Civil Engineering

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Open Access
Safety and Operational Impact of Truck Platooning on Geometric Design Parameters
(2023-03-28) Chowdhury, Md Tanvir Uddin; Park, Peter Y.
The most well-known benefits of heavy commercial vehicle (HCV) platooning are fuel savings and emission reductions. HCV platooning under SAE automation level 4 or 5 would also address the truck driver shortage by eliminating the driver from one or more HCVs in a platoon. This dissertation investigates the safety and operational implications of SAE level 4 HCV platooning on North American roadways. The research develops modified analytical models and micro-simulation models (PTV VISSIM) for analyzing impacts on two-lane rural highways, urban arterial roadways, and freeways. The study considers different time headways (0.6 sec and 1.2 sec) between the platooning vehicles, and three market penetration rates (0%, 5%, and 10%). The two-lane rural highways chapter investigates the passing sight distance (PSD) required to overtake an HCV platoon. The urban arterial roadways chapter compares existing traffic controls with traffic signal priority (TSP) for HCV platoons. The freeways chapter investigates freeway acceleration lane length on merging segments for HCV platooning operations. The findings suggest that two-HCV platooning with 0.6 sec time headway and a 5% market penetration rate can be allowed on designated North American roadways. With proper passing lanes, two-HCV platoons can be operated on two-lane rural highways that already permit long combination vehicle operations. Even with TSP, HCV platooning on urban arterial roadways at penetration rates higher than 5% at our selected intersection may, however, cause significant delays and overwhelm the traffic system. On freeways, two-HCV platooning at a 5% market penetration rate where the freeway acceleration lane is at least 600m long appear to be feasible. The study will assist transportation professionals and policymakers in understanding the consequences of HCV platoons and deciding whether to allow HCV platooning on North American roadways.
Open Access
Stress-Strain Models for UHPFRC and Application in Seismic Design and Retrofit of Bridges
(2023-03-28) Mohammed, Ismail; Pantazopoulou, Stavroula
With the advent of Ultra-High-Performance Fiber-Reinforced Concrete (UHPFRC), most shortcomings of conventional concrete are mitigated, since UHPFRC has exceptional mechanical and durability properties. The behavior of the material in tension is the most important property that need be characterized with confidence for practical implementation of UHPFRC in construction. This is often extracted through reverse inverse analysis of flexural tests – existing inverse analysis methods are fraught with great uncertainty and scatter. In this thesis, several alternative characterization methods are explored and corroborated with test results, including an inverse analysis procedure that is consistent with first principles, as well as a practical, chart-based procedure for quality control by practitioners. Apart from the direct tension response, the tension stiffening property of UHPFRC when it interacts with embedded reinforcement was also studied both experimentally and through detailed finite element simulation. Parameters of the study included the volumetric ratio of fibers, casting methodology, loading protocol and the condition of the embedded reinforcement (corroded or uncorroded). Results quantify the amount of tension stiffening that UHPFC cover can provide to reinforcement. The emphasis on tensile stress and strain capacity of UHPFRC is of interest in seismic retrofitting of existing columns through jacketing. In this work a design framework was developed to design UHPFRC jackets by setting performance objectives for the retrofitted column, strain limits for the UHPFRC material in tension and compression, and by development of a constitutive relationship for the encased concrete under the influence of confinement imparted by the jacket. The study includes an illustrative example of a bridge pier confined with two alternative UHPFRC materials of different strength, indicating the effectiveness of the proposed methodology in estimating the performance limit states of the retrofitted component.
Open Access
Numerical Prediction of Expansive Soil Behavior in Changing Climate
(2023-03-28) Seyfi, Sahand; Bashir, Rashid
The prediction of expansive soil shrinkage/swelling response to climate cycles is of great importance for geotechnical engineers. The climate change is anticipated to cause significant changes in the hydrological cycles that consequently results in higher risk of damage to the structures constructed on expansive soils. In this study, a single stress state variable framework was adopted to describe the void ratio as a function of effective stress for soils in unsaturated state. A two-dimensional finite element model that couples variably saturated flow and stress-strain analysis was developed to simulate the behavior of expansive clay subject to change in soil moisture content. The developed numerical model was used to assess the impact of climate change on the behaviour of Regina Clay in the city of Regina, Saskatchewan. The results indicated that the frequency of large expansive ground heaving events is considerably higher under critical future Regina climate scenario compared to historical climate.
