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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Relationship of Exercise, Age, and Gender on Decompression Sickness and Venous Gas Emboli During 2-Hour Oxygen Prebreathe Prior to Hypobaric Exposure

We evaluated four 2-hour oxygen prebreathe protocols combining adynamia (non-walking) and 4 different amounts of exercise for potential use with extravehicular activity (EVA) on the International Space Station. Phase I: upper and lower body exercises using dual-cycle ergometry (75% VO2 max for 10 min). Phase 11: same ergometry plus 24 min of light exercise that simulated space suit preparations. Phase III: same 24 min of light exercise but no ergometry, and Phase IV: 56 min of light exercise without ergometry. After 80 min on 100% O2, the subjects breathed 26.5% O2 - 73.5% N2 for 30 min at 10.2 psi. All subjects performed a series of upper body exercises from a recumbent position for 4 hrs at 4.3 psi to simulate EVA work. Venous gas emboli (VGE) were monitored every 12 min using precordial Doppler ultrasound. The 39 female and 126 male exposures were analyzed for correlations between decompression sickness (DCS) or VGE, and risk variables. The duration and quantity of exercise during prebreathe inversely relates to DCS and VGE incidence. The type and distribution of the 19 cases of DCS were similar to historical cases. There was no correlation of age, gender, body mass index, or fitness level with greater incidence of DCS or all VGE. However there were more Grade IV VGE in males > 40 years (10 of 19) than in those =< 40 years (3 of 107), with p<0.01 from Fisher's Exact Chi square The latency time for VGE was longer (103 min +/- 56 SD, n = 15 versus 53 min +/- 31, n =13) when the ergometry occurred about 15 min into the prebreathe than when performed at the start of the prebreathe, but the order of the ergometry did not influence the overall DCS and VGE incidence. An increasing amount of exercise during prebreathes reduced the risk of DCS during subsequent exposures to 4.3 psi. Age, gender, or fitness level did not correlate with the incidence of DCS or VGE (combination of Grades I-IV). However males greater than 40 years had a higher incidence of Grade IV VGE.

Conkin, J.↗
NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events, and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, enable detection of atmospheric features during daytime operations with a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗
NASA NTRS2008

Rescue Shuttle Flight Re-Entry: Controlling Astronaut Thermal Exposure

A rescue mission for the STS-125 Hubble Telescope Repair Mission requires reentry from space with 11 crew members aboard, exceeding past cabin thermal load experience and risking crew thermal stress potentially causing cognitive performance and physiological decrements. The space shuttle crew cabin air revitalization system (ARS) was designed to support a nominal crew complement of 4 to 7 crew and 10 persons in emergencies, all in a shirt-sleeve environment. Subsequent to the addition of full pressure suits with individual cooling units, the ARS cannot maintain a stable temperature in the crew cabin during reentry thermal loads. Bulk cabin thermal models, used for rescue mission planning and analysis of crew cabin air, were unable to accurately represent crew workstation values of air flow, carbon dioxide, and heat content for the middeck. Crew temperature models suggested significantly elevated core temperatures. Planning for an STS-400 potential rescue of seven stranded crew utilized computational fluid dynamics (CFD) models to demonstrate inhomogeneous cabin thermal properties and improve analysis compared to bulk models. In the absence of monitoring of crew temperature, heart rate, metabolic rate and incomplete engineering data on the performance of the integrated cooling garment/cooling unit (ICG/CU) at cabin temperatures above 75 degrees F, related systems & models were reevaluated and tests conducted with humans in the loop. Changes to the cabin ventilation, ICU placement, crew reentry suit-donning procedures, Orbiter Program wave-off policy and post-landing power down and crew extraction were adopted. A second CFD and core temperature model incorporated the proposed changes and confirmed satisfactory cabin temperature, improved air distribution, and estimated core temperatures within safe limits. CONCLUSIONS: These changes in equipment, in-flight and post-landing procedures, and policy were implemented for the STS-400 rescue shuttle & will be implemented in any future rescue flights from the International Space Station of stranded shuttle crews.

