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Alumina (Al2O3) thin film coatings are applied on Al alloys using Plasma Electrolytic Oxidation (PEO) method to reduce the wear and corrosion problems. Plasma Electrolytic Aluminating (PEA) is a technique which could generate Alumina coatings on cast iron, mild steel and copper alloys. In this study, the aim is to explore the anti-wear and anti-corrosion behaviours of PEA Alumina coatings on gray cast iron. The dry sliding tribology test data was obtained from Pin-on-Disk (POD) tests against SAE 52100 steel and Tungsten Carbide (WC) counterfaces. Comparing with the PEO Alumina coatings, the PEA Alumina coating has much lower Coefficient of Friction (COF) and less wear. The microstructure, chemical composition and phase composition of this coating were investigated with Scanning Electron Microscope (SEM), Energy-Dispersive X-Ray Spectroscopy (EDX) and X-Ray Diffraction (XRD), respectively. There was FeO (or FeAl2O4) found on the PEA Alumina coating.

This study provides an overview of a novel method for evaluating in-vehicle speech intelligibility using the Speech Intelligibility Index (SII). The approach presented is based on a measured speech signal evaluated at the sentence Speech Reception Threshold (sSRT) in a simulated driving environment. In this context, the impact of different band importance functions in the evaluation of the SII using the Hearing in Noise Test (HINT) in a driving simulator is investigated.

Rollover crash is one of the most serious safety problems for light weight vehicles. In the USA, rollover crashes account for almost one-third of all occupant fatalities in light weight vehicles. Similar statistics are found for other countries. Thus, rollover crashes have received significant attention in recent years. In the USA and Canada, automotive manufacturers are required to comply with the roof strength requirement of “1.5 times the unloaded vehicle weight” to ensure safety in rollover. NHTSA is currently considering a set of countermeasures to improve the rollover safety, where one of the proposals is to increase the roof strength limit to “2.5 times the unloaded vehicle weight”. This increased roof strength limit seemingly has been motivated based on the benchmark study of current vehicle fleet.

This research focuses on the response of the Q3, Hybrid III 3-year-old dummy and a child finite element model in a simulated 213 sled test. The Q3 and Hybrid III 3-year old child finite element models were developed by First Technology Safety Systems. The 3-year-old child finite element model was developed by Nagoya University by model-based scaling from the AM50 (50 percentile male) total human model for safety. The child models were positioned in a forward facing, five-point child restraint system using Finite Element Model Builder. An acceleration pulse acquired from an experimental 213 sled test, which was completed following the guidelines outlined in the Federal Motor Vehicle Safety Standard 213 using a Hybrid III 3-year-old dummy, was applied to the seat buck supporting the child restraint seat. The numerical simulations utilizing the Q3, Hybrid III 3-year-old and the child finite element model were conducted using the explicit non-linear finite element code LS-DYNA.

We are witnessing a rapid and ongoing expansion of nanoscience, driven by potential applications in advanced materials and nanotechnology. There is a race to develop techniques that may allow controlling the size, shape of nanostructures that can allow the tuning of their optical and electronic properties. Plasmonics is a field that encompasses and profits from the optical enhancement in nanostructures that support plasmon excitations. One of these new techniques is surface-enhanced Raman scattering (SERS), commonly used for nanostructure characterization. In the present report, we present a theoretical model for plasmon excitation and electric field enhancement that help to provide an explanation for the special features observed in experimental SERS. Two sets of experimental results are discussed illustrating the make out of the signature of the plasmonics producing the optical enhancement.

Due to considerable efforts of automobile manufacturers to attenuate various noise sources within the passenger compartment, other sources, including induction noise have become more noticeable. The present study investigates the feasibility of using a non-conventional noise cancellation technique to improve the acoustic performance of an automotive induction system by using acoustic energy derived from the exhaust manifold as the dynamic noise source to cancel intake noise. The validity of this technique was first investigated analytically using a computational engine simulation software program. Using these results, a physical model of the bridge was installed and tested on a motored engine. The realized attenuation of the intake noise was evaluated using conventional FFT analysis techniques as well as psychoacoustic metrics including loudness, sharpness, roughness and fluctuation strength.

