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Technical Paper

Study of Incremental Bending Test on Aluminum Sheets

2018-04-03
2018-01-0807
Bendability is one of the most important formability characteristics in sheet metal forming, so it has to be understood for robust aluminum stamping process designs. Crack is one of the major failure modes in aluminum sheet bending. In this study, a new “incremental bending” method is proposed to reduce the risk of bending failure. A novel laboratory test methodology is conducted to test the 5xxx series aluminum sheet bendability with 3D digital image correlation (DIC) measurement system. The designs of test apparatus and test procedure are introduced in this paper. Through the data processing and evaluation of a sequence image acquisition, the major strain histories within the zone of the through thickness crack of test samples are measured. Testing results show that incremental bending is capable of reducing peak strain on the outer surface obviously compared with traditional non-incremental bending. The more step, more movement, the more peak strain reduction.
Technical Paper

Measurement of Strain Distribution for Hole Expansion with Digital Image Correlation (DIC) System

2011-04-12
2011-01-0993
Advanced high strength steels (AHSS) are increasingly used in automotive industry. A major issue for AHSS stamping is edge cracking. This failure mode is difficult to predict by conventional forming limit curve (FLC). The material edge stretchability is mainly evaluated using the hole expansion test. In this study, digital Image Correlation (DIC) is applied for strain measurement. DIC is a non-contact, full field, high accuracy and direct measurement technique that provides more detailed information for the evolution of strains on the sheet surface. Tests were conducted for five AHSS and nine cases. This paper will explain in detail the DIC technique and its results.
Technical Paper

Effect of Threaded Fastener Condition on Low Cycle Fatigue Failures in Metric Bolts Under Transverse Loading

2008-04-14
2008-01-0700
This paper presents an experimental investigation of the effect of threaded fastener condition on the low cycle fatigue behavior of a tightened metric fastener under a fully reversed, cyclic transverse load. The test set-up subjects tightened, threaded fasteners to the combined effect of axial, torsional, bending, and transverse shear loading. The two conditions of the fasteners were “as received” and “ultrasonically cleaned and oiled”. Fatigue performance at three different bolt tension levels was investigated. Based on preliminary testing arbitrarily selected amplitude of 0.05 inches was used for the cyclic transverse displacement, at a frequency of 10 Hz. A Scanning Electron Microscope (SEM) was used to assess the failure mode on a bolt fracture surface. The bolt stresses are sensitive to both thread and under head friction characteristics.
Technical Paper

Reliability Estimation of Large-Scale Dynamic Systems by using Re-analysis and Tail Modeling

2009-04-20
2009-01-0200
Probabilistic studies can be prohibitively expensive because they require repeated finite element analyses of large models. Re-analysis methods have been proposed with the premise to estimate accurately the dynamic response of a structure after a baseline design has been modified, without recalculating the new response. Although these methods increase computational efficiency, they are still not efficient enough for probabilistic analysis of large-scale dynamic systems with low failure probabilities (less or equal to 10-3). This paper presents a methodology that uses deterministic and probabilistic re-analysis methods to generate sample points of the response. Subsequently, tail modeling is used to estimate the right tail of the response PDF and the probability of failure a highly reliable system. The methodology is demonstrated on probabilistic vibration analysis of a realistic vehicle FE model.
Technical Paper

Imprecise Reliability Assessment When the Type of the Probability Distribution of the Random Variables is Unknown

2009-04-20
2009-01-0199
In reliability design, often, there is scarce data for constructing probabilistic models. It is particularly challenging to model uncertainty in variables when the type of their probability distribution is unknown. Moreover, it is expensive to estimate the upper and lower bounds of the reliability of a system involving such variables. A method for modeling uncertainty by using Polynomial Chaos Expansion is presented. The method requires specifying bounds for statistical summaries such as the first four moments and credible intervals. A constrained optimization problem, in which decision variables are the coefficients of the Polynomial Chaos Expansion approximation, is formulated and solved in order to estimate the minimum and maximum values of a system’s reliability. This problem is solved efficiently by employing a probabilistic re-analysis approach to approximate the system reliability as a function of the moments of the random variables.
Technical Paper

