Price Faculty of Engineering Scholarly Works
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Browsing Price Faculty of Engineering Scholarly Works by Author "Bibeau, Eric"
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- ItemRestrictedPerformance of Marine Kinetic Turbine in the Wake(2013) Birjandi, Amir Hossein; Chatoorgoon, Vijay; Bibeau, EricUnlike the uniform and low turbulence conditions of flow in water tunnels and towing tanks, flow in rivers, channels and oceans is highly turbulent and non-uniform due to the eddies with size that exceeds the diameter of the turbine. This condition accentuates in hydrokinetic farm applications where multiple turbines operate in eddies shed behind the upstream turbines. This data set represents the water tunnel test results of non-uniform inflow and upstream vortices on the quality of the output power and the performance of vertical turbines. The non-uniform flow condition is generated by placing cylinders with different sizes upstream of the turbine. The performance characteristics of the turbine operating behind cylinders are compared to that of the turbine operating in uniform inflow. Cylinders with different sizes are placed upstream of the scaled model turbine at various longitudinal and lateral locations. The effect of non-uniform inflow on the average output power and the instantaneous power fluctuations are presented in this Data set.
- ItemOpen AccessStatistical Development of a Duty Cycle for Plug-in Vehicles in a North American Urban Setting Using Fleet Information(2010) Shahidinejad, Soheil; Bibeau, Eric; Filizadeh, ShaahinDevelopment of a daily duty cycle based on real world driving behavior and parking times is a critical requirement in the optimal design of power-train components of a plug-in vehicle. Standard driving cycles cannot completely emulate the real-world power demand of a vehicle and its downtimes in particular. To address these shortcomings, a large database of one year of measured data collected from a fleet of 76 cars in the city of Winnipeg, MB, Canada is obtained and is then used to develop a new duty cycle. This paper describes a methodology for statistical analysis of the fleet data, including while a vehicle is parked. Due to the intrinsic differences in vehicle usage profiles during weekdays and weekends, two 24-h duty cycles with suitable windows of opportunity for charging are developed for weekday and weekend driving patterns. The uniqueness of the proposed statistical methodology and the resulting duty cycles contribute to addressing the present shortcomings of standard driving cycles.