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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

A Biomechanical Approach to Assessing Hip Fracture Risk

Bone loss in microgravity is well documented, but it is difficult to quantify how declines in bone mineral density (BMD) contribute to an astronaut's overall risk of fracture upon return. This study uses a biomechanical approach to assessing hip fracture risk, or Factor of Risk (Phi), which is defined as the ratio of applied load to bone strength. All long-duration NASA astronauts from Expeditions 1-18 were included in this study (n=25), while crewmembers who flew twice (n=2) were treated as separate subjects. Bone strength was estimated based on an empirical relationship between areal BMD at the hip, as measured by DXA, and failure load, as determined by mechanical testing of cadaver femora. Fall load during a sideways fall was calculated from a previously developed biomechanical model, which takes into account body weight, height, gender, and soft tissue thickness overlying the lateral aspect of the hip that serves to attenuate the impact force. While no statistical analyses have been performed yet, preliminary results show that males in this population have a higher FOR than females, with a post- flight Phi of 0.87 and 0.36, respectively. FOR increases 5.1% from preflight to postflight, while only one subject crossed the fracture "threshold" of Phi = 1, for a total of 2 subjects with a postflight Phi > 1. These results suggest that men may be at greater risk for hip fracture due largely in part to their relatively thin soft tissue padding as compared to women, since soft tissue thickness has the highest correlation (R(exp 2)= .53) with FOR of all subject-specific parameters. Future work will investigate changes in FOR during recovery to see if baseline risk levels are restored upon return to 1-g activity. While dual x-ray absorptiometry (DXA) is the most commonly used clinical measure of bone health, it fails to provide compartment-specific information that is useful in assessing changes to bone quality as a result of microgravity exposure. Peripheral quantitative computed tomography (pQCT) accomplishes this by imaging transverse "slices" of the long bones. This project was a re-analysis of a 90 day bed rest study to determine if changes to cortical and trabecular compartments could be detected in the distal tibia with statistical significance using a new pQCT image analysis method. Nearly all changes in bone mineral density (BMD) and cross sectional area (CSA) measures were seen with statistical significance, with the exception of a change in cortical BMD. Total bone CSA increased by 1.1 % (p =0.01), cortical CSA decreased by - 5.6% (p<0.001) and trabecular CSA increased by 1.76% (p=0.007); the combination of which suggests bone resorption occurred at the endocortical surface in response to mechanical unloading by bed rest. Furthermore, total BMD and trabecular BMD decreased (-3.8%, p=0.001 and -2.8%, p =0.007, respectively), while decreases in cortical BMD failed to reach significance (-1.2%, p=0.07). Given that compartment-specific changes are seen with significance and are likely to influence bone strength, it is recommended that pQCT remain a standard measure used in bed rest because it provides a unique measure by which to better evaluate the efficacy of countermeasures to microgravity-induced bone loss.

Ellman, Rachel↗
NASA NTRS2007

The Variable X-Ray Spectrum of Markarian 766. II. Time-resolved Spectroscopy

Time-resolved spectroscopy, slicing XMM and Suzaku data down to 25 ks elements was used to investigate whether absorption or scattering components dominate the spectral variations in Mrk 766. Results: Time-resolved spectroscopy confirmed that spectral variability in Mrk 766 can be explained by either of two interpretations of principal components analysis. Detailed investigation confirmed that rapid changes in the relative strengths of scattered and direct emission or rapid changes in absorber covering fraction provide good explanations of most of the spectral variability. However, a strong correlation between the 6.97 keV absorption line and primary continuum together with rapid opacity changes showed that variations in a complex and multi-layered absorber, most likely a disk wind, are the dominant source of spectral variability in Mrk 766.

