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Ultrasonic spot welding (USW) is a promising joining method for magnesium to steel to overcome the difficulties of fusion welding for these two materials with significant differences in melting temperatures. In a previous paper, the results of ultrasonic spot welding of magnesium to steel, with sonotrode engaged Mg piece, was presented. In this study, same material combination (0.8-mm-thick galvanized mild steel and 1.6-mm Mg AZ31B-H24) was used, but with sonotrode engaging steel piece. Various welding time, from 0.4 to 2.0 sec, were applied. Tensile lap-shear test, optical metallography, and scanning electron micrography were conducted for joint strength measurement and microstructural evaluation. The joint strength reached over 4.2 kN at 1.8 sec welding time. Mg-Zn eutectic was formed at the interface, indicating the interfacial temperature over 344°C. The study demonstrated USW to be a viable process for potential manufacturing of mixed-metal joints.

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.

This paper presents on-going finite element modeling efforts of friction stir spot welding (FSSW) process using Abaqus/Explicit as a finite element solver. Three-dimensional coupled thermal-stress model was used to calculate thermo-mechanical response of FSSW process. Adaptive meshing and advection schemes, which makes it possible to maintain mesh quality under large deformations, is utilized to simulate the material flow and temperature distribution in FSSW process. The predicted overall deformation shape of the weld joint resembles that experimentally observed. Temperature and stress graphs in the radial direction as well as temperature-deformation distribution plots are presented.

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.

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.

Metal additive manufacturing has high potential to produce automobile parts, due to its shape flexibility and unique material properties. On the other hand, residual stress which is generated by rapid solidification causes deformation, cracks and failure under building process. To avoid these problems, understanding of internal residual stress distribution is necessary. However, from the view point of measureable area, conventional residual stress measurement methods such as strain gages and X-ray diffractometers, is limited to only the surface layer of the parts. Therefore, neutron which has a high penetration capability was chosen as a probe to measure internal residual stress in this research. By using time of flight neutron diffraction facility VULCAN at Oak Ridge National Laboratory, residual stress for mono-cylinder head, which were made of aluminum alloy, was measured non-distractively. From the result of precise measurement, interior stress distribution was visualized.

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.

Additive manufacturing was used to fabricate a head for an automotive-scale single-cylinder engine operating on natural gas. The head was consisted of a bimetallic composition of stainless steel and bronze. The engine performance using the bimetallic head was compared against the stock cast iron head. The heads were tested at two speeds (1200 and 1800 rpm), two brake mean effective pressures (6 and 10 bar), and two equivalence ratios (0.7 and 1.0). The bimetallic head showed good durability over the test and produced equivalent efficiencies, exhaust temperatures, and heat rejection to the coolant to the stock head. Higher combustion temperatures and advanced combustion phasing resulted from use with the bimetallic head. The implication is that with optimization of the valve timing, an efficiency benefit may be realized with the bimetallic head.

Increasing the strength of materials is effective in reducing weight and boosting structural part performance, but there are cases in where the residual strain generated during the process of manufacturing of high-strength materials results in a decline of durability. It is therefore important to understand how the residual strain in a manufactured component changes due to processing conditions. In the case of a connecting rod, because the strain load on the connecting rod rib sections is high, it is necessary to clearly understand the distribution of strain in the ribs. However, because residual strain is generally measured by using X-ray diffractometers or strain gauges, measurements are limited to the surface layer of the parts. Neutron beams, however, have a higher penetration depth than X-rays, allowing for strain measurement in the bulk material.

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.

Microstructures and failure mechanisms of spot friction welds (SFW) in aluminum 5754 lap-shear specimens were investigated. In order to study the effect of tool geometry on the joint strength of spot friction welds, a concave tool and a flat tool were used. In order to understand the effect of tool penetration depth on the joint strength, spot friction welds were prepared with two different penetration depths for each tool. The results indicated that the concave tool produced slightly higher joint strength than the flat tool. The joint strength did not change for the two depths for the flat tool whereas the joint strength slightly increases as the penetration depth increases for the concave tool. The experimental results show that the failure mechanism is necking and shearing for the spot friction welds made by both tools. The failure was initiated and fractured through the upper sheet under the shoulder indentation near the crack tip.

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.

Aluminum alloys containing cerium have excellent castability and retain a substantial fraction of their room temperature strength at temperatures of 200°C and above. High temperature strength is maintained through a thermodynamically trapped, high surface energy intermetallic. Dynamic load partitioning between the aluminum and the intermetallic increases mechanical response. Complex castings have been produced in both permanent mold and sand castings. This versatile alloy system, using an abundant and inexpensive co-product of rare earth mining, is suitable for parts that need to maintain good properties when exposed to temperatures between 200 and 315°C.

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.

We examine the effects on materials temperatures and engine efficiency via simulations of engines operating at temperatures which exceed the thermal limits of today’s materials. Potential focus areas include high-speed, high-load operation (in the fuel-enrichment zone) as well as conditions of selective cooling at lower speeds and loads. We focus on a light-duty DISI and a heavy-duty CI engine using GT-Power. Temperature distributions within the head, block, piston, and valves were obtained from 3D FEA simulations coupled with 1D GT-Power representations of the engine’s gas flow and combustion regions.

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.