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At least 307 records · Page 17

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NASA NTRS2022

Characterization of Response Times Based on Voice Communication and Traffic Surveillance Data

A barrier to the integration of remotely piloted aircraft operations in the U.S. National Airspace System is the latency of voice communications between the air traffic controller and the remote pilot, and the latency of communication between the aircraft and the remote pilot. The latency can be substantial especially when satellite-based beyond-radio-line-of-sight communication and relay through the aircraft are employed. This study uses voice recordings of controller-pilot communications and aircraft track data to establish a baseline of pilot readback latencies and maneuver detection delays in the current piloted operations. A machine learning pipeline was developed to parse the contents of the air traffic control clearances including the callsigns using natural language processing. After manually validating the results obtained using the pipeline, the average pilot readback latency was found to be about 0.6 seconds. The average latency between the end of maneuver (inferred from track data), initiated by the pilot in response to the clearance, and the end of clearance was found to be about 176 seconds for altitude change commands, 69 seconds for heading change commands, and 182 seconds for speed change commands. The average latency between the beginning of maneuver and the end of clearance was found to be about 17 seconds for altitude change commands, 17seconds for heading change commands, and 25 seconds for speed change commands.

controller-pilot communication↗

NASA NTRS2021

Research Report: Building a File Observatory for Secure Parser Development

"Parsing untrusted data is notoriously challenging.Failure to handle maliciously crafted data correctly can (anddoes) lead to a wide range of vulnerabilities. The Languagetheoretic security (LangSec) philosophy seeks to obviate the needfor developers to apply ad hoc solutions by, instead, offeringformally correct and verifiable input handling throughout thesoftware development lifecycle. One of the key components indeveloping secure parsers is a broad coverage corpus that enablesdevelopers to understand the problem space for a given formatand to use, potentially, as seeds for fuzzing and other automatedtesting. In this paper, we offer an update on the developmentof a file observatory to gather and enable analysis on a diversecollection of files at scale. Specifically, we report on the additionof a bug tracker corpus and new analytic methods on our existingcorpus."

Stonebraker, Ryan↗

NASA NTRSDate not supplied

Mixed Integer Linear Programming in Planning

This project, Activity Planning with Resources for the Exploration of Space (APRES), uses a mixed-integer linear program (MILP) to solve planning problems. This work enables APRES to interpret a model file and output a solution with improved human readability. A plan model is optimized using a MILP solver and the best solution is taken. Once a plan is generated, it is parsed allowing it to retain only desired information and modified for swift human readability.

Christina Erwin↗

NASA NTRS2022

File Specification for MERRA-2 Climate Statistics Products

The Modern Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) contains a wealth of information that can be used for weather and climate studies. By combining the assimilation of observations with a frozen version of the Goddard Earth Observing System (GEOS), a global analysis is produced at an hourly temporal resolution spanning from January 1980 through present (Gelaro et al., 2017). It can be difficult to parse through a multidecadal dataset such as MERRA-2 to evaluate the interannual variability of weather that occurs on a daily timescale, let alone determine the occurrence of an extreme weather event. Furthermore, it was recognized that standard metrics were needed to evaluate climate change among climate models and international research efforts. As a result of these concerns, the Expert Team on Climate Change Detection and Indices (ETCCDI) developed a set of indices that represent the frequency and intensity of extreme weather events using a daily time series of 2-m air temperature (T2m) and precipitation (Alexander et al., 2016). These indices were used as a basis to comprise a list of fields that represent daily extreme temperature and precipitation events, heatwaves, multi-day precipitation, as well monthly percentile statistics from the MERRA-2 dataset. Also included in this data product is a climatological long term mean and standard deviation representing the interannual variability on a monthly timescale.

