Mechanical Engineering

Permanent URI for this collectionhttps://hdl.handle.net/10315/34419

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  • Item type: Item , Access status: Open Access ,
    Investigation and Characterization of the Optical, Thermal, and Adsorption Properties of Carbon Aerogels for CO2 Capture Applications
    (2026-03-10) Heidari, Parham; O'Brien, Paul G.
    Climate change driven by rising atmospheric CO₂ concentrations has intensified the need for efficient, regenerable solid sorbents. Carbon aerogels are promising candidates due to their ultra-high porosity, low density, and tunable structure, yet their coupled optical, photothermal, and CO₂ adsorption behaviour as monolithic sorbents remains insufficiently characterized. This thesis investigates a disc-shaped carbon aerogel for CO₂ capture under flue-gas-like conditions to clarify how its radiative and thermal properties govern adsorption performance and photothermal regeneration. The aerogel was characterized using UV–Vis–NIR and FTIR spectroscopy to measure reflectance, transmittance, and absorptance across the solar and thermal-infrared ranges. Mid-wave infrared thermography under a xenon arc lamp (1 Sun irradiance) quantified transient heating and cooling. Dynamic breakthrough experiments with a 11% CO₂ / 89% N₂ mixture at 25 °C, followed by photothermal desorption at 110 °C, were performed to determine CO₂ capacity and regeneration performance. Optical measurements showed negligible transmittance and low reflectance from the ultraviolet through the mid-infrared, corresponding to broadband absorptance generally above 0.9 and high effective emissivity in the thermal-imaging band. Under 1 Sun illumination, the surface temperature rose from ~28 °C to ~64 °C within 1–2 min and cooled rapidly back toward ambient once the light source was removed, indicating efficient radiative heating and low thermal mass. Breakthrough measurements yielded a net CO₂ adsorption capacity of 1.88 mmol g⁻¹ and a photothermal desorption capacity of 1.14 mmol g⁻¹, with good reproducibility but partial hysteresis between adsorption and desorption. Overall, the results demonstrate that carbon aerogels can combine meaningful CO₂ uptake with favourable photothermal characteristics, making them strong candidates for radiatively driven temperature-swing adsorption processes. The work provides a quantitative baseline for future material design, further characterization, and reactor-level optimisation of carbon-aerogel-based CO₂ capture systems
  • Item type: Item , Access status: Open Access ,
    What limits the greater adoption of 3D printing in Canada? Identifying the Barriers to the Adoption of 3D printing in Canada
    (2026-03-10) Di Scipio, Nicholas; Maxwell, Andrew L.
    Despite significant advances in materials, equipment, and applications, the adoption of 3D printing in Canadian manufacturing remains limited, with most firms restricting its use to prototyping rather than full-scale production. This thesis investigates why this gap persists by examining the economic, technical, organizational, and cultural factors shaping adoption decisions. Drawing on semi-structured interviews with industry stakeholders across manufacturing firms, suppliers, and supporting organizations, the study combines empirical insights with established technology adoption theories, including the Technology Acceptance Model, Diffusion of Innovation, and the Product Adoption Process. The findings show that slow adoption is not driven by technical limitations alone. Instead, adoption is influenced by interconnected perceptions of risk, cost, capability, and organizational readiness, reinforced by conservative decision-making cultures, limited internal expertise, and uncertainty around qualification and certification. Customer expectations related to lead time, customization, and reliability further shape adoption behavior, either accelerating experimentation or reinforcing risk aversion. Regional infrastructure differences and ecosystem maturity also affect firms’ ability to progress beyond trial use. Based on these findings, the thesis proposes a synthesized adoption framework that captures adoption as an iterative, feedback-driven process rather than a linear sequence. The framework integrates individual perceptions, organizational conditions, and external pressures to better reflect real-world adoption dynamics. This research contributes a practical and theoretically grounded lens for understanding 3D printing adoption in Canada and provides a foundation for future research, policy development, and industry strategies aimed at supporting broader and more sustained adoption.