Open Access
Rhodosporidium Toruloides as Robust Yeasts for Advanced Biofuel Production Using Wood Hydrolysate
(2023-03-28) Saini, Rahul; Brar, Satinder Kaur
In response to increasing global energy demand as well as greenhouse emissions from petroleum fuels, sustainable and renewable sources have been intensely researched to produce biofuel. For instance, microbial lipids have been recognized as a potential feedstock for biofuel production due to their similarities with vegetable oils in terms of fatty acids. Typically, microorganisms capable of accumulating more than 20% lipids are known as oleaginous microorganisms. These microorganisms can thrive on various renewable substrates and biochemically convert excess carbon into lipids. One such example of a renewable substrate is lignocellulosic biomass, which produces hydrolysate containing hexoses and pentoses sugars upon pre-treatment and saccharification, and thus could be employed as a potential substrate for microbial lipids. However, wood hydrolysate presents several challenges such as low consumption of pentose sugars, and the presence of microbial growth inhibitors such as furans, organic acids and phenols. In this sense, Rhodosporidium toruloides, an oleaginous yeast, could be employed to produce lipids due to its ability to accumulate 50-70% of lipids, consume C5 sugars, and tolerate inhibitors. Thus, the present thesis explores the ability of R. toruloides-1588 to thrive on undetoxified hydrolysate derived from forestry residues (hardwood and softwood sawdust) and accumulate lipids. Additionally, several strategies were employed to increase the lipid titer such as carbon and nitrogen ratios, fed-batch fermentation, and carbohydrate supplementation such as crude glycerol, which resulted in maximum lipid accumulation of 56.3% (w/w) along with more than 90% consumption of carbohydrates. A life cycle assessment has been also performed to identify the hotspots in terms of energy consumption, greenhouse gas emission, and waste produced during the lipid production process. Lastly, the strain was accessed for its ability to thrive on microbial growth inhibitor such as furfural and use it as an energy source. Based on the above findings, the current dissertation concludes that R. toruloides-1588 can thrive on undetoxified wood hydrolysate, accumulate lipids that can serve as a feedstock for biofuel production and provide aid in the further development of biorefinery industries.
Open Access
Fabrication of Novel In-Situ Remediation Tools for Unconventional Oil Contamination
(2023-03-28) Davoodi, Seyyed Mohammadreza; Brar, Satinder Kaur; Martel, Richard
The aftermath of unconventional oil (UO) accidents highlights the lack of preparedness of governments to deal with UO emergencies. Because bioremediation is considered slow process, physicochemical treatment processes are necessary in removing contaminants to constrain the spread of oil. In preliminary phase of study, bed systems for adsorption of oil compounds packed with modified dolomite were applied as pre-treatment for bioremediation systems. The high affinity of oil molecules to the active sites due to hydrophobic nature of dolomite surface, as well as low solubility of oil in water, resulted in rapid process of oil adsorption on external surface of modified dolomite. UO contaminated site contain high concentration of polyaromatic hydrocarbons (PAHs). Thus, the final phase of study focused on finding enzyme mixture for biodegradation of PAHs contaminated sites for water and soil treatment. In this regard, screening of indigenous bacteria, identification of involved enzymes, and biodegradation tests were carried out. Several combinations of the pre-selected strains were used to create most prompting consortium for enzyme production. To mimic in situ application of enzyme mixture, bioremediation of pyrene contaminated soil was carried out in soil column tests. The average values of pyrene removal after 6 weeks indicated that the enzyme cocktail can be an appropriate concentration for soil enzymatic bioremediation in the soil column system. A bioinspired device was fabricated as a sustainable remedial method. Our results showed that after 200 seconds of circulating the enzyme solution 100% of anthracene in 1.5 L of 4.6 mg/L was removed from the beaker side. In addition to the circulation of PAH degrading enzymes in hollow fiber lumens, aliphatic degrading enzymes confined in multilayer nanofibrous membrane systems play an important role in the removal of oily compounds. Based on our studies, modified polyimide aerogels were suitable to support enzyme immobilization. The degradation tests clearly showed that immobilized enzymes had biodegradation ability for model substrate in contaminated water. Our results confirmed that immobilization of cocktail enzyme mixture enhanced their storage stability, more than 45% of its residual activity at 15 ± 1 ºC for 16 days. This study could set the guideline for the enzymatic bioremediation of aromatic pollutants especially polycyclic aromatic hydrocarbons in highly contaminated soil and water body.
