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Cooled EGR continues to be a key technology to meet emission regulations, with EGR coolers performing a critical role in the EGR system. Designing EGR coolers that reliably manage thermal loads is a challenge with thermal fatigue being a top concern. The ability to estimate EGR cooler thermal fatigue life early in the product design and validation cycle allows for robust designs that meet engine component reliability requirements and customer expectations. This paper describes a process to create an EGR cooler thermal fatigue life model. Components which make up the EGR cooler have differing thermal responses, consequently conjugate transient CFD must be used to accurately model metal temperatures during heating and cooling cycles. Those metal temperatures are then imported into FEA software for structural analysis. Results from both the CFD and FEA are then used in a simplified numerical model to estimate the virtual strain of the EGR cooler.

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.

The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

A head gasket is a component that sits between the engine block/liner and cylinder head(s) in an internal combustion engine. Its purpose is to seal high pressure combustion gasses in the cylinders and to seal coolant and engine oil. It is the most critical sealing application in an engine. As a general practice, the load deflection(L/D) characteristic is generated by the gasket manufacturer for edge molded or composite gasket types. However, in the case of a solid-sheet metallic gasket, where the gasket is expected to undergo localized yielding to provide adequate conformance and sealing, usually supplier may not be able to provide the required L/D curve due to difficulties to experimentally separate the large loads and small displacements from the elastic loads and deflections of the experimental apparatus. In absence of L/D curve, the typical analysis approach is to model gasket as 3D continuum elements available in ansys by considering nonlinear material and frictional contacts.

The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.

The combustion process after auto-ignition is investigated. Depending on the non-uniformity of the end gas, auto-ignition could initiate a flame, produce pressure waves that excite the engine structure (acoustic knock), or result in detonation (normal or developing). For the “acoustic knock” mode, a knock intensity (KI) is defined as the pressure oscillation amplitude. The KI values over different cycles under a fixed operating condition are observed to have a log-normal distribution. When the operating condition is changed (over different values of λ, EGR, and spark timing), the mean (μ) of log (KI/GIMEP) decreases linearly with the correlation-based ignition delay calculated using the knock-point end gas condition of the mean cycle. The standard deviation σ of log(KI/GIMEP) is approximately a constant, at 0.63. The values of μ and σ thus allow a statistical description of knock from the deterministic calculation of the ignition delay using the mean cycle properties

This paper presents an experimental setup and an equivalent FEM simulation methodology to accurately predict the response of Engine Control Module (ECM) assembly mounted on a commercial vehicle subjected to road vibrations. Comprehensive vibration study is carried out. It involved Modal characteristics determination followed by random vibration characterization of the ECM assembly. A hammer impact experiment is first performed in lab to estimate the natural frequencies and mode shapes of ECM assembly. Mounting conditions in test specimen are kept similar to the actual mounting settings on vehicle. Natural frequencies and mode shapes predicted from free vibration experiment are compared with finite element (FE) based modal analysis. The importance of capturing the assembly stiffness more accurately by incorporating pre-stress effects like bolt-pretension and gravity, is emphasized.

Dynamometer (dyno) durability testing plays a significant role in reliability and durability assessment of commercial engines. Frequently, durability test procedures are based on warranty history and corresponding component failure modes. Evolution of engine designs, operating conditions, electronic control features, and diagnostic limits have created challenges to historical-based testing approaches. A physics-based methodology, known as Load Matrix, is described to counteract these challenges. The technique, developed by AVL, is based on damage factor models for subsystem and component failure modes (e.g. fatigue, wear, degradation, deposits) and knowledge of customer duty cycles. By correlating dyno test to field conditions in quantifiable terms, such as customer equivalent miles, more effective and efficient durability test suites and test procedures can be utilized. To this end, application of Load Matrix to a heavy-duty diesel engine is presented.

In this paper we investigate the optimal forming of conical cups of AL 2008-T4 through the use of real-time process control. We consider a flat, frictional binder the force of which can be determined precisely through closed-loop control. Initially the force is held constant throughout the forming of the cup, and various levels of force are tested experimentally and with numerical simulation. Excellent agreement between experiment and simulation is observed. The effects of binder force on cup shape, thickness distribution, failure mode and cup failure height are investigated, and an “optimal” constant binder force is determined. For this optimal case, the corresponding punch force is recorded as a function of punch displacement and is used in subsequent closed-loop control experiments. In addition to the constant force test, a trial variable binder force test was performed to extend the failure height beyond that obtained using the “optimal” constant force level.

Draw beads are widely utilized as a mechanism for providing proper restraining force to a sheet in a forming operation. In this paper, numerical simulations using the nonlinear finite element method are conducted to model the process of drawing a sheet through various draw bead configurations to study the mechanics of draw bead restraint. By examing the sensitivity of the draw bead restraining force due to the change of the draw bead penetration, the work shows that the penetration has the potential to be a very good element for varying and controlling restraining force during the process. A closed-loop feedback control of draw bead penetration using a proportional-integral controller is achieved by the combination of the original finite element simulation and a special element which links penetration to a pre-defined restraining force trajectory.

