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All around the world, steps are being taken to improve the quality of our environment. Prominent among these are the definition, implementation, and attainment of increasingly stringent emissions regulations for all types of engines, including off-highway diesels. These rigorous regulations have driven use of technologies like after-treatment, advanced air systems, and advanced fuel systems. Fuel dispensed off-highway is routinely and significantly dirtier than fuel from on-highway outlets. Furthermore, fuels used in developing countries can be up to 30 times dirtier than the average fuels in North America. Poor fuel cleanliness, coupled with the higher pressures and performance demands of modern fuel systems, create life challenges greater than encountered with cleaner fuels. This can result in costly disruption of operations, loss of productivity, and customer dissatisfaction in the off-highway market.

Fuel cell vehicles are currently undergoing extensive research and development because of their potential for high efficiency and low emissions. A complete well-to-wheels evaluation is helpful when considering the introduction of advanced vehicles that could use a new fuel, such as hydrogen. Several modeling tools developed by Argonne National Laboratory were used to evaluate the impact of several new vehicle configurations. A transient vehicle simulation software code, PSAT (Powertrain System Analysis Toolkit), was used with a transient fuel cell model derived from GCTool (General Computational Toolkit); and GREET (Greenhouse gases, Regulated Emissions and Energy use in Transportation) was employed in estimating well-to-tank performances. This paper compares the well-to-wheels impacts of several advanced SUVs, including conventional, parallel and series hybrid-electric and fuel cell vehicles.

This paper covers the development of computer simulation models of the Vapor Compression Distillation (VCD) process, the Super Critical Water Oxidation (SCWO) process, and two versions of a Vapor Phase Catalytic Ammonia Reduction (VPCAR) process. These process level models have combined into two Integrated Water Reclamation Systems (IWRS). Results from these integrated models, in conjunction with other data sources, have been used to develop a preliminary comparison of the two systems. Also discussed in this paper is the development of a Vapor Phase Catalytic Ammonia Reduction teststand and the development of a new urine analog for use with the teststand and computer models.

Since the mid 1980s, NASA has developed advanced waste management technologies that collect and process waste. These technologies include incineration, hydrothermal oxidation, pyrolysis, electrochemical oxidation, activated carbon production, brine dewatering, slurry bioreactor oxidation, composting, NOx control, compaction, and waste collection. Some of these technologies recover resources such as water, oxygen, nitrogen, carbon dioxide, carbon, fuels, and nutrients. Other technologies such as the Waste Collection System (WCS - the commode) collect waste for storage or processing. The need for waste processing varies greatly depending upon the mission scenario. This paper reviews the waste management technology development activities conducted by NASA since the mid 1980s and explores the drivers that determine the application of these technologies to future missions.

Waste management is a critical component of life support systems for manned space exploration. Human occupied spacecraft and extraterrestrial habitats must be able to effectively manage the waste generated throughout the entire mission duration. The requirements for waste systems may vary according to specific mission scenarios but all waste management operations must allow for the effective collection, containment, processing, and storage of unwanted materials. NASA's Crew Exploration Vehicle usually referred to as the CEV, will have limited volume for equipment and crew. Technologies that reduce waste storage volume free up valuable space for other equipment. Waste storage volume is a major driver for the Orion waste compactor design. Current efforts at NASA Ames Research Center involve the development of two different prototype compactors designed to minimize trash storage space.

The National Highway Traffic Safety Administration (NHTSA) plays a crucial role in guiding the formulation of Corporate Average Fuel Economy (CAFE) standards, and at the forefront of this regulatory process stands Argonne National Laboratory (Argonne). Argonne, a U.S. Department of Energy (DOE) research institution, has developed Autonomie—an advanced and comprehensive full-vehicle simulation tool that has solidified its status as an industry standard for evaluating vehicle performance, energy consumption, and the effectiveness of various technologies. Under the purview of an Inter-Agency Agreement (IAA), the DOE Argonne Site Office (ASO) and Argonne have assumed the responsibility of conducting full-vehicle simulations to support NHTSA's CAFE rulemaking initiatives. This paper introduces an innovative approach that hinges on a large-scale simulation process, encompassing standard regulatory driving cycles tailored to various vehicle classes and spanning diverse timeframes.

