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Three-dimensional flows around a car configuration, a Mazda RX-7, were computed by directly integrating the governing unsteady, incompressible Navier-Stokes equations. A well-established finite-difference procedure was utilized. The basic equations were formulated in a generalized coordinate system. A third-order upwind scheme was applied to discretize the equations, and the numerical solutions were acquired without using any explicit turbulence models. Elaborate numerical results were presented at a high Reynolds number, Re=106 (based on the body length). In order to investigate the influence of the cross wind, computations were carried out for two yaw angles, i.e., 0 degree and 30 degrees. Extensive flow visualizations, using state-of-the-art computer graphics, were performed; details of the three-dimensional flow structure were examined. Well-controlled wind tunnel experiments were also conducted.

This paper presents an Axiomatic Design framework for manufacturing system design and illustrates how lean cellular manufacturing can achieve volume flexibility. Axiomatic Design creates a design framework by mapping the functional requirements of a system to specific design parameters. Volume flexibility is often neglected as a requirement of manufacturing systems. Very few industries are fortunate enough to experience stable or predictable product demand. In reality, demand is often volatile and uncertain. It is important that manufacturing system designers are aware of manufacturing system types which can accommodate volume flexibility and follow a structured design methodology that assures that all requirements are met by the system.

Optimal design of modern direct injection spark-ignition engines depends heavily on the characteristics and distribution of the fuel spray. This study was designed to compliment imaging experiments of changes in the spray structure due to fuel volatility and operating conditions. Use of phase-Doppler particle analysis (PDPA) allows quantitative point measurements of droplet diameter and velocity. In agreement with imaging experiments, the results show that the spray structure changes not only with ambient gas density, which is often measured, but also with fuel temperature and volatility. The mean droplet diameter was found to decrease substantially with increasing fuel temperature and decreasing ambient density. Under conditions of low potential for vaporization, the observed trends in mean droplet sizes agree with published correlations for pressure-swirl atomizers.

Optimal design of modern direct injection spark-ignition engines depends heavily on the characteristics and distribution of the fuel spray. This study was designed to investigate changes in the spray properties due to fuel volatility and operating conditions using a firing optically-accessible engine with planar laser-induced fluorescence (PLIF) imaging. The results show that the spray structure changes not only with ambient gas density, which is often measured, but also with fuel temperature and volatility. As ambient pressure decreases and fuel temperature increases, the volatile ends of multi-component fuels evaporate quickly, disrupting the spray structure and producing a vapor core along the axis of the spray. Beyond a certain point, evaporation is rapid enough to expand the initial cone angle of the spray while causing a decrease in the overall spray width.

Lubricant viscosity along the engine cylinder liner varies by an order of magnitude due to local temperature variation and vaporization effects. Tremendous potential exists for fuel economy improvement by optimizing local viscosity variations for specific operating conditions. Methods for analytical estimation of friction and wear in the power-cylinder system are reviewed and used to quantify opportunities for improving mechanical efficiency and fuel economy through lubricant formulation tailored specifically to liner temperature distributions. Temperature dependent variations in kinematic viscosity, density, shear thinning, and lubricant composition are investigated. Models incorporating the modified Reynolds equation were used to estimate friction and wear under the top ring and piston skirt of a typical 11.0 liter diesel engine.

Catalytic and non-catalytic engine aftertreatment components, such as the diesel oxidation catalyst (DOC), selective catalytic reduction on filter (SCRF), the gasoline particulate filter (GPF) and the diesel particulate filter (DPF) are complex, multifunctional emissions control technologies that are robustly designed for extended use in harsh automotive exhaust environments. Over the useful component lifetime, lubricant-derived inorganic and incombustible ash accumulates in and/or on the surface of the aforementioned aftertreatment components, resulting in degraded performance and other potential problems. In order to better understand effects of ash in such components, a multiscale analytical approach is necessary, requiring a variety of experimental tools.

Three-piece oil control rings (TPOCR) are widely used in the majority of modern gasoline engines and they are critical for lubricant regulation and friction reduction. Despite their omnipresence, the TPOCRs’ motion and sealing mechanisms are not well studied. With stricter emission standards, gasoline engines are required to maintain lower oil consumption limits, since particulate emissions are strongly correlated with lubricant oil emissions. This piqued our interest in building a numerical model coupling TPOCR dynamics and oil transport to explain the physical mechanisms. In this work, a 2D dynamics model of all three pieces of the ring is built as the main frame. Oil transport in different zones are coupled into the dynamics model. Specifically, two mass-conserved fluid sub-models predict the oil movement between rail liner interface and rail groove clearance to capture the potential oil leakage through TPOCR. The model is applied on a 2D laser induced fluorescence (2D-LIF) engine.

We report on a feasibility study of an optical micro-electro-mechanical systems (MEMS) flow sensor to measure flow rate using Moiré fringe displacement of a floating element. Due to constraints on weight, power, and size for space environmental systems, the development of sensor components that minimize the equivalent systems mass (ESM) while maintaining or exceeding required specifications is highly desirable. A feature of the optical detection method is a physical separation of electrical components from the flow stream. The geometric Moiré fringe shift optically amplifies small displacements by the ratio of the fringe pitch to the movable grating pitch that is detected using an external CCD imager, providing an electrically isolated, robust, direct scheme for detecting flow from shear stress induced displacement.

The NOx emission and knock characteristics of a PFI engine operating on ethanol/gasoline mixtures were assessed at 1500 and 2000 rpm with λ =1 under Wide-Open-Throttle condition. There was no significant charge cooling due to fuel evaporation. The decrease in NOx emission and exhaust temperature could be explained by the change in adiabatic flame temperature of the mixture. The fuel knock resistance improved significantly with the gasohol so that ignition could be timed at a value much closer or at MBT timing. Changing from 0% to 100% ethanol in the fuel, this combustion phasing improvement led to a 20% increase in NIMEP and 8 percentage points in fuel conversion efficiency at 1500 rpm. At 2000 rpm, where knocking was less severe, the improvement was about half (10% increase in NIMEP and 4 percentage points in fuel conversion efficiency).

Protecting the piston ring and liner interface is critical to the proper operation of internal combustion engines. Specifically, the dry region, which is the portion of the liner above the Top Dead Center (TDC) of the Oil Control Ring (OCR), needs proper lubrication to reduce wear and to maintain sustainability. However, the mechanisms by which oil is distributed to such region have not been investigated. This paper presents the first attempt to understand dry region lubrication by means of the oil-gas interaction below the top ring gap through a combination of experimental and modeling approaches. An optical engine with 2D Laser Induced Fluorescence (2D-LIF) technique was applied to visualize the oil flow below the top ring gap. It was observed that the two vortices downstream the top ring gap can cause oil bridging towards the liner, providing lubrication to the ring-liner interface.

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.