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Recently Michelin has been developing a new airless, integrated tire and wheel combination called the Tweel® tire. The Tweel tire aims at performance levels beyond those possible with conventional pneumatic technology because of its shear band design, added suspension, and potentially decreased rolling resistance. In this paper, we will focus on the environmental impact of the Tweel tire during its life-cycle from manufacturing, through use and disposal. Since the Tweel tire is currently still in the research phase and is not manufactured and used on a large scale, there are uncertainties with respect to end-of-life scenarios and rolling resistance estimates that will affect the LCA. Nevertheless, some preliminary conclusions of the Tweel tire's environmental performance in comparison to a conventional radial tire can be drawn.

Although the design phase can account for a sizable amount of the resources consumed during the product realization process, the time and costs associated with the design process are often neglected when making design decisions. To investigate this issue, we define a process-centric decision model in which the design-phase consumption of resources, such as time and money, is explicitly modeled. While it is clear that the utility of a design is almost always directly impacted by the monetary costs of the design process, our decision model also accounts for the fact that the profit earned by a product depends strongly on its launch date. The decision model allows us thus to consider the trade-off between the time necessary for analysis and the improvement in product quality that results from the analysis. The decision model is sufficiently generic that almost any set of beliefs about the alternatives or analyses, as well as any utility-based preference structure can be modeled.

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-in-trail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011.

In early phases of conceptual design stages for developing a new car in the modern automobile industry, the lack of systematic methodology to efficiently converge to an agreement between the aesthetics and aerodynamic performance tremendously increases budget and time. During these procedures, one of the most important tasks is to create geometric information which is versatilely morphable upon the demands of both of stylists and engineers. In this perspective, this paper proposes a Spline-based Modeling Algorithm (SMA) to implement into performing aerodynamic design optimization research based on CFD analysis. Once a 3-perspective schematic of a car is given, SMA regresses the backbone boundary lines by using optimum polynomial interpolation methods with the best goodness of fit, eventually reconstructing the 3D shape by linearly interpolating from the extracted boundaries minimizing loss of important geometric features.

Modeling and simulation are commonly used in all stages of the design process. This is particularly vital to the success of systems engineering projects where the system under consideration is complex and involves interactions between many interdisciplinary subsystems. In the refining stages of the design process (after concept selection), models and simulations can be used to refine and optimize a system with respect to the decision maker’s objectives. In this paper, a dynamic model of a hydraulic backhoe serves as a test-bed for a large-scale sensitivity analysis and subsequent optimization of the most significant design parameters. The model is optimized under uncertainty with respect to a multi-attribute utility function that includes fuel consumption, cost of the key components, and machine performance.

A review of the research accomplished in 2009 in the System-Level Design, Analysis and Simulation Tools (SLDAST) of the NASA's Airspace Systems Program is presented. This research thrust focuses on the integrated system-level assessment of component level innovations, concepts and technologies of the Next Generation Air Traffic System (NextGen) under research in the ASP program to enable the development of revolutionary improvements and modernization of the National Airspace System. The review includes the accomplishments on baseline research and the advancements on design studies and system-level assessment, including the cluster analysis as an annualization standard of the air traffic in the U.S. National Airspace, and the ACES-Air MIDAS integration for human-in-the-loop analyzes within the NAS air traffic simulation.

Turboelectric propulsion is a technology that can potentially reduce aircraft noise, increase fuel efficiency, and decrease harmful emissions. In a turbo-electric system, the propulsor (fans) is no longer connected to the turbine through a mechanical connection. Instead, a superconducting generator connected to a gas turbine produces electrical power which is delivered to distributed fans. This configuration can potentially decrease fuel burn by 10% [1]. One of the primary challenges in implementing turboelectric electric propulsion is designing the power distribution system to transmit power from the generator to the fans. The power distribution system is required to transmit 40 MW of power from the generator to the electrical loads on the aircraft. A conventional aircraft distribution cannot efficiently or reliably transmit this large amount of power; therefore, new power distribution technologies must be considered.

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.

In order to improve understanding of the primary atomization process for diesel-like sprays, a collaborative experimental and computational study was focused on the near-nozzle spray structure for the Engine Combustion Network (ECN) Spray D single-hole injector. These results were presented at the 5th Workshop of the ECN in Detroit, Michigan. Application of x-ray diagnostics to the Spray D standard cold condition enabled quantification of distributions of mass, phase interfacial area, and droplet size in the near-nozzle region from 0.1 to 14 mm from the nozzle exit. Using these data, several modeling frameworks, from Lagrangian-Eulerian to Eulerian-Eulerian and from Reynolds-Averaged Navier-Stokes (RANS) to Direct Numerical Simulation (DNS), were assessed in their ability to capture and explain experimentally observed spray details. Due to its computational efficiency, the Lagrangian-Eulerian approach was able to provide spray predictions across a broad range of conditions.

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.

