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Recent Submissions
Reverse Logistics Network Design for Additive Remanufacturing
(University of Waterloo, 2025-08-08) Afros, Sheila
The current push for businesses to adopt sustainable supply chain practices contributes to a circular economy, a systems-focused approach designed to allow resources to be used and reused for as long as possible. The Canadian Net-Zero Emissions Accountability Act and the 2030 Emissions Reduction Plan developed by the Canadian federal government aim to regulate the environmental footprint by reducing greenhouse gas (GHG) emissions. Some of these goals can be achieved by designing reverse logistics networks. Reverse logistics is the design of a network for the purpose of collecting end-of-life/end-of-use products and reusing, repairing, refurbishing, remanufacturing, and/or recycling.
This thesis proposes four models to design a reverse logistics network: deterministic, multi-period, stochastic, and a game theory model. The models are formulated as bi-objective mixed-integer linear programs. The design of the network is optimized with respect to economic and environmental objectives. The balancing of costs and environmental objectives during the design of the reverse logistics network provides the decision-maker with additional information on how environmental goals can be met. The models aim to determine the optimal locations for remanufacturing facilities and the optimal flow of parts to and from these facilities. The bi-objective models are solved using the weighted sum method, which allows for Pareto-optimal solutions to be analyzed. The models are solved using Gurobi in Python.
Deterministic, stochastic, and game theory models are applied to a case study for the remanufacturing of front lower control arms in the automotive industry in Ontario, Canada. The stochastic model is motivated by the uncertainty in the supply of end-of-life vehicles. The stochastic model is solved using the deterministic equivalent. The game theory model complements the aforementioned approach. It facilitates the triangulation of the results.
The models select the optimal locations for the remanufacturing facilities. Significantly, all three models applied to the case study produce similar results. The quantitative results demonstrate that the optimal solution based on the case study data is when multiple facilities are located, one facility should be opened in Ottawa and at least one other in the GTA. When only one facility is located, it should be placed in the GTA (either Mississauga or Brampton). Overall, the results reveal that small investments can lead to significant reductions in greenhouse emissions released during transportation.
The results can be scaled to design a reverse logistics network for Canada and inform environmental policies. The results and findings of this study may be used to inform policies on the reduction of transportation emissions. The contributions that the thesis makes to the field are: (i) it incorporates greenhouse gas emissions into the models; (ii) it allows decision-makers to compare the results of the three models (deterministic, stochastic, and game theory) applied to the case study; and (iii) it applies the models to real-world data.
Dynamic Modeling, Analysis, and Control of Integrated Electricity and District Heating Systems
(University of Waterloo, 2025-08-08) Muhammad, Muhammad Abuelhamd Mahmoud
Some of the main challenges with more efficient and cleaner energy systems include the development of Integrated Electricity and Heating Systems (IEHSs). Thus, the proposed research explores IEHSs in the context of Microgrids (MGs) and Bulk Power System (BPS), including the integration of Small Modular Reactors (SMRs) to provide both electricity and heat. In this context, the main goal is to study dynamics and control of IEHSs, with an emphasis on District Heating Networks (DHNs) for efficient energy use. Thus, the proposed work aims to support a cleaner energy transition in both remote communities and urban areas through the use of IEHSs, focusing on two key objectives, namely, developing a comprehensive dynamic models of a combined DHN and Electric Power Network (EPN) to study energy exchanges between these systems, and the provision of ancillary services for power grids for both BPSs and MGs.
A dynamic DHN and EPN model is first developed for MGs, considering all relevant heating and electricity system details, but especially soil limitations, extreme low temperatures, and piping insulation to minimize heat loss. The accurate sizing of the Heat Pumps (HPs) based on thermal load requirements, weather conditions, and consumer profiles is also discussed, proposing a demand management control to enhance MG primary frequency regulation, which facilitates the integration of variable Renewable Energy Sources (RESs) in power grids. The proposed dynamic models are applied, tested, and validated in a realistic community MG based on a remote community EPN located at Kasabonika Lake First Nation (KLFN) in Northern Ontario. It is shown that the DHN facilitates the proper integration of RESs in isolated MGs through the development of novel EPN control
systems.
