Civil Engineering

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https://hdl.handle.net/10315/34418

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Open Access
A Safety Analysis of Left-Turning Maneuvers for Long-Combination Vehicles
(2025-04-10) Marchesan, Luciano; Gingerich, Kevin
A growing number of goods are shipped in Ontario using long-combination vehicles (LCVs). LCVs can significantly increase the amount of cargo carried per shipment, while reducing shipping costs and environmental impacts of freight road travel. Questions remain regarding their safety due to their larger size and wider maneuvering. This thesis furthers our understanding of LCV safety considerations in last-mile areas during left-turning maneuvers by focusing on conflicts with infrastructure and road users. Intersections are selected along Peel Region’s Strategic Goods Movement Network and left-turning swept path analyses are performed using AutoTurn. A microsimulation of the intersections is developed, where the existing network is modeled in Vissim while LCVs are added as potential road users. The Surrogate Safety Assessment Model is then used to analyze the microsimulation results pertaining to potential collisions. It was found that existing last-mile infrastructure is ill-equipped to accommodate LCVs and requires adjustments for future LCV use.
Open Access
Design and Installation of Ultra-High Performance Fiber Reinforced Precast Jackets for Retrofitting Concrete Piers
(2025-04-10) Salazar Gonzalez, Roberto; Pantazopoulou, Stavroula
Ultra-high performance fiber-reinforced concrete (UHPFRC) has emerged in the last decade as a new alternative material for retrofitting reinforced concrete structures such as buildings and bridges. One of the most common applications of UHPFRC today is restoring bridge decks and construction joints. UHPFRC can also be applied to the retrofit of principal structural components, such as beams and columns. Decks are repaired by the addition of UHPFRC overlays, whereas columns can be retrofitted with UHPFRC by applying a new layer on the original cross-section, or by removing the concrete cover and replacing it with UHPFRC. This technique is known as jacketing, and it is an attractive solution due to the outstanding mechanical properties of UHPFRC and the fact that the retrofit may be limited to the length of the critical regions and does not have to cover the total height of the column. Specifically, with regards to UHPFRC Jacketing, research on UHPFRC has been conducted when used as a cast-in-place solution. In this research, UHPFRC jacketing is studied as a seismic retrofit alternative, to quantify the jacket's contribution to the various mechanisms of resistance (flexure, shear, reinforcement anchorage capacity, and the confinement effectiveness of the jacket in enhancing the strength and deformation capacity of encased concrete). With confinement effectiveness being the primary knowledge gap, the study included an extensive experimental component, where rectangular concrete prisms modeling concrete columns were jacketed with precast UHPFRC jackets. The objective of the experimental study was to test the proof of concept of jacketing with precast jackets made of UHPFRC, and to also shed light on the contribution of the jackets to the deformation capacity of encased concrete in order to quantify the jacket's effectiveness. As part of the research, the method of connection of the jacket segments and characterization of the materials were designed and optimized through testing. Two possible connectors were designed and tested, providing good results. Several columns were tested under monotonic and cyclic loading, after assembling the precast jackets designed and fabricated for the needs of the study. Parameters of investigation included two jacket thicknesses (i.e. 25 mm and 37.5 mm), the type of connectors between precast components, the loading method (monotonic or cyclic compression load on the encased concrete) and the method of jacketing (cast in situ vs. attaching precast jackets). Finite element modeling was included to understand the lateral resistance to dilation of the encased concrete imparted by the jackets. The deformation capacity of the columns was enhanced substantially. The findings in this research aim to provide a valuable understanding of UHPFRC as a retrofit solution in the form of jacketing.
Open Access
A Bikeability Index for Last-Mile Electric Cargo Cycles
(2025-04-10) Tran, David Chiu; Gingerich, Kevin
A scoring index is developed to analyze the attractiveness of bike routes in urban areas for last-mile logistics using electric cargo cycles (ECCs). This thesis creates the ECC scoring index using a survey with participants riding on four routes within the York University Keele Campus. A literature review is conducted to identify twelve variables for the score. Data is collected using a GPS-connected smartphone, a Gyroscope and a GoPro camera. Participants are asked to rate specified variables on infrastructure, safety and behaviour. The analytical hierarchy process is used to compute the weights for each variable using pairwise comparisons. Variables with the highest weights out of 100% include collision risk (24.3%-25.5%), visibility (11.1%-13.0%) and pavement condition (9.9%-12.4%). A simplified scoring index is derived using variables that could easily be applied to other routes to test its transferability.
