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NASA NTRS2012

Requirements-Driven Log Analysis Extended Abstract

Imagine that you are tasked to help a project improve their testing effort. In a realistic scenario it will quickly become clear, that having an impact is diffcult. First of all, it will likely be a challenge to suggest an alternative approach which is significantly more automated and/or more effective than current practice. The reality is that an average software system has a complex input/output behavior. An automated testing approach will have to auto-generate test cases, each being a pair (i; o) consisting of a test input i and an oracle o. The test input i has to be somewhat meaningful, and the oracle o can be very complicated to compute. Second, even in case where some testing technology has been developed that might improve current practice, it is then likely difficult to completely change the current behavior of the testing team unless the technique is obviously superior and does everything already done by existing technology. So is there an easier way to incorporate formal methods-based approaches than the full edged test revolution? Fortunately the answer is affirmative. A relatively simple approach is to benefit from possibly already existing logging infrastructure, which after all is part of most systems put in production. A log is a sequence of events, generated by special log recording statements, most often manually inserted in the code by the programmers. An event can be considered as a data record: a mapping from field names to values. We can analyze such a log using formal methods, for example checking it against a formal specification. This separates running the system for analyzing its behavior. It is not meant as an alternative to testing since it does not address the important in- put generation problem. However, it offers a solution which testing teams might accept since it has low impact on the existing process. A single person might be assigned to perform such log analysis, compared to the entire testing team changing behavior.

log analysis↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Cu Growth Rates on Geostationary Imagery and Linkages to Cloud Organization

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Common tropical cloud features, such as convective rolls and cold pool fronts, form and persist for different periods within environments that support such development. Determining differences in lifecycle amongst these features in varying environments requires viewing their evolution from initiation to decay. Geostationary satellites provide a means to follow the clouds with enhanced spatiotemporal sampling from space. We apply a cloud-tracking tool to study lifecycle properties of shallow cumulus sampled during the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign of 2019. The mission conducted airborne and shipborne operations over the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented on AHI 0.5-km visible reflectance and tracked during the daylit hours of several research flights that exhibited ideal atmospheric conditions for tracking. The resulting cloud tracks were collected according to regions containing airborne sampling of individual clouds at various stages of their lifecycles, yielding ensembles of tracks in separate environments. We present an analysis on lifecycle properties extracted from the cloud-track ensembles and their potential connections to cloud organizations observed throughout CAMP2Ex. Each ensemble is evaluated by calculating cloud-layer growth rates and comparing to spatial parameters, including track-achieved area and cloud-top height. The apparent clustering of growth rates for specific ensembles is then compared against overall cloud organizations, such as isolated congestus and cold pool fronts, that are observed with the airborne data. Finally, we consider how such differences in cloud growth appear in the airborne radar observations of intercepted cloud tracks.

Cloud Tracking↗
NASA NTRS2022

Flight Software Dictionary Development for the Mars2020 Rover

The Mars2020 project, developed and operated by the Jet Propulsion Laboratory (JPL), successfully landed the Perseverance rover and its flying companion Ingenuity on the surface of Mars on February 18th 2021. Perseverance combines heritage and cutting-edge flight software and hardware to accomplish crucial mission requirements related to Martian surface sampling. The design, development, and operation of NASA’s large strategic science missions require the ability to communicate spacecraft capabilities to hundreds of engineers across multiple disciplines. The interaction between flight and ground software development, Verification and Validation (V&V), Assembly, Test, and Launch Operations (ATLO), and management each demand quick understanding of unique slices of information for each discipline. This information includes the current capabilities of the flight system as well as future capabilities and their status as they are developed and tested. Despite the fundamental and critical nature of this information, the flight software dictionaries used to track it are a stumbling block for many projects. These dictionaries provide the cornerstone for the interpretation of data sent from the spacecraft, allowing for quick comprehension by engineers on the ground. During both spacecraft development and operations, flight software dictionary management includes significant challenges due to the large number of interfacing systems and the subtle yet distinct needs of each.The engineering of flight software dictionaries for Mars2020 had numerous challenges, most-notably: parallel dictionary development to support simultaneous separate flight software build campaigns for each mission phase (cruise and surface), managing requests for operations-enabling information without perturbing the heritage interface with the rover, and the introduction of new tools by the dictionary stakeholders that forced the dictionary team to innovate and redesign the heritage tool chain. These challenges generated guiding principles for the dictionary development effort: emphasize coding best practices and unit testing in the dictionary code development tool chain, use institutionally provided COTS (commercial-off-the-shelf) tools whenever possible, and maintain the heritage flight-ground interface all while advancing operations-enabling information via a loosely coupled interface.Throughout development and operations, the Mars2020 dictionary toolchain included IBM DOORS Next Generation, GitHub, Microsoft Excel, Docker, Jenkins, and a significant custom-built Python codebase. Significant interfaces included JPL’s command and control software, heritage flight software team tools and processes, and the many cloud-based ground tools developed for the mission.This paper will discuss the requirements for the Mars2020 dictionary development, the development team’s response to those requirements, lessons learned throughout the process, steps taken towards automated deliveries and continuous integration of stakeholder inputs, potential toolchain improvements for Mars2020, and key takeaways that could be applied to future missions.

