Greenhouse Temperature Research Articles

Automatic control of air temperature in the greenhouse considering the weather forecast data

The paper concerns the problem of improving energy efficiency and the quality of air temperature automatic control in industrial greenhouses. The article proposes a method based on the principle of disturbance compensation using weather forecast data. The plant dynamic model structure is described by the linear 1st order aperiodic link with delay both for the control circuit and for the disturbance circuit. To solve the problem of time delays in the plant mathematical model it is suggested along with the use of outside temperature sensor signal to take into account the weather forecast data for the outdoor temperature changes over the specific forthcoming interval of time. It allows the controller to generate appropriate compensation control signal in advance. The block diagram of the automatic control system of the greenhouse temperature is given. Theoretical mathematical expressions for the regulation algorithm and analysis of regulation quality are obtained and the results of numerical modeling of the temperature control process are presented. The proposed automatic control method can be used to regulate the air temperature in buildings with high requirements for microclimate parameters.

Leaf tip necrosis and seedling leaf rust resistance conditioned by Lr34 in wheat grown at low temperatures

Wheat leaf rust, caused by Puccinia triticina Eriks., is a common and destructive disease of wheat worldwide. The durable leaf rust-resistance gene Lr34 is typically described as an adult plant resistance gene, which is not expressed at the seedling stage at normal greenhouse temperatures. However, Lr34 is expressed at the seedling stage when plants with Lr34 are grown at low temperatures, i.e. approximately 8°C. Lines and cultivars with Lr34 demonstrate a range of responses from near immunity to intermediate reactions on the primary leaf. The Thatcher-Lr34 near isogenic lines ‘RL6058ʹ (Thatcher*6/PI58548) and ‘RL6091ʹ (Tc*6/Chinese Spring) were resistant to a number of P. triticina virulence phenotypes at the seedling stage when grown under these cool conditions, but were susceptible at typical greenhouse temperatures. A double haploid population from a cross between ‘Thatcher’ and ‘RL6058ʹ, previously genotyped for Lr34, was grown at 8°C and screened for leaf rust response at the seedling stage. The population is segregated by a seedling resistance gene that corresponds to the presence of a resistance allele of Lr34. After extended incubation at cold temperatures, the seedling progeny lines with Lr34 also developed distinct leaf tip necrosis; this phenotype was absent in susceptible plants, similar to their reaction as adult plants. When uninfected plants from this population were grown to the adult plant stage at 10°C, those with the Lr34 resistance allele had extensive leaf necrosis and shrunken, sometimes sterile, spikes.

A method for modelling greenhouse temperature using gradient boost decision tree

An accurate environment model is a fundamental issue in greenhouses control to improve the energy consumption efficiency and to increase the crop yield. With the increase of agricultural data generated by the Internet of Things (IoT), more feasible models are necessary to get full usage of such information. In this research, a Gradient Boost Decision Tree (GBDT) model based on the newly-developed Light Gradient Boosting Machine algorithm (LightGBM or LGBM) was proposed to model the internal temperature of a greenhouse. Features including climate variables, control variables and additional temporal information collected within five years were used to construct a suitable dataset to train and validate the LGBM model. An adaptive cross-validation method was developed as a novelty to improve the LGBM model performance and self-adaptive ability. For comparison of the predictive accuracy, a Back-Propagation (BP) Neural Network model and a Recurrent Neural Network (RNN) model were built under the same process. Another two GBDT algorithms, Extreme Gradient Boosting (Xgboost) and Stochastic Gradient Boosting (SGB), were also introduced to compare the predictive accuracy with LGBM model. Results suggest that the LGBM has best fitting ability for the temperature curves with RMSE value at 0.645℃, as well as the fastest training speed among all algorithms with 60 times faster than the other two neural network algorithms. The LGBM has strongly potential application prospect on both greenhouse environment prediction and real-time predictive control.

