5 The use of Computational Fluid Dynamics tools for indoor environmental design (p. 119-120)

Qingyan (Yan) Chen and Zhiqiang (John) Zhai

5.1 Introduction

Since human beings spend more than 90% of their time indoors in developed countries, design of indoor environment is crucial to the comfort and welfare of the building occupants. However, this is not an easy task. Woods (1989) reported that about 800,000 to 1,200,000 commercial buildings in the United States containing 30–70 million workers have had problems related to the indoor environment. If the problems can be fixed through technologies, Fisk (2000) estimated that for the United States, the potential annual savings and productivity could be $15–$40 billion from reduced sick building syndrome symptoms, and $20–$200 billion from direct improvements in worker performance that are unrelated to health.

In addition, building safety is a major concern of building occupants. Smoke and fire has claimed hundreds of lives every year in the United States. After the anthrax scare following the September 11, 2001 attacks in the United States, how to protect buildings from terrorist attacks by releasing chemical/biological warfare agents becomes another major issue of building safety concerns. In the past few years, Computational Fluid Dynamics (CFD) has gained popularity as an efficient and useful tool in the design and study of indoor environment and building safety, after having been developed for over a quarter of a century.

The applications of CFD in indoor environment and building safety are very wide, such as some of the recent examples for natural ventilation design (Carriho-da-Graca et al. 2002), prediction of smoke and fire in buildings (Lo et al. 2002; Yeoh et al. 2003), particulate dispersion in indoor environment (Quinn et al. 2001), building element design (Manz 2003), and even for space indoor environment analysis (Eckhardt and Zori 2002). Some other applications are more complicated and may deal with solid materials, and may integrate other building simulation models. Recent examples are the study of building material emissions for indoor air quality assessment (Topp et al. 2001; Huang and Haghighat 2002; Murakami et al. 2003) and for more accurate building energy and thermal comfort simulations (Bartak et al. 2002; Beausoleil- Morrison 2002; Zhai and Chen 2003).

Often, the outdoor environment has a significant impact on the indoor environment, such as in buildings with natural ventilation. To solve problems related to natural ventilation requires the study of both the indoor and outdoor environment together, such as simulations of outdoor airflow and pollutant dispersion (Sahm et al. 2002; Swaddiwudhipong and Khan 2002) and combined indoor and airflow studies (Jiang and Chen 2002). CFD is no longer a patent for users with PhD degrees. Tsou (2001) has developed online CFD as a teaching tool for building performance studies, including issues such as structural stability, acoustic quality, natural lighting, thermal comfort, and ventilation and indoor air quality.

Compared with experimental studies of indoor environment and building safety, CFD is less expensive and can obtain results much faster, due to the development in computing power and capacity as well as turbulence modeling. CFD can be applied to test flow and heat transfer conditions where experimental testing could prove very difficult, such as in space vehicles (Eckhardt and Zori 2002). Even if experimental measurements could be conducted, such an experiment would normally require hundreds of thousands dollars and many months of workers’ time (Yuan et al. 1999). However, CFD results cannot be always trusted, due to the assumptions used in turbulence modeling and approximations used in a simulation to simplify a complex real problem of indoor environment and building safety.

Although a CFD simulation can always give a result for such a simulation, it may not necessarily give the correct result. A traditional approach to examine whether a CFD result is correct is by comparing the CFD result with corresponding experimental data. The question now is whether one can use a robust and validated CFD program, such as a well-known commercial CFD program, to solve a problem related to indoor environment and building safety without validation. This forms the main objective of the chapter. This chapter presents a short review of the applications of CFD to indoor environment design and studies, and briefly introduces the most popular CFD models used.

The chapter concludes that, although CFD is a powerful tool for indoor environment design and studies, a standard procedure must be followed so that the CFD program and user can be validated and the CFD results can be trusted. The procedure includes the use of simple cases that have basic flow features interested and experimental data available for validation. The simulation of indoor environment also requires creative thinking and the handling of complex boundary conditions. It is also necessary to play with the numerical grid resolution and distribution in order to get a gridindependent solution with reasonable computing effort.

This investigation also discusses issues related to heat transfer. It is only through these incremental exercises that the user and the CFD program can produce results that can be trusted and used for indoor environment design and studies.