The presented research also studies IEHSs to serve a broader geographical region beyond MGs. Thus, it proposes to investigate the impacts of IEHSs on the dynamic operation of the BPS in collaboration with Ontario’s Independent Electricity System Operator (IESO), using SMRs as the primary source for both electricity and thermal energy demand. For this purpose, a comprehensive dynamic model of a boiling water SMR power plant, incorporating all essential components, including the reactor, steam turbine, and steam flow control system, is first developed to evaluate its practical application in power grids. Unlike previous studies that focus on individual elements, this work proposes the first full system model with direct steam expansion, capturing key thermal-hydraulic dynamics of the reactor, such as pressure variations and two-phase drift velocity, to improve simulation accuracy. The incorporation of a DHN is then studied, demonstrating that the reactor efficiency can be improved by enabling combined heat and power generation and the provision of ancillary services, which collectively would increase the overall performance and efficiency of the BPS.
The proposed SMR dynamic models are integrated into a widely used power system analysis tool to assess their dynamic performance and impact on Ontario’s BPS. The results highlight the operational flexibility and frequency regulation potential of the BWRX-300, demonstrating its feasibility for practical deployment in modern power grids while also discussing the potential challenges of integrating it within large-scale power networks. Furthermore, the results of the SMR-based DHN models highlight the strong potential of SMRs for cogeneration applications, demonstrating their operational flexibility in practical settings and illustrating a significant reduction in energy consumption compared to heating systems based solely on HPs, which is the current trend.
Development of Lora Battery-Free Water Leak Detection
(University of Waterloo, 2025-08-07) Brown, Brandon
This study explores the development of a battery-free water leak detection system that
leverages energy harvesting sensors and LoRa (Long Range) communication to overcome the
limitations of Bluetooth Low Energy (BLE) technology. While BLE offers low power
consumption, its range is limited to approximately 50 meters, making it unsuitable for wide
area monitoring. In contrast, LoRa provides transmission distances of up to 10 kilometres and
excellent indoor wall penetration, enabling broader scalability for smart infrastructure
applications. The goal of this research is to integrate LoRa modules into a self-powered sensing
platform, eliminating the need for conventional batteries or wired power sources.
However, the transition to a battery-free system introduces a key challenge: the LoRa module
requires high peak currents, often exceeding 100 mA, for successful activation and data
transmission, which electrochemical energy harvesting devices cannot directly supply.
Experimental testing showed that single energy harvesting cells failed to activate the LoRa
chip due to insufficient current, despite producing sufficient open-circuit voltage. Attempts to
connect sensors in series or parallel offered partial improvements but still lacked the required
stability and power density to sustain beaconing. These issues were further compounded by
mismatched performance between cells and high internal resistance, limiting energy transfer
efficiency.
To overcome power limitations, the system integrated a DC-DC boost converter and a 100 mF
supercapacitor to store and deliver energy in short bursts for LoRa transmission. Enhancements
in sensor design and enclosure durability improved activation speed and energy reliability.
Electrical tests confirmed efficient energy use and successful LoRa beaconing, demonstrating
the feasibility of battery-free, long-range leak detection for scalable, low-maintenance
monitoring.
Autoregressive Generative Models for Many-body Physics
(University of Waterloo, 2025-08-07) Teoh, Yi Hong
Many body physics, the study of emergent behavior from the microscopic interactions between countless degrees of freedom, is fundamental to our understanding of the universe. Understanding these systems enable the design and development of everything from materials, pharmaceuticals and even machine learning algorithms. However, to our knowledge, classical simulation of these systems are naturally insufficient and or inefficient.
Recent developments in quantum processors herald a new age in the study of many body systems. The ability to process, extract and generalize the information from such devices is pertinent to new discoveries in the field.
In recent years, autoregressive generative models have been proven to have remarkable capabilities in a wide range of applications, from machine translation, text summarization to image generation. These models not only allow exact evaluation of the likelihood but also enable independent and identically distributed samples to be drawn from their encapsulated complex joint probability distribution of many degrees of freedom. Additionally, these models have demonstrated emergence, where the model exhibits complex behaviors allowing exceptional performance in a wide range of scenarios. These algorithms are prime candidates for the extraction of information from quantum processors and many-body systems.
In current times, data from quantum processors is still rare and expensive, as such we desire the most efficient method to extract information from such limited data. Generative models reveal themselves to be powerful tools in this scenario, achieving higher accuracies with little data.
