首页> 外文期刊>Journal of Applied Meteorology and Climatology >An Experimental Field Dataset with Buoyant, Neutral, and Dense Gas Atmospheric Releases and Model Comparisons in Low-Wind Speed (Diffusion) Conditions
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An Experimental Field Dataset with Buoyant, Neutral, and Dense Gas Atmospheric Releases and Model Comparisons in Low-Wind Speed (Diffusion) Conditions

机译:低风速(扩散)条件下具有浮力,中性和密集气体大气释放的实验现场数据集和模型比较

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摘要

A unique field dataset from a series of low-wind speed experiments, modeling efforts using three commonly used models to replicate these releases, and statistical analysis of how well these models were able to predict the plume concentrations is presented. The experiment was designed to generate a dataset to describe the behavior of gaseous plumes under low-wind conditions and the ability of current, commonly used models to predict these movements. The dataset documents the release and transport of three gases: ammonia (buoyant), ethylene (neutral), and propylene (dense) in low-wind speed (diffusion) conditions. Release rates ranged from 1 to 20 kg h~1. Ammonia and ethylene had five 5-min releases each to represent puff releases and five 20-min releases each to represent plume releases. Propylene had five 5-min puffs, six 20-min plumes, and a single 30-min plume. Thirty-two separate releases ranging from 6 to 47 min were conducted, of which only 30 releases generated useful data. The data collectedincluded release rates, atmospheric concentrations to 100 m from the release point, and local meteorological conditions. The diagnostics included nine meteorological stations on 100-m centers and 36 photoionization detectors in a radial pattern. Three current state-of-the-practice models, Aerial Locations of Hazardous Atmospheres (ALOHA), Emergency Prediction Information code (EPIcode), and Second-Order Closure Integrated Puff (SCIPUFF), were used to try to duplicate the measured field results. Low wind speeds are difficult to model, and all of the models had difficulty replicating the field measurements. However, the work does show that these models, if used correctly, are conservative (overpredict concentrations) and can be used for safety and emergency planning.
机译:提供了一系列低风速实验的独特现场数据集,使用三个常用模型来模拟这些排放的建模工作,并对这些模型能够很好地预测羽流浓度进行统计分析。设计该实验是为了生成一个数据集,以描述低风条件下气态烟羽的行为以及当前常用模型预测这些运动的能力。该数据集记录了在低风速(扩散)条件下三种气体的释放和传输:氨(浮力),乙烯(中性)和丙烯(浓)。释放速率为1至20 kg h〜1。氨和乙烯分别有5个5分钟的释放时间代表粉扑释放,有5个20分钟的释放分别代表烟羽释放。丙烯有5个5分钟的抽吸,6个20分钟的抽吸和一个30分钟的抽吸。进行了32次单独的发布,范围从6到47分钟,其中只有30个发布产生了有用的数据。收集的数据包括释放速率,距释放点至100 m的大气浓度和当地气象条件。诊断包括以100米为中心的9个气象站和以放射状分布的36个光电离检测器。三种当前的实际状态模型,即危险大气层的位置(ALOHA),紧急情况预测信息代码(EPIcode)和二阶封闭积分吹气(SCIPUFF),用于尝试复制实测结果。低风速很难建模,并且所有模型都难以复制现场测量结果。但是,这项工作确实表明,如果正确使用这些模型,则它们是保守的(过度预测的浓度),可用于安全和应急计划。

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