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NASA NTRS2024

Automated Detection of Spurious Signals in VLBI Phase Calibration Data

In this memorandum, a set of processing strategies for automatic masking of phase calibration tones is outlined as implemented in the software package PIMA in the task Generate Phase Calibration Mask, or GEPM. The task relies on a robust procedure of cleaning phase calibration data before employing several mathematical strategies designed to selectively identify spurious signals from phase calibration tones. These strategies were derived as more rigorous implementations of heuristics traditionally used by analysts in manually identifying problematic phase calibration data. The task is intended to automate the process of generating a phase calibration mask and in so doing increase the speed and regularity of VLBI analysis. At the outset of the project, a series of goals were identified to evaluate the success of this mask generation. This included the development of an algorithm to identify and mask short-term (defined as less than 10 seconds in length) spurious signals affecting phase calibration data, the development of an algorithm to identify and mask phase calibration tones affected by constant radio-frequency interference, the implementation of a detection scheme for identifying large jumps in phase calibration phase caused by clock breaks, and finally a method of reporting phase calibration health metrics to the user. Processing of over 10 experiments has demonstrated that the final form of the task GEPM as detailed in this technical memorandum satisfies each of these conditions and satisfactorily performs the task of automatic phase calibration data masking, although the wide variety in quality and characteristics of phase calibration data makes a single solution to the problem quite difficult. A series of user inputs have therefore been defined to assist analysts in tailoring automatic masking to specific stations and phase calibration generators. The vast majority of applicable code was written in FORTRAN to increase execution speed and ease of interfacing with the existing code base in PIMA, but a wrapper function in Python was also written to allow for a simpler method of interacting with GEPM and inputting relevant parameters. In addition to this report, thorough documentation was added to the already existing repositories associated with PIMA as a whole.

Geodesy↗

NASA NTRS2001

Development of a Space Radiation Monte-Carlo Computer Simulation Based on the FLUKE and Root Codes

The radiation environment in space is a complex problem to model. Trying to extrapolate the projections of that environment into all areas of the internal spacecraft geometry is even more daunting. With the support of our CERN colleagues, our research group in Houston is embarking on a project to develop a radiation transport tool that is tailored to the problem of taking the external radiation flux incident on any particular spacecraft and simulating the evolution of that flux through a geometrically accurate model of the spacecraft material. The output will be a prediction of the detailed nature of the resulting internal radiation environment within the spacecraft as well as its secondary albedo. Beyond doing the physics transport of the incident flux, the software tool we are developing will provide a self-contained stand-alone object-oriented analysis and visualization infrastructure. It will also include a graphical user interface and a set of input tools to facilitate the simulation of space missions in terms of nominal radiation models and mission trajectory profiles. The goal of this project is to produce a code that is considerably more accurate and user-friendly than existing Monte-Carlo-based tools for the evaluation of the space radiation environment. Furthermore, the code will be an essential complement to the currently existing analytic codes in the BRYNTRN/HZETRN family for the evaluation of radiation shielding. The code will be directly applicable to the simulation of environments in low earth orbit, on the lunar surface, on planetary surfaces (including the Earth) and in the interplanetary medium such as on a transit to Mars (and even in the interstellar medium). The software will include modules whose underlying physics base can continue to be enhanced and updated for physics content, as future data become available beyond the timeframe of the initial development now foreseen. This future maintenance will be available from the authors of FLUKA as part of their continuing efforts to support the users of the FLUKA code within the particle physics community. In keeping with the spirit of developing an evolving physics code, we are planning as part of this project, to participate in the efforts to validate the core FLUKA physics in ground-based accelerator test runs. The emphasis of these test runs will be the physics of greatest interest in the simulation of the space radiation environment. Such a tool will be of great value to planners, designers and operators of future space missions, as well as for the design of the vehicles and habitats to be used on such missions. It will also be of aid to future experiments of various kinds that may be affected at some level by the ambient radiation environment, or in the analysis of hybrid experiment designs that have been discussed for space-based astronomy and astrophysics. The tool will be of value to the Life Sciences personnel involved in the prediction and measurement of radiation doses experienced by the crewmembers on such missions. In addition, the tool will be of great use to the planners of experiments to measure and evaluate the space radiation environment itself. It can likewise be useful in the analysis of safe havens, hazard migration plans, and NASA's call for new research in composites and to NASA engineers modeling the radiation exposure of electronic circuits. This code will provide an important complimentary check on the predictions of analytic codes such as BRYNTRN/HZETRN that are presently used for many similar applications, and which have shortcomings that are more easily overcome with Monte Carlo type simulations. Finally, it is acknowledged that there are similar efforts based around the use of the GEANT4 Monte-Carlo transport code currently under development at CERN. It is our intention to make our software modular and sufficiently flexible to allow the parallel use of either FLUKA or GEANT4 as the physics transport engine.

