Theses & Dissertations

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    Supply Chain Design of Biocarbon Production from Miscanthus through Hydrothermal Carbonization in Southern Ontario: A Life Cycle Assessment Perspective
    (University of Guelph, ) Mohammad Zamani, Sajad; Dutta, Animesh
    Miscanthus has emerged as a promising energy crop, with successful plantation feasibility demonstrated in southern Ontario. Converting this low-value biomass into valuable biocarbon through hydrothermal carbonization (HTC) presents new opportunities and markets for this feedstock. To promote the scale-up of HTC for biocarbon production from Miscanthus in southern Ontario, an environmentally focused approach was adopted, utilizing various tools and methods to establish diverse supply chain scenarios within the region. Through life cycle assessment (LCA) analysis, it was found that biomass densification at farms did not offer significant environmental benefits in the defined scenarios. However, integrating anaerobic digestion (AD) with HTC resulted in considerably higher environmental advantages compared to using HTC alone. Based on the study's findings, the east side of southern Ontario emerged as the most suitable location for establishing a supply chain dedicated to biocarbon production.
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    Enhancement of Energy Storage Using Extended Surfaces, Composite Materials, Geometric Alterations, and Thermal Diodes
    (University of Guelph, ) Mills, Timothy; Mahmud, Shohel; Tasnim, Syeda
    Thermal management, a historic field from which the first industrial revolution arose in the form the steam engine, continues to be just as important today. Demand for residential and commercial heating and air-conditioning continues to rise while electronics continue to become ever more power dense leading to enhanced cooling demands. Technologies such as phase change material (PCM), thermal diodes, and composite material continue to present opportunities for development to increase thermal performance. Chapter 1 in this thesis focuses on the addition of a novel fin geometry into coconut oil, which operates as a phase change material. The analysis is numerical and is validated experimentally with an investment cast aluminum fin. Chapter 2 analytically investigates the combination of multiple materials into a high-performance semi-infinite body. The performance metric used was the surface temperature of the body at a given point in time for a given applied heat flux. It was found that certain combinations of materials resulted in higher performance than either of their two constituent materials alone. Chapter 3 details the design of a thermal diode using a novel construction where natural convection currents in a fluid are augmented by ferrous particles and an oscillating magnetic field. The resultant asymmetry of the effective thermal conductivity was found to be in excess of 30. That is to say, the directionality of the heat flux through the device caused the thermal conductivity to multiply over 30-fold. Finally, chapter 4 details a numerical study into concrete thermal energy storage. The heat from a block of concrete of elevated temperature is discharged using internal ducts of differing cross section. The result being that the heat transfer was more effective when alternative duct shapes were used when compared with the industry standard circular tubes.
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    Development of non-destructive testing techniques for the detection of glyphosate residue in selected pulses
    (University of Guelph, ) ., SINDHU; Annamalai, Manickavasagan
    Canada is one of the leading producers and exporters of pulses worldwide. Dry beans, dry peas, lentils, and chickpeas are the most common types of pulses cultivated in Canada. The cultivation of pulses relies on the application of several types of pesticides to enhance the productivity by safeguarding pulse crops from pests, weeds, and insects. Among numerous pesticides, glyphosate is one of the most extensively used broad-spectrum systemic herbicides used as a weed control spray or a desiccant. The excessive application of glyphosate on pulses could result in a negative impact on trade, leading to commodity rejection. As a result, the purpose of the study was to investigate non-destructive testing techniques for the detection of glyphosate residues in Canadian-grown pulses at five concentration levels (5 mg/kg, 10 mg/kg, 15 mg/kg and 20 mg/kg). In order to perform non-destructive testing of glyphosate residues in pulses, a standard protocol was developed for the artificial spiking of glyphosate in selected pulses at desired levels. The study involved six pulse types (chickpea, yellow pea, red lentil, large green lentil, French green lentil, and black beluga lentil), four different concentrations (5 mg/kg, 10 mg/kg, 15 mg/kg and 20 mg/kg) and two different solvents (water and water + ethanol (50:50)). The study demonstrated that the highest glyphosate absorption as determined by enzyme-linked immunosorbent assay (ELISA) was observed when water was used as solvent in all pulses and at all concentration levels. The glyphosate residues in the six selected intact pulses were determined using Fourier transform infrared (FTIR) spectroscopy technique. The optimum model was