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The automotive refrigerant system can occasionally exhibit an excessive noise out of air-conditioner (A/C) vents during vehicle’s developments. If the vehicle has been parked for long hours in summer and the A/C system is turned on, sometimes hissing noise is induced by the refrigerant flow. In order to understand the mechanism, a lot of bench and vehicle tests were conducted. However, there is still not enough to understand the physical behavior in detail. Therefore, for the first step, the visualization method to capture the behavior of multi-phased refrigerant flow jet inside the pipe was proposed with a high-speed camera, some light devices and acrylic test piece. In addition, image analysis to quantify the flow regime from a series of observed snapshots. Using proposed method, the correlation study between flow and noise was performed at A/C bench test. As a result, different flow features such as the velocity can be observed in the occurrence of the noise or not.

Improving fuel efficiency often affects NVH performance. Modifying a vehicle’s design in the latter stages of development to improve NVH performance is often costly. Therefore, to optimize the cost performance, a Multi-Attribute Balancing (MAB) approach should be employed in the early design phases. This paper proposes a solution based on a unified 1D system simulation model across different vehicle performance areas. In the scope of this paper the following attributes are studied: Fuel economy, Booming, Idle, Engine start and Drivability. The challenges to be solved by 1D simulation are the vehicle performance predictions, taking into account the computation time and accuracy. Early phase studies require a large number of scenarios to evaluate multiple possible parameter combinations employing a multi-attribute approach with a systematic tool to ease setup and evaluation according to the determined performance metrics.

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.

Reliability analysis of engineering structures such as bridges, airplanes, and cars require calculation of small failure probabilities. These probabilities can be calculated using standard Monte Carlo simulation, but this method is impractical for most real-life systems because of its high computational cost. Many studies have focused on reducing the computational cost of a reliability assessment. These include bootstrapping, Separable Monte Carlo, Importance Sampling, and the Combined Approximations. The computational cost can also be reduced using an efficient method for deterministic analysis such as the mode superposition, mode acceleration, and the combined acceleration method. This paper presents and demonstrates a method that uses a combination of Sobol quasi-random sequences and bootstrapping to reduce the number of function calls. The study demonstrates that the use of quasi-random numbers in conjunction bootstrapping reduces dramatically computational cost.

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.

An experimental study was conducted to evaluate the variable amplitude fatigue behavior of a neat polymer (polypropylene impact co-polymer) and a polymer composite made of polybutylene terephthalate (PBT) with 30 wt% short glass fibers. Fatigue tests were conducted on un-notched and notched specimens at room temperatures. Plate-type specimens were prepared in the transverse direction with respect to the injection mold flow direction and a circular hole was drilled in the center of notched specimens. Two-step loadings (high-low and low-high) tests at two damage ratio of 0.2 and 0.5 at stress ratios of R = 0.1 and -1 were conducted to investigate load sequence effects and prediction accuracy of the linear damage rule. Different behaviors were observed for unreinforced and short glass fiber reinforced polymers under the two-step loading tests.

Without engine noise, the cabin of an electric vehicle is quiet, but on the other hand, it becomes easy to perceive refrigerant-induced noise in the automotive air-conditioning (A/C) system. When determining the A/C system at the design stage, it is crucial to verify whether refrigerant-induced noise occurs in the system or not before the real A/C systems are made. If refrigerant-induced noise almost never occurs during the design stage, it is difficult to evaluate by vehicle testing at the development stage. This paper presents a 1D modeling methodology for the assessment of refrigerant-induced noise such as self-excitation noise generated by pressure pulsation through the thermal expansion valve (TXV). The GT-SUITE commercial code was used to develop a refrigerant cycle model consisting of a compressor, condenser, evaporator, TXV and the connecting pipe network.

A KIVA code which is customized for passenger car's diesel engines is linked with an engine performance simulator and demonstrated with our optimizing calculation system. Aiming to fulfill our target calculation speed, the combustion model of the KIVA code is changed from a chemical reaction calculation method to a chemical equilibrium calculation method which is introduced a unique technique handling chemical species maps. Those maps contain equilibrium mole fraction data of chemical species according to equivalence ratio and temperature. Linking the KIVA code to the engine simulator helps to evaluate engine performance by indicated mean effective pressure (IMEP). The optimizing calculation system enables to obtain response surfaces. Observing the response surfaces, clear views of engine performance characteristics can be seen. The overview of this calculation system and some examples of the calculation are shown in this paper.

Compression ratio of newly developed gasoline engines has been increased in order to improve fuel efficiency. But in-cylinder pressure around top dead center (TDC) before spark ignition timing is higher than expectation, because the low temperature oxidization (LTO) generates some heat. The overview of introduced calculation method taking account of the LTO heat of unburned gas, how in-cylinder pressure is revised and some knowledge of knocking prediction using chemical kinetics are shown in this paper.

