结合模拟和测量的有效数据集用于自然通风奶牛场的排放分析

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES
Julian Hartje, Abu Zar Shafiullah
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引用次数: 0

摘要

由于大的侧壁开口,对自然通风的牲畜建筑的排放进行量化是具有挑战性的。此外,测量活动是昂贵和耗时的,因此在一年中仅限于几个短的测量周。但是,排放因子或年平均值是从这些数据集推断出来的。模拟可以补充这一数据集,使其得到扩展,从而扩大排放因子外推或评价畜舍和管理系统的基础。该数据集包括自然通风牛棚计算流体动力学(CFD)模拟的求解数据以及相应的模拟和几何文件。模拟使用来自德国三个自然通风牛棚测量活动的数据集进行验证。结合德国气象局(DWD)的天气数据,可以调查在测量周之外发生的天气情况。有了现有的数据集,进一步的调查是可能的。结合测量数据,可以详细研究模拟技术,数据聚合和新的数值模拟方法的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validated dataset combining simulations and measurements for emission analysis of naturally ventilated dairy barns
Quantifying emissions from naturally ventilated livestock buildings is challenging due to the large side wall openings. In addition, measurement campaigns are expensive and time consuming and are therefore limited to a few short measurement weeks during the year. However, emission factors or annual averages are extrapolated from these data sets. Simulations can complement this data set by extending it and thus broadening the basis for the extrapolation of emission factors or evaluation of the barn and management system. The dataset presented consists of solution data from computational fluid dynamics (CFD) simulations of naturally ventilated cattle barns and the corresponding simulation and geometry files. The simulations were validated using data sets from measurement campaigns in three naturally ventilated cattle barns in Germany. Together with weather data from the German Weather Service (DWD), weather situations that occurred outside the measurement weeks could be investigated. With the presented data set further investigations are possible. Together with the measured data, simulation techniques, data aggregation and the development of new numerical modelling approaches can be investigated in detail.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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