  • Item type: Item , Access status: Open Access ,
    Photothermal Lateral Flow Assay with Inertial Microfluidic Enrichment for Early Detection of E. coli in Urinary Tract Infections
    (2026-03-10) Ghazi, Yasaman; Rezai, Pouya
    Escherichia coli is the leading cause of urinary tract infections (UTIs), yet rapid and specific diagnosis at the point of care remains challenging. Conventional diagnostic methods, including urine culturing and microscopy, are time-intensive, require trained personnel, and often lack specificity for E. coli, limiting their effectiveness in resource-limited or time-critical settings. While lateral flow assays (LFAs) offer simplicity and portability, their clinical utility is constrained by a high visual limit of detection (LOD). This thesis presents an integrated diagnostic platform that combines passive microfluidic bacterial enrichment with photothermal detection to significantly improve LFA sensitivity for UTI diagnostics. Bacterial preconcentration was achieved using viscoelastic forces generated by flowing polyethylene oxide (PEO) solutions through custom-fabricated PDMS microchannels with straight, symmetric zigzag, and asymmetric zigzag geometries. Optimal enrichment was obtained in a straight 25 µm × 25 µm channel operated at 2 µL/min with 1000 ppm PEO, resulting in approximately an order-of-magnitude increase in bacterial concentration through sample volume reduction while retaining target cells. In parallel, a photothermal detection approach based on lock-in thermography was developed to detect temperature modulations arising from nanoparticle–target interactions on LFA test and control lines. This method enabled quantitative signal extraction beyond visual inspection and provided an additional two-order-of-magnitude sensitivity enhancement. Together, the integrated enrichment and photothermal detection platform achieved an overall ~1000-fold sensitivity improvement compared to standard visual LFAs. These results demonstrate the strong potential of combining passive microfluidic preconcentration with photothermal readout for rapid, sensitive, and reliable point-of-care UTI diagnostics. Identified limitations include manual operation, reliance on desktop-based processing, and pressure constraints of PDMS microchannels. Future work should focus on validation with clinical urine samples, platform automation with onboard fluidic and signal processing, evaluation of rigid microchannels for higher-pressure operation, and extension to additional bacterial pathogens and diagnostic applications.
  • Item type: Item , Access status: Open Access ,
    Development of Emissive Porous Polymers and Parabolic Trough Underside Reflectors for Enhanced Radiative Cooling
    (2026-03-10) Chiu, Po-Chun; O'Brien, Paul G.
    A trough-enhanced radiative cooling (RC) system was developed and experimentally evaluated to achieve high-efficiency passive cooling under real outdoor conditions. Polymer-based porous PVDF-HFP emitters with high solar reflectance and strong atmospheric emittance were fabricated and integrated with parabolic trough reflectors. Monte Carlo ray tracing and heat balance simulations were conducted to predict temperature performance under various solar irradiance and convection scenarios. The experimental results revealed stable sub-ambient cooling of 1.2–4.2 °C during the day and up to 4 °C at night, demonstrating consistent cooling even under partial cloud coverage. Numerical predictions agreed well with measurements, showing less than 1 °C deviation, indicating the model’s reliability in evaluating RC performance. The validated model enables predictive design and optimization of trough-integrated RC systems, while the findings highlight the potential of reflective geometries in enhancing cooling power and scalability for energy-efficient thermal management and sustainable building applications.
