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Transient operating conditions in electrical systems not only have significant impact on the operating behavior of individual components but indirectly affect system and component reliability and life. Specifically, transient loads can cause additional loss in the electrical conduction path consisting of windings, power electronic devices, distribution wires, etc., particularly when loads introduce high peak vs. average power ratios. The additional loss increases the operating temperatures and thermal cycling in the components, which is known to reduce their life and reliability. Further, mechanical stress caused by dynamic loading, which includes load torque cycling and high peak torque loading, increases material fatigue and thus reduces expected service life, particularly on rotating components (shaft, bearings).

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.

Future aircraft systems are projected to have order of magnitude greater power and thermal demands, along with tighter constraints on the performance of the power and thermal management subsystems. This trend has led to the need for a fully integrated design process where power and thermal systems, and their interactions, are considered simultaneously. To support this new design paradigm, a general framework for codifying and checking specifications and requirements is presented. This framework is domain independent and can be used to translate requirement language into a structured definition that can be quickly queried and applied to simulation and measurement data. It is constructed by generalizing a previously developed power quality analysis framework. The application of this framework is demonstrated through the translation of thermal specifications for airborne electrical equipment, into the SPecification And Requirement Evaluation (SPARE) Tool.

Experimental Hardware-in-the-loop (xHIL) testing utilizing signal and/or power emulation imposes a hard real-time requirement on models of emulated subsystems, directly limiting their fidelity to what can be achieved in real-time on the available computational resources. Most real-time simulators are CPU-based, for which the overhead of an instruction-set architecture imposes a lower limit on the simulation step size, resulting in limited model bandwidth. For power-electronic systems with high-frequency switching, this limit often necessitates using average-value models, significantly reducing fidelity, in order to meet the real-time requirement. An alternative approach emerging recently is to use FPGAs as the computational platform, which, although offering orders-of-magnitudes faster execution due to their parallel architecture, they are more difficult to program and their limited fabric space bounds the size of models that can be simulated.

This paper introduces a method for conducting experimental hardware-in-the-loop (xHIL), in which behavioral-level models are coupled with an advanced power emulator (APE) to emulate an electrical load on a power generation system. The emulator is commanded by behavioral-level models running on an advanced real-time simulator that has the capability to leverage Central Processing Units (CPUs) and field programmable gate arrays (FPGA) to meet strict real-time execution requirements. The paper will be broken down into four topics: 1) the development of a solution to target behavioral-level models to an advanced, real-time simulation device, 2) the development of a high-bandwidth, high-power emulation capability, 3) the integration of the real-time simulation device and the APE, and 4) the application of the emulation system (simulator and emulator) in an xHIL experiment.

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.

Of all aircraft power and thermal loads, flight controls can be the most challenging to quantify because they are highly variable. Unlike constant or impulsive loads, actuator power demands more closely resemble random processes. Some inherent nonlinearities complicate this even further. Actuation power consumption and waste heat generation are both sensitive to input history. But control activity varies considerably with mission segment, turbulence and vehicle state. Flight control is a major power consumer at times, so quantifying power demand and waste heat is important for sizing power and thermal management system components. However, many designers sidestep the stochastic aspects of the problem initially, leading to overly conservative system sizing. The overdesign becomes apparent only after detailed flight simulations become available. These considerations are particularly relevant in trade studies comparing electric versus hydraulic actuation.

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.

Movement toward more-electric architectures in military and commercial airborne systems has led to electrical power systems (EPSs) with complex power flow dynamics and advanced technologies specifically designed to improve power quality in the system. As such, there is a need for tools that can quickly analyze the impact of technology insertion on the system-level dynamic transient and spectral power quality and assess tradeoffs between impact on power quality versus weight and volume. Traditionally, this type of system level analysis is performed through computationally intensive time-domain simulations involving high fidelity models or left until the hardware fabrication and integration stage. In order to provide a more rapid analysis prior to hardware development and integration, stochastic equivalent circuit analysis is developed that can provide power quality assessment directly in the frequency domain.

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.

An IPTMS hardware facility has been established in the laboratories of the Aerospace Systems Directorate of the Air Force Research Laboratory (AFRL) at Wright-Paterson Air Force Base (WPAFB). This hardware capability was established to analyze the transient behavior of a high power Electrical Power System (EPS) coupled virtually to a Thermal Management System (TMS) under fast dynamic loading conditions. The system incorporates the use of dynamic electrical load, engine emulation, energy storage, and emulated thermal loads operated to investigate dynamics under step load conditions. Hardware architecture and control options for the IPTMS are discussed. This paper summarizes the IPTMS laboratory demonstration system, its capabilities, and preliminary test results.