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This article presents an approach for comparing alternative repairable systems and calculating the value of information obtained by testing a specified number of such systems. More specifically, an approach is presented to determine the value of information that comes from field testing a specified number of systems in order to appropriately estimate the reliability metric associated with each of the respective repairable systems. Here the reliability of a repairable system will be measured by its failure rate. In support of the decision-making effort, the failure rate is translated into an expected utility based on a utility curve that represents the risk tolerance of the decision-maker. The algorithm calculates the change of the expected value of the decision with the sample size. The change in the value of the decision represents the value of information obtained from testing.

Design optimization occurs through a series of decisions that are a standard part of the product development process. Decisions are made anywhere from concept selection to the design of the assembly and manufacturing processes. The effectiveness of these decisions is based on the information available to the decision maker. Decision analysis provides a structured approach for quantifying the value of information that may be provided to the decision maker. This paper presents a process for determining the value of information that can be gained by evaluating linearly correlated design alternatives. A unique approach to the application of Bayesian Inference is used to provide simulated estimates in the expected utility with increasing observations sizes. The results provide insight into the optimum observation size that maximizes the expected utility when assessing correlated decision alternatives.

Over the last two decades inverse problems have become increasingly popular due to their widespread applications. This popularity continuously demands designers to find alternative methods, to solve the inverse problems, which are efficient and accurate. It is important to use effective techniques that are both accurate and computationally efficient. This paper presents a method for solving inverse problems through Artificial Neural Network (ANN) theory. The paper also presents a method to apply Grey Wolf optimizer (GWO) algorithm to inverse problems. GWO is a recent optimization method producing superior results. Both methods are then compared to traditional methods such as Particle Swarm Optimization (PSO) and Markov Chain Monte Carlo (MCMC). Four typical engineering design problems are used to compare the four methods. The results show that the GWO outperforms other methods both in terms of efficiency and accuracy.

The Combined Approximation (CA) method is an efficient reanalysis method that aims at reducing the cost of optimization problems. The CA uses results of a single exact analysis, and it is suitable for different types of structures and design variables. The second author utilized CA to calculate the frequency response function of a system at a frequency of interest by using the results at a frequency in the vicinity of that frequency. He showed that the CA yields accurate results for small frequency perturbations. This work demonstrates a methodology that utilizes CA to reduce the cost of Monte Carlo simulation (MCs) of linear systems under random dynamic loads. The main idea is to divide the power spectral density function (PSD) of the input load into several frequency bins before calculating the load realizations.

This paper proposes a multi-level decoupled method for optimizing the structural design of a wind turbine blade. The proposed method reduces the design space by employing a two-level optimization process. At the high-level, the structural properties of each section are approximated by an exponential function of the distance of that section from the blade root. High-level design variables are the coefficients of this approximating function. Target values for the structural properties of the blade are determined at that level. At the low-level, sections are divided into small decoupled groups. For each section, the low-level optimizer finds the thickness of laminate layers with a minimum mass, whose structural properties meet the targets determined by the high-level optimizer. In the proposed method, each low-level optimizer only considers a small number of design variables for a particular section, while traditional, single-level methods consider all design variables simultaneously.

Importance Sampling is a popular method for reliability assessment. Although it is significantly more efficient than standard Monte Carlo simulation if a suitable sampling distribution is used, in many design problems it is too expensive. The authors have previously proposed a method to manage the computational cost in standard Monte Carlo simulation that views design as a choice among alternatives with uncertain reliabilities. Information from simulation has value only if it helps the designer make a better choice among the alternatives. This paper extends their method to Importance Sampling. First, the designer estimates the prior probability density functions of the reliabilities of the alternative designs and calculates the expected utility of the choice of the best design. Subsequently, the designer estimates the likelihood function of the probability of failure by performing an initial simulation with Importance Sampling.

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.