Turner, T. J.↗
NASA NTRS2007

Decision-Tree Formulation With Order-1 Lateral Execution

A compact symbolic formulation enables mapping of an arbitrarily complex decision tree of a certain type into a highly computationally efficient multidimensional software object. The type of decision trees to which this formulation applies is that known in the art as the Boolean class of balanced decision trees. Parallel lateral slices of an object created by means of this formulation can be executed in constant time considerably less time than would otherwise be required. Decision trees of various forms are incorporated into almost all large software systems. A decision tree is a way of hierarchically solving a problem, proceeding through a set of true/false responses to a conclusion. By definition, a decision tree has a tree-like structure, wherein each internal node denotes a test on an attribute, each branch from an internal node represents an outcome of a test, and leaf nodes represent classes or class distributions that, in turn represent possible conclusions. The drawback of decision trees is that execution of them can be computationally expensive (and, hence, time-consuming) because each non-leaf node must be examined to determine whether to progress deeper into a tree structure or to examine an alternative. The present formulation was conceived as an efficient means of representing a decision tree and executing it in as little time as possible. The formulation involves the use of a set of symbolic algorithms to transform a decision tree into a multi-dimensional object, the rank of which equals the number of lateral non-leaf nodes. The tree can then be executed in constant time by means of an order-one table lookup. The sequence of operations performed by the algorithms is summarized as follows: 1. Determination of whether the tree under consideration can be encoded by means of this formulation. 2. Extraction of decision variables. 3. Symbolic optimization of the decision tree to minimize its form. 4. Expansion and transformation of all nested conjunctive-disjunctive paths to a flattened conjunctive form composed only of equality checks when possible. If each reduced conjunctive form contains only equality checks and all of these forms use the same variables, then the decision tree can be reduced to an order-one operation through a table lookup. The speedup to order one is accomplished by distributing each decision variable over a surface of a multidimensional object by mapping the equality constant to an index

James, Mark↗
NASA NTRS2010

In-Situ Focusing Inside a Thermal Vacuum Chamber

Traditionally, infrared (IR) space instruments have been focused by iterating with a number of different thickness shim rings in a thermal vacuum chamber until the focus meets requirements. This has required a number of thermal cycles that are very expensive as they tie up many integration and test (I&T)/ environmental technicians/engi neers work ing three shifts for weeks. Rather than creating a test shim for each iteration, this innovation replaces the test shim and can focus the instrument while in the thermal vacuum chamber. The focus tool consists of three small, piezo-actuated motors that drive two sets of mechanical interface flanges between the instrument optics and the focal- plane assembly, and three optical-displacement metrology sensors that can be read from outside the thermal vacuum chamber. The motors are used to drive the focal planes to different focal distances and acquire images, from which it is possible to determine the best focus. At the best focus position, the three optical displacement metrology sensors are used to determine the shim thickness needed. After the instrument leaves the thermal vacuum chamber, the focus tool is replaced with the precision-ground shim ring. The focus tool consists of two sets of collars, one that mounts to the backside of the interface flange of the instrument optics, and one that mounts to the backside of the interface flange of the focal plane modules. The collars on the instrument optics side have the three small piezo-actuated motors and the three optical displacement metrology systems. Before the instrument is focused, there is no shim ring in place and, therefore, no fasteners holding the focal plane modules to the cameras. Two focus tooling collars are held together by three strong springs. The Orbiting Carbon Observatory (OCO) mission spectrometer was focused this way (see figure). The motor described here had to be moved five times to reach an acceptable focus, all during the same thermal cycle, which was verified using pupil slicing techniques. A focus accuracy of .20.100 microns was achieved.

Liebe, Carl Christian↗
NASA NTRS2010

Probabilistic Simulation for Nanocomposite Fracture

A unique probabilistic theory is described to predict the uniaxial strengths and fracture properties of nanocomposites. The simulation is based on composite micromechanics with progressive substructuring down to a nanoscale slice of a nanofiber where all the governing equations are formulated. These equations have been programmed in a computer code. That computer code is used to simulate uniaxial strengths and fracture of a nanofiber laminate. The results are presented graphically and discussed with respect to their practical significance. These results show smooth distributions from low probability to high.

