and radiation are the dominant forms of heat transfer. The measurements show that
the difference between the air temperature inside and outside the greenhouse is
strongly linked to solar radiation and secondly to wind speed. However, Chow and
Hold (2010) obtained the following conclusions from studying buoyancy forces
from thermal gradients:
(a) Thermal radiation without air involvement changes air temperature distribution by radiating upper zone thermal energy in the wall toward the lower zone
wall, which then affects air temperature through conduction and convection;
(b) The inclusion of air absorption increases the effect of radioactive thermal
redistribution by allowing air to absorb and radiate heat, reducing temperature
gradients further; and
(c) Thermal boundary conditions and heat loads affect the predicted absolute
temperature bounds, but do not affect the temperature distribution.
Radiation conditions play an important role in redistributing heat. Atmospheric
conditions, especially relative humidity, are important for the calculation of
radiation and heat transfer.
12.4.5 Turbulence and Buoyancy
As computing power has increased, the complexity and sophistication of CFD
models have also increased. According to Norton and Sun (2006), the standard k-e
turbulence model commonly used in CFD models for greenhouses, in some cases
provides inadequate results, and the choice of turbulence models must be based on
the phenomena involved in the simulation. Different turbulence models give rise to
differences in speed, temperature, and humidity patterns, confirming the importance of choosing the model that most closely matches the actual conditions of
turbulence (Roy and Boulard 2005). Teitel et al. (2005) showed that the output of
the turbulent heat flux is mainly due to cold air entering the greenhouse, which
produces hot and cold eddies coming in and out of the greenhouse. Roy and
Boulard (2005) showed that the effects of wind direction on climate parameters
inside the greenhouse are usually simulated by using different turbulence models
available, to determine the energy balance between the flow of perspiration and the
flow of radiation. Under ventilation parameters based on Bernoulli’s theorem,
Majdoubi et al. (2007), showed that bad ventilation performance is not a result of
the low value of the greenhouse wind-related ventilation efficiency coefficient, but
rather, that the low rate of discharge due to pressure drop in airflow is generated
both by the use of anti-insect screens with small openings as an obstruction due to
the orientation of the rows of crops. Moreover, Rouboa and Monteiro (2007) note
that the RNG turbulence model is best suited to simulate microclimates in arcshaped greenhouses.
According to Baxevanou et al. (2008), the circulation of air buoyancy effect
shows the importance of internal temperature gradients, forced convection
12 Advances in Computational Fluid Dynamics Applied to Biosystems
351
the difference between the air temperature inside and outside the greenhouse is
strongly linked to solar radiation and secondly to wind speed. However, Chow and
Hold (2010) obtained the following conclusions from studying buoyancy forces
from thermal gradients:
(a) Thermal radiation without air involvement changes air temperature distribution by radiating upper zone thermal energy in the wall toward the lower zone
wall, which then affects air temperature through conduction and convection;
(b) The inclusion of air absorption increases the effect of radioactive thermal
redistribution by allowing air to absorb and radiate heat, reducing temperature
gradients further; and
(c) Thermal boundary conditions and heat loads affect the predicted absolute
temperature bounds, but do not affect the temperature distribution.
Radiation conditions play an important role in redistributing heat. Atmospheric
conditions, especially relative humidity, are important for the calculation of
radiation and heat transfer.
12.4.5 Turbulence and Buoyancy
As computing power has increased, the complexity and sophistication of CFD
models have also increased. According to Norton and Sun (2006), the standard k-e
turbulence model commonly used in CFD models for greenhouses, in some cases
provides inadequate results, and the choice of turbulence models must be based on
the phenomena involved in the simulation. Different turbulence models give rise to
differences in speed, temperature, and humidity patterns, confirming the importance of choosing the model that most closely matches the actual conditions of
turbulence (Roy and Boulard 2005). Teitel et al. (2005) showed that the output of
the turbulent heat flux is mainly due to cold air entering the greenhouse, which
produces hot and cold eddies coming in and out of the greenhouse. Roy and
Boulard (2005) showed that the effects of wind direction on climate parameters
inside the greenhouse are usually simulated by using different turbulence models
available, to determine the energy balance between the flow of perspiration and the
flow of radiation. Under ventilation parameters based on Bernoulli’s theorem,
Majdoubi et al. (2007), showed that bad ventilation performance is not a result of
the low value of the greenhouse wind-related ventilation efficiency coefficient, but
rather, that the low rate of discharge due to pressure drop in airflow is generated
both by the use of anti-insect screens with small openings as an obstruction due to
the orientation of the rows of crops. Moreover, Rouboa and Monteiro (2007) note
that the RNG turbulence model is best suited to simulate microclimates in arcshaped greenhouses.
According to Baxevanou et al. (2008), the circulation of air buoyancy effect
shows the importance of internal temperature gradients, forced convection
12 Advances in Computational Fluid Dynamics Applied to Biosystems
351