Open Access
Practical Applications of Machine Learning to Underground Rock Engineering
(2023-03-28) Morgenroth, Josephine; Khan, Usman T.; Perras, Matt A.
Rock mechanics engineers have increasing access to large quantities of data from underground excavations as sensor technologies are developed, data storage becomes cheaper, and computational speed and power improve. Machine learning has emerged as a viable approach to process data for engineering decision making. This research investigates practical applications of machine learning algorithms (MLAs) to underground rock engineering problems using real datasets from a variety of rock mass deformation contexts. It was found that preserving the format of the original input data as much as possible reduces the introduction of bias during digitalization and results in more interpretable MLAs. A Convolutional Neural Network (CNN) is developed using a dataset from Cigar Lake Mine, Saskatchewan, Canada, to predict the tunnel liner yield class. Several hyperparameters are optimized: the amount of training data, the convolution filter size, and the error weighting scheme. Two CNN architectures are proposed to characterize the rock mass deformation: (i) a Global Balanced model that has a prediction accuracy >65% for all yield classes, and (ii) a Targeted Class 2/3 model that emphasizes the worst case yield and has a recall of >99% for Class 2. The interpretability of the CNN is investigated through three Input Variable Selection (IVS) methods. The three methods are Channel Activation Strength, Input Omission, and Partial Correlation. The latter two are novel methods proposed for CNNs using a spatial and temporal geomechanical dataset. Collectively, the IVS analyses indicate that all the available digitized inputs are needed to produce good CNN performances. A Long-Short Term Memory (LSTM) network is developed using a dataset for Garson Mine, near Sudbury, Ontario, Canada, to predict the stress state in a FLAC3D model. This is a novel method proposed to semi-automate calibration of finite-difference models of high-stress environments. A workflow for optimizing the hyperparameters of the LSTM network is proposed. The performance of the LSTM network predicting the three principal stresses is improved as compared to predicting the six-component stress tensor, with corrected Akaike Information Criterion (AICc) values of -59.62 and -45.50, respectively. General recommendations are made with respect to machine learning algorithm development for practical rock engineering problems, in terms of how to format and pre-process inputs, select architectures, tune hyperparameters, and determine engineering verification metrics. Recommendations are made to demonstrate how algorithms can be rendered interpretable with the application of tools that already exist in the field of machine learning.
Open Access
Machine Learning Architectures for Modelling International Roughness in Cold Region Pavements
(2023-03-28) Abu Rish, Eyad Mohamed Na; Bashir, Rashid
One of the most commonly used pavement performance indicators is the International Roughness Index (IRI). Currently used IRI models are often developed using regression analysis with little emphasis on climate. Recent studies have started using Machine Learning (ML) for IRI model development; however, the studies' scope is limited and often restricted to algorithms such as neural networks. Additionally, a systematic comparison between different ML algorithms in modelling IRI cannot be found in the literature. This study develops and systematically compares IRI models using regression analysis and ML methods. The economic and environmental implications of using site-specific models over general models are also examined in this study. This study also analyzes the impacts of climate change on pavement roughness for pavements with different subgrade soil types. This study's results support the use of ML, especially gradient-boosted ensemble algorithms, in developing IRI models as they have superior predicting capabilities and can provide much more value than traditional regression methods, such as regression analysis. The results also found that ML was able to produce meaningful results when regression analysis failed to do so.