Pinsky, L. S.↗

NASA NTRS2002

An expert system for fault management assistance on a space sleep experiment

The expert system, Principal Investigator-in-a-box, or [PI], was designed to assist astronauts or other operators in performing experiments outside their expertise. Currently, the software helps astronauts calibrate instruments for a Sleep and Respiration Experiment without contact with the investigator on the ground. It flew on the Space Shuttle missions STS-90 and STS-95. [PI] displays electrophysiological signals in real time, alerts astronauts via the indicator lights when a poor signal quality is detected, and advises astronauts how to restore good signal quality. Thirty subjects received training on the sleep instrumentation and the [PI] interface. A beneficial effects of [PI] and training reduced troubleshooting time. [PI] benefited subjects on the most difficult scenarios, even though its lights were not 100% accurate. Further, questionnaires showed that most subjects preferred monitoring waveforms with [PI] assistance rather than monitoring waveforms alone. This study addresses problems of complex troubleshooting and the extended time between training and execution that is common to many human operator situations on earth such as in power plant operation, and marine exploration.

NASA Discipline Neuroscience↗

NASA NTRS2014

NASA Wearable Technology CLUSTER 2013-2014 Report

Wearable technology has the potential to revolutionize the way humans interact with one another, with information, and with the electronic systems that surround them. This change can already be seen in the dramatic increase in the availability and use of wearable health and activity monitors. These devices continuously monitor the wearer using on-‐body sensors and wireless communication. They provide feedback that can be used to improve physical health and performance. Smart watches and head mounted displays are also receiving a great deal of commercial attention, providing immediate access to information via graphical displays, as well as additional sensing features. For the purposes of the Wearable Technology CLUSTER, wearable technology is broadly defined as any electronic sensing, human interfaces, computing, or communication that is mounted on the body. Current commercially available wearable devices primarily house electronics in rigid packaging to provide protection from flexing, moisture, and other contaminants. NASA mentors are interested in this approach, but are also interested in direct integration of electronics into clothing to enable more comfortable systems. For human spaceflight, wearable technology holds a great deal of promise for significantly improving safety, efficiency, autonomy, and research capacity for the crew in space and support personnel on the ground. Specific capabilities of interest include: Continuous biomedical monitoring for research and detection of health problems. Environmental monitoring for individual exposure assessments and alarms. Activity monitoring for responsive robotics and environments. Multi-modal caution and warning using tactile, auditory, and visual alarms. Wireless, hands-free, on-demand voice communication. Mobile, on-demand access to space vehicle and robotic displays and controls. Many technical challenges must be overcome to realize these wearable technology applications. For example, to make a wearable device that is both functional and comfortable for long duration wear, developers must strive to reduce electronic mass and volume while also addressing constraints imposed by the body attachment method. Depending on the application, the device must be placed in a location that the user can see and reach, and that provides the appropriate access to air and the wearer's skin. Limited power is available from body-‐worn batteries and heat must be managed to prevent discomfort. If the clothing is to be washed, there are additional durability and washability hurdles that traditional electronics are not designed to address. Finally, each specific capability has unique technical challenges that will likely require unique solutions. In addition to the technical challenges, development of wearable devices is made more difficult by the diversity of skills required and the historic lack of collaboration across domains. Wearable technology development requires expertise in textiles engineering, apparel design, software and computer engineering, electronic design and manufacturing, human factors engineering, and application-‐specific fields such as acoustics, medical devices, and sensing. Knowledge from each of these domains must be integrated to create functional and comfortable devices. For this reason, the diversity of knowledge and experience represented in the Wearable Technology is critical to overcoming the fundamental challenges in the field.