Gillis, David B.↗
NASA NTRS2011

Science Hybrid Orbiter and Lunar Relay (SCHOLR) Architecture and Design

Considered both a stepping-stone to deep space and a key to unlocking the mysteries of planetary formation, the Moon offers a unique opportunity for scientific study. Robotic precursor missions are being developed to improve technology and enable new approaches to exploration. Robots, lunar landers, and satellites play significant roles in advancing science and technologies, offering close range and in-situ observations. Science and exploration data gathered from these nodes and a lunar science satellite is intended to support future human expeditions and facilitate future utilization of lunar resources. To attain a global view of lunar science, the nodes will be distributed over the lunar surface, including locations on the far side of the Moon. Given that nodes on the lunar far side do not have direct line-of-sight for Earth communications, the planned presence of such nodes creates the need for a lunar communications relay satellite. Since the communications relay capability would only be required for a small portion of the satellite s orbit, it may be possible to include communication relay components on a science spacecraft. Furthermore, an integrated satellite has the potential to reduce lunar surface mission costs. A SCience Hybrid Orbiter and Lunar Relay (SCHOLR) is proposed to accomplish scientific goals while also supporting the communications needs of landers on the far side of the Moon. User needs and design drivers for the system were derived from the anticipated needs of future robotic and lander missions. Based on these drivers and user requirements, accommodations for communications payload aboard a science spacecraft were developed. A team of interns identified and compared possible SCHOLR architectures. The final SCHOLR architecture was analyzed in terms of orbiter lifetime, lunar surface coverage, size, mass, power, and communications data rates. This paper presents the driving requirements, operational concept, and architecture views for SCHOLR within a lunar surface nodal network. Orbital and bidirectional link analysis, between lunar nodes, orbiter, and Earth, as well as a conceptual design for the spacecraft are also presented

Trase, Kathryn K.↗
NASA NTRS2009

Damage Tolerance Testing of a NASA TransHab Derivative Woven Inflatable Module

Current options for Lunar habitat architecture include inflatable habitats and airlocks. Inflatable structures can have mass and volume advantages over conventional structures. However, inflatable structures carry different inherent risks and are at a lower Technical Readiness Level (TRL) than more conventional metallic structures. One of the risks associated with inflatable structures is in understanding the tolerance to induced damage. The Damage Tolerance Test (DTT) is designed to study the structural integrity of an expandable structure. TransHab (Figure 1) was an experimental inflatable module developed at the NASA/Johnson Space Center in the 1990 s. The TransHab design was originally envisioned for use in Mars Transits but was also studied as a potential habitat for the International Space Station (ISS). The design of the TransHab module was based on a woven design using an Aramid fabric. Testing of this design demonstrated a high level of predictability and repeatability with analytical predictions of stresses and deflections. Based on JSC s experience with the design and analysis of woven inflatable structures, the Damage Tolerance Test article was designed and fabricated using a woven design. The DTT article was inflated to 45 psig, representing 25% of the ultimate burst pressure, and one of the one-inch wide longitudinal structural members was severed by initiating a Linear Shaped Charge (LSC). Strain gage measurements, at the interface between the expandable elements (straps) and the nonexpandable metallic elements for pre-selected longitudinal straps, were taken throughout pressurization of the module and strap separation. Strain gage measurements show no change in longitudinal strap loading at the bulkhead interface after strap separation indicating loads in the restraint layer were re-distributed local to the damaged area due to the effects of friction under high internal pressure loading. The test completed all primary objectives with better than expected results. This paper will discuss space inflatable structures, damage tolerance analysis, test results, and applicability to the Lunar architecture.

Edgecombe, John↗
NASA NTRS2021

Satellite Remote Sensing Observations of Trans-Atlantic Dust Transport and Deposition: A Multi-Sensor Analysis

We analyze the decade-long (2007-2016) record of aerosol measurements from four distinctive sensors, namely CALIOP, MODIS, MISR, and IASI, to quantify the trans-Atlantic dust transport and deposition. These satellite sensors use different techniques to characterize particle size and shape properties; and we have developed sensor-specific methods (broadly categorized into size-based and shape-based method) to derive dust optical depth (DOD). The size-based DOD from MODIS and IASI generally agrees better with AERONET-derived DOD than the shape-based DOD from CALIOP and MISR does. Overall, the shape-based DOD is smaller than the size-based DOD by about 25%, which is consistent with distinctive ways of accounting for coarse-spherical particles of dust-pollution internal mixture. While such dust-pollution mixtures are counted as dust in the size-based DOD, they are excluded in the shape-based DOD. DOD is not a good proxy for dust deposition. Instead, the dust deposition depends strongly on the gradient of DOD on a monthly basis and can be derived by calculating the meridional and zonal dust mass flux based on the three-dimensional distributions of dust. Among the remote sensing measurements, difference in dust deposition is smaller than that of DOD, suggesting that different satellites characterize the DOD gradient more consistently than DOD itself. Satellite measurements of dust deposition and DOD also provide an accurate estimate of the dust loss frequency (LF) that measures how efficient the dust is removed from the atmosphere. We found that these remote sensing measurements yield similar LF values of 0.078 –0.102 d-1, which however is factors of 2-5 smaller than model simulations. This analysis provides valuable insights into potential deficiencies in models’ emission and transport/removal processes and hence helps guide model improvement.