Chamis, Christos C.↗
NASA NTRS2010

Fracture Mechanics Analyses of the Slip-Side Joggle Regions of Wing-Leading Edge Panels

The Space Shuttle Orbiter wing comprises of 22 leading edge panels on each side of the wing. These panels are part of the thermal protection system that protects the Orbiter wings from extreme heating that take place on the reentry in to the earth atmosphere. On some panels that experience extreme heating, liberation of silicon carbon (SiC) coating was observed on the slip side regions of the panels. Global structural and local fracture mechanics analyses were performed on these panels as a part of the root cause investigation of this coating liberation anomaly. The wing-leading-edge reinforced carbon-carbon (RCC) panels, Panel 9, T-seal 10, and Panel 10, are shown in Figure 1 and the progression of the stress analysis models is presented in Figure 2. The global structural analyses showed minimal interaction between adjacent panels and the T-seal that bridges the gap between the panels. A bounding uniform temperature is applied to a representative panel and the resulting stress distribution is examined. For this loading condition, the interlaminar normal stresses showed negligible variation in the chord direction and increased values in the vicinity of the slip-side joggle shoulder. As such, a representative span wise slice on the panel can be taken and the cross section can be analyzed using plane strain analysis.

Raju, Ivatury S.↗
NASA NTRS2010

HDU Pressurized Excursion Module (PEM) Prototype Systems Integration

The Habitat Demonstration Unit (HDU) project team constructed an analog prototype lunar surface laboratory called the Pressurized Excursion Module (PEM). The prototype unit subsystems were integrated in a short amount of time, utilizing a skunk-works approach that brought together over 20 habitation-related technologies from a variety of NASA centers. This paper describes the system integration strategies and lessons learned, that allowed the PEM to be brought from paper design to working field prototype using a multi-center team. The system integration process included establishment of design standards, negotiation of interfaces between subsystems, and scheduling fit checks and installation activities. A major tool used in integration was a coordinated effort to accurately model all the subsystems using CAD, so that conflicts were identified before physical components came together. Some of the major conclusions showed that up-front modularity that emerged as an artifact of construction, such as the eight 45 degree "pie slices" making up the module whose steel rib edges defined structural mounting and loading points, dictated much of the configurational interfaces between the major subsystems and workstations. Therefore, 'one of the lessons learned included the need to use modularity as a tool for organization in advance, and to work harder to prevent non-critical aspects of the platform from dictating the modularity that may eventually inform the fight system.

Gill, Tracy R.↗
NASA NTRS2011

Multiplexed Energy Coupler for Rotating Equipment

A multiplexing antenna assembly can efficiently couple AC signal/energy into, or out of, rotating equipment. The unit only passes AC energy while blocking DC energy. Concentric tubes that are sliced into multiple pieces are assembled together so that, when a piece from an outer tube aligns well with an inner tube piece, efficient energy coupling is achieved through a capacitive scheme. With N outer pieces and M inner pieces, an effective N x M combination can be achieved in a multiplexed manner. The energy coupler is non-contact, which is useful if isolation from rotating and stationary parts is required. Additionally, the innovation can operate in high temperatures. Applications include rotating structure sensing, non-contact energy transmission, etc.

Zhao, Xiaoliang↗
NASA NTRS2011

Formal methods for test case generation

The invention relates to the use of model checkers to generate efficient test sets for hardware and software systems. The method provides for extending existing tests to reach new coverage targets; searching *to* some or all of the uncovered targets in parallel; searching in parallel *from* some or all of the states reached in previous tests; and slicing the model relative to the current set of coverage targets. The invention provides efficient test case generation and test set formation. Deep regions of the state space can be reached within allotted time and memory. The approach has been applied to use of the model checkers of SRI's SAL system and to model-based designs developed in Stateflow. Stateflow models achieving complete state and transition coverage in a single test case are reported.

