Search Results

Experimental decklids for the Cadillac STS sedan were made with Al AA5083 sheet outer panels and Mg AZ31B sheet inner panels using regular-production forming processes and hardware. Joining and coating processes were developed to accommodate the unique properties of Mg. Assembled decklids were evaluated for dimensional accuracy, slam durability, and impact response. The assemblies performed very well in these tests. Explicit and implicit finite element simulations of decklids were conducted, and showed that the Al/Mg decklids have good stiffness and strength characteristics. These results suggest the feasibility of using Mg sheet closure panels from a structural perspective.

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.

Understanding the flow characteristics and, especially, how the aerodynamic forces are influenced by the changes in the vehicle body shape, are very important in order to improve vehicle aerodynamics. One specific goal of aerodynamic shape optimization is to predict the local shape sensitivities for aerodynamic forces. The availability of a reliable and efficient sensitivity analysis method will help to reduce the number of design iterations and the aerodynamic development costs. Among various shape optimization methods, the Adjoint Method has received much attention as an efficient sensitivity analysis method for aerodynamic shape optimization because it allows the computation of sensitivity information for a large number of shape parameters simultaneously.

In today's light-weight vehicles, the strength of spot welds plays an important role in overall product integrity, reliability and customer satisfaction. Naturally, there is a need for a quick and reliable technique to inspect the quality of the welds. In the past, the primary quality control tests for detecting weld defects are the destructive chisel test and peel test [1]. The non-destructive evaluation (NDE) method currently used in industry is based on ultrasonic inspection [2, 3, 4]. The technique is not always successful in evaluating the nugget size, nor is it effective in detecting the so-called “cold” or “stick” welds. Therefore, it is necessary to develop a precise and reliable noncontact NDE method for spot welds. There have been numerous studies in predicting the weld nugget size by considering the spot-weld process [5, 6].

This paper discusses the treatment of uncertainties corresponding to relatively few samples of random-variable quantities. The importance of this topic extends beyond experimental data uncertainty to situations involving uncertainty in model calibration, validation, and prediction. With very sparse samples it is not practical to have a goal of accurately estimating the underlying variability distribution (probability density function, PDF). Rather, a pragmatic goal is that the uncertainty representation should be conservative so as to bound a desired percentage of the actual PDF, say 95% included probability, with reasonable reliability. A second, opposing objective is that the representation not be overly conservative; that it minimally over-estimate the random-variable range corresponding to the desired percentage of the actual PDF. The presence of the two opposing objectives makes the sparse-data uncertainty representation problem an interesting and difficult one.

In 2006, the Insurance Institute for Highway Safety (IIHS) released a new Low Speed Bumper Test Protocol for passenger cars1. The new test protocol included the development of a deformable barrier that the vehicle would impact at low speeds. IIHS positioned the new barrier to improve correlation to low speed collisions in the field, and also to assess the ability of the bumper system to protect the vehicle from damage. The bumper system must stay engaged to the barrier to protect other vehicle components from damage. The challenge is to identify the bumper system design features that minimize additional cost and mass to keep engagement to the barrier. The results of the Design for Six Sigma analysis identified the design features that increase the stiffness of the bumper system enable it to stay engaged to the barrier and reduce the deflection.

This study summarizes the peer-reviewed literature regarding the use of raw pyrolysis liquids (PLs) created from woody biomass as fuels for compression-ignition (CI) engines. First, a brief overview is presented of fast pyrolysis and the potential advantages of PLs as fuels for CI engines. Second, a discussion of the general composition and properties of PLs relative to conventional, petroleum-derived diesel fuels is provided, with emphasis on the differences that are most likely to affect PL performance in CI-engine applications. Next, a synopsis is given of the peer-reviewed literature describing experimental studies of CI engines operated using neat PLs and PLs combined in various ways with other fuels. This literature conclusively indicates that raw PLs and PL blends cannot be used as “drop-in replacements” for diesel fuel in CI engines, which is reflected in part by none of the cited studies reporting successful operation on PL fuels for more than twelve consecutive hours.

The Federal Aviation Administration Airworthiness Assurance Nondestructive Inspection Validation Center (FAA-AANC) is currently conducting a detection reliability study pertaining to the detection of cracks in multi-layered aluminum sheets. This paper describes the design, production and characterization of test specimens that are currently being used to conduct third layer Probability of Detection (PoD) experiments. Pertinent aspects of the lap splice joints for Boeing 737 aircraft, Line Numbers 292 - 2565 are included in the test specimens. A preliminary analysis of the data indicates that for some inspectors, traditional measures of performance - in particular PoD curves based on maximum likelihood fit to two-parameter lognormal curve - may be misleading.

Global programs are placing demands on vehicle platforms to achieve structural durability robustness across a broader spectrum of vehicle configurations and use conditions. This robustness is optimally achieved by (a) localizing energy absorption to lower cost components, and (b) narrowing the spread in loads generated during durability events, which in turn minimizes the cost and mass impact to the vehicle platform. A generalized philosophy for conducting load optimization and for improving energy management for various types of events is presented here. Various techniques that have been employed at GM are explained by way of illustration.

This study documents a method developed for dynamically measuring occupant pocketing during various low-speed rear impact, or “whiplash” sled tests. This dynamic pocketing measurement can then be related to the various test parameters used to establish the performance rating or compliance results. Consumer metric and regulatory tests discussed within this paper as potential applications of this technique include, but are not limited to, the Insurance Institute for Highway Safety (IIHS) Low Speed Rear Impact (LSRI) rating, Federal Motor Vehicle Safety Standard (FMVSS) 202a, and European New Car Assessment Program (EURO-NCAP) whiplash rating. Example metrics are also described which may be used to assist in establishing the design position of the head restraint and optimize the balance between low-speed rear impact performance and customer comfort.