remote sensing↗
NASA NTRS2017

International Space Station (ISS) Bacterial Filter Elements (BFEs): Filter Efficiency and Pressure Testing of Returned Units

The air revitalization system aboard the International Space Station (ISS) provides the vital function of maintaining a clean cabin environment for the crew and the hardware. This becomes a serious challenge in pressurized space compartments since no outside air ventilation is possible, and a larger particulate load is imposed on the filtration system due to lack of sedimentation due to the microgravity environment in Low Earth Orbit (LEO). The ISS Environmental Control and Life Support (ECLS) system architecture in the U.S. Segment uses a distributed particulate filtration approach consisting of traditional High-Efficiency Particulate Adsorption (HEPA) media filters deployed at multiple locations in each U.S. Segment module; these filters are referred to as Bacterial Filter Elements, or BFEs. These filters see a replacement interval, as part of maintenance, of 2-5 years dependent on location in the ISS. In this work, we present particulate removal efficiency, pressure drop, and leak test results for a sample set of 8 BFEs returned from the ISS after filter replacement. The results can potentially be utilized by the ISS Program to ascertain whether the present replacement interval can be maintained or extended to balance the on-ground filter inventory with extension of the lifetime of ISS beyond 2024. These results can also provide meaningful guidance for particulate filter designs under consideration for future deep space exploration missions.

Filtration↗
NASA NTRS1999

Microgravity Experiments to Evaluate Electrostatic Forces in Controlling Cohesion and Adhesion of Granular Materials

The bulk behavior of dispersed, fluidized, or undispersed stationary granular systems cannot be fully understood in terms of adhesive/cohesive properties without understanding the role of electrostatic forces acting at the level of the grains themselves. When grains adhere to a surface, or come in contact with one another in a stationary bulk mass, it is difficult to measure the forces acting on the grains, and the forces themselves that induced the cohesion and adhesion are changed. Even if a single gain were to be scrutinized in the laboratory, it might be difficult, perhaps impossible, to define the distribution and character of surface charging and the three- dimensional relationship that charges (electrons, holes) have to one another. The hypothesis that we propose to test in microgravity (for dielectric materials) is that adhesion and cohesion of granular matter are mediated primarily by dipole forces that do not require the presence of a net charge; in fact, nominally electrically neutral materials should express adhesive and cohesive behavior when the neutrality results from a balance of positive and negative charge carriers. Moreover, the use of net charge alone as a measure of the electrical nature of grain-to-grain relationships within a granular mass may be misleading. We believe that the dipole forces arise from the presence of randomly-distributed positive and negative fixed charge carriers on grains that give rise to a resultant dipole moment. These dipole forces have long-range attraction. Random charges are created whenever there is triboelectrical activity of a granular mass, that is, whenever the grains experience contact/separation sequences or friction. Electrostatic forces are generally under-estimated for their role in causing agglomeration of dispersed grains in particulate clouds, or their role in affecting the internal frictional relationships in packed granular masses. We believe that electrostatic, in particular dipole-mediated processes, are pervasive and probably affect, at some level, everything from astrophysical-scale granular systems such as interstellar nebulae, protoplanetary dust and debris disks, planetary-scale systems such as debris palls from meteorite impact, volcanic eruptions, and aeolian dust storms, all the way to industrial-scale systems in mining, powder and grain processing, pharmaceuticals, and smoke-stack technologies. NASA must concern itself with the electrostatic behavior of dust and sand on Mars because of its potentially critical importance to human exploration. The motion and adhesion of martian surface materials will affect the design and performance of spacesuits, habitats, processing plants, solar panels, and any externally exposed equipment such as surface rovers or communication and weather stations. Additionally, the adhesion of dust and sand could greatly enhance contact with the potentially toxic components of the martian soil.

