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Continuous efforts to develop a lightweight alloy suitable for the most demanding applications in automotive industry resulted in a number of advanced aluminum (Al) and magnesium alloys and manufacturing routes. One example of this is the application of 319 Al alloy for production of 3.6L V6 gasoline engine blocks. Aluminum is sand cast around Fe-liner cylinder inserts, prior to undergoing the T7 heat treatment process. One of the critical factors determining the quality of the final product is the type, level, and profile of residual stresses along the Fe liners (or extent of liner distortion) that are always present in a cast component. In this study, neutron diffraction was used to characterize residual stresses along the Al and the Fe liners in the web region of the cast engine block. The strains were measured both in Al and Fe in hoop, radial, and axial orientations. The stresses were subsequently determined using generalized Hooke's law.

The continued need of vehicle weight reduction provides impetus for research into the development of novel automotive casting alloys and their processing technologies. Where possible, ferrous components are being replaced by aluminum (Al) and magnesium (Mg) alloy counterparts. This transition, however, requires a systematic optimization of the alloys and their manufacturing processes to enable production of defect-free castings. In this context, prevention of hot tears remains a challenge for Al and Mg alloy thin-wall castings. Hot tears form in semi-solid alloy subjected to localized tensile stress. Classical methods of stress measurement present numerous experimental limitations. In this research, neutron diffraction (ND) was used as a novel tool to obtain stress maps of castings and to quantify the effect of two processes used to eliminate hot tears in permanent mold castings: 1) increasing of the mold temperature during casting of Mg alloys, and 2) grain refinement of Al alloys.

The 9-meter wind tunnel of the National Research Council (NRC) of Canada is equipped with a boundary layer suction system, center belt and wheel rollers to simulate ground motion relative to test articles. Although these systems were originally commissioned for testing of full-scale automotive models, they are appropriately sized for ground simulation with half-scale tractor-trailer combinations. The size of the tunnel presents an opportunity to test half-scale commercial vehicles at full-scale Reynolds numbers with a model that occupies 3% of the test section cross-sectional area. This study looks at the effects of ground simulation on the force and pressure data of a half-scale model with rotating tractor wheels. A series of model changes, typical of a drag reduction program, were undertaken and each configuration was tested with both a fixed floor and with full-ground simulation to evaluate the effects of this technology on the total and incremental drag coefficients.

Turbulence is known to influence the aerodynamic and aeroacoustic performance of ground vehicles. What is not thoroughly understood are the characteristics of turbulence that influence this performance and how they can be applied in a consistent manner for aerodynamic design and evaluation purposes. Through collaboration between Transport Canada and the National Research Council Canada (NRC), a project was undertaken to develop a system for generating road-representative turbulence in the NRC 9 m Wind Tunnel, named the Road Turbulence System (RTS). This endeavour was undertaken in support of a larger project to evaluate new and emerging drag reduction technologies for heavy-duty vehicles. A multi-stage design process was used to develop the RTS for use with a 30% scale model of a heavy-duty vehicle in the NRC 9m Wind Tunnel.

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the sensitivity of intentional lateral offsets over a range of intervehicle spacings. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb. In addition, the SAE J1939 instantaneous fuel rate was calibrated against the gravimetric measurements and used as proxy for additional analyses. The testing campaign demonstrated the effects of intervehicle gaps, following-vehicle longitudinal control, and manual lateral control. The new results are compared to previous truck-platooning studies to reinforce the value of the new information and demonstrate similarity to past trends. Fuel savings for the following vehicle was observed to exceed 10% at closer following distances.

Autonomous vehicles are currently a subject of great interest and there is heavy research on creating and improving algorithms for detecting objects in their vicinity. A ROS-based deep learning approach has been developed to detect objects using point cloud data. With encoded raw light detection and ranging (LiDAR) and camera data, several basic statistics such as elevation and density are generated. The system leverages a simple and fast convolutional neural network (CNN) solution for object identification and localization classification and generation of a bounding box to detect vehicles, pedestrians and cyclists was developed. The system is implemented on an Nvidia Jetson TX2 embedded computing platform, the classification and location of the objects are determined by the neural network. Coordinates and other properties of the object are published on to various ROS topics which are then serviced by visualization and data handling routines.

People through many years of experience, have developed a great intuitive sense for navigation and spatial awareness. With this intuition people are able to apply a near rules based approach to their driving. With a transition to autonomous driving, these intuitive skills need to be taught to the system which makes perception is the most fundamental and critical task. One of the major challenges for autonomous vehicles is accurately knowing the position of the vehicle relative to the world frame. Currently, this is achieved by utilizing expensive sensors such as a differential GPS which provides centimeter accuracy, or by using computationally taxing algorithms to attempt to match live input data from LiDARs or cameras to previously recorded data or maps. Within this paper an algorithm and accompanying hardware stack is proposed to reduce the computational load on the localization of the robot relative to a prior map.

