Search Results

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Fracture split forged steel connecting rods are utilized in many new high performance automotive engines to increase durability. Higher strength levels are needed as the power density increases. Fracture splitting without plastic deformation is necessary for manufacturability. Metallurgical design is a key for achieving the required performance levels. Several medium carbon steels containing 0.07 wt pct P, 0.06 wt pct S and various amounts of Mn, Si, V, and N were produced by vacuum induction melting laboratory heats and hot working the cast ingots into plates. The plates were cooled at varying rates to simulate typical cooling methods after forging. Microstructures were generally ferrite and pearlite as evaluated by light optical and scanning electron microscopy. Mechanical properties were determined by standard tensile tests, high strain rate notched tensile tests, and Charpy V-notch impact tests to assess “splittability”.

Although soot-formation processes in diesel engines have been well characterized during the mixing-controlled burn, little is known about the distribution of soot throughout the combustion chamber after the end of appreciable heat release during the expansion and exhaust strokes. Hence, the laser-induced incandescence (LII) diagnostic was developed to visualize the distribution of soot within an optically accessible single-cylinder direct-injection diesel engine during this period. The developed LII diagnostic is semi-quantitative; i.e., if certain conditions (listed in the Appendix) are true, it accurately captures spatial and temporal trends in the in-cylinder soot field. The diagnostic features a vertically oriented and vertically propagating laser sheet that can be translated across the combustion chamber, where “vertical” refers to a direction parallel to the axis of the cylinder bore.

Despite numerous research efforts, there is no reliable and widely accepted tool for the prediction of erosion prone material surfaces due to collapse of cavitation bubbles. In the present paper an Erosion Aggressiveness Index (EAI) is proposed, based on the pressure loads which develop on the material surface and the material yield stress. EAI depends on parameters of the liquid quality and includes the fourth power of the maximum bubble radius and the bubble size number density distribution. Both the newly proposed EAI and the Cavitation Aggressiveness Index (CAI), which has been previously proposed by the authors based on the total derivative of pressure at locations of bubble collapse (DP/Dt>0, Dα/Dt<0), are computed for a cavitating flow orifice, for which experimental and numerical results on material erosion have been published. The predicted surface area prone to cavitation damage, as shown by the CAI and EAI indexes, is correlated with the experiments.

Autonomous ground vehicles can use a variety of techniques to navigate the environment and deduce their motion and location from sensory inputs. Visual Odometry can provide a means for an autonomous vehicle to gain orientation and position information from camera images recording frames as the vehicle moves. This is especially useful when global positioning system (GPS) information is unavailable, or wheel encoder measurements are unreliable. Feature-based visual odometry algorithms extract corner points from image frames, thus detecting patterns of feature point movement over time. From this information, it is possible to estimate the camera, i.e., the vehicle’s motion. Visual odometry has its own set of challenges, such as detecting an insufficient number of points, poor camera setup, and fast passing objects interrupting the scene. This paper investigates the effects of various disturbances on visual odometry.

Since the advent of P/M technology as a near net shape production process, millions of mechanical components of various shapes and sizes have been produced. Although P/M continues to be one of the fast growing shaping processes, it suffers from the inability to produce intricate geometry's such as internal tapers, threads or recesses perpendicular to pressing direction. In such cases application of machining as a secondary forming operation becomes the preferred alternative. However, machining of P/M parts due to their inherent porosity is known to decrease tool life and increase tool chatter and vibration. Consequently, several attempts have been made to improve the machinability of P/M materials by either addition of machinability enhancing elements such as sulfur, calcium, tellurium, selenium, etc., or by resin impregnation of P/M parts.

Engineering new technology and products challenges managers to balance design innovation and program risk. To do this, managers need methods to judge future results to avoid program and product disasters. Besides the traditional prediction tools of schedule, simulations and “iron tests”, process control standards (with measurements) can also be applied to the development programs to mitigate risks. This paper briefly discusses the theory and case history behind some new process control methods and standards currently in place at Caterpillar's Electrical & Electronics department. Process standards reviewed in this paper include process mapping, ISO9001, process controls, and process improvement models (e.g. SEI's CMMs.)

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

In the last decade, considerable advances have been made in reliability-based design optimization (RBDO). One assumption in RBDO is that the complete information of input uncertainties are known. However, this assumption is not valid in practical engineering applications, due to the lack of sufficient data. In practical engineering design, information concerning uncertainty parameters is usually in the form of finite samples. Existing methods in uncertainty based design optimization cannot handle design problems involving epistemic uncertainty with a shortage of information. Recently, a novel method referred to as Bayesian Reliability-Based Design Optimization (BRBDO) was proposed to properly handle design problems when engaging both epistemic and aleatory uncertainties [1]. However, when a design problem involves a large number of epistemic variables, the computation task for BRBDO becomes extremely expensive.

Researchers desire to evaluate system reliability uniquely and efficiently. Despite its strong technical demand, little progress has been made on system reliability analysis in the last two decades. Up to now, bound methods for system reliability prediction have been dominant. For system reliability bounds, the second order bound method gives fairly accurate prediction for system reliability assuming that the probabilities of second-order joint events are accurately obtained. Two primary challenges in system reliability analysis are evaluation of the probabilities of second-order joint events and no unique system reliability for design optimization. Firstly, the greatest technical demand is found in an accurate and efficient method to numerically evaluate the probability of a second-order joint event.

