Civil Engineering

Permanent URI for this collectionhttps://hdl.handle.net/10315/34418

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Access status: Open Access ,
Subscription & Per-Day Pricing vs Same-Day Service: A Simulation of Temporally Consolidated Delivery Systems
(2025-11-11) Jeoung, Won Mo; Nourinejad, Mehdi
Same day delivery is often viewed as the benchmark for last mile logistics because of its convenience and time savings, but its adoption as a wide spread service is limited by high costs. Orders vary between time and location, restricting economies of scale and often resulting in inefficient routes where multiple vehicles serve the same neighborhood within short intervals. To address these issues, this thesis introduces temporal consolidation, where deliveries are grouped and scheduled for specific days of the week or month. Using simulations of customers with different order behaviors and locations, we evaluate delivery scenarios that include grouping requests, optimizing travel routes, and adjusting delivery frequencies. Results show that consolidated deliveries reduce total travel distance compared with same day service. Customers are generally willing to accept longer consolidation periods when paired with cost savings, while higher delivery prices increase demand for faster service.
Access status: Open Access ,
Data-Driven Bike-Share Ridership Prediction and Network Optimization
(2025-11-11) Mohseni Hosseinabadi, Ghazaleh; Park, Peter; Nourinejad, Mehdi
Shared micro-mobility systems, particularly station-based bike-sharing networks, have become key components of urban transportation, yet their planning remain challenged by spatial and technological complexities. This dissertation develops integrated models for ridership prediction, station placement optimization, and electrification planning to address these challenges. First, a customized Graph Neural Network framework using GraphSAGE is introduced for station-to-station ridership prediction, integrating network topology, sociodemographic features, and station attributes. Applied to Toronto, the model outperforms linear, spatial, and tree-based benchmarks, demonstrating its ability to capture latent dependencies and support demand-responsive planning. Second, a continuum approximation model is proposed for station placement optimization, using a force-based algorithm that balances attraction from demand centers with inter-station forces. This ridership-driven approach departs from conventional accessibility methods by directly aligning locations with demand. Applied to Vancouver, the model reveals optimal spacing patterns and highlights strategies for ridership-driven network expansion under varying demand conditions. Third, the dissertation extends infrastructure planning to electrified systems by introducing a two-dimensional Markovian state-of-charge framework for e-bikes. A heuristic charger deployment algorithm, enhanced by a single-pooling state approximation, maximizes expected ridership and identifies high-impact charging locations, achieving near-optimal performance in case studies from Pittsburgh, Vancouver, and San Francisco. Finally, the models are integrated into a web-based, GIS-enabled decision-support tool that combines predictive, prescriptive, and descriptive analytics to enable scenario-based planning. Demonstrations in Toronto and Vancouver illustrate the tool’s scalability and practical value. This research advances methodological foundations and practical tools for developing resilient, data-driven, and electrified bike-sharing networks across diverse urban environments.
Access status: Open Access ,
Signal timing for LCV trucks on a road network using reinforcement learning
(2025-11-11) Ghanbari Sefiddargoleh, Mohammad; Gingerich, Kevin
Freight activity in urban networks is rising, and jurisdictions such as Ontario are encouraging the use of Long Combination Vehicles (LCVs) to consolidate freight loads. This thesis quantifies the delays and queueing on 16 intersections in the Region of Peel and introduces an adaptive signal-control strategy. Tested scenarios include (1) existing signal timing plans without LCVs and (2) with LCVs, (3) a single-intersection double deep q-network (DDQN) controller without LCVs and (4) with LCVs. Introducing LCVs under existing signal timings raised network-wide delay by 14 % for all vehicles and 22 % for trucks when LCVs comprised just 1.7 % of traffic. The proposed DDQN was found to reduce average delays for all vehicles and trucks based on various conditions. Future work should extend the single intersection approach to a multi-agent framework and explore continuous-time action spaces for even finer control.