Open Access
Seismic Assessment, Repair and Retrofit of Existing Corroded Structures Using UHPC Jacketing
(2023-03-28) El-Joukhadar, Nicolas; Pantazopoulou, Stavroula
The bulk of our developed environment was constructed in the mid to late 20th century, when design codes did not address the importance of ductility and confinement, placing most of today’s concrete infrastructure in danger in case of a seismic event. Current assessment guidelines such as Eurocode 8-III or ASCE 41-17 take the lack of detailing into consideration in the assessment procedure however, they do not address a major concern, reinforcement corrosion. In this dissertation, modifications to current assessment guidelines were proposed and validated in order to take corrosion damage into consideration. Expressions for residual material properties as well as residual mechanical properties of columns were proposed with reinforcement mass loss being the only variable. The viability of using UHPC as both a strengthening and protective material against corrosion was studied in this dissertation. It was found that UHPC fully mitigates corrosion in case no service cracks were present and significantly reduces the corrosion rate in case of cracks between 0.5mm and 2mm were present. The final portion of the dissertation deals with repair and strengthening of corroded lap-spliced columns. Six lap-spliced columns designed based on pre-1970s design standards were constructed and subjected to artificial corrosion. Some of the specimens were tested without any prior strengthening intervention to simulate an earthquake damaging an existing column. They were then repaired using UHPC jacketing and re-tested under cyclic displacement reversals while other columns were strengthened after corrosion and then tested. This was done in order to study the increase in strength and ductility in case the strengthening was done prior to or after seismic activity. The results show a significant increase in strength and ductility of the columns, imparted by thin UHPC jackets replacing the conventional concrete cover.
Open Access
Risk Analysis Using Artificial Intelligence Algorithms to Prevent Collisions on Roadway Segments
(2022-12-14) Mohammadi, Ahmad; Park, Peter Y.
This thesis focused on improving the risk analysis algorithms used in collision avoidance systems (CASs) designed to reduce the risk of three types of collision on roadway segments: animal-to-vehicle collisions, pedestrian-to-vehicle collisions, and pedestrian-to-pedestrian collisions. Currently available CASs use only one input indicator. This approach is limited as the CASs: apply a simple risk analysis algorithm based on a fixed threshold to identify risky situations; cannot simultaneously capture a variety of important collision contributing factors; and cannot combine multiple contributing factors into a single composite risk indicator. The goal of this thesis was to use artificial intelligence algorithms to create a composite risk indicator based on a combination of various input indicators. The thesis goal was achieved through four objectives: 1) Develop a fuzzy rule-based algorithm for a next generation roadside animal detection system; 2) Develop a fuzzy rule-based algorithm for a smart protection system to reduce the number of collisions with police officers on duty on the roadway; 3) Develop a semi-supervised machine learning algorithm for a smart protection system to reduce the number of collisions with police officers on duty on the roadway; and 4) Develop a risk analysis approach to evaluate physical distancing on urban sidewalks. Improvement of the existing risk analysis algorithm in objective 1 resulted in capturing driver behavior, animal behavior, and the spatial and temporal interaction between animal and vehicle. It also resulted in differentiating risk for following and leading vehicle and generating no-risk when vehicle passed from animal. Objectives 2 and 3 were part of the same CAS study. Improvement of the existing risk analysis algorithm in both objectives 2 and 3 resulted in capturing pedestrian behavior, driver behavior, the spatial and temporal interaction between pedestrian and vehicle with 94% accuracy when estimating all risk labels, and 88% success when identifying near miss collisions. Objective 4 successfully reflected the role of density and exposure time in the level of physical distancing. It could help decision-makers to select the most appropriate interventions (e.g., sidewalk expansion) for pedestrians to maintain physical distancing.