Combined Effects of Ventilation and Irrigation on Temperature, Humidity, Tomato Yield, and Quality in the Greenhouse

Ventilation and soil moisture influence greenhouse cultivation. Experiments were conducted at Xinxiang Irrigation Research Base of the Chinese Academy of Agricultural Sciences, Henan Province, China, to identify how ventilation and irrigation affected the greenhouse microenvironment. To develop ventilation and irrigation protocols that increase crop yield and improve the quality of drip-irrigated tomatoes grown in the greenhouse, three ventilation modes (T1, T2, and T3) were developed by opening vents in different locations in a completely randomized pattern. T1 had open vents on the north wall and roof of the greenhouse. T2 had open vents on the north and south walls and the roof. T3 had open vents on the north and south walls. Three irrigation treatments (W1, W2, and W3) were designed based on the accumulated water surface evaporation (Ep) of a standard 20-cm evaporation pan. The irrigation quantities were 0.9×Ep (W1), 0.7×Ep (W2), and 0.5×Ep (W3). The spatial and temporal distributions of temperature and humidity were analyzed for different combinations of ventilation and irrigation to identify their effects on tomato yield and fruit quality. Major results were as follows: 1) In addition to solar radiation, ventilation had an important influence on Ep and, on a daily scale, ventilation had a significant effect on Ep (P < 0.05). 2) Ventilation had a significant effect on indoor wind speed, but the effect varied during different growth stages. During the flowering and fruit setting stage, wind speed for T2 significantly differed from those of T1 and T3 (P < 0.01). During the harvest stage, the three ventilation treatments had significantly different effects (P < 0.01). A correlation analysis showed high correlation between T2 wind speed and T3 wind speed (R = 0.831), but low correlation between T2 wind speed and T1 wind speed (R = 0.467). 3) The effect of ventilation on greenhouse humidity and temperature was greater than the effect of irrigation. The differences in air temperature among various combined treatments of ventilation and irrigation were significant for the flowering and fruiting stages (P < 0.05), but they were not significant for the late harvest stage (P > 0.05). There were significant differences in humidity on sunny days (P < 0.01), but no significant differences on cloudy or rainy days (P > 0.05). Air temperature at 2 m was greater than canopy temperature, but humidity at 2 m was less than that at canopy level. 4) Irrigation water quantity was positively correlated with tomato yield and negatively correlated with the fruit quality indicators total soluble solids, vitamin C content, organic acid content, and soluble sugars content. Ventilation had an effect primarily during the harvest period; it had no significant effect on yield (P > 0.05). However, it had a significant effect on vitamin C content and the sugar:acid ratio (P < 0.01). The combination treatment of T2W2 is recommended as the optimal treatment for greenhouse tomatoes using drip irrigation to produce an optimal combination of crop yield and fruit quality. This study provides theoretical and technical support for the improvement of greenhouse climate control by optimizing greenhouse ventilation and irrigation techniques to promote tomato yield and improve fruit quality.

Comparison of Optimized and Conventional Models of Passive Solar Greenhouse—Case Study: The Indoor Air Temperature, Irradiation, and Energy Demand

This study was carried out to optimize a computational model of a new underground passive solar greenhouse to improve thermal performance, storage, and saving of heat solar energy. Optimized and conventional passive solar greenhouse were compared in regards of indoor air temperature, irradiation, and energy demand. Six different materials were used in the conventional model. In addition, TRNSYS software was employed to determine heat demand and irradiation in the greenhouse. The results showed that the annual total heating requirement in the optimized model was 30% lower than a conventional passive solar system. In addition, the resulting average air temperature in the optimized model ranged from −4 to 33.1 °C in the four days of cloud, snow, and sun. The average air temperature in the conventional passive solar greenhouse ranged from −8.4 to 24.7 °C. The maximum monthly heating requirement was 796 MJ/m2 for the Wtype87 model (100-mm lightweight concrete block) and the minimum value was 190 MJ/m2 for the Wtype45 model (50-mm insulation with 200-mm clay tile) in a conventional passive solar greenhouse while the monthly heating requirement estimated 126 MJ/m2 for the optimized greenhouse model. The predictability of the TRNSYS model was calculated with a coefficient of determination (R2) of 95.95%.

