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8 Research products, page 1 of 1

  • Canada
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  • 2017-2021
  • Open Access
  • Transport Research

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  • Open Access
    Authors: 
    Stoyanovich, Sawyer; Zeyu Yang; Hanson, Mark; Hollebone, Bruce P; Orihel, Diane M; Palace, Vince; Rodriguez-Gil, Jose R; Faragher, Robert; Fatemah S Mirnaghi; Keval Shah; +1 more
    Publisher: Wiley
    Project: NSERC

    The main petroleum product transported through pipelines in Canada is diluted bitumen (dilbit), a semi-liquid form of heavy crude oil mixed with natural gas condensates to facilitate transport. The weathering, fate, behaviour, and environmental effects of dilbit are crucial to consider when responding to a spill, however few environmental studies on dilbit have been completed. Here we report on 11-day long experimental spills of dilbit (Cold Lake Winter Blend) in outdoor micro-cosms meant to simulate a low-energy aquatic system containing natural lake water and sedi-ments treated with a low (1:8,000 oil:water) and high (1:800 oil:water) volume of dilbit. In the first 24 hours of the experiment, volatile hydrocarbons quickly evaporated from the dilbit, result-ing in increased dilbit density and viscosity. These changes in dilbit’s physical and chemical properties ultimately led to its submergence after 8 days. We also detected rapid accumulation of polycyclic aromatic compounds in the water column of the treated-microcosms following the spills. Our study provides new information on the environmental fate and behaviour of dilbit in a freshwater environment that will be critical to environmental risk assessments of proposed pipe-line projects. In particular, our study demonstrates the propensity for dilbit to sink under ambient environmental conditions in fresh waters typical of many boreal lakes.

  • Open Access English
    Authors: 
    Hussain, Akhtar; Musilek, Petr;
    Country: Canada

    Instead of using a dedicated backup power source to fulfill the energy needs of buildings during contingencies, a reward mechanism for providing reliability-as-a-service (RaaS) via electric vehicles (EVs) is proposed in this study. The proposed positive reward mechanism comprises an upfront reward portion (paid upon registering) and a per-event reward portion (paid based on the amount of energy used). Similarly, a negative reward is applied to the registered EV owners not complying with their contracts. In addition, a score updating mechanism is proposed to incentivize EVs following their contracts and penalize the violating EVs. The score will be decisive during events when more EVs are available than the required energy. The use of EVs for providing RaaS is compared with two commonly used technologies for backup power, i.e., diesel generator and battery storage. Simulations have shown that the proposed scheme can significantly save the cost for building operators/owners while providing revenues for EV owners. The fairness in incentive allocation versus the amount of used energy is also demonstrated.

  • Open Access English
    Authors: 
    Verma, Aman; Nimana, Balwinder S.; Olateju, Babatunde; Rahman, Md. Mustafizur; Radpour, Saeidreza; Canter, Christina E.; Subramanyam, Veena; Paramashivan, Deepak; Vaezi, Mahdi; Kumar, Amit;
    Country: Canada

    The growth in bitumen and synthetic crude oil (SCO) production in the Canadian oil sands industry has superseded pipeline capacity growth in recent years, leading to the increased interest in the transport of crude oil by rail to desired markets. However, the specific techno-economic parameters that facilitate increased competitiveness of either transportation mode against the other is seldom addressed in the existing literature. This paper involves the development of a rail and pipeline techno-economic transport model, which is used to ascertain the transportation cost of both options for a market distance range of 1-3000 km and a production scale of 100,000-750,000 barrels per day (bpd). The transportation cost for either option is highly sensitive to the market distance, transportation scale and crude grade being transported; however, pipelines are generally more competitive for large transportation scales, while the cost-effectiveness of rail transport is realized particularly at smaller transportation scales. In general, pipelines are cost efficient for the transportation of crude oil in the majority of scenarios investigated. Rail can be more economical than pipeline under certain conditions. The use of insulated rail cars for the transport of raw bitumen is the area with greatest potential for cost competitiveness against pipelines.