Simon, Cory↗

NASA NTRS1993

RAID 7 disk array

Each RAID level reflects a different design architecture. Associated with each is a backdrop of imposed limitations, as well as possibilities which may be exploited within the architectural constraints of that level. There are three unique features that differentiate RAID 7 from all other levels. RAID 7 is asynchronous with respect to usage of I/O data paths. Each I/O drive (includes all data and one parity drives) as well as each host interface (there may be multiple host interfaces) has independent control and data paths. This means that each can be accessed completely, independently, of the other. This is facilitated by a separate device cache for each device/interface as well. RAID 7 is asynchronous with respect to device hierarchy and data bus utilization. Each drive and each interface is connected to a high speed data bus controlled by the embedded operating system to make independent transfers to and from central cache. RAID 7 is asynchronous with respect to the operation of an embedded real time process oriented operating system. This means that exclusive and independent of the host, or multiple host paths, the embedded OS manages all I/O transfers asynchronously across the data and parity drives. A key factor to consider is that of the RAID 7's ability to anticipate and match host I/O usage patterns. This yields the following benefits over RAID's built around micro-code based architectures. RAID 7 appears to the host as a normally connected Big Fast Disk (BFD). RAID 7 appears, from the perspective of the individual disk devices, to minimize the total number of accesses and optimize read/write transfer requests. RAID 7 smoothly integrates the random demands of independent users with the principles of spatial and temporal locality. This optimizes small, large, and time sequenced I/O requests which results in users having an I/O performance which approaches performance to that of main memory.

Stout, Lloyd↗

NASA NTRS2017

SLS Payload Transportation Beyond LEO

NASA has successfully completed the Critical Design Review (CDR) of the heavy lift Space Launch System (SLS) and is working towards the first flight of the vehicle in 2018. SLS will begin flying crewed missions with an Orion capsule to the lunar vicinity every year after the first 2 flights starting in the early 2020's. As early as 2021, in addition to delivering an Orion capsule to a cislunar destination, SLS will also deliver ancillary payload, termed "Co-manifested Payload (CPL)", with a mass of at least 5.5 mT and volume up to 280 m3 simultaneously to that same destination. Later SLS flights have a goal of delivering as much as 10 mT of CPL to cislunar destinations. In addition to cislunar destinations, SLS flights may deliver non-crewed, science-driven missions with Primary Payload (PPL) to more distant destinations. SLS PPL missions will utilize a unique payload fairing offering payload volume (ranging from 320 m3 to 540 m3) that greatly exceeds the largest existing Expendable Launch Vehicle (ELV) fairing available. The Characteristic Energy (C3) offered by the SLS system will generate opportunities to deliver up to 40 mT to cislunar space, and deliver double PPL mass or de-crease flight time by half for some outer planet destinations when compared to existing capabilities. For example, SLS flights may deliver the Europa Clipper to a Jovian destination in under 3 years by the mid 2020's, compared to the 7+ years cruise time required for current launch capabilities. This presentation will describe ground and flight accommodations, interfaces, resources, and performance planned to be made available to potential CPL and PPL science users of SLS. In addition, this presentation should promote a dialogue between vehicle developers, potential payload users, and funding sources in order to most efficiently evolve required SLS capabilities to meet diverse payload needs as they are identified over the next 35 years and beyond.

Creech, S. D.↗

NASA NTRS1999

Development and Performance of the ACTS High Speed VSAT

The Advanced Communication Technology Satellite (ACTS), developed by the U.S. National Aeronautics and Space Administration (NASA) has demonstrated the breakthrough technologies of Ka-band, spot beam antennas, and on-board processing. These technologies have enabled the development of very small aperture terminals (VSAT) and ultra-small aperture terminals (USAT) which have capabilities greater than were previously possible with conventional satellite technologies. However, the ACTS baseband processor (BBP) is designed using a time division multiple access (TDMA) scheme, which requires each earth station using the BBP to transmit data at a burst rate which is much higher than the user throughput data rate. This tends to mitigate the advantage of the new technologies by requiring a larger earth station antenna and/or a higher-powered uplink amplifier than would be necessary for a continuous transmission at the user data rate. Conversely, the user data rate is much less than the rate that can be supported by the antenna size and amplifier. For example, the ACTS TI VSAT operates at a burst rate of 27.5 Mbps, but the maximum user data rate is 1.792 Mbps. The throughput efficiency is slightly more than 6.5%. For an operational network, this level of overhead will greatly increase the cost of the user earth stations, and that increased cost must be repeated thousands of times, which may ultimately reduce the market for such a system. The ACTS High Speed VSAT (HS VSAT) is an effort to experimentally demonstrate the maximum user throughput data rate which can be achieved using the technologies developed and implemented on ACTS. Specifically, this was done by operating the system uplinks as frequency division multiple access (FDMA), essentially assigning all available TDMA time slots to a single user on each of two uplink frequencies. Preliminary results show that using a 1.2-m antenna in this mode, the HS VSAT can achieve between 22 and 24 Mbps out of the 27.5 Mbps burst rate, for a throughput efficiency of 80-88%. This paper describes the modifications made to the TI VSAT to enable it to operate at high speed, including hardware considerations, interface modifications, and software modifications. In addition, it describes the results of NASA HS VSAT experiments, continuing work on an improved user interface, and plans for future experiments.