Open Access
Cold Active Enzyme Booster Technology (EnBooT) for Biodegradation of P-Xylene
(2022-12-14) Miri, Saba; Brar, Satinder Kaur; Martel, Richard
p-xylene is used as a solvent in medical technology, the leather, paint, and rubber industries. The principal pathway of human contact to p-xylene is via soil and groundwater contamination. Bioremediation offers potential advantages such as being cost-effective and environmentally friendly with lesser undue damage to environments. The main aim of this project is to find an enzyme mixture for biodegradation of p-xylene contaminated sites. In this regard, screening of indigenous bacteria, identification of involved enzymes, and biodegradation tests were carried out. The results showed that xylene monooxygenase (XMO) and catechol 2,3-dioxygenase (C2,3D) have a matching end product, they acted in symphony to degrade p-xylene. The mixture of these enzymes confirmed the complete degradation of p-xylene within 48 h in groundwater (initial concentration of 200 mg/L), 7 days in soil tests (initial concentration of 10,000 -12,000 mg/kg of soil) at 15°C, which is revolutionary for the industrial sector. In soil column tests, different concentrations of the enzyme mixture were used (1x, 5x, and 10x dilution). In this test, 92-94% p-xylene removal was achieved in the treated soil with a 5x diluted enzyme mixture (contained 10 U/mL of XMO and 20 U/mL of C2,3D). Our results showed that biodegradation is a scale-dependent phenomenon and the maximum degradation rate decreased from ~90% to 68% from the soil column to tank tests. It is due to limited access of enzymes to trapped p-xylene in soil pores, low dissolved oxygen, soil heterogeneity, and free phase contaminant. In addition, one of the major challenges in the practical and commercial application of these enzymes is their inherent instability. Our results showed that immobilization improved the stability of enzymes. For example, micro/nano biochar-chitosan matrices increased the stability of enzymes with more than 50% residual activity after 30 days at 4±1 ºC, while the free enzymes had less than 10% of its activity. Overall, this cold-active enzyme mixture can be applied for the biodegradation of all BTEX compounds (benzene, toluene, ethylbenzene, and xylenes). This study could set the guideline for the enzymatic bioremediation of mono-aromatic pollutants in contaminated soil and groundwater under cold conditions.
Open Access
Secondary Moment Effects on Slender Reinforced Masonry Walls
(2022-12-14) Sparling, Adrien Joseph James; Palermo, Dan
Slender masonry walls can be an effective loadbearing component of buildings that require high ceilings such as warehouses and gymnasiums. This type of construction is also efficient in terms of material usage and over-all construction costs. The proven long-term durability of existing masonry buildings makes this construction material an attractive option; however, the limited experimental testing on slender walls in out-of-plane flexure combined with high axial loads have led to conservative prescriptive restrictions on their design in Canadian and U.S. standards. The experimental testing presented herein aims to advance knowledge on Reinforced Masonry (RM) walls and introduces a novel method of reinforcement for new masonry wall construction. This novel method consists of applying Near-Surface Mounted (NSM) steel reinforcement rather than conventional embedded reinforcement. The first phase of the research included numerical Finite Element (FE) analysis and experimental testing of 3 m tall RM walls subjected to four-point out-of-plane loading; the second phase consisted of experimental testing of 8 m tall slender (slenderness ratio kh/t = 42) RM walls subjected to combined axial loading and four-point out-of-plane loading. For both phases, the flexural stiffness (EI) of the walls was assessed through multiple approaches (using reinforcement strain, surface strain, and out-of-plane displacement data), and compared to the stiffness calculated using the current Canadian masonry design standard (CSA S304-14) formulation. The equation for the effective flexural stiffness in the current design standard was observed to underestimate the stiffness response in most loading conditions, however it does not provide a consistently accurate value. An alternative method for calculating flexural stiffness was therefore proposed, which accounts for loss of stiffness from repeated loading, or accidental overload, as well as the effect of applied axial loads. Throughout this dissertation, the performance of RM walls with conventional embedded reinforcement is compared to the performance of walls with NSM steel bars. RM walls with NSM steel reinforcement exhibited higher flexural stiffness, and displacement ductility comparable to or exceeding that of RM walls with conventional reinforcement. In addition, a design example illustrated how NSM steel reinforcement can be beneficial for the design of walls with large secondary moment effects.