Marshall, J.↗
NASA NTRS2015

IceCube: CubeSat 883-GHz Radiometry for Future Ice Cloud Remote Sensing

Ice clouds play a key role in the Earth's radiation budget, mostly through their strong regulation of infrared radiation exchange. Accurate observations of global cloud ice and its distribution have been a challenge from space, and require good instrument sensitivities to both cloud mass and microphysical properties. Despite great advances from recent spaceborne radar and passive sensors, uncertainty of current ice water path (IWP) measurements is still not better than a factor of 2. Submillimeter (submm) wave remote sensing offers great potential for improving cloud ice measurements, with simultaneous retrievals of cloud ice and its microphysical properties. The IceCube project is to enable this cloud ice remote sensing capability in future missions, by raising 874-GHz receiver technology TRL from 5 to 7 in a spaceflight demonstration on 3-U CubeSat in a low Earth orbit (LEO) environment. The NASAs Goddard Space Flight Center (GSFC) is partnering with Virginia Diodes Inc (VDI) on the 874-GHz receiver through its Vector Network Analyzer (VNA) extender module product line, to develop an instrument with precision of 0.2 K over 1-second integration and accuracy of 2.0 K or better. IceCube is scheduled to launch to and subsequent release from the International Space Station (ISS) in mid-2016 for nominal operation of 28 plus days. We will present the updated design of the payload and spacecraft systems, as well as the operation concept. We will also show the simulated 874-GHz radiances from the ISS orbits and cloud scattering signals as expected for the IceCube cloud radiometer.

cloud ice remote sensing↗
NASA NTRSDate not supplied

Constraints on the Origin of Mercury’s Large Core from Core-Mantle Differentiation Models

Mercury’s core is notoriously large when compared to other planets of our solar system. The origin of this large core is still uncertain. Available data on the surface composition and internal structure of Mercury from the past MESSENGER mission and future data collected by BepiColombo will continue to provide clues to Mercury’s formation. Here, we present results combining experimental data on elemental distribution between core and mantle with spacecraft data, to estimate bulk Mercury composition. We applied this strategy to major elements (Fe, Si, Mg, Al and O), as well as minor elements (Cr and Ti), and compared derived compositions to chondritic data and the chemical compositions of the other terrestrial planets. Our results show that Mercury has a chemical composition significantly different from all known materials of the solar system. In addition, numerous scenarios were proposed to explain Mercury’s structure, including “chaotic models” such as giant impacts and “orderly models” such as aerodynamic sorting. Here, we tested whether Mercury’s composition can be explained by mantle stripping by impacts. We will show how such a scenario reconciles several features of Mercury’s geochemistry with chondritic data. We will also discuss the outlook of additional constraints from supplementary data potentially collected by BepiColombo.

Mercury↗
NASA NTRSDate not supplied

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗
NASA NTRS2009

CCSDS Spacecraft Monitor and Control Mission Operations Interoperability Prototype

We are entering a new era in space exploration. Reduced operating budgets require innovative solutions to leverage existing systems to implement the capabilities of future missions. Custom solutions to fulfill mission objectives are no longer viable. Can NASA adopt international standards to reduce costs and increase interoperability with other space agencies? Can legacy systems be leveraged in a service oriented architecture (SOA) to further reduce operations costs? The Operations Technology Facility (OTF) at the Johnson Space Center (JSC) is collaborating with Deutsches Zentrum fur Luft- und Raumfahrt (DLR) to answer these very questions. The Mission Operations and Information Management Services Area (MOIMS) Spacecraft Monitor and Control (SM&C) Working Group within the Consultative Committee for Space Data Systems (CCSDS) is developing the Mission Operations standards to address this problem space. The set of proposed standards presents a service oriented architecture to increase the level of interoperability among space agencies. The OTF and DLR are developing independent implementations of the standards as part of an interoperability prototype. This prototype will address three key components: validation of the SM&C Mission Operations protocol, exploration of the Object Management Group (OMG) Data Distribution Service (DDS), and the incorporation of legacy systems in a SOA. The OTF will implement the service providers described in the SM&C Mission Operation standards to create a portal for interaction with a spacecraft simulator. DLR will implement the service consumers to perform the monitor and control of the spacecraft. The specifications insulate the applications from the underlying transport layer. We will gain experience with a DDS transport layer as we delegate responsibility to the middleware and explore transport bridges to connect disparate middleware products. A SOA facilitates the reuse of software components. The prototype will leverage the capabilities of existing legacy systems. Various custom applications and middleware solutions will be combined into one system providing the illusion of a set of homogenous services. This paper will document our journey as we implement the interoperability prototype. The team consists of software engineers with experience on the current command, telemetry and messaging systems that support the International Space Station (ISS) and Space Shuttle programs. Emphasis will be on the objectives, results and potential cost saving benefits.