FEA Simulation of Induction Hardening and Residual Stress of Auto Components

2009-04-20
2009-01-0418
The paper studies the distributions of residual stresses in auto components after induction hardening. Three prototype parts are analyzed in this paper. Firstly, the temperature fields of the analyzed parts are quantitatively simulated during quenching by simulating surface heating to the austenitization temperature of the material. Secondly, the formation and states of the residual stresses are predicted. Therefore the distribution of residual stress is simulated and shows compressive stresses on the surface of components so that the strength can be improved. The simulated results by computer are compared with experimental results. The good comparison indicates that the results obtained by the FEA analysis are reliable. Thus, it can be concluded that the FEA (Finite element analysis) program is effectively developed to simulate heating and quenching processes and residual stresses distribution.
Technical Paper

Correlation of Axle Build Parameters to End-of-Line NVH Test Performance Part I: Preparing the Data for Multivariate Regression Analysis

2012-04-16
2012-01-0727
The first part of a detailed examination of multivariate correlation of several axle assembly and component parameters to the assembly NVH performance (vibration) measured at the end of the assembly process is presented focusing on preparing the data for multivariate regression analysis. The study is based on test results and measurements acquired from multiple axle assemblies built with the same hypoid gearset, thus effectively eliminating the affect of gearset variation on the test result. Several major components within the axle are considered including the differential housing (that controls wheel differentiation during turns), the axle housing, and several assembly parameters.
Technical Paper

Correlation of Axle Build Parameters to End-of-Line NVH Test Performance Part II: Multivariate Regression Analysis

2012-04-16
2012-01-0728
The second part of a detailed examination of multivariate correlation of several axle assembly and component parameters to the assembly NVH performance (vibration) measured at the end of the assembly process is presented focusing on the multivariate linear regression analysis. The study is based on test results and measurements acquired from multiple axle assemblies built with the same hypoid gearset, thus effectively eliminating the affect of gearset variation on the test result. Several major components within the axle are considered including the differential housing (that controls wheel differentiation during turns), the axle housing, and several assembly parameters. Details of the multivariate regression include formulation of the linear regression model, model refinements through analysis of subsets of the variables, tests of significance and residual analysis.
Technical Paper

The Influence of Edge Quality on Edge Stretching Limit for Aluminum Alloy

2016-04-05
2016-01-0416
This paper presents the measurement and analysis of the edge stretching limit of aluminum alloy using digital image correlation. The edge stretching limit, also known as the “edge thinning limit,” is the maximum thinning strain at a point of edge failure resulting from tension; which may be predisposed by edge quality. Edge fracture is a vital failure mode in sheet metal forming, however it is very difficult to measure. A previous study enabled the measurement of edge thinning strain by using advanced digital image correlation but it did not consider how the edge quality could affect the edge stretching limit of aluminum alloy. This paper continues to measure edge thinning strain by comparing polished to unpolished AA5754, thus determining the effect edge quality has on the edge stretching limit. To enable the measurement by optical method for a very long and thin sample, a notch is used to localize where edge failure occurs.
Technical Paper

Assessment of Critical Plane Models Using Non-Proportional Low Cycle Fatigue Test Data of 304 Stainless Steel

2016-04-05
2016-01-0380
Two popular critical plane models developed by Fatemi-Socie and Smith-Watson-Topper were derived from the experimental observations of the nucleation and growth of cracks during loading. The Fatemi-Socie critical plane model is applicable for the life prediction of materials for which the dominant failure mechanism is shear crack nucleation and growth, while the Smith-Watson-Topper model, for materials that fail predominantly by crack growth on planes perpendicular to the planes of maximum tensile strain or stress. The two critical plane models have been validated primarily by in-phase and 90° out-of-phase loading, and few, on the complex, non-proportional loading paths. A successful critical plane model should be able to predict both the fatigue life and the dominant failure planes. However, some experimental studies indicate the 304 stainless steel has the two possible failure modes, shear and tensile failure dominant, depending on the loading mode and stress and strain states.
Technical Paper