This paper examines issues related to planning, programming and execution of machining operations by a robot in the context of machining large parts with complex geometries by a gantry-mounted robotic system. Parts were created from surface data in a CAD/CAM environment. The same environment was used to generate tool paths using a conventional machine tool approach. These paths were converted to robot trajectories and validated using mathematical kinematic models of the robotic system. Validation was performed according to various criteria related to process performance. Associated robot programs were then automatically generated. The manufacturing cell was progressively integrated according to requirements resulting from iterative process characterization. A metrology-based calibration procedure was designed that considerably improved the system's positioning precision.

The 9-meter wind tunnel of the National Research Council (NRC) of Canada is commonly employed in testing of class 8 tractors at full- and model-scales. In support of this work a series of tests of an identical model at full- and half-scale were performed to investigate some of the effects resulting from simulation compromises. Minimum Reynolds Number considerations drive the crucial decisions of what scale and speed to employ for testing. The full- and half-scale campaigns included Reynolds Number sweeps allowing conclusions to be reached on the minimum Reynolds number required for testing of fully-detailed commercial truck models. Furthermore the Reynolds sweeps were repeated at a variety of yaw angles to examine whether the minimum Reynolds Number was a function of yaw angle and the resulting flow regime changes. The test section of the NRC 9-meter wind tunnel is not sufficiently long to accommodate a full-scale tractor and a typical trailer length of 48′ or more.

The Flight Research Laboratory (FRL), National Research Council (NRC) of Canada is currently developing an in-flight aircraft aerodynamic model identification technique that determines the small perturbation model at a given test condition. Initial demonstrations have been carried out using the NRC Falcon 20 research aircraft. An efficient system architecture, in terms of both software algorithms and hardware processing, has been designed to meet the stringent near real-time requirements of an in-flight system. As well, novel hardware and software techniques are being applied to the calibration and measurement of the fundamental in-flight parameters, such as air data. The small perturbation models are then combined to develop a global model of the aircraft that is validated by comparing the model response to flight data. The maneuvers were performed according to the FAA Acceptance Test Guide (ATG).

A comparison of scanning mobility particle sizer (SMPS) and laser-induced incandescence (LII) measurements of diesel particulate matter (PM) was performed. The results reveal the significance of the aggregate nature of diesel PM on interpretation of size and volume fraction measurements obtained with an SMPS, and the accuracy of primary particle size measurements by LII. Volume fraction calculations based on the mobility diameter measured by the SMPS substantially over-predict the space-filling volume fraction of the PM. Correction algorithms for the SMPS measurements, to account for the fractal nature of the aggregate morphology, result in a substantial reduction in the reported volume. The behavior of the particulate volume fraction, mean and standard deviation of the mobility diameter, and primary particle size are studied as a function of the EGR for a range of steady-state engine speeds and loads for a turbocharged direct-injection diesel engine.

A joint program between Bell Helicopter Textron Canada and the Flight Research Laboratory of Canada's National Research Council was initiated to address the aerodynamic modelling challenges of the Bell M427 helicopter. The primary objective was to use the NRC parameter estimation technique, based on modified maximum likelihood estimation (MMLE), on a limited set of flight test data to efficiently develop an accurate forward-flight mathematical model of the Bell M427. The effect of main rotor design changes on the aircraft stability characteristics was also investigated, using parameter estimation. This program has demonstrated the feasibility of creating a forward-flight rotorcraft aerodynamic mathematical model based on time-domain parameter estimation, and the ability of a 6 degree-of-freedom MMLE model to accurately document the impact of minor rotor modifications on aircraft stability.

Intermittent and highly transient dense diesel sprays were investigated using laser diffraction and laser sheet illumination techniques to decipher the internal spray structure. Through careful experimental design, the unperturbed structure of the dense core region of a transient full cone diesel spray was observed for the first time. Diffraction measurements showed that larger droplets exist at the spray periphery and the Sauter mean diameter decreases from the periphery to the spray centerline. The results from both laser diffraction and 2-D imaging are inconsistent with the existence of an intact liquid core extending to a few hundred nozzle diameters. The intermittent and highly transient nature of diesel sprays ensures rapid and complete atomization within no more than twenty nozzle diameters.