Wireless Power Transfer (WPT) promises automated and highly efficient charging of electric and plug-in-hybrid vehicles. As commercial development proceeds forward, the technical challenges of efficiency, interoperability, interference and safety are a primary focus for this industry. The SAE Vehicle Wireless Power and Alignment Taskforce published the Recommended Practice J2954 to help harmonize the first phase of high-power WPT technology development. SAE J2954 uses a performance-based approach to standardizing WPT by specifying ground and vehicle assembly coils to be used in a test stand (per Z-class) to validate performance, interoperability and safety. The main goal of this SAE J2954 bench testing campaign was to prove interoperability between WPT systems utilizing different coil magnetic topologies. This type of testing had not been done before on such a scale with real automaker and supplier systems.

Connectivity and automation provide the potential to use information about the environment and future driving to minimize energy consumption. Aerodynamic drag can also be reduced by close-gap platooning using information from vehicle-to-vehicle communications. In order to achieve these goals, the designers of control strategies need to simulate a wide range of driving situations in which vehicles interact with other vehicles and the infrastructure in a closed-loop fashion. RoadRunner is a new model-based system engineering platform based on Autonomie software, which can collectively provide the necessary tools to predict energy consumption for various driving decisions and scenarios such as car-following, free-flow, or eco-approach driving, and thereby can help in developing control algorithms.

Remotely operating complex robotic mechanisms in unstructured natural environments is difficult at best. When the communications time delay is large, as for a Mars exploration rover operated from Earth, the difficulties become enormous. Conventional approaches, such as rate control of the rover actuators, are too inefficient and risky. The Intelligent Mechanisms Laboratory at the NASA Ames Research Center has developed over the past four years an architecture for operating science exploration robots in the presence of large communications time delays. The operator interface of this system is called the Virtual Environment Vehicle Interface (VEVI), and draws heavily on Virtual Environment (or Virtual Reality) technology. This paper describes the current operational version of VEVI, which we refer to as version 2.0. In this paper we will describe the VEVI design philosophy and implementation, and will describe some past examples of its use in field science exploration missions.

The development of virtual environment technology at NASA Ames Research Center and other research institutions has created opportunities for enhancing human performance. The application of this technology to training astronaut flight crews planning to go onboard the International Space Station has already begun at the NASA Johnson Space Center. A unique application of virtual environments to crew training is envisioned at NASA Ames Research Center which combines state of the art technology with haptic feedback to create a method for training crewmembers on critical life sciences operations which require fine motor skills. This paper describes such a concept, known as the Virtual Glovebox, as well as surveys other applications of virtual environments to astronaut crew training.

Other than in Japan, medium and heavy duty vehicles (MHDVs) are not regulated despite accounting for a significant portion of the fuel consumed (about 26% in the US in 2008). Government agencies worldwide are currently evaluating options to address that issue. Due to the large number of vehicle applications, some of them being “one of a kind”, vehicle modelling and simulation offers an attractive solution to medium and heavy duty regulations. This paper discusses the advantages and challenges of vehicle simulation to support regulations.

The successful commercialization of Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) can provide significant benefits by reducing the United States' growing dependence on petroleum fuels for transportation; decreasing polluting and greenhouse gas emissions; and facilitating a long-term transition to sustainable renewable energy sources. Recognizing these benefits, the U.S. Department of Energy (DOE) supports an active program of long-range R&D to develop electric vehicle (EV) and hybrid electric vehicle (HEV) technologies and to accelerate their commercialization. The DOE Office of Advanced Automotive Technologies (OAAT) supports several innovative R&D programs, conducted in partnership with DOE's national laboratories, industry, other government agencies, universities, and small businesses. The Office has two key R&D cooperative agreements with the U.S. Advanced Battery Consortium (USABC) to develop high-energy batteries for EVs and high-power batteries for HEVs.

Over the past couple of years, Argonne National Laboratory has tested, analyzed, and validated automobile models for the light duty vehicle class, including several types of powertrains including conventional, hybrid electric, plug-in hybrid electric and battery electric vehicles. Argonne’s previous works focused on the light duty vehicle models, but no work has been done on medium and heavy-duty vehicles. This study focuses on the validation of shifting control in advanced automatic transmission technologies for medium duty vehicles by using Argonne’s model-based high-fidelity, forward-looking, vehicle simulation tool, Autonomie. Different medium duty vehicles, from Argonne’s own fleet, including the Ram 2500, Ford F-250 and Ford F-350, were tested with the equipment for OBD (on-board diagnostics) signal data record. For the medium duty vehicles, a workflow process was used to import test data.

