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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.

The increased availability of natural gas (NG) in the U.S. has renewed interest in the application to heavy-duty (HD) diesel engines in order to realize fuel cost savings and reduce pollutant emissions, while increasing fuel economy. Reactivity controlled compression ignition (RCCI) combustion employs two fuels with a large difference in auto-ignition properties to generate a spatial gradient of fuel-air mixtures and reactivity. Typically, a high octane fuel is premixed by means of port-injection, followed by direct injection of a high cetane fuel late in the compression stroke. Previous work by the authors has shown that NG and diesel RCCI offers improved fuel efficiency and lower oxides of nitrogen (NOx) and soot emissions when compared to conventional diesel diffusion combustion. The work concluded that NG and diesel RCCI engines are load limited by high rates of pressure rise (RoPR) (>15 bar/deg) and high peak cylinder pressure (PCP) (>200 bar).

Lean burn or EGR diluted combustion with enhanced charge motion is effective in improving the efficiency of spark ignition engines. However, the ignition process under these conditions is getting more challenging due to higher ignition energy required by the lean or diluted mixture, as well as the interactions of the gas flow on the flame kernel. Enhanced spark discharge energy is essential to initiate the combustion under these conditions. Moreover, the discharge process should be more carefully controlled to improve the effectiveness of the spark. In this study, spark ignition systems with boosted discharge energy are used to ignite diluted air-fuel mixture under forced flow conditions. The impacts of the discharge current level, the discharge duration and the discharge current profile on the ignition are investigated in detail using optical diagnosis.

The ever-stringent emission regulations are major challenges for the diesel fueled engines in automotive industry. The applications of advanced after-treatment technologies as well as alternative fuels [1] are considered as promising methodology to reduce exhaust emission from compression ignition (CI) engines. Using dimethyl ether (DME) as an alternative fuel has been extensively studied by many researchers and automotive manufactures since DME has demonstrated enormous potential in terms of emission reduction, such as low CO emission, and soot and sulfur free. However, the effect of employing DME in a lean NOX trap (LNT) based after-treatment system has not been fully addressed yet. In this work, investigations of the long breathing LNT system using DME as a reductant were performed on a heated after-treatment flow bench with simulated engine exhaust condition.

This study describes a zero-dimensional algorithm for tracking the intake dilution in real-time. The inputs to the model are the oxygen concentration from the exhaust oxygen sensor, the manifold air pressure and temperature (MAP/MAT), the mass air flow (MAF) and the estimated fuel injected per cycle from the engine control module. The intake manifold, the exhaust manifold and EGR system are discretized into 3 volumes and the detailed concentrations of the gas species comprising the exhaust, EGR and intake streams are tracked at each time step (on a cycle-by-cycle basis). The model does not need the EGR ratio to be known in advance and is also applicable to oxygenated fuels such as ethanol. The model response is tuned to a multi-cylinder engine and the model output is empirically validated against a wide range of engine operations including load and EGR transients.

For internal combustion engine systems, lean and diluted combustion is an important technology applied for fuel efficiency improvement. Because of the thermodynamic boundary conditions and the presence of in-cylinder flow, the development of a well-sustained flame kernel for lean combustion is a challenging task. Reliable spark discharge with the addition of enhanced delivered energy is thus needed at certain time durations to achieve successful combustion initiation of the lean air-fuel mixture. For a conventional transistor coil ignition system, only limited amount of energy is stored in the ignition coil. Therefore, both the energy of the spark discharge and the duration of the spark discharge are bounded. To break through the energy limit of the conventional transistor coil ignition system, in this work, an adaptive spark ignition system is introduced. The system has the ability to reconstruct the conductive ion channels whenever it is interrupted during the spark discharge.

Electric vehicle is increasingly becoming popular and an alternative choice for the consumers because of its environment-friendly operation. Permanent magnet synchronous machines are widely and commonly used as traction motors since they provide higher torque and power density. High torque and power density mean higher current which eventually causes higher temperature rise in the motor. Higher temperature rise directly affects the motor output. Standard tests for UDDS (Urban Dynamometer Driving Schedule) and HWFET (Highway Fuel Economy Driving Schedule) drive cycles are used to determine performance of traction motors in terms of torque, power, efficiency and thermal health. Traction motors require high torque at low speed for starting and climbing; high power at high speed for cruising; wide speed range; a fast torque response; high efficiency over wide torque and speed ranges and high reliability.

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.

Empirical results indicated that the engine emission and fuel efficiency of low-temperature combustion (LTC) cycles can be optimized by adjusting the fuel-injection scheduling in order to obtain appropriate combustion energy release or heat-release rate patterns. Based on these empirical results the heat-release characteristics were correlated with the regulated emissions such as soot, hydrocarbon and oxides of nitrogen. The transition from conventional combustion to LTC with the desired set of heat-release rate has been implemented. This transition was facilitated with the simplified heat-release characterization wherein each of the consecutive engine cycles was analyzed with a real-time controller embedded with an FPGA (field programmable gate array) device. The analyzed results served as the primary feedback control signals to adjust fuel injection scheduling. The experimental efforts included the boost/backpressure, exhaust gas recirculation, and load transients in the LTC region.

