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Despite numerous research efforts, there is no reliable and widely accepted tool for the prediction of erosion prone material surfaces due to collapse of cavitation bubbles. In the present paper an Erosion Aggressiveness Index (EAI) is proposed, based on the pressure loads which develop on the material surface and the material yield stress. EAI depends on parameters of the liquid quality and includes the fourth power of the maximum bubble radius and the bubble size number density distribution. Both the newly proposed EAI and the Cavitation Aggressiveness Index (CAI), which has been previously proposed by the authors based on the total derivative of pressure at locations of bubble collapse (DP/Dt>0, Dα/Dt<0), are computed for a cavitating flow orifice, for which experimental and numerical results on material erosion have been published. The predicted surface area prone to cavitation damage, as shown by the CAI and EAI indexes, is correlated with the experiments.

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.

Researchers desire to evaluate system reliability uniquely and efficiently. Despite its strong technical demand, little progress has been made on system reliability analysis in the last two decades. Up to now, bound methods for system reliability prediction have been dominant. For system reliability bounds, the second order bound method gives fairly accurate prediction for system reliability assuming that the probabilities of second-order joint events are accurately obtained. Two primary challenges in system reliability analysis are evaluation of the probabilities of second-order joint events and no unique system reliability for design optimization. Firstly, the greatest technical demand is found in an accurate and efficient method to numerically evaluate the probability of a second-order joint event.

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.

A one-dimensional model simulating the oxidation of CO, HC, and NO was developed to predict the gaseous emissions downstream of a diesel oxidation catalyst (DOC). The model is based on the conservation of mass, species, and energy inside the DOC and draws on past research literature. Steady-state experiments covering a wide range of operating conditions (exhaust temperatures, flow rates and gaseous emissions) were performed, and the data were used to calibrate and validate the model. NO conversion efficiencies of 50% or higher were obtained at temperatures between 300°C and 350°C. CO conversion efficiencies of 85% or higher and HC conversion efficiencies of 75% or higher were found at every steady state condition above 200°C. The model agrees well with the experimental results at temperatures from 200°C to 500°C, and volumetric flow rates from 8 to 42 actual m3/min.

Elastomers are traditionally designed for use in applications that require specific mechanical properties. Unfortunately, these properties change with respect to many different variables including heat, light, fatigue, oxygen, ozone, and the catalytic effects of trace elements. When elastomeric mounts are designed for NVH use in vehicles, they are designed to isolate specific unwanted frequencies. As the elastomers age however, the desired elastomeric properties may have changed with time. This study looks at the variability seen in new vehicle engine mounts and how the dynamic properties change with respect to miles accumulated on fleet and durability test vehicles.

The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.

With stringent emission regulations, aftertreatment systems with a Diesel Particulate Filter (DPF) and a Selective Catalytic Reduction (SCR) are required for diesel engines to meet PM and NOx emissions. The adoption of aftertreatment increases the back pressure on a typical diesel engine and makes engine calibration a complicated process, requiring thousands of steady state testing points to optimize engine performance. When configuring an engine to meet Tier IV final emission regulations in the USA or corresponding Stage IV emission regulations in Europe, this high back pressure dramatically impacts transient performance. The peak NOx, smoke and exhaust temperature during a diesel engine transient cycle, such as the Non-Road Transient Cycle (NRTC) defined by the US Environmental Protection Agency (EPA), will in turn affect the performance of the aftertreatment system and the tailpipe emissions level.

Caterpillar Inc. has developed a new diesel engine fuel system, powered by hydraulics and controlled electronically. This Hydraulic Electronic Unit Injector, (HEUI), requires no mechanical actuating or mechanical control devices, and offers many advantages over conventional fuel injection systems. Inherent features of the HEUI Fuel System include injection pressure control independent of engine load or speed, totally flexible injection timing, and full electronic control of injection parameters. Packaging the HEUI Fuel System on an engine is simple, as the injector is compact and available in a variety of configurations. The hydraulic actuating circuit is straightforward, using lubricating oil from the engine sump. Hydraulic lines may be internal to the engine or external. This paper describes the Caterpillar HEUI Fuel System, its operating features, performance advantages, and application to diesel engines.

Catalytic converters have become a viable aftertreatment system for reducing emissions from on-highway diesel engines. This paper addresses the development and production qualification of a catalytic converter. The testing programs that were utilized to qualify the converter system for production included emissions performance, emissions durability, physical durability, and field test programs. This paper reports on the specific tests that were utilized for the emissions performance and emissions durability testing programs. An explanation on the development of an accelerated durability test program is also included. The physical durability section of the paper discusses the development and execution of laboratory bench tests to insure the catalytic converter/muffler maintains acceptable physical integrity.

