaminant particles, they may be getting trapped in Stall 2, which may explain the build-up. Future Work 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Figure 7. CONTAM transient results: airflow rates through bottom gaps of stall gaps 1. Determine whether restroom ventilation system is sufficiently robust to remove contaminants and maintain restroom IAQ 2. Determine whether the ventilation system is over-performing with respect to standard IAQ levels 3. Determine whether sensors are sufficiently reliable to accurately detect contaminant levels of interest References and/or Acknowledgments Dounis, A. , & Caraiscos, C. (2009). Advanced control systems engineering for energy and comfort management in a building environment - A review. Renewable and Sustainable Energy Reviews, 12461261. Environmental Protection Agency, "Indoor Air Quality (IAQ), " Environmental Protection Agency, 3 October 2019. [Online]. Available: https: //www. epa. gov/indoor-air-quality-iaq/introduction-indoor-air-quality. [Accessed 17 February 2020]. General Services Administration. (n. d. ). System Overview. Retrieved from Sustainable Facilities Tool: https: //sftool. gov/explore/green-building/section/9/hvac/system-overview#facility-wide Guyot, G. , Sherman, M. H. , & Walker, I. S. (2017). Smart ventilation energy and indoor air quality performance in residential buildings: A review. Energy & Buildings, 416 -430. Figure 4. Model of CFD zone in CFD 0 Editor A) CFD zone Stall 2 is shown with small gaps, to aid with CFD calculation. The airflow vector field is shown. B) Stall 2 is shown with true-size larger gaps. Large gaps are difficult for CFD software to solve particle distributions. The purple and gray rectangular boxes represent the location of the toilet in the stall, where contaminant sources are generated. M. M. D. Levitt and M. J. H. Bond Jr. , "Volume, Composition, and Source of Intestinal Gas, " Gastroenterology, vol. 59, no. 6, pp. 921 -929, 1970. Figure 7. CONTAM transient results: Number of particles present in Stall 2 based particle diameter National Institute of Standards and Technology. (2018, June 27). Software CONTAM. Retrieved from NIST: https: //www. nist. gov/services-resources/software/contam Wang, L. , Dols, W. S. , & Chen, Q. (2010). Using CFD Capabilities of CONTAM 3. 0 for Simulating Airflow and Contaminant Transport in and around Buildings. HVAC&R Research, 749 -763.