Pyrzak, Guy↗
NASA NTRS2002

Solid Freeform Fabrication: An Enabling Technology for Future Space Missions

The emerging class of direct manufacturing processes known as Solid Freeform Fabrication (SFF) employs a focused energy beam and metal feedstock to build structural parts directly from computer aided design (CAD) data. Some variations on existing SFF techniques have potential for application in space for a variety of different missions. This paper will focus on three different applications ranging from near to far term to demonstrate the widespread potential of this technology for space-based applications. One application is the on-orbit construction of large space structures, on the order of tens of meters to a kilometer in size. Such structures are too large to launch intact even in a deployable design; their extreme size necessitates assembly or erection of such structures in space. A low-earth orbiting satellite with a SFF system employing a high-energy beam for high deposition rates could be employed to construct large space structures using feedstock launched from Earth. A second potential application is a small, multifunctional system that could be used by astronauts on long-duration human exploration missions to manufacture spare parts. Supportability of human exploration missions is essential, and a SFF system would provide flexibility in the ability to repair or fabricate any part that may be damaged or broken during the mission. The system envisioned would also have machining and welding capabilities to increase its utility on a mission where mass and volume are extremely limited. A third example of an SFF application in space is a miniaturized automated system for structural health monitoring and repair. If damage is detected using a low power beam scan, the beam power can be increased to perform repairs within the spacecraft or satellite structure without the requirement of human interaction or commands. Due to low gravity environment for all of these applications, wire feedstock is preferred to powder from a containment, handling, and safety standpoint. The energy beams may be either electron beam or laser, and the developments required for either energy source to achieve success in these applications will be discussed.

Taminger, Karen M. B.↗
NASA NTRS2002

Structural Weight Estimation for Launch Vehicles

This paper describes some of the work in progress to develop automated structural weight estimation procedures within the Vehicle Analysis Branch (VAB) of the NASA Langley Research Center. One task of the VAB is to perform system studies at the conceptual and early preliminary design stages on launch vehicles and in-space transportation systems. Some examples of these studies for Earth to Orbit (ETO) systems are the Future Space Transportation System [1], Orbit On Demand Vehicle [2], Venture Star [3], and the Personnel Rescue Vehicle[4]. Structural weight calculation for launch vehicle studies can exist on several levels of fidelity. Typically historically based weight equations are used in a vehicle sizing program. Many of the studies in the vehicle analysis branch have been enhanced in terms of structural weight fraction prediction by utilizing some level of off-line structural analysis to incorporate material property, load intensity, and configuration effects which may not be captured by the historical weight equations. Modification of Mass Estimating Relationships (MER's) to assess design and technology impacts on vehicle performance are necessary to prioritize design and technology development decisions. Modern CAD/CAE software, ever increasing computational power and platform independent computer programming languages such as JAVA provide new means to create greater depth of analysis tools which can be included into the conceptual design phase of launch vehicle development. Commercial framework computing environments provide easy to program techniques which coordinate and implement the flow of data in a distributed heterogeneous computing environment. It is the intent of this paper to present a process in development at NASA LaRC for enhanced structural weight estimation using this state of the art computational power.

