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Diesel engine exhaust aftertreatment components, especially the diesel particulate filter (DPF), are subject to various modes of degradation over their lifetimes. One particular adverse effect on the DPF is the significant rise in pressure drop due to the accumulation of engine lubricant-derived ash which coats the inlet channel walls effectively decreasing the permeability of the filter. The decreased permeability due to ash in the DPF can result in increased filter pressure drop and decreased fuel economy. A unique two-step approach, consisting of experimental measurements and direct numerical simulations using ultra-high resolution 3D imaging data, has been utilized in this study to better understand the effects of ash accumulation on engine aftertreatment component functionality.

The Engine-Out Particulate Matter (EOPM) was collected from a spark ignition engine operating in steady state using a heated quartz fiber filter. The samples were weighted to obtain an EOPMindex and were analyzed using Scanning Electron Microscopy. The EOP Mindex was not sensitive to the engine rpm and load. When the mixture is very rich (air equivalence ratio λ less than ∼ 0.7), the EOPM comprise mostly of soot particles from fuel combustion. In the lean to slightly rich region (0.8 < λ < 1.2), however, the EOPM are dominated by particles derived from the lubrication oil.

The presence of liquid fuel inside the engine cylinder is believed to be a strong contributor to the high levels of hydrocarbon emissions from spark ignition (SI) engines during the warm-up period. Quantifying and determining the fate of the liquid fuel that enters the cylinder is the first step in understanding the process of emissions formation. This work uses planar laser induced fluorescence (PLIF) to visualize the liquid fuel present in the cylinder. The fluorescing compounds in indolene, and mixtures of iso-octane with dopants of different boiling points (acetone and 3-pentanone) were used to trace the behavior of different volatility components. Images were taken of three different planes through the engine intersecting the intake valve region. A closed valve fuel injection strategy was used, as this is the strategy most commonly used in practice. Background subtraction and masking were both performed to reduce the effect of any spurious fluorescence.

This paper describes recent work on developing an extensible information grid for risk management at NASA — a RISK INFORMATION GRID. This grid is being developed by integrating information grid technology with risk management processes for a variety of risk related applications. To date, RISK GRID applications are being developed for three main NASA processes: risk management — a closed-loop iterative process for explicit risk management, program/project management — a proactive process that includes risk management, and mishap management — a feedback loop for learning from historical risks that ‘escaped’ other processes. This is enabled through an architecture involving an extensible database, structuring information with XML, ‘schema-less’ mapping of XML, and secure server-mediated communication using standard protocols.

A number of airlines have FOQA programs that analyze archived flight data. Although this analysis process is extremely useful for assessing airline concerns in the areas of aviation safety, operations, training, and maintenance, looking at flight data in isolation does not always provide the context necessary to support a comprehensive analysis. To improve the analysis process, the Aviation Data Integration Project (ADIP) has been developing techniques for integrating flight data with auxiliary sources of relevant aviation data. ADIP has developed an aviation data integration system (ADIS) comprised of a repository and associated integration middleware that provides rapid and secure access to various data sources, including weather data, airport operating condition (ATIS) reports, radar data, runway visual range data, and navigational charts.

The Rotating Disk Analytical System (R-DAS) is an in-situ, bio-analytical technology, which utilizes a micro-fluidic disk with similar form factor as an audio compact disc to enhance and augment microgravity-based cellular and molecular biology research. The current micro-fluidic assay performs live cell/dead cell analysis using fluorescent microscopy. Image acquisition and analysis are performed for each of the selected microscope slide windows. All images are stored for later download and possible further post analysis. The flight version of the R-DAS will occupy a double mid-deck shuttle locker or one quarter of an ISS rack. The control system for the R-DAS consists of a set of interactive software components. These components interact with one another to control disk rotation, vertical and horizontal stage motion, sample incubation, image acquisition and analysis, and human interface.

Computer simulation of extravehicular activity (EVA) is increasingly being used in planning and training for EVA. A space suit model is an important, but often overlooked, component of an EVA simulation. Because of the inherent difficulties in collecting angle and torque data for space suit joints in realistic conditions, little data exists on the torques that a space suit’s wearer must provide in order to move in the space suit. A joint angle and torque database was compiled on the Extravehicular Maneuvering Unit (EMU), with a novel measurement technique that used both human test subjects and an instrumented robot. Using data collected in the experiment, a hysteresis modeling technique was used to predict EMU joint torques from joint angular positions. The hysteresis model was then applied to EVA operations by mapping out the reach and work envelopes for the EMU.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

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.

A new oil-fringe imaging skin friction (FISF) technique to measure skin friction on wind tunnel models is presented. In the method used to demonstrate the technique, lines of oil are applied on surfaces that connect the intended sets of measurement points, and then a wind tunnel is run so that the oil thins and forms interference fringes that are spaced proportional to local skin friction. After a run the fringe spacings are imaged with a CCD-array digital camera and measured on a computer. Skin friction and transition measurements on a two-dimensional wing are presented and compared with computational predictions.

We examine the requirements for on-board aircraft sensor systems that would allow pilots to “see through” poor weather, especially fog, and land and rollout aircraft under conditions that currently cause flight cancellations and airport closures. Three visual aspects of landing and rollout are distinguished: guidance, hazard detection and hazard recognition. The visual features which support the tasks are discussed. Three broad categories of sensor technology are examined: passive millimeter wave (PMMW), imaging radar, and passive infrared (IR). PMMW and imaging radar exhibit good weather penetration, but poor spatial and temporal resolution. Imaging radar exhibits good weather penetration, but typically relies on a flat-earth assumption which can lead to interpretive errors. PMMW systems have a narrow field of view. IR has poorer weather penetration but good spatial resolution.