بررسی اثرات پیرودکسین، تیامین و اسید فولیک بر ویژگیهای رشدی، زایشی و بیوشیمیایی گوجهفرنگی (.Solanum lycopersicum L) رقم ’دلفوس‘

بررسی اثرات پیرودکسین، تیامین و اسید فولیک بر ویژگیهای رشدی، زایشی و بیوشیمیایی گوجهفرنگی (.Solanum lycopersicum L) رقم ’دلفوس‘

Development and Validation of Air-to-Water Heat Pump Model for Greenhouse Heating

This study proposes a building energy simulation (BES) model of an air-to-water heat pump (AWHP) system integrated with a multi-span greenhouse using the TRNSYS-18 program. The proposed BES model was validated using an experimental AWHP and a multi-span greenhouse installed in Kyungpook National University, Daegu, South Korea (latitude 35.53° N, longitude 128.36° E, elevation 48 m). Three AWHPs and a water storage tank were used to fulfill the heat energy requirement of the three-span greenhouse with 391.6 m2 of floor area. The model was validated by comparing the following experimental and simulated results, namely, the internal greenhouse temperature, the heating load of the greenhouse, heat supply from the water storage tank to the greenhouse, heat pumps’ output water temperature, power used by the heat pumps, coefficient of performance (COP) of the heat pump, and water storage tank temperature. The BES model’s performance was evaluated by calculating the root mean square error (RMSE) and the Nash–Sutcliffe efficiency (NSE) coefficient of validation results. The overall results correlated well with the experimental and simulated results and encouraged adopting the BES model. The average calculated COP of the AWHP was 2.2 when the outside temperature was as low as −13 °C. The proposed model was designed simply, and detailed information of each step is provided to make it easy to use for engineers, researchers, and consultants.

A Method for Greenhouse Temperature Prediction Based on XGBoost Algorithm and Linear Residual Model

Temperature prediction is significant for precise control of the greenhouse environment. Traditional machine learning methods usually rely on a large amount of data. Therefore, it is difficult to make a stable and accurate prediction based on a small amount of data. This paper proposes a temperature prediction method for greenhouses. With the prediction target transformed to the logarithmic difference of temperature inside and outside the greenhouse,the method first uses XGBoost algorithm to make a preliminary prediction. Second, a linear model is used to predict the residuals of the predicted target. The predicted temperature is obtained combining the preliminary prediction and the residuals. Based on the 20-day greenhouse data, the results show that the target transformation applied in our method is better than the others presented in the paper. The MSE (Mean Squared Error) of our method is 0.0844, which is respectively 20.7%, 76.0%, 10.2%, and 95.3% of the MSE of LR (Logistic Regression), SGD (Stochastic Gradient Descent), SVM (Support Vector Machines), and XGBoost algorithm. The results indicate that our method significantly improves the accuracy of the prediction based on the small-scale data.

Changes in Greenhouse Temperature and Solar Radiation by Fogging and Shading During Hydroponics in Summer Season

