Search Results

We propose a new metamodeling method to characterize the output (response) random process of a dynamic system with random parameters, excited by input random processes. The metamodel can be then used to efficiently estimate the time-dependent reliability of a dynamic system using analytical or simulation-based methods. The metamodel is constructed by decomposing the input random processes using principal components or wavelets and then using a few simulations to estimate the distributions of the decomposition coefficients. A similar decomposition is also performed on the output random process. A kriging model is then established between the input and output decomposition coefficients and subsequently used to quantify the output random process corresponding to a realization of the input random parameters and random processes. What distinguishes our approach from others in metamodeling is that the system input is not deterministic but random.

The automotive industry has a strong need for lightweight materials capable of withstanding large mechanical loads. Advanced high-strength steels (AHSS), which have high tensile strength and formability, show great promise for automotive applications, yet if they are to be more widely used, it's important to understand their deformation behavior; this is particularly important for the development of forming limit diagrams (FLD) used in stamping processes. The goal of the present study was to determine the extent to which anisotropy introduced by the rolling direction affects the local fracture strain. Three grades of dual-phase AHSS and one high-strength low-alloy (HSL A) 50ksi grade steel were tested under plane strain conditions. Half of the samples were loaded along their rolling direction and the other half transverse to it. In order to achieve plane strain conditions, non-standard dogbone samples were loaded on a wide-grip MTS tensile test machine.

Design optimization often relies on computational models, which are subjected to a validation process to ensure their accuracy. Because validation of computer models in the entire design space can be costly, a recent approach was proposed where design optimization and model validation were concurrently performed using a sequential approach with both fixed and variable-size local domains. The variable-size approach used parametric distributions such as Gaussian to quantify the variability in test data and model predictions, and a maximum likelihood estimation to calibrate the prediction model. Also, a parametric bootstrap method was used to size each local domain. In this article, we generalize the variable-size approach, by not assuming any distribution such as Gaussian. A nonparametric bootstrap methodology is instead used to size the local domains. We expect its generality to be useful in applications where distributional assumptions are difficult to verify, or not met at all.

Multi-attribute decision making and multi-objective optimization complement each other. Often, while making design decisions involving multiple attributes, a Pareto front is generated using a multi-objective optimizer. The end user then chooses the optimal design from the Pareto front based on his/her preferences. This seemingly simple methodology requires sufficient modification if uncertainty is present. We explore two kinds of uncertainties in this paper: uncertainty in the decision variables which we call inherent design problem (IDP) uncertainty and that in knowledge of the preferences of the decision maker which we refer to as preference assessment (PA) uncertainty. From a purely utility theory perspective a rational decision maker maximizes his or her expected multi attribute utility.

Warranty forecasting of repairable systems is very important for manufacturers of mass produced systems. It is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. Moreover, systems may be produced with a defective component resulting in extensive warranty costs even after the defective component is detected and replaced with a new design. In this paper, we present a forecasting method to predict the ENF of a repairable system using observed data which is used to calibrate a Generalized Renewal Processes (GRP) model. Manufacturing of products may exhibit different production patterns with different failure statistics through time. For example, vehicles produced in different months may have different failure intensities because of supply chain differences or different skills of production workers, for example.

A complete probabilistic model of uncertainty in probabilistic analysis and design problems is the joint probability distribution of the random variables. Often, it is impractical to estimate this joint probability distribution because the mechanism of the dependence of the variables is not completely understood. This paper proposes modeling dependence by using copulas and demonstrates their representational power. It also compares this representation with a Monte-Carlo simulation using dispersive sampling.

Embedded systems continue to become more complex. As a result, more companies are utilizing model-based design (MBD) development methods and tools. The use of MBD methods and tools is helpful in increasing time to market and having instant feedback on the system design. One area that continues to mature is the testing and verification of the MBD systems. This paper introduces a hybrid approach to functional tests. The test system is composed of simulation software and real-time hardware. It is not always necessary to test a system in a real-time environment, but it is recommended if the goal is to deploy the system to a situation that requires real-time response. Vehicle drive cycles and powertrain control are utilized in this research as the example test case for this paper. In order to test the algorithms on a real-time system, it is necessary to understand the target controller's computing limitations and adjust the algorithms to meet these limitations.