Aluminum Sheet Springback (Side-Wall-Curl) Study

2017-03-28
2017-01-0396
Vehicle weight reduction is a significant challenge for the modern automotive industry. In recent years, the amount of vehicular components constructed from aluminum alloy has increased due to its light weighting capabilities. Automotive manufacturing processes, predominantly those utilizing various stamping applications, require a thorough understanding of aluminum fracture predictions methods, in order to accurately simulate the process using Finite Element Method (FEM) software or use it in automotive engineering manufacture. This paper presents the strain distribution of A5182 aluminum samples after punch impact under various conditions by Digital Image Correlation (DIC) system, its software also measured the complete strain history, in addition to sample curvature after it was impacted; therefore obtaining the data required to determine the amount of side-wall-curl (Aluminum sheet springback) present after formation.
Technical Paper

An Efficient Re-Analysis Methodology for Vibration of Large-Scale Structures

2007-05-15
2007-01-2326
Finite element analysis is a well-established methodology in structural dynamics. However, optimization and/or probabilistic studies can be prohibitively expensive because they require repeated FE analyses of large models. Various reanalysis methods have been proposed in order to calculate efficiently the dynamic response of a structure after a baseline design has been modified, without recalculating the new response. The parametric reduced-order modeling (PROM) and the combined approximation (CA) methods are two re-analysis methods, which can handle large model parameter changes in a relatively efficient manner. Although both methods are promising by themselves, they can not handle large FE models with large numbers of DOF (e.g. 100,000) with a large number of design parameters (e.g. 50), which are common in practice. In this paper, the advantages and disadvantages of the PROM and CA methods are first discussed in detail.
Technical Paper

A Study on the Effects of Simulation Parameters on Springback Prediction

2000-03-06
2000-01-1109
The use of commercial finite element analysis (FEA) software to perform stamping feasibility studies of automotive components has grown extensively over the last decade. Although product and process engineers have now come to rely heavily on results from FEA simulation for manufacturability of components, the prediction of springback has still not been perfected. Springback prediction for simple geometries is found to be quite accurate while springback prediction in complex components fails to compare with experimental results. Since most forming simulation FEA software uses a dynamic explicit solution method, the choice of various input parameters greatly affects the prediction of post formed stresses in the final component. Accurate stress prediction is critical for determination of springback, therefore this study focuses on the effects of some of the simulation parameters such as, element size, tool/loading speed and loading profile.
Technical Paper

Design Optimization and Reliability Estimation with Incomplete Uncertainty Information

2006-04-03
2006-01-0962
Existing methods for design optimization under uncertainty assume that a high level of information is available, typically in the form of data. In reality, however, insufficient data prevents correct inference of probability distributions, membership functions, or interval ranges. In this article we use an engine design example to show that optimal design decisions and reliability estimations depend strongly on uncertainty characterization. We contrast the reliability-based optimal designs to the ones obtained using worst-case optimization, and ask the question of how to obtain non-conservative designs with incomplete uncertainty information. We propose an answer to this question through the use of Bayesian statistics. We estimate the truck's engine reliability based only on available samples, and demonstrate that the accuracy of our estimates increases as more samples become available.
Technical Paper

The Role of Automated FMEA in Automotive Reliability Improvement

2006-04-03
2006-01-1619
An important challenge facing automotive Original Equipment Manufacturer's (OEMs) is to bring a product to the consumer that meets the Voice Of the Customer (VOC) with high reliability. Although not an explicitly stated requirement, the desire for highly reliable products is an implicit want of most, if not all customers. The specific challenge to an OEM is to develop products with high reliability under shortened design cycles, cost reduction initiatives, and pressures to produce products with focus market appeal. This paper evaluates the current situation, use, and overall effectiveness of Failure Modes & Effects Analysis (FMEA) and its role in improving the reliability of automotive products. The need for a semi-formal or formal methodology for identifying product failure modes is developed.
Technical Paper