Open Access
Influence of Breaking Bores on the Transport of Macroplastics
(2022-12-14) Patel, Preet Laljibhai; Krol, Magdalena; Karimpour, Shooka
Each year there is an influx of several million tonnes of plastic into oceans. Transport and mobility of aquatic plastics are shaped by many factors including flow conditions. Surge waves - highly turbulent transient flows - observed in rivers and near coastal areas, can result in substantial turbulent mixing and have the potential to transport mismanaged plastic waste offshore. The transport of plastics in flow conditions induced by surge waves and the variation in the transport process owing to the changes in the hydrodynamic properties of a surge wave and macroplastic properties, have not been investigated. In this study, laboratory experiments were performed using a hydraulic flume, to produce surge wave Froude number ranging from 1.40 to 4.90. An in-house particle tracking velocimetry platform was used to capture the transport of macroplastics, which was simulated using solid macro-sized negatively buoyant acrylic, and positively buoyant high-density polyethylene and polypropylene plastic balls. The overall results highlight that the horizontal transport of all the macroplastics was governed by surge wave celerity and macroplastics initial momentum, while the vertical transport was influenced by surge wave Froude number. As macroplastics size decreased, there was an increase in horizontal and vertical transport, since it was easier to mobilize them against their buoyancy. This study illustrates that under high mixing conditions, plastics with marginal density from water, can entrain heavily with the flow, moving against their buoyancy. This research highlighted the transport and mobility of aquatic plastics to promote a healthier and cleaner aquatic environment.
Open Access
Impact of Climate Change on Thermal Behavior of Pavement Structures in Ontario
(2022-12-14) Basit, Abdul; Bashir, Rashid; Perras, Matthew
In recent years, numerous studies have highlighted that the climate across the world is changing rapidly due to increased Green House Gas (GHG) emissions. The Intergovernmental Panel on Climate Change (IPCC) has reported that ambient temperatures across Canada are rising twice than the rest of the world. In light of climate change, it is vital to adapt our best practices in pavement material selection and road weight restrictions to avoid potential disruption. Traditionally, asphalt binder selection based on the Superior Performing Asphalt Pavements (Superpave) Performance Grade Asphalt Concrete (PGAC) system relies on historic climatic conditions in relation to the expected in-service temperature range of the flexible pavement. Moreover, in Canada, the Spring Load Restriction (SLR) periods are imposed on the basis of subsurface temperature data obtained from Road Weather Information System (RWIS) and Spring Load Adjustment (SLA) stations in conjunction with visual observations. In view of climate change, it is crucial to investigate the extent to which pavement surface and subsurface temperatures will be affected by ambient conditions in the future. This is to assess the relative impact on appropriate PGAC selection and appropriate SLR recommendations for more durable and resilient pavement structures. In this study, regression models were developed to determine the relationships between asphalt pavement surface temperature and ambient weather data from various weather stations within the Ontario Ministry of Transportation’s RWIS. Moreover, this study also involves the investigation of climate change effect on SLR periods using future climate projections. Regression models were developed to determine the relationships between freeze/thaw depths and climate indices using data from existing SLA and RWIS stations within Ontario. Firstly, the relative impact of climate change on pavement surface and subsurface temperature extremes were estimated for different Representative Concentration Pathways (RCPs) using the regression models. After that, appropriate PGAC selection and SLR recommendations to meet projected pavement temperatures were assessed. It was anticipated that in the future, climate change could potentially cause changes to asphalt binder grades and changes in SLR periods across the Province of Ontario depending on the severity of the projected warming due to climate change.