여름철 수경재배 시 포그 분무와 차광 처리에 의한 하우스 내부의 온도 및 광 변화를 모니터링하였다. 시험 1은 2019년 8월 맑은 날을 기준으로 무처리, 차광, 포그, 포그 + 차광 등 각각 4처리 하였다. 시험 2는 시험 1에서 온도 저감 효과가 가장 좋았던 포그 + 차광 처리를 이용하여 멜론 ‘달고나’, ‘소풍가자’ 2품종에 대해 2020년 여름 기간에 실증 재배를 실시 하였다. 시험 1의 결과 포그 + 차광 혼합처리 시 온도 저감 효과가 뚜렷하여 하우스 내부 온도가 외부 온도보다 가장 낮은 경우 약 4°C 정도 낮게 나타났다. 하우스 내부와 외부의 온도 편차를 살펴보면 포그와 차광 혼합처리에서는 평균 2－4°C 더 낮아졌고, 포그 또는 차광 단일 처리구는 하우스 내부 및 외부 간의 온도 편차가 거의 없었으며, 무처리는 하우스 내부 온도가 외부 온도보다 평균 3－4°C 더 높은 것으로 조사되었다. 하우스 내외부 일사량 변화를 측정한 결과 무처리구와 포그 단일 처리의 하우스 내부 일사량 변화가 비슷하였고, 차광 단일 처리와 포그와 차광 혼합처리의 하우스 내부 일사량 변화가 서로 비슷하였다. 무처리와 비슷한 포그만 처리한 경우 일반적인 비닐 피복재에 의한 하우스 내부 일사량 저하의 영향만 관찰되었다. 특히 포그 + 차광 처리의 경우 차광 단일 처리와 매우 유사한 일사량의 변화가 관찰되었다. 이러한 결과를 바탕으로 2020년 여름에 실증 재배를 한 결과, 8월 외부 기온 최대 36.3°C일 때 냉방 처리 하우스 내부 기온은 32.4°C 정도 유지 되었으며, 약 3.9°C 정도 온도 저감 효과가 있었다. 생산된 멜론의 과중은 1.3－1.5kg 다소 작았으나, 가용성 고형물 함량은 12.6－13.3°Brix로 단맛은 양호한 편이었다. 포그와 차광 혼합 냉방처리를 이용 할 경우 여름철 고온기 온도 저감 효과를 가져 올 수 있고 멜론의 정상적인 생육과 과실 수확이 가능하였다.

Greenhouse temperature control based on Fuzzy Logic

There is a close relationship between crop growth and the control of environmental variables, as well as irrigation and fertilizers supplied. This article presents a system for collecting a greenhouse temperature, capable of acting in the opening or closing window system as a regulator of this environmental variable. Controlling the temperature acting on the opening or closing of the windows is convenient, since it does not require additional fuel, resulting in an economical alternative. Regarding control algorithm, Fuzzy Logic was used as a correction temperature technique. The proposal can be a good option for greenhouses that are not automated yet, saving costs by moving from human-assisted monitoring to automatic temperature monitoring.

Application of Nonlinear Adaptive Control in Temperature of Chinese Solar Greenhouses

The system of a greenhouse is required to ensure a suitable environment for crops growth. In China, the Chinese solar greenhouse plays a crucial role in maintaining a proper microclimate environment. However, the greenhouse system is described with complex dynamic characteristics, such as multi-disturbance, parameter uncertainty, and strong nonlinearity. It is difficult for the conventional control method to deal with the above problems. To address these problems, a dynamic model of Chinese solar greenhouses was developed based on energy conservation laws, and a nonlinear adaptive control strategy combined with a Radial Basis Function neural network was presented to deal with temperature control. In this approach, nonlinear adaptive controller parameters were determined through the generalized minimum variance laws, while unmodeled dynamics were estimated by a Radial Basis Function neural network. The control strategy consisted of a linear adaptive controller, a neural network nonlinear adaptive controller, and a switching mechanism. The research results show that the mean errors were 0.8460 and 0.2967, corresponding to a conventional PID method and the presented nonlinear adaptive scheme, respectively. The standard errors of the conventional PID method and the nonlinear adaptive control strategy were 1.8480 and 1.3342, respectively. The experimental results fully prove that the presented control scheme achieves better control performance, which meets the actual requirements.

Highly Efficient Raindrop Energy-Based Triboelectric Nanogenerator for Self-Powered Intelligent Greenhouse.