Open Access
De-carbonizing Passenger Electric Vehicles and Medium-to-Heavy-Duty Electric Trucks: A Strategic Framework for the City of Toronto and the Province of Ontario
(2025-04-10) Khosravian, Kamand; Nourinejad, Mehdi
Addressing climate change and reducing greenhouse gas (GHG) emissions is driving a global shift towards electric vehicles (EVs). Canada, with its commitment to achieving net-zero GHG emissions by 2050, places high priority on accelerating EV adoption and establishing a robust EV charging infrastructure. This study proposes a comprehensive framework to optimize EV charging station deployment across Ontario, with each chapter divided into two sections: one focusing on light-duty passenger EVs within Toronto’s urban landscape and the other on medium- and heavy-duty trucks along the Highway 401-A20 corridor, spanning from Rivière-du-Loup, Quebec, to Windsor, Ontario. Using empirical data on EV ownership, existing charging infrastructure, and travel patterns, this study develops an optimization model for passenger electric vehicles within Toronto’s wards. The model identifies the optimal number and types of chargers needed to minimize installation costs while meeting the energy demands of Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs). By considering factors such as charging rates, charger availability, costs, and commuting distances, it evaluates drivers' charging behaviors for work and leisure trips and determines the required charger quantities accordingly. Additionally, the model incorporates home charging availability and the ratio of garage orphans—those without home charging options. This adaptable methodology offers valuable insights for urban planning and policy development in areas with similar needs. Focusing on medium- and heavy-duty electric vehicles (MHDEVs), this study addresses the unique challenges of optimizing charging and route planning along the Highway 401-A20 corridor, from Rivière-du-Loup to Windsor. A key barrier to electric truck adoption lies in balancing limited range with delivery timelines while adhering to Canada’s on-duty regulations mandating driver rest periods. The study presents a robust framework that integrates essential factors—including initial state of charge, battery consumption rates, charging station availability, and rest stop requirements—to minimize travel time and identify optimal locations for combined charging and resting facilities along this critical corridor. Given the increasing rate of EV adoption across various vehicle classes, deploying new chargers is crucial to meet future demand. This study contributes to more effective station deployment by addressing the distinct needs of both urban and rural areas while accommodating the varying properties of different vehicle types. The developed framework provides a foundation for strategic infrastructure planning to support EV expansion in Ontario and offers a scalable approach for broader applications.
Open Access
Study of a Bacterial Coculture for Benzene, Toluene, Ethylbenzene and Xylene Degradation
(2025-04-10) Hernandez Ospina, Diego Alejandro; Brar, Satinder K.
Approximately one-quarter of the Canadian population relies on groundwater for daily activities. However, the expanding economy and increased human activities have driven a higher demand for petroleum hydrocarbons, resulting in elevated levels of hazardous pollutants like Benzene, Toluene, Ethylbenzene, and Xylene (BTEX) in the environment, which are well-documented for their carcinogenic properties and alarming risk to public health and wildlife protection in the country. This study explores the potential of a co-culture of S. fonticola and M. esteraromaticum for the effective degradation of BTEX compounds. The obtained results showed a total BTEX degradation of 47%, 45% and 42% by the coculture, M. esteraromaticum and S. fonticola, respectively. Furthermore, the bacterial co-culture showed higher benzene (99%) and toluene (71%), ethylbenzene (85%) and xylene (62%) degradation compared to the individual strains over 42 hours. This study reveals coculture potential for both BTEX multi-compound degradation as well as benzene and toluene individual degradation. Future studies are recommended to further enhance BTEX degradation using coculture by testing multiple inducers, and immobilization materials (e.g. biochar) in varied natural settings (e.g. temperature, pH, salinity, BTEX concentration) while exploring mechanistic pathways and cometabolism occurrence among BTEX compounds. Finally, this co-culture shows a prospect for other studies which helps to advance and offer more sustainable and effective solutions for on-site BTEX remediation.