A Reliability-Based Design Optimization (RBDO) method for multiple failure regions is presented. The method uses a Probabilistic Re-Analysis (PRRA) approach in conjunction with an approximate global metamodel with local refinements. The latter serves as an indicator to determine the failure and safe regions. PRRA calculates very efficiently the system reliability of a design by performing a single Monte Carlo (MC) simulation. Although PRRA is based on MC simulation, it calculates “smooth” sensitivity derivatives, allowing therefore, the use of a gradient-based optimizer. An “accurate-on-demand” metamodel is used in the PRRA that allows us to handle problems with multiple disjoint failure regions and potentially multiple most-probable points (MPP). The multiple failure regions are identified by using a clustering technique. A maximin “space-filling” sampling technique is used to construct the metamodel. A vibration absorber example highlights the potential of the proposed method.

The problem of predicting the quality of weld is critical to manufacturing. A great deal of data is collected under multiple conditions to predict the quality. The data generated at Daimler Chrysler has been used to develop a model based on grammatical evolution. Grammatical Evolution Technique is based on Genetic Algorithms and generates rules from the data which fit the data. This paper describes the development of a software tool that enables the user to choose input variables such as the metal types of top and bottom layers and their thickness, intensity and speed of laser beam, to generate a three dimensional map showing weld quality. A 3D weld quality surface can be generated in response to any of the two input variables picked from the set of defining input parameters. This tool will enable the user to pick the right set of input conditions to get an optimal weld quality. The tool is developed in Matlab with Graphical User Interface for the ease of operation.

This paper presents a computer generated model of a hydraulic circuit that is typically seen in hybrid hydraulic vehicles (HHV's). HHV's have shown considerable potential for increasing fuel economy and decreasing emissions for mid-size and commercial trucks that exhibit urban driving habits. The aim of the present model is to aid in further optimizing the performance of the hybrid powertrain and serve as a baseline for future studies into the noise and vibration (NV) associated with the system. The model simulates the regenerative braking process of a parallel type hybrid hydraulic propulsion system. Regenerative braking captures and stores otherwise lost energy into an accumulator. This stored energy can then later be used to propel the vehicle, thus reducing the vehicle's reliance on a conventional internal combustion engine (ICE). This model will serve as a baseline for future developments and will be expanded and validated experimentally in ensuing research.

Low frequency torsional vibrations can be a significant source of objectionable vehicle vibrations and in-vehicle boom, especially with changes in engine operation required for improved fuel economy. These changes include lower torque converter lock-up speeds and cylinder deactivation. This paper has two objectives: 1) Examine the effect of increased torsional vibrations on vehicle NVH performance and ways to improve this performance early in the program using test and simulation techniques. The important design parameters affecting vehicle NVH performance will be identified, and the trade-offs required to produce an optimized design will be examined. Also, the relationship between torsional vibrations and mount excursions, will be examined. 2) Investigate the ability of simulation techniques to predict and improve torsional vibration NVH performance. Evaluate the accuracy of the analytical models by comparison to test results.

Brake torque variation is a source of objectionable NVH body/chassis response. Such input commonly results from brake disk thickness variation. The NVH dynamic characteristics of a vehicle can be assessed and quantified through experimental modal testing for determination of mode resonance frequency, damping property, and shape. Standard full vehicle modal testing typically utilizes a random input excitation into the vehicle frame or underbody structure. An alternative methodology was sought to quantify and predict body/chassis sensitivity to brake torque variation. This paper presents a review of experimental modal test methodologies investigated for the reproduction of vehicle response to brake torque variation in a static laboratory environment. Brake caliper adapter random and sine sweep excitation input as well as body sine sweep excitation in tandem with an intentionally locked brake will be detailed.

This paper describes the application of the modal compliance method to a complex structure such as a vehicle body in white, and the extension of the method from normal modes to the complex modes of a complete vehicle. In addition to the usual bending and torsion calculations, the paper also describes the application of the method to less usual tests such as second torsion, match-boxing and breathing. We also show how the method can be used to investigate the distribution of compliance throughout the structure.

