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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.

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.

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.

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.

In this paper, a recently-developed algorithmic method of deriving the state equations of power systems containing power electronic components is described. Therein the system is described by the pertinent branch parameters and the circuit topology; however, unlike circuit-based algorithms, the difference equations are not implemented at the branch level. Instead, the composite system state equations are established. A demonstration of the computer implementation of this algorithm to model a variable-speed, constant-frequency aircraft generation system is described. Because of the large number of states and complexity of the system, particular attention is placed on the development of a model structure which provides optimal simulation efficiency.

The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.

This paper presents hydraulic topographies using a network of valves to achieve better energy efficiency, reliability, and performance. The Topography with Integrated Energy Recovery (TIER) system allows the valves and actuators to reconfigure so that flow from assistive loads on actuators can be used to move actuators with resistive loads. Many variations are possible, including using multiple valves with either a single pump/motor or with multiple pump/motors. When multiple pump/motors are used, units of different displacements can be chosen such that units are controlled to minimize time operating at low displacement, thus increasing overall system efficiency. Other variations include configurations allowing open loop or closed loop pump/motors to be used, the use of fixed displacement pump/motors, or the ability to store energy in an accumulator. This paper gives a system level overview and summarizes the hydraulic systems using the TIER approach.

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.

A mathematical model of a gas-charged mono-tube racing damper is presented. The model includes bleed orifice, piston leakage, and shim stack flows. It also includes models of the floating piston and the stiffness characteristics of the shim stacks. The model is validated with experimental tests on an Ohlins WCJ 22/6 damper and shown to be accurate. The model is exercised to show the effects of tuning on damper performance. The important results of the exercise are 1) the pressure variation on the compression side of the piston is insignificant relative to that on the rebound side because of the gas charge, 2) valve shim stiffness can be successfully modeled using stacked thin circular plates, 3) bleed orifice settings dominate the low speed regime, and 4) shim stack stiffness dominates the high speed regime.

Today, there are several hundreds of manufacturing processes available to the designer to choose from, and the number is constantly increasing. The ability to choose a manufacturing process for a particular user need set in the early stage of the design process is necessary. In metalcasting alone, there are over forty different processes with different capabilities. A designer can benefit from knowing the manufacturing process alternatives available to him. Inaccurate process selection can lead to financial losses and market share erosion. This paper discusses a methodology for selection of a metalcasting process based on a number of user specified attributes or requirements. A model of user requirements was developed and these requirements were matched with the capabilities of each metalcasting process. The metalcasting process which best meets these needs is suggested.

This work proposes a new method to design crashworthiness structures that made of functionally graded cellular (porous) material. The proposed method consists of three stages: The first stage is to generate a conceptual design using a topology optimization algorithm so that a variable density is distributed within the structure minimizing its compliance. The second stage is to cluster the variable density using a machine-learning algorithm to reduce the dimension of the design space. The third stage is to maximize structural crashworthiness indicators (e.g., internal energy absorption) and minimize mass using a metamodel-based multi-objective genetic algorithm. The final structure is synthesized by optimally selecting cellular material phases from a predefined material library. In this work, the Hashin-Shtrikman bounds are derived for the two-phase cellular material, and the structure performances are compared to the optimized structures derived by our proposed framework.

This work presents the implementation of the Efficient Global Optimization (EGO) approach for the design of composite materials under dynamic loading conditions. The optimization algorithm is based on design and analysis of computer experiments (DACE) in which smart sampling and continuous metamodel enhancement drive the design towards a global optimum. An expected improvement function is maximized during each iteration to locate the designs that update the metamodel until convergence. The algorithm solves single and multi-objective optimization problems. In the first case, the penetration of an armor plate is minimized by finding the optimal fiber orientations. Multi-objective formulation is used to minimize the intrusion and impact acceleration of a composite tube. The design variables include the fiber orientations and the size of zones that control the tube collapse.

The On-line Project Information System (OPIS) is a LAMP-based (Linux, Apache, MySQL, PHP) system being developed at NASA Ames Research Center to improve Agency information transfer and data availability, largely for improvement of system analysis and engineering. The tool will enable users to investigate NASA technology development efforts, connect with experts, and access technology development data. OPIS is currently being developed for NASA's Exploration Life Support (ELS) Project. Within OPIS, NASA ELS Managers assign projects to Principal Investigators (PI), track responsible individuals and institutions, and designate reporting assignments. Each PI populates a “Project Page” with a project overview, team member information, files, citations, and images. PI's may also delegate on-line report viewing and editing privileges to specific team members. Users can browse or search for project and member information.