  • Item type: Item , Access status: Open Access ,
    Development of a Self-Heating Consolidation Procedure for 3D-Printed Continuous Wire Polymer Composite Laminates
    (2026-03-10) Barbuio, Thomas John; Melenka, Garrett; Kempers, Roger
    The voids in 3D-printed continuous wire polymer composites (CWPCs) reduce the wire-polymer adhesion, which can decrease their strength and stiffness and their in-part sensing accuracy. This thesis shows the development, implementation and effects of a consolidation procedure to reduce the voids in unidirectional and cross-ply 3D-printed CWPC laminates. The consolidation procedure used resistive heating combined with hot-pressing to reduce the internal voids. Image processing of sample cross sections proved the void content in consolidated samples were 91.6% lower compared to unprocessed, while flexural tests found 5% and 12% higher flexural strength and stiffness respectively. Next, the effects of the consolidation procedure were tested on the uniaxial tensile properties of unidirectional and cross-ply 3D-printed CWPC samples, showing promising results for transverse reinforced CWPC samples. The results of the two studies performed showed that the consolidation procedure significantly reduces the void content of the samples, and thus positively impacts the mechanical properties.
  • Item type: Item , Access status: Open Access ,
    Laser-Carbonized Graphene and Lignin Films for Sustainable Transient RFID Electronics
    (2025-11-11) Khan, Juveiria; Rizvi, Reza
    The growing problem of electronic waste calls for new materials that are sustainable and easy to recycle. This thesis focuses on developing conductive films for transient and flexible electronics using two different material systems. In the first part, cellulose paper was used as a biodegradable base. Three types of coatings were prepared: (i) graphene oxide (GO), (ii) GO with ascorbic acid (AA) as a reducing agent, and (iii) GO with a mixture of ascorbic acid and sodium lignosulfonate (Na-Lgs) to provide extra carbon content. After coating, the samples were treated with a laser to create conductive patterns directly on the cellulose. This study shows that cellulose can serve as a compostable material for electronics while still offering useful electrical properties. In the second part, polyethylene terephthalate (PET) films were coated with compressible flow exfoliated (CFE) graphene. PET provided strength and flexibility, while the graphene coating gave an initial conductivity that was further improved by laser carbonization. The PET/CFE system achieved very low sheet resistance, with the best value recorded at 16.17 Ω/sq, showing excellent electrical performance compared to many earlier studies. To evaluate both systems, several techniques were used: SEM to study the surface and cross-section of the films, TGA to test thermal stability, Raman spectroscopy to analyze graphitic structure, FTIR to confirm chemical changes, and sheet resistance measurements to check electrical performance. Overall, the results show two promising directions: cellulose-based films for biodegradable and eco-friendly devices, and PET/CFE graphene films for high conductivity and robust performance. In particular, the PET/CFE graphene system, with its low sheet resistance, shows strong potential for further development towards commercial RFID tags and other high-performance flexible electronic devices.
  • Item type: Item , Access status: Open Access ,
    Automated Micro-CT Image Segmentation and Void Analysis of HDPE-HGM Syntactic Foams Using Machine Learning
    (2025-11-11) Shiv Shankar, Riya Vasan; Melenka, Garrett; Rivzi, Reza
    Syntactic foams are a subclass of composite materials in which the matrix is embedded with hollow microspheres, offering a high strength-to-weight ratio suitable for the aerospace, marine, and automotive industries. The microspheres create porosity, visually indistinguishable from voids caused by manufacturing during imaging, both of which influence mechanical performance. Quantification and classification are, therefore, crucial for quality control and predictive modelling. This thesis proposes an integrated pipeline utilizing micro-CT imaging and unsupervised learning to segment and quantify voids, particles, and matrix in HDPE-HGM syntactic foams. A hybrid segmentation technique leveraging slice-wise thresholding and K-means clustering resulted in an F1 score of 0.92 compared to LabKit for voids. Voids were further classified into raster voids and HGM cavities based on shape descriptors, with subsequent spatial analysis performed using the R-index and clustering coefficients. Morphological features were correlated to Ultimate Tensile Strength and Young's Modulus. A custom GUI enables 3D visualization and segmented mesh export, facilitating the creation of digital twins for enhanced material analysis and process optimization.