Cerro, Jeff↗
NASA NTRS2014

ldentifying Episodes of Earth Science Phenomena Using a Big-Data Technology

A significant portion of Earth Science investigations is phenomenon- (or event-) based, such as the studies of Rossby waves, volcano eruptions, tsunamis, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. We have constructed a prototype Automated Event Service (AES) system that is used to methodically mine custom-defined events in the reanalysis data sets of atmospheric general circulation models. Our AES will enable researchers to specify their custom, numeric event criteria using a user-friendly web interface to search the reanalysis data sets. Moreover, we have included a social component to enable dynamic formation of collaboration groups for researchers to cooperate on event definitions of common interest and for the analysis of these events. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon (ES phenomenon). A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an El Nino, is each an episode of a named ES phenomenon, and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a duration (often finite) and an associated geo-location as a function of time; it's therefore an entity embedded in four-dimensional (4D) spatiotemporal space. Earth Science phenomena with the potential to cause massive economic disruption or loss of life often rivet the attention of researchers. But, broader scientific curiosity also drives the study of phenomena that pose no immediate danger, such as land/sea breezes. Due to Earth System's intricate dynamics, we are continuously discovering novel ES phenomena. We generally gain understanding of a given phenomenon by observing and studying individual events. This process usually begins by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, as mentioned previously, comprehensive records only exist for a very limited set of high-impact phenomena; aside from these, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. The reason for the lack of comprehensive records for most of the ES phenomena is mainly due to the perception that they do not pose immediate and/or severe threat to life and property. Thus they are not consistently tracked, monitored, and catalogued. Many phenomena even lack precise and/or commonly accepted criteria for definitions. Moreover, various Earth Science observations and data have accumulated to a previously unfathomable volume; NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data, which are steadily increasing. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. We have not only envisioned AES as an environment for identifying customdefined events but also aspired for it to be an interactive environment with quick turnaround time for revisions of query criteria and results, as well as a collaborative environment where geographically distributed experts may work together on the same phenomena. A Big Data technology is thus required for the realization of such a system. In the following, we first introduce the technology selected for AES in the next section. We then demonstrate the utility of AES using a use case, Blizzard, before we conclude.

Kuo, Kwo-Sen↗
NASA NTRS2004

Hot Stuff? Thermal Imaging Applied to Cryocrystallography

In the past we have used thermal imaging techniques to visualize the cryocooling processes of macromolecular crystals. From these images it was clear that a cold wave progresses through a crystal starting at the face closest to the origin of the cold stream and ending at the point furthest away. During these studies we used large volume crystals, which were clearly distinguished fiom the loop holding them. These large crystals, originally grown for neutron diffiaction studies, were chosen deliberately to enhance the imaging. As an extension to this work, we present used thermal imaging to study small crystals, held in a cryo-loop, in the presence of vitrified mother liquor. The different d a r e d transmission and reflectance properties of the crystal in comparison to the mother liquor surrounding it are thought to be the parameter that produces the contrast that makes the crystal visible. An application of this technology may be the determination of the exact location of small crystals in a cryo-loop. Data fkom initial tests in support of application development was recorded for lysozyme crystals and for bFGF/dna complex crystals, which were cryocooled and imaged in large loops, both with visible light mad with h i k e d rdi&tion. The crystals were clearly distinguished from the vitrified solution in the infiared spectrum, while in the case of the bFGF/dna complex the illumination had to be carefully manipulated to make the crystal visible in the visible spectrum. These results suggest that the thermal imaging may be more sensitive than visual imaging for automated location of small crystals. However, further work on small crystals robotically mounted at SSRL did not clearly visualize those crystals. The depth of field of the camera proved to be limiting and a different cooling geometry was used, compared to the previous, successful experiments. Analysis to exploit multiple images to improve depth of field and experimental work to understand cooling geometry effects is ongoing. These results will be presented along with advantages and disadvantages of the technique and a discussion of how it might be applied.