Access status: Open Access ,
Surface Infrastructure Improvement for Efficient Long Combination Vehicles and Truck Platooning Operation
(2025-11-11) Akkeh, Jowel; Park, Peter Y.
The growing demand for freight transportation has led to increased congestion on urban arterial roads, requiring innovative solutions such as long combination vehicles (LCVs) and heavy commercial vehicle (HCV) platooning. However, these approaches face challenges at intersections due to limited green time and insufficient lane storage for left turns. This study examines the use of Intelligent Transportation Systems (ITS) to enhance truck travel time, specifically through Freight Signal Priority (FSP) and dedicated truck left-turn lanes (DTLL). A methodology was developed to identify intersections requiring truck priority measures. Using PTV VISSIM, a micro-simulation model was created for a 19.2 km corridor with 32 signalized intersections. Freight vehicle composition included 5% LCVs and single-unit trucks. Eight models were used for comparative analysis. Model 1 represents the 'do-nothing' scenario that includes the assumption of 5% LCVs, Model 2 applies the FSP scenario, Model 3 includes the DTLL scenario, and Model 4 combines Models 2 (FSP) and 3 (DTLL). Model 5 assessed a 5% penetration rate of HCV Platooning under existing conditions. Model 6 adds FSP to Model 5, Model 7 adds DTLL to Model 5, and Model 8 combines Models 6 (FSP) and 7 (DTLL). The study found that implementing both FSP and DTLL together yields better results than applying each individually. This integrated approach demonstrated improvements in efficiency, traffic flow, and sustainability by reducing travel time and greenhouse gas (GHG) emissions for all vehicles.
Access status: Open Access ,
Numerical Modelling for Alternative Solution Designs of Steel and Timber Structures in Fire
(2025-11-11) Chin, Kathryn Leigh; Gales, John A.
The objective of this thesis is to increase confidence in alternative solution designs, since its use has increased. Through experimental data collection, a better understanding of steel and timber behaviour in fire was gained and the knowledge was transferred to numerical model development. A validated modelling methodology allows designers to predict structural performance in fire which can then be used to justify decision making and as a method to show the design is code compliant. This thesis examined the performance of steel trusses exposed to a localized fire with a complementary heat transfer and thermal deformation model. For timber, cone calorimeter experiments were completed on various timber products with complementary heat transfer models followed by an exploratory study on thermal parameters in modelling. The thesis provides recommendations for best practices and future research regarding finite element modelling of steel and timber to further develop tools for alternative solution designs.
Access status: Open Access ,
Understanding Water Quality Interactions Within a Decentralized Drinking Water System in a Community in Nunavik, Canada
(2025-11-11) Mahgoub, Ammar Yasir; Gora, Stephanie
This study examined microbial water quality in a subarctic Canadian community reliant on a decentralized truck-to-cistern system. Samples were collected from 40 residential cisterns and various stages of the local water treatment plant (WTP) to measure adenosine triphosphate (ATP), an indicator of microbial activity. Non-parametric statistical tests addressed five research questions related to spatial variation, building age, WTP effectiveness, correlations with water quality parameters, and cistern configuration. No significant differences were found between cisterns across different zones or construction periods. However, ATP levels varied significantly across WTP stages, and cleaning had a measurable impact on microbial activity. Moderate correlations between ATP and turbidity were also identified. While results support improved monitoring practices, the study’s limited sampling and single-community focus restrict broader generalization. Future work should expand sampling duration, include biofilm analysis, and utilize pilot cisterns and digital twins to better understand and manage microbial risks in truck-to-cistern systems.
