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The beneficial effects of contact disruption in modulation-assisted machining of aerospace alloys have been well documented, but sources for such improvements are not well understood. This study explores the underlying nature of differences that occur in energy dissipation during conventional and modulation-assisted machining by characterizing the relationship between controllable process parameters and their effects on chip formation. Simultaneous in situ force and tool position measurements are used to show that the forces in modulation-assisted machining can be described by empirical force models in conventional machining conditions. These models are found to accurately describe plastic dissipation over a range of modulation conditions and configurations, including in cases where energy expenditure decreases with the application of modulation. These observations suggest that the underlying response in modulation-assisted machining is analogous to that of conventional machining.

The identification of the dominant noise sources in diesel engines and the assessment of their contribution to far-field noise is a process that can involve both fired and motored testing. In the present work, the cross-spectral densities of signals from cylinder pressure transducers, accelerometers mounted on the engine surface, and microphones (in the near and far fields), were used to identify dominant noise sources and estimate the transfer paths from the various “inputs” (i.e., the cylinder pressures, the accelerometers and the near field microphones) to the far field microphones. The method is based on singular value decomposition of the input cross-spectral matrix to relate the input measurements to independent virtual sources. The frequencies at which a particular input is strongly affected by an independent source are highlighted, and with knowledge of transducer locations, inferences can be drawn as to possible noise source mechanisms.

In order to ensure the safety of a structure, adequate strength for structural elements must be provided. Moreover, catastrophic deformations such as buckling must be prevented. Using the linear finite element method, deterministic buckling analysis is completed in two main steps. First, a static analysis is performed using an arbitrary ordinate applied loading pattern. Using the obtained element axial forces, the geometric stiffness of the structure is assembled. Second, an eigenvalue problem is performed between structure's elastic and geometric stiffness matrices, yielding the structure's critical buckling loads. However, these deterministic approaches do not consider uncertainty the structure's material and geometric properties. In this work, a new method for finite element based buckling analysis of a structure with uncertainty is developed. An imprecise probability formulation is used to quantify the uncertainty present in the mechanical characteristics of the structure.

The structural excitation by turbulent flow pressure fluctuations continues to be an important part of vehicle NVH analysis and design. Much of the analytical work on turbulent flow has been limited to flow over smooth, flat surfaces. Measurements and CFD analyses show a significantly different pressure spectrum for flows over an obstruction. The coupling of the turbulent pressure excitation to the structural vibration and transmitted sound depends on the spatial matching between the source and response fields. This paper develops an analytical model for the spatial correlation of turbulent flow pressure fluctuations downstream of an obstruction. Such a model is useful in the early design stage of a vehicle and is compatible with SEA models of the fluid structure interaction.

In computational fluid dynamic (CFD) and computational aeroacoustics (CAA) simulations, the wall surface is normally treated as a purely reflective wall. However, some surface treatments are usually applied in experiments. Thus, the acoustic simulations cannot be validated by experimental results. One of the major challenges is how to define acoustically boundary conditions in a well-posed way. In aeroacoustics analysis, impedance is a quantity to characterize reflectivity and absorption of an acoustically treated surface, which may be introduced into the numerical models as a frequency-domain boundary condition. However, CFD and CAA simulations are time-domain computations, meaning the frequency-domain impedance boundary condition cannot be adopted directly. Several methods, including the three-parameter model, the z-transform method and the reflection coefficient model, were developed.

Experimental measurements of tire tread band vibration have provided direct evidence that higher order structural-acoustic modes exist in tires, not just the well-known fundamental acoustical mode. These modes display both circumferential and radial pressure variations within the tire's air cavity. The theory governing these modes has thus been investigated. A brief recapitulation of the previously-presented coupled structural-acoustical model based on a tensioned string approach will be given, and then an improved tire-acoustical model with a ring-like shape will be introduced. In the latter model, the effects of flexural and circumferential stiffness are considered. This improved model accounts for propagating in-plane vibration in addition to the essentially structure-borne flexural wave and the essentially airborne longitudinal wave accounted for in the previous model. The longitudinal structure-borne wave “cuts on” at the tire's circumferential ring frequency.

