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- ItemOpening Size E ects on Airflow Pattern and Airflow Rate of a Naturally Ventilated Dairy Building : A CFD Study(Basel : MDPI, 2020) Saha, Chayan Kumer; Yi, Qianying; Janke, David; Hempel, Sabrina; Amon, Barbara; Amon, ThomasAirflow inside naturally ventilated dairy (NVD) buildings is highly variable and difficult to understand due to the lack of precious measuring techniques with the existing methods. Computational fluid dynamics (CFD) was applied to investigate the effect of different seasonal opening combinations of an NVD building on airflow patterns and airflow rate inside the NVD building as an alternative to full scale and scale model experiments. ANSYS 2019R2 was used for creating model geometry, meshing, and simulation. Eight ventilation opening combinations and 10 different reference air velocities were used for the series of simulation. The data measured in a large boundary layer wind tunnel using a 1:100 scale model of the NVD building was used for CFD model validation. The results show that CFD using standard k-ε turbulence model was capable of simulating airflow in and outside of the NVD building. Airflow patterns were different for different opening scenarios at the same external wind speed, which may affect cow comfort and gaseous emissions. Guiding inlet air by controlling openings may ensure animal comfort and minimize emissions. Non-isothermal and transient simulations of NVD buildings should be carried out for better understanding of airflow patterns.
- ItemNon-linear temperature dependency of ammonia and methane emissions from a naturally ventilated dairy barn(Amsterdam : Elsevier, 2016) Hempel, Sabrina; Saha, Chayan Kumer; Fiedler, Merike; Berg, Werner; Hansen, Christiane; Amon, Barbara; Amon, ThomasAmmonia (NH3) and methane (CH4) emissions from naturally ventilated dairy barns affect the environment and the wellbeing of humans and animals. Our study improves the understanding of the dependency of emission rates on climatic conditions with a particular focus on temperature. Previous investigations of the relation between gas emission and temperature mainly rely on linear regression or correlation analysis. We take up a preceding study presenting a multilinear regressionmodel based onNH3 and CH4 concentration and temperaturemeasurements between 2010 and 2012 in a dairy barn for 360 cows inNorthern Germany.We study scatter plots and non-linear regressionmodels for a subset of these data and show that the linear approximation comes to its limits when large temperature ranges are considered. The functional dependency of the emission rates on temperature differs among the gases. For NH3, the exponential dependency assumed in previous studies was proven. For methane, a parabolic relation was found. The emissions show large daily and annual variations and environmental impact factors like wind and humidity superimpose the temperature dependency but the functional shape in general persists. Complementary to the former insight that high temperature increases emissions, we found that in the case of CH4, also temperatures below 10 C lead to an increase in emissions from ruminal fermentation which is likely to be due to a change in animal activity. The improved prediction of emissions by the novel non-linear model may support more accurate economic and ecological assessments of smart barn concepts.