  • Open Access English
    Authors: 
    McGowan, Ellen;
    Country: Canada

    The coronavirus disease 2019 (COVID-19) has radically impacted public transport ridership and service provision across the country. Since the outbreak of the virus, transit agencies have had to adapt to new and rapidly evolving conditions. Many agencies modified services to reflect lower ridership levels and to ensure the safety of both riders and operators. These changes in service were guided by public health agencies, as well as major transit associations like the Canadian Urban Transit Association (CUTA) and International Association of Public Transport (UITP). Other agencies implemented precautionary measures like rear door boarding, temporary fare suspension, and reduced capacity limits to enable the safe continuity of operations. As the COVID-19 pandemic continues, transit agencies are having to strike a balance between providing enough transportation options for essential travel and reducing service offerings to match the declining overall demand for mobility services. Using a case study of Grand River Transit (GRT) in the Region of Waterloo, this report will document the impacts of COVID-19 on transit agencies and their responses, with a focus on modifications to services. By analyzing the challenges that transit agencies faced in modifying transit services, this report will offer guidance on the protocols and procedures that should be established for an effective pandemic response. Further, the findings of this report will help to inform discussions and guide decisions on the role and operation of public transit in future pandemic events. 

  • Open Access English
    Authors: 
    Grande, Giuseppe;
    Country: Canada

    This research presents a series of projects that contribute to the understanding of how traffic variability affects the measurement and application of annual average daily traffic (AADT). AADT is the most fundamental traffic statistic in transportation engineering. It is defined as the number of vehicles expected to use a facility on an average day. However, traffic is known to experience periodical fluctuations over time; these periodicities are location-specific. This underlying variability in time and space can be lost when calculating and reporting AADT. This research comprises four research projects. The first evaluates the effectiveness of multiple AADT formulations using simulated data loss scenarios. It finds that a relatively new methodology, proposed by the Federal Highway Administration in the United States, removes a small, systematic bias (0.1%) from the existing calculation convention and reduces the width of the 95% confidence interval by 0.5%. The second project provides a method for measuring and reducing the error produced during the assignment step of the AADT estimation process. It applies this method to a case study, finding that the novel assignment method reduces errors by 2.5% on average. The third project explores the use of unconventional traffic data sources (passively-collected vehicle probe data) in tandem with conventional sources. The research finds that speed-based probe data are most closely correlated with truck-specific volume data, specifically around urban centres and along major trade routes. In the studied data, the Pearson correlation coefficient reached 0.9 at some sites. The final project tests the sensitivity of grade crossing design and regulation to predicted fluctuations in traffic. The results show that daily variations in traffic can cause sites to be apparently over- or under-designed for a day or group of days, when compared to regulatory standards. Moreover, they show that within-day variations can be used to express more detailed grade crossing exposure estimates than the daily averages that are used in current regulations. On aggregate, the research finds that, while AADT estimates are convenient to calculate and ubiquitously applied, there is a need to better disclose the source data and methodologies used to produce AADT estimates to avoid misuse and false assumptions about comparability. Further, AADT summarizes the traffic at a site into a single average volume, which fails to express the known periodical traffic variability at a site.

  • Open Access English
    Authors: 
    Pariyarath, Anand Maniyam;
    Country: Canada

    Increased penetration of electric vehicles (EVs) and renewable energy sources (RESs) in power systems can directly affect the system reliability and impose additional complexities to planning and operation due to their uncertainties. The traditional planning methods based on deterministic analysis fail to accurately capture the impact of the aforementioned uncertainty on the system reliability. In this thesis, a reliability-oriented distribution system analysis methodology that captures the complex interactions between EVs, photovoltaic (PV) power production, and energy storage is proposed. Firstly, a two-layer stochastic EV charging demand estimation model is proposed. The model comprises of a traffic layer representing the spatial-temporal distributions of EVs and an electrical network layer describing the impact of EV charging demand on electrical network. A Dynamic Hidden Markov model is used to capture the EV movements in the traffic layer. The ability of the traffic layer model to faithfully represent the random travel pattern of actual vehicles used by different types of drivers is examined. Secondly, a novel stochastic solar radiation model based on probability distributions of the first-order differences of hourly global solar horizontal radiation is proposed to calculate the stochastic power output of the PV system. Measured solar radiation data from four different locations with varying climate characteristics were used to evaluate the proposed model in comparison to two previously reported models. Additionally, various computational models such as the EV charging station model, reliability evaluation model, and economic evaluation model are developed to support the reliability and economic evaluation with necessary inputs. Monte Carlo simulation (MCS) is used to analyze a range of best to worst-case scenarios for more optimal outcomes. A range of sensitivity analysis is performed to illustrate the reliability and economic impact due to EV charging, PV power production and various operating strategies. Several new reliability indices are proposed to quantify the impact of EV charging characteristics, RES penetration, and energy storage system (ESS) on the reliability performance of distribution systems. Finally, an optimization algorithm along with developed stochastic models and MCS framework is used for the optimization of the resource sizes considering EV charging stations (EVCSs) life-cycle costs, reliability and emissions.