Component sound quality is an important factor in the design of competitive diesel engines. One component noise that causes complaints is the gear rattle that originates in the front-of-engine gear train which drives the fuel pump and other accessories. The rattle is caused by repeated tooth impacts resulting from fluctuations in differential torsional acceleration of the driving gears. These impacts generate a broadband, impulsive noise that is often perceived as annoying. In most previous work, the overall sound quality of diesel engines has been considered without specifically focusing on predicting the perception of gear rattle. Gear rattle level has been quantified based on angular acceleration measurements, but those measurements can be difficult to perform. Here, the emphasis was on developing a metric based on subjective testing of the perception of gear rattle.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

Over the last decade, a number of hybrid architectures have been proposed with the main goal of minimizing energy consumption of off-highway vehicles. One of the architecture subsets which has progressively gained attention is hydraulic hybrids for earth-moving equipment. Among these architectures, hydraulic hybrids with secondary-controlled drives have proven to be a reliable, implementable, and highly efficient alternative with the potential for up to 50% engine downsizing when applied to excavator truck-loading cycles. Multi-input multi-output (MIMO) robust linear control strategies have been developed by the authors' group with notable improvements on the control of the state of charge of the high pressure accumulator. Nonetheless, the challenge remains to improve the actuator position and velocity tracking.

Interest in natural gas as an alternative fuel source to petroleum fuels for light-duty vehicle applications has increased due to its domestic availability and stable price compared to gasoline. With its higher hydrogen-to-carbon ratio, natural gas has the potential to reduce engine out carbon dioxide emissions, which has shown to be a strong greenhouse gas contributor. For part-load conditions, the lower flame speeds of natural gas can lead to an increased duration in the inflammation process with traditional port-injection. Direct-injection of natural gas can increase in-cylinder turbulence and has the potential to reduce problems typically associated with port-injection of natural gas, such as lower flame speeds and poor dilution tolerance. A study was designed and executed to investigate the effects of direct-injection of natural gas at part-load conditions.

Advanced internal combustion engines, although generally more efficient than conventional combustion engines, often encounter limitations in multi-cylinder applications due to variations in the combustion process. This study leverages experimental data from an inline 6-cylinder heavy-duty dual fuel engine equipped with a fully-flexible variable intake valve actuation system to study cylinder-to-cylinder variations in power production. The engine is operated with late intake valve closure timings in a dual-fuel combustion mode featuring a port-injection and a direct-injection fueling system in order to improve fuel efficiency and engine performance. Experimental results show increased cylinder-to-cylinder variation in IMEP as IVC timing moves from 570°ATDC to 610°ATDC, indicating an increasingly uneven fuel distribution between cylinders.

An experiment has been developed to investigate the ignition characteristics of ultra-lean premixed H2/air mixtures by a supersonic hot jet. The hot jet is generated by combustion of a stoichiometric mixture in a small prechamber. The apparatus adopted a dual-chamber design in which a small-volume (1% of the main chamber by volume) prechamber was installed within a large-volume main chamber. A small orifice (nozzle) connects the two chambers. Spark initiated combustion inside the prechamber causes a pressure rise and pushes the gases though the nozzle, resulting in a hot jet that would ignite the lean mixture in the main chamber. Simultaneous high-speed Schlieren photography and OH* Chemiluminescence were applied to visualize the jet penetration and the ignition processes inside the main chamber. Hot Wire Pyrometry (HWP) was used to measure temperature distribution of the transient hot jet.