MERRA-2↗

NASA NTRSDate not supplied

Investigating Amino Acid Heterogeneity in Milligram-Scale Samples of the Murchison CM2 Carbonaceous Chondrite

Analyses of different aliquots of the Tagish Lake meteorite have resulted in amino acid abundance variations of an order of magnitude or more, even when performed using the same techniques, by the same personnel, in the same laboratories (e.g., Simkus et al. 2019). Up to ~five-fold variations have been observed for specific amino acids in different samples of the same meteorite, such as α aminoisobutryic acid (AIB) in Murchison. These variations are often attributed differing sample composition or differing alteration history, neither of which is mutually exclusive. Distinguishing between these two explanations is challenging and time consuming, requiring detailed mineralogical analyses to be performed in conjunction with high precision organics analysis. The potential for innate sample-level heterogeneity presents a significant complication when parsing the effects of different processes or conditions during preparation of meteorite samples for analysis, as differences in organic yields or abundances could be due to differences in laboratory processing or differences among the samples themselves. In this work, we investigated the degree of innate organic heterogeneity present in a single ~250 mg chip of divided into 21 samples.

A. S. Burton↗

NASA NTRSDate not supplied

Digitizing Named Entities Found Within Letters of Agreement

Letters of Agreement (LOAs) are text-based air traffic control documents that contain procedures and actions agreed upon by the different parties, typically two or more FAA facilities, that are subject to an agreement. The documents contain among other things generic constraints, which are explicit and implicit combinations of procedures that limit a flight’s trajectory and affects pilot actions. For example, a controller may be required, to assign a specific altitude to an aircraft crossing the boundary between two airspaces. Although LOA generic constraints directly impact the trajectory of an aircraft, they are not currently available in a digital form that can be used for (or directly ingested into automated) flight planning. Instead, the constraints are manually input into an onboard or ground based system. LOA documents are primarily stored at a controlling facility and the generic constraints are implemented by experienced air traffic controllers and pilots primarily using voice instructions. This increases the workload of the controllers, likelihood of error (e.g., due to noisy communication) and makes it impractical for implementation with unmanned aircraft. Therefore, steps must be taken to make existing constraints machine interpretable to enable e.g., automated handoffs which in turn would reduce controller workload. With recent advances in natural language processing, especially the rise in digitization of text documents (e.g., medical documents) and automated extraction of information therein, it is now possible to extract flight specific constraints from LOAs. The goal of this work is to digitize named entities through a combination of natural language processing tasks: named entity disambiguation, toponym resolution, and numeric parsing to extract general constraint components contained within LOAs, herein referred to as Entity Enhancement (EE). Starting with a small list of named entities (e.g., ARTCC, Tower, Altitude and Speed), EE can extract the named entities while simultaneously converting the string-based output into a digital format using an ensemble of processes like rule-based gazetteers and syntactic-lexical patterns. The digital format contains a diverse set of information based on the entity label in question, ranging from standardized facility names to units of measure (e.g., feet) and other numeric information. Upon validating our approach using a truth dataset, we show an overall F1-Score of 0.71 for the extraction process. Looking beyond entity enhancement, we are also working towards the goal of completely digitizing the general constraints by performing EE and fitting them into a standardized exchange model (XM) such as the Aeronautical Information Exchange Model (AIXM). This will allow for easy distribution and dissemination of LOA constraints to air users, better searchability within documents, and enable ingestion into automated flight planning. Finally, we show a preliminary version of the proposed XM architecture and demonstrate how the model can be populated from the EE output.

Stephen S. B. Clarke↗

NASA NTRS2022

Research Report: Progress on Building a File Observatory for Secure Parser Development

Parsing untrusted data is notoriously challenging.Failure to handle maliciously crafted data correctly can (anddoes) lead to a wide range of vulnerabilities. The Languagetheoretic security (LangSec) philosophy seeks to obviate the needfor developers to apply ad hoc solutions by, instead, offeringformally correct and verifiable input handling throughout thesoftware development lifecycle. One of the key components indeveloping secure parsers is a broad coverage corpus that enablesdevelopers to understand the problem space for a given formatand to use, potentially, as seeds for fuzzing and other automatedtesting. In this paper, we offer an update on work reportedat the LangSec 2021 conference on the development of a fileobservatory to gather and enable analysis on a diverse collectionof files at scale. The initial focus of the observatory is on PortableDocument Format (PDF) files and file formats typically embeddedin PDFs. In this paper, we report on refactoring the ingestprocess, applying new analytic methods, and improving the User Interface.

