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How to simplify computer simulated persons (CSPs) for modeling personal microenvironments: comparison and case studies.

Article Excerpt
INTRODUCTION

Different computer simulated persons (CSPs) have been developed to represent occupants for indoor airflow simulation using computational fluid dynamics (CFD). These CSPs range from very complex, human-like configuration to very simple, box-like shape. Complicated CSPs usually require large number of computational grids and long computing time. On the other hand, overly simplified CSPs may significantly influence the simulation accuracy of personal micro-environment, especially for non-mixing type ventilation such as personal or displacement ventilation. A guide to properly simplify CSPs is urgently necessary for current research.

In the past, different CSPs have been used in room airflow or indoor air quality models. He and Yang (2005) compared the contaminant removal by displacement ventilation (DV) and mixing ventilation based on experiments and CFD simulations. Cubic box was used to represent the persons and equipment in their study. Zhang et al. (2005) also used cubic CSPs to evaluate the thermal comfort and indoor air quality in classrooms, retail shops, and industrial workshops. Hayashi et al. (2002) adopted a person-like CSP to investigate the effect of inhalation under DV chamber. The CSP, though more complex than cuboid box, is still a simplified one. Later, the same CSP was applied by Zhang et al. (2005) to study the respiration area caused by unsteady breathing. Besides these simplified CSPs, very complex, detailed CSPs were also used in previous research. Bjorn and Nielsen (2002) developed detailed CSPs to investigate the dispersal of exhaled air in DV rooms. The simulation results of a seated detailed CSP and a cuboid CSP were compared by Topp and Nielsen (2002) and Sideroff and Dang (2005). They concluded that a simple geometry was sufficient for studying global airflow, but detailed geometry should be applied to assess the local flow condition. However, they did not mention to what complexity the CSP must be in order to accurately assess local flow near the person. Murakami (2004) developed a standing detailed CSP to analyze microclimates around the human body. This CSP was generated according to a real human body, thus it is supposed to be more accurate than pervious simplified CSPs. Gao and Niu (2004) developed a seated, detailed CSP using laser scanning technology. They applied it to investigate the performance of a personal ventilation system. A seated detailed CSP was adopted by Sorensen et al. (2003) to study the radiative heat transfer at different parts of the CSP. They divided their CSP into foot, leg, thigh etc. There were totally 10 different parts. The heat transfer coefficient of each part was estimated based on their simulation result.

Detailed CSPs require fine, and usually unstructured grids to mesh the geometry accurately. A very simple case such as a cubic room with a single occupant may need more than [10.sup.5]-[10.sup.6] grids to ensure the accuracy. And the calculation time can be up to several days for a single node personal computer (for example, the detailed CSP case with 400,000 grids running on a P4 2.6GHz PC with 1G memory). Therefore, it is usually too time consuming to use such detailed CSPs. Simple CSPs are always preferred if they would not significantly affect the accuracy of simulation. Under what circumstances such simple CSPs could be used, and how to simplify the CSPs? These problems have not been well studied yet.

The objective of this paper is to investigate quantitatively the simulation error due to CSP simplification. Different CSP simplification strategies are proposed. The simulation results by applying these strategies are compared with those by using the detailed CSP in a displacement ventilation case, the latter being validated by the benchmark experimental data (Kato and Yang, 2003).

CSP SIMPLIFICATION METHODOLOGY

Both the CSP geometry and heat source distribution may...

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