This paper describes a novel design and verification process for analytical methods used in the development of advanced combustion strategies in internal combustion engines (ICE). The objective was to improve brake thermal efficiency (BTE) as part of the US Department of Energy SuperTruck program. The tools and methods herein discussed consider spray formation and injection schedule along with piston bowl design to optimize combustion efficiency, air utilization, heat transfer, emission, and BTE. The methodology uses a suite of tools to optimize engine performance, including 1D engine simulation, high-fidelity CFD, and lab-scale fluid mechanic experiments. First, a wide range of engine operating conditions are analyzed using 1-D engine simulations in GT Power to thoroughly define a baseline for the chosen advanced engine concept; secondly, an optimization and down-select step is completed where further improvements in engine geometries and spray configurations are considered.

One way to develop an understanding of soot formation and oxidation processes that occur during direct injection and combustion in an internal combustion engine is to image the natural luminosity from soot over time. Imaging is possible when there is optical access to the combustion chamber. After the images are acquired, the next challenge is to properly interpret the luminous distributions that have been captured on the images. A major focus of this paper is to provide guidance on interpretation of experimental images of soot luminosity by explaining how radiation from soot is predicted to change as it is transmitted through the combustion chamber and to the imaging. The interpretations are only limited by the scope of the models that have been developed for this purpose. The end-goal of imaging radiation from soot is to estimate the amount of soot that is present.

Green Light Optimized Speed Advisory (GLOSA) systems have the objective of providing a recommended speed to arrive at a traffic signal during the green phase of the cycle. GLOSA has been shown to decrease travel time, fuel consumption, and carbon emissions; simultaneously, it has been demonstrated to increase driver and passenger comfort. Few studies have been conducted using historical cycle-by-cycle phase probabilities to assess the performance of a speed advisory capable of recommending a speed for various traffic signal operating modes (fixed-time, semi-actuated, and fully-actuated). In this study, a GLOSA system based on phase probability is proposed. The probability is calculated prior to each trip from a previous week’s, same time-of-day (TOD) and day-of-week (DOW) period, traffic signal controller high-resolution event data.

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.

Nowadays, the increasing number of structural high pressure die casting (HPDC) aluminum parts need to be joined with high strength steel (HSS) parts in order to reduce the weight of vehicle for fuel-economy considerations. Self-Pierce Riveting (SPR) has become one of the strongest mechanical joining solutions used in automotive industry in the past several decades. Joining HPDC parts with HSS parts can potentially cause joint quality issues, such as joint button cracks, low corrosion resistance and low joint strength. The appropriate heat treatment will be suggested to improve SPR joint quality in terms of cracks reduction. But the heat treatment can also result in the blister issue and extra time and cost consumption for HPDC parts. The relationship between the microstructure of HPDC material before and after heat treatment with the joint quality is going to be investigated and discussed for interpretation of cracks initiation and propagation during riveting.

In an Adaptive Cycle Engine (ACE), thermodynamics favors combustion starting while the compressed, premixed air and fuel are still flowing into the cylinder through the transfer valve. Since the flow velocity is typically high and is predicted to reach sonic conditions by the time the transfer valve closes, the flame might be subjected to extensive stretch, thus leading to aerodynamic quenching. It is also unclear whether a single spark, or even a succession of sparks, will be sufficient to achieve complete combustion. Given that the first ACE prototype is still being built, this issue is addressed by numerical simulation using the G-equation model, which accounts for the effect of flame stretching, over a 3D domain representing a flat-piston ACE cylinder, both with inward- and outward-opening valves. A k-epsilon turbulence model was used for the highly turbulent flow field.

The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

The compression ratio is a strong lever to increase the efficiency of an internal combustion engine. However, among others, it is limited by the knock resistance of the fuel used. Natural gas shows a higher knock resistance compared to gasoline, which makes it very attractive for use in internal combustion engines. The current paper describes the knock behavior of two gasoline fuels, and specific incylinder blend ratios with one of the gasoline fuels and natural gas. The engine used for these investigations is a single cylinder research engine for light duty application which is equipped with two separate fuel systems. Both fuels can be used simultaneously which allows for gasoline to be injected into the intake port and natural gas to be injected directly into the cylinder to overcome the power density loss usually connected with port fuel injection of natural gas.