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At least 901 records · Page 50

Cancer Risk Assessment for Space Radiation

Predicting the occurrence of human cancer following exposure to any agent causing genetic damage is a difficult task. This is because the uncertainty of uniform exposure to the damaging agent, and the uncertainty of uniform processing of that damage within a complex set of biological variables, degrade the confidence of predicting the delayed expression of cancer as a relatively rare event within any given clinically normal individual. The radiation health research priorities for enabling long-duration human exploration of space were established in the 1996 NRC Report entitled "Radiation Hazards to Crews of Interplanetary Missions: Biological Issues and Research Strategies". This report emphasized that a 15-fold uncertainty in predicting radiation-induced cancer incidence must be reduced before NASA can commit humans to extended interplanetary missions. That report concluded that the great majority of this uncertainty is biologically based, while a minority is physically based due to uncertainties in radiation dosimetry and radiation transport codes. Since that report, the biologically based uncertainty has remained large, and the relatively small uncertainty associated with radiation dosimetry has increased due to the considerations raised by concepts of microdosimetry. In a practical sense, however, the additional uncertainties introduced by microdosimetry are encouraging since they are in a direction of lowered effective dose absorbed through infrequent interactions of any given cell with the high energy particle component of space radiation. The biological uncertainty in predicting cancer risk for space radiation derives from two primary facts. 1) One animal tumor study has been reported that includes a relevant spectrum of particle radiation energies, and that is the Harderian gland model in mice. Fact #1: Extension of cancer risk from animal models, and especially from a single study in an animal model, to humans is inherently uncertain. 2) One human database is predominantly used for assessing cancer risk caused by space radiation, and that is the Japanese atomic bomb survivors. Fact #2: The atomic-bomb-survivor database, itself a remarkable achievement, contains uncertainties. These include the actual exposure to each individual, the radiation quality of that exposure, and the fact that the exposure was to acute doses of predominantly low-LET radiation, not to chronic exposures of high-LET radiation expected on long-duration interplanetary manned missions.

Richmond, Robert C.↗

Variability in Morphology and Thermophysical Properties of Pitted Cones in Acidalia Planitia and Cydonia Mensae

The northern plains of Mars contain a number of unique landforms and are unique in terms of their topography and composition . Much of the speculation about the northern plains centers on whether there was ever a northern ocean, and if there was, was it long-lived or ephemeral? The northern plains also hosts the Vastitas Borealis Formation which has been variously interpreted as the residue from a northern ocean , and pre-existing material reworked by cold-weather processes . In this work we examine a set of unusual features resident on the northern plains, the pitted cones originally recognized in Viking data . Our focus is on the pitted cones in Acidalia and Cydonia regions. The pitted cones of the northern plains have been hypothesized as being equivalent to terrestrial cinder cones , rootless cones , pingos , and mud volcanoes . To examine the Acidalia and Cydonia regions, multispectral data from the Mars Odyssey THEMIS, gridded topography from Mars Global Surveyor (MGS) MOLA, images from MGS MOC, and mineralogic and thermal inertia information from MGS TES have been assembled in a Geographic Information System. Analysis of MOC Narrow Angle camera images

Farrand, W. H.↗

Automated Wildfire Detection Through Artificial Neural Networks

We have tested and deployed Artificial Neural Network (ANN) data mining techniques to analyze remotely sensed multi-channel imaging data from MODIS, GOES, and AVHRR. The goal is to train the ANN to learn the signatures of wildfires in remotely sensed data in order to automate the detection process. We train the ANN using the set of human-detected wildfires in the U.S., which are provided by the Hazard Mapping System (HMS) wildfire detection group at NOAA/NESDIS. The ANN is trained to mimic the behavior of fire detection algorithms and the subjective decision- making by N O M HMS Fire Analysts. We use a local extremum search in order to isolate fire pixels, and then we extract a 7x7 pixel array around that location in 3 spectral channels. The corresponding 147 pixel values are used to populate a 147-dimensional input vector that is fed into the ANN. The ANN accuracy is tested and overfitting is avoided by using a subset of the training data that is set aside as a test data set. We have achieved an automated fire detection accuracy of 80-92%, depending on a variety of ANN parameters and for different instrument channels among the 3 satellites. We believe that this system can be deployed worldwide or for any region to detect wildfires automatically in satellite imagery of those regions. These detections can ultimately be used to provide thermal inputs to climate models.

