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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.

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.

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.

Layered materials are one of the most commonly used acoustical treatments in the automotive industry, and have gained increased attention, especially owing to the popularity of electric vehicles. Here, a method to model and couple layered systems with various layer types (i.e., poro-elastic layers, solid-elastic layers, stiff panels, and fluid layers) is derived that makes it possible to stably predict their acoustical properties. In contrast with most existing methods, in which an equation system is constructed for the whole structure, the present method involves only the topmost layer and its boundary conditions at two interfaces at a time, which are further simplified into an equivalent interface. As a result, for a multi-layered system, the proposed method splits a complicated system into several smaller systems and so becomes computationally less expensive.

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.

The optimal design of hybrid-electric vehicle power systems poses a challenge to the system analyst, who is presented with a host of parameters to fine-tune, along with stringent performance criteria and multiple design objectives to meet. Herein, a methodology is presented to transform such a design task into a constrained multi-objective optimization problem, which is solved using a distributed evolutionary algorithm. A power system model representative of a series hybrid-electric vehicle is considered as a paradigm to support the illustration of the proposed methodology, with particular emphasis on the power system's time-domain performance.

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.

The negative consequences of unsafe behaviors on the job heavily contribute to the rising costs of doing business in terms of both organization dollars and diminished human quality of life. Developing a safety culture provides a positive proactive approach toward creating a working environment where safety is a top priority. An integral part of accomplishing this task is directly related to training individuals on how the interactions that occur among organizational members and the messages their behaviors send influence others' behaviors. This can be best addressed through communication skill development initiatives including mutual responsibility, trust, avoiding punitive strategies and facilitating assertiveness.

As part of the NASA Specialized Center of Research and Training for Advanced Life Support (NSCORT-ALS) at Purdue University, a complementary disinfection process, which uses ultraviolet (UV) radiation as the primary disinfectant and iodine as the secondary, residual disinfectant, is being developed. UV radiation was selected as the primary disinfectant because it is effective at inactivating a broad spectrum of microorganisms and has minimal potential for the formation of disinfection byproducts. Iodine, which is effective at inactivating many microorganisms and is less likely to react and form disinfection byproducts than other halogens, was selected as the residual disinfectant because it has the potential for dual use as an on-line UV monitor, as well as a disinfectant.

Recognizing that technicians and managers need additional skills in order to compete for and successfully fill management positions, a major air carrier requested that Purdue University perform a study with employees in order to identify specific skills that are required to perform successfully in leadership positions. The study identified three core competencies (leadership, communication, and management processes) needed to be a successful leader in a major air carrier environment and outlined several related knowledge and skills within each area. Currently, many individuals in front line and mid-level management are lacking in several of these knowledge bases and skill sets. Consequently, the value of addressing current deficiencies through educational and experiential learning opportunities was proposed.

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.

The Purdue University EcoMakers team has completed its first year of the EcoCAR 2 Competition, in which the team has designed a Parallel-Through-the-Road Plug-in Hybrid Electric Vehicle that meets the performance requirements of a mid-size sedan for the US market, maintaining capability, utility and consumer satisfaction while minimizing emissions, energy consumption and petroleum use. The team is utilizing a 1.7L 14 CI engine utilizing B20 (20% biodiesel, 80% diesel), a 16.2 kW-hr A123 battery pack, and a Magna E-Drive motor to power the front and rear wheels. This will allow the vehicle to have a charge-depleting range of 75 miles. The first year was focused on the simulation of the vehicle, in which the team completed the controls, packaging and integration, and electrical plans for the vehicle to be used and implemented in years two and three of the competition.

Due to the instabilities that may occur in power systems with regulated loads such as those used in military aircraft, ships, and terrestrial vehicles, many analysis techniques and design methodologies have been developed to ensure stable operation for expected operating conditions. However, many of these techniques are difficult to apply to complex systems and do not guarantee large-displacement stability following major disturbances such as faults, regenerative operation, large pulsed loads, and/or the loss of generating capacity. In this paper, a design paradigm is set forth guaranteeing large-displacement stability of a power system containing a significant penetration of regulated (constant-power) loads for any value of load power up to and including the steady-state rating of the source. Initial investigations are performed using an idealized model of a dc-source to determine the minimum requirements that ensure large-displacement stability.

The Indiana Space Grant Consortium is one of 52 members of the National Space Grant College and Fellowship Program (“Space Grant”), which was initiated by NASA in 1988. Space Grant is designed to be a source of NASA-related information, awards, and programs to enhance education, outreach, and workforce development for the United States. Based on the land grant model of public university education, Space Grant seeks to spread the vision of NASA to increase science, technology, engineering, and math (STEM) awareness; NASA-related education; workforce development; outreach and research activities. This paper describes the evolution of these activities in Indiana.

Hybrid powertrains with multiple sources of power have generated new control challenges in the automotive industry. Purdue University's participation in EcoCAR 2, an Advanced Vehicle Technology Competition managed by the Argonne National Laboratories and sponsored by GM and DOE, has provided an exciting opportunity to create a comprehensive test-bench for the development and validation of advanced hybrid powertrain control strategies. As one of 15 competing university teams, the Purdue EcoMakers are re-engineering a donated 2013 Chevrolet Malibu into a plug-in parallel- through-the-road hybrid-electric vehicle, to reduce its environmental impact without compromising performance, safety or consumer acceptability. This paper describes the Purdue team's control development process for the EcoCAR 2 competition.

The NASA Specialized Center of Research and Training in Advanced Life Support (ALS/NSCORT) Education and Outreach Program is designed to engage audiences through concepts and technologies highlighted in the NSCORT research program. The outreach program is composed of three thrust areas. These areas are technical outreach (graduate education, technology transfer, presentations to industry, etc.), educational outreach (professional development, undergraduate, K-12), and public outreach (museums, state fairs, etc.) Program design of the technical and educational outreach began in January 2003. This paper reports anecdotal data on one ALS/NSCORT outreach program and gives a brief description of the other programs in their pilot stages. Technical and educational outreach programs developed to date include: 1) Summer Fellowship Research Program, 2) Distance Learning Course, 3) Key Learning Community Collaborative Project and 4) Mission to Mars.

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization.

Shell-and-tube heat exchangers, commonly referred to as radiators, are the most prevalent type of heat exchanger within the automotive industry. A pivotal goal for automotive designers is to increase their thermal effectiveness while mitigating pressure drop effects and minimizing the associated costs of design and operation. Their design is a lengthy and intricate process involving the manual creation and refinement of computer-aided design (CAD) models coupled with iterative multi-physics simulations. Consequently, there is a pressing demand for an integrated tool that can automate these discrete steps, yielding a significant enhancement in overall design efficiency. This work aims to introduce an innovative automation tool to streamline the design process, spanning from CAD model generation to identifying optimal design configurations. The proposed methodology is applied explicitly to the context of shell-and-tube heat exchangers, showcasing the tool's efficacy.

Current gasoline-gas vapor recovery system is incomplete, for it cannot adjust the vapor-liquid ratio automatically due to the change of working temperature. To solve this problem, this paper intends to design a new system and optimize its parameters. In this research, variables control method is used for tests while linear regression is used for data processing. This new system moves proportion valve away and adds a DSP control module, a frequency conversion device, and a temperature sensor. With this research, it is clearly reviewed that the vapor-liquid ratio should remains 1.0 from 0 °C to 20 °C as its working temperature, be changed into 1.1 from 20 °C to 25 °C, be changed into 1.2 from 25 °C to 30 °C, and be changed into 1.3 when the working temperature is above 30 °C.