Adhesive bonding has many applications in the automotive industry. The single-lapped bonded joint is the most typically used among various bonding types. This paper presents experimental research for determining the strain field of the single-lapped joint under tensile loading. The materials for the joint are epoxy-based structural adhesive and low-carbon electrolytic zinc steel plate. In the study, a DIC (digital image correlation) system was adopted to measure the strain distribution of the bonded joint during a tensile test. The bonded steel coupons in the tensile test were prepared according to the ASTM standard. During the measurement, images of the coupon joint were taken before and after the deformation process. Then the DIC system measured the strain of bonded joint by comparing two consecutive images. The measured data from the DIC was compared to data taken simultaneously from a traditional extensometer.

The automobile industry has an increasing demand for lightweight components, improve product performance, efficiency and increase safety. For optimization of design and manufacturing of these components the detail measurement of critical material properties such as strain limit, strength coefficients, anisotropy coefficients et al, are required. The most commonly used method for finding the material properties is tensile test with extensometer. But this system only provides an average strain over the specimen gauge length and is not applicable to post diffuse necking. Digital Image Correlation (DIC) technique is the latest state of art technique. Because of its capability of fast data acquisition, this technique is suited well for characterization of material properties both in the elastic and plastic ranges. It also has advantages of full field, non-contact, and considerately high precision for displacement and strain measurements.

Sheet metal stamping involves a system of complex tribological (friction, lubrication, and wear), heat transfer, and material strain interactions. Accurate coefficient of friction, strain, and lubrication regime data is required to allow proper modeling of the various sheet stamping processes. In addition, non-intrusive means of monitoring the coefficient of friction in production stamping operations would be of assistance for efficiently maintaining proper stamping quality and to indicate when adjustments to the various stamping parameters, including maintenance, would be advantageous. One of the key sub-systems of the sheet metal stamping process is the draw bead. This paper presents an investigation of the tribology of the draw bead using a Draw Bead Simulator (DBS) Machine and automotive zinc-coated sheet steels. The investigation and findings include: 1) A new, non-intrusive method of measuring the surface temperature of the sheet steel as it passes through the draw bead.

Exhaust gas recirculation (EGR) has been proven an effective strategy for the ignition and combustion control in homogeneous charge compression ignition (HCCI) engines. Carbon dioxide (CO2), a major constituent in EGR, was found to pose a coupled effect on engine combustion: reduced intake oxygen concentration (dilution effect), increased gas heat capacity (thermal effect) and participation of CO2 in chemical reactions (chemical effect). In this paper, a numerical study using a detailed chemical kinetic model was conducted, aiming to isolate the dilution, thermal and chemical effects of CO2 on the two-stage auto-ignition process of n-heptane at engine-like pressure conditions. Four different initial temperatures were selected in this study, representing the low-temperature dominant region, the boundary between the low-temperature region and the negative temperature coefficient (NTC) region, the NTC region and the high temperature region, respectively.

Imposing tensile stress on an edge of a sheet metal blank is a common condition in many sheet metal forming operations, making edge formability a very important factor to consider. Because edge formability varies greatly among different materials, cutting methods (and their control parameters), it is very important to have access to an experimental technique that would allow for quick and reliable evaluation of edge formability for a given case. In this paper, two existing techniques are compared: the hole expansion test and the tensile test. It is shown that the hole expansion test might not be adequate for many cases, and is prone to overestimating the limiting strain, because the burr on the sheared edge is typically smaller than what is observed in production. The tensile test represents an effective alternative to the hole expansion test. Advantages and disadvantages of each case are discussed.