Miller, Jerry↗

BODY SENSING SYSTEM

System and method for performing one or more relevant measurements at a target site in an animal body, using a probe. One or more of a group of selected internal measurements is performed at the target site, is optionally combined with one or more selected external measurements, and is optionally combined with one or more selected heuristic information items, in order to reduce to a relatively small number the probable medical conditions associated with the target site. One or more of the internal measurements is optionally used to navigate the probe to the target site. Neural net information processing is performed to provide a reduced set of probable medical conditions associated with the target site.

Mah, Robert W.↗

NDE Development for Inspection of the Ares I Crew Launch Vehicle

NASA is designing a new crewed launch vehicle called Ares I to replace the Space Shuttle after its scheduled retirement in 2010. This new launch vehicle will build on the Shuttle technology in many ways including using a first stage based upon the Space Shuttle Solid Rocket Booster, advanced aluminum alloys for the second stage tanks, and friction stir welding to assemble the second stage. Friction stir welding uses a spinning pin that is inserted in the joint between two panels that are to be welded. The pin mechanically mixes the metal together below the melting temperature to form the weld. Friction stir welding allows high strength joints in metals that would otherwise lose much of their strength as they are melted during the fusion welding process. One significant change from the Space Shuttle that impacts NDE is the implementation of self-reacting friction stir welding for non-linear welds on the primary metallic structure. The self-reacting technique differs from the conventional technique because the load of the pin tool pressing down on the metal being joined is reacted by a nut on the end of the tool rather than an anvil behind the part. No spacecraft has ever flown with a self-reacting friction stir weld, so this is a major advancement in the manufacturing process, bringing with it a whole new set of challenges for NDE to overcome. Another impact is the proposed usage of an aluminum face sheet, phenolic honeycomb sandwich structure for a common bulkhead between the fuel and oxidizer tanks. This design was used on the second stage of Saturn IB and the second and third stages of Saturn V, but both the manufacturing and subsequent inspection were very costly and time consuming so a more efficient inspection method is sought. The current state of development of these inspections will be presented, along with other information pertinent to NDE of the Ares I.

Richter, Joel↗

Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P < 0.001; RMSE = 1.1 m) and mixed forests (R2 = 0.93, P < 0.001, RMSE = 0.8 m) produced the best results. Estimates over deciduous forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

Yu, Yifan↗

Method and system for fault accommodation of machines

A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine. Control settings of the actual controller are adjusted, represented by the simulated controller, for controlling the actual machine, represented by the simulated machine, in response to a fault condition of the actual machine, based on the Pareto frontier-based solution space, to maximize desirable operational conditions and minimize undesirable operational conditions while operating the actual machine in a region of the solution space defined by the Pareto frontier.

Goebel, Kai Frank↗

Software for Analyzing Laminar-to-Turbulent Flow Transitions

Software assurance is the planned and systematic set of activities that ensures that software processes and products conform to requirements, standards, and procedures. Examples of such activities are the following: code inspections, unit tests, design reviews, performance analyses, construction of traceability matrices, etc. In practice, software development projects have only limited resources (e.g., schedule, budget, and availability of personnel) to cover the entire development effort, of which assurance is but a part. Projects must therefore select judiciously from among the possible assurance activities. At its heart, this can be viewed as an optimization problem; namely, to determine the allocation of limited resources (time, money, and personnel) to minimize risk or, alternatively, to minimize the resources needed to reduce risk to an acceptable level. The end result of the work reported here is a means to optimize quality-assurance processes used in developing software. This is achieved by combining two prior programs in an innovative manner

Chang, Chau-Lyan↗

Software for Optimizing Quality Assurance of Other Software

Software assurance is the planned and systematic set of activities that ensures that software processes and products conform to requirements, standards, and procedures. Examples of such activities are the following: code inspections, unit tests, design reviews, performance analyses, construction of traceability matrices, etc. In practice, software development projects have only limited resources (e.g., schedule, budget, and availability of personnel) to cover the entire development effort, of which assurance is but a part. Projects must therefore select judiciously from among the possible assurance activities. At its heart, this can be viewed as an optimization problem; namely, to determine the allocation of limited resources (time, money, and personnel) to minimize risk or, alternatively, to minimize the resources needed to reduce risk to an acceptable level. The end result of the work reported here is a means to optimize quality-assurance processes used in developing software.

