Greenhouse Model Research Articles

Practical Structural Design and Construction of an Innovative Composite Plastic Greenhouse

A composite plastic material made of recycled Polyethylene terephthalate (PET), Nylon, and glass fiber reinforced Nylon was innovated and applied to the construction of a prototype simple greenhouse in this study. With reference to the mechanical properties of a conventional galvanized steel greenhouse, sectional dimensions of the composite plastic structural members were determined. Structural performances of the conventional galvanized steel and the composite plastic greenhouse models were analyzed under static design wind loads. It was realized that the greenhouse model designed with composite plastic 田-sections of 5 mm wall thickness could have peak displacement response and sectional forces comparable to that of the galvanized steel greenhouse. Therefore, the 田-sections with 5 mm wall thickness were manufactured and used to construct the prototype simple greenhouse. On-site free vibration tests were conducted to estimate the dynamic characteristics of the prototype for validating the design assumptions and assembly procedure. The test results indicated that the prototype had a similar vibration period to that predicted from the numerical model. Moreover, the composite plastic greenhouse could have an average damping ratio of 6.2%.

Experimental analysis of agricultural solar dryer

The drying process is simply the moisture extraction process of a product. It can be achieved with different approaches. In these processes, thermal drying is most widely used for drying agricultural products. This drying systems are normally divided into low and high temperature dryers according to their working temperature levels. In low temperature drying systems, natural-circulation greenhouse model dryers seem the most desirable method for use in remote regions. There are operationally and competitive economically to natural open sun drying. Here solar collector of dimensions (1.25m×1m×0.2m) with area of 1.25m2 has been painted black to absorb solar radiation and the solar drying cabinet that is divided into 3 number divisions separated by four removable shelves. Each shelf is 0.3m wide and 0.5m in length and is composed of a wooden boundary framed nylon wire mesh. For loading and unloading purposes, both sides of the drying chamber walls are sealed with wood and a shutter on the back. During this research, grapes were dried. In the four days after drying, the grapes’ moisture content was decreased from 81.7% to 36.7%. The drying air flows naturally through the commodity. The operating modes are discussed in this research. The results were discussed for designed solar agricultural dryer. Also it involves with the design and fabrication of agriculture solar dryer that can be manufactured in rural areas in an economic way.

Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control

With the global increase in food demand, closed and controlled greenhouses are an essential source for year-round crop production. Maintaining the optimum conditions inside the greenhouse throughout the year is critical to improving crop quality and yield. However, greenhouses consume more resources than other commercial buildings due to their inefficient operation and structure. Therefore, a data-driven model predictive control approach for a semi-closed greenhouse is proposed for temperature control and reducing energy consumption in this study. The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. The greenhouse model's performance is evaluated under varying scenarios, such as increasing the prediction time step and changing the number of samples in the training data set. Results illustrated that the MPC approach had a better temperature control than the greenhouse adaptive control system for winter and summer with an RMSE value of 0.33 °C and 0.36 °C, respectively. Similarly, model predictive control resulted in an energy reduction of 7.70% for winter and 16.57% for the summer season. The proposed model predictive control framework is flexible and can be applied to other greenhouse systems by tuning the model on the new data set.

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%.

Modeling, Design and Construction of a Zero-Energy PV Greenhouse for Applications in Mediterranean Climates

This paper concerns the design, modelling, and construction of a high-efficiency mini PV greenhouse performing as a Nearly Zero Energy Building (NZEB). The greenhouse is equipped with a semi-transparent roof-mounted photovoltaic system (3 kWhp) that feeds an air-source heat pump providing cooling and heating. The PV-generated power can be also stored in a battery. A dynamic simulation model (EPlus) of the real greenhouse is developed to predict its performance and investigate beneficial control strategies. The hourly profiles of different variables (energy, temperatures, illuminance) are deeply investigated. The energy-saving strategies, as reflective shading and controlled natural ventilation, prove to reduce the yearly energy needs by 30%. The energy storage model is developed by the Authors and coupled with hourly solar production. The PV electric model includes the temperature effect on module performance, the inverter efficiency curve, and the battery state of charge. The coupled dynamic analysis shows that the photovoltaic plant meets the air conditioning requirements for 94% of the hours of operation and that the energy surplus could feed the grid with approximately 1355 kWhel per year. The validation of the present model will be possible with future measurements and monitoring of the greenhouse once operating in place.