Styrene-Butadiene Rubber (SBR), a copolymer of butadiene and styrene, is widely used in the automotive industry due to its high durability and resistance to abrasion, oils and oxidation. Some of the common applications include tires, vibration isolators, and gaskets, among others. This paper characterizes the dynamic behavior of SBR and discusses the suitability of a visco-elastic model of elastomers, known as the Kelvin model, from a mathematical and physical point of view. An optimization algorithm is used to estimate the parameters of the Kelvin model. The resulting model was shown to produce reasonable approximations of measured dynamic stiffness. The model was also used to calculate the self heating of the elastomer due to energy dissipation by the viscous damping components in the model. Developing such a predictive capability is essential in understanding the dynamic behavior of elastomers considering that their dynamic stiffness can in general depend on temperature.

As the use of electronic devices in automobiles increases, the reliability of such devices is becoming increasingly important. One possible failure is due to leakage resulted from imperfect hermetical seal in mircochips and microelectronic packages. This paper presents an optical technique referred to as shearography for rapid evaluation of hermetics seals. The proposed process of leaking testing is very fast and practical.

This paper presents an optical method for evaluating residual stresses. The approach is based on measuring the deformation due to the relief of stress produced by a blind-hole drilling technique. The deformation is rapidly measured by shearography. Unlike the strain gage method, this method does not require mounting strain gages /transducers. A rapid process for detection of residual stress using a micro-indentation technique is also present. The method is practical for employment in a production/field environment.

The reliability theory of repairable systems is vastly different from that of non-repairable systems. The authors have recently proposed a ‘decision-based’ framework to design and maintain repairable systems for optimal performance and reliability using a set of metrics such as minimum failure free period, number of failures in planning horizon (lifecycle), and cost. The optimal solution includes the initial design, the system maintenance throughout the planning horizon, and the protocol to operate the system. In this work, we extend this idea by incorporating flexibility and demonstrate our approach using a smart charging electric microgrid architecture. The flexibility is realized by allowing the architecture to change with time. Our approach “learns” the working characteristics of the microgrid. We use actual load and supply data over a short time to quantify the load and supply random processes and also establish the correlation between them.

Experimental results on influence of trimming conditions on the shape of the sheared surface are combined with the results of stretching sheared samples after trimming. The objective of the research described in this paper is to study the mechanism of fracture initiation and cracks propagation during half-a-dog bone tensile test representing sheared edge stretching condition. One side of the sample had sheared surface obtained by the trimming process while the other side of the sample had a smooth surface. Significant attention was paid to understanding of fracture sources. An interrupted tensile test approach was employed to track fracture initiation and propagation during stretching of sheared surface. The results of the experimental study indicated that multiple sources of fracture were observed in the burr area for trimming with clearances exceeding 10% of the material thickness.

This paper develops a design paradigm for universal products. Universal design is term used for designing products and systems that are equally accessible to and usable by people with and without disabilities. Two common challenges for research in this area are that (1) There is a continuum of disabilities making it hard to optimize product features, and (2) There is no effective benchmark for evaluating such products. To exacerbate these issues, data regarding customer disabilities and their preferences is hard to come by. We propose a copula-based approach for modeling market coverage of a portfolio of universal products. The multiattribute preference of customers to purchase a product is modeled as Frank's Archimedean Copula. The inputs from various disparate sources can be collected and incorporated into a decision system.

Experimental results on influence of trimming conditions on the shape of the sheared surface are combined with the results of stretching sheared samples after trimming. The objective of the research described in this paper is to study the mechanism of fracture initiation and cracks propagation during half-a-dog bone tensile test representing sheared edge stretching condition. One side of the sample had sheared surface obtained by the trimming process while the other side of the sample had a smooth surface. Significant attention was paid to understanding of fracture sources. An interrupted tensile test approach was employed to track fracture initiation and propagation during stretching of sheared surface. The results of the experimental study indicated that multiple sources of fracture were observed in the burr area for trimming with clearances exceeding 10% of the material thickness.

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.