Field testing of an extended life coolant technology in Class 8 trucks, equipped with Caterpillar C-12 engines revealed excellent coolant life with negligible inhibitor depletion to 400,000 miles with no refortification and no coolant top-off. In separate evaluations in Caterpillar 3406E equipped trucks, extended corrosion protection and component durability were established out to 700,000 miles, without the need for refortification other than top-off.

This paper presents real-world driving energy and fuel consumption results for the second-generation Chevrolet Volt plug-in hybrid electric vehicle (PHEV). A drive cycle, local to Michigan Technological University, was designed to mimic urban and highway driving test cycles in terms of distance, transients and average velocity, but with significant elevation changes to establish an energy intensive real-world driving cycle for assessing potential energy savings for connected and automated vehicle (CAV) control. The investigation began by establishing baseline and repeatability of energy consumption at various battery states of charge. It was determined that drive cycle energy consumption under a randomized set of boundary conditions varied within 3.6% of mean energy consumption regardless of initial battery state of charge.

Sound intensity measurement techniques that used a two-microphone configuration, were first developed in the late 1970s. Originally, the focus was on improving precision during testing or post-processing. However, with the advent of modern, sophisticated equipment, the focus has shifted to the apparatus. Availability of phase-matched microphones has made post-test correction obsolete as the microphones eliminate a majority of the errors before the data is even collected. This accuracy, however, comes at a cost, as phase-matched microphones are highly priced. This paper discusses employing the method of improving post-processing precision, using inexpensive, current equipment. The phase error of the system is corrected using a simple calibration technique and a handheld phase calibrator that is similar to the one used for amplitude calibration of microphones.

A full calibration exercise of a diesel engine air path can take months to complete (depending on the number of variables). Model-based calibration approach can speed up the calibration process significantly. This paper discusses the overall calibration process of the air-path of the Cat® C7.1 engine using statistical machine learning tool. The standard Cat® C7.1 engine's twin-stage turbocharger was replaced by a VTG (Variable Turbine Geometry) as part of an evaluation of a novel air system. The changes made to the air-path system required a recalculation of the air path's boost set point and desired EGR set point maps. Statistical learning processes provided a firm basis to model and optimize the air path set point maps and allowed a healthy balance to be struck between the resources required for the exercise and the resulting data quality.

With stringent emission regulations, many subsystems that abate engine tailpipe-out emissions become a necessary part for engines. The increased level of complexity poses technical challenges for the quality and reliability for modern engines. Among the spectrum of quality control methodologies, one conventional methodology focuses on every component's quality to ensure that the accumulative deviation is within predetermined limits. This conventional methodology tightens the component tolerance during the manufacturing process and typically results in increased cost. Another conventional methodology that is on the other side of the spectrum focuses on tailoring an engine calibration solution to offset the manufacturing differences. Although the tailored engine calibration solution reduces manufacturing cost for components, it increases the development and validation cost for engines. Given the cost and time constraints, system integration plays an important role in engine development.

An over-expanded spark ignited engine was investigated in this work via engine simulation with a design constrained, mechanically actuated Atkinson cycle mechanism. A conventional 4-stroke spark-ignited turbo-charged engine with a compression ratio of 9.2 and peak brake mean effective pressure of 22 bar was selected for the baseline engine. With geometry and design constraints including bore, stroke, compression ratio, clearance volume at top dead center (TDC) firing, and packaging, one over-expanded engine mechanism with over expansion ratio (OER) of 1.5 was designed. Starting with a validated 1D engine simulation model which included calibration of the in-cylinder heat transfer model and SI turbulent combustion model, investigations of the Atkinson engine including cam optimization was studied. The engine simulation study included the effects of offset of piston TDC locations as well as different durations of the 4-strokes due to the mechanism design.

Sonic flow, pulse-width-modulated electronic fuel injectors for gaseous fuels provide precise, stable and reliable service for over 1 billion cycles. Techniques for precision flow calibration are described along with dynamic response characteristics. Application techniques including pressure regulation, filtration and procedures for adjusting flow calibration for changes in gas pressure, temperature and composition are presented. Applications include single point (throttle body or mixer), multi-point constant flow and multipoint sequential strategies. Durability testing in parallel with a utility pipeline regulator fully conserves power and gaseous fuel in a simple, low cost, multiple injector test bank.