Open Access
Modelling long term conditions in Canadian deep geological repository
(2025-04-10) Abdullah Asad, Md.; Krol, Magdalena; Molnar, Ian
Canada’s plan for long term (1 million years) management of high-level nuclear waste includes a deep geological repository (DGR). The DGR design involves an engineered barrier system (EBS) within a low permeability host rock (crystalline or sedimentary) that serves as a natural barrier. The EBS includes copper coated used fuel containers (UFCs) within highly compacted bentonite. Over the DGR lifetime, different hydrogeological and geochemical conditions can evolve in the repository. These transient conditions include bentonite saturation, UFC heating, evaporation and condensation, geochemical reaction, adsorption, and microbial activity. Depending on site-specific conditions, bisulfide (HS-) produced by sulfate reducing bacteria in the host rock could slowly transport (diffuse) through the bentonite to the UFC surface and corrode the copper coating and produce hydrogen (H2). Therefore, HS- corrosion assessment is complex and requires a robust numerical model. This thesis describes the development of a HS- transport and reaction model and explores how DGR transient hydrogeological and geochemical conditions affect HS- transport and UFC corrosion. The model predicted slower saturation evolution in the sedimentary DGR due to the rock’s low permeability compared to the crystalline DGR. The slower saturation evolution in the sedimentary DGR delayed HS- transport and therefore HS- corrosion. The model also assessed the relative importance of different processes (e.g. heating, saturation, reaction, adsorption), and system behaviour over time due to the inclusion of these processes, was understood. For example, heating accelerated bisulfide transport while partially saturated bentonite and bisulfide reaction, or adsorption, limited it. In addition, the combined effects of heating, saturation, and bisulfide reaction or adsorption with bentonite were not pronounced over the long DGR life span. Bisulfide transport was simulated for the entire DGR lifespan and was found to be delayed (~50-800 years) due to HS- and iron (Fe2+) reaction or HS- adsorption. However, the HS- diffusion delays are relatively short in a DGR lifespan (1 million years) and does not impact long term HS- corrosion, which stays below Canada’s HS- corrosion depth tolerance. Lastly, amongst various modelling scenarios, the H2 solubility limit was never surpassed, indicating the unlikelihood of H2 gas pressure build-up in a DGR under explored modelling conditions.
Open Access
Thermally assisted fracturing of ancient rock surfaces due to environmental effects: The case of the Valley of the Kings (Egypt) and Langoren Island
(2025-04-10) Alcaino Olivares, Rodrigo Antonio; Perras, Matthew; Leith, Kerry; Ziegler, Martin
Temperature fluctuations from climatic cycles can induce thermo-mechanical fatigue, impacting the stability of rock masses, specially in shallow bedrocks and slopes. This research investigates the mechanism driving fatigue at two distinct environments: Långören Island in Finland and the Valley of the Kings in Egypt. Installed monitoring systems at these locations continuously track rock slabs subjected to temperature cycles. The sensors recorded annual deformation ratios of 0.04 mm/°C for Finland and 0.05 mm/°C for Egypt, indicating cumulative fatigue effects over time. Limited literature on deformation ratios complicates comprehensive comparisons. Mechanical and thermal conditions were documented through geological mapping and laboratory tests, while 2D finite-difference numerical models were developed using FLAC®. For Långören Island, a linear correlation between measured and simulated data yielded an R² of 0.85, with a slope of 0.5 and an intercept of 0.45 mm, indicating the need for further calibration. In contrast, the Valley of the Kings model achieved a slope of 0.85 and a lower intercept of 0.001 mm, with a similar correlation (R² = 0.80), suggesting a better match between measured and simulated data. Despite the similar R² values, the shorter study period at Långören Island likely led to greater data scatter, affecting the overall fit, whereas the longer-term monitoring at the Valley of the Kings allowed for refined modeling of site-specific factors. In the Valley of the Kings, observed conditions and the site’s complex geometry prompted the development of a thermo-mechanical model in FLAC3D®. A calibrated 3D model was used to explore transient conditions from April 2018 to March 2019, with a 156 different variations used including localized plasticity to account for inelastic displacements recorded through July 2023. The simulations correlated with measurements, yielding an R² of 0.90, a slope of 0.65, and intersection of 0.3 mm for the first 12 months from April 218 to March 2019. A conceptual approach using Goodman’s diagram, related mean and alternating deviatoric stresses to assess fatigue failure. A novel thermo-mechanical fatigue criterion based on crack initiation stress thresholds of 11.4 MPa for the Valley of the Kings predicts further crack growth due to thermal fluctuations. This framework can be applied to various scenarios involving natural rocks and concrete structures subjected to environmental temperature changes, linking material properties to fatigue failure mechanisms. Understanding thermal fatigue is crucial to preserving natural cliffs and rock built infrastructure of cultural significance, ultimately improving rock engineering design resilience to safeguard for the future.