EcoCAR 2: Plugging In to the Future (EcoCAR) is North America's premier collegiate automotive engineering competition, challenging students with systems-level advanced powertrain design and integration. The three-year Advanced Vehicle Technology Competition (AVTC) series is organized by Argonne National Laboratory, headline sponsored by the U. S. Department of Energy (DOE) and General Motors (GM), and sponsored by more than 28 industry and government leaders. Fifteen university teams from across North America are challenged to reduce the environmental impact of a 2013 Chevrolet Malibu by redesigning the vehicle powertrain without compromising performance, safety, or consumer acceptability. During the three-year program, EcoCAR teams follow a real-world Vehicle Development Process (VDP) modeled after GM's own VDP. The VDP serves as a roadmap for the engineering process of designing, building and refining advanced technology vehicles.

Resource recovery, including that of urine water extraction, is one of the most crucial aspects of long-term life support in interplanetary space travel. This paper will consequently examine an innovative approach to processing raw, undiluted urine based on low-temperature freezing. This strategy is uniquely different from NASA's current emphasis on either ‘integrated’ (co-treatment of mixed urine, grey, and condensate waters) or ‘high-temperature’ (i.e., VCD [vapor compression distillation] or VPCAR [vapor phase catalytic ammonia removal]) processing strategies, whereby this liquid freeze-thaw (LiFT) procedure would avoid both chemical and microbial cross-contamination concerns while at the same time securing highly desirable reductions in likely ESM levels.

The application of biological treatment to solid waste is very promising to facilitate recycling of water, carbon, and nutrients and to reduce the resupply needs of long-term crewed space missions. Degradation of biodegradable solid wastes generated during such a mission is under investigation as part of the NASA Center of Research and Training (NSCORT) at Purdue University. Processing in the solids thermophilic aerobic reactor (STAR) involves the use of high temperature micro-aerobic slurry conditions to degrade solid wastes, enabling the recycling of water, carbon, and nutrients for further downstream uses. Related research presently underway includes technical development and optimization of STAR operations as well as a complementary evaluation of post-STAR processing for gas-stream purification, water recovery by condensate purification, and residuals utilization for both mushroom growth media and nutritional support for fish growth.

Solids thermophilic aerobic reactor (STAR) processing of biodegradable solid waste residuals uses high temperature conditions to reduce waste volume, inactivate pathogens, and render products that may enter the recycle system by providing plant substrate, fish food, and mushroom growth medium. The STAR process recovers and enables the reuse of nutrients, water, and carbon. During the time of this study, STAR was operated at a 3% solids loading rate, with an 11-day retention time at a temperature range of 50-55°C. This document presents the following details: a the evolution to date of the STAR reactor b review of reactor operation and analytical methods c a synopsis of the performance results and related discussion, and d a synopsis of future goals relative to this project's associated research roadmap.

The effectiveness of ultraviolet (UV) disinfection is governed by the UV dose to which microorganisms are exposed. In treatment operations, all UV disinfection systems deliver a distribution of UV doses. The ability to accurately estimate the dose distribution delivered by an operating UV system is a critical aspect of its design. Moreover, the availability of tools to accurately predict the dose distribution for an existing UV system makes it possible to develop reliable, quantitative predictions of process performance in these systems. The dose distribution can be estimated by employing computational fluid dynamics (CFD) and UV radiation intensity field modeling. UV dose-distribution data is then coupled with UV dose-response behavior for target microorganisms to yield an estimate of process performance.

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.

“Truck Ride” in this study refers to some vehicle ride parameters involved in tractor-trailer combinations. For the study, a mathematical model of a tractor-trailer vehicle as a vibrating system was developed. Principles of vibration theory were applied to the model while a digital computer was employed to investigate the complex system. To parallel the analytical investigation of the tractor-trailer vehicle, vehicle studies were conducted using a magnetic tape recorder and associated instrumentation installed in the tractor. Parameters studied included coupler position on the tractor, laden weight of trailer, spring rates of the different axles of the combination, damping capacity associated with each spring rate, vehicle speed, and “tar strip” spacing of the highway and cab mountings. The mathematical results were used as a basis for empirical study. A comparison of calculated and empirical data are reported.