  • Item type: Item , Access status: Open Access ,
    Electrochemical Microfluidic Sensors with Integrated Ion-Selective Polymer Membranes for the Detection of Trace Ions in Water
    (2025-11-11) Oseyemi, Ayobami Elisha; Rezai, Pouya
    There is an increasing demand for low-cost, portable, and sensitive sensing technologies for detecting trace levels of metal ions in water to support public health, environmental monitoring, and energy applications. Traditional analytical methods, while accurate, are limited by their reliance on bulky equipment, high cost, and complex electrode modification, making them unsuitable for real-time or on-site use. This research addresses these limitations by developing a microfluidic electrochemical sensor platform that integrates in-situ synthesized, stand-alone ion-imprinted polymer (IIP) membranes for the selective detection of sodium (Na⁺), lead (Pb²⁺), and lithium (Li⁺) ions in water. The study employed a stepwise methodology: an ion-selective polymer membrane was first developed to detect salinity, achieving a 28-fold sensitivity improvement and a detection limit of 0.45 ppm. Next, a Na-IIP membrane using 15-crown-5 as an ionophore achieved 58 ppb detection with over threefold sensitivity enhancement. Finally, Pb-IIP and Li-IIP membranes were developed, attaining detection limits of 7.3 ppb and 168 ppb, respectively, with high selectivity over competing ions. All configurations demonstrated high reproducibility, multi-ion selectivity, and recovery rates ranging from 69% to 109% in municipal tap water. The stand-alone membrane design simplifies fabrication, enhances stability, and is compatible with continuous-flow operation. This work advances the development of scalable, point-of-need sensing systems and offers a foundation for future multiplexed and automated water quality monitoring platforms.
  • Item type: Item , Access status: Open Access ,
    Low Reynolds Number Settling of Cylindrical Rods with Various Geometries in a Quiescent Fluid
    (2025-11-11) Hamidi, Amirhossein; Hanson, Ronald
    This dissertation is motivated by the atmospheric transport of microplastic fibres, a growing environmental concern. The atmosphere is recognized as a major pathway for the long-range transport of microfibres. However, many atmospheric simulations simplify fibre geometry, often representing them as volume-equivalent spheres or straight cylinders, despite the more complex shapes observed in microfibre samples from atmospheric deposits. This research aims to enhance our understanding of the settling behavior of curved, V-shaped, U-shaped, and S-shaped cylindrical rods within the Reynolds number and aspect ratio range associated with the atmospheric transport of microfibres. A series of experiments were conducted using millimeter-scale metal rods with aspect ratios ranging from 10 to 120, settling in a quiescent water-glycerin chamber to replicate Reynolds numbers below 7. A stereo-PTV system was employed, with two side cameras tracking terminal settling velocities and orientations, while a bottom camera captured potential spinning motions. Using a three-dimensional calibration algorithm, the terminal velocities and orientations of the rods were determined in real-life space. Results demonstrate that curved and V-shaped rods settle faster than straight rods of the same dimensions, with V-shaped rods settling only slightly faster than curved rods of equivalent projected length. U-shaped rods exhibit a transition in orientation from vertical to oblique above a critical Reynolds number or below a critical middle arm length ratio. They consistently settle faster than straight rods because of their non-zero inclination angle. Furthermore, their terminal velocity either peaks at a specific aspect ratio or remains constant due to a trade-off between side arm length and rod inclination. S-shaped rods exhibit spinning motions at a constant rate while settling at the same velocity as the straight rods of identical dimensions. Their spinning rate peaks at an intermediate middle arm length ratio, which was experimentally and theoretically investigated. New models were developed to estimate the terminal velocity of rods with these geometries, which can also be applied to predict the terminal velocity and the horizontal travel distance of microfibres of various shapes. This study highlights the crucial role of fibre morphology in determining vertical terminal velocity and, consequently, horizontal dispersion in the atmosphere.