Intergenerational Facility Alternatives: Transitioning Care Options for Aging Parents and Children with Autism

Purpose: The objective was twofold: 1) summarize research-informed environmental characteristics into Mostafa’s seven ASPECTSS™ criteria for people who are aging, and for children who have autism, and 2) apply those characteristics within the context of a Green House planned intergenerational facility providing support to adult child with autism, and their parent(s). Background: The rate of Autism Spectrum Disorder (ASD) diagnoses is increasing, making it important to design spaces for people with ASD. Approximately 85% of children with ASD live with their parents (Mykyta, 2012). Ahrentzen & Steele (2010) identified the need to develop housing options for people with ASD. Method: Design considerations from a literature review were organized into two tables: 1) aging adults and 2) people who have ASD. Shared characteristics were placed into a third table using Mostafa’s seven ASPECTSS™ criteria, and then applied to the intergenerational facility plan to demonstrate the effectiveness of intentional planning by caregivers and the design community. Results: When integrating Mostafa’s ASPECTSS™ framework, and the intergenerational Green House Model, the application of design choices within housing demonstrates that appropriately designed space can positively impact persons and families with autism, regardless of age. Conclusion: Findings show numerous overlapping design criteria for people with autism and aging adults that can lead to effective environmental solutions for both. This facility type has the potential to minimize family fracture since aging parents are supported in their ability to care for their child with autism.

Computational Fluid Dynamics (CFD) Analysis of Two Types of Greenhouse in Humid Climates in Optimizing Air Flow Distribution for Organic Food Production in Times of Pandemic

In a greenhouse we find multiple variables that have great impacts on crops, for this a CFD model is built to simulate microclimate distribution and obtain optimal climate control for the growth of the crop. Analyzes of solar heat gains, heat losses, and temperature and air distributions for each special moment provide a good guide for product selection. In the CFD simulation the greenhouse volume and wind speed will be obtained for an optimal temperature distribution. The time required for maintenance, the need for sensor calibration, natural deterioration, and unexpected failures will have to be taken into account. The analyzes show a comparison between various variations of the air flow velocity in 0.5 m / s, 1 m / s and 1.5 m / s in two different models of greenhouses, which we will obtain the optimal model for the development and elaboration of a greenhouse. Demonstrating the efficiency of CFD models for the design, simulation and application of greenhouses.

Dynamic Energy Exchange Modelling for a Plastic-Covered Multi-Span Greenhouse Utilizing a Thermal Effluent from Power Plant

To utilize the energy in the thermal effluent, many attempts have been made to use the thermal effluent for agricultural facilities such as greenhouses. As the first step, it is important to estimate the energy loads of the greenhouse for deciding a suitable scale for the heating and cooling. Then, it is available to estimate the energy efficiency of the thermal effluent heat pump system installed in the greenhouse. Therefore, the main objectives of this study were to design and validate an energy model of the experimental greenhouse growing Irwin mangoes and to estimate the annual and maximum energy loads using building energy simulation (BES). Field experiments were conducted in a multi-span plastic-covered greenhouse growing Irwin mangoes to measure the internal environments of the greenhouse and crop characteristics. The energy exchange model of the greenhouse considering crop, cladding, heat pump was developed using BES. The BES model was validated using the data measured at field experiments. The designed model was found to be able to provide satisfactory estimates of the changes of the internal air temperature of the greenhouse (R2 = 0.94 and d = 0.97). The hourly energy loads computed by using the validated model were used to analyse the periodic and maximum energy loads according to the growth stage of the cultivated crops. Finally, the energy costs were compared according to the type of energy source based on the calculated annual energy loads. The average energy cost when using the thermal effluent—heat pump system was found to be 68.21% lower than that when a kerosene boiler was used.

Innovative Communities: A Global Nursing Perspective.

The author in this article explores four innovations in communities that offer a place of welcome and growth while inviting all to see people, including those with intellectual or developmental challenges, elders, persons with dementia, and persons with chronic progressive diseases very differently than is widely assumed. These four innovative communities are L'Arche Homes and Communities, the Green House Model of Long-Term Care, the village of Hogeweyk, Holland, and Lyfebulb. Implications for nursing and healthcare are discussed.

Numerical Modeling of Air Pollutants and Greenhouse Gases Emissions in Intermodal Transport Chains

This paper discusses the most attractive emission compliance options (emission abatement technologies and cleaner fuels) in intermodal transport chains that include short sea shipping. Most studies on emissions-based transport chain comparisons have estimated high levels of nitrogen and sulfur oxide emissions in maritime transportation, decreasing its competitiveness. However, the consequences of regulatory and technological developments and the integration of maritime transport in intermodal transport chains have not yet been considered in detail. In order to address this research gap, a numerical model for computing emissions from different transport modes in an intermodal transport network, under the effect of these developments, is presented that is based on bottom–up emission factors that depend on the fuel type, engine type, and operational profile of each vehicle. Different emissions scenarios are chosen for specific unimodal and intermodal routes (short sea shipping-based) between Portugal and northwestern Europe. Conclusions are drawn on estimated values of air pollutant emissions and greenhouse emissions, in CO2-eq per unit of cargo, in each scenario. These results allow the identification of the most environmentally friendly transport chains, thus supporting the development of adequate transport policies.

Incorporating cultivar-specific stomatal traits into stomatal conductance models improves the estimation of evapotranspiration enhancing greenhouse climate management

The effect of considering cultivar differences in stomatal conductance (g s ) on relative air humidity (RH)-related energy demand was addressed. We conducted six experiments in order to study the variation in evapotranspiration (ET c ) of six pot rose cultivars, investigate the underlying processes and parameterise a g s -based ET c model. Several levels of crop ET c were realised by adjusting the growth environment. The commonly applied Ball–Woodrow–Berry g s -sub-model (BWB-model) in ET c models was validated under greenhouse conditions, and showed a close agreement between simulated and measured ET c . The validated model was incorporated into a greenhouse simulator. A scenario simulation study showed that selecting low-g s cultivars reduces energy demand (≤5.75%), depending on the RH set point. However, the BWB-model showed poor prediction quality at RH lower than 60% and a good fit at higher RH. Therefore, an attempt was made to improve model prediction: the in situ -obtained data were employed to adapt and extend either the BWB-model, or the Liu-extension with substrate water potential (Ψ; BWB-Liu-model). Both models were extended with stomatal density (D s ) or pore area. Although the modified BWB-Liu-model (considering D s ) allowed higher accuracy (R 2 = 0.59), as compared to the basic version (R 2 = 0.31), the typical lack of Ψ prediction in greenhouse models may be problematic for implementation into real-time climate control. The current study lays the basis for the development of cultivar specific cultivation strategies as well as improving the g s sub-model for dynamic climate conditions under low RH using model-based control systems. • Relative air humidity control is a key but costly aspect of greenhouse climate. • Accurate estimation of evapotranspiration (ET c ) is essential for relative air humidity regulation. • Six pot rose cultivars and several cultivation regimes were used. • ET c estimation was improved using cultivar-specific stomatal conductance parameters. • The use of low-stomatal conductance cultivars secures energy saving (2.5–5.75%).

Разработка модульного программно-аппаратного комплекса управления стендом с моделью космической оранжереи

Space greenhouses (SG) that can be used for enriching the astronauts’ diet are also considered a means of improving the astronauts’ life environment in autonomous crewed expeditions. One of the main requirements for SC is to minimize the specific consumption of the main onboard resources: energy, space, refrigerant, and labor-hours per unit mass of grown product. Experiments on adaptive optimization of irradiation and illumination spectrum were performed and a hardware and software complex (HSC) was developed to control the test-stand with the SG model. The main object of control is an intermittently pressure-sealed chamber with temperature and humidity sensors, as well as an IR gas analyzer. The latter determines the visible photosynthesis of the plants based on the dynamics of CO2 absorption. The sensors and actuators are connected to a Mega 2560 AVR microcontroller connected to a Raspberry Pi 4B single-board computer via a USB-UART converter. The modular software package was created on the basis of the ROS (Robot Operating System) framework, which minimizes the training period for new developers and experiment operators. The first HSC versions were successfully tested on a test-stand with Chinese cabbage to find the trajectory of optimal lighting parameters during the growth process. The HSC made it possible to carry out several replications of a 2-factor experiment to study the drift of the optimal LED lighting modes during a 10 days’ period with daily variation of 2 factors — the current in the red LED circuit and the current in the white LED circuit. Optimal change patterns in the lighting parameters for a test-stand with a space greenhouse model were obtained.

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.

The influence of greenhouse support structures on ion flow field under overhead high voltage direct current lines

When an overhead high voltage direct current (HVDC) line is near a greenhouse, surface charges on the dielectric film distort the electric field nearby. Extensive experimental researches have been conducted regarding charge characteristics, and various algorithms have been proposed to calculate the ion flow field considering the charged film. However, existing studies do not consider the greenhouse support structures. In this paper, based on the ion flow field simulation with charged film, a more complete greenhouse model considering support structures is built. The support structures are treated as grounded conductors. Experimental results agree well with the calculations. Then, the influences of the frames and the wall (two typical types of support structures) are analyzed separately. The analysis considers the frame radius, position, and number, as well as the wall position and width. The total electric field is divided into three parts by charge sources, the effects of which are analyzed separately. The co-effect of the two kinds of support structures is also analyzed. The calculations show that the support structures, which are conductive and grounded, can effectively reduce the ground-level electric field. This research can predict the absolute value and help us understand the characteristics of the actual electric field near a greenhouse built under overhead HVDC lines.