System Reliability-Based Design using a Single-Loop Method

2007-04-16
2007-01-0555
An efficient approach for series system reliability-based design optimization (RBDO) is presented. The key idea is to apportion optimally the system reliability among the failure modes by considering the target values of the failure probabilities of the modes as design variables. Critical failure modes that contribute the most to the overall system reliability are identified. This paper proposes a computationally efficient, system RBDO approach using a single-loop method where the searches for the optimum design and for the most probable failure points proceed simultaneously. Specifically, at each iteration the optimizer uses approximated most probable failure points from the previous iteration to search for the optimum. A second-order Ditlevsen upper bound is used for the joint failure probability of failure modes. Also, an easy to implement active strategy set is employed to improve algorithmic stability.
Technical Paper

An Efficient Possibility-Based Design Optimization Method for a Combination of Interval and Random Variables

2007-04-16
2007-01-0553
Reliability-based design optimization accounts for variation. However, it assumes that statistical information is available in the form of fully defined probabilistic distributions. This is not true for a variety of engineering problems where uncertainty is usually given in terms of interval ranges. In this case, interval analysis or possibility theory can be used instead of probability theory. This paper shows how possibility theory can be used in design and presents a computationally efficient sequential optimization algorithm. The algorithm handles problems with only uncertain or a combination of random and uncertain design variables and parameters. It consists of a sequence of cycles composed of a deterministic design optimization followed by a set of worst-case reliability evaluation loops. A crank-slider mechanism example demonstrates the accuracy and efficiency of the proposed sequential algorithm.
Technical Paper

Simulation of Tire-Snow Interfacial Forces for a Range of Snow Densities with Uncertainty

2006-04-03
2006-01-0497
The objective of this paper is to assess the effect of snow density on tire-snow interaction in the presence of uncertainty. The snow-depth dependent finite element analysis (FEA) and semi-analytical models we have developed recently can predict tire-snow interfacial forces at a given density under combined slip conditions. One drawback of the models is that they are only applicable for fresh, low-density snow due to the unavailability of a density-dependent snow model. In reality, the snow density on the ground can vary between that of fresh snow to heavily compacted snow that is similar to ice. Even for fresh snow on the ground, as a vehicle moves forward, the rear wheels experience higher snow densities than the front wheels. In addition, being a natural material, snow's physical properties vary significantly even for the same density.
Technical Paper

A FEM Model to Predict Pressure Loading Cycle for Hydroforming Processes

1999-03-01
1999-01-0677
Tubular hydroforming is a novel process that has recently gained much attention due to its cost-effective application in the automotive industry. Hydroformed automotive parts have high strength to weight ratio and have good repeatability with high dimensional accuracy. At this time, there is little experience in modeling the hydroforming process to better understand its application and researchers have tried using stamping simulation software to analyze the process. Unlike conventional sheet stamping which is a displacement driven process, tubular hydroforming is a force driven process and its success is governed by the nature of internal pressurization. Hence, a new three-dimensional finite element model using a computationally efficient 6-noded shell element has been developed. A simple pressure prediction model has been developed and integrated into the formulation for effective control of the process.
Technical Paper

Simulation-Based Reliability Analysis of Automotive Wind Noise Quality

2004-03-08
2004-01-0238
An efficient simulation-based method is proposed for the reliability analysis of a vehicle body-door subsystem with respect to an important quality issue -- wind noise. A nonlinear seal model is constructed for the automotive wind noise problem and the limit state function is evaluated using finite element analysis. Existing analytical as well as simulation-based methods are used to solve this problem. A multi-modal adaptive importance sampling method is then developed for reliability analysis at system level. It is demonstrated through this industrial application problem that the multi-modal adaptive importance sampling method is superior to existing methods in terms of efficiency and accuracy. The method can easily handle implicit limit-state functions, with variables of any statistical distributions.
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