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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 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.

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.

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.

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.

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 following computational study examines the structure of sonic hydrogen jets using inlet conditions similar to those encountered in direct-injection hydrogen engines. Cases utilizing the same mass and momentum flux while varying exit-to-chamber pressure ratios have been investigated in a constant-volume computational domain. Furthermore, subsonic versus sonic structures have been compared using both hydrogen and ethylene fuel jets. Finally, the accuracy of scaling arguments to characterize an underexpanded jet by a subsonic “equivalent jet” has been assessed. It is shown that far downstream of the expansion region, the overall jet structure conforms to expectations for self-similarity in the far-field of subsonic jets. In the near-field, variations in fuel inlet-to-chamber pressure ratios are shown to influence the mixing properties of sonic hydrogen jets. In general, higher pressure ratios result in longer shock barrel length, though numerical resolution requirements increase.

Deep-hole drilling is among the most critical precision machining processes for production of high-performance discrete components. The effects of drilling with superimposed, controlled low-frequency modulation - Modulation-Assisted Machining (MAM) - on the surface textures created in deep-hole drilling (ie, gun-drilling) are discussed. In MAM, the oscillation of the drill tool creates unique surface textures by altering the burnishing action typical in conventional drilling. The effects of modulation frequency and amplitude are investigated using a modulation device for single-flute gun-drilling on a computer-controlled lathe. The experimental results for the gun-drilling of titanium alloy with modulation are compared and contrasted with conventional gun-drilling. The chip morphology and surface textures are characterized over a range of modulation conditions, and a model for predicting the surface texture is presented. Implications for production gun-drilling are discussed.

Conventional hydraulic steering systems keep improving performance and driving comfort by introducing advanced features via mechanical design. The ever increasing mechanical complexity requires the advanced modeling and simulation technology to mitigate the risks in the early stage of the development process. In this paper, we focus on advanced modeling tools environment with an example of a load sensing hydraulic steering system. The complete system architecture is presented. Analytical equations are developed for a priority valve and a steering control unit as the foundation of modeling. The full version of hydraulic steering system model is developed in Dymola platform. In order to capture interaction between steering and vehicle, the co-simulation platform between the hydraulic steering system and vehicle dynamics is established by integrating Dymola, Carsim and Simulink.

This paper presents a simulation model for the analysis of internal gear ring pumps. The model follows a multi domain simulation approach comprising sub-models for parametric geometry generation, fluid dynamic simulation, numerical calculation of characteristic geometry data and CAD/FEM integration. The sub-models are interacting in different domains and relevant design and simulation parameters are accessible in a central, easy to handle graphical user interface. The potentials of the described tool are represented by simulation results for both steady state and transient pump operating conditions and by their correlation with measured data. Although the presented approach is suitable to all applications of gear ring pumps, a particular focus is given to hydraulic actuation systems used in automotive drivetrain applications.

Excessive vibration and poor controllability occur in many mobile fluid power applications, with negative consequences as concerns operators' health and comfort as well as machine safety and productivity. This paper addresses the problem of reducing oscillations in fluid power machines presenting a novel control technique of general applicability. Strong nonlinearities of hydraulic systems and the unpredictable operating conditions of the specific application (e.g. uneven ground, varying loads, etc.) are the main challenges to the development of satisfactory general vibration damping methods. The state of the art methods are typically designed as a function of the specific application, and in many cases they introduce energy dissipation and/or system slowdown. This paper contributes to this research by introducing an energy efficient active damping method based on feedback signals from pressure sensors mounted on the flow control valve block.

The four-microphone standing wave tube system has proven useful for measuring the absorption and transmission loss of various fibrous and non-fibrous absorbers. The system is fast, repeatable, accurate and compact. This paper discusses the advantages of the four-microphone system for measuring the transmission loss in lateral-flow absorber systems. The original four-microphone round impedance tube system and the migration to a four-microphone square tube system are discussed. The four-microphone square tube system allows effective study of filled and partially filled cavities.

Notched spoilers may be used to suppress flow-induced cavity resonance in vehicles with open sunroofs or side windows. The notches are believed to generate streamwise vortices that break down the structure of the leading edge cross-stream vortices predominantly responsible for the cavity excitation. The objectives of the present study were to gain a better understanding of the buffeting suppression mechanisms associated with notched spoilers, and to gather data for computational model verification. To this end, experiments were performed to characterize the surface pressure field downstream of straight and notched spoilers mounted on a rigid wall to observe the effects of the notches on the static and dynamic wall pressure. Detailed flow velocity measurements were made using hot-wire anemometry. The results indicated that the presence of notches on the spoiler reduces drag, and thus tends to move the flow reattachment location closer to the spoiler.

This paper presents a method for indirect measurement of tire slip angles from chassis acceleration, yaw rate, and steer angle measurements. The chassis is assumed to be rigid so that acceleration data can be integrated to estimate velocities of the front and rear of the vehicle, from which slip angles can be predicted. The difference in front and rear slip angles is indicative of vehicle oversteer/understeer. Understeer data can then be correlated with position on the track to better understand vehicle handling behavior, aiding the tuning process. The technique is presented, and shown to work well with simulated data, even when the data is corrupted with up to 20% noise. Therefore, the inversion process presented here is theoretically sound. However, when the technique is applied to measured data from race cars, it is shown to be inaccurate. One suspected problem is the difficulty of getting accurate yaw rate data.

A temperature estimation algorithm (thermal observer) that provides accurate estimates of the thermal states of an electric machine in real time is presented. The thermal observer is designed to be a Kalman filter that combines thermal state predictions from a lumped-parameter thermal model of the electric machine with temperature measurements from a single external temperature sensor. An analysis based on the error covariance matrix of the Kalman filter is presented to guide the selection of the best sensor location. The thermal observer performance is demonstrated using a 3.8 kW permanent-magnet machine. Comparison of the thermal observer estimates and the actual temperatures demonstrate that this approach can provide accurate knowledge of the machine's thermal states despite modeling uncertainty and unknown initial machine thermal states.

A layered approach to the simulation of dynamically interdependent systems is presented. In particular, the approach is applied to the integrated engineering plant of a notional all-electric warship. The models and parameters of the notional ship are presented herein. This approach is used to study disruptions to the integrated engineering plant caused by anti-ship missiles. Example simulation results establish the effectiveness of this approach in examining the propagation of faults and cascading failures throughout a dynamically interdependent system of systems.