Establishing a sustainable energy supply is necessary for intelligent greenhouse environmental management. Compared with traditional energy, green and eco-friendly energy is more conducive to protecting the agricultural production environment. In this study, a fluorinated superhydrophobic greenhouse film is proposed as a negative triboelectric layer material for the construction of a triboelectric nanogenerator that harvests raindrop energy (RDE-TENG). Moreover, an upgraded configuration is adopted, where the bulk effect between the lower/upper electrode and film replaces the interfacial effect of the liquid-solid interface, thereby promoting charge transfer. The results show that the RDE-TENG can serve as a sustainable energy source for greenhouse temperature and humidity sensors that assists in realizing intelligent control of the environment and guides agricultural production processes. This device exhibits high-voltage and a stable output; thus, it has the potential to replace traditional energy sources, which helps toward realizing a self-powered intelligent greenhouse planting mode.

Cultivation of Organics in Controlled Environment Greenhouse

A greenhouse is essentially an enclosed structure, which traps the short wavelength solar radiation and stores the long wavelength thermal radiation to create a favourable microclimate for higher productivity. The sun’s radiation incident on the greenhouse has two parts: direct radiation and an associated diffuse sky radiation. The diffuse part is not focused by the lenses and goes right through Frensel lenses onto the surface of the absorbers. This energy is absorbed and transformed into heat, which is then transported via the liquid medium in copper pipes to the water (heat) storage tanks or, if used, open fish tanks. In this way, an optimal temperature for both plant cultivation and fish production can be maintained. Stable plant growth conditions are light, temperature and air humidity. Light for the photosynthesis of plants comes from the diffuse radiation, which is without substantial fluctuations and variation throughout most of the day. The air temperature inside the greenhouse is one of the factors that have an influence on the precocity of production. The selective collector acts in a more perceptible way on extreme air temperatures inside the greenhouse. Hence, the system makes it possible to avoid the excessive deviation of the temperature inside the greenhouse and provides a favourable microclimate for the precocity of the culture. Sediment and some associated water from the sediment traps are used as organic fertiliser for the plant cultivation. The present trend in greenhouse cultivation is to extend the crop production season in order to maximise use of the equipment and increase annual productivity and profitability. However, in many Mediterranean greenhouses, such practices are limited because the improper cooling methods (mainly natural or forced ventilation) used do not provide the desired micro-climatic condition during the summer of a composite climate. Also, some of these greenhouses have been built where the meteorological conditions require some heating during the winter, particularly at night. The worst scenario is during the winter months when relatively large difference in temperature between day and night occurs. However, overheating of the greenhouse during the day is common, even in winter, requiring ventilation of the structure. Hence, several techniques have been proposed for the storage of the solar energy received by the greenhouse during the day and its use to heat the structure at night. Reviews of such techniques are presented in this article. Air or water can be used for heat transport. The circulating water is heated during the day via two processes. The water absorbs part of the infrared radiation of the solar spectrum. Since the water is transparent in the visible region, they do not compete with the plants that need it. Alternatively, the water exchanges heat with the greenhouse air through the walls. At night, if the greenhouse temperature goes down below a specified value, the water begins to circulate acting as heat transfer surfaces heating the air in the greenhouse.

Innovative Development of Programmable Phase Change Materials and Their Exemplary Application

The research project Fraunhofer Cluster of Excellence “Programmable Materials” aims to develop new materials that can change their properties according to defined boundaries. This article describes the development and use of a novel programmable phase change material (PCM) for latent heat storage applications. At the moment, these PCMs have a programmable trigger mechanism incorporated that activates the crystallization of the material as a reaction to a defined stimulus so that the stored heat is released. In future development stages, programmability is to be integrated on the material level. The latent heat storage that is based on PCMs can be recharged by using the energy of the sun. As an example, for a possible application of such a material, the use of a novel programmable PCM in greenhouses to support heating energy reduction or to reduce the risk of frost is explained. Using the hygrothermal simulation tool WUFI® Plus, the effects in greenhouse constructions without and with commercially available or novel programmable PCMs are calculated and presented in the present article. The calculations are based on the material data of calcium chloride hexahydrate (CaCl2-6H2O), as this material serves as a basic material for the development of programmable PCM compositions. The results of the simulations show a positive impact on the indoor temperatures in greenhouses in view of the risk of frost and the reduction of heating energy. Thus, the vegetation period can be extended in combination with a lower energy load. By an eligible actuation mechanism, an inherent material system for temperature control can be created.

