Application of Semi-Empirical Ventilation Models in A Mediterranean Greenhouse with Opposing Thermal and Wind Effects. Use of Non-Constant Cd (Pressure Drop Coefficient Through the Vents) and Cw (Wind Effect Coefficient)

The present work analyses the natural ventilation of a multi-span greenhouse with one roof vent and two side vents by means of sonic anemometry. Opening the roof vent to windward, one side vent to leeward, and the other side vents to windward (this last vent obstructed by another greenhouse), causes opposing thermal GT (m3 s−1) and wind effects Gw (m3 s−1), as outside air entering the greenhouse through the roof vent circulates downward, contrary to natural convection due to the thermal effect. In our case, the ventilation rate RM (h−1) in a naturally ventilated greenhouse fits a second order polynomial with wind velocity uo (RM = 0.37 uo2 + 0.03 uo + 0.75; R2 = 0.99). The opposing wind and thermal effects mean that ventilation models based on Bernoulli’s equation must be modified in order to add or subtract their effects accordingly—Model 1, in which the flow is driven by the sum of two independent pressure fields GM1=√(∣∣G2T±G2w∣∣) , or Model 2, in which the flow is driven by the sum of two independent fluxes GM2=|GT±Gw| . A linear relationship has been obtained, which allows us to estimate the discharge coefficient of the side vents (CdVS) and roof vent (CdWR) as a function of uo [CdVS = 0.028 uo + 0.028 (R2 = 0.92); CdWR = 0.036 uo + 0.040 (R2 = 0.96)]. The wind effect coefficient Cw was determined by applying models M1 and M2 proved not to remain constant for the different experiments, but varied according to the ratio uo/∆Tio0.5 or δ [CwM1 = exp(−2.693 + 1.160/δ) (R2 = 0.94); CwM2 = exp(−2.128 + 1.264/δ) (R2 = 0.98)]

Combination of image processing and artificial neural networks as a novel approach for the identification of Bemisia tabaci and Frankliniella occidentalis on sticky traps in greenhouse agriculture

Integrated Pest Management (IPM) lies at the core of the current efforts to reduce the use of deleterious chemicals in greenhouse agriculture. IPM strategies rely on the early detection and continuous monitoring of pest populations, a critical task that is not only time-consuming but also highly dependent on human judgement and therefore prone to error. In this study, we propose a novel approach for the detection and monitoring of adult-stage whitefly (Bemisia tabaci) and thrip (Frankliniella occidentalis) in greenhouses based on the combination of an image-processing algorithm and artificial neural networks. Digital images of sticky traps were obtained via an image-acquisition system. Detection of the objects in the images, segmentation, and morphological and color property estimation was performed by an image-processing algorithm for each of the detected objects. Finally, classification was achieved by means of a feed-forward multi-layer artificial neural network. The proposed whitefly identification algorithm achieved high precision (0.96), recall (0.95) and F-measure (0.95) values, whereas the thrip identification algorithm obtained similar precision (0.92), recall (0.96) and F-measure (0.94) values

Effects of ventilator configuration on the flow pattern of a naturally-ventilated three-span Mediterranean greenhouse

Natural ventilation used in agricultural greenhouses is important to control greenhouse microclimate. The effect of the ventilator configuration on the flow pattern of a three-span Mediterranean greenhouse with an obstacle to airflow (a neighbouring greenhouse) was investigated. Two different ventilator configurations, two or three half-arch roof vents with two roll-up side vents, were evaluated using sonic anemometry. It was observed that the flow pattern through the greenhouse depends of the ventilation surfaces distribution and the obstruction to the ventilation system. Moreover, the magnitude and distribution of ventilation surface affected the overall ventilation rate and the ventilation rate at plant level. The ventilator configuration with two roof and two side vents improved air movement at the plant level, although the overall volumetric flow rate was lower than that with three roof and two side vents

Effect of material ageing and dirt on the behaviour of greenhouse insect-proof screens

