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Subject: Pressure drop ×

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    Airflow resistance of two hop varieties
    (Tartu : Estonian Agricultural University, Faculty of Agronomy, 2021) Ziegler, T.; Teodorov, T.
    The quality of hops used in brewing is substantially reliant upon the processing step of drying. To ensure effective drying in kiln as well conveyor-belt dryers, homogeneous distribution of air is of particular importance. Uneven air distribution often results in inefficient drying and nonuniform moisture content of the hop cones. The air distribution naturally is governed by the airflow resistances in the individual floors or belts of a dryer. Hence, in order to quantify the airflow resistance of hop cones at different air velocities and bed heights, systematic measurements were carried out. In addition to determining the bulk densities of hops, the investigations included trials with fresh and dried hop samples. Clear differences were observed between hop varieties both in measured pressure drops and in bulk densities. Moreover, in the case of fresh hops, a non-linear increase in pressure drop with bed height was ascertained. Semiempirical equations were developed to describe pressure drop as a function of air velocity. This work will contribute to the design of dryers with optimum airflow distribution and thus enhance the efficiency of drying as well as the product quality.
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    CFD modelling of an animal occupied zone using an anisotropic porous medium model with velocity depended resistance parameters
    (Amsterdam [u.a.] : Elsevier, 2021) Doumbia, E. Moustapha; Janke, David; Yi, Qianying; Amon, Thomas; Kriegel, Martin; Hempel, Sabrina
    The airflow in dairy barns is affected by many factors, such as the barn’s geometry, weather conditions, configurations of the openings, cows acting as heat sources, flow obstacles, etc. Computational fluids dynamics (CFD) has the advantages of providing detailed airflow information and allowing fully-controlled boundary conditions, and therefore is widely used in livestock building research. However, due to the limited computing power, numerous animals are difficult to be designed in detail. Consequently, there is the need to develop and use smart numerical models in order to reduce the computing power needed while at the same time keeping a comparable level of accuracy. In this work the porous medium modeling is considered to solve this problem using Ansys Fluent. A comparison between an animal occupied zone (AOZ) filled with randomly arranged 22 simplified cows’ geometry model (CM) and the porous medium model (PMM) of it, was made. Anisotropic behavior of the PMM was implemented in the porous modeling to account for turbulence influences. The velocity at the inlet of the domain has been varied from 0.1 m s−1 to 3 m s−1 and the temperature difference between the animals and the incoming air was set at 20 K. Leading to Richardson numbers Ri corresponding to the three types of heat transfer convection, i.e. natural, mixed and forced convection. It has been found that the difference between two models (the cow geometry model and the PMM) was around 2% for the pressure drop and less than 6% for the convective heat transfer. Further the usefulness of parametrized PMM with a velocity adaptive pressure drop and heat transfer coefficient is shown by velocity field validation of an on-farm measurement.