Rich many-body systems typically inhabit higher dimensional spaces compared to the 1-dimensional sequence of autoregressive models. Consequently, a choice is required regarding the traversal of these higher dimensional systems. We explore the effects linked to this choice of traversal in the training of such models.
Furthermore, we systematically probe the generalization abilities of autoregressive generative models in a variety of axes, such as in size and parameters, for typical discrete and continuous many-body systems.
Finally, Inspired by the recent establishment of correspondence between machine learning and many-body physics, we integrate real-space renormalization group into the model architecture. This integration of a many-body physics technique with machine learning demonstrates considerable promise for the future development of powerful architectures capable of achieving generality.
They decried the bio-politics of illicit substance use: the perspectives of people who use drugs on access to opioid agonist treatment in rural and remote communities of British Columbia
(University of Waterloo, 2025-08-07) Jayathilake, Amreetha
Overdose toxicity claims the lives of 21 people per day on average in Canada, making the overdose crisis a leading public health concern. British Columbia (BC) has one of the highest rates of illicit drug-related overdoses in the country, with rural and remote communities being disproportionately affected by 30-50% increased risk of overdose mortality. Despite this, most research related to illicit drug use focuses on large urban centres and lacks research for the impetus defining increased overdose risk in rural and remote communities. Many people who use drugs (PWUD) are comorbidly diagnosed with opioid use disorder (OUD) for which the current gold-standard of treatment is opioid agonist treatment (OAT). OAT is prescribed by a medical professional and includes medications such as methadone or buprenorphine/naloxone and requires the observation of dose intake by a clinician, pharmacist, or nurse. OAT is said to decrease mortality risk and improve treatment outcomes for PWUD with OUD, albeit, its use and availability is lacking in rural and remote communities, owing to a multitude of intrinsic, extrinsic, and environmental factors, stemming from prohibitionary laws on drugs. Given the unique barriers faced by PWUD drugs in rural and remote settings, the resulting policy and program recommendations of urban centres cannot directly be translated to smaller settings.
Accordingly, the primary goal of this thesis work is to understand the experiences of PWUD and their access to OAT in rural and remote communities of the qathet region in BC. This work is complemented with three sub-goals: firstly, to understand the perspective of using a virtual OAT application program to aid in OAT medication adherence; secondly, to acknowledge the individual participant stories in such a way that aids in fighting-back against drug policy; and thirdly, to illustrate the importance of selecting appropriate analytical frameworks that work to establish agency for the people who the research is about. These efforts are demonstrated within the manuscripts included in chapters 4 and 5. Chapter 4 utilizes a content analysis to describe participant experience with access to OAT in the qathet, with a focus on data related to the virtual application, Sonara Health, that was presented as a potential solution to problems identified in data from year-1 interviews. Chapter 5 uses longitudinal data from participant experience with access to OAT in the qathet to describe and exemplar the use of feminist relational discourse analysis (FRDA), an analytic tool rooted in Foucauldian discourse and a feminist epistemology, with a focus on individual and contrapuntal voices.
These works utilized a qualitative research design involving a rapid ethnography taking place in 2024 and 2025 and is embedded within a larger longitudinal research project that began in 2022. These works involve a total of 32 PWUD and Indigenous-PWUD who had previous experience accessing OAT in the qathet. Semi-structured interviews were completed with participants in 2023 and 2024 years of the research study. These works utilized a community based participatory research (CBPR) design partnering with community organizations (qathet Community Action Team, Tla’min Health Centre) and involve the principles of ownership, control, access, and possession (OCAP) principles as it relates to data involving Indigenous participants.
Taken together, these works establish the overall aim of the thesis: to aid in understanding the rural specific access barriers and facilitators to OAT for PWUD in rural and remote communities of BC, whilst simultaneously strived to use the research to empower PWUD by giving voice to their lived experiences. Accordingly, this thesis adds to the limited body of research regarding experiences of PWUD on OAT in rural and remote communities and presented a novel solution through gaining perspectives on the Sonara app. Additionally, this thesis involved the demonstration of FRDA as a promising analytic approach to showcase research with PWUD, which to our knowledge is the first of its kind. This work highlights the clear need to implement novel approaches to OAT service utilization in rural and remote communities whilst demonstrating the importance of focusing on the participants and their voices as primary to the research.