Stonebraker, Ryan↗

NASA NTRS2023

Space Networking Implementation for Lunar Operations

The High-Rate Delay Tolerant Networking (HDTN) project at NASA has developed a performance optimized and open-source Delay Tolerant Networking (DTN) implementation. The primary goal is to create a scalable networking solution to increase the scientific data return rate of space missions. To reach this goal, HDTN must span multiple edge cases in space networking by including tools and configurations to accommodate a wide range of space systems. Typically, HDTN evaluations are conducted on a laboratory emulation test bed, made up of hardware accelerated x86 based systems capable of data rates over 10 Gbps. HDTN must have an effective implementation process on a wide range of systems to increase the sustainability of the design. One important implementation option is with low-level embedded systems which could be used on small robotic missions. This paper details the implementation process, benchmark testing, and performance results of HDTN in multiple configurations on Raspberry Pi 4 devices. By implementing HDTN on a Raspberry Pi 4, a process for building HDTN onto ARM processors was developed and utilized to conduct benchmark tests in multiple network configurations, achieving a data rate performance exceeding 600 Mbps. Based on these results, HDTN proved to run on small ARM based systems with slight modifications to the build procedure. These results were then extended to evaluating an implementation of the HDTN software parsed across several Raspberry Pi 4 nodes. To test this capability, HDTN was configured in a simplified cut-through setup and distributed among multiple Raspberry Pi 4 processors. This distributed architecture was benchmark tested in a similar fashion to the testing of a singular HDTN implementation. The results from the benchmark testing are used to examine how these implementation options and capabilities can expand the use cases for DTN, and particularly with small robotic missions.

Space Networking↗

NASA NTRS2024

SMAnalytics Automated Shape Memory Test Analysis Software User's Manual: UCFTC, UPER, and DSC Test Methods, Version 1.0.2

Over the course of 60 years of shape memory alloy research and development, the properties of these alloys have been measured using various testing methods, which are often customized by the organization performing the test. However, commercial adoption of shape memory alloys in aeronautic actuator applications requires reducing property uncertainty through standardizing test methods. Historically, differential scanning calorimetry (DSC) has been used to measure transformation temperatures under stress-free conditions. This testing method is well established, and tests are run under the applicable standard, ASTM F2004-17: Standard Test Method for Transformation Temperature of Nickel-Titanium Alloys by Thermal Analysis. Two other test methods for measuring strains and transformation temperatures under constant load or free recovery after prestraining have only recently been standardized—ASTM E3097: Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of SMAs (UCFTC) and ASTM E3098: Standard Test Method for Mechanical Uniaxial Pre-Strain and Thermal Free Recovery of SMAs (UPFR). These standards represent a critical step forward in producing reliable material property data for the use of these alloys in aeronautics and other commercial areas. However, no standard programs or software packages were previously available for postprocessing UCFTC- and UPFR-type test data to extract property data. Each organization that performed the testing analyzed data using its own custom manual methods, such as using a plot and a straight edge, spreadsheet plotting methods, or custom code routines, to extract the required values for strains, stresses, and transformation temperatures. SMAnalytics represents the first publicly available uniform software package for processing data generated using the DSC, UCFTC, and UPFR test methods, as well as many modifications of these methods, including loading in martensite versus austenite and performing multiple thermal cycles at stress. In doing so, it provides a tool for reducing potential error or variability in the measured values due to the precision of the technique used and person-to-person variability. It is also expected that this automated data-parsing tool can accelerate the data analysis phase of the test campaign, especially for large data files. This User’s Manual describes how the SMAnalytics software works and the method for its use.