Open Access
Data-Driven Optimization of Automated Speed Enforcement Logistics
(2025-04-10) Hedayati Mobarakeh, Mandana; Nourinejad, Mehdi
Canada’s collision fatalities are about 2000 lives a year, decreasing in the last decade, reaching 1745 in 2020 due to initiatives like Vision Zero. Among municipalities’ priorities is to enforce speed limits to reduce speeding-induced traffic fatalities, constituting 27 % of all traffic fatalities in Canada. An emerging strategy toward this goal is the deployment of , which detects violators through speed cameras positioned alongside designated roads. Empirical evidence from existing Automated Speed Enforcement (ASE) practices shows that the number of citations drops each month as driver become aware of camera locations and lower their driving speeds. Hence, ASE cameras are often relocated in cycles to expand their reach to more places and further deter speeding violations. The complexities of deployment lie in choosing camera locations and cycle duration, which have the highest deterrence impact on speeding during a planning period. This study proposes a data-driven model to classify camera site locations based on the effectiveness of ASE enforcement. Then, a Markov decision process optimization model is presented to find the optimal camera locations at each cycle and the length of the cycles for minimizing speed violations across the entire transportation network, considering limitations such as the number of available cameras.
Open Access
Pricing and Matching in Three-Sided On-Demand Delivery Services
(2025-04-10) Davoodi, Mojtaba; Nourinejad, Mehdi; Park, Peter
On-demand delivery services allow customers to browse suppliers to choose their desired product, considering some criteria for receiving at the door. Crowd-sourced drivers pick-up orders from suppliers and deliver to customers. The three players, including customers, suppliers, and drivers, form a three-sided market where successful orders depend on all players' adequate presence. The platform balances the market towards certain profit-generating outcomes by optimally matching the orders and implementing a pricing strategy by charging customers and suppliers a fee and paying drivers a wage. A heuristic algorithm is proposed, comprising matching and pricing modules: one matches customer orders to suppliers and drivers, while the other optimizes the platform's profit by selecting pricing parameters. The findings demonstrate that the platform can influence market dynamics by strategically setting these parameters, satisfying the players' utility, and maximizing profit. The platform's success relies on regulating these parameters to attract the most players and generate profit.
Open Access
Optimal Automated Vehicle Piloting: Avoiding Perfection being the Enemy of the Good
(2025-04-10) Dhaness, Joshua Devindra; Nourinejad, Mehdi
Optimal timing for automated vehicle (AV) pilot programs is essential to balance early implementation benefits against the goal of perfected safety. Although AV technology is not accident-free, it shows potential in reducing crash rates. This work introduces a mathematical framework designed to maximize social welfare through AV pilots, integrating elements such as safety metrics, technology diffusion, and learning effects. The framework’s three models address scenarios that social planners may encounter, offering flexibility in balancing initial risks with anticipated safety improvements over time. A case study illustrates these models, emphasizing the framework’s utility in navigating trade-offs like managing higher early failure rates while leveraging learning-based enhancements. By adjusting input parameters, planners can customize pilot designs to meet community needs. Future improvements, such as variable weighting and iterative testing, are proposed to enhance the framework’s adaptability and its capacity to capture critical AV deployment considerations.
Open Access
Monitoring and Modeling Long-term Environmental Influences on a Shallow Excavation Using Machine Learning: Case Study of Tomb TT95 in the Theban Necropolis, Luxor, Egypt
(2025-04-10) Vasileiou, Apostolos; Perras, Matthew; Khan, Usman T.
Exposure of rock in thermal cycling has been linked to reduction in intact rock sample strength at a laboratory scale and has been characterized as a potential triggering mechanism for rock falls. However, the long-term effect of climatic fluctuations on shallow rock excavations still remains unknown. This research investigates the long-term effects of climatic fluctuations on shallow rock excavations by monitoring a damaged pillar in TT95, an underground funerary chapel in Theban Necropolis, Luxor, Egypt. Using two orthogonally placed extensometers, relative displacements of the pillar were measured alongside temperature and humidity. Findings indicate that pillar displacements correlate with seasonal temperature changes, showing a 0.02 mm/year drift. Data-driven CNN models were developed for forecasting, with one extensometer model achieving high accuracy (R²: 0.98) and the other performing poorly (R²: -0.2). The study suggests that continued pillar drift could cause loose rock blocks on the chapel ceiling to detach over time.