  • Item type: Item , Access status: Open Access ,
    Revitalizing Simulations of Colloidal and Interfacial Systems: From Atomistic Trajectories to Data-Centric Insights
    (2025-11-11) Imani Parashkooh, Hasan; Jian, Cuiying
    This dissertation advances methodological frameworks for investigating complex systems characterized by competing interactions. Structured around three interrelated themes, the research develops methods to tackles challenges in water-in-oil emulsions, chemical inhibition in asphaltene aggregation, and adsorption energy prediction. While each theme addresses unique challenges, they all contribute to quantitative understanding of interactions across scales, integrating structural, thermodynamic, and energetic perspectives to establish governing principles for system behavior. The first theme elucidates the interplay between asphaltene aggregation and water-in-oil droplet coalescence. Molecular Dynamics (MD) simulations conducted in pentane solvents reveal the mutual influences of asphaltene and water droplets, highlighting a nonmonotonic trend in polyaromatic stacking with increasing droplet sizes. An innovative in-house tool is introduced to analyze droplet coalescence modes, demonstrating that droplet growth predominantly occurs around a nucleation site, which is the largest droplet. In the second theme, a novel approach for calculating partial molar volumes (PMVs) directly from MD simulation trajectories is presented. This approach has been validated against experimental data, yielding an average error of 4.41%. When applied to systems containing model asphaltenes, organic solvents, and chemical inhibitors, the PMV analysis elucidates molecular-level inhibition mechanisms. Specifically, it shows that inhibitors enhance solubility by altering nanoaggregate size and number, with their polar and nonpolar segments interacting with different regions of the asphaltene molecules and the solvent. The third and final theme highlights the critical need for efficient and accurate adsorption energy predictions, a fundamental aspect of catalysis, materials design, and a key factor in mitigating asphaltene deposition. Traditional methods of calculating adsorption energy such as Density Functional Theory (DFT) are computationally demanding, particularly for large, complex adsorbates like aromatics. To overcome these limitations, this work applies pretrained graph neural networks (GNNs) with a directional message passing architecture. The model is trained to capture geometric relationships between small adsorbates and metallic or metal oxide surfaces, linking them to energy and atomic forces. Here, it is fine-tuned to adapt these learned interactions for larger molecules, including aromatics. Two curated datasets, a diverse adsorbate-substrate collection and a specialized aromatic subset, are employed to balance generalizability with specificity. Results indicate that the sheer volume of fine-tuning data has a greater impact on model adaptation than using smaller but more domain-specific datasets. Moreover, the results show that selectively fine-tuning the early layers, which focus on geometric features, achieves performance comparable to full model retraining. This highlights the crucial role of geometric feature adaptation. Collectively, these themes contribute to the refinement of data-driven methodologies for complex interfacial and amorphous systems, providing actionable insights into structural, thermodynamic, and energetic properties that were previously inaccessible. Nano-scale simulations with extensive temporal and spatial sampling are essential, as competing interactions make it impossible to predict dominant factors without comprehensive analysis. By reutilizing existing simulation data, the innovations presented here enhance sustainability and efficiency, with broad implications for physical chemistry, materials science, and industrial applications.
  • Item type: Item , Access status: Open Access ,
    Vision Tracking System for In-Situ Tissue Bioprinting
    (2025-11-11) Zakharova, Kateryna Viktorivna; Czekanski, Aleksander
    Maintaining printing accuracy despite the constant motion is one of the main difficulties in printing on moving surfaces. Traditional 3D printers are made for stationary platforms. Changing them to work on dynamic surfaces calls for the creation of new control algorithms and methodologies. In-situ (from Latin: in its original place) printing refers to a process where bioprinting or additive manufacturing technologies are used directly at the site of application. The core component of our vision tracking system is a real-time algorithm powered by a Deep Learning model that monitors the printing surface – a harmed part of the human body. This system relies on advanced Computer Vision technologies to accurately track the moving surface's position and orientation. Our experiments in simulations proved the concept of the robot's ability to adjust to a dynamic environment. A multi-camera system and a 6-DOF robot arm are included in the experimental setup of this research.