An experimental study was conducted to evaluate the effect of water absorption on tensile and fatigue behaviors of an impact-modified short glass fiber polyamide-6 and a short glass fiber polybutylene terephthalate. Specimens were prepared in the longitudinal and transverse directions with respect to the injection mold flow direction and immersed in water. Kinetics of water absorption was studied and found to follow the Fick's law. Tensile tests were performed at room temperature with specimens in the longitudinal and transverse directions and with various degrees of water absorption. Mathematical relations were developed to represent tensile properties as a function of water content. Load-controlled tension-tension fatigue tests were conducted in both longitudinal and transverse directions and correlations between tensile and fatigue strengths were obtained. Specimen fracture surfaces were also microscopically studied and mechanisms of tensile and fatigue failures were identified.

With improvements in casting technology, cast iron can be an alternative to steel in some applications due to its similar strength. One objective of this study was to analyze cast iron data obtained from the literature and evaluate predictive correlations between its tensile, microstructural, and fatigue properties. Reasonably good correlation of tensile strength and yield strength were found with hardness. However, fatigue strength could not be correlated with hardness or tensile properties. Another objective of this study was to evaluate tensile and compressive means stress effects on fatigue behavior of 120-90-02 ductile cast iron experimentally, as well as analytically by using predictive models. Mean stress levels were chosen such that R ratios in load-controlled tests were −7, −3, −1, 0, 1/3, 0.5, and 0.75. Modified Goodman, Smith-Watson-Topper, FKM and the Fatemi-Socie mean stress parameters were used to account for the mean stress effect on fatigue life.

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.

Tip-in/Tip-out of the accelerator pedal generates transient torque oscillations in the driveline. These oscillations may be amplified by P/T, suspension and body modes and will eventually be sensible at the receiver side in the vehicle, for example at the seat or at the steering-wheel. The forces that are active during this transient excitation are influenced by non-linear effects in both the suspension and the power train mounts. In order to understand the contribution of each of these forces to the total interior target response (e.g. seat rail vibration) a detailed investigation is performed. Traditional force identification methods are not suitable for low-frequent, transient phenomena like tip-in/tip-out. Mount stiffness method can not be used because of non-linear effects in the P/T and suspension mounts. Application of matrix inversion method based on trimmed body vibration transfer functions is not possible due to numerical condition problems.

Automotive fenders is one such example where specialized thermoplastic material Noryl GTX* (blend of Polyphenyleneoxide (PPO) + Polyamide (PA)) has successfully replaced metal by meeting functional requirements. The evolution of a fender design to fulfill these requirements is often obtained through a combination of unique material properties and predictive engineering backed design process that accounts for fender behavior during the various phases of its lifecycle. This paper gives an overview of the collaborative design process between Mitsubishi Motors Corporation and SABIC Innovative Plastics and the role of predictive engineering in the evolution of a thermoplastic fender design of Mitsubishi Motors Corporation's compact SUV RVR fender launched recently. While significant predictive work was done on manufacturing and use stage design aspects, the focus of this paper is the design work related to identifying support configuration during the paint bake cycle.

Driving car means to control a vehicle according to a target path, e.g. road and speed, with some constraints. Human driving models have been proposed and applied for simulations. However, human control in driving has not been analyzed sufficiently comparing with that of machine control system in term of control theory. Input - output property with internal information processing is not easily measured and described. Response of human driving is not as quicker as that of machine controller but human can learn vehicle response to driving operation and predict target changes. Driving behavior of an expert driver and a beginner in an emission test cycle was measured and difference in target speed tracking was looked into with performance indices. The beginner's operation was less stable than that of the expert. Transfer function of the vehicle system was derived based on linearized model to investigate human driving behavior as a tracking controller in the system.

The chassis are subject to both road profile and engine or pump/motor vibration when a vehicle is moving on the road. The suspension is developed to reduce the effect of the road conditions to the chassis. The vibration from engine or pump/motor of hydraulic hybrid vehicles (HHV) will be also transmitted to the chassis and needs to be isolated. A mixed mode magnetorheological (MR) fluid mount is presented to isolate force vibration for a two degree of freedom (DOF) model based on quarter car concept. The MR fluid mount is designed to work in flow mode and squeeze mode separately and simultaneously. The skyhook control for the MR fluid mount is also been designed and simulated. Both displacement transmissibility and force transmissibility for each mode and for combined modes have been obtained. These simulation results present a basis for designing a more effective controller to control both the displacement transmissibility and force transmissibility.

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.

The paper presents the design and control aspects of a magnetorheological (MR) fluid based mount. The proposed design yields a high static stiffness and a low dynamic stiffness in the working frequency range of the mount, enhancing the vibration isolation capabilities of the mount compared to existing hydraulic mounts. Vertical vibrations, namely displacement/force transmissibility, can be isolated or significantly reduced, in real time, by controlling the fluid yield stress through an applied electric current. The mount governing equations are derived and the effectiveness of the mount is evaluated for two cases: low frequency-high displacement and at high frequency-low displacement. These cases correspond to the operation of the mount in squeeze mode and in flow mode, respectively. Preliminary results on the implementation of a skyhook control strategy are also presented.