کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6539470 1421099 2018 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Computational model of methane and ammonia emissions from dairy barns: Development and validation
ترجمه فارسی عنوان
مدل محاسباتی انتشار گازهای متان و آمونیاک از انبارهای لبنی: توسعه و اعتبار سنجی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
The increased global demand for milk and other dairy products over the past decades is a cause for concern due to the potential for environmental impact. Ammonia produced by housed dairy cows can contribute to the formation of particulate matter and nitrous oxide which both contribute to the greenhouse effect. The methane produced by these cows also contributes to the greenhouse effect. Scientists and engineers face the challenge of developing methods to reduce the environmental impact of dairy production while not inhibiting the ability of producers to keep up with demand. Emission of methane and ammonia are highly dependent on feed composition, barn design and operation, manure management making this a challenging topic to study experimentally. Using computational models to simulate the generation and dispersion of gaseous species within dairy housing can facilitate the exploration of cost-effective gas mitigation strategies. Thus a steady-state computational fluid dynamics (CFD) model capable of simulating biologically based generation of methane, ammonia, and heat and their transport within the domain was developed and validated. The effect of buoyancy forces on the accuracy and stability of the solutions was explored. The model was validated with experimental data collected from emission chambers located at USDA-ARS Dairy Forage Research Center in Wisconsin, USA. Concentration of ammonia and methane, due to controlled injections from cylinders and biological generations from a dairy cow, were measured in the chambers using a FTIR gas analyzer. Results of the validated CFD model could be used to predict gaseous emissions under a range of environmental, design, and experimental treatment parameters.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 149, June 2018, Pages 80-89
نویسندگان
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