Simultaneous low NOx (< 0.15 g/kWh) & soot (< 0.01 g/kWh) are attainable for enhanced premixed combustion that may lead to higher levels of hydrocarbons and carbon monoxide emissions as the engine cycles move to low temperature combustion, which is a departure from the ultra low hydrocarbon and carbon monoxide emissions, typical of the high compression ratio diesel engines. As a result, the fuel efficiency of such modes of combustion is also compromised (up to 5%). In this paper, advanced strategies for fuel injection are devised on a modern 4-cylinder common rail diesel engine modified for single cylinder research. Thermal efficiency comparisons are made between the low temperature combustion and the conventional diesel cycles. The fuel injection strategies include single injection with heavy EGR, and early multi-pulse fuel injection under low or medium engine loads respectively.

Extensive empirical work indicates that the exhaust emission and fuel efficiency of modern common-rail diesel engines characterise strong resilience to biodiesel fuels when the engines are operating in conventional high temperature combustion cycles. However, as the engine cycles approach the low temperature combustion (LTC) mode, which could be implemented by the heavy use of exhaust gas recirculation (EGR) or the homogeneous charge compression ignition (HCCI) type of combustion, the engine performance start to differ between the use of conventional and biodiesel fuels. Therefore, a set of fuel injection strategies were compared empirically under independently controlled EGR, intake boost, and exhaust backpressure in order to improve the neat biodiesel engine cycles.

Low temperature combustion (LTC), though effective to reduce soot and oxides of nitrogen (NOx) simultaneously from diesel engines, operates in narrowly close to unstable regions. Adaptive control strategies are developed to expand the stable operations and to improve the fuel efficiency that was commonly compromised by LTC. Engine cycle simulations were performed to better design the combustion control models. The research platform consists of an advanced common-rail diesel engine modified for the intensified single cylinder research and a set of embedded real-time (RT) controllers, field programmable gate array (FPGA) devices, and a synchronized personal computer (PC) control and measurement system.

In this work, engine tests were performed to realize EGR-enabled LTC on a single-cylinder common-rail diesel engine with three different compression ratios (17.5, 15 and 13:1). The engine performance was first investigated at 17.5:1 compression ratio to provide baseline results, against which all further testing was referenced. The intake boost and injection pressure were progressively increased to ascertain the limiting load conditions for the compression ratio. To extend the engine load range, the compression ratio was then lowered and EGR sweep tests were again carried out. The strength and homogeneity of the cylinder charge were enhanced by using intake boost up to 3 bar absolute and injection pressure up to 180 MPa. The combustion phasing was locked in a narrow crank angle window (5~10° ATDC), during all the tests.

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.

Preliminary empirical and modeling analyses are conducted to evaluate the energy efficiency of in-cylinder and external fuel injection strategies and their impact on the energy required to enable diesel particulate filter (DPF) regeneration for instance. During the tests, a thermal wave that is generated from the engine propagates along the exhaust pipe to the DPF substrate. The thermal response of the exhaust system is recorded with the thermocouple arrays embedded in the exhaust system. To implement the external fuel injection, an array of thermocouples and pressure sensors in the DPF provide the necessary feedback to the control system. The external fuel injection is dynamically adjusted based on the thermal response of the DPF substrate to improve the thermal management and to reduce the supplemental energy. This research intends to quantify the effectiveness of the supplemental energy utilization on aftertreatment enabling.

Diesel engines operating in the low-temperature combustion (LTC) mode generally tend to produce very low levels of NOx and soot. However, the implementation of LTC is challenged by the higher cycle-to-cycle variation with heavy EGR operation and the narrower operating corridors. The robustness and efficiency of LTC operation in diesel engines can be enhanced with improvements in the promptness and accuracy of combustion control. A set of field programmable gate array (FPGA) modules were coded and interlaced to suffice on-the-fly combustion event modulations. The cylinder pressure traces were analyzed to update the heat release rate concurrently as the combustion process proceeds prior to completing an engine cycle. Engine dynamometer tests demonstrated that such prompt heat release analysis was effective to optimize the LTC and the split combustion events for better fuel efficiency and exhaust emissions.

This paper presents a fundamental thermodynamic modeling approach to study internal combustion engines. The computations of the thermodynamic functions, especially availability, have been developed to seek better energy utilization, analyze engine performance and optimize design of spark ignition (SI) engines fueled with compressed natural gas (CNG), by using both the first and the second law analyses. A single-zone heat release model with constant thermodynamic properties is built into the air cycle simulation, while a more comprehensive two-zone combustion model with burning rate as a sinusoidal function of crank angle is built into the fuel/air thermodynamic engine cycle simulation. The computations mainly include pressure, unburned and burned zone temperature, indicated work, heat loss, mass blowby, availability destruction due to combustion, fuel chemical availability, availability transfer with heat, availability transfer with work and availability exhaust to the environment.

The fuel called E-85 can be burned effectively in engines similar to the engines currently mass-produced for use with gasoline. Since the ethanol component of this fuel is produced from crops such as corn and sugar cane, the fuel is almost fully renewable. The different physical and chemical properties of E-85, however, do require certain modifications to the common gasoline engine. The Windsor - St. Clair team has focused their attention to modifications that will improve fuel efficiency and reduce tailpipe emissions. Other modifications were also performed to ensure that the vehicle would still operate with the same power and driveability as its gasoline counterpart.

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.

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.