developed using partial least squares regression (PLSR) technique and variable importance in projection (VIP) and selectivity ratio (sRatio) based variable selection method with a correlation coefficient for prediction (R2p) of 0.93, 0.92, 0.96, 0.91, 0.96, and 0.92 whereas a root mean square error of prediction (RMSEP) value of 1.293, 1.402, 0.982, 0.912, 0.984 and 1.302 for yellow pea, chickpea, large green lentil, red lentil, black beluga, and French green lentil, respectively. Similarly, the detection of glyphosate residues in red lentil flour and large green lentil flour was carried out employing FTIR spectroscopy. The VIP-PLSR model worked optimum for both red lentil flour and large green lentil flour, leading to a R2p of 0.931 and 0.985, and RMSEP of 1.385 and 0.757 respectively. The effectiveness of surface-enhanced Raman spectroscopy (SERS) was studied to determine the glyphosate residue levels in intact chickpeas and yellow peas. The PLSR model along with spectral pre-processing showed the maximum accuracy in chickpea and yellow pea with a R2p of 0.95 and 0.99, and RMSEP values of 1.105 and 1.709, respectively. The feasibility of using near-infrared (NIR) hyperspectral imaging (HSI) system in the 900 - 2500 nm wavelength range was studied to detect glyphosate residue levels in intact black beluga lentil, red lentil, large green lentil, and French green lentil. The VIP-PLSR method showed highest performance in the selected lentils with a R2p and RMSEP 0.933 and 1.915 for black beluga lentils, a R2p and RMSEP of 0.925 and 2.066 for red lentils. Whereas, in large green lentil and French green lentil the R2p and RMSEP were 0.940 and 1.741 and 0.941 and 1.726 respectively. Overall, the findings highlight the potential of FTIR, SERS, and NIR HSI techniques for rapid and non-destructive detection of glyphosate content in both intact pulses and pulse flours. The integration of these approaches into commercial milling units could enhance the effective prediction of glyphosate levels in pulse samples. Additionally, these monitoring techniques could play a vital role in ensuring the consistent quality and rigorous adherence to safety standards.
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    Investigation of Defects in an EPP Process Using Statistical Analysis Methods
    (University of Guelph, ) Elkhalifa, Mayada; Moussa, Soha Eid; Moussa, Medhat; Hassan, Marwan
    Given the current defective parts that are being created within the Expanded Polypropylene (EPP) automated machines in automotive manufacturing, a focus was developed to study the EPP process and investigate if defect creation could be anticipated based on sensor readings. Statistical analysis methods are used to analyze data collected from the sensors at an EPP press at a local Guelph auto parts manufacturer. Data were collected from different sensors in the press and were analyzed against the output produced. Linear regression, Pearson correlation, logistic regression, and bi-serial correlation are the four statistical methods used for this study. This research investigates an automotive EPP process to understand how it operates in addition to testing some statistical methods to determine if they could be useful in defect prediction. This study confirmed that not all the statistical techniques used were useful for this application. Of the four methods considered, one, bi-serial correlation was found to give interesting results.
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    Biologically Inspired Approaches to Escape and Rescue of Multiple Robots Based on Neurodynamic Models
    (University of Guelph, ) Li, Junfei; Yang, Simon
    Intelligent escape and rescue are growing research areas to handle emergency situations, such as fires, earthquakes, hurricanes, and military conflicts. Biologically inspired approaches draw inspiration from advantageous biological strategies, mechanisms, and structures for the development of intelligent robotic systems that can autonomously escape threats and rescue targets. Biologically inspired approaches provide promising solutions with improved efficiency of system performance, flexibility in dynamic environments, and robustness to various uncertainties. This thesis focuses on developing novel biologically inspired approaches to escape and rescue of multi-robot systems in dynamic and complex environments. Firstly, a novel evasion strategy is designed for multiple evaders against a faster pursuer in dynamic environments. A neurodynamics-based approach is proposed to approximate the pursuit-evasion game, instead of differential games, which can provide real-time responses to sudden changes in complex environments. Secondly, a novel fish-inspired collective escape approach is developed for multi-robot systems to leave away from threats with limited sensing ability. The proposed neurodynamics-based self-adaptive mechanism enables multi-robot systems with the self-adaptive ability in responding to environmental changes. Finally, a novel feature learning-based bio-inspired neural network (FLBBINN) is proposed to quickly generate a heuristic rescue path in complex and dynamic environments to improve the effectiveness and efficiency of multi-robot systems. Extensive real-robot experiments are conducted to verify the performance of the proposed approaches in real-world environments.