For decades, the industry standard for laboratory durability simulations has been based on reproducing quantified vehicle responses. That is, build a running vehicle, measure its responses over a variety of durability road surfaces and reproduce those responses in the laboratory for durability evaluation. To bring a vehicle to market quickly, the time between tightening the last bolt on a prototype test vehicle and starting the durability evaluation test must be minimized. A method to derive 4-Post simulator displacements without measuring or predicting vehicle responses is presented.

Engineering has continuously strived to improve the vehicle development process to achieve high quality designs and quick to launch products. The design process has to have the tools and capabilities to help ensure both quick to the market product and a flawless launch. To achieve high fidelity and robust design, mistakes and other quality issues must be addressed early in the engineering process. One way to detect problems early is to use the math based modeling and simulation techniques of the analysis group. The correlation of the actual vehicle performance to the predictive model is crucial to obtain. Without high correlation, the change management process begins to get complicated and costs start to increase exponentially. It is critical to reduce and eliminate the risk in a design up front before tooling begins to kick off. The push to help achieve a high rate of correlation has been initiated by engineering management, seeing this as an asset to the business.

Current manufacture of alternative energy sources for automobiles, such as fuel cells and lithium-ion batteries, uses repeating energy modules to achieve targeted balances of power and weight for varying types of vehicles. Specifically for lithium-ion batteries, tens to hundreds of identical plastic parts are assembled in a repeating fashion; this assembly of parts requires complex dimensional planning and high degrees of quality control. This paper will address the aspects of dimensional quality for repeated, injection molded thermoplastic battery components and will include the following: First, dimensional variation associated with thermoplastic components is considered. Sources of variation include the injection molding process, tooling or mold, lot-to-lot material differences, and varying types of environmental exposure. Second, mold tuning and cavity matching between molds for multi-cavity production will be analyzed.

The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.

As customer dissatisfaction with interior trim components is tracked by the JDPowers question on “surface durability”, there is a need to increase the durability of the parts that are molded in color. In particular, door trim panel lowers are susceptible to surface damage which results in an unfavorable appearance. To address this issue, an assessment of the various factors that can affect surface durability was conducted using talc filled TPO materials in order to determine the optimum set of physical properties. The team used Design for Six Sigma (DFSS) methodology. A Taguchi orthogonal experiment was used and included control system factors of material, grain, gloss, and color. Noise factors included molding process parameters, aging, and piece to piece variation. The output was a measure of the scratch resistance of the molded plaque which was defined by a Delta L calculation.

The paper will discuss the results of a study to develop lightweight steel proof-of-concept front lower control arm (FLCA) designs that are less expensive and achieve equivalent structural performance relative to a baseline forged aluminum FLCA assembly. A current production forged aluminum OEM sedan FLCA assembly was selected as an aggressive mass target based on competitive benchmarking of vehicles of its size. CAE structural optimization methods were used to determine the initial candidate sheet steel and forged designs. Two (2) sheet steel FLCA designs and one (1) forged steel FLCA design were selected and developed to meet specified performance criteria. An iterative optimization strategy was used to minimize the mass of each design while meeting the specified stiffness, durability, extreme load, and longitudinal buckling strength requirements.

This paper deals with the development of a Hood Slam Process Automator (PA) to automate the pre-processing tasks of the virtual slam assessment with non-linear Nastran Transient Sol. 129 on all types of hoods. The slam analysis generally consumes a lot of analyst's time for building the slam models, typically six hours and is very tedious and has the potential for errors. The Hood Slam PA will automatically create and perform slam analysis pre-processing tasks within HyperMesh software such as creating latch striker interface, creating seals and bumpers with CBUSH1D elements, assigning transient slam speed to the hood and will finally generate the Nastran non-linear transient (Sol.129) hood slam analysis input files. The ready to run analysis input files will be submitted to the Nastran solver and the analysis results will then be post processed using HyperView software.

The present study defines the functional requirements for a liftgate and the body in order to avoid rattle, squeak, and other objectionable noises. A Design For Six Sigma (DFSS) methodology was used to study the impact of various constraint components such as bumpers, wedges, and isolated strikers on functional requirements. These functional requirements include liftgate frequency, acoustic cavity frequency, and the stiffness of the liftgate body opening. It has been determined that the method of constraining the gate relative to the body opening has a strong correlation to the noise generated. The recommended functional performance targets and constraint component selection have been confirmed by actual testing on a vehicle. Recommendations for future liftgate design will be presented.

1 As global automotive manufacturers prepare for the introduction of HFO-1234yf as the low Global Warming Potential (GWP) refrigerant solution in Europe and North America concerns over compressor durability due to oil migration still remain. This preliminary study evaluates several different variables that affect oil migration. Several compressor suppliers each having their own unique oil formulation for HFO-1234yf were included. Comparisons between vehicle tests and various accelerated lab test methods are made. In R134a automotive system the thresholds that cause compressor warranty are well understood. This study will compare AC systems running with HFO-1234yf at the same time identical systems with R134a are run to understand the relative effect of HFO-1234yf versus R134a.

Roof racks are designed for carrying luggage during customers' travels. These rails need to be strong enough to be able to carry the luggage weight as well as be able to withstand aerodynamic loads that are generated when the vehicle is travelling at high speeds on highways. Traditionally, roof rail gage thickness is increased to account for these load cases (since these are manufactured by extrusion), but doing so leads to increased mass which adversely affects fuel efficiency. The current study focuses on providing the guidelines for strategically placing lightening holes and optimizing gage thickness so that the final design is robust to noise parameters and saves the most mass without adversely impacting wind noise performance while minimizing stress. The project applied Design for Six Sigma (DFSS) techniques to optimize roof rail parameters in order to improve the load carrying capacity while minimizing mass.