The environmental impact of aircraft, specifically in the areas of noise and NOx emissions, has been a growing community concern. Coupled with the increasing cost and diminishing supply of traditional fossil fuels, these concerns have fueled substantial interest in the research and development of alternative power sources for aircraft. In 2003, NASA and the Department of Defense awarded a five year research cooperative agreement to a team of researchers from three different universities to address the design and analysis of revolutionary aeropropulsion technologies.

Over the past few years, modern aircraft design has experienced a paradigm shift from designing for performance to designing for affordability. This paper contains a probabilistic approach that will allow traditional deterministic design methods to be extended to account for disciplinary, economic, and technological uncertainty. The probabilistic approach was facilitated by the Fast Probability Integration (FPI) technique; a technique which allows the designer to gather valuable information about the vehicle's behavior in the design space. This technique is efficient for assessing multi-attribute, multi-constraint problems in a more realistic fashion. For implementation purposes, this technique is applied to illustrate how both economic and technological uncertainty associated with a Very Large Transport aircraft may be assessed.

Neural network augmented model inversion control is used to provide a civilian tilt-rotor aircraft with consistent response characteristics throughout its operating envelope, including conversion flight. The implemented response types are Attitude Command Attitude Hold in the longitudinal channel, and Rate Command Attitude Hold about the roll and yaw axes. This article describes the augmentation in the roll channel and the augmentation for the yaw motion including Heading Hold at low airspeeds and automatic Turn Coordination at cruise flight. Conventional methods require extensive gain scheduling with tilt-rotor nacelle angle and airspeed. A control architecture is developed that can alleviate this requirement and thus has the potential to reduce development time. It also facilitates the implementation of desired handling qualities, and permits compensation for partial failures.

The Vapor Phase Catalytic Ammonia Removal (VPCAR) technology has been previously discussed as a viable option for the Exploration Water Recovery System. This technology integrates a phase change process with catalytic oxidation in the vapor phase to produce potable water from exploration mission wastewaters. A developmental prototype VPCAR was designed, built and tested under funding provided by a National Research Announcement (NRA) project. The core technology, a Wiped Film Rotating Device (WFRD) was provided by Water Reuse Technologies under the NRA, whereas Hamilton Sundstrand Space Systems International performed the hardware integration and acceptance test of the system. Personnel at the Ames Research Center performed initial systems test of the VPCAR using ersatz solutions. To assess the viability of this hardware for Exploration Life Support (ELS) applications, the hardware has been modified and tested at the MSFC ECLS Test Facility.

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.

In long-duration, closed human habitats in space that include crop growth, one challenge that is faced while designing a candidate waste processor is the composition of solid-waste loads, which include human waste, packaging and food-processing materials, crop spoilage, and plant residues. In this work, a new modeling tool is developed to characterize crop residues and food wastes based on diet in order to support the design of solid-waste technologies for closed systems. The model predicts amounts of crop residues and food wastes due to food processing, crop harvests, and edible spoilage. To support the design of solid-waste technologies, the generation of crop residues and food wastes was characterized for a 600-day mission to Mars using integrated menu, crop, and waste models. The three sources of plant residues and food waste are identified to be food processors, crop harvests, and edible spoilage.

Some selected segments of the ascent and the on-orbit data from the Space Shuttle flight, STS114, as well as some selected laboratory test article data have been analyzed using wavelets, power spectrum and autocorrelation function. Additionally, a simple approximate noise test was performed on these data segments to confirm the presence or absence of white noise behavior in the data. This study was initially directed at characterizing the on-orbit background against which a signature due to an impact during on-orbit operation could be identified. The laboratory data analyzed here mimic low velocity impact that the Orbiter may be subjected to during the very initial stages of ascent.

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.

Linear regression is the primary data analysis method used in the development of air traffic delay models. When the data being studied does indeed have an underlying linear model, this approach would produce the best-fitting model as expected. However, it has been argued by ATM researchers [Wieland2005, Evans2004] that the underlying delay models are primarily non-linear. Furthermore, the delays being modeled often depend not only on the observable independent variables being studied but also on other variables not being considered. The traditional regression approach alone may not be best suited to study these type of problems. In this paper, we propose an alternate methodology based on partitioning the data using statistical and decision tree learning methods. We then show the utility of this model in a variety of different ATM modeling problems.

Results of computations of flows, sprays and combustion performed in an optically- accessible Diesel engine are presented. These computed results are compared with measured values of chamber pressure, liquid penetration, and soot distribution, deduced from flame luminosity photographs obtained in the engine at Sandia National Laboratories and reported in the literature. The computations were performed for two operating conditions representing low load and high load conditions as reported in the experimental work. The computed and measured peak pressures agree within 5% for both the low load and the high load conditions. The heat release rates derived from the computations are consistent with expectations for Diesel combustion with a premixed phase of heat release and then a diffusion phase. The computed soot distribution shows noticeable differences from the measured one.