Modern technology in the study of ventilation.
In general, airflow can be analyzed using three types of methods: experimental, theoretical, and numerical simulation. Because they use direct measurement systems, experimental methods obtain the most practical data, but directly measuring air velocities and ventilation rates in agricultural buildings is difficult. It is also difficult to establish identical and stable boundary conditions in a field experiment due to unstable and unpredictable weather conditions. Ultimately, field experiments require considerable labor, time, space, and cost. Because of these difficulties, several indirect methods, involving theoretical models, have been developed for the study of ventilation. Typically, though, models can only predict overall ventilation rates. They are not much use in locating problems, such as poorly ventilated areas, within a building.
Recently, an aerodynamic approach has been applied to predict and control complicated airflow distributions in large agricultural buildings. This approach uses the technology of aerodynamics, such as wind tunnels, particle image velocimetry (PIV), and computational fluid dynamics (CFD). These techniques have several advantages over field experiments in the study of agricultural ventilation. First, by maintaining stable, identical boundary conditions, they can easily simulate and change weather conditions and structural specifications.
Second, they can visualize airflow patterns quantitatively as well as qualitatively. For example, wind tunnels have been around for more than a century, but for most of that time, only qualitative airflow visualizations have been conducted in them. Particle image velocimetry (PIV) can analyze airflow quantitatively, making wind tunnel tests much more versatile. Moreover, CFD can compute airflow and all psychrometric conditions of air at any location in the area of interest. While field methods require extensive instrumentation and high measurement accuracy in well-defined experiments, aerodynamic technologies can greatly decrease research time.
Wind tunnels produce a controlled stream of air to study the effects of air on moving objects, such as aircraft, or on stationary objects, such as buildings. Compared to field experiment using full-scale objects, wind tunnel tests typically use small-scale models, which make it possible to change the shape or size of the object and then analyze the data. This lowers the cost and produces a large volume and range of data in a short time. However, scaling down the test object, as well as the airflow properties, can affect the results, and the size difference must be calculated to ensure that the results are valid. For example, even though the structural model may be 1/16 scale, the air velocity and pressure cannot be simply scaled down to 1/16. Various scaling theories have been established to perform the necessary calculations.
Shown below is the large wind tunnel at the National Institute of Agricultural Engineering (NIAE) of the Rural Development Administration (RDA) in Korea. The air velocity can be adjusted from 0.3 to 15 m/s, and over 60 m/s of wind can be applied to small-scale models. This wind tunnel is used for studies in the structural design of agricultural buildings, ventilation system design, decisions regarding farm location, usage of wind energy in agriculture, and improvements in pesticide efficiency. The operation of the fan, model turntable, and sensors is controlled by computers. Generally, a smoke generator, light source, and digital camera are used to visualize the airflows qualitatively around the model on the turntable. In simple cases, a small flag is used to gauge the wind direction.
Particle image velocimetry
The ability to see flow patterns in and around a model under investigation often provides insight into an aerodynamic problem. The easiest method to obtain this information is through flow visualization. Flow visualization is the process of revealing otherwise invisible information, such as velocity, pressure, density, and temperature. In recent years, most airflow analysis has been performed using computer simulation, and the resolution has been steadily improving. In addition, calculation time has been greatly reduced. However, it is very difficult to evaluate the accuracy of flow visualization because of non-comparable experimental data. In an experimental study, conventional point measurement techniques only allow local measurement of air velocity and pressure. Using this technique, it is impossible to analyze the overall variation of airflow within a space, and installation of additional sensors can interfere with the airflow pattern.
Particle image velocimetry (PIV) can overcome this problem. PIV is a non-contact method, so it does not disturb the airflow while accurately visualizing the overall flow field at a certain time. PIV systems measure velocity by determining particle displacement using a double-pulsed laser technique. A laser light sheet illuminates a plane in the flow, and the positions of particles in that plane are recorded using a digital or film camera. A fraction of a second later, a second laser pulse illuminates the same plane, creating a second particle image. From these two particle images, PIV analysis algorithms obtain the particle displacements for the entire flow region imaged. This technique provides velocity information at hundreds or even thousands of locations quickly, easily, and reliably. Flow properties, such as vorticity and strain rates, are obtained for the entire region, and other properties, such as mean turbulence and other higher-order flow statistics, can be calculated.
PIV has quickly become the newest high technology in flow analysis, and several newly developed PIV systems have been introduced for aerodynamic studies, including cinematic PIV, stereoscopic PIV, and holographic PIV. The PIV system includes laser and light-sheet optics, an image capture/shifting component, a synchronizer, and a computer. Lasers are widely used in PIV because of their ability to emit monochromatic light with high energy density, which can easily be bundled into thin light-sheets for illuminating and recording the tracer particles without chromatic aberrations.
Computational fluid dynamics
Numerical simulation is the most significant recent development in the computer industry. The typical numerical analysis technique for aerodynamic studies is computational fluid dynamics (CFD). CFD models predict distributions of internal airflow, air temperatures, humidity, dust, and gas and show the affect of structural elements on airflow. A shortcoming of CFD is that the accurate calculation of the flow field requires adequate experimental data in order to determine whether the problem has been modeled correctly. So far, few have investigated the validity of CFD-based simulations with actual data of airflow because of the difficulties of airflow analysis in the field.
In CFD, the computational domain is divided into small cells, called control volumes, in each of which a value for the simulated variables is calculated (e.g., air speed and direction, temperature, gas and dust concentration, etc.). Conservation principles of mass, energy, and momentum are also applied to each of these control volumes. After the model has been supplemented with suitable boundary conditions, which define the influence of environmental factors outside the computational domain, the values of the variables in each control volume are calculated in an iterative process. The computational effort required for CFD can be enormous, depending on the number of cells in the domain, the number of variables in each cell, and the kind of transport processes being simulated.
Commercial CFD programs are usually a two-part package consisting of a preprocessor and a main module. The preprocessor is used to create the cell geometry that makes the calculations possible. The main module is then used to specify physical models, boundary conditions, and fluid and material properties.
Conclusion: there's more to come
New aerodynamic technologies cannot replace field experiments completely because real-world conditions can only be observed through field experiments. However, these new technologies can be helpful in overcoming the disadvantages of field experiments. In particular, the aerodynamic approach can contribute to improved environmental control in agriculture buildings because a building's internal climate depends strongly on airflow distribution. At the same time, the inherent weaknesses of aerodynamic studies using wind tunnels, PIV, and CFD can be overcome by field experiments. Studies of forced and natural ventilation of livestock houses as well as quantitative visualization of internal airflow in multispan greenhouses using aerodynamic technologies are currently in progress at NIAE in Korea. In addition, our international cooperative research programs based on these technologies have already been conducted with national research institutes in Japan, France, and other countries. Clearly, there is much more to come in the study of ventilation and structural design of agricultural buildings.
ASAE member In-Bok Lee is affiliated with the National Institute of Agricultural Engineering, Rural Development Administration, Suwon-City, Korea 441-1001; 82+31-290-1878, fax 82+31-290-1930, firstname.lastname@example.org.
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|Publication:||Resource: Engineering & Technology for a Sustainable World|
|Date:||Nov 1, 2004|
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