  • Open Access English
    Authors: 
    Du, Q.; Kim, A. M.; Zheng, Y.;
    Country: Canada

    In Canada’s Northwest Territories, goods are delivered to remote communities and natural resource extraction sites by inland barge, trucks, and for some goods, air. Combinations of all-weather and winter roads are used in the winter months, while river barge transport and all-weather roads are used in the summer. However, Northern Canada is disproportionately impacted by climate change, which results in greater variability in water level conditions on the Mackenzie River from year to year. This in turn critically affects tug-and-barge operations on the river. This paper investigates Mackenzie River Corridor freight delivery performance – with a focus on the river route – considering how variations in river water conditions can impact network operations and operational costs. We investigate the impacts of water level variation on shippers’ route choice decisions, waterway supply capacity and the resulting overall performance of the freight transport system. Model outcomes provide insights into how the multimodal transportation network may be utilized and perform (quantified by delays and generalized costs) under different water level scenarios. The overarching purpose of the analysis is to provide guidance for infrastructure investment decision-making and business case development, to maintain an effective freight transportation network in the face of on-going climate change impacts.

  • Open Access English
    Authors: 
    Klassen-Townsend, Karalee;
    Country: Canada

    Traffic volume data, commonly summarized as annual average daily traffic (AADT), is a fundamental input for transportation engineering decisions. Current traffic monitoring guidance provides insufficient detail on the development of AADT estimates from short-duration counts conducted within towns. This is due to limited knowledge of the attributes that characterize a town count and uncertainty about the temporal factors required to estimate AADT from short-duration town count data. This research addressed these gaps by using a decision algorithm and GIS analysis to identify which short-duration counts should be considered town counts and by developing and validating a methodology to estimate AADT from short-duration town count data. The analysis demonstrated that temporal factors generated from continuous counts conducted near towns could be reliably applied to short-duration town count data. This finding enables traffic monitoring authorities to leverage existing data and methods to improve the representativeness of traffic volume estimates in towns.

search
Include:
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
8 Research products, page 1 of 1
  • Open Access
    Authors: 
    Stoyanovich, Sawyer; Zeyu Yang; Hanson, Mark; Hollebone, Bruce P; Orihel, Diane M; Palace, Vince; Rodriguez-Gil, Jose R; Faragher, Robert; Fatemah S Mirnaghi; Keval Shah; +1 more
    Publisher: Wiley
    Project: NSERC

    The main petroleum product transported through pipelines in Canada is diluted bitumen (dilbit), a semi-liquid form of heavy crude oil mixed with natural gas condensates to facilitate transport. The weathering, fate, behaviour, and environmental effects of dilbit are crucial to consider when responding to a spill, however few environmental studies on dilbit have been completed. Here we report on 11-day long experimental spills of dilbit (Cold Lake Winter Blend) in outdoor micro-cosms meant to simulate a low-energy aquatic system containing natural lake water and sedi-ments treated with a low (1:8,000 oil:water) and high (1:800 oil:water) volume of dilbit. In the first 24 hours of the experiment, volatile hydrocarbons quickly evaporated from the dilbit, result-ing in increased dilbit density and viscosity. These changes in dilbit’s physical and chemical properties ultimately led to its submergence after 8 days. We also detected rapid accumulation of polycyclic aromatic compounds in the water column of the treated-microcosms following the spills. Our study provides new information on the environmental fate and behaviour of dilbit in a freshwater environment that will be critical to environmental risk assessments of proposed pipe-line projects. In particular, our study demonstrates the propensity for dilbit to sink under ambient environmental conditions in fresh waters typical of many boreal lakes.

  • Open Access English
    Authors: 
    Hussain, Akhtar; Musilek, Petr;
    Country: Canada

    Instead of using a dedicated backup power source to fulfill the energy needs of buildings during contingencies, a reward mechanism for providing reliability-as-a-service (RaaS) via electric vehicles (EVs) is proposed in this study. The proposed positive reward mechanism comprises an upfront reward portion (paid upon registering) and a per-event reward portion (paid based on the amount of energy used). Similarly, a negative reward is applied to the registered EV owners not complying with their contracts. In addition, a score updating mechanism is proposed to incentivize EVs following their contracts and penalize the violating EVs. The score will be decisive during events when more EVs are available than the required energy. The use of EVs for providing RaaS is compared with two commonly used technologies for backup power, i.e., diesel generator and battery storage. Simulations have shown that the proposed scheme can significantly save the cost for building operators/owners while providing revenues for EV owners. The fairness in incentive allocation versus the amount of used energy is also demonstrated.