Access status: Open Access ,
Scalable Urban Crowdsensing: Data Contributor and Consumer Dynamics
(2025-11-11) Heydarigharaei, Elham; Nourinejad, Mehdi
Dynamic transportation routing and parking management rely on real-time data on traffic conditions and curbside availability. Traditional data collection methods require significant infrastructure investments and processing capacity, making them costly and often impractical for large-scale implementation. In contrast, crowdsensing leverages data from users’ smart devices, offering a cost-effective alternative for collecting real-time information. However, crowdsensed data is often noisy, inaccurate, unstructured, and heavily dependent on voluntary user contributions. This thesis is motivated by the central question: how can we effectively design and manage platforms, such as parking management and routing, that rely on such incomplete yet abundant data? To address this, several key studies are presented. The first study, Leveraging Data Contributors to Enhance Social Welfare Through Crowdsensing, examines how user-generated data can improve decision-making at service facilities such as parking lots. By aggregating reported wait times, the platform provides real-time estimates that help incoming users decide whether to enter. This research determines the optimal fraction of data contributors needed to maximize the collective benefit, social welfare, of facility users. The second study, Route Choice Using Crowd-Generated Travel Time Information, explores how crowdsensed travel times influence traffic assignment. Two critical factors, contribution ratio (the proportion of travelers sharing data) and observation window (the period over which data is collected), must be balanced to minimize network-wide travel times. This study analyzes their effects on perceived travel risks and proposes solutions to maintain their optimal values, ensuring efficiency in routing decisions. The third study, Resource Allocation and Route Generation for Urban Mobile Sensing, focuses on optimizing the number and routes of sensing agents, users carrying data collection devices, to enhance efficiency. By determining the optimal number of agents and their navigation paths, this study minimizes total travel costs while ensuring that each parking spot is revisited within the specified headway constraints. A case study in Toronto demonstrates the practical applicability of the proposed optimization framework for parking occupancy detection. The fourth study, Implementing Parking Occupancy Detection Using Dashcam Footage, develops a sensing system that analyzes dashcam video to detect real-time parking occupancy. By applying advanced video processing techniques, this project provides dynamic and scalable insights into urban parking availability. It aims to overcome the limitations of traditional parking data collection tools, such as stationary cameras and sensors, which face challenges related to installation, maintenance, and regulation. Instead, mobile technologies like dashcams, LiDAR, and ultrasound sensors offer a more scalable solution for capturing on-street parking availability. Together, these studies contribute to improving the efficiency of crowdsensing platforms by analyzing the impact of three types of crowdsensed data: wait times, travel times, and urban monitoring reports. These data types are examined across three distinct domains: service facilities (e.g., parking facilities), transportation networks (e.g., scenarios involving multiple modes of transportation or alternative routes with varying congestion levels), and urban monitoring (e.g., parking availability detection, pedestrian safety, and traffic flow monitoring). The research examines how access to such data influences individual decision-making, particularly in the presence of competing alternatives, as well as its impact on overall system performance. Furthermore, it investigates the factors affecting the accuracy and reliability of crowdsensed data in each domain and explores how optimizing these factors can enhance both user experience and system-wide efficiency.
Access status: Open Access ,
Microplastics Transport in Turbulent Flow: Investigating the Effects of Physical Characteristics and Flow Dynamics
(2025-11-11) Shamskhany, Arefeh; Karimpour, Shooka
The surge in global plastic production has led to increasing plastic pollution in aquatic environments, where plastic debris fragments into microplastics (MPs), particles smaller than 5 mm, through weathering processes. MPs are transported by ambient flow across different aquatic compartments, posing ubiquitous risks to the ecosystem health. Effective mitigation of MPs' risks requires a comprehensive understanding of MPs' transport and mobility. Turbulence and the natural settling or rising movements of MPs are fundamental transport mechanisms, yet many aspects of how MPs' diverse physical properties affect these processes remain underexplored. Density, size, and shape are amongst critical physical properties of MPs that shape their transport and affect flow interactions. This PhD dissertation investigates the effects of MPs’ physical properties on their transport and mixing in turbulent flows using numerical and experimental approaches. The findings of this research elucidate how density, size, and shape affect the behaviour of MPs, providing explanations for their selective abundance and distribution in aquatic environments. Results of this PhD dissertation illustrate that lower marginal densities relative to the ambient fluid, smaller sizes, and non-spherical shapes make MPs more susceptible to the transient dynamics of the ambient flow as such MPs deviate significantly from their terminal behaviours. The findings explain the distant transport of smaller non-spherical MPs and the absence of smaller MPs of common polymers in offshore surface layers, as such particles are more likely transported to deeper water columns by in-depth currents. This research also explores the advantages of dynamic Lagrangian modelling over commonly used kinematic approaches, emphasizing the importance of particle acceleration for MPs with higher mixing levels, particularly those with smaller sizes, lower marginal densities, and non-spherical shapes. These findings contribute to understanding MPs' transport and distribution based on their physical properties and flow dynamics and offer a foundation for developing effective strategies to mitigate the ecological impacts of MPs.