  • Item type: Item , Access status: Open Access ,
    Improvements in Microfabrication of Integrated Collagen Scaffolds Containing Embedded Microchannels Inside 3D Extracellular Matrix with 2D Basement Membrane Linings
    (2025-11-11) Ali Maghzian; Rezai, Pouya
    Collagen's biocompatibility, biodegradability, and cell-adhesive properties make it vital for developing biomimetic scaffolds in tissue engineering. This thesis enhances the microfabrication of collagen scaffolds with micro-conduits, mimicking the Extracellular Matrix (ECM). These scaffolds feature a 3D porous collagen sponge, mimicking the interstitial matrix, with embedded microchannels with varying widths (70-1000 μm) resembling veins and vessels and micropatterns, as well as a 2D collagen film lining the microchannel walls that mimic the basement membrane. Through soft lithography, freeze-drying, and contact printing, scaffolds with enclosed macrochannels in multiple layers were created and reinforced with composite effects of components and crosslinking. Characterization methods included microscopy, ImageJ analysis, optical profilometry, flow studies, and SEM imaging. Factors influencing scaffold flatness and achievable microchannel dimensions were investigated in a parametric study. Preliminary cultures evaluated scaffold viability for culturing mice brain tissue and studying various cell behaviors, including HEp2, HEp2D and HEK 293T cell lines. These scaffolds offer customizable physical characteristics for diverse tissue applications, facilitating blood vessel modeling, cell co-culture, and drug delivery studies.
  • Item type: Item , Access status: Open Access ,
    Design, Fabrication, and Experimental Characterization of a Focusable Solar Simulator for High and Low Flux Solar Thermal Applications
    (2025-07-23) Badaloo, Rajiv Motilal; Cooper, Thomas
    High-flux solar simulators (HFSS) advance solar thermal research but are traditionally costly and complex, limiting access for smaller institutions. This thesis presents a low-cost, adaptable solar simulator using commercially available xenon arc cinema searchlights and Fresnel lenses for dynamic irradiance control. The system was characterized through direct flux measurements with a pyranometer and indirect flux mapping via a CMOS camera, enabling detailed analysis of irradiance distribution, temporal stability, and efficiency. Experimental results showed an average irradiance of 2819 W/m² over a 12×12-inch area, peak irradiance of 2348 kW/m² with Fresnel lens concentration, and efficiencies up to 22.4% at full intensity. Real-world tests on radiative cooling coatings confirmed the simulator's capability to replicate concentrated solar conditions accurately. This study demonstrates a scalable, practical alternative to traditional HFSS, enhancing accessibility for smaller research facilities and laying a foundation for future multi-lamp and advanced optical configurations.
  • Item type: Item , Access status: Open Access ,
    The Impact of Entrepreneurship Education on the Development of Entrepreneurial Intention Among Engineering Students: The Mediating Role of Entrepreneurial Mindset and Self-Efficacy.
    (2025-07-23) Seyedalikhani, Fatemehsadat; Maxwell, Andrew L.
    This thesis explores how entrepreneurship education (EE) influences the development of entrepreneurial intention (EI) among engineering students, specifically examining the mediating roles of entrepreneurial mindset (EM) and entrepreneurial self-efficacy (ESE). Considering the growing global importance of innovation and entrepreneurial skills, the study investigates the degree to which EE enhances EI by fostering EM and strengthening ESE. Using a quantitative survey of 431 engineering students at York University’s Lassonde School of Engineering, the study applied structural equation modeling to examine the direct and indirect effects of EE on EI through EM and ESE. Our findings show that EE significantly enhances EI, with both EM and ESE positively mediating this relationship. In this research, we investigated the impact of entrepreneurship education on entrepreneurial mindset and on entrepreneurial intention. In reality this relationship is more complex, and causality might be in the opposite direction. Future research should investigate the interplay between these entrepreneurial components and the iterative nature of their evolving relationships. This highlights the value of integrating EE into engineering curricula to develop the EM needed in today’s technology-driven world. The research contributes to existing literature by quantifying EE's impact on EI and offers practical implications for educational policy and curriculum development, advocating for the continued inclusion of EE to effectively prepare engineering students for entrepreneurial careers and foster economic innovation and growth.