  • Open Access English
    Authors: 
    Verma, Aman; Nimana, Balwinder S.; Olateju, Babatunde; Rahman, Md. Mustafizur; Radpour, Saeidreza; Canter, Christina E.; Subramanyam, Veena; Paramashivan, Deepak; Vaezi, Mahdi; Kumar, Amit;
    Country: Canada

    The growth in bitumen and synthetic crude oil (SCO) production in the Canadian oil sands industry has superseded pipeline capacity growth in recent years, leading to the increased interest in the transport of crude oil by rail to desired markets. However, the specific techno-economic parameters that facilitate increased competitiveness of either transportation mode against the other is seldom addressed in the existing literature. This paper involves the development of a rail and pipeline techno-economic transport model, which is used to ascertain the transportation cost of both options for a market distance range of 1-3000 km and a production scale of 100,000-750,000 barrels per day (bpd). The transportation cost for either option is highly sensitive to the market distance, transportation scale and crude grade being transported; however, pipelines are generally more competitive for large transportation scales, while the cost-effectiveness of rail transport is realized particularly at smaller transportation scales. In general, pipelines are cost efficient for the transportation of crude oil in the majority of scenarios investigated. Rail can be more economical than pipeline under certain conditions. The use of insulated rail cars for the transport of raw bitumen is the area with greatest potential for cost competitiveness against pipelines.

  • Open Access English
    Authors: 
    McGowan, Ellen;
    Country: Canada

    The coronavirus disease 2019 (COVID-19) has radically impacted public transport ridership and service provision across the country. Since the outbreak of the virus, transit agencies have had to adapt to new and rapidly evolving conditions. Many agencies modified services to reflect lower ridership levels and to ensure the safety of both riders and operators. These changes in service were guided by public health agencies, as well as major transit associations like the Canadian Urban Transit Association (CUTA) and International Association of Public Transport (UITP). Other agencies implemented precautionary measures like rear door boarding, temporary fare suspension, and reduced capacity limits to enable the safe continuity of operations. As the COVID-19 pandemic continues, transit agencies are having to strike a balance between providing enough transportation options for essential travel and reducing service offerings to match the declining overall demand for mobility services. Using a case study of Grand River Transit (GRT) in the Region of Waterloo, this report will document the impacts of COVID-19 on transit agencies and their responses, with a focus on modifications to services. By analyzing the challenges that transit agencies faced in modifying transit services, this report will offer guidance on the protocols and procedures that should be established for an effective pandemic response. Further, the findings of this report will help to inform discussions and guide decisions on the role and operation of public transit in future pandemic events. 

  • Open Access English
    Authors: 
    Grande, Giuseppe;
    Country: Canada

    This research presents a series of projects that contribute to the understanding of how traffic variability affects the measurement and application of annual average daily traffic (AADT). AADT is the most fundamental traffic statistic in transportation engineering. It is defined as the number of vehicles expected to use a facility on an average day. However, traffic is known to experience periodical fluctuations over time; these periodicities are location-specific. This underlying variability in time and space can be lost when calculating and reporting AADT. This research comprises four research projects. The first evaluates the effectiveness of multiple AADT formulations using simulated data loss scenarios. It finds that a relatively new methodology, proposed by the Federal Highway Administration in the United States, removes a small, systematic bias (0.1%) from the existing calculation convention and reduces the width of the 95% confidence interval by 0.5%. The second project provides a method for measuring and reducing the error produced during the assignment step of the AADT estimation process. It applies this method to a case study, finding that the novel assignment method reduces errors by 2.5% on average. The third project explores the use of unconventional traffic data sources (passively-collected vehicle probe data) in tandem with conventional sources. The research finds that speed-based probe data are most closely correlated with truck-specific volume data, specifically around urban centres and along major trade routes. In the studied data, the Pearson correlation coefficient reached 0.9 at some sites. The final project tests the sensitivity of grade crossing design and regulation to predicted fluctuations in traffic. The results show that daily variations in traffic can cause sites to be apparently over- or under-designed for a day or group of days, when compared to regulatory standards. Moreover, they show that within-day variations can be used to express more detailed grade crossing exposure estimates than the daily averages that are used in current regulations. On aggregate, the research finds that, while AADT estimates are convenient to calculate and ubiquitously applied, there is a need to better disclose the source data and methodologies used to produce AADT estimates to avoid misuse and false assumptions about comparability. Further, AADT summarizes the traffic at a site into a single average volume, which fails to express the known periodical traffic variability at a site.