Open Access
Effect of Climate Change on Slope Stability of Variably Saturated Embankments Using Local Factor of Safety and In-Situ Stress Finite Element Analysis
(2022-08-08) Bagheri, Farsheed; Bashir, Rashid
The global climate change process is actively underway and is expected to continue over the century. It has been predicted that the climate variables such as precipitation and potential evaporation will change significantly over the course of the century. Consequent changes in moisture content patterns within the earth structures, can destabilize, currently stable natural and engineered slopes and infrastructure embankments. In this research, the effect of climate change on the stability of embankments is quantified by estimating a field of Local Factor of Safety (LFS) using a coupled in-situ stress finite element analysis and variably saturated flow analysis. In this method, the effect of moisture content variation on the effective stress is taken into account using suction stress state.
Open Access
Oleaginous Yeast as a Cell Factory for the Sustainable Biofuel Feedstock Production from the Canadian Forest Residues
(2022-08-08) Osorio Gonzalez, Carlos Saul; Brar, Satinder Kaur; Ramirez, Antonio Avalos
With an ever-growing population, global energy demand increases, thereby contributing to the depletion of fossil resources and their limited reserves. Thereby, to lessen the environmental damage caused by fossil fuels, there has been a surge of interest in developing and producing biofuels from renewable feedstocks, such as microbial lipids. Typically, they are derived via a biochemical process using liquid hydrolysates obtained from forestry residues as a substrate. However, microbial lipid production using hydrolysates presents numerous challenges, including the need for a strain that can accumulate high lipid titers, consume five-carbon sugars (C5), and tolerate inhibitory compounds (e.g., furans, phenols, and organic acids), among others. Out of several microorganisms, Rhodosporidium toruloides, an oleaginous yeast, could be a potential alternative to produce lipids. It is known to accumulate lipids up to 70% of its dry cell weight, use different carbon sources, and tolerate several inhibitory compounds. In this sense, the current thesis explores the ability of Rhodosporidium toruloides as a bio-factory to produce microbial lipids using C5 and C6 wood hydrolysates as a culture media. Different R. toruloides strains were screened, and R. toruloides-1588 was determined to have the highest lipid accumulation of 35%. Following the culture media, carbon to nitrogen ratio, use of lipid inducers, and sugar concentration optimization, the lipid accumulation increased from 35% to 57.14%, with 95% and 80% of glucose and xylose utilization in hydrolysates, respectively. Likewise, palmitic, stearic, and oleic fatty acids were the most prominently on the produced lipids. Finally, R. toruloides-1588 demonstrates the capacity to grow, accumulate lipids, and transform furfural into furfuryl alcohol and 2-furoic acid. The strain was also assessed for its ability to tolerate inhibitory compounds, such as 5-hydroxymethyl furfural, vanillin, syringaldehyde, levulinic acid, ferulic acid, acetic acid, vanillic acid, and aminobenzoic acid. With all these findings, this dissertation concludes that R. toruloides-1588 is a suitable microorganism to produce microbial lipids, which can serve as a feedstock to manufacture biodiesel or advanced biofuels using undetoxified wood hydrolysates as a renewable and sustainable culture media.
Open Access
Parking Policies in Dense Urban Areas: A Comparison of Hourly, Progressive, and Time-of-Day Pricing
(2022-08-08) Ornelas, David Antonio; Park, Peter; Nourinejad, Mehdi
Parking supply and demand are often imbalanced in urban areas, causing adverse consequences such as excessive search times and long walking distances. Many parking authorities use parking pricing as a demand management strategy by charging either a fixed daily fee or an hourly price for parking. An emerging alternative is progressive pricing, where drivers pay an hourly price that increases if their parking duration is longer than a predetermined threshold. An econometric model is developed to investigate the optimal design of hourly and progressive pricing under revenue and social welfare maximization. The equilibrium properties of the generalized econometric model are then examined. A parking capable micro-simulation model of a study area in downtown Toronto, Canada, is also developed to validate the econometric model. Results show that when the market is composed of two distinct driver groups, progressive pricing yields a greater revenue compared to hourly pricing under revenue maximization.
