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The design and operation of ventilation systems for animal housing is a crucial component in maintaining a suitable environment for both animals and workers by removing heat, moisture, and gas species. However, important design and operational criteria, such as profiles of velocity and extent of mixing within animal housing, can be difficult to study experimentally. Thus, a computational fluid dynamics (CFD) model of a commercial dairy holding area, including the generation of transport of heat and gas species within the domain, was developed. The animal-occupied zone (AOZ) was modeled using porous media. The model was evaluated with experimental data of velocity and gas concentration. Results indicated that the airflow uniformity and air speed could be increased within the holding area by modifying the configuration of the side curtain openings and using concrete walls to guide airflow; a 20% increase in average velocity within the AOZ was achieved. Results of the CFD model have shown it to be an effective tool for gaining insight into the complex mixing patterns within holding areas to improve the design of animal housing. [ABSTRACT FROM AUTHOR]

The increased global demand for milk and other dairy products over the past decade has heightened concerns about the potential for increased environmental impacts. Accurate measurement of gas emissions from dairy cows is essential to assess the effects of cow diets and other management practices on both the composition and rate of gas emissions. In this article, methodologies are described to instrument, calibrate, and assess the uncertainty of gas emissions by cows housed in chambers that simulate production settings. The supply and exhaust ducts of each chamber were equipped with pitot tubes, temperature and relative humidity probes, and gas samplers to monitor airflow rates, gas composition, and gas emission rates. A Fourier transform infrared spectroscopy (FTIR) instrument was used to quantify gaseous concentrations in the gas samples on a semi-continuous basis. The measurement uncertainty of the rate of gaseous emission from the chambers was quantified, and gas concentration and differential pressure, as measured by the pitot tubes, were identified as the primary parameters contributing to gas emission uncertainties. Mass recovery tests determined that the recovery of methane from each chamber was within 10% of the released mass. Fan operating curves were experimentally determined to identify optimum differential chamber pressures to minimize gas leakage from the chambers. A computational fluid dynamics model was developed to assess air mixing patterns and define steady-state conditions. The model was validated with experimental data of air velocity within each chamber. These procedures will facilitate accurate measurement of gas emissions from housed dairy cows and provide a laboratory to test various gas mitigation treatments. [ABSTRACT FROM AUTHOR]

Biofuels derived from algae are becoming an increasingly viable alternative to petroleum-based fuels; however, research and development in the field must continue to advance the technology before biofuels can be produced in an economical and environmentally friendly manner. Unlike with photobioreactors, there is no generally accepted model for evaluating the growth of algae in open raceways because algal growth involves a large number of variables. For this reason, computational fluid dynamics (CFD) could prove to be a valuable and effective tool for the design, optimization, and operation of large-scale raceway ponds under local environmental conditions. CFD can elucidate and quantify the complex sets of variables that govern heat, mass, and flow patterns within the pond and provide spatiotemporal data concerning algal concentration and other water quality variables, such as light and temperature. The corresponding outcomes will enable designers to create more efficient ponds and more accurately predict growth under a variety of scenarios, as well as optimize the pond's operation in order to produce the maximum amount of biomass possible within a given locality. The present study focuses on developing user-defined functions capable of capturing key parameters, verifying the CFD outcomes against existing experimental data, providing computational solutions, and assessing the sensitivity of the model. [ABSTRACT FROM AUTHOR]