LBL渗透模型是一种将天气信息与气密性结合起来计算住宅空气渗透的简化方法。在本报告中，我们将渗透模型预测与我们的移动渗透测试单元（MITU）收集的数据进行比较。MITU是一个全尺寸测试结构，收集详细的天气和渗透测量数据。为了探索预测误差的来源，我们检查了LBL渗透模型中的四个简化假设:1）通过建筑物外壳裂缝的流量可以近似为孔板流量，2）风致和烟囱诱导的渗透可以正交添加，3）风致渗透可通过平均三个纵横比和典型比的值来表示；4）风致渗透可通过平均所有风向的值来表示。我们使用与实测数据的比较来定性地检查这些影响，并使用MITU渗透的详细计算机模拟来量化每个影响。 每个假设的影响都由偏差和分散性表示。（偏差是平均误差，分散度是模型跟踪渗透率短期波动能力的度量。）我们表明，孔口流量假设会导致8%的偏差和20%的分散，而正交假设会导致一致的过度预测（偏差=12%，分散=6%）。对于MITU，平均宽高比会导致一些预测过高（偏差=11%，散射=14%）。虽然它降低了模型跟踪渗透的能力（散射=19），但在风向上的平均值对平均渗透率几乎没有影响（偏差=0）。与实测数据相比，LBL模型的偏差为10%，分散性为28%。引文:研讨会，ASHRAE交易，1983年，第89卷，pt。华盛顿特区2B。

The LBL infiltration model is a simplified method for combining weather information with air tightness to calculate residential air infiltration. In this report, we compare infiltration-model predictions with data collected by our Mobile Infiltration Test Unit (MITU), a full-scale test structure that gathers detailed weather and infiltration measurements. To probe for sources of prediction errors, we examine four simplifying assumptions made in the LBL infiltration model : 1) that the flow through the cracks in the building shell can be approximated by orifice flow, 2) that wind-induced and stack induced infiltration can be added in quadrature, 3) that wind-induced infiltration can be represented by averaging the values for three aspect and typical ratios, 4) that wind-induced infiltration can be represented by averaging the values for all wind directions. We use comparisons with measured data to examine these effects qualitatively, and use detailed computer simulations of infiltration in MITU to quantify each effect. The effects of each assumption are represented by the bias and scatter. (The bias is the average error, and the scatter is a measure of the ability of a model to track short-term fluctuations in infiltration rate.) We show that the orifice flow assumption causes an 8% bias and a scatter of 20%, and that the quadrature assumption causes consistent overprediction (bias = 12%, scatter = 6%). For MITU, averaging over aspect ratio causes some overprediction (bias = 11%, scatter = 14%). Although it reduces the ability of the model to track infiltration (scatter = 19 averaging over wind direction has little effect on the mean infiltration rate (bias = 0). When compared to measured data, the LBL model has a bias of 10% and scatter of 28%.