Snell, E. H.↗
NASA NTRS2004

Video Guidance Sensors Using Remotely Activated Targets

Four updated video guidance sensor (VGS) systems have been proposed. As described in a previous NASA Tech Briefs article, a VGS system is an optoelectronic system that provides guidance for automated docking of two vehicles. The VGS provides relative position and attitude (6-DOF) information between the VGS and its target. In the original intended application, the two vehicles would be spacecraft, but the basic principles of design and operation of the system are applicable to aircraft, robots, objects maneuvered by cranes, or other objects that may be required to be aligned and brought together automatically or under remote control. In the first two of the four VGS systems as now proposed, the tracked vehicle would include active targets that would light up on command from the tracking vehicle, and a video camera on the tracking vehicle would be synchronized with, and would acquire images of, the active targets. The video camera would also acquire background images during the periods between target illuminations. The images would be digitized and the background images would be subtracted from the illuminated-target images. Then the position and orientation of the tracked vehicle relative to the tracking vehicle would be computed from the known geometric relationships among the positions of the targets in the image, the positions of the targets relative to each other and to the rest of the tracked vehicle, and the position and orientation of the video camera relative to the rest of the tracking vehicle. The major difference between the first two proposed systems and prior active-target VGS systems lies in the techniques for synchronizing the flashing of the active targets with the digitization and processing of image data. In the prior active-target VGS systems, synchronization was effected, variously, by use of either a wire connection or the Global Positioning System (GPS). In three of the proposed VGS systems, the synchronizing signal would be generated on, and transmitted from, the tracking vehicle. In the first proposed VGS system, the tracking vehicle would transmit a pulse of light. Upon reception of the pulse, circuitry on the tracked vehicle would activate the target lights. During the pulse, the target image acquired by the camera would be digitized. When the pulse was turned off, the target lights would be turned off and the background video image would be digitized. The second proposed system would function similarly to the first proposed system, except that the transmitted synchronizing signal would be a radio pulse instead of a light pulse. In this system, the signal receptor would be a rectifying antenna. If the signal contained sufficient power, the output of the rectifying antenna could be used to activate the target lights, making it unnecessary to include a battery or other power supply for the targets on the tracked vehicle.

Bryan, Thomas C.↗
NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗
NASA NTRS1995

Investigation of biomass burning and aerosol loading and transport in South America utilizing geostationary satellites

This study attempts to assess the extent of burning and associated aerosol transport regimes in South America and the South Atlantic using geostationary satellite observations, in order to explore the possible roles of biomass burning in climate change and more directly in atmospheric chemistry and radiative transfer processes. Modeling and analysis efforts have suggested that the direct and indirect radiative effects of aerosols from biomass burning may play a major role in the radiative balance of the earth and are an important factor in climate change calculations. One of the most active regions of biomass burning is located in South America, associated with deforestation in the selva (forest), grassland management, and other agricultural practices. As part of the NASA Aerosol Interdisciplinary Program, we are utilizing GOES-7 (1988) and GOES-8 (1995) visible and multispectral infrared data (4, 11, and 12 microns) to document daily biomass burning activity in South America and to distinguish smoke/aerosols from other multi-level clouds and low-level moisture. This study catalogues the areal extent and transport of smoke/aerosols throughout the region and over the Atlantic Ocean for the 1988 (July-September) and 1995 (June-October) biomass burning seasons. The smoke/haze cover estimates are compared to the locations of fires to determine the source and verify the haze is actually associated with biomass burning activities. The temporal resolution of the GOES data (half-hourly in South America) makes it possible to determine the prevailing circulation and transport of aerosols by considering a series of visible and infrared images and tracking the motion of smoke, haze and adjacent clouds. The study area extends from 40 to 70 deg W and 0 to 40 deg S with aerosol coverage extending over the Atlantic Ocean when necessary. Fire activity is estimated with the GOES Automated Biomass Burning Algorithm (ABBA). To date, our efforts have focused on GOES-7 and GOES-8 ABBA development, algorithm development for aerosol monitoring, data acquisition and archiving, and participation in the SCAR-C and SCAR-B field programs which have provided valuable information for algorithm testing and validation. Implementation of the initial version of the GEOS-8 ABBA on case studies in North, Central, and South America has demonstrated the improved capability for monitoring diurnal fire activity and smoke/aerosol transport with the GOES-8 throughout the Western Hemisphere.