Model Predictive Control versus Traditional Relay Control in a High Energy Efficiency Greenhouse

The sustainable agriculture cultivation in greenhouses is constantly evolving thanks to new technologies and methodologies able to improve the crop yield and to solve the common concerns which occur in protected environments. In this paper, an MPC-based control system has been realized in order to control the indoor air temperature in a high efficiency greenhouse. The main objective is to determine the optimal control signals related to the water mass flow rate supplied by a heat pump. The MPC model allows a predefined temperature profile to be tracked with an energy saving approach. The MPC has been implemented as a multiobjective optimization model that takes into account the dynamic behavior of the greenhouse in terms of energy and mass balances. The energy supply is provided by a ground coupled heat pump (GCHP) and by the solar radiation while the energy losses related to heat transfers across the glazed envelope. The proposed MPC method was applied in a smart innovative greenhouse located in Italy, and its performances were compared with a traditional reactive control method in terms of deviation of the indoor temperature in respect to the desired one and in terms of electric power consumption. The results demonstrated that, for a time horizon of 20 h, in a greenhouse with dimensions 15.3 and 9.9 m and an average height of 4.5 m, the proposed MPC approach saved about 30% in electric power compared with a relay control, guaranteeing a consistent and reliable temperature profile in respect to the predefined tracked one.

Implementation of Fuzzy Logic on Internet of Things-Based Greenhouse

This research is an internet of things-based monitoring system using LoRaWAN and the IoT Thingspeak application server. This research is focused on helping farmers, or the agriculture sector focused on Pakcoy. Pakcoy is a plant that can live at an altitude of 500-1200 meters above sea level using the Greenhouse concept; Pakcoy plants can be protected from pests. Nutrients for Pakcoy are sprayed through the leaves, accelerating the provision of nutrients for plants. The Fuzzy Sugeno method is used to control the Greenhouse temperature and Soil Moisture for effective plant development, as well as monitoring the Greenhouse temperature, soil moisture, and pH of the growing media based on the Internet of Things that uses the Long Range 915 Mhz, therefore, the users can find out in real-time the data can be accessed by using Thingspeak and can be used in areas where internet access is difficult.

A fast and practical one-dimensional transient model for greenhouse temperature and humidity

This paper introduces a new transient greenhouse model which uses a mechanistic method to estimate the temperature and humidity in typical Chinese solar greenhouses. A novel and easy-to-use wall temperature estimation method based on the energy balance was adopted for the environment model rather than using boundary temperature measurements. In this way, the number of model inputs is considerably reduced, and the proposed model is able to predict future greenhouse climate conditions by utilizing only the weather forecast. The model validation was performed in two different greenhouses (each with different sizes and physical parameters, such as the greenhouse volume, the roof and wall areas, the wall materials and so on) on three typical days in 2019 and 2020, and over four consecutive weeks in different seasons during 2016 and 2019 . Promising results were obtained and the model performed well in different operating modes; these included having the vents completely closed, opening the vents, and completely closing the vents in the cold season with an additional thermal insulation blanket covering. The validation results demonstrate that the proposed model can be widely adapted to different sizes of typical Chinese solar greenhouses, as well as to different weather conditions. Thus, the developed model is a flexible and valuable tool that can be used for greenhouse climate simulation, temperature and humidity control, and as a decision-making support system to help manage solar greenhouses.

