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Ultrasonic spot welds were made between sheets of 0.8-mm-thick hot-dip-galvanized mild steel and 1.6-mm-thick AZ31B-H24. Lap-shear strengths of 3.0-4.2 kN were achieved with weld times of 0.3-1.2 s. Failure to achieve strong bonding of joints where the Zn coating was removed from the steel surface indicate that Zn is essential to the bonding mechanism. Microstructure characterization and microchemical analysis indicated temperatures at the AZ31-steel interfaces reached at least 344°C in less than 0.3 s. The elevated temperature conditions promoted annealing of the AZ31-H24 metal and chemical reactions between it and the Zn coating.

Three dimensional fabrics have seen increasing use lately as composite reinforcements. Advantages over prepreg or chopped fiber processes can include cost, handling, consistent quality, impact behavior, and resistance to delamination [1]. To gain acceptance in the transportation industry it is imperative that properties including dynamic and fatigue behavior be designable. A Progressive Failure Analysis (PFA) was developed jointly by Alpha Star Corp and NASA to predict fatigue life of composites and determine their damage mechanisms so that the life could be extended. The title of this software package is GENOA™, and it was used to focus on the three dimensional fabric called 3WEAVE™ made by 3TEX, Inc. It was discovered through fatigue testing that void content greatly affected fatigue life for the 3D E-glass fabric reinforcing a polyurethane modified vinyl ester resin called Dion 9800 from Reichhold. This is a common characteristic for most structural materials.

We present techniques of symbolic time-series analysis which are useful for analyzing temporal patterns in dynamic measurements of engine combustion variables. We focus primarily on techniques that characterize predictability and the occurrence of repeating temporal patterns. These methods can be applied to standard, cycle-resolved engine combustion measurements, such as IMEP and heat release. The techniques are especially useful in cases with high levels of measurement and/or dynamic noise. We illustrate their application to experimental data from a production V8 engine and a laboratory single-cylinder engine.

The objective of the research presented in this paper was to assess the influence of stamping process on crash response of UltraLight Steel Auto Body (ULSAB) [1] vehicle. Considered forming effects included thickness variations and plastic strain hardening imparted in the part forming process. The as-formed thickness and plastic strain for front crash parts were used as input data for vehicle crash analysis. Differences in structural performance between crash models with and without forming data were analyzed in order to determine the effects and feasibility of integration of forming processes and crash models.

We utilize physically-based models for diesel exhaust catalytic oxidation and urea-based selective catalytic NOx reduction to study their impact on drive cycle performance of hypothetical light-duty diesel-powered hybrid and plug-in hybrid vehicles (HEVs and PHEVs). The models have been implemented as highly flexible SIMULINK block modules that can be used to study multiple engine-aftertreatment system configurations. The parameters of the NOx reduction model have been adjusted to reflect the characteristics of commercially available Cu-zeolite catalysts, which are of widespread current interest. We demonstrate application of these models using the Powertrain System Analysis Toolkit (PSAT) software for vehicle simulations, along with a previously published methodology that accounts for emissions and temperature transients in the engine exhaust.

The heat treatment of steel parts is an essential step in the manufacturing of high-performance components for a variety of commercial and military products. Distortion in the size and shape of parts resulting from the heat treatment process is a pervasive manufacturing problem that causes higher finishing costs, excessive scrap and rework, long delivery times, and negative environmental impact. To date, techniques that have been developed to reduce or eliminate heat treatment distortion are largely based on experience and have been limited to trial and error. This presentation describes the philosophy and results of an ongoing collaborative project to develop a methodology and computer simulation capability to predict ferrous alloy component response (distortion, residual stress, and microstructure) to industrial heat treatment processes for automotive, truck, bearing, and aerospace applications.

The computer-aided-design and analysis of a robust casting process requires the optimization of both mold filling and solidification. A number of commercial casting codes are available for modeling the fluid flow during mold filling and the heat transfer during solidification. The next generation casting process models will build on present capabilities to allow the prediction of microporosity and other defects and microstructure. This paper will discuss the issues involved in the development of next generation casting process models and present results from a computer model for microporosity prediction that is based on first principles, and will take into account alloy composition, alloy microstructure, the initial hydrogen content of the liquid alloy, and the resistance to inter-dendritic fluid flow to feed shrinkage.

