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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.

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.

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.

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.

Extensive empirical work indicates that exhaust gas recirculation (EGR) is effective to lower the flame temperature and thus the oxides of nitrogen (NOx) production in-cylinder in diesel engines. Soot emissions are reduced in-cylinder by improved fuel/air mixing. As engine load increases, higher levels of intake boost and fuel injection pressure are required to suppress soot production. The high EGR and improved fuel/air mixing is then critical to enable low temperature combustion (LTC) processes. The paper explores the properties of the Fuels for Advanced Combustion Engines (FACE) Diesel, which are statistically designed to examine fuel effects, on a 0.75L single cylinder engine across the full range of load, spanning up to 15 bar IMEP. The lower cetane number (CN) of the diesel fuel improved the mixing process by prolonging the ignition delay and the mixing duration leading to substantial reduction of soot at low to medium loads, improving the trade-off between NOx and soot.

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.

In the recent decades, the emission and fuel efficiency regulations put forth by the emission regulation agencies have become increasingly stringent and this trend is expected to continue in future. The advanced spark ignition (SI) engines can operate under lean conditions to improve efficiency and reduce emissions. Under such lean conditions, the ignition and complete combustion of the charge mixture is a challenge because of the reduced charge reactivity. Enhancement of the in-cylinder charge motion and turbulence to increase the flame velocity, and consequently reduce the combustion duration is one possible way to improve lean combustion. The role of air motion in better air-fuel mixing and increasing the flame velocity, by enhancing turbulence has been researched extensively. However, during the ignition process, the charge motion can influence the initial spark discharge, resulting flame kernel formation, and flame propagation.

Hollow polymer-based automotive components cannot, in general, be directly injection molded because they cannot be ejected from the mold. The common practice is to injection mold two or more parts, and then join these together with a welding process. Of the many joining process available, laser welding has an advantage in geometric design freedom. The laser weld joints are also generally stronger than those of vibration welds because the weld joints are located in the walls rather than on external flanges. Eliminating the external flanges also makes the part more compact. In transmission laser welding processes, the laser beam passes through a transparent part to its interface with an opaque part. The beam energy is absorbed near the interface in the opaque part, and heat flows back across to the transparent half to make the weld pool. So successful laser welds are possible only when there is a continuous interfacial fit between the parts.

Laser cladding is a method of material deposition through which a powdered or wire feedstock material is melted and consolidated by use of a laser to coat part of a substrate. Determining the parameters to fabricate the desired clad bead geometry for various configurations is problematic as it involves a significant investment of raw materials and time resources, and is challenging to develop a predictive model. The goal of this research is to develop an experimental methodology that minimizes the amount of data to be collected, and to develop a predictive model that is accurate, adaptable, and expandable. To develop the predictive model of the clad bead geometry, an integrated five-step approach is presented. From the experimental data, an artificial neural network model is developed along with multiple regression equations.

Laser cladding is used to coat a surface of a metal to enhance the metallurgical properties at the surface level of a substrate. For surface cladding operations, overlapping bead geometry is required. Single bead analyses do not provide a complete representation of essential properties; hence, this research focuses on overlapping conditions. The research scope targets the coaxial laser cladding process specifically for P420 stainless steel clad powder using a fiber optic laser with a 4.3 mm spot size on a low/medium carbon structural steel plate (AISI 1018). Many process parameters influence the bead geometrical shape, and it is assumed that the complex temperature distributions within the process could cause subsequent large variations in hardness values. The bead overlap configurations experiments are performed with 40%, 50% and 60% bead overlaps for a three-pass bead formation.

This empirical work investigates the impacts of thermodynamic parameters, such as pressure and temperature, and fuel properties, such as fuel Cetane number and aromatic contents on ignition delay in diesel engines. Systematic tests are conducted on a single-cylinder research engine to evaluate the ignition delay changes due to the fuel property differences at low, medium and high engine loads under different EGR dilution ratios. The test fuels offer a range of Cetane numbers from 28 to 54.2 and aromatic contents volume ratios from 19.4% to 46.6%. The experimental results of ignition delays are used to derive an ignition delay model modified from Arrhenius’ expression. Following the same format of Arrhenius’ equation, the model incorporates the pressure and temperature effects, and further includes the impacts of intake oxygen concentration, fuel Cetane number and aromatic contents volume ratio on the ignition delay.