The bending fatigue performance of high temperature (1050 °C) vacuum carburized Nb modified 8620 steel, with niobium additions of 0.02, 0.06 and 0.1 wt pct, was evaluated utilizing a modified Brugger specimen geometry. Samples were heated at two different rates (20 and 114 °C min-1) to the carburizing temperature resulting in different prior austenite grain structures that depended on the specific Nb addition and heating rate employed. At the lower heating rate, uniform fine grained prior austenite grain structures developed in the 0.06 and 0.1 Nb steels while a duplex grain structure with the presence of large (>200 μm grains) developed in the 0.02 Nb steel. At the higher heating rate the propensity for abnormal grain growth was highest in the 0.02 Nb steel and complete suppression of abnormal grain growth was achieved only with the 0.1 Nb steel.

This paper presents an innovative approach for quality engineering using the Eigenvector Dimension Reduction (EDR) Method. Currently industry relies heavily upon the use of the Taguchi method and Signal to Noise (S/N) ratios as quality indices. However, some disadvantages of the Taguchi method exist such as, its reliance upon samples occurring at specified levels, results to be valid at only the current design point, and its expensiveness to maintain a certain level of confidence. Recently, it has been shown that the EDR method can accurately provide an analysis of variance, similar to that of the Taguchi method, but is not hindered by the aforementioned drawbacks of the Taguchi method. This is evident because the EDR method is based upon fundamental statistics, where the statistical information for each design parameter is used to estimate the uncertainty propagation through engineering systems.

Drawbeads in production stamping dies often have insufficient penetration of the male bead into the female cavity. With insufficient penetration, the actual bending radii of the sheet metal are larger than the geometrical radii of the drawbead. The actual bending radii in the sheet directly affect the force that restrains sheet movement. To predict the restraining stress due to a drawbead, it is necessary to know the actual bending radii in the sheet as it passes though the drawbead. Data from a previous study are used to develop empirical regression equations for predicting measured radii of the sheet that is bent around the radii in a drawbead. A physical model for the evolution of the sheet radii as the drawbead closes is proposed. This model is consistent with the empirical equations and the mechanics of the sheet bending process.

With the increased use of tubular steel products, especially for automotive hydroforming applications, there is increased interest in understanding the mechanical properties measured by tensile tests from specimens of different orientations in the tube. In this study, two orientations of tensile specimens were evaluated -- axial specimens with and without flattening and flattened circumferential specimens. Three steels were evaluated -- two thicknesses of aluminum killed drawing quality (AKDQ) steel and one thickness of high strength low alloy (HSLA) steel. Mechanical property data were obtained from the flat stock, conventional production tubes and quasi tubes. Quasi tubes were produced from the flat stock on a 3-roll bender, but the quasi tube was not welded or sized.

In recent years, Nearfield Acoustical Holography (NAH) has been used to identify stationary vehicle exterior noise sources. However that application has usually been limited to individual components. Since powertrain noise sources are hidden within the engine compartment, it is difficult to use NAH to identify those sources and the associated partial field that combine to create the complete exterior noise field of a motor vehicle. Integrated Nearfield Acoustical Holography (INAH) has been developed to address these concerns: it is described here. The procedure entails sensing the sources inside the engine compartment by using an array of reference microphones, and then calculating the associated partial radiation fields by using NAH. In the second part of this paper, the use of farfield arrays is considered. Several array techniques have previously been applied to identify noise sources on moving vehicles.

Elastomers are traditionally designed for use in applications that require specific mechanical properties. Unfortunately, these properties change with respect to many different variables including heat, light, fatigue, oxygen, ozone, and the catalytic effects of trace elements. When elastomeric mounts are designed for NVH use in vehicles, they are designed to isolate specific unwanted frequencies. As the elastomers age however, the desired elastomeric properties may have changed with time. This study looks at the variability seen in new vehicle engine mounts and how the dynamic properties change with respect to miles accumulated on fleet and durability test vehicles.

A revolutionary interplanetary rapid transit concept for transporting scientists and explorers between Earth and Mars is presented by Global Aerospace Corporation under funding from the NASA Institute for Advanced Concepts (NIAC) with support from the Colorado School of Mines, and Science Applications International Corporation. We describe an architecture that uses highly autonomous spaceships, dubbed Astrotels; small Taxis for trips between Astrotels and planetary Spaceports; Shuttles that transport crews to and from orbital space stations and planetary surfaces; and low-thrust cargo freighters. In addition we discuss the production of rocket fuels using extraterrestrial materials; aerocapture to slow Taxis at the planets; and finally describe a number of trade studies and their life-cycle cost results.

Propelled by the renewed international interest in returning to the Moon, an international consortium organized the first European Lunar Base Design Workshop in the summer of 2002. The objective of this Workshop was to propose new design concepts for human and robotic exploration of the Moon and move beyond the outdated ‘man-in-a-can’ genre of space architecture. The Workshop introduced a new genre in lunar base architecture, deriving from bold, innovative and unconventional thinking. It generated experimental concepts for sustainable, advanced, user-oriented architectures for future lunar bases. The Workshop participants chose diverse moon mission scenarios including ice mining, solar cell production, lunar telescopes, He3 mining, research and commercial operations. This paper will present the most important explorations and concepts from this Workshop. It will discuss the rationale behind adopting a multidisciplinary and multicultural design studio approach.

Most of the history of systems engineering has been focused on processes for engineering a single complex system. However, most large enterprises design, manufacture, operate, sell, or support not one product but multiple product lines of related but varying systems. They seek to optimize time to market, costs of development and production, leverage of intellectual assets, best use of talented human resources, overall competitiveness, overall profitability and productivity. Optimizing globally across multiple product lines does not follow from treating each system family member as an independently engineered system or product. Traditional systems engineering principles can be generalized to apply to families. This article includes a multi-year case study of the actual use of a generic model-based systems engineering methodology for families, Systematica™, across the embedded electronic systems products of one of the world's largest manufacturers of heavy equipment.