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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.

Contamination protection of brake rotors has been a challenge for the auto industry for a long time. As contamination of a rotor causes corrosion, and that in turn causes many issues like pulsation and excessive wear of rotors and linings, a rotor splash protection shield became a common part for most vehicles. While the rotor splash shield provides contamination protection for the brake rotor, it makes brake cooling performance worse because it blocks air reaching the brake rotor. Therefore, balancing between contamination protection and enabling brake cooling has become a key critical factor when the splash shield is designed. Although the analysis capability of brake cooling performance has become quite reliable, due to lack of technology to predict contamination patterns, the design of the splash protection shield has relied on engineering judgment and/or vehicle tests. Optimization opportunities were restricted by cost and time associated with vehicle tests.

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.

We propose a composite thermal model of the vehicle passenger compartment that can be used to predict and analyze thermal comfort of the occupants of a vehicle. Physical model is developed using heat flow in and out of the passenger compartment space, comprised of glasses, roof, seats, dashboard, etc. Use of a model under a wide variety of test conditions have shown high sensitivity of compartment air temperature to changes in the outside air temperature, solar heat load, temperature and mass flow of duct outlet air from the climate control system of a vehicle. Use of this model has subsequently reduced empiricism and extensive experimental tests for design and tuning of the automatic climate control system. Simulation of the model allowed several changes to the designs well before the prototype hardware is available.

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.

During the automotive brake system design and development process, a large number of performance characteristics must be comprehended, assessed, and balanced against each other and, at times, competing performance objectives for the vehicle under development. One area in brake development that is critical to customer acceptance due to its impact on a vehicle's perceived quality is brake pedal feel. While a number of papers have focused on the specification, quantification and modeling of brake pedal feel and the various subsystem characteristics that affect it, few papers have focused specifically on brake corner hoses and their effect on pedal feel, in particular, during race-track conditions. Specifically, the effects of brake hose fluid consumption pedal travel and brake system response is not well comprehended during the brake development process.

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.

Homogenous Charge Compression Ignition (HCCI) combustion offers significant efficiency improvements compared to conventional gasoline engines. However, due to the nature of HCCI combustion, traditional HCCI engines show some degree of sensitivity to in-cylinder thermal conditions; thus higher cylinder-to-cylinder variation was observed especially at low load and high load operating conditions due to different injector characteristics, different amount of reforming as well as non-uniform EGR distribution. To address these issues, a cylinder balancing control strategy was developed for a multi-cylinder engine. In particular, the cylinder balancing control strategy balances CA50 and AF ratio at high load and low load conditions, respectively. Combustion noise was significantly reduced at high load while combustion stability was improved at low load with the cylinder balancing control.

Two-stage turbochargers are a recent solution to improve engine performance, reducing the turbo-lag phenomenon and improving the matching. However, the definition of the control system is particularly complex, as the presence of two turbochargers that can be in part operated independently requires effort in terms of analysis and optimization. This work documents a characterization study of two-stage turbocharger systems. The study relies on a mean-value model of a Diesel engine equipped with a two-stage turbocharger, validated on experimental data. The turbocharger is characterized by a VGT actuator and a bypass valve (BPV), both located on the high-pressure turbine. This model structure is representative of a “virtual engine”, which can be effectively utilized for applications related to analysis and control. Using this tool, a complete characterization was conducted considering key operating conditions representative of FTP driving cycle operations.

Magnesium alloy extrusions offer potentially more mass saving compared to magnesium castings. One of the tasks in the United States Automotive Materials Partnership (USAMP) ?Magnesium Front End Research and Development? (MFERD) project is to evaluate magnesium extrusion alloys AM30, AZ31 and AZ61 for automotive body applications. Solid and hollow sections were made by lowcost direct extrusion process. Mechanical properties in tension and compression were tested in extrusion, transverse and 45 degree directions. The tensile properties of the extrusion alloys in the extrusion direction are generally higher than those of conventional die cast alloys. However, significant tension-compression asymmetry and plastic anisotropy need to be understood and captured in the component design.

Magnesium alloys are the lightest structural metal and recently attention has been focused on using them for structural automotive components. Fatigue and durability studies are essential in the design of these load-bearing components. In 2006, a large multinational research effort, Magnesium Front End Research & Development (MFERD), was launched involving researchers from Canada, China and the US. The MFERD project is intended to investigate the applicability of Mg alloys as lightweight materials for automotive body structures. The participating institutions in fatigue and durability studies were the University of Waterloo and Ryerson University from Canada, Institute of Metal Research (IMR) from China, and Mississippi State University, Westmorland, General Motors Corporation, Ford Motor Company and Chrysler Group LLC from the United States.

Engine cylinder deactivation is used to save engine pumping loss but raises oil consumption concerns for the deactivated cylinders. In this paper, general mechanisms of oil transport via piston rings are reviewed. The characteristic of oil transport and oil accumulation in a cylinder deactivation mode through the piston ring path are analyzed. Suggestions to reduce the oil transport to the combustion chamber in a deactivated cylinder are discussed. In a deactivated cylinder, the amount of oil brought into the combustion chamber by the top ring up-scraping due to the ring/bore conformability difference between intake stroke and compression stroke is much less compared to a firing cylinder. However, compared to a firing cylinder, a deactivated cylinder has more oil entering the combustion chamber through the top ring end gap and ring groove as a result of the lower cylinder gas pressure, lower ring temperature and more frequent top ring axial movements.

Fully Flexible Valve Actuation (FFVA) systems provide maximum flexibility to adjust lift profiles of engine intake and exhaust valves. A research grade electro-hydraulic servo valve based FFVA system was designed to be used with an engine in a test cell to precisely follow desired lift profiles. Repetitive control was chosen as the control strategy. Crank angle instead of time is used to trigger execution to ensure repeatability. A single control is used for different engine speeds even though the period for one revolution changes with engine speeds. The paper also discusses lift profile extension, instantaneous lift profile switching capability and built-in safety features.

Brake caliper and corner behavior in the off-brake condition can lead, at times, to brake system performance issues such as residual drag (and related issues such as pulsation, judder, and loss of fuel economy), and caliper pryback during aggressive driving maneuvers. The dynamics in the brake corner can be strikingly complex, with numerous friction interfaces, rubber component and grease dynamics, deflections of multiple components, and significant dependence on usage conditions. Displacements of moving parts are usually small, and the residual forces in the caliper interfaces involved are also small in comparison with other forces acting on the same components, making direct observation very difficult. The present work attempts to illuminate off-brake behavior in two different conditions - residual drag and pryback - through the use of low-range pressure distribution sensors placed in between the caliper (pistons and fingers) and the brake pad pressure plates.

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.