  • Open Access English
    Authors: 
    Pariyarath, Anand Maniyam;
    Country: Canada

    Increased penetration of electric vehicles (EVs) and renewable energy sources (RESs) in power systems can directly affect the system reliability and impose additional complexities to planning and operation due to their uncertainties. The traditional planning methods based on deterministic analysis fail to accurately capture the impact of the aforementioned uncertainty on the system reliability. In this thesis, a reliability-oriented distribution system analysis methodology that captures the complex interactions between EVs, photovoltaic (PV) power production, and energy storage is proposed. Firstly, a two-layer stochastic EV charging demand estimation model is proposed. The model comprises of a traffic layer representing the spatial-temporal distributions of EVs and an electrical network layer describing the impact of EV charging demand on electrical network. A Dynamic Hidden Markov model is used to capture the EV movements in the traffic layer. The ability of the traffic layer model to faithfully represent the random travel pattern of actual vehicles used by different types of drivers is examined. Secondly, a novel stochastic solar radiation model based on probability distributions of the first-order differences of hourly global solar horizontal radiation is proposed to calculate the stochastic power output of the PV system. Measured solar radiation data from four different locations with varying climate characteristics were used to evaluate the proposed model in comparison to two previously reported models. Additionally, various computational models such as the EV charging station model, reliability evaluation model, and economic evaluation model are developed to support the reliability and economic evaluation with necessary inputs. Monte Carlo simulation (MCS) is used to analyze a range of best to worst-case scenarios for more optimal outcomes. A range of sensitivity analysis is performed to illustrate the reliability and economic impact due to EV charging, PV power production and various operating strategies. Several new reliability indices are proposed to quantify the impact of EV charging characteristics, RES penetration, and energy storage system (ESS) on the reliability performance of distribution systems. Finally, an optimization algorithm along with developed stochastic models and MCS framework is used for the optimization of the resource sizes considering EV charging stations (EVCSs) life-cycle costs, reliability and emissions.

  • Open Access English
    Authors: 
    Du, Q.; Kim, A. M.; Zheng, Y.;
    Country: Canada

    In Canada’s Northwest Territories, goods are delivered to remote communities and natural resource extraction sites by inland barge, trucks, and for some goods, air. Combinations of all-weather and winter roads are used in the winter months, while river barge transport and all-weather roads are used in the summer. However, Northern Canada is disproportionately impacted by climate change, which results in greater variability in water level conditions on the Mackenzie River from year to year. This in turn critically affects tug-and-barge operations on the river. This paper investigates Mackenzie River Corridor freight delivery performance – with a focus on the river route – considering how variations in river water conditions can impact network operations and operational costs. We investigate the impacts of water level variation on shippers’ route choice decisions, waterway supply capacity and the resulting overall performance of the freight transport system. Model outcomes provide insights into how the multimodal transportation network may be utilized and perform (quantified by delays and generalized costs) under different water level scenarios. The overarching purpose of the analysis is to provide guidance for infrastructure investment decision-making and business case development, to maintain an effective freight transportation network in the face of on-going climate change impacts.

  • Open Access English
    Authors: 
    Klassen-Townsend, Karalee;
    Country: Canada

    Traffic volume data, commonly summarized as annual average daily traffic (AADT), is a fundamental input for transportation engineering decisions. Current traffic monitoring guidance provides insufficient detail on the development of AADT estimates from short-duration counts conducted within towns. This is due to limited knowledge of the attributes that characterize a town count and uncertainty about the temporal factors required to estimate AADT from short-duration town count data. This research addressed these gaps by using a decision algorithm and GIS analysis to identify which short-duration counts should be considered town counts and by developing and validating a methodology to estimate AADT from short-duration town count data. The analysis demonstrated that temporal factors generated from continuous counts conducted near towns could be reliably applied to short-duration town count data. This finding enables traffic monitoring authorities to leverage existing data and methods to improve the representativeness of traffic volume estimates in towns.