Menzel, Paul↗
NASA NTRS2000

The Video Guidance Sensor: Space, Earth, Ground, and Sea

Engineers at the Marshall Space Flight Center (MSFC) have been developing and testing video-based sensors for automated spacecraft guidance for several years. The next generation of Video Guidance Sensor (VGS) is being designed to be faster and more capable than ever. It will have applications to relative position measurement in any field of endeavor. The system works by sequentially firing two different wavelengths of laser diodes at the target (which has retroreflectors) and processing the two images. Since the target only reflects one wavelength, it shows up well in one image and not at all in the other. Because the target's dimensions are known, the relative positions and attitudes of the target and the sensor can be computed from the spots reflected from the target. The current sensor operates at 5 Hz at ranges from 1 to 110 meters with a 20 deg. field-of-view. The Video Guidance Sensor (VGS) developed over the past several years has performed well in testing and met the objective of being used as the terminal guidance sensor for an automated rendezvous and capture system. The first VGS was successfully tested in closed-loop 3-degree-of-freedom (3-DOF) tests in 1989 and then in 6-DOF open-loop tests in 1992 and closed-loop tests in 1993-4. Development and testing continued, and in 1995 approval was given to test the VGS in an experiment on the Space Shuttle. The VGS flew in 1997 and in 1998, performing well during both flight experiments. During the development and testing before, during, and after the flight experiments, numerous areas for improvement were found. The next generation of VGS is being designed to operate at up to 100 Hz tracking rates and at ranges from 0.5 to 200 meters. In addition to its use as a spacecraft guidance sensor, it could be used as an alignment aid for an operator of a remote system (giving position and attitude feedback data), as a feedback system for a robotic arm, or for automated vehicle guidance. The next generation VGS, with its higher tracking rates, smaller size, and lower power could be used in more places than the original VGS, and by using LED's instead of laser diodes, the system would be eye-safe at any range. More potential applications include aerial station keeping (keeping 2 or more autonomous aircraft within particular relative positions), under-water robotics, and the guidance of ground vehicles in predefined areas equipped with sets of targets.

Howard, Richard T.↗
NASA NTRS2011

Automated Cryocooler Monitor and Control System

A system was designed to automate cryogenically cooled low-noise amplifier systems used in the NASA Deep Space Network. It automates the entire operation of the system including cool-down, warm-up, and performance monitoring. The system is based on a single-board computer with custom software and hardware to monitor and control the cryogenic operation of the system. The system provides local display and control, and can be operated remotely via a Web interface. The system controller is based on a commercial single-board computer with onboard data acquisition capability. The commercial hardware includes a microprocessor, an LCD (liquid crystal display), seven LED (light emitting diode) displays, a seven-key keypad, an Ethernet interface, 40 digital I/O (input/output) ports, 11 A/D (analog to digital) inputs, four D/A (digital to analog) outputs, and an external relay board to control the high-current devices. The temperature sensors used are commercial silicon diode devices that provide a non-linear voltage output proportional to temperature. The devices are excited with a 10-microamp bias current. The system is capable of monitoring and displaying three temperatures. The vacuum sensors are commercial thermistor devices. The output of the sensors is a non-linear voltage proportional to vacuum pressure in the 1-Torr to 1-millitorr range. Two sensors are used. One measures the vacuum pressure in the cryocooler and the other the pressure at the input to the vacuum pump. The helium pressure sensor is a commercial device that provides a linear voltage output from 1 to 5 volts, corresponding to a gas pressure from 0 to 3.5 MPa (approx. = 500 psig). Control of the vacuum process is accomplished with a commercial electrically operated solenoid valve. A commercial motor starter is used to control the input power of the compressor. The warm-up heaters are commercial power resistors sized to provide the appropriate power for the thermal mass of the particular system, and typically provide 50 watts of heat. There are four basic operating modes. "Cool " mode commands the system to cool to normal operating temperature. "Heat " mode is used to warm the device to a set temperature near room temperature. "Pump " mode is a maintenance function that allows the vacuum system to be operated alone to remove accumulated contaminants from the vacuum area. In "Off " mode, no power is applied to the system.

