According to the analysis in the previous sections, the following parameters are most important in design of the displacement system:
• Supply airflow rate and temperature • Air temperature at floor level • Vertical temperature gradient • Maximum air velocity at floor level
• Stratification height (lower zone height) or contaminant concentration gradi- ent
• Energy consumption
• First costs and maintenance costs
The most complete design guidelines available are those developed by Skistad (1994). He used a five-step approach:
1. Determine the required airflow rate for removal of surplus heat based on the cool- ing load and the air temperature difference between supply and exhaust openings. 2. Find the required airflow rate for removal of pollutants according to ventilation
standards.
3. Choose the larger of the two flow rates determined at Steps 1 and 2 as the venti- lation rate.
4. Determine supply air temperature under assumptions of θf = 0.5 and constant vertical temperature gradient.
5. Choose supply diffusers according to the data provided by manufacturers in order to avoid draft.
A more recent version of the deign guide can be found from the REHVA guide- book (REHVA 2002).
Despite the simple design guidelines, there are problems. Figure 2.2 shows that θf varies from 0.2 to 0.7, and the vertical temperature gradient is not a constant. If
the actual ∆Tf < 0.5 ∆Te, the vertical temperature gradient will be larger than the expected gradient. The design guidelines assume ∆Tf = 0.5 ∆Te. If the actual ∆Tf > 0.5 ∆Te, the selected V based on ∆Tf = 0.5 ∆Te will be larger than needed.
A different approach proposed by Chen et al. (1991) used a design atlas. The atlas, based on experimental and computational results, contains detailed informa- tion on indoor airflow, indoor air quality, and thermal comfort for various configu- rations of spaces. Unfortunately, the atlas at present does not cover a wide range of spaces and conditions.
It seems necessary to improve current available design guidelines for the displacement ventilation system to ensure good indoor air quality and thermal comfort in the space.
From the above review and a survey among architects and energy consumption in the U.S. (Chen et al. 1999), we may conclude that design guidelines available in the literature cannot be used with confidence. Many assumptions need further clar- ification so that designers can use the design guidelines with confidence. U.S. build- ings, especially perimeter zones of such buildings, have a high cooling load. Design of displacement ventilation must address these zones. The special features in U.S. buildings considered in this book include offices, classrooms, and industrial work- shops.
For these types of spaces, this book will present experimental tests used to obtain reliable data on the performances of displacement ventilation. A CFD program was validated against these data. By using the program, this book shows how to conduct numerical simulations of a large number of cases of displacement ventilation in the three types of spaces and how to establish a database on the perfor- mances. Based on the database, this book further presents a model for prediction of temperature difference between head and foot levels and a model for ventilation effectiveness for design purpose. The book will also compare the energy and first costs of the displacement ventilation system with a mixing ventilation system. Finally, the book presents design guidelines for the displacement ventilation system developed from the study. These will be discussed in the following chapters.
Experimental Study and
Validation of CFD Program
Displacement ventilation may provide better indoor air quality and save energy, but there is a question of the usefulness of this technology in U.S. buildings with higher cooling requirements. A first step in preparing a design guideline is careful study of displacement ventilation for several typical U.S. buildings.
Two main approaches are available for the study of airflow and pollutant trans- port in buildings: experimental investigation and computer simulation. Experimen- tal investigation, although it is reliable, is very expensive and time consuming. Computer simulation is inexpensive, but it may not be reliable. For evaluation of the indoor environment provided by displacement ventilation, the computational fluid dynamics (CFD) technique seems most appropriate, if it is validated by experimental data. This combined approach was used to generate the results presented in this book.
Many experimental data are available in the literature, but very few of them can be used for the validation. Experimental data for CFD validation must contain detailed information of flow and thermal boundary conditions as well as flow and thermal parameters measured in the space. The data must also include an error anal- ysis. Unfortunately, not many of the experimental data include such detailed infor- mation. Popular data for validating room airflow are from Cheesewright et al. (1986) and Nielsen et al. (1978). Cheesewright's data are for natural convection and Nielsen's data are for forced convection. However, it is still not certain that a CFD program validated by their data can be used for normal room airflow with mixed convection (a combination of natural and forced convection).
This chapter presents detailed experimental data for displacement ventilation, which is mixed convection and represents ventilation reality in many buildings. The experimental data are used to validate a CFD program with a suitable turbulence model. There are many turbulence models available. The “standard” k-ε model (Launder and Spalding 1974) is probably most widely used in engineering calcula- tions due to its relative simplicity. However, the model sometimes provides poor results for indoor airflow. Many modifications have been applied to the standard
model. However, the modified models do not have a general applicability for indoor airflow. Chen (1995 and 1996) calculated the various indoor flows with eight differ- ent turbulence models. His study concluded that the re-normalization group (RNG) k-ε model (Yokhot et al. 1992) is the best among the eddy-viscosity models tested. This chapter will also compare this model’s prediction for displacement ventilation in a room with the experimental data.
3.1 EXPERIMENTAL FACILITY