建立了一个计算流体力学模型，用于研究带有不同送风扩散器的房间的气流特性。本文以一个典型的座椅房间为研究对象，对送风位置、送风次数和送风口开度对气流特性的影响进行了数值研究。这项工作的重点是空气流动模式，以及房间里很少有人居住的热行为。作为全尺寸三维房间模型的输入，开发了一个二维送风扩散器模型，用于向房间提供气流方向和大小。 通过改变送风扩散器的类型、角度和速度，研究了配风对热舒适参数的影响。还调查了供气扩散器的位置和数量。预处理策略用于创建具有参数化特征的几何模型。采用商用模拟软件“Fluent 6.3”求解气流分布过程中质量守恒、三动量守恒和能量守恒的微分方程。 流动的湍流效应由发展良好的两方程湍流模型表示。本文采用了工业应用中最广泛的湍流模型之一，即所谓的标准k-e湍流模型。室内空气温度分布和相对湿度的数值预测包括空气温度和相对湿度。通过这项工作进行的热舒适预测基于PMV（预测平均投票）模型和PPD（人们不满意的百分比）模型，PMV和PPD使用Fanger’s模型进行估计。 引用:德克萨斯州达拉斯ASHRAE会议论文。

A computational fluid dynamics model is developed to examine the air flow characteristics of a room with different supply air diffusers. The paper is devoted to numerically investigate the influence of location and number of air supply and extracts openings on air flow properties in a typical seating room. The work focuses on air flow patterns, thermal behavior in the room where few number of occupants. As an input to the full-scale 3-D room model, a 2-D air supply diffuser model that supplies direction and magnitude of air flow into the room is developed. Air distribution effect on thermal comfort parameters was investigated depending on changing the air supply diffusers type, angels and velocity. Air supply diffusers locations and number were also investigated. The pre-processor Gambit is used to create the geometric model with parametric features. Commercially available simulation software "Fluent 6.3" is incorporated to solve the differential equations governing the conservation of mass, three momentum and energy in the processing of air flow distribution. Turbulence effects of the flow are represented by the well developed two equation turbulence model. In this paper work, the so-called standard k-e turbulence model, one of the most widespread turbulence models for industrial applications, was utilized. Basic parameters included in this work are air dry bulb temperature, air velocity, relative humidity and turbulence parameters are used for numerical predictions of indoor air distribution and thermal comfort. The thermal comfort predictions through this work were based on the PMV (Predicted Mean Vote) model and the PPD (Percentage People Dissatisfied) model, the PMV and PPD were estimated using Fanger’s model.