Feather, Martin↗

A State-of-the-Art Experimental Laboratory for Cloud and Cloud-Aerosol Interaction Research

The state of the art for predicting climate changes due to increasing greenhouse gasses in the atmosphere with high accuracy is problematic. Confidence intervals on current long-term predictions (on the order of 100 years) are so large that the ability to make informed decisions with regard to optimum strategies for mitigating both the causes of climate change and its effects is in doubt. There is ample evidence in the literature that large sources of uncertainty in current climate models are various aerosol effects. One approach to furthering discovery as well as modeling, and verification and validation (V&V) for cloud-aerosol interactions is use of a large "cloud chamber" in a complimentary role to in-situ and remote sensing measurement approaches. Reproducing all of the complex interactions is not feasible, but it is suggested that the physics of certain key processes can be established in a laboratory setting so that relevant fluid-dynamic and cloud-aerosol phenomena can be experimentally simulated and studied in a controlled environment. This report presents a high-level argument for significantly improved laboratory capability, and is meant to serve as a starting point for stimulating discussion within the climate science and other interested communities.

Fremaux, Charles M.↗

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Ott, L.↗

Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data

This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances.

Gorinevsky, Dimitry↗

Cost-Effective Telemetry and Command Ground Systems Automation Strategy for the Soil Moisture Active Passive (SMAP) Mission

Soil Moisture Active Passive (SMAP) is an Earth-orbiting, remote-sensing NASA mission slated for launch in 2014. The ground data system (GDS) being developed for SMAP is composed of many heterogeneous subsystems, ranging from those that support planning and sequencing to those used for real-time operations, and even further to those that enable science data exchange. A full end-to-end automation of the GDS may result in cost savings during mission operations, but it would require a significant upfront investment to develop such a comprehensive automation. As demonstrated by the Jason-1 and Wide-field Infrared Survey Explorer (WISE) missions, a measure of "lights-out" automation for routine, orbital pass, ground operations can still reduce mission costs through smaller staffing of operators and limiting their working hours. The challenge, then, for the SMAP GDS engineering team, is to formulate an automated operations strategy--and corresponding system architecture -- to minimize operator intervention during routine operations, while balancing the development costs associated with the scope and complexity of automation. This paper discusses the automated operations approach being developed for the SMAP GDS. The focus is on automating the activities involved in routine passes, which limits the scope to real-time operations. A key subsystem of the SMAP GDS -- NASA's AMMOS Mission Data Processing and Control System (AMPCS) -- provides a set of capabilities that enable such automation. Also discussed are the lights-out pass automations of the Jason-1 and WISE missions and how they informed the automation strategy for SMAP. The paper aims to provide insights into what is necessary in automating the GDS operations for Earth satellite missions.

soil moisture↗

Cost-Effective Telemetry and Command Ground Systems Automation Strategy for the Soil Moisture Active Passive (SMAP) Mission

Soil Moisture Active Passive (SMAP) is an Earth-orbiting, remote-sensing NASA mission slated for launch in 2014.[double dagger] The ground data system (GDS) being developed for SMAP is composed of many heterogeneous subsystems, ranging from those that support planning and sequencing to those used for real-time operations, and even further to those that enable science data exchange. A full end-to-end automation of the GDS may result in cost savings during mission operations, but it would require a significant upfront investment to develop such comprehensive automation. As demonstrated by the Jason-1 and Wide-field Infrared Survey Explorer (WISE) missions, a measure of "lights-out" automation for routine, orbital pass ground operations can still reduce mission cost through smaller staffing of operators and limited work hours. The challenge, then, for the SMAP GDS engineering team is to formulate an automated operations strategy--and corresponding system architecture--to minimize operator intervention during operations, while balancing the development cost associated with the scope and complexity of automation. This paper discusses the automated operations approach being developed for the SMAP GDS. The focus is on automating the activities involved in routine passes, which limits the scope to real-time operations. A key subsystem of the SMAP GDS--NASA's AMMOS Mission Data Processing and Control System (AMPCS)--provides a set of capabilities that enable such automation. Also discussed are the lights-out pass automations of the Jason-1 and WISE missions and how they informed the automation strategy for SMAP. The paper aims to provide insights into what is necessary in automating the GDS operations for Earth satellite missions.

