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In the last two decades engine research has been mainly focused on reducing pollutant emissions. This fact together with growing awareness about the impacts of climate change are leading to an increase in the importance of thermal efficiency over other criteria in the design of internal combustion engines (ICE). In this framework, the heat transfer to the combustion chamber walls can be considered as one of the main sources of indicated efficiency diminution. In particular, in modern direct-injection diesel engines, the radiation emission from soot particles can constitute a significant component of the efficiency losses. Thus, the main of objective of the current research was to evaluate the amount of energy lost to soot radiation relative to the input fuel chemical energy during the combustion event under several representative engine loads and speeds. Moreover, the current research characterized the impact of different engine operating conditions on radiation heat transfer.

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

In the last decade, considerable advances have been made in reliability-based design optimization (RBDO). One assumption in RBDO is that the complete information of input uncertainties are known. However, this assumption is not valid in practical engineering applications, due to the lack of sufficient data. In practical engineering design, information concerning uncertainty parameters is usually in the form of finite samples. Existing methods in uncertainty based design optimization cannot handle design problems involving epistemic uncertainty with a shortage of information. Recently, a novel method referred to as Bayesian Reliability-Based Design Optimization (BRBDO) was proposed to properly handle design problems when engaging both epistemic and aleatory uncertainties [1]. However, when a design problem involves a large number of epistemic variables, the computation task for BRBDO becomes extremely expensive.

This paper presents an innovative approach for quality engineering using the Eigenvector Dimension Reduction (EDR) Method. Currently industry relies heavily upon the use of the Taguchi method and Signal to Noise (S/N) ratios as quality indices. However, some disadvantages of the Taguchi method exist such as, its reliance upon samples occurring at specified levels, results to be valid at only the current design point, and its expensiveness to maintain a certain level of confidence. Recently, it has been shown that the EDR method can accurately provide an analysis of variance, similar to that of the Taguchi method, but is not hindered by the aforementioned drawbacks of the Taguchi method. This is evident because the EDR method is based upon fundamental statistics, where the statistical information for each design parameter is used to estimate the uncertainty propagation through engineering systems.

Current Diesel engines development is facing challenging vibro-acoustic requirements and at the same time is struggling with the need to reduce as much as possible the cost and the weight of the engine. The latter obviously has become a key player for fuel consumption reduction. Large covers are commonly used in the base engine design and their noise contribution to total radiated noise is not negligible. Typical covers architecture shows thick cast and ribbed plates, meaning heavy and expensive covers. An interesting option is represented by using thin stamped covers either in aluminum or in steel, that have to show a low vibrational response. The current paper focuses on the structural optimization of such a peculiar design, trying to mitigate as much as possible its noise radiation with the intent to avoid any additional acoustic enabler (e.g. wrapping by means of acoustic foams) that will increase the final cost of the component.

Three high pressure multi-hole GDI injectors, one manufactured by Continental, two manufactured by Bosch, are experimentally characterized under various injection strategies in terms of instantaneous mass flow rate and fuel dispersion. Spray visualization within an optically accessible pressure vessel allows the measurement of the single jet cone angle and penetration length. A portable numerical model for the issuing spray dynamics is developed within the AVL Fire code, exploiting a log-normal distribution for the initial droplets diameter, whose expected value and variance are properly defined as a function of the main physical parameters. Tuning of the entering constants is realized by means of an automatic optimization procedure. An example of application of the spray model within a 3D simulation of the in-cylinder process of a GDI engine is presented. Effects of splitting injection into two successive events are discussed.

This paper describes the heat transfer model of a composite aluminum brake rotor and compares the predicted temperatures to dynamometer measurements taken during a 15 fade stop trial. The model is based on meshed surface geometry which is simulated using RadTherm software. Methods for realistically modeling heat load distribution, surface rotation, convection cooling and radiation losses are also discussed. A comparison of the simulation results to the dynamometer data shows very close agreement throughout the fade stop trial. As such, the model is considered valid and will be used for further Steel Clad Aluminum (SCA) rotor development.

The introduction of a thin fluid layer between two layers of sheet metal offers a highly effective and economical alternative to the use of constrained viscoelastic damping layers in sheet metal structures. A diesel engine gear cover, which is constructed of two sheet metal sections spot welded together, takes advantage of fluid layer damping to produce superior vibration and sound radiation performance. In this paper, the bending of a double layered plate coupled through a thin fluid layer is modeled using a traveling wave approach which results in a impedance function that can be used to assess the vibration and sound radiation performance of practical double layered plate structures. Guided by this model, the influence of fluid layer thickness and inside-to-outside sheet thickness is studied.

To reduce the number and severity of accidents, automakers have invested in active safety systems to detect and track neighboring vehicles to prevent accidents. These systems often employ RADAR and LIDAR, which are not degraded by low lighting conditions. In this research effort, reflections from deer were measured using two sensors often employed in automotive active safety systems. Based on a total estimate of one million deer-vehicle collisions per year in the United States, the estimated cost is calculated to be $8,388,000,000 [1]. The majority of crashes occurs at dawn and dusk in the Fall and Spring [2]. The data includes tens of thousands of RADAR and LIDAR measurements of white-tail deer. The RADAR operates from 76.2 to 76.8 GHz. The LIDAR is a time-of-flight device operating at 905 nm. The measurements capture the deer in many aspects: standing alone, feeding, walking, running, does with fawns, deer grooming each other and gathered in large groups.

Surrogate targets are used throughout the automotive industry to safely and repeatably test Advanced Driver Assistance Systems (ADAS) and will likely find similar applications in tests of Automated Driving Systems. For those test results to be applicable to real-world scenarios, the surrogate targets must be representative of the real-world objects that they emulate. Early target development efforts were generally divided into those that relied on sophisticated radar measurement facilities and those that relied on ad-hoc measurements using automotive grade equipment. This situation made communication and interpretation of results between research groups, target developers and target users difficult. SAE J3122, “Test Target Correlation - Radar Characteristics”, was developed by the SAE Active Safety Systems Standards Committee to address this and other challenges associated with target development and use. J3122 addresses four topics.