Rushby, John↗
NASA NTRS2011

Development of Monte Carlo Capability for Orion Parachute Simulations

Parachute test programs employ Monte Carlo simulation techniques to plan testing and make critical decisions related to parachute loads, rate-of-descent, or other parameters. This paper describes the development and use of a MATLAB-based Monte Carlo tool for three parachute drop test simulations currently used by NASA. The Decelerator System Simulation (DSS) is a legacy 6 Degree-of-Freedom (DOF) simulation used to predict parachute loads and descent trajectories. The Decelerator System Simulation Application (DSSA) is a 6-DOF simulation that is well suited for modeling aircraft extraction and descent of pallet-like test vehicles. The Drop Test Vehicle Simulation (DTVSim) is a 2-DOF trajectory simulation that is convenient for quick turn-around analysis tasks. These three tools have significantly different software architectures and do not share common input files or output data structures. Separate Monte Carlo tools were initially developed for each simulation. A recently-developed simulation output structure enables the use of the more sophisticated DSSA Monte Carlo tool with any of the core-simulations. The task of configuring the inputs for the nominal simulation is left to the existing tools. Once the nominal simulation is configured, the Monte Carlo tool perturbs the input set according to dispersion rules created by the analyst. These rules define the statistical distribution and parameters to be applied to each simulation input. Individual dispersed parameters are combined to create a dispersed set of simulation inputs. The Monte Carlo tool repeatedly executes the core-simulation with the dispersed inputs and stores the results for analysis. The analyst may define conditions on one or more output parameters at which to collect data slices. The tool provides a versatile interface for reviewing output of large Monte Carlo data sets while preserving the capability for detailed examination of individual dispersed trajectories. The Monte Carlo tool described in this paper has proven useful in planning several Crew Exploration Vehicle parachute tests.

Moore, James W.↗
NASA NTRS2010

Collective Intelligence and Three Aspects of Planning in Organizations: A NASA Example

For many complex sociotechnical systems, planning seems to require explicit coordination; certainly, in executing a plan the activities of different actors must be tightly coupled. However, distributing the needed planning information can be very burdensome and error prone, because different groups need different collections of information, updated or kept current on different time cycles. Further, the information needed to form successful plans is often highly distributed, and while feedback about the success of prior plans may exist, it may not be available to those in a position of using this to improve plans or to detect and resolve other problems in the system (Weick, 1995). Tools to support various aspects of planning have been developed, and can provide a huge benefit to the individuals working on that aspect. To be tractable, most solutions address a quite bounded slice of work, isolating it from the larger context. Prospective planning takes place over multiple, nested cycles of decision making. This builds a plan that specifies activities of different granularity. "Subplans" may specify multiple parallel activities by different groups and individuals, as well as sequential, nested actions by a single actor. Planning produces valuable, sharable, external, representations: in addition to prospective use, plans support retrospective assessment and also action in the present. Viewing planning in a larger context - both temporal and organizational -- enables noticing what one does not know and generating more systemic and effective solutions. Viewing a problem as one of collective intelligence invites thinking about the larger organizational context. Many approaches to supporting collective intelligence do not support execution of highly contingent actions, distributed across many players, and hence provide incomplete support for planning. However, CI technology maybe helpful in managing the processes of gathering information for decision making in planning and of distributing plan information to various actors, needed on various time cycles.

Billman, Dorrit↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗
NASA NTRS2011

The Impact of Warm Pool El Nino Events on Antarctic Ozone

Warm pool El Nino (WPEN) events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific in austral spring and summer. Previous work found an enhancement in planetary wave activity in the South Pacific in austral spring, and a warming of 3-5 K in the Antarctic lower stratosphere during austral summer, in WPEN events as compared with ENSO neutral. In this presentation, we show that weakening of the Antarctic vortex during WPEN affects the structure and magnitude of high-latitude total ozone. We use total ozone data from TOMS and OMI, as well as station data from Argentina and Antarctica, to identify shifts in the longitudinal location of the springtime ozone minimum from its climatological position. In addition, we examine the sensitivity of the WPEN-related ozone response to the phase of the quasi-biennial oscillation (QBO). We then compare the observed response to WPEN events with Goddard Earth Observing System chemistry-climate model, version 2 (GEOS V2 CCM) simulations. Two, 50-year time-slice simulations are forced by annually repeating SST and sea ice climatologies, one set representing observed WPEN events and the second set representing neutral ENSO events, in a present-day climate. By comparing the two simulations, we isolate the impact of WPEN events on lower stratospheric ozone, and furthermore, examine the sensitivity of the WPEN ozone response to the phase of the QBO.

