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Career development is no longer something you focus on in your twenties and are set for life, it is ongoing and constant. New technologies, globalization and the world-wide competition for jobs demand that we continue to grow our skills and knowledge throughout our life. This session will provide you with tools to help you meet this demand as an engineering professional. Participants will create a personal mission statement and set career goals, identify the best way to research new opportunities and build their network while also crafting a personal brand with consistent messaging. Organizer Martha Schanno, SAE International Panelist Caryn Mateer, Transformational Leaders Intl. Kathleen Riley, Transformational Leaders Intl.

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).

In order to ensure the safety of a structure, adequate strength for structural elements must be provided. Moreover, catastrophic deformations such as buckling must be prevented. Using the linear finite element method, deterministic buckling analysis is completed in two main steps. First, a static analysis is performed using an arbitrary ordinate applied loading pattern. Using the obtained element axial forces, the geometric stiffness of the structure is assembled. Second, an eigenvalue problem is performed between structure's elastic and geometric stiffness matrices, yielding the structure's critical buckling loads. However, these deterministic approaches do not consider uncertainty the structure's material and geometric properties. In this work, a new method for finite element based buckling analysis of a structure with uncertainty is developed. An imprecise probability formulation is used to quantify the uncertainty present in the mechanical characteristics of the structure.

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.

Disposal of automobile shredder residue (ASR), remaining from the reclamation of steel from junked automobiles, promises to be an increasing environmental and economic concern. Argonne National Laboratory (ANL) is investigating alternative technology for recovering value from ASR while also, it is hoped, lessening landfill disposal concerns. Of the ASR total, some 20% by weight consists of plastics. Preliminary work at ANL is being directed toward developing a protocol, both mechanical and chemical (solvent dissolution), to separate and recover polyurethane foam and the major thermoplastic fraction from ASR. Feasibility has been demonstrated in laboratory-size equipment.

The purpose of this paper is to outline the development and implementation of SAE J2953. SAE J2953 contains the requirements and procedures of interoperability testing. Within SAE J2953 interoperability test articles are defined as an Electric Vehicle Supply Equipment (EVSE) paired with a Plug-in Electric Vehicle (PEV). SAE J2953 requires the development and application of test fixtures with the ability to monitor mechanical forces and electrical signals of a charge system without modification or disassembly of the EVSE and PEV under test. Electrical signal monitoring includes pilot, proximity, and line conductors of the SAE J1772 TM AC coupler. This paper will outline the requirements of the fixtures as well as a specific build. Data will be presented showing full implementation of the SAE J2953 procedures including root-cause analysis and standards gap discovery.

Cavitation plays an important role in fuel injection systems. It alters the nozzle's internal flow structure and discharge coefficient, and also contributes to injector wear. Quantitatively measuring and mapping the cavitation vapor distribution in a fuel injector is difficult, as cavitation occurs on very short time and length scales. Optical measurements of transparent model nozzles can indicate the morphology of large-scale cavitation, but are generally limited by the substantial amount of scattering that occurs between vapor and liquid phases. These limitations can be overcome with x-ray diagnostics, as x-rays refract, scatter and absorb much more weakly from phase interfaces. Here, we present an overview of some recent developments in quantitative x-ray diagnostics for cavitating flows. Measurements were conducted at the Advanced Photon Source at Argonne National Laboratory, using a submerged plastic test nozzle.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.

The process of shredding end-of-life vehicles to recover metals results in a byproduct commonly referred to as shredder residue. The four and a half million metric tons of shredder residue produced annually in the United States is presently land filled. To meet the challenges of automotive materials recycling, the U.S. Department of Energy is supporting research at Argonne National Laboratory in cooperation with the Vehicle Recycling Partnership (VRP) of the United States Council for Automotive Research (USCAR) and the American Plastics Council. This paper presents the results of a study that was conducted by Argonne to determine variations in the composition of shredder residue from different shredders. Over 90 metric tons of shredder residues were processed through the Argonne pilot plant. The contents of the various separated streams were quantitatively analyzed to determine their composition and to identify materials that should be targeted for recovery.

Preliminary research in our laboratory has demonstrated that boric acid is an effective lubricant with an unusual capacity to reduce the sliding friction (providing friction coefficients as low as 0.02) and wear of metallic and ceramic materials. More recent studies have revealed that water or methanol solutions of boric acid can be used to prepare strongly bonded layers of boric acid on aluminum surfaces. It appears that boric acid molecules have a strong tendency to bond chemically to the naturally oxidized surfaces of aluminum and its alloys and to make these surfaces very slippery. Recent metal-formability tests indicated that the boric acid films applied to aluminum surfaces worked quite well, improving draw scale performance by 58 to 75%.

A 2-D CFD model was developed to describe the heat transfer, and reaction kinetics in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state as well as the transient behavior of the flow and heat transfer during the trap regeneration processes. The trap temperature profile was determined by numerically solving the 2-D unsteady energy equation including the convective, heat conduction and viscous dissipation terms. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations (Opris, 1997). The reaction kinetics were described using a discretized first order Arrhenius function. The 2-D term describing the reaction kinetics and particulate matter conservation of mass was added to the energy equation as a source term in order to represent the particulate matter oxidation. The filtration model describes the particulate matter accumulation in the trap.

Technical groups worldwide have been actively developing specifications and requirements for biodegradable hydraulic fluids for mobile applications. These groups have recognized that an industry-wide specification is necessary due to the increase in environmental awareness in the agriculture, construction, forestry, and mining industries, and to the increasing number of local regulations primarily throughout Europe. Caterpillar has responded to this need by publishing a requirement, Caterpillar BF-1, that may be used by Caterpillar dealers, customers, and industry to help select high-performance biodegradable hydraulic fluids. This requirement was written with the input of several organizations that are known to be involved with the development of similar types of specifications and requirements.

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.

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.

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.

When compared with new oil, used diesel engine oils exhibited thermal conductivity that increases as the concentration of soot increases. The magnitude of the effect depends on the oil composition, and on the size and dispersion of the soot particles. Although soot in engine oil is generally deleterious to engine performance from the standpoint of wear and deposits, no negative effects were observed on the thermal performance of the oil itself; indeed, even slight positive effects are expected for oils that maintain soot in stable dispersion. Therefore, the thermal challenge for engine oils in diesel engines that use exhaust gas recirculation will be to prevent soot deposition on engine surfaces.

The induction hardening process involves a complex interaction of electromagnetic heating, rapid cooling, metallurgical phase transformations, and mechanical behavior. Many factors including induction coil design, power, frequency, scanning velocity, workpiece geometry, material chemistry, and quench severity determine a process outcome. This paper demonstrates an effective application of a numerical analysis tool for understanding of induction hardening. First, an overview of the Caterpillar induction simulation tool is briefly discussed. Then, several important features of the model development are examined. Finally, two examples illustrating the use of the computer simulation tool for solving induction-hardening problems related to cracking and distortion are presented. These examples demonstrate the tool's ability to simulate changes in process parameters and latitude of modeling steel or cast iron.

This paper summarizes the successful application of Computational Fluid Dynamics (CFD) analysis to predict and control the cavitation erosion in a hydraulic control valve. The accurate control of different vehicle operations demands very fine spool modulations in a hydraulic valve. The precise spool modulations create very high flow rates and high-pressure drops in the valve. The low local fluid pressure regions create cavitation inside the valve. Due to the explosion of bubbles there is a high erosion damage to the valve body as well as the spool surface. The CFD analysis has been used to predict the location of cavitation origination and also used to control the cavitation by redistributing the flow inside the valve.