Britcliffe, Michael J.↗
NASA NTRS2024

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗
NASA NTRS1992

The manned transportation system study - Defining human pathways into space

The Manned Transportation System (MTS) Study, conducted by a NASA-Industry Team (NIT), has developed substantiating data for subsequent NASA decisions on the “right” set of manned transportation elements needed for human access to space. It also provides the framework for detailed definition of those manned transportation elements. Including the next manned transportation system, to be developed. Process and product are presented to inform the aerospace community and subject our approach and conclusions to peer review, NASA/JSC lead the NIT, with participation from KSC, LaRC, MSFC, and NASA/Headquarters, along with six aerospace contractor (Boeing, General Dynamics, Lockheed Martin Marietta, McDonnell Douglas, and Rockwell). Each major milestone was archived through team consensus. Our mission model was derived from the FY90 Civil Needs Data Base (CNDB) and included flight assignments for Department of Defense (DOD) missions. Identifying and defining architecture evaluation criteria, i.e. attributes, specified the amount and type of data needed for each concept under consideration. Several architectures, each beginning with today’s transportation systems, were defined using representative systems to explore our future options and address specific questions currently being debated. Our solutions are a function of the level of space activity the nation chooses to follow. However, they all emphasize affordability, safety, routineness, and reliability. Finally, key issues associated with our current business practices were challenged and the impact associated with those practices quantified.

NASA Langley Research Center↗
NASA NTRS1997

Computer based imaging and analysis of root gravitropism

Two key issues in studies of the nature of the gravitropic response in roots have been the determination of the precise pattern of differential elongation responsible for downward bending and the identification of the cells that show the initial motor response. The main approach for examining patterns of differential growth during root gravitropic curvature has been to apply markers to the root surface and photograph the root at regular intervals during gravitropic curvature. Although these studies have provided valuable information on the characteristics of the gravitropic motor response in roots, their labor intensive nature limits sample size and discourages both high frequency of sampling and depth of analysis of surface expansion data. In this brief review we describe the development of computer-based video analysis systems for automated measurement of root growth and shape change and discuss some key features of the root gravitropic response that have been revealed using this methodology. We summarize the capabilities of several new pieces of software designed to measure growth and shape changes in graviresponding roots and describe recent progress in developing analysis systems for studying the small, but experimentally popular, primary roots of Arabidopsis. A key finding revealed by such studies is that the initial gravitropic response of roots of maize and Arabidopsis occurs in the distal elongation zone (DEZ) near the root apical meristem, not in the main elongation zone. Another finding is that the initiation of rapid elongation in the DEZ following gravistimulation appears to be related to rapid membrane potential changes in this region of the root. These observations have provided the incentive for ongoing studies examining possible links between potential growth modifying factors (auxin, calcium, protons) and gravistimulated changes in membrane potential and growth patterns in the DEZ.

NASA Discipline Plant Biology↗
NASA NTRS2012

Next Generation NASA Initiative for Space Geodesy

Space geodesy measurement requirements have become more and more stringent as our understanding of the physical processes and our modeling techniques have improved. In addition, current and future spacecraft will have ever-increasing measurement capability and will lead to increasingly sophisticated models of changes in the Earth system. Ground-based space geodesy networks with enhanced measurement capability will be essential to meeting these oncoming requirements and properly interpreting the sate1!ite data. These networks must be globally distributed and built for longevity, to provide the robust data necessary to generate improved models for proper interpretation ofthe observed geophysical signals. These requirements have been articulated by the Global Geodetic Observing System (GGOS). The NASA Space Geodesy Project (SGP) is developing a prototype core site as the basis for a next generation Space Geodetic Network (SGN) that would be NASA's contribution to a global network designed to produce the higher quality data required to maintain the Terrestrial Reference Frame and provide information essential for fully realizing the measurement potential of the current and coming generation of Earth Observing spacecraft. Each of the sites in the SGN would include co-located, state of-the-art systems from all four space geodetic observing techniques (GNSS, SLR, VLBI, and DORIS). The prototype core site is being developed at NASA's Geophysical and Astronomical Observatory at Goddard Space Flight Center. The project commenced in 2011 and is scheduled for completion in late 2013. In January 2012, two multiconstellation GNSS receivers, GODS and GODN, were established at the prototype site as part of the local geodetic network. Development and testing are also underway on the next generation SLR and VLBI systems along with a modern DORIS station. An automated survey system is being developed to measure inter-technique vector ties, and network design studies are being performed to define the appropriate number and distribution of these next generation space geodetic core sites that are required to achieve the driving ITRF requirements. We present the status of this prototype next generation space geodetic core site, results from the analysis of data from the established geodetic stations, and results from the ongoing network design studies.