The present work examines the variations in the aerodynamic characteristics of four insect-proof screens by means of wind tunnel tests and digital image processing. The tested insect-proof screens were examined in three different conditions: (i) in their new, unused state; (ii) under conditions of accumulated dust and dirt after a period of 3 to 4 years of use; and (iii) under clean conditions after a period of 3 to 4 years of use and a cleaning treatment with high-pressure water. The deterioration of the screens caused the mesh to become less tense, therefore increasing its thickness and improving its aerodynamic behaviour despite a slight increase of the thread diameter and a subsequent decrease of the 2-dimensional porosity. The pressure drop coefficient, Fφ, of the used but clean screens was 1.5% to 8.8% lower (for u=1.0 m/s) than that of the new ones, thus increasing the discharge coefficient, Cd,φ, by between 0.8% and 4.8% as a result of the presence of the screens. On the other hand, comparison of the used screens in their clean and unclean states showed that the accumulation of dirt has a major bearing on their aerodynamic characteristics: Fφ increased by between 16.5% and 61.2% (for u=1.0 m/s) for the unclean screens, resulting in a Cd,φ reduction of between 7.5% and 21.3% and therefore a lower natural ventilation capacity of the greenhouse. A regular cleaning treatment of the insect-proof screens is a simple measure that improves the natural ventilation capacity of the greenhouse

An Auto-Tuning PI Control System for an Open-Circuit Low-Speed Wind Tunnel Designed for Greenhouse Technology

Wind tunnels are a key experimental tool for the analysis of airflow parameters in many fields of application. Despite their great potential impact on agricultural research, few contributions have dealt with the development of automatic control systems for wind tunnels in the field of greenhouse technology. The objective of this paper is to present an automatic control system that provides precision and speed of measurement, as well as efficient data processing in low-speed wind tunnel experiments for greenhouse engineering applications. The system is based on an algorithm that identifies the system model and calculates the optimum PI controller. The validation of the system was performed on a cellulose evaporative cooling pad and on insect-proof screens to assess its response to perturbations. The control system provided an accuracy of <0.06 m·s‾1 for airflow speed and <0.50 Pa for pressure drop, thus permitting the reproducibility and standardization of the tests. The proposed control system also incorporates a fully-integrated software unit that manages the tests in terms of airflow speed and pressure drop set points

Models for characterising the aerodynamics of insect-proof screens from their geometric parameters

This study characterised the geometric and aerodynamic parameters of 35 insect-proof screens with different weft and warp threads, with porosities ranging from 0.237 to 0.556 m2 m-2. The geometric parameters were assessed by analysing digital images, and the aerodynamic parameters were determined using tests in a low-speed wind tunnel. Using the experimental measurements, four different models were developed and validated to estimate the aerodynamic parameters of an insect-proof screen from two or more of their geometric parameters: (i) to estimate the pressure drop coefficient Fφ based on the thread diameter Reynolds number (Red) and screen porosity φ [m2 m-2] Fφ=(0.4810002+11.5331/Red)×((1–φ2)/φ2) (R2 = 93.9% with a p-value = 0.000); (ii) estimating Fφ based on the screen thickness Reynolds number (Ret) and screen porosity φ [m2 m-2] Fφ = (0.475502+26.2114/Ret)×((1–φ2)/φ2) (R2 = 92.1% with a pvalue = 0.000); (iii) estimating screen permeability Kp=Dh2φ3/(2.0679 (1–φ)2)+3.8362×10–10 (R2=56.3%//56.2 % with a p-value<0.05) as a function of thread diameter Dh [m] and porosity φ [m2 m-2]; (iv) estimating the inertial factor Y=0.0571195+0.135966· Dh/Di (R2=58.1% with a p-value=0.0000) as a function of thread diameter [m] and the inner pore diameter Di [m]. These models gave improved accuracy compared with the previous models described in the literature. Models for aerodynamic parameters of the insect-proof screens Kp and Y based in their geometric characteristics are very important to simulate the effects of insect screens in ventilation studies using computational fluid dynamic (CFD) studies

Effect of material ageing and dirt on the behaviour of greenhouse insect-proof screens