Following the development of new technologies in Vehicle Thermal Management aiming to both enhancing the MAC System efficiency and reducing the thermal load to be managed, a prediction tool based on the AMEsim platform was developed at Advanced PD EMEA. This tool is dedicated to predict the effect of the implementation of sensors monitoring both the relative humidity and the carbon dioxide (CO2) concentration (taking into account passengers' generated moisture and CO2). This model implemented with the usual comfort inputs (CO2 and RH acceptable ranges) considers the system variables influencing the comfort and predicts the increase of both RH and CO2 concentration in the cabin compartment in any driving cycle depending on the number of occupants.

Though the purpose of a vehicle's suspension is multi-faceted and complex, the fundamentals may be simply stated: the suspension exists to provide the occupants with a tolerable ride, while simultaneously ensuring that the tires maintain good contact with the ground. At the root of the familiar ride/handling compromise, is the problem that tuning efforts which improve either grip or handling are generally to the detriment of the other. This study seeks to set forth a clear means for examining the familiar ride/handing compromise, by first exploring the key ideas of these terms, and then by describing the development of content-rich metrics to permit a direct optimization strategy. For simplicity, the optimization problem was examined in a unilateral manner, where heave (vertical; z-axis) behaviour is examined in isolation, though the methods described herein may be extended to pitch and roll behaviour as well.

The ‘boundary of space’ model representing all possible positions which may be occupied by a mechanism during its normal range of motion (for all positions and orientations) is called the work envelope. In the robotic domain, it is also known as the robot operating envelope or workspace. Several researchers have investigated workspace boundaries for different degrees of freedom (DOF), joint types and kinematic structures utilizing many approaches. The work envelope provides essential boundary information, which is critical for safety and layout concerns, but the work envelope information does not by itself determine the reach feasibility of a desired configuration. The effect of orientation is not captured as well as the coupling related to operational parameters. Included in this are spatial occupancy concerns due to linking multiple kinematic chains, which is an issue with multi-tasking machine tools, and manufacturing cells.

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.

Gantry robots are mainly employed for applications requiring large workspace, with limited higher manipulability in one direction than the others. The Gantries offer very good mechanical stiffness and constant positioning accuracy, but low dexterity. Common gantries are CNC machines with three translational joints XYZ (3DOF) and usually with an attached wrist (+3DOF). The translational joints are used to move the tool in any position in the 3D workspace. The wrist is used to orient the tool by rotation about X, Y and Z axis. This standard kinematic structure (3T3R) produces a rectangular workspace. In this paper a full kinematic model for a 6DOF general CNC (gantry) machine is presented, along with the Jacobian matrix and singularity analysis. Using Denavit-Hartenberg convention, firstly, the general kinematic structure is presented, in order to assign frames at each link. The forward kinematic problem is solved using Maple 17 software.

Laser cladding is a novel process of surface coating, and researchers in both academia and industry are developing additive manufacturing solutions for large, metallic components. There are many interlinked process parameters associated with laser cladding, which may have an impact on the resultant microhardness profile throughout the bead zone. A set of single bead laser cladding experiments were done using a 4 kW fiber laser coupled with a 6-axis robotic arm for 420 martensitic stainless steel powder. A design of experiments approach was taken to explore a wide range of process parameter settings. The goal of this research is to determine whether robust predictive models for hardness can be developed, and if there are predictive trends that can be employed to optimize the process settings for a given set of process parameters and microhardness requirements.

Fiber composite materials are widely used in many industrial applications - specially in automotive, aviation and consumer goods. Introducing light-weighting material solutions to reduce vehicle mass is driving innovative materials research activities as polymer composites offer high specific stiffness and strength compared to contemporary engineering materials. However, there are issues related to high production volume, automation strategies and handling methods. The state of the art for the production of these light-weight flexible textile or composite fiber products is setting up multi-stage manual operations for hand layups. Material handling of flexible textile/fiber components is a process bottleneck. Consequently, the long term research goal is to develop semi-automated pick and place processes for flexible materials utilizing collaborative robots within the process. Collaborative robots allow for interactive human-machine tasks to be conducted.