Open Access
A Swept Path Analysis of Intersection Designs for Long Combination Vehicles
(2022-08-08) Saha, Ucchas; Gingerich, Kevin
The efficiency of a supply chain depends heavily on a region's ability to accommodate trucks of varying sizes. Intersections are potential bottleneck locations for first- and last-mile logistics, where complexities arise due to inadequate geometric properties. The superior productivity of Long Combination Vehicles (LCVs) has led to increasing adoption by large establishments. However, LCVs face significant impediments due to their extra lengths and subsequent impacts on turning envelopes. This thesis focuses on the range and combination of geometric factors leading to successful LCV right-turn movements, such as curb radii and lane widths. Swept-path simulations are conducted for seven intersections in the Region of Peel using AutoTURN software to classify scenarios as pass or fail. Binomial logit models are estimated from these results. The correct prediction rates of the models range from 74% to 97%. A quick-response toolkit is developed to assist roadway authorities in the LCV route acceptance process.
Open Access
Numerical Study of Turbulent Characteristics and Aeration Patterns in Breaking Surge Waves
(2022-08-08) Li, Zhuoran; Karimpour, Shooka
Positive breaking surge waves are caused by a sudden change in flow. 3D numerical simulation provides a holistic approach to simulate the turbulent behaviour behind a breaking surge wave. A combination of Volume of Fluid (VOF) method and Large Eddy Simulation (LES) is utilized for Froude numbers ranging from 1.71 to 2.49. Computational mesh is refined sufficiently to improve the LES quality by resolving at least 90% of the total Turbulent Kinetic Energy (TKE). At surge toe, strong aeration and surface perturbation are observed caused by intense TKE in the area. Velocity perturbations show positive turbulent production in xy-plane rather than yz-plane as the shear instability exists in xy-plane. Finally, the vortices start from a 1D structure at the toe and exhibit rod shape upstream in anisotropy maps. This study highlights the role of instability mechanisms in the formation of a breaking surge wave.
Open Access
Characterization of UHPFRC Materials for Bridge Construction: An Opportunity to Offset the Need for Prestressing in Bridge Decks
(2022-03-03) Husain, Syed Abdul Basit; Pantazopoulou, Stavroula
In the current decade, an increasing number of reinforced concrete bridge structures are deemed to be in need of repair either due to the short durability lifetime of the materials of their original design, or due to climatic extremes that cause the concrete materials to fail (Mermigas 2018). This is especially true for structures such as bridges which are continuously exposed to variations of the environment including temperature, moisture, and road de-icing salts (Carl 1971, L. Spellman 1971, Demich 1975, Steinkamp 2015). In the present work, a detailed research study of a Canadian UHPFRC material product is undertaken with the objective to investigate the material performance to determine its durability life and identify the limitations and challenges the prequalification process and Code Guidelines present when used to characterize the material. Further, the applicability of the Annex A8.1 was explored of the design procedures using a design benchmark example. The exciting finding of this investigation concluded that by taking advantage of the mechanical properties of this material, it is possible to produce design alternatives for large bridge spans without prestressing (Lee et al. 2017). To quantify the global effects on the response of the structural components comprising UHPFRC materials, design parameters affecting the flexural response of UHPFRC girders were studied.
Open Access
Artificial Intelligence-Based Prediction of Permeable Pavement Surface Infiltration Rates
(2022-03-03) Malik, Arham; Khan, Usman; Butler, Liam
Permeable pavements are a type of low impact development technology that is an alternative to conventional asphalt pavements. These pavements are used to address urban stormwater runoff concerns through infiltration and storage. Overtime, sediments carried by stormwater runoff degrade the performance of these pavements and can eventually diminish the infiltration capacity to the point where no infiltration takes place. The objective of this research is to develop a data-driven model to predict the infiltration rate of permeable pavements. Four permeable concrete lab specimens were constructed and subjected to clogging cycles while obtaining surface images and infiltration data. An artificial neural network was created to investigate the relationship between the images of the pavement surface and its associated surface infiltration rate. Results indicated that image parameters do change significantly as pavements clog and are suitable as inputs to predict surface infiltration rate, although model variability needs to be addressed.