Lucord, Steve↗
NASA NTRSDate not supplied

Calcium and Magnesium Distribution Between Sulfide and Silicate Melts: Thermodynamic Modeling and Insights into Mercury's Mantle-Crust Differentiation

Mercury stands out as the terrestrial planet with the lowest degree of oxidation among all planets of our solar system. It is characterized by a high abundance of sulfur, which is expected to replace oxygen in silicate melts. This sulfur enrichment could lead to sulfide saturation in its mantle, potentially resulting in the formation of sulfides rich in calcium and magnesium. Utilizing experimental data from the literature, we constructed a thermodynamic model to explore the partitioning of calcium and magnesium between sulfide and silicate melts. This model aims to improve our comprehension of the chemical equilibria driving the process of mantle-crust differentiation on Mercury. Our models indicate that increased temperature, decreased pressure, and low concentrations of iron, oxygen, and carbon within the sulfide phase, along with low sulfur concentrations in the silicate phase, favor calcium’s partitioning into the sulfide. Additionally, magnesium partitioning into the sulfide melt is favored with decreased pressure, decreased temperature, low concentrations of iron and calcium within the sulfide, and low concentrations of sulfur within the silicate. Our results suggest that up 9.4% and 5.6% Ca and Mg, respectively, can be present in sulfides equilibrated with sulfide-saturated silicate melts during mantle-crust differentiation. Further investigation will focus on the distribution of sulfide phases within the mantle and crust to better constrain Mercury’s internal structure.

Taylor McCombs↗
NASA NTRS2014

Ionosphere Plasma State Determination in Low Earth Orbit from International Space Station Plasma Monitor

A plasma diagnostic package is deployed on the International Space Station (ISS). The system - a Floating Potential Measurement Unit (FPMU) - is used by NASA to monitor the electrical floating potential of the vehicle to assure astronaut safety during extravehicular activity. However, data from the unit also reflects the ionosphere state and seems to represent an unutilized scientific resource in the form of an archive of scientific plasma state data. The unit comprises a Floating Potential probe and two Langmuir probes. There is also an unused but active plasma impedance probe. The data, at one second cadence, are collected, typically for a two week period surrounding extravehicular activity events. Data is also collected any time a visiting vehicle docks with ISS and also when any large solar events occur. The telemetry system is unusual because the package is mounted on a television camera stanchion and its data is impressed on a video signal that is transmitted to the ground and streamed by internet to two off center laboratory locations. The data quality has in the past been challenged by weaknesses in the integrated ground station and distribution systems. These issues, since mid‐2010, have been largely resolved and the ground stations have been upgraded. Downstream data reduction has been developed using physics based modeling of the electron and ion collecting character in the plasma. Recursive algorithms determine plasma density and temperature from the raw Langmuir probe current voltage sweeps and this is made available in real time for situational awareness. The purpose of this paper is to describe and record the algorithm for data reduction and to show that the Floating probe and Langmuir probes are capable of providing long term plasma state measurement in the ionosphere. Geophysical features such as the Appleton anomaly and high latitude modulation at the edge of the Auroral zones are regularly observed in the nearly circular, 51 deg inclined, 400 km altitude ISS orbit. Evidence of waves in the ion collection current data is seen in geographic zones known to exhibit the spread‐F phenomenon. An anomaly in the current collection characteristic of the cylindrical probe appears also too be organized by the geomagnetic field.

Kramer, Leonard↗
NASA NTRS1997

An Automated Method for Identifying Inconsistencies within Diagrammatic Software Requirements Specifications

The development of large-scale, composite software in a geographically distributed environment is an evolutionary process. Often, in such evolving systems, striving for consistency is complicated by many factors, because development participants have various locations, skills, responsibilities, roles, opinions, languages, terminology and different degrees of abstraction they employ. This naturally leads to many partial specifications or viewpoints. These multiple views on the system being developed usually overlap. From another aspect, these multiple views give rise to the potential for inconsistency. Existing CASE tools do not efficiently manage inconsistencies in distributed development environment for a large-scale project. Based on the ViewPoints framework the WHERE (Web-Based Hypertext Environment for requirements Evolution) toolkit aims to tackle inconsistency management issues within geographically distributed software development projects. Consequently, WHERE project helps make more robust software and support software assurance process. The long term goal of WHERE tools aims to the inconsistency analysis and management in requirements specifications. A framework based on Graph Grammar theory and TCMJAVA toolkit is proposed to detect inconsistencies among viewpoints. This systematic approach uses three basic operations (UNION, DIFFERENCE, INTERSECTION) to study the static behaviors of graphic and tabular notations. From these operations, subgraphs Query, Selection, Merge, Replacement operations can be derived. This approach uses graph PRODUCTIONS (rewriting rules) to study the dynamic transformations of graphs. We discuss the feasibility of implementation these operations. Also, We present the process of porting original TCM (Toolkit for Conceptual Modeling) project from C++ to Java programming language in this thesis. A scenario based on NASA International Space Station Specification is discussed to show the applicability of our approach. Finally, conclusion and future work about inconsistency management issues in WHERE project will be summarized.