remote-sensing↗

Modeling Spacecraft Fuel Slosh at Embry-Riddle Aeronautical University

As a NASA-sponsored GSRP Fellow, I worked with other researchers and analysts at Embry-Riddle Aeronautical University and NASA's ELV Division to investigate the effect of spacecraft fuel slosh. NASA's research into the effects of fuel slosh includes modeling the response in full-sized tanks using equipment such as the Spinning Slosh Test Rig (SSTR), located at Southwest Research Institute (SwRI). NASA and SwRI engineers analyze data taken from SSTR runs and hand-derive equations of motion to identify model parameters and characterize the sloshing motion. With guidance from my faculty advisor, Dr. Sathya Gangadharan, and NASA flight controls analysts James Sudermann and Charles Walker, I set out to automate this parameter identification process by building a simple physical experimental setup to model free surface slosh in a spherical tank with a simple pendulum analog. This setup was then modeled using Simulink and SimMechanics. The Simulink Parameter Estimation Tool was then used to identify the model parameters.

Schlee, Keith L.↗

Testing Small CPAS Parachutes Using HIVAS

The High Velocity Airflow System (HIVAS) facility at the Naval Air Warfare Center (NAWC) at China Lake was successfully used as an alternative to flight test to determine parachute drag performance of two small Capsule Parachute Assembly System (CPAS) canopies. A similar parachute with known performance was also tested as a control. Realtime computations of drag coefficient were unrealistically low. This is because HIVAS produces a non-uniform flow which rapidly decays from a high central core flow. Additional calibration runs were performed to characterize this flow assuming radial symmetry from the centerline. The flow field was used to post-process effective flow velocities at each throttle setting and parachute diameter using the definition of the momentum flux factor. Because one parachute had significant oscillations, additional calculations were required to estimate the projected flow at off-axis angles. The resulting drag data from HIVAS compared favorably to previously estimated parachute performance based on scaled data from analogous CPAS parachutes. The data will improve drag area distributions in the next version of the CPAS Model Memo.

Ray, Eric S.↗

Bounding the Role of Black Carbon in the Climate System: a Scientific Assessment

Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg/yr in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W/sq m with 90% uncertainty bounds of (+0.08, +1.27)W/sq m. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W/sq m. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W/sq m with 90% uncertainty bounds of +0.17 to +2.1 W/sq m. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W/sq m, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (0.50 to +1.08) W/sq m during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (0.06 W/sq m with 90% uncertainty bounds of 1.45 to +1.29 W/sq m). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

black carbon↗

Advanced Background Subtraction Applied to Aeroacoustic Wind Tunnel Testing

An advanced form of background subtraction is presented and applied to aeroacoustic wind tunnel data. A variant of this method has seen use in other fields such as climatology and medical imaging. The technique, based on an eigenvalue decomposition of the background noise cross-spectral matrix, is robust against situations where isolated background auto-spectral levels are measured to be higher than levels of combined source and background signals. It also provides an alternate estimate of the cross-spectrum, which previously might have poor definition for low signal-to-noise ratio measurements. Simulated results indicate similar performance to conventional background subtraction when the subtracted spectra are weaker than the true contaminating background levels. Superior performance is observed when the subtracted spectra are stronger than the true contaminating background levels. Experimental results show limited success in recovering signal behavior for data where conventional background subtraction fails. They also demonstrate the new subtraction technique's ability to maintain a proper coherence relationship in the modified cross-spectral matrix. Beam-forming and de-convolution results indicate the method can successfully separate sources. Results also show a reduced need for the use of diagonal removal in phased array processing, at least for the limited data sets considered.

Bahr, Christopher J.↗