  • Item type: Item , Access status: Open Access ,
    Comprehensive Lifecycle Assessment of Direct Air Capture Systems for Carbon-Dioxide Removal from the Atmosphere
    (2025-07-23) Eke, Victor Obinna; O'Brien, Paul G.
    This thesis evaluates the environmental performance of Direct Air Capture (DAC) technologies through a review of life cycle assessments (LCA), focusing on low-temperature systems integrated with solar energy for adsorbent regeneration. The methodology combines ISO-standardized LCA modeling with experimental validation using silica-supported polyethyleneimine adsorbents under photothermal regeneration conditions. Three heating configurations (natural gas, solar-thermal, and hybrid solar-electric) were evaluated across diverse geographical regions. Results show solar-based systems significantly outperform conventional systems, with potential emissions reductions up to 290 kg CO₂-eq per ton of CO₂ captured. Laboratory experiments demonstrated thermal system desorption required 3.0 GJ/kg CO₂ (0.07% efficiency), while the photothermal system required 707 MJ/kg CO₂ (0.29% efficiency), confirming photothermal regeneration's feasibility for low-energy DAC operation. While regeneration energy dominates environmental impact, infrastructure, transport, and storage collectively contribute significantly. DAC deployment should prioritize regions with abundant solar resources and clean electricity grids, with policy frameworks incentivizing these optimal configurations.
  • Item type: Item , Access status: Open Access ,
    Experimental and Analytical Investigation of an Array of Sessile Droplets Behaviour on Heated and Unheated Substrates
    (2025-07-23) Azzam, Ahmed Elsaid; Amirfazli, Alidad
    **Summary (194 words):** This thesis investigates the evaporation and interaction dynamics of sessile droplets, crucial for applications in thermal management, microfluidics, and surface wetting. A novel and computationally efficient **Point Source Model (PSM)** was developed to predict droplet evaporation on isothermal and heated surfaces. By simplifying complex mass transfer processes, the PSM provides accurate results with minimal computational cost. Initially, the PSM modeled quasi-steady, **purely diffusive evaporation** of two droplets, capturing the effects of **separation distance** and **evaporation modes**—Constant Contact Angle (CCA) and Constant Contact Radius (CCR)—with deviations under 9% compared to experiments. A **critical separation ratio (L/d ≥ 10)** marked the onset of independent behavior. To address heated substrates, the model incorporated **natural convection** via a new empirical correlation. For **Ra·L/d < 400**, diffusion dominates, while for **Ra·L/d > 2400**, convection stabilizes. Further experiments explored **vapor-mediated interactions** between water and propylene glycol-water droplets at 24–135°C. Significant increases in droplet velocity and fragmentation were observed, especially at **20% PG**, driven by surface tension gradients. Finally, the PSM was extended to a **three-droplet array**, revealing enhanced **vapor shielding** and a new isolation threshold (**L/d > 20**), emphasizing the impact of droplet geometry on evaporation behavior.
  • Item type: Item , Access status: Open Access ,
    Thermal and Hydraulic Characterization of Hook-Shaped Fins and Dimples
    (2025-07-23) Alrefaey, Karim; Kempers, Roger
    In forced convection, extended surface arrays enhance heat transfer by increasing surface area, promoting fluid mixing, and generating turbulence. Their thermal-hydraulic performance can be modified by introducing tip clearance or adjusting the attack angle. This study quantifies the heat transfer coefficient and pressure drop of GRIPMetal arrays – hook-shaped fins with dimples – under varying tip clearances and attack angles. Experiments with water-cooled GRIPMetal surfaces explored Reynolds numbers (Re) from 600 to 12,000, while simulations examined attack angles (α) from 0° to 90°. Results showed that GRIPMetal significantly outperforms smooth surfaces, with Nusselt number (Nu) enhancements of 2.4 to 5.7 times higher, despite increased pressure drop. Accounting for the pressure drop penalty, the overall performance factor remained above 1.4. Numerical findings revealed that α = 22.5° improved Nu by 44% at Re = 5000, and some configurations reduced pressure drop. These results highlight GRIPMetal’s potential as a cost-effective heat transfer enhancement method.