Quintana, J.↗

NASA NTRS2010

Overview of the Graphical User Interface for the GERMcode (GCR Event-Based Risk Model)

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERMcode calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERMcode also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERMcode for application to thick target experiments. The GERMcode provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERMcode GUI, as well as providing training applications.

Kim, Myung-Hee Y.↗

NASA NTRSDate not supplied

Early Artemis Surface Navigation: Challenges, Approaches, and Opportunities

The early Artemis missions represent the return of humanity to the surface of the Moon and provide opportunities for meeting early science and exploration goals. Position, Navigation, and Timing (PNT) capabilities are a fundamental element and inform operational design, flight rules, and the ability to meet these. This paper provides an overview of the needs, potential implementations, challenges, and concepts of operations in the initial human surface missions, Artemis III and IV. These early excursions are a crucial learning opportunity to gain more experience in the actual operational environment for Artemis V and beyond where exploration objectives and complexity increases. As part of the study, the team defined a threshold performance navigation requirement (including position and orientation) to meet crew safe return and assessed a breadth of navigation approaches that could be deployed to augment the crew’s baseline navigation capability. Data was collected in terms of size, mass, power, operational constraints, environment constraints, interface, and performance to define the technical metrics. Given these, the trade team conducted polling among the various Artemis Campaign elements to capture preference, integration challenges, and operational impacts. These were used to develop weightings and inform a ranked order of solutions across each of the early missions. The results of the study recommended augmenting the initial orientation capability with additional navigation sensors to provide coarse position and heading information to the crew to enable a safe contingency walk-back when out of video range. The team identified opportunities for embedding this hardware in future scenarios to provide an integrated solution. With the deployment of the LunaNet’s Lunar Augmented Navigation System, the crew will be able to maintain accurate real-time navigation knowledge with minimal physical impacts. Discussion of future testing and continued analysis is included in this paper. These forward plans and long-term architecture systems will enable a powerful navigation approach for orbiting and surface users, enabling a high level of scientific return and crew safety.

Evan Anzalone↗

NASA NTRSDate not supplied

Early Artemis Surface Navigation: Challenges, Approaches, and Opportunities

Evan Anzalone↗

NASA NTRS2010

Overview of the Graphical User Interface for the GERM Code (GCR Event-Based Risk Model

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERM code calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERM code also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERM code accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERM code for application to thick target experiments. The GERM code provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERM code GUI, as well as providing training applications.

Kim, Myung-Hee↗

NASA NTRS2011

Development of the Sasquatch Drop Test Footprint Tool

The Crew Exploration Vehicle Parachute Assembly System (CPAS) is the parachute system for NASA s Orion spacecraft. CPAS is currently in the design and testing phase of development. The test program consists of numerous drop tests, wherein a test article rigged with parachutes is extracted or released from an aircraft. During such tests, range safety is paramount, as is the recoverability of the parachutes and test article. It is crucial to establish an aircraft release point that will ensure that the article and all items released from it will land in safe locations. Early in the CPAS project, a legacy tool (previously used on the X-38 project) was used to determine a safe release point and to predict the landing locations (the footprint) of the payload and all released objects. Due to increasing test complexity and the need for a more flexible tool, a new footprint predictor tool, called Sasquatch, was created in MATLAB. This tool takes in a simulated trajectory for the test article, information about all released objects, and atmospheric wind data (simulated or actual) to calculate the trajectories of the released objects. Dispersions are applied to the landing locations of those objects, taking into account the variability of winds, aircraft release point, and object descent rate. A safe aircraft release point is determined based on the landing locations of the payload and released objects. The release point, landing locations, and dispersions are plotted on a simple map of the drop zone for easy reference. To date, Sasquatch has been used for thirteen drop tests. Comparing the predictions with actual test results has allowed for significant improvements in the tool s predictive capabilities, especially the incorporation of a well-correlated horizontal throw model. Intended future improvements to the tool include tighter dispersions on the landing locations, Monte Carlo capability, direct input from trajectory simulations, and a graphical user interface.

