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Near-Field Acoustical Holography (NAH) is an inverse process in which sound pressure measurements made in the near-field of an unknown sound source are used to reconstruct the sound field so that source distributions can be clearly identified. NAH was originally based on performing spatial transforms of arrays of measured pressures and then processing the data in the wavenumber domain, a procedure that entailed the use of very large microphone arrays to avoid spatial truncation effects. Over the last twenty years, a number of different NAH methods have been proposed that can reduce or avoid spatial truncation issues: for example, Statistically Optimized Near-Field Acoustical Holography (SONAH), various Equivalent Source Methods (ESM), etc.

Due the increasing concern with the acoustic environment within automotive vehicles, there is an interest in measuring the acoustical properties of automotive door seals. These systems play an important role in blocking external noise sources, such as aerodynamic noise and tire noise, from entering the passenger compartment. Thus, it is important to be able to conveniently measure their acoustic performance. Previous methods of measuring the ability of seals to block sound required the use of either a reverberation chamber, or a wind tunnel with a special purpose chamber attached to it. That is, these methods required the use of large and expensive facilities. A simpler and more economical desktop procedure is thus needed to allow easy and fast acoustic measurement of automotive door seals.

Pumped two-phase systems using mini or microchannel heat sink evaporators are prime candidates for high heat flux applications due to relatively low pumping power requirements and efficient heat removal in compact designs. A number of challenges exist in the implementation of these systems including: ensuring subcooled liquid to the pump to avoid cavitation, avoiding dry out conditions in heat exchangers that can lead to failures of the components under cooling, and avoiding flow instabilities that can damage components in an integrated system. To reduce risk and cost, modeling and simulation can be employed in the design and development of these complex systems, but such modeling must include the relevant behavior necessary to capture the above dynamic effects.

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.

Bioregenerative systems for removal of gaseous contaminants are desired for long-term space missions to reduce the equivalent system mass of the air cleaning system. This paper describes an innovative design of a new biofiltration test lab for investigating the capability of biofiltration process for removal of ersatz multi-component gaseous streams representative of spacecraft contaminants released during long-term space travel. The lab setup allows a total of 24 bioreactors to receive identical inlet waste streams at stable contaminant concentrations via use of permeations ovens, needle valves, precision orifices, etc. A unique set of hardware including a Fourier Transform Infrared (FTIR) spectrometer, and a data acquisition and control system using LabVIEW™ software allows automatic, continuous, and real-time gas monitoring and data collection for the 24 bioreactors. This lab setup allows powerful factorial experimental design.

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.

Gas engines often utilize a small-volume pre-chamber in which fuel is injected at near stoichiometric condition to produce a hot turbulent jet which then ignites the lean mixture in the main chamber. Hot jet ignition has several advantages over traditional spark ignition, e.g., more reliable ignition of extra-lean mixtures and more surface area for ignition resulting in faster burning and improved combustion burn time. Our previous experimental results show that supersonic jets could extend the lean flammability limit of fuel/air mixtures in the main chamber in comparison to subsonic jets. The present paper investigated the characteristics of supersonic hot jets generated by combustion of stoichiometric H2/air in a pre-chamber to understand the ignition mechanism of ultra-lean mixtures by supersonic hot jets.

An experimental-analytic method of determining the stress distribution in narrow faced spur gear teeth is presented. The successful application of photostress to this contact problem is reported. It utilizes a digital computer routine developed for separating stresses in any general two-dimensional region. Results for two pairs of gears are presented. Comparison is made with values predicted by the modified Lewis formula, the Kelley and Pedersen equation, and by the Belajef solution of the Hertz contact problem for two cylinders.

This paper reviews some applications of lattice Boltzmann methods (LBM) to compute multiphase flows. The method is based on the solution of a kinetic equation which describes the evolution of the distribution of the population of particles whose collective behavior reproduces fluid behavior. The distribution is modified by particle streaming and collisions on a lattice. Modeling of physics at a mesoscopic level enables LBM to naturally incorporate physical properties needed to compute complex flows. In multiphase flows, the surface tension and phase segregation are incorporated by considering intermolecular attraction forces. Furthermore, the solution of the kinetic equations representing linear advection and collision, in which non-linearity is lumped locally, makes it parallelizable with relative ease. In this paper, a brief review of the lattice Boltzmann method relevant to engine sprays will be presented.

This paper describes a simulation approach for the modeling of tandem external gear pumps. A tandem gear pump is the combination of two pumps with a common drive shaft. Such design architecture finds application in certain automotive transmission systems. The model presented in this work is applicable for pumps with both helical and spur gears. The simulation model is built on the HYGESim (HYdraulic GEars machines Simulator) previously developed by the authors for external spur gear units. In this work, the model formulation is properly extended to the capabilities of simulating helical gears. Starting directly from the CAD drawings of the unit, the fluid-dynamic model solves the internal instantaneous tooth space volume pressures and the internal flows following a lumped parameter approach. The simulation tool considers also the radial micro-motion of the gears, which influences the internal leakages and the features of the meshing process.