  • Item type: Item , Access status: Open Access ,
    Capture of Free-Floating Targets Using End-to-End Reinforcement Learning: Theoretical Foundations and Ground Demonstrations
    (2025-07-23) Beigomi, Bahador; Zhu, George Z.H.
    This doctoral research addresses the challenge of autonomously capturing free-floating, tumbling space debris using robotic manipulators for debris removal in space. Space debris poses a growing risk to near-Earth operations and satellite services. The dissertation explores autonomous grasping of non-cooperative debris in microgravity through Deep Reinforcement Learning (DRL) and advanced robotic manipulation. A high-fidelity simulation environment is developed using the PyBullet physics engine with domain randomization to train and evaluate DRL agents under realistic dynamics. The agents use hierarchical control strategies, combining curriculum-based learning for path planning and tactile sensor feedback for force regulation to minimize disturbances to the target. Simulation studies of multiple DRL algorithms, including Soft Actor-Critic, show success rates over 90% in grasping tasks with varying debris shapes and conditions. A Hardware-in-the-Loop testbed at York University, with dual Fanuc robots and active gravity compensation, further tests these policies, while additional experiments at the University of Luxembourg’s Zero-G Lab confirm the system’s adaptability in microgravity. Results demonstrate that the agents can align and capture free-floating targets without destabilizing forces. Hardware tests verify high grasp stability even with spinning debris, showcasing the potential for autonomous space debris removal. This research advances space robotics by integrating DRL methodologies with experimental validation, enabling safer, more efficient future debris removal missions.
  • Item type: Item , Access status: Open Access ,
    Design and Fabrication of Microfluidic Electrochemical Sensor for Lead Detection in Drinking Water
    (2025-07-23) Shapour Jafargholinejad; Rezai, Pouya; Gora, Stephanie
    This research aimed to enhance microfluidic electrochemical sensors for water quality analysis by simplifying fabrication and leveraging secondary flow effects. Using low-cost materials and laser-cutting techniques, sensors were constructed and characterized. Graphene-carbon paste electrodes were utilized. Through statistical analysis, curved channels significantly improved sensor response due to Dean vorticity formation, enhancing analyte-electrode interaction. Square wave voltammetry demonstrated superior lead detection in curved-channel sensors over straight channels, confirmed by calibration curves using deionized and real water samples. For lead detection, the curved-channel sensor achieved a detection limit of 2.26 µg/L and a sensitivity of 0.0332 µA/(µg/L), surpassing the straight-channel sensor's performance. This research offers a cost-effective, easy-to-fabricate, and modifier-free option for heavy metal detection, particularly lead, in drinking water.
  • Item type: Item , Access status: Open Access ,
    Ultrasonic Fouling Mitigation for Renewable Energy Powered Reverse Osmosis Desalination Systems
    (2025-07-23) Horrigan, Liam; Freire-Gormaly, Marina
    This thesis examines the use of ultrasound to mitigate the performance degradation of reverse osmosis membrane filtration systems due to the accumulation of contaminants on membrane surfaces known as fouling. Numerical models of the phenomena responsible for the fouling mitigation effects of ultrasound were produced. An approach by which ultrasound could be applied to fouling mitigation within commercially available reverse osmosis modules was developed. Relationships between the application of ultrasound and temperature distributions within the fluid contained in filtration modules were investigated for instrumentation and performance assessment purposes. A novel ultrasonic horn was developed and theoretically verified for enhancing the effectiveness of ultrasonic fouling mitigation within commercially available reverse osmosis modules. An experiment was also designed to assess the effectiveness of the approach developed, for which an experimental setup was developed and constructed. Preliminary experiments have been conducted. Future research will focus on detailed experimental analysis.