Aviation training has remained largely untouched by decades of development in cognitive science. In aviation, people must be trained to perform complicated tasks and make good operational decisions in complex dynamic environments. However, traditional approaches to professional aviation training are not well designed to accomplish this goal. Aviation training has been based mainly on relatively rigid classroom teaching of factual information followed by on-the-job mentoring. This approach tends to compartmentalize knowledge. It is not optimal for teaching operational decision-making, and it is costly in time and personnel. The effectiveness of training can be enhanced by designing programs that support the psychological processes involved in learning, retention, retrieval, and application. By building programs that are informed by current work in cognitive science and that utilize modern technological advances, efficient training programs can be created.

A comparison of resource cost was made between processed peanut oil and a bulk supply of peanut oil within a reference menu using nominal yield values from literature and equivalency factors from the Exploration Life Support (ELS) Baseline Values and Assumptions Document (BVAD). Results of the comparison show a potential mass savings of up to 496.3 kg if a bulk supply of oil were to replace processed peanut oil within identified recipes. Direct comparison of processed peanut oil and bulk oil commodities shows the cost-to-launch value for processed peanut oil will be 3.2 times greater than a bulk supply. This replacement would also remove 164.4 kg of solid waste generated through peanut processing. These values and the general versatility of a bulk supply of oil indicate that recipes under the bulk commodity supply scenario should use a variety of oils.

NASA's plans to implement the Vision for Space Exploration include extensive human-robot cooperation across an enterprise spanning multiple missions, systems, and decades. To make this practical, strong enterprise-level interface standards (data, power, communication, interaction, autonomy, and physical) will be required early in the systems and technology development cycle. Such standards should affect both the engineer and operator roles that humans adopt in their interactions with robots. For the engineer role, standards will result in reduced development lead-times, lower cost, and greater efficiency in deploying such systems. For the operator role, standards will result in common autonomy and interaction modes that reduce operator training, minimize workload, and apply to many different robotic platforms. Reduced quantities of spare hardware could also be a benefit of standardization.

The blade crossing event of a coaxial counter-rotating rotor is a potential source of noise and impulsive blade loads. Blade crossings occur many times during each rotor revolution. In previous research by the authors, this phenomenon was analyzed by simulating two airfoils passing each other at specified speeds and vertical separation distances, using the compressible Navier-Stokes solver OVERFLOW. The simulations explored mutual aerodynamic interactions associated with thickness, circulation, and compressibility effects. Results revealed the complex nature of the aerodynamic impulses generated by upper/lower airfoil interactions. In this paper, the coaxial rotor system is simulated using two trains of airfoils, vertically offset, and traveling in opposite directions. The simulation represents multiple blade crossings in a rotor revolution by specifying horizontal distances between each airfoil in the train based on the circumferential distance between blade tips.

Using synchrotron x-radiography and mass deconvolution techniques, this work reveals strikingly interesting structural and dynamic characteristics of the direct injection (DI) gasoline hollow-cone sprays in the near-nozzle region. Employed to measure the sprays, x-radiography allows quantitative determination of the fuel distribution in this optically impenetrable region with a time resolution of better than 1 μs, revealing the most detailed near-nozzle mass distribution of a DI gasoline fuel spray ever detected. Based on the x-radiographs of the spray collected from four different perspectives, enhanced mathematical and numerical analyses were developed to deconvolute the mass density of the gasoline hollow-cone spray. This leads to efficient and accurate regression curve fitting of the measured experimental data to obtain essential parameters of the density distribution that are then used in reconstructing the cross-sectional density distribution at various times and locations.

Most previous measurements of diesel sprays have yielded few details regarding the near-nozzle structure of the sprays. X-ray radiography measurements have provided quantitative, time-resolved measurements of spray behavior, but the radiography data are projections of the actual fuel distribution. In this study, diesel sprays from two axial, single-hole nozzles are measured using x-ray radiography from several viewing angles. A model-based reconstruction is used to determine the actual density distribution from the projected data. The spray from the hydroground nozzle is eccentric and relatively dense, while the spray from the non-hydroground nozzle is asymmetric and far less dense. Even several mm from the nozzles, the calculated density values are high enough to call into question the assumptions underlying many standard CFD spray models.

This paper introduces control strategy analysis and performance degradation for the 2010 Toyota Prius under different thermal conditions. The goal was to understand, in as much detail as possible, the impact of thermal conditions on component and vehicle performances by analyzing a number of test data obtained under different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory. A previous study analyzed the control behavior and performance under a normal ambient temperature; thus the first step in this study was to focus on the impact when the ambient temperature is cold or hot. Based on the analyzed results, thermal component models were developed in which the vehicle controller in the simulation was designed to mimic the control behavior when temperatures of the components are cold or hot. Further, the performance degradation of the components was applied to the mathematical models based on analysis of the test data.