NVH refinement of passenger vehicles is crucial to customer acceptance of contemporary vehicles. This paper describes the vehicle NVH development process, with specific examples from a Diesel sedan application that was derived from gasoline engine-based vehicle architecture. Using an early prototype Diesel vehicle as a starting point, this paper examines the application of a Vehicle Interior Noise Simulation (VINS) technique in the development process. Accordingly, structureborne and airborne noise shares are analyzed in the time-domain under both steady-state and transient test conditions. The results are used to drive countermeasure development to address structureborne and airborne noise refinement. Examples are provided to highlight the refinement process for “Diesel knocking” under idle as well as transient test conditions. Specifically, the application of VINS to understanding the influence of high frequency dynamic stiffness of hydro-mounts on Diesel clatter noise is examined.

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.

The need for efficient space utilization has provided a framework for the design of a 248mm family of torque converters that supports a wide choice of engine and transmission combinations. The axial length of the part and its weight have been substantially reduced while the performance range has been broadened without degradation of efficiency. The new converter operates in an expanded slipping clutch mode. It significantly contributes to the performance and fuel economy improvements of related vehicles. To meet the cost target, the comprehensive lineup and the resulting complexity have required a high level of component interchangeability. During the design phase, the manufacturing core competencies were scrutinized and process redundancies eliminated, both resulting in optimization of material selection and applicable technology.

This paper identifies the difference in powertrain cooling system content levels using a nominal and a +3 Standard deviation maximum temperature design approach. Variation simulation analysis tools are used along with a 1-D cooling system performance model to predict resulting temperature distribution for different combinations of input variable populations. The analysis will show differential in powertrain cooling system content, mass, and impact to fuel economy for a nominal vs. +3 sigma design approach.

Brake judder, which is a low frequency excitation of the suspension and thus, the body structure during low-G braking, is mainly felt at the steering wheel and throughout the vehicle structure. Brake judder is a problem that costs manufacturers millions of dollars in warranty cost and undesirable trade offs. The magnitude of judder response depends not only on the brake torque variation, but also on the suspension design character-istics. This paper discusses the judder simulation process using ADAMS software to investigate the suspension design sensitivity to the first order brake judder performance. The paper recommends “tuning knobs” to suspension designers and vehicle development engineers to resolve issues in the design and development stages. Various suspension design varia-bles including geometry and compliances as well as brake related characteristics were investigated.

A serpentine flow channel is one of the most common and practical channel layouts for a PEM fuel cell since it ensures the removal of water produced in a cell. While the reactant flows along the flow channel, it can also leak or cross to neighboring channels via the porous gas diffusion layer due to a high pressure gradient. Such a cross flow leads to effective water removal in a gas diffusion layer thus enlarging the active area for reaction although this cross flow has largely been ignored in previous studies. In this study, neutron radiography is applied to investigate the liquid water accumulation and its effect on the performance of a PEM fuel cell. Liquid water tends to accumulate in the gas diffusion layer adjacent to the flow channel area while the liquid water formed in the gas diffusion layer next to the channel land area seems to be effectively removed by the cross leakage flow between the adjacent flow channels.

To mitigate head impact injuries of vehicle occupants in impact accidents, the FMVSS 201 requires padding of vehicle interior so that under the free-moving-head-form impact, the head injury criterion (HIC) is below the limit. More recently, pedestrian head impact on the vehicle bonnet has been a subject being studied and regulated as requirements to the automobile manufacturers. Over the years, the square wave has been considered as the best waveform for head impacts, although it is impractical to achieve. This paper revisits the head impact topic and challenges the optimality of aiming at the square waveform. It studies several different simple waveforms, with the objective to achieve minimal HIC or minimal crush space required in head-form impacts. With that it is found that many other waveforms can be more efficient and more practical than the square wave, especially for the pedestrian impact.