Open Access
Dynamic Parking Pricing using Transaction Data
(2024-11-07) Luo, Wenhan; Nourinejad, Mehdi
Managing on-street parking in dense urban areas poses challenges due to high demand and limited parking space availability, leading to increased congestion and search times for drivers. This thesis explores the efficacy of implementing a dynamic parking pricing policy inside a parking network to mitigate these challenges. Dynamic parking pricing adjusts prices based on parking demands, aiming to balance parking occupancy across different areas. The research investigates the feasibility of utilizing transaction data to predict parking occupancy, eliminating the need for expensive occupancy detection infrastructure. A predictive Neural Network is generated, and a price-setting algorithm is proposed to optimize and change parking prices to increase availability in high-occupied areas and attract drivers to underutilized spaces.
Open Access
Towards an improved understanding of the importance hydrologically diverse data for training flood forecasting models
(2024-11-07) Snieder, Everett Joshua; Khan, Usman T.
Floods constitute a major threat to populations and infrastructure. Flood frequency and severity are projected to increase due to factors such as climate change and urbanisation. Flood early warning systems (FEWS), which rely on models that predict streamflow, provide relevant groups (e.g., transportation authorities, police, schools, etc.) with advance notice of flood risk, allowing them to respond early and minimise flood damage. However, Canada has inadequate flood forecasting infrastructure and lacks a national system. To address the projected flood risk, there is a crucial need to improve modelling capabilities in Canadian watersheds. The following manuscript-based dissertation presents a series of case studies that propose methodological improvements to hydrological modelling frameworks, focusing on the selection of training data for flood forecasting studies. The studies also demonstrate applications of machine learning (ML) to improve model accuracy and reliability. These studies span a wide range of spatiotemporal conditions, ranging from forecasting flash-flooding at sub-hourly frequencies in small urban watersheds, to nationwide, multi-day forecasts. Each of the four studies exploits the benefits of hydrologically diverse training data for improving model performance as FEWS. The first manuscript introduces a novel ensemble model framework for traditional, physics-based urban stormwater models. The method leverages the concept of equifinality to generate ensembles with diverse parameter value estimates, which are shown to outperform traditionally calibrated models. The second and third manuscripts evaluate pure ML-based ensembles. The second manuscript simplifies flood forecasting by framing it as a binary problem. The Synthetic Minority Oversampling TEchnique (SMOTE) algorithm is applied to increase the proportion of flood samples in the dataset, which is shown to improve flood forecast accuracy at the expense of an increased number of false positives. Next, three ensemble algorithms and five classifiers are systematically compared; extreme learning machines (ELMs) and support vector machines (SVMs) are found to be the strongest classifiers. The third manuscript proposes an improvement to popular ensemble algorithms, which consists of embedding synthetic oversampling within the ensemble loop, to increase the covariance of ensemble member predictions. The fourth manuscript evaluates a novel cluster-based training data selection framework for regionally trained deep learning models. The method is used to show how data from hydrologically dissimilar basins is more useful to improving performance in a target basin, compared to data from the target basin itself, or proximal basins. Collectively, the results of these studies advance techniques for achieving improvements in model performance, especially during high streamflow conditions, which are most important to flood warning systems.
Open Access
Optical Detection of Azithromycin in Water and Urine Using Molecularly Imprinted Polymer-Microfluidics Integration
(2024-11-07) Noha Mohamed Hosny Hasaneen; Brar, Satinder Kaur; Rezai, Pouya
Azithromycin (AZM) is one of the most used antibiotics worldwide. Monitoring its concentration in urine and water is essential to control the spread of antibiotic-resistant bacteria. Two new methods for AZM analysis in artificial urine were developed using fluorescence-based microscopic and spectrophotometric techniques after forming an ion-pair complex with fluorescein isothiocyanate. The fluorescence method showed higher sensitivity and precision, with a linear range of 0-31.25 µg/mL, LOD of 0.41 µg/mL, and LOQ of 1.23 µg/mL, compared to the spectrophotometric one. Moreover, it showed a narrower recovery range of AZM from artificial urine samples, indicating higher precision in complex matrices compared to the spectrophotometric one. For enhanced selectivity and portability, a study on integrating molecularly imprinted polymer (MIP) as synthetic receptor inside a microfluidic device with the fluorescence-based detection method was performed. Despite the challenges with specificity, the study constitutes a promising detailed investigation where both extraction and detection of AZM can be done on the same platform using optical techniques. This approach can be potentially extended to enable multiplexing, where a microfluidic device with multiple channels, each containing an MIP specific for a different target compound can be used.