The present work examines the variations in the aerodynamic characteristics of four insect-proof screens by means of wind tunnel tests and digital image processing. The tested insect-proof screens were examined in three different conditions: (i) in their new, unused state; (ii) under conditions of accumulated dust and dirt after a period of 3 to 4 years of use; and (iii) under clean conditions after a period of 3 to 4 years of use and a cleaning treatment with high-pressure water. The deterioration of the screens caused the mesh to become less tense, therefore increasing its thickness and improving its aerodynamic behaviour despite a slight increase of the thread diameter and a subsequent decrease of the 2-dimensional porosity. The pressure drop coefficient, Fφ, of the used but clean screens was 1.5% to 8.8% lower (for u=1.0 m/s) than that of the new ones, thus increasing the discharge coefficient, Cd,φ, by between 0.8% and 4.8% as a result of the presence of the screens. On the other hand, comparison of the used screens in their clean and unclean states showed that the accumulation of dirt has a major bearing on their aerodynamic characteristics: Fφ increased by between 16.5% and 61.2% (for u=1.0 m/s) for the unclean screens, resulting in a Cd,φ reduction of between 7.5% and 21.3% and therefore a lower natural ventilation capacity of the greenhouse. A regular cleaning treatment of the insect-proof screens is a simple measure that improves the natural ventilation capacity of the greenhouse

An Auto-Tuning PI Control System for an Open-Circuit Low-Speed Wind Tunnel Designed for Greenhouse Technology

Wind tunnels are a key experimental tool for the analysis of airflow parameters in many fields of application. Despite their great potential impact on agricultural research, few contributions have dealt with the development of automatic control systems for wind tunnels in the field of greenhouse technology. The objective of this paper is to present an automatic control system that provides precision and speed of measurement, as well as efficient data processing in low-speed wind tunnel experiments for greenhouse engineering applications. The system is based on an algorithm that identifies the system model and calculates the optimum PI controller. The validation of the system was performed on a cellulose evaporative cooling pad and on insect-proof screens to assess its response to perturbations. The control system provided an accuracy of <0.06 m·s‾1 for airflow speed and <0.50 Pa for pressure drop, thus permitting the reproducibility and standardization of the tests. The proposed control system also incorporates a fully-integrated software unit that manages the tests in terms of airflow speed and pressure drop set points

Application of Semi-Empirical Ventilation Models in A Mediterranean Greenhouse with Opposing Thermal and Wind Effects. Use of Non-Constant Cd (Pressure Drop Coefficient Through the Vents) and Cw (Wind Effect Coefficient)

The present work analyses the natural ventilation of a multi-span greenhouse with one roof vent and two side vents by means of sonic anemometry. Opening the roof vent to windward, one side vent to leeward, and the other side vents to windward (this last vent obstructed by another greenhouse), causes opposing thermal GT (m3 s&minus;1) and wind effects Gw (m3 s&minus;1), as outside air entering the greenhouse through the roof vent circulates downward, contrary to natural convection due to the thermal effect. In our case, the ventilation rate RM (h&minus;1) in a naturally ventilated greenhouse fits a second order polynomial with wind velocity uo (RM = 0.37 uo2 + 0.03 uo + 0.75; R2 = 0.99). The opposing wind and thermal effects mean that ventilation models based on Bernoulli&rsquo;s equation must be modified in order to add or subtract their effects accordingly&mdash;Model 1, in which the flow is driven by the sum of two independent pressure fields G M 1 = | G T 2 &plusmn; G w 2 | , or Model 2, in which the flow is driven by the sum of two independent fluxes G M 2 = | G T &plusmn; G w | . A linear relationship has been obtained, which allows us to estimate the discharge coefficient of the side vents (CdVS) and roof vent (CdWR) as a function of uo [CdVS = 0.028 uo + 0.028 (R2 = 0.92); CdWR = 0.036 uo + 0.040 (R2 = 0.96)]. The wind effect coefficient Cw was determined by applying models M1 and M2 proved not to remain constant for the different experiments, but varied according to the ratio uo/∆Tio0.5 or &delta; [CwM1 = exp(&minus;2.693 + 1.160/&delta;) (R2 = 0.94); CwM2 = exp(&minus;2.128 + 1.264/&delta;) (R2 = 0.98)]