Individuals with hearing impairments often report hearing difficulties within the driving environment. This is an ever growing issue given the increasing population of senior aged drivers. In this study, Speech Intelligibility Index (SII) is used to predict in-vehicle speech intelligibility of individuals having common hearing impairments. The effect of hearing threshold levels obtained from audiograms and the impact of vehicle background noise measured for various vehicle operating conditions, road surface types and talker and listener configurations are investigated. This is done by using measured and user-defined speech spectra as described by ANSI S3.5-1997 (Methods for Calculation of the Speech Intelligibility Index). The results demonstrate poor speech intelligibility for most situations considered and provide evidence for the need to improve automotive interior sound quality in terms of speech intelligibility for hearing impaired drivers including aged drivers.

This research focuses on comparing the biomechanical response of the head and neck of the Hybrid III 3-year-old anthropometric test device finite element model and pediatric cadaver data, under flexion-extension bending and axial tensile loading conditions. Previous experimental research characterized the quasi-static biomechanical response of the pediatric cervical spine under flexion-extension bending and tolerance in tensile distraction loading conditions. Significant differences in rotational and linear stiffness were found between the Hybrid III model and the pediatric cadaver data. In this research the biomechanical child cadaver neck response has been implemented into the 3-year-old Hybrid III child dummy FE model. An explicit finite element code (LS-DYNA) and the modified Hybrid III model were used to numerically simulate the previous cadaver tests and validate the altered Hybrid III neck.

This research focuses on the further development of a child finite element model whereby implementation of pediatric cadaver testing observations considering the biomechanical response of the neck of children under tensile and bending loading has occurred. Prior to this investigation, the biomechanical neck response was based upon scaled adult cadaver behaviour. Alterations to the material properties associated with ligaments, intervertebral discs and facet joints of the pediatric cervical spine were considered. No alteration to the geometry of the child neck finite element model was considered. An energy based approach was utilized to provide indication on the appropriate changes to local neck biomechanical characteristics. Prior to this study, the biomechanical response of the neck of the child finite element model deviated significantly from the tensile and bending cadaver tests completed by Ouyang et al.

Whole field displacement/strain measurement of automotive components can be done efficiently by digital image correlation based technique. Inverse problems with this kind of input data, such as the identification of damage parameters/effective modulus in different part of a component, can be pursued by either virtual fields method or finite element model updating. In this paper, the two methods are applied to the identification of a tension plate with a circular hole, and different aspects of the two methods are discussed. It is found that the success of virtual fields method relies on the choice of a set of optimal virtual displacement fields; finite element model updating, on the other hand, can be applied to any geometry and any load condition, and can also be applied to problems where only limited number of measurements are available. However, its performance relies on the choice of optimization algorithms.

Ignition performance is critical for the implementation of diluted combustion for spark-ignition engines. The short circuit and restrike phenomena can influence the initial ignition volume and discharge duration which are important for the stable ignition processes. In this study, the short circuits and restrikes of spark channels are studied with various flow velocities, spark plug gaps and discharge energies. The development of the spark channels is captured by using the direct imaging technique with a CMOS camera equipped with an image intensifier. A multi-coil ignition system is designed to enable flexible control of discharge energies. The results show that the spark plug gap size is a critical parameter to suppress the phenomena of short circuits and restrikes. With the enlargement of spark plug gap, the maximum and average lengths of the spark channel effectively increase.

The paper describes a closed-loop vehicle simulation environment developed to support a virtual vehicle design and testing methodology, proposed for the University of Windsor Formula SAE team. Virtual prototyping and testing were achieved through co-simulation of Matlab/Simulink® and Carsim®. The development of the required hybrid-control driver and vehicle models are described. The proposed models were validated with in vehicle test data. The proposed methods have shown to be effective and robust in predicting driver response, while controlling the vehicle within the developed simulation environment.

The effects of engine noise in plastic manifolds has been a subject of study in the automotive Industry. Several SAE papers have been published on the subject. Most testing described requires access to engine dynamometers and other elaborate equipment. As part of a general study of plastic intake manifold noise characteristics, this study was undertaken to develop a synthesis bench for enabling low cost noise testing of plastic induction systems including plastic manifolds. Computer simulation of engine intake noise was used as part of a correlation between the plastic manifold synthesis bench and actual engine measurements. The Fast Fourier Transform (FFT) analysis provided analogous results between the predicted theoretical and two measured signals with a fundamental frequency at approximately 80 Hz. Qualitative and statistical comparisons of the time domain signals also proved equally favourable. Recommendations are included for further development of this approach.