Computational fluid dynamics (CFD) model has been widely applied in internal combustion (IC) engine research. The integration of chemical kinetic model with CFD provides an opportunity for researchers to investigate the detailed chemical reactions for better understanding the combustion process of IC engines. However, the simulation using CFD has generally focused on the examination of primary parameters, such as temperature and species distributions. The detailed investigation on chemical reactions is limited. This paper presents the development of a post-processing tool capable of calculating the rate of production (ROP) of interested species with the known temperature, pressure, and concentration of each species in each cell simulated using CONVERGE-SAGE CFD model.

With increasing use of boat-tails on Canadian roads, a concern had been raised regarding the possibility for ice and snow to accumulate and shed from the cavity of a boat-tail affixed to a dry-van trailer, posing a hazard for other road users. This paper describes a preliminary evaluation of the potential for ice and snow accumulation in the cavity of a boat-tail-equipped heavy-duty vehicle. A transient CFD approach was used and combined with a quasi-static particle-tracking simulation to evaluate, firstly, the tendency of various representative ice or snow particles to be entrained in the vehicle wake, and secondly, the potential of such particles to accumulate on the aft end of a dry-van trailer with and without various boat-tail configurations. Results of the particle tracking analyses showed that the greatest numbers of particles impinge on the base of the trailer for the no-boat-tail case, concentrated on the upper surface of the back face of the trailer.

The noise generated by the flow of air past a transport truck is a key design factor for the manufacturers of these vehicles as the sound levels in the cabin are a significant component of driver comfort. This paper describes a collaboration between Volvo GTT and the National Research Council Canada to measure the in-cabin aeroacoustics of a full-scale cab-over tractor in the NRC 9 m Wind Tunnel. Acoustic instrumentation was installed inside the tractor to record cabin noise levels and externally to acquire tunnel background noise data. Using a microphone mounted on the driver’s-side tunnel wall as a reference to remove variations in background noise levels between data points, differences in cabin noise levels were able to be detected when comparing the tractor with different configurations. The good repeatability of the data allowed for differences of as little as 0.5 dB to be measured.

The use of carbon fiber reinforced thermoset composites has doubled in the last decade raising questions about the waste generated from manufacturing and at end-of-life, especially in the aircraft industry. In this study, 2.5 cm long carbon fibers were recovered from thermoset composite waste using a commercial scale pyrolysis process. Scanning electron microscopy, density measurements, single filament tensile testing as well as micro-droplet testing were performed to characterize the morphology, mechanical properties, and surface adhesion of the fibers. The recycled fibers appeared to be mostly undamaged and clean, exhibiting comparable mechanical properties to virgin carbon fibers. A carding process followed by an ultrasound treatment produced randomly aligned recycled fiber mats. These mats were used to fabricate composite plates, with fiber volume fractions up to 40 %, by infusion / compression molding.

Adoption of hydro-processed esters and fatty acid biojet fuels is a critical component for the sustainability of the aviation industry. Aviation biofuels reduce pollution and provide alternatives to conventional fossil fuels. A study of the impacts of biofuels on emissions from a T56 turbo-prop engine was undertaken as a joint effort among several departments of the Government of Canada. In this study, particulate (including particle number and black carbon (BC) mass) and regulated gaseous emissions (CO2, CO, NO, NO2, THC) were characterized with the engine operating on conventional F-34 jet fuel and jet fuel blended with camelina-based hydro-processed biojet fuel (C-HEFA) by 50% in volume. Emissions characterization, conducted after 20-hour ground engine durability tests, showed immediate significant reductions in particle number and BC mass when the engine was operated on the C-HEFA blend.

The aerodynamic forces experienced by vehicles depend on a variety of factors including wind direction, traffic, and roadside vegetation. Such complex boundary conditions often result in unsteady flow separation and the formation of large-scale coherent structures, which, in turn, significantly influence the aerodynamics of following vehicles. To gain a deeper understanding of the unsteady behaviour of such vehicle wakes under large-scale conditions, a time-resolved field measurement technique is required. Existing methods, such as tomographic particle image velocimetry and three-dimensional particle tracking velocimetry are unfortunately quite limited at these scales. Furthermore, such techniques require complex multi-camera calibrations, hazardous lasers, and optical access from many vantage points.

The authors present transient wind velocity measurements from two successive, well-documented truck platooning track-test campaigns to assess the wake-shedding behavior experienced by trucks in various platoon formations. Utilizing advanced analytics of data from fast-response (100-200-Hz) multi-hole pressure probes, this analysis examines aerodynamic flow features and their relationship to energy savings during close-following platoon formations. Applying Spectral analysis to the wind velocity signals, we identify the frequency content and vortex-shedding behavior from a forward truck trailer, which dominates the flow field encountered by the downstream trucks. The changes in dominant wake-shedding frequencies correlate with changes to the lead and follower truck fuel savings at short separation distances.