Open Access
Nonlinear Seismic Assessment Criteria for Reinforced Masonry Structures in Canada
(2024-11-07) Calcagno, Marco; Pantazopoulou, Stavroula
The objective of this thesis was to bridge the knowledge gap that exists in the assessment of reinforced masonry structures in Canada under seismic loading. Despite the seismic risk present in Canada, there is no formally approved seismic risk-based assessment framework for existing RM structures, and instead, U.S. evaluation criteria (NIST, ASCE/SEI - 41, TMS 402) are used for the assessment of structures built to the Canadian design code (CSA S304). The work presented in this thesis aims to validate the extension of the ASCE/SEI-41 codes to the Canadian context through the development of a comprehensive database of over 70 reinforced masonry walls built and tested in Canadian Academic Institutions. Code-based analytical values of strengths, stiffness, mode of failure, and drift capacities, were compared with the experimentally recorded values and reported failure patterns.
Open Access
Investment and Financing of Roadway Digital Infrastructure for Automated Driving
(2024-11-07) Ahmadian Shahreza, MohammadAmir; Nourinejad, Mehdi
Connected automated vehicles (CAVs) rely on sensors to scan their environment, enabling efficient decision-making, though their limited range poses challenges. Enhancing CAV operations by leveraging cooperative sensing via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications offers ways to improve autonomy. This study examines optimal investments in vehicular connectivity and stationary sensor deployment under different traffic conditions. Our results highlight the trade-off between roadside stationary sensors and CAV-mounted sensors. Results show that for low traffic flow and constrained budgets, infrastructure investment is preferable, while higher traffic flow favors connectivity among CAVs. Additionally, the analysis shows that an optimal toll cannot fully cover digital infrastructure costs, though if safety benefits are factored in, covering the costs of constructing such infrastructure becomes feasible. The self-financing theorem also holds for the case of digitalization of existing roads if their flow-capacity ratio exceeds a certain threshold.
Open Access
The Use of Instrumented Capillary Rise Experiments with Time-Domain Reflectometry to Determine Capillary Rise and Soil Salinity in Real-Time
(2024-11-07) Samoon, Urooma; Bashir, Rashid
The movement of saltwater in soils through capillary rise poses a concern, given its potential to affect both soil structure and hydraulic properties. This emphasizes the critical necessity of real-time monitoring to accurately measure and assess the salt concentration in the soil. Time-Domain Reflectometry (TDR) can be used to simultaneously measure the volumetric water content and bulk electrical conductivity of soil over time. Bulk electrical conductivity serves as a valuable metric for estimating pore water electrical conductivity, providing a basis for establishing a correlation with the salt concentration in the soil. Capillary rise experiments, instrumented with TDR probes, were conducted to measure the volumetric water content and bulk electrical conductivity of two distinct sand grades (30/40 and 40/50). These experiments encompassed a series of trials involving varying concentrations of salt solutions, juxtaposed with a control test utilizing deionized water. Further batch testing was conducted using the same sands to establish empirical relationships between bulk electrical conductivity and soil pore water concentration. The time series data, encompassing experimental volumetric water content and concentration from the capillary rise experiment, was used for inverse modelling to estimate soil hydraulic and solute transport properties. The findings from this study indicate that TDR provides accurate results for water content and electrical conductivity in column capillary rise experiments. The results also suggest that TDR observation data coupled with inverse modelling provides a soil water characteristic curve comparable to that measured using an evaporation method with the use of HYPROP. The outcomes of this study offer valuable insights into comprehending the intricate dynamics of water and salt within soil systems.
Open Access
Understanding the impact of the scavenging capacity on costs of the UV chlorine advanced oxidation process for drinking water treatment using the external calibration method and the development of cost curves.