The fuel injection process in the port of a firing 4-valve SI engine at part load and 25°C head temperature was observed by a high speed video camera. Fuel was injected when the valve was closed. The reverse blow-down flow when the intake valve opens has been identified as an important factor in the mixture preparation process because it not only alters the thermal environment of the intake port, but also strip-atomizes the liquid film at the vicinity of the intake valve and carries the droplets away from the engine. In a series of “fuel-on” experiments, the fuel injected in the current cycle was observed to influence the fuel delivery to the engine in the subsequent cycles.

A Lagrangian random vortex-boundary element method has been developed for the simulation of unsteady incompressible flow inside three-dimensional domains with time-dependent boundaries, similar to IC engines. The solution method is entirely grid-free in the fluid domain and eliminates the difficult task of volumetric meshing of the complex engine geometry. Furthermore, due to the Lagrangian evaluation of the convective processes, numerical viscosity is virtually removed; thus permitting the direct simulation of flow at high Reynolds numbers. In this paper, a brief description of the numerical methodology is given, followed by an example of induction flow in an off-centered port-cylinder assembly with a harmonically driven piston and a valve seat situated directly below the port. The predicted flow is shown to resemble the flow visualization results of a laboratory experiment, despite the crude approximation used to represent the geometry.

Predicting and testing for hover performance, both in and out of ground effect, and transition performance, from jet- to wing-borne flight and back, for vertical/short takeoff and landing (V/STOL) configurations can be a difficult task. Large-scale testing of these configurations can provide for a better representation of the flow physics than small-scale testing. This paper will discuss some of the advantages in testing at large-scale and some test techniques and issues involved with testing large-scale STOVL models. The two premier test facilities for testing large- to full-scale STOVL configurations are the Outdoor Aerodynamic Research Facility (OARF) and the 80- by 120-Foot Wind Tunnel of the National Full-Scale Aerodynamics Complex (NFAC). Other items of discussion will include force and moment measurements, jet efflux decay, wall effects, tunnel flow breakdown, strut interference, and flow visualization options.

A processing system has been developed to meet increasing demands for detailed noise measurement of aircraft in wind tunnels. Phased arrays enable spatial and amplitude measurements of acoustic sources, including low signal-to-noise sources not measurable by conventional measurement techniques. The Microphone Array Phased Processing System (MAPPS) provides processing and visualization of acoustic array measurements made in wind tunnels. The system uses networked parallel computers to provide noise maps at selected frequencies in a near real-time testing environment. The system has been successfully used in two subsonic, hard-walled wind tunnels, the NASA Ames 7- by 10-Foot Wind Tunnel and the NASA Ames 12-Foot Wind Tunnel. Low level airframe noise that can not be measured with traditional techniques was measured in both tests.

This paper presents an Axiomatic Design framework for manufacturing system design and illustrates how lean cellular manufacturing can achieve volume flexibility. Axiomatic Design creates a design framework by mapping the functional requirements of a system to specific design parameters. Volume flexibility is often neglected as a requirement of manufacturing systems. Very few industries are fortunate enough to experience stable or predictable product demand. In reality, demand is often volatile and uncertain. It is important that manufacturing system designers are aware of manufacturing system types which can accommodate volume flexibility and follow a structured design methodology that assures that all requirements are met by the system.

Optimal design of modern direct injection spark-ignition engines depends heavily on the characteristics and distribution of the fuel spray. This study was designed to compliment imaging experiments of changes in the spray structure due to fuel volatility and operating conditions. Use of phase-Doppler particle analysis (PDPA) allows quantitative point measurements of droplet diameter and velocity. In agreement with imaging experiments, the results show that the spray structure changes not only with ambient gas density, which is often measured, but also with fuel temperature and volatility. The mean droplet diameter was found to decrease substantially with increasing fuel temperature and decreasing ambient density. Under conditions of low potential for vaporization, the observed trends in mean droplet sizes agree with published correlations for pressure-swirl atomizers.

Optimal design of modern direct injection spark-ignition engines depends heavily on the characteristics and distribution of the fuel spray. This study was designed to investigate changes in the spray properties due to fuel volatility and operating conditions using a firing optically-accessible engine with planar laser-induced fluorescence (PLIF) imaging. The results show that the spray structure changes not only with ambient gas density, which is often measured, but also with fuel temperature and volatility. As ambient pressure decreases and fuel temperature increases, the volatile ends of multi-component fuels evaporate quickly, disrupting the spray structure and producing a vapor core along the axis of the spray. Beyond a certain point, evaporation is rapid enough to expand the initial cone angle of the spray while causing a decrease in the overall spray width.

MIT Lincoln Laboratory is tasked by the U.S. Federal Aviation Administration to investigate the use of the NEXRAD polarimetric radars* for the remote sensing of icing conditions hazardous to aircraft. A critical aspect of the investigation concerns validation that has relied upon commercial airline icing pilot reports and a dedicated campaign of in situ flights in winter storms. During the month of February in 2012 and 2013, the Convair-580 aircraft operated by the National Research Council of Canada was used for in situ validation of snowstorm characteristics under simultaneous observation by NEXRAD radars in Cleveland, Ohio and Buffalo, New York. The most anisotropic and easily distinguished winter targets to dual pol radar are ice crystals.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida.