Projects
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Development of a Plant Growth Chamber with Open Source Architectures
Bachelor Thesis
Plant growth chambers are artificially lighted enclosed spaces in which environmental factors are controlled for observing plant responses to them. However, they are devices that usually are costly and not readily available locally. Therefore, it is proposed to develop a plant growth chamber with open-source architectures, capable of achieving preset environmental control to perform plant responses experiments. The engineering adaptive design methodology was applied to construct a prototype with readily available materials and components. The developed prototype allowed for monitoring and controlling environmental conditions such as air temperature, relative humidity, CO2 concentration and plant photoperiod. The system was evaluated with different environmental configurations, nine with no plants and three with plants (cucumber seedlings). The developed device has an operating range of 20 to 40°C and from 2 to 25°C for air temperature on the daylight time and dark time, respectively. For CO2 enrichment it is capable of operating in the range of 400 to 2000 ppm. The web-based user interface allows for the remote monitoring of the climate and the development of the seedlings.
Temperature and Relative humidity prediction in greenhouse using Artificial Neural Networks
Bachelor Internship
The greenhouse microclimate is a typical complicated nonlinear system, which provides the plants with good environmental conditions for growing. Temperature and humidity are considered key factors in greenhouse climate and they are the results of complex and interactive heat and mass exchanges between the inside air and the several other elements of the greenhouse and the outside boundaries. It is hard to build the greenhouse mechanism model with simple mathematical formulas or transform functions.
Sensitivity Analysis of a Chinese Solar Greenhouse climate model
Master Major thesis
The Chinese Solar Greenhouse (CSG) is a type of protected cultivation applied in the northern rural areas of China. For getting an accurate forecast of the inside climate conditions and to be able to implement a controller, it is required to perform a sensitivity analysis as part of the model development process. The objective of this thesis project is to perform the sensitivity analysis of the model developed by Zhou et al. (2020) for estimating the climate inside a CSG, to identify the parameters (greenhouse design parameters) that have the greatest influence on the model output (air temperature). Three different methods were applied and compared. A one-at-a-time (OAT) sensitivity analysis was used to determine the local sensitivities and select a subset of parameters for global analysis. Additionally, a multiple linear regression and a variance-based method were applied for global sensitivity analysis. The study resulted in a ranking on the relevance of the parameters from the CSG climate model. By comparing the outcomes of the different methodologies it was compared the suitability of global sensitivity
analysis and local sensitivity analysis for complex models such as the CSG climate model.