Access status: Open Access ,
Parametric Design of Multi-Echelon Last-Mile Delivery Systems Using Novel Technologies
(2025-07-23) Dehqani Viniche, Bahar; Nourinejad, Mehdi
The growing demand for fast and cost-effective last-mile delivery has prompted logistics operators to explore emerging delivery technologies such as autonomous vehicles (AVs) and drones. This dissertation investigates the design and strategic planning of multi-echelon last-mile delivery systems using emerging delivery technologies. Through three complementary studies, we explore the integration of AVs and drones into traditional truck-based delivery networks using analytical models and parametric design frameworks. The first study examines recipient-dependent routing policies in AV-enabled deliveries, where recipients participate by using their AVs for parcel pickup. We introduce and analyze three delivery policies- AV pickup, Hybrid pickup, and Crowdsourced delivery— and derive upper and lower bounds on their total system costs. These policies are compared against the traditional truck delivery model, with results showing that recipient-dependent strategies become increasingly dominant as the number of deliveries grows. The second study extends this concept to the delivery of perishable goods, where delivery time is critical. Using parametric design, we introduce length-constrained (time-sensitive) routing models and compare AV, Hybrid, and crowdsourcing policies to traditional truck delivery. Our findings show that AV integration offers significant advantages in reducing delivery failure for perishable goods, particularly under increasing hand-off costs and high delivery density. The third study focuses on tactical fleet planning and routing in drone-assisted last-mile delivery. We model a mixed fleet of trucks and drones, considering drone range, truck and drone capacities, multi-launching, and vehicle synchronization. Using continuous approximation, we derive closed-form solutions for fleet composition and routing strategies under varying operational scenarios. The analysis yields policy spaces that guide optimal system design based on drone and truck operational parameters, such as vehicle speeds and capacity limits. This dissertation, through its integrated studies, offers a unified framework for the strategic design and operational evaluation of multi-echelon last-mile delivery systems using emerging delivery technologies. The models developed provide managerial insights for logistics planners, policymakers, and researchers seeking scalable and efficient delivery solutions.
Access status: Open Access ,
Pre-emptive and Reactive Resource Allocation in Emergency Response
(2025-07-23) Khaksar, Ali; Nourinejad, Mehdi
Emergency response departments face significant challenges due to resource scarcity and fluctuating incident demands. Traditional static resource allocation, assigning resources to fixed stations, often results in inefficiencies, leaving resources underutilized or insufficient in high-demand areas. To address these shortcomings, this research develops a dynamic resource allocation framework tailored specifically for fire departments. The framework integrates preemptive strategies based on historical data and predictive modeling with reactive strategies responding to real-time emergencies. Validated through a case study in Fredericton, Canada, using data from 2017 to 2021, results demonstrate that dynamic allocation significantly reduces response times and enhances resource efficiency compared to static methods. This study provides a data-driven, practical approach to optimizing resource management in fire departments, effectively addressing operational constraints such as geographic challenges, varying demands, and limited resource availability, thereby improving efficiency, readiness, and effectiveness in emergency response operations.
Access status: 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.
Access status: 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.
Access status: 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.
Access status: 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.
Access status: 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.
Access status: 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.
Access status: 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.
Access status: 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.
Access status: 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.
Access status: 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.

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