(2024-11-07) Lima-Thompson, Reece Curtis; Gora, Stephanie
UV-driven advanced oxidation processes (e.g. UV/H2O2, UV/Cl) that couple UV irradiation with oxidizing chemicals to generate highly reactive species such as ·OH radicals and reactive chlorine species are increasingly being recommended for the removal of recalcitrant organic contaminants in drinking water and wastewater. Establishing the doses of UV and oxidant required to achieve treatment objectives is challenging because many species besides the contaminant(s) of interest exert a scavenging capacity for the highly reactive species generated in advanced oxidation processes. Overall, the aim of this research was to establish whether a colour-based test developed to measure the hydroxyl radical scavenging capacity of water samples could be adapted to measure the scavenging capacity of reactive chlorine species in addition to hydroxyl radicals. The results were used to estimate the cost implications of installing a UV/H2O2 or UV/Cl reactor in a drinking water treatment plant. Initial capital and ongoing operational and maintenance cost curves were developed to characterize the potential cost savings of utilizing the method to treat a well-known contaminant of concern.
Open Access
Investigating Bisulfide Sorption onto Bentonite through Laboratory Experiments and Numerical Modelling
(2024-11-07) Papry, Sifat Azad; Krol, Magdalena
The long-term performance evaluation of the Canadian deep geologic repository (DGR) relies significantly on bentonite clay, a crucial material in the engineered barrier system. One safety concern is microbiologically influenced corrosion of the used fuel containers (UFCs) which may occur if bisulfide (HS-) transports through the bentonite buffer to the UFC surface. HS- sorption onto bentonite can reduce the corrosion risk, but its dynamics are not yet well-understood, especially in DGR environments. Hence, this study offers a comprehensive insight into HS- sorption process onto bentonite through extensive laboratory experiments and numerical modelling. First, a robust methodology was developed to build confidence in the experimental procedure. Subsequently, six sets of batch experiments (including desorption tests) were performed as a function of temperature (10-40°C), contact time (1-120 hours), liquid to solid mass ratios (L:S) (100-1000), initial HS- concentration (1-6 mg L-1), pH (9-11), and ionic strength (0.01 M-1 M NaCl). The experimental results indicated that HS- sorption onto bentonite occurred faster, and the equilibrium sorption capacity increased (by 3%) with increasing temperature. However, sorption decreased with increasing pH and ionic strength. Several established kinetic and isotherm models were applied to the experimental data to provide insight into HS- sorption dynamics onto bentonite. In addition, desorption test results indicated that HS- was irreversibly sorbed on bentonite. Surface analyses conducted using scanning electron microscopy along with energy dispersive spectroscopy, suggested that sorption might have occurred due to chemical reactions of HS- with the iron (Fe) present in bentonite. Lastly, a thermodynamic-based sorption model was developed in PHREEQC assuming that sorption was driven by three key processes: (i) redox reaction with the structural Fe3+ sites, (ii) surface precipitation as iron sulfide, FeS (likely mackinawite), and (iii) surface complexation reactions with surface hydroxyl group (OH) at the edge sites of montmorillonite. The model successfully described the experimental trends and provided valuable insights into the relative contribution of each process to the total sorption mechanism. Altogether, this study provides novel insights from experimental and numerical modelling that enhance the understanding of HS- sorption onto bentonite, which supports the Canadian DGR design and other nuclear repositories worldwide.
Open Access
Evaluation of the Flexural Response of Steel Reinforced UHP-FRC Beams Using Distributed Sensing
(2024-10-28) Giuseppe Domenico Garisto; Butler, Liam; Pantazopoulou, Stavroula
The interaction between ultra-high-performance fibre-reinforced concrete (UHP-FRC) and steel reinforcement significantly affects the displacement ductility of UHP-FRC beams in flexure, leading to a brittle failure mechanism due to crack localization. Previous studies faced limitations in fully exploring this interaction due to conventional sensors. Distributed fibre-optic sensors (DFOS), particularly based on optical frequency domain reflectometry (OFDR), offer new insights. In our study, DFOS and strain gauges monitored strains along longitudinal reinforcement and support wire during four-point loading tests on beams with varying fibre contents (1% and 3%) and reinforcement ratios (1.5% and 2.3%). Results showed that lower fibre content and higher reinforcement ratio led to greater ductility, indicated by increased curvature and strain peaks. Finite element modelling underestimated experimental responses, suggesting a need for improved material property characterization.