Global emission legislations for diesel engines are becoming increasingly stringent. While the exhaust gas composition requirements for prior iterations of emission legislation could be met with improvements in the engine's combustion process, the next issue of European, North American and Japanese emission limits greater than 2005 will require more rigorous measures, mainly employment of exhaust gas aftertreatment systems. As a result, many American diesel OEMs are considering NOx adsorbers as a means to achieve 2007+ emission standards. Since the efficacy of a NOx adsorber over its lifetime is significantly affected by sulfur (“sulfur poisoning”), forthcoming reductions in diesel fuel sulfur (down to 15 ppm), have raised industry concerns regarding compatibility and possible poisoning effects of sulfur from the lubricant.

This paper presents the Statistical Energy Approach (SEA) method for estimating the gross response in complex interconnected structural systems. The method is intended to compensate for the difficulties present in evaluating parameters and excitation needed when attempting to use traditional methods of linear vibration analysis. The amount of information needed to apply the method is modest and the formulas are easy to use. Some limitation on application is demonstrated by a detailed example.

One of the goals of designing engineering systems is to maximize the system's reliability. A reliable system must satisfy its functional requirements without failure throughout its intended lifecycle. The typical means to achieve a desirable level of reliability is through preventive maintenance of a system; however, this involves cost. A more fundamental approach to the problem is to maximize the system's reliability by preventing failures from occurring. A key question is to find mechanisms (and the means to implement them into a system) that will prevent its system range from going out of the design range. Functional periodicity is a means to achieve this goal. Three examples are discussed to illustrate the concept. In the new electrical connector design, it is the geometric functional periodicity provided by the woven wire structure. In the case of integrated manufacturing systems, it is the periodicity in scheduling of the robot motion.

A common scenario in engineering design is the availability of several black-box functions that describe an event with different levels of accuracy and evaluation cost. Solely employing the highest fidelity, often the most expensive, black-box function leads to lengthy and costly design cycles. Multi-fidelity modeling improves the efficiency of the design cycle by combining information from a small set of observations of the high-fidelity function and large sets of observations of the low-fidelity, fast-to-evaluate functions. In the context of Bayesian optimization, the most popular multi-fidelity model is the auto-regressive (AR) model, also known as the co-kriging surrogate. The main building block of the AR model is a weighted sum of two Gaussian processes (GPs). Therefore, the AR model is well suited to exploit information generated by sources that present strong linear correlations.

Eigenvalues of a simple rotating flexible disk-shaft system are obtained using different methods. The shaft is supported radially by non-rigid bearings, while the disk is situated at one end of the shaft. Eigenvalues from a finite element and a multi-body dynamic tool are compared against an established analytical formulation. The Campbell diagram based on natural frequencies obtained from the tools differ from the analytical values because of oversimplification in the analytical model. Later, detailed whirl analysis is performed using AVL Excite multi-body tool that includes understanding forward and reverse whirls in absolute and relative coordinate systems and their relationships. Responses to periodic force and base excitations at a constant rotational speed of the shaft are obtained and a modified Campbell diagram based on this is developed. Whirl of the center of the disk is plotted as an orbital or phase plot and its rotational direction noted.

Gear profile deviation is the difference in gear tooth profile from the ideal involute geometry. There are many causes that result in the deviation. Deflection under load, manufacturing, and thermal effects are some of the well-known causes that have been reported to cause deviation of the gear tooth profile. The profile deviation caused by gear tooth profile deformation due to interference-fit assembly has not been discussed previously. Engine timing gear trains, transmission gearboxes, and wind turbine gearboxes are known to use interference-fit to attach the gear to the rotating shaft. This paper discusses the interference-fit joint design and the mechanism of tooth profile deformation due to the interference-fit assembly in gear trains. A new analytical method to calculate the profile slope deviation change due to interference-assembly of parallel axis spur gears is presented.

Automotive timing gear trains, transmission gearboxes, and wind turbine gearboxes are some of the application examples known to use interference-fit to attach the gear to the rotating shaft. This paper discusses the interference-fit joint design and the finite element analysis to demonstrate the distortion. The mechanism of tooth profile distortion due to the interference-fit assembly in gear trains is discussed by demonstrating the before and after assembly gear profile measurements. An algorithm to calculate the profile slope deviation change is presented. The effectiveness of the computational algorithm to predict the distortion is demonstrated by comparing with measurements. Finally, steps to mitigate the interference assembly effects are discussed.

This paper describes research to analyze widespread fatigue damage in lap joints. The particular objective is to determine when large numbers of small cracks could degrade the joint strength to an unacceptable level. A deterministic model is described to compute fatigue crack growth and residual strength of riveted panels that contain multiple cracks. Fatigue crack growth tests conducted to evaluate the predictive model are summarized, and indicate good agreement between experimental and numerical results. Monte Carlo simulations are then performed to determine the influence of statistical variability on various analysis parameters.

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means for interrogating the condition of the filter itself.