Greenhouse Climate Controller by Using of Internet of Things Technology and Fuzzy Logic

The Internet of Things (IoT) is a new, ongoing revolution. It often uses wireless sensor network (WSN) technologies because these technologies are among the most important solutions for monitoring and controlling the systems. This article provides a model of a smart greenhouse. In this regard, the main contribution of this paper is an innovative implementation of a micro-climate controlled environment for optimal plant growth, based on loT technology and using a fuzzy logic controller. Using this system, we attempted to optimize the functionality of the system proposed by exploiting an Arduino UNO board for data acquisition and processing. The input variables are analog values captured by ZigBee wireless network sensors that are then processed using fuzzy logic control software with heating and extractor control signals. At the same time, all data were sent to the server through a Wi-Fi internet connection, which permitted remote monitoring and analysis of the data via a web browser with tablets, smartphones, and laptops. Results show that the choice of a fuzzy logic controller could promote a comfortable greenhouse micro-climate. Also, we showed the efficiency of our proposed solution for greenhouse climate remote monitoring anywhere via IoT technology.

Thermal Model Development of a Biomass Regenerated Desiccant Supported Greenhouse Cooling for Orchid Cultivation

In this paper, a novel scheme of biomass regenerated desiccant supported greenhouse cooling with distributed fan-pad evaporative system has been proposed. The system aims to provide suitable thermal condition inside the greenhouse for cultivation of high value flowers like varieties of Orchid which require a temperature between 21 °C to 26 °C and humidity from 50 to 70% for the sub-tropical climate prvailing in the plains of India. In the proposed system two stage desiccant based cooling is used to obtain a low humidity ratio. A biomass based heating system is coupled for regeneration of the desiccant. Thermal modeling of desiccant wheel and greenhouse are done to estimate air temperature inside the greenhouse. A comparative study has been made based on estimated greenhouse air temperature with the results of the reference model available in the literature. From the performance analysis of the proposed system, it is revealed that the maximum temperature of the greenhouse air can be restricted within 25 °C and 25.8 °C for a hot and humid day prevailing in the month of July and September respectively. However the system can maintain a lower temperature of 19 °C during the morning time which is more conducive for target plantation (Orchid) in the given region.

Prediction Error-Driven Memory Consolidation for Continual Learning: On the Case of Adaptive Greenhouse Models

This work presents an adaptive architecture that performs online learning and faces catastrophic forgetting issues by means of an episodic memory system and of prediction-error driven memory consolidation. In line with evidence from brain sciences, memories are retained depending on their congruence with the prior knowledge stored in the system. In this work, congruence is estimated in terms of prediction error resulting from a deep neural model. The proposed AI system is transferred onto an innovative application in the horticulture industry: the learning and transfer of greenhouse models. This work presents models trained on data recorded from research facilities and transferred to a production greenhouse.

Design and simulation of a control for the opening and closing of the side ventilation windows in a greenhouse

An optimal control for the opening and closing of the side ventilation windows of a greenhouse can be obtained from a mathematical model of the crop and the greenhouse. In the greenhouse model, control input is the ventilation, and to carry out the instrumentation in the immediate future, this term we related with the aperture of the lee and windward side ventilation windows. We consider a model with four states variables: the structural biomass of leaves, the structural biomass of fruit, the nonstructural biomass (nutrients) and the carbon dioxide. Even though the control of carbon dioxide concentration inside the greenhouse is not directly addressed in this study, optimal control of the opening and closing of vents significantly complements the regulation of the carbon dioxide concentration. To apply the optimal control theory, we select a functional cost in order to increase the benefit of the farmer.

Modeling of Seawater Greenhouse by a block diagram environment program and an equations solver program and simulations on different Moroccan locations

Modeling of Seawater Greenhouse by a block diagram environment program and an equations solver program and simulations on different Moroccan locations

옥상온실과 통합된 소규모 호텔의 냉/난방 부하 산정을 위한 에너지 해석에 관한 연구

This study conducted a building energy simulation (BES) to compare the heating and cooling loads of a stand-alone greenhouse with a small hotel with an integrated rooftop greenhouse. The TRNSYS program was used to calculate the heating and cooling loads of the buildings. Numerical simulations were conducted for the stand-alone greenhouse model, a stand-alone small hotel model, and a small hotel with an integrated rooftop greenhouse model to compare the heating and cooling loads of each building. The results showed that the heating loads and total loads of the integrated model were reduced 20% and 15.7% than stand-alone model, respectively. Furthermore, if the temperature setting of the greenhouse was changed for different vegetables, the heating and cooling loads of the buildings varied. The setting temperature for high-temperature vegetables showed the largest energy reduction in the heating and cooling loads of the buildings. In conclusion, the integrated rooftop greenhouse had the advantage of energy reduction when it was installed on a conventional small hotel.