An operational challenge associated with SCR catalysts is the NH3 slip control, particularly for commercial small pore Cu-zeolite formulations as a consequence of their significant ammonia storage capacity. The desorption of NH3 during increasing temperature transients is one example of this challenge. Ammonia slipping from SCR catalyst typically passes through a platinum based ammonia oxidation catalyst (AMOx), leading to the formation of the undesired byproducts NOx and N2O. We have discovered a distinctive characteristic, an overlapping NH3 desorption and oxidation, in a state-of-the-art Cu-zeolite SCR catalyst that can minimize NH3 slip during temperature transients encountered in real-world operation of a vehicle.

Neutron diffraction is a powerful tool that can be used to identify the phases present and to measure the spacing of the atomic planes in a material. Thus, the residual stresses can be determined within a component and/or the phases present. New intercritically austempered irons rely on the unique properties of the austenite phase present in their microstructures. If these materials are to see widespread use, methods to verify the quality (behavior consistency) of these materials and to provide guidance for further optimization will be needed. Neutron diffraction studies were performed at the second generation neutron residual stress facility (NRSF2) at the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory on a variety of intercritically austempered irons. For similar materials, such as TRIP steels, the strengthening mechanism involves the transformation of metastable austenite to martensite during deformation.

Driver is a key component in vehicle simulation. An ideal driver model simulates driving patterns a human driver may perform to negotiate road profiles. There are simulation packages having the capability to simulate driver behavior. However, it is rarely documented how they work with road profiles. This paper proposes a new truck driver model for vehicle simulation to imitate actual driving behavior in negotiating road grade and curvature. The proposed model is developed based upon Gipps' car-following model. Road grade and curvature were not considered in the original Gipps' model although it is based directly on driver behavior and expectancy for vehicles in a stream of traffic. New parameters are introduced to capture drivers' choice of desired speeds that they intend to use in order to negotiating road grade and curvature simultaneously. With the new parameters, the proposed model can emulate behaviors like uphill preparation for different truck drivers.

Metal Compression Forming (MCF) is a variant of the squeeze casting process, in which molten metal is allowed to solidify under pressure in order to close porosity and form a sound part. However, the MCF process applies pressure on the entire mold face, thereby directing pressure on all regions of the casting and producing a uniformly sound part. The process is capable of producing parts with properties close to those of forgings, while retaining the near net shape, complexity in geometry, and relatively low cost of the casting process. The paper describes the casting process development involved in the production of an aluminum A357 alloy motor mount bracket, including the use of a filling and solidification model to design the gating and determine process parameters. Tensile properties of the component are presented and correlated with those of forged components.

Urea-SCR systems are potentially a highly-effective means of NOX reduction for light-duty diesel vehicles. However, use of urea-SCR technologies at low temperatures presents unique technical challenges. This study was undertaken to provide more knowledge about low temperature urea decomposition and the resulting effects on SCR performance. Data are presented for experiments using two SCR catalysts of differing size with a light-duty diesel engine. Analyses of the NOX reduction efficiency, NH3 storage phenomena, and unregulated emissions are shown. Over production of NO2 by the oxidation catalyst is demonstrated to be problematic at 25,000 hr-1 space velocity for a range of temperatures. This leads to production of N2O by both SCR catalysts that is higher when urea is injected than when NH3 is injected.

A transient, one-dimensional lean NOx trap (LNT) model is described and implemented for vehicle systems simulations. The model accounts for conservation of chemical species and thermal energy, and includes the effects of O₂ storage and NOx storage (in the form of nitrites and nitrates). Nitrites and nitrates are formed by diffusion of NO and NO₂, respectively, into sorbent particles, and reaction rates are controlled by chemical kinetics and solid-phase diffusion. The model also accounts for thermal aging and sulfation by means of empirical correlations, which have been derived from laboratory experiments. Example simulation results using the Powertrain Systems Analysis Toolkit (PSAT) are presented.