Zhang, Zhong↗
NASA NTRS1998

Verification of Space Station Secondary Power System Stability Using Design of Experiment

This paper describes analytical methods used in verification of large DC power systems with applications to the International Space Station (ISS). Large DC power systems contain many switching power converters with negative resistor characteristics. The ISS power system presents numerous challenges with respect to system stability such as complex sources and undefined loads. The Space Station program has developed impedance specifications for sources and loads. The overall approach to system stability consists of specific hardware requirements coupled with extensive system analysis and testing. Testing of large complex distributed power systems is not practical due to size and complexity of the system. Computer modeling has been extensively used to develop hardware specifications as well as to identify system configurations for lab testing. The statistical method of Design of Experiments (DoE) is used as an analysis tool for verification of these large systems. DOE reduces the number of computer runs which are necessary to analyze the performance of a complex power system consisting of hundreds of DC/DC converters. DoE also provides valuable information about the effect of changes in system parameters on the performance of the system. DoE provides information about various operating scenarios and identification of the ones with potential for instability. In this paper we will describe how we have used computer modeling to analyze a large DC power system. A brief description of DoE is given. Examples using applications of DoE to analysis and verification of the ISS power system are provided.

Karimi, Kamiar J.↗
NASA NTRS1996

Accurate Predictions of Mean Geomagnetic Dipole Excursion and Reversal Frequencies, Mean Paleomagnetic Field Intensity, and the Radius of Earth's Core Using McLeod's Rule

The geomagnetic spatial power spectrum R(sub n)(r) is the mean square magnetic induction represented by degree n spherical harmonic coefficients of the internal scalar potential averaged over the geocentric sphere of radius r. McLeod's Rule for the magnetic field generated by Earth's core geodynamo says that the expected core surface power spectrum (R(sub nc)(c)) is inversely proportional to (2n + 1) for 1 less than n less than or equal to N(sub E). McLeod's Rule is verified by locating Earth's core with main field models of Magsat data; the estimated core radius of 3485 kn is close to the seismologic value for c of 3480 km. McLeod's Rule and similar forms are then calibrated with the model values of R(sub n) for 3 less than or = n less than or = 12. Extrapolation to the degree 1 dipole predicts the expectation value of Earth's dipole moment to be about 5.89 x 10(exp 22) Am(exp 2)rms (74.5% of the 1980 value) and the expected geomagnetic intensity to be about 35.6 (mu)T rms at Earth's surface. Archeo- and paleomagnetic field intensity data show these and related predictions to be reasonably accurate. The probability distribution chi(exp 2) with 2n+1 degrees of freedom is assigned to (2n + 1)R(sub nc)/(R(sub nc). Extending this to the dipole implies that an exceptionally weak absolute dipole moment (less than or = 20% of the 1980 value) will exist during 2.5% of geologic time. The mean duration for such major geomagnetic dipole power excursions, one quarter of which feature durable axial dipole reversal, is estimated from the modern dipole power time-scale and the statistical model of excursions. The resulting mean excursion duration of 2767 years forces us to predict an average of 9.04 excursions per million years, 2.26 axial dipole reversals per million years, and a mean reversal duration of 5533 years. Paleomagnetic data show these predictions to be quite accurate. McLeod's Rule led to accurate predictions of Earth's core radius, mean paleomagnetic field intensity, and mean geomagnetic dipole power excursion and axial dipole reversal frequencies. We conclude that McLeod's Rule helps unify geo-paleomagnetism, correctly relates theoretically predictable statistical properties of the core geodynamo to magnetic observation, and provides a priori information required for stochastic inversion of paleo-, archeo-, and/or historical geomagnetic measurements.

Voorhies, Coerte V.↗
NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, (1) increased the 1064 nm SNR by 75%, (2) increased the number of layers detected (any resolution) by 30%, and (3) enabled detection of 40% more atmospheric features during daytime operations at a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS operational data products. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