This work contributes to the overall goal of identifying and reducing noise sources and propagation in hydraulic systems. This is a general problem and a primary design concern for all fluid power applications. The need for new methods for identification of noise sources and transmission is evident in order to direct future modeling and experimental efforts aimed at reducing noise emissions of current fluid power machines. In this paper, this goal is accomplished through the formulation of noise functions used to identify contributions and transfer paths from different components of the system. An experimental method for noise transfer path analysis was developed and tested on a simple hydraulic system composed of a reference external gear pump, attached lines, and loading valve. Pressure oscillations in the working fluid are measured at the outlet of the pump. Surface vibrations are measured at multiple locations on the pump and connected system.

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.

Early experience with precision farming technology suggests that some hardware and software may follow a rapid S curve adoption path, but that the use of integrated precision farming systems may take longer to develop and be subject to false starts and periods of stagnation. Yield monitors appear to be following a classic S curve adoption path. Precision farming adoption is like that of hybrid corn because changes in organizations will be required to use it effectively. It is like motorized mechanization because it is coming on the market in an immature form and lends itself to farmer tinkering.

In this paper, an aggregate system level modeling and analysis framework is proposed to facilitate the integration and design of advanced life support systems (ALSS). As in process design, the goal is to choose values for the degrees of freedom that achieve the best overall ALSS behavior without violating any system constraints. At the most fundamental level, this effort will identify the constraints and degrees of freedom associated with each subsystem and provide estimates of the system behavior and interactions involved in ALSS. This work is intended to be a starting point for developing insights into ALSS from a systems engineering point of view. At this level, simple aggregate static input/output mapping subsystem models from existing data and the NASA ALS BVAD document are used to debug the model and demonstrate feasibility.

Spherical beamforming was used to visualize sound radiation during a vehicle passby test. Forward and backward propagation procedures are compared in terms of computational expense. A spherical spreading correction factor is described, along with a maximum liklihood procedure for obtaining an optimal array weighting dependent on the relative distance between the microphones and the focus point. The de-Dopplerized microphone outputs are multiplied by the weighting factors and summed to yield the source strengths over a reconstruction plane “attached” to the vehicle. Results obtained using a 16 element sparse array during an actual passby are used to demonstrate the present approach.

Electric machinery is typically based upon the interaction of magnetic fields and current to produce electromagnetic force or torque. However, force and torque can also be produced through the use of electric fields. The purpose of this investigation is to briefly analyze the use of a switched capacitance electric field based machine to see if it may have aerospace applications for use as either propulsion motor for unmanned aerospace vehicle (UAV) or lightweight flywheel applications for aerospace applications. It is shown that although its use as a hub propulsion motor is not feasible, it may be a candidate for use in a power flywheel energy storage system.

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.

The basic idea behind large-eddy simulation (LES) is to accurately resolve the large energy-containing scales and to use subgrid-scale (SGS) models for the smaller scales. The accuracy of LES can be significantly impacted by the numerical discretization schemes and the choice of the SGS model. This work investigates the accuracy of low-order LES codes in the simulation of a turbulent round jet which is representative of fuel jets in engines. The turbulent jet studied is isothermal with a Reynolds number of 6800. It is simulated using Converge, which is second-order accurate in space and first-order in time, and FLEDS, developed at Purdue University, which is sixth-order accurate in space and fourth-order in time. The high-order code requires the resolution of acoustic time-scales and hence is approximately 10 times more expensive than the low-order code.

There has always been, from the very first UAV, a need for providing cost-effective methods of deploying unmanned aircraft systems at high altitudes. Missions for UAVs at high altitudes are used to conduct atmospheric research, perform global mapping missions, collect remote sensing data, and establish long range communications networks. The team of Gevers Aircraft, Technology Management Group, and Purdue University have designed an innovative balloon launched UAV for these near space applications. A UAV (Payload Return Vehicle) with a nested morphing wing was designed in order to meet the challenges of high altitude flight, and long range and endurance without the need for descent rate control with rockets or a feathering mode.

The design of better active materials for lithium-ion batteries (LIBs) is crucial to satisfy the increasing demand of high performance batteries for portable electronics and electric vehicles. Currently, the development of new active materials is driven by physical experimentation and the designer’s intuition and expertise. During the development process, the designer interprets the experimental data to decide the next composition of the active material to be tested. After several trial-and-error iterations of data analysis and testing, promising active materials are discovered but after long development times (months or even years) and the evaluation of a large number of experiments. Bayesian global optimization (BGO) is an appealing alternative for the design of active materials for LIBs. BGO is a gradient-free optimization methodology to solve design problems that involve expensive black-box functions. An example of a black-box function is the prediction of the cycle life of LIBs.