Hurwitz, Margaret M.↗
NASA NTRS2009

Tracking Vector Magnetograms with the Magnetic Induction Equation

The differential affine velocity estimator (DAVE) that we developed in 2006 for estimating velocities from line-of-sight magnetograms is modified to directly incorporate horizontal magnetic fields to produce a differential affine velocity estimator for vector magnetograms (DAVE4VM). The DAVE4VM's performance is demonstrated on the synthetic data from the anelastic pseudospectral ANMHD simulations that were used in the recent comparison of velocity inversion techniques by Welsch and coworkers. The DAVE4VM predicts roughly 95% of the helicity rate and 75% of the power transmitted through the simulation slice. Intercomparison between DAVE4VM and DAVE and further analysis of the DAVE method demonstrates that line-of-sight tracking methods capture the shearing motion of magnetic footpoints but are insensitive to flux emergence - the velocities determined from line-of-sight methods are more consistent with horizontal plasma velocities than with flux transport velocities. These results suggest that previous studies that rely on velocities determined from line-of-sight methods such as the DAVE or local correlation tracking may substantially misrepresent the total helicity rates and power through the photosphere.

Schuck, P.↗
NASA NTRS2006

"One-Stop Shopping" for Ocean Remote-Sensing and Model Data

OurOcean Portal 2.0 (http:// ourocean.jpl.nasa.gov) is a software system designed to enable users to easily gain access to ocean observation data, both remote-sensing and in-situ, configure and run an Ocean Model with observation data assimilated on a remote computer, and visualize both the observation data and the model outputs. At present, the observation data and models focus on the California coastal regions and Prince William Sound in Alaska. This system can be used to perform both real-time and retrospective analyses of remote-sensing data and model outputs. OurOcean Portal 2.0 incorporates state-of-the-art information technologies (IT) such as MySQL database, Java Web Server (Apache/Tomcat), Live Access Server (LAS), interactive graphics with Java Applet at the Client site and MatLab/GMT at the server site, and distributed computing. OurOcean currently serves over 20 real-time or historical ocean data products. The data are served in pre-generated plots or their native data format. For some of the datasets, users can choose different plotting parameters and produce customized graphics. OurOcean also serves 3D Ocean Model outputs generated by ROMS (Regional Ocean Model System) using LAS. The Live Access Server (LAS) software, developed by the Pacific Marine Environmental Laboratory (PMEL) of the National Oceanic and Atmospheric Administration (NOAA), is a configurable Web-server program designed to provide flexible access to geo-referenced scientific data. The model output can be views as plots in horizontal slices, depth profiles or time sequences, or can be downloaded as raw data in different data formats, such as NetCDF, ASCII, Binary, etc. The interactive visualization is provided by graphic software, Ferret, also developed by PMEL. In addition, OurOcean allows users with minimal computing resources to configure and run an Ocean Model with data assimilation on a remote computer. Users may select the forcing input, the data to be assimilated, the simulation period, and the output variables and submit the model to run on a backend parallel computer. When the run is complete, the output will be added to the LAS server for

Li, P. Peggy↗
NASA NTRS2011

New Insights in Tropospheric Ozone and its Variability

We have produced time-slice simulations using the Goddard Earth Observing System Version 5 (GEOS-5) coupled to a comprehensive stratospheric and tropospheric chemical mechanism. These simulations are forced with observed sea surface temperatures over the past 25 years and use constant specified surface emissions, thereby providing a measure of the dynamically controlled ozone response. We examine the model performance in simulating tropospheric ozone and its variability. Here we show targeted comparisons results from our simulations with a multi-decadal tropical tropospheric column ozone dataset obtained from satellite observations of total column ozone. We use SHADOZ ozonesondes to gain insight into the observed vertical response and compare with the simulated vertical structure. This work includes but is not limited to ENSO related variability.

Oman, Luke D.↗
NASA NTRS2011

Terahertz Computed Tomography of NASA Thermal Protection System Materials

A terahertz axial computed tomography system has been developed that uses time domain measurements in order to form cross-sectional image slices and three-dimensional volume renderings of terahertz-transparent materials. The system can inspect samples as large as 0.0283 cubic meters (1 cubic foot) with no safety concerns as for x-ray computed tomography. In this study, the system is evaluated for its ability to detect and characterize flat bottom holes, drilled holes, and embedded voids in foam materials utilized as thermal protection on the external fuel tanks for the Space Shuttle. X-ray micro-computed tomography was also performed on the samples to compare against the terahertz computed tomography results and better define embedded voids. Limits of detectability based on depth and size for the samples used in this study are loosely defined. Image sharpness and morphology characterization ability for terahertz computed tomography are qualitatively described.

Roth, D. J.↗
NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