EVALUATING HOW THE TEMPERATURE CHANGES IN A SUNKEN SOLAR GREENHOUSE

An increasing amount of sunlight is available to sunken greenhouses located in northern China, but it remains unclear how the indoor temperature changes at different heights and at the north and south ends of the structure. To study how the temperature in a single indoor section, at multiple points, varies in a sunken solar greenhouse, 10 measurement lines were arranged in a section 30 m from the west wall. Each line was equipped with a corresponding WT-59 wireless sensor. Temperature and humidity data were collected from 8 March 2019 to 26 December 2019. The following results were obtained. (1) The indoor temperature variation in a day could be divided into four stages: from 0:00 to 7:30 h, the temperature at all measurement points decreased linearly; from 7:30 to 14:30 h, the temperature at all measurement points increased curvilinearly; from 14:30 to 18:00, the temperature at all measurement points decreased curvilinearly; and from 18:30 to 24:00, the temperature at all measurements points decreased linearly. (2) The maximum temperature on sunny days in the greenhouse was higher than that on cloudy days and snowy days, but the maximum temperature on cloudy days and snowy days in the greenhouse occurred 3 h earlier than on sunny days. (3) The lowest average temperature of a sunken solar greenhouse over 3–6 months was 7.5ଌ, without heating. The research results provide theoretical and reference data on how the temperature changes in the interior of a solar greenhouse and inform about the three-dimensional planting height and ventilation times.

AN ESTIMATION METHOD FOR GREENHOUSE TEMPERATURE UNDER THE INFLUENCE OF EVAPORATIVE COOLING SYSTEM

Temperature is one of the most important plant growth parameters that should be controlled in the greenhouses. The present study was aimed to assess the thermal behavior of a greenhouse with and without the fan and pad (FP) evaporative cooling system. A method was developed to approximate the greenhouse temperature based on the mass and energy balance equations. For this purpose, both of the fan and pad evaporative cooling system, and the greenhouse were studied. The results of the theoretical analysis were compared with those achieved by the experiments. Maximum deviations of 5.32, 5.56 and 4.53oC were observed between the theoretical and experimental temperatures of the inside air, the floor and the cover of the greenhouse without the cooling system, respectively. Whereas, the mean absolute error values associated with the predicted temperatures of the greenhouse with the FP system were ranged between 1.50 and 25.67%. Based on the obtained values for the correlation coefficient, root mean square error and mean absolute magnitude error, it was concluded that the models satisfactorily predicted the temperature of the greenhouse components. An air circulation system inside the greenhouse can be proposed to maintain the lumped condition even at the high temperatures, and lead to smaller errors. The results indicated that the inside air, the floor and the cover temperature of the greenhouse reduced by respectively 20.6, 13.0 and 20.6 oC when using the FP system with the air velocity of 4.4 ms-1 and the pad thickness of 6 cm.

CFD Comparative Study Between Different Forms of Solar Greenhouses and Orientation Effect

Only scarce studies that were adopted have considered two properties, the structure safety and energy, where the aero-dynamic and energetic phenomena were taken into account simultaneously in the agricultural greenhouses area. In fact, in this numerical study, the response of the greenhouse has been investigated in outside climate conditions, by considering the orientation relatively to the wind direction velocity and solar trajectory. A resolution of the physical problem combined between the thermal and dynamical fluid flow equations have been based on the Ansys Fluent software. The results showed that the difference between inside and outside air temperature of greenhouse has been strongly affected by the reorientation of the tunnel greenhouse structure, or by the design of the tunnel structure that was adopted in the dome and chapel shape. Moreover, the safety properties of greenhouse structure linked to the drag stress can be developed when based on the interaction fluid-structure analysis. In this view, a temperature profile evolution versus different heights inside greenhouse was highlighted. As well as like continues of our previous study of the drag evolution over tunnel design body proved by the results found in the literature will be compared with chapel and dome designs.