Merkowitz, S. M.↗
NASA NTRS2011

Automated Miniaturized Instrument for Space Biology Applications and the Monitoring of the Astronauts Health Onboard the ISS

Human space travelers experience a unique environment that affects homeostasis and physiologic adaptation. The spacecraft environment subjects the traveler to noise, chemical and microbiological contaminants, increased radiation, and variable gravity forces. As humans prepare for long-duration missions to the International Space Station (ISS) and beyond, effective measures must be developed, verified and implemented to ensure mission success. Limited biomedical quantitative capabilities are currently available onboard the ISS. Therefore, the development of versatile instruments to perform space biological analysis and to monitor astronauts' health is needed. We are developing a fully automated, miniaturized system for measuring gene expression on small spacecraft in order to better understand the influence of the space environment on biological systems. This low-cost, low-power, multi-purpose instrument represents a major scientific and technological advancement by providing data on cellular metabolism and regulation. The current system will support growth of microorganisms, extract and purify the RNA, hybridize it to the array, read the expression levels of a large number of genes by microarray analysis, and transmit the measurements to Earth. The system will help discover how bacteria develop resistance to antibiotics and how pathogenic bacteria sometimes increase their virulence in space, facilitating the development of adequate countermeasures to decrease risks associated with human spaceflight. The current stand-alone technology could be used as an integrated platform onboard the ISS to perform similar genetic analyses on any biological systems from the tree of life. Additionally, with some modification the system could be implemented to perform real-time in-situ microbial monitoring of the ISS environment (air, surface and water samples) and the astronaut's microbiome using 16SrRNA microarray technology. Furthermore, the current system can be enhanced substantially by combining it with other technologies for automated, miniaturized, high-throughput biological measurements, such as fast sequencing, protein identification (proteomics) and metabolite profiling (metabolomics). Thus, the system can be integrated with other biomedical instruments in order to support and enhance telemedicine capability onboard ISS. NASA's mission includes sustained investment in critical research leading to effective countermeasures to minimize the risks associated with human spaceflight, and the use of appropriate technology to sustain space exploration at reasonable cost. Our integrated microarray technology is expected to fulfill these two critical requirements and to enable the scientific community to better understand and monitor the effects of the space environment on microorganisms and on the astronaut, in the process leveraging current capabilities and overcoming present limitations.

Human space travelers↗
NASA NTRS2015

The Application of New Optical Meteor Flux Routines to the 2014 May Camelopardalid Outburst

NASA's Meteoroid Environment Office (MEO) is charged with monitoring the meteoroid environment in near-Earth space for the protection of satellites and spacecraft. The MEO has recently established eight wide-field meteor cameras, four cameras each at two separate stations to calculate automated meteor fluxes in the millimeter size range. Each camera consists of a 17 mm focal length Schneider lens on a Watec 902H2 Ultimate CCD video camera, producing a 21.7 x 15.5 degree field of view. This configuration has a limiting meteor magnitude of about +5. One station is located at Marshall Space Flight Center in Huntsville, Alabama and the other is 31.8 kilometers away at a school in Decatur, Alabama. Both single-station and double-station fluxes are calculated every morning using data from the previous night. The flux algorithms employed here differ from others currently in use in that they do not assume a single height for all meteors observed in the common camera volume. In the MEO system, the volume is broken up into a set of height intervals, with the collecting areas determined by the position of the active shower or sporadic source radiant. The flux per height interval is calculated and summed to obtain the total meteor flux. As the mass is also computed from the photometry, a mass flux can also be calculated. First, a weather algorithm indicates if sky conditions are clear enough to calculate fluxes, at which point a limiting magnitude algorithm is employed. The limiting magnitude algorithm performs a fit of stellar magnitudes versus camera intensities. The stellar limiting magnitude is derived from this and converted to a limiting meteor magnitude for the active shower or sporadic source. The fluxes are scaled to an average limiting magnitude throughout the night and zenithal hourly rate (ZHR's) are output daily along with flux values. In addition to this process, results will be presented as applied to the 2014 May Camelopardalid outburst, using data from several different optical systems, which looked at May Camelopardalids in different size ranges.

Blaauw, Rhiannon↗