Bledsoe, Kristin J.↗

NASA NTRSDate not supplied

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗

NASA NTRS2015

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗

NASA NTRS2011

Intelligent Wireless Sensor Networks for System Health Monitoring

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of PAN configuration, providing the appropriate response for maintaining overall sensor system function, even when sensor modules fail or the WSN is reconfigured. The session will present the architecture and technical feasibility of creating fault-tolerant WSNs for aerospace applications based on our application of the technology to a Structural Health Monitoring testbed. The interim results of WSN development and testing including our software architecture for intelligent sensor management will be discussed in the context of the specific tradeoffs required for effective use. Initial certification measurement techniques and test results gauging WSN susceptibility to Radio Frequency interference are introduced as key challenges for technology adoption. A candidate Developmental and Flight Instrumentation implementation using intelligent sensor networks for wind tunnel and flight tests is developed as a guide to understanding key aspects of the aerospace vehicle design, test and operations life cycle.

networks↗

NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗

NASA NTRS2011

Asynchronous Message Service Reference Implementation

This software provides a library of middleware functions with a simple application programming interface, enabling implementation of distributed applications in conformance with the CCSDS AMS (Consultative Committee for Space Data Systems Asynchronous Message Service) specification. The AMS service, and its protocols, implement an architectural concept under which the modules of mission systems may be designed as if they were to operate in isolation, each one producing and consuming mission information without explicit awareness of which other modules are currently operating. Communication relationships among such modules are self-configuring; this tends to minimize complexity in the development and operations of modular data systems. A system built on this model is a society of generally autonomous, inter-operating modules that may fluctuate freely over time in response to changing mission objectives, modules functional upgrades, and recovery from individual module failure. The purpose of AMS, then, is to reduce mission cost and risk by providing standard, reusable infrastructure for the exchange of information among data system modules in a manner that is simple to use, highly automated, flexible, robust, scalable, and efficient. The implementation is designed to spawn multiple threads of AMS functionality under the control of an AMS application program. These threads enable all members of an AMS-based, distributed application to discover one another in real time, subscribe to messages on specific topics, and to publish messages on specific topics. The query/reply (client/server) communication model is also supported. Message exchange is optionally subject to encryption (to support confidentiality) and authorization. Fault tolerance measures in the discovery protocol minimize the likelihood of overall application failure due to any single operational error anywhere in the system. The multi-threaded design simplifies processing while enabling application nodes to operate at high speeds; linked lists protected by mutex semaphores and condition variables are used for efficient, inter-thread communication. Applications may use a variety of transport protocols underlying AMS itself, including TCP (Transmission Control Protocol), UDP (User Datagram Protocol), and message queues.

Burleigh, Scott C.↗

NASA NTRS2018

The Evolution of Payload Data Capabilities on the Commercial Visiting Vehicles that Service the International Space Station

For over 10 years, NASA has been working with U.S.-based commercial companies to support the design, development, and operations of new commercial space vehicles. The purpose of these vehicles is to provide cargo and crew transportation services to the International Space Station (ISS) and to stimulate the commercial space transportation industry to Low-Earth Orbit (LEO). Along with the ability to provide a couple tons of cargo to the ISS each mission, the commercial visiting vehicles also provide the ability to transfer NASA payloads to and from the ISS in an active, powered state. To take advantage of this capability, NASA requirements for the data services that payloads need while they are integrated into the visiting vehicles have grown with each set of commercial contracts. Today, NASA desires for payload data services encompass a variety of capabilities including payload health and status (H&S) telemetry monitoring, visiting vehicle environment data monitoring, and payload commanding. The intent of these capabilities is to provide payload developers with situational awareness and the ability to quickly diagnose any problems with payload operations prior to vehicle docking or post-landing to support immediate troubleshooting response. As new requirements for payload data services have emerged over the years, the ISS Payload Operations Integration Center (POIC) at the NASA Marshall Space Flight Center (MSFC) has established ground segment interfaces to the visiting vehicle control centers to enable payload developers to use these services. Many technical and programmatic challenges have been faced while establishing these interfaces. The most significant challenge faced has been in finding the right balance amongst providing interfaces to payloads that are compatible with the ISS so that payload hardware or software changes are not necessary to ensure compatibility with the visiting vehicles; keeping POIC ground system development costs low by standardizing implementation approaches across commercial vehicle partners; and fostering commercialization through supporting vendor-unique implementations that are commercially economical. This paper will first detail the data services that will be available to payload users under each commercial visiting vehicle contract. Secondly, this paper will offer discussion of the most significant technical and programmatic challenges faced to-date in offering these new data services to payload developers.

Wiggins, Lindsay M.↗