Carbon fiber composite use in automobiles and light trucks could dramatically reduce energy use and engine-out emissions. However, worldwide capacity of 28,000 tonnes per year of carbon fiber from polyacrylonitrile (PAN) and petroleum pitch could support limited automotive use. Production of high-volume, industrial-grade fiber from renewable and recycled polymers (lignin, recycled plastics, regenerated cellulosics) could meet automotive demand. Profiles of material volumes, carbon content, and melting points indicate several attractive candidates for production melt-spun carbon fiber feedstocks. Effects on the carbon fiber production cycle and its integration into automotive production are discussed.

Given the importance of the fuel-injection process on the combustion and emissions performance of gasoline direct injected engines, there has been significant recent interest in understanding the fluid dynamics within the injector, particularly around the needle and through the nozzles. The pressure losses and transients that occur in the flow passages above the needle are also of interest. Simulations of these injectors typically use the nominal design geometry, which does not always match the production geometry. Computed tomography (CT) using x-ray and neutron sources can be used to obtain the real geometry from production injectors, but there are trade-offs in using these techniques. X-ray CT provides high resolution, but cannot penetrate through the thicker parts of the injector. Neutron CT has excellent penetrating power but lower resolution.

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving.

To quantify the fuel economy (FE) effect of some common vehicle accessories or alterations, a compact passenger sedan and a sport utility vehicle (SUV) were subjected to SAE J2263 coastdown procedures. Coastdowns were conducted with low tire pressure, all windows open, with a roof top or hitch-mounted cargo carrier, and with the SUV pulling an enclosed cargo trailer. From these coastdowns, vehicle dynamometer coefficients were developed which enabled the execution of vehicle dynamometer experiments to determine the effect of these changes on vehicle FE and emissions over standard drive cycles and at steady highway speeds. In addition, two minivans were subjected to coastdowns to examine the similarity in derived coefficients for two duplicate vehicles of the same model. The FE penalty associated with the rooftop cargo box mounted on the compact sedan was as high as 25-27% at higher speeds, where the aerodynamic drag is most pronounced.

The Friction Stir Spot Welding (FSSW) process is a derivative of the friction stir welding (FSW) process, without lateral movement of the tool during the welding process. It has been applied in the production of aluminum joining for various Mazda and Toyota vehicles. Most of the applications and published studies were concentrated in aluminum sheet in the range of 1.0 to 1.5 mm, suitable for non-structural automotive closure applications. The objective of this study is to study the feasibility of FSSW process for automotive structural aluminum joining, up to 3 mm in thickness, for potentially replacement of self-piercing rivets (SPR) process. Joining thicker aluminum with FSSW tooling with a typical smooth concave shoulder and threaded probing pin, requires long process time, which would not be appropriate in mass-production automotive body construction. In this paper, an innovative FSSW tool with grooved shoulder was developed.

The latent heat-of-vaporization (HoV) of blends of biofuel and hydrocarbon components into gasolines has recently experienced expanded interest because of the potential for increased HoV to increase fuel knock resistance in direct-injection (DI) engines. Several studies have been conducted, with some studies identifying an additional anti-knock benefit from HoV and others failing to arrive at the same conclusion. Consideration of these studies holistically shows that they can be grouped according to the level of fuel octane sensitivity variation within their fuel matrices. When comparing fuels of different octane sensitivity significant additional anti-knock benefits associated with HoV are sometimes observed. Studies that fix the octane sensitivity find that HoV does not produce additional anti-knock benefit. New studies were performed at ORNL and NREL to further investigate the relationship between HoV and octane sensitivity.

Lean Gasoline Direct Injection (LGDI) combustion is a promising technical path for achieving significant improvements in fuel efficiency while meeting future emissions requirements. Though Stoichiometric Gasoline Direct Injection (SGDI) technology is commercially available in a few vehicles on the American market, LGDI vehicles are not, but can be found in Europe. Oak Ridge National Laboratory (ORNL) obtained a European BMW 1-series fitted with a 2.01 LGDI engine. The vehicle was instrumented and commissioned on a chassis dynamometer. The engine and after-treatment performance and emissions were characterized over US drive cycles (Federal Test Procedure (FTP), the Highway Fuel Economy Test (HFET), and US06 Supplemental Federal Test Procedure (US06)) and steady state mappings. The vehicle micro hybrid features (engine stop-start and intelligent alternator) were benchmarked as well during the course of that study.