Shape Memory Alloy↗

NASA NTRSDate not supplied

A new template for developing C++ applications in NASA's Core Flight System

In this presentation, we will demonstrate an example Core Flight System (cFS) application written in C++, compatible with the Draco releases of the Core Flight Executive (cFE) and NASA Operating System Abstraction Layer (OSAL). The application boilerplate, supporting library, and associated generation script were recently developed and licensed under the permissive Apache License 2.0 with the goal of easing the cFS app development with C++. The design and features of this application will be presented, including a higher-level interface for interactions with the cFE software bus pipes, tables, and event services. Data structures are provided for centralized telecommand and telemetry parsing which isolates bookkeeping of message components from the calling code in an application's core logic. Specific advantages of writing a cFS application in C++ will be shown, including easier avoidance of symbol collisions via namespaces, expanded compile-time checks via constant expressions, default initialization for data structures, null safety via references, improved syntax for operating on multi-dimensional arrays, and reliable serialization of enumerations via enumeration classes. Special considerations needed for integrating a C++ application will be identified, including function linkage, exceptions, and stack unwinding. Evidence for the usefulness of this template will be discussed in the context of development of a flight software application used for interfacing with a solid-state data recorder.

Dominick Allen↗

NASA NTRSDate not supplied

Individual Response Trends to Urban Air Mobility Noise in A Laboratory Study

Advanced Air Mobility, of which Urban Air Mobility (UAM) is a subset, presents new opportunities for more dynamic aviation transportation systems. It is essential to understand the human response to the noise of these vehicles for sustainable operations. This research aims to investigate the relationship between the noise level and number of events on individual human annoyance to UAM vehicle noise. A “noise and number” laboratory psychoacoustic study was conducted in the Exterior Effects Room at NASA Langley Research Center in January 2023. A total of 38 participants listened to 4-minute audio clips of UAM vehicle flyover noise and provided their annoyance response on an 11-point numerical scale. A test hypothesis was that annoyance to multiple flyovers can be found by adding the annoyance responses to individual flyovers. Results for the overall test subject pool suggest that annoyance grows faster than hypothesized as the number of aircraft events increases. This trend of faster annoyance growth only seems to hold when the individual flyovers are heard as distinct events. Parsing the data down to individuals provides further insight into the mechanisms contributing to the increased annoyance with number of events.

noise and number↗

NASA NTRSDate not supplied

NASA CARA Tools

The NASA Conjunction Assessment Risk Analysis (CARA) team has created and posted to GitHub a set of MATLAB software tools for collision assessment (CA) analysis. The software is provided to the public under a NASA Open-Source Software Agreement and is maintained/updated by the CARA Analysis team. Capabilities provided within the toolset include algorithms in assessing probability of collision (Pc), collision consequence, covariance realism, Orbit Determination (OD) quality assessment, and single covariance max Pc. Additionally, a set of utilities are provided for astrodynamics topics closely related to CA, such as: Conjunction Data Message (CDM) parsing, covariance transformations, coordinate system transformations, etc. The repository is regularly updated on a monthly basis and new functionality will be added as algorithms are approved for public release. This presentation will provide a brief introduction to the toolset, highlight some of the key components which can be used in operations, and will present information on algorithms that are in the release pipeline and can be expected soon. This software will enable operators to independently perform CA calculations using the same core algorithms that CARA uses in operations.

L. Baars↗

NASA NTRSDate not supplied

Modeling NASA’s Procedural Requirement Processes - Implications for Digital Future

The National Aeronautics and Space Administration (NASA) has an ongoing Digital Transformation effort and to leverage and showcase the power of Digital Transformation, an effort is underway to develop an integrated, datacentric, model representing NASA’s key process requirements. The task was divided into three phases: As Is modeling, Analysis, and To Be Planning. As part of this effort, a team has completed the first Phase I of the modeling task and is nearing completion of the second phase. This effort will capture the key elements as requirements, responsibilities, allocations, roles, products, and associated lifecycle elements. The scope of modeling included NASA’s NPR 7120.5 (Project and Program Management), NPR 7123.1 (Systems Engineering) and NPRs 8705.2 (Risk classification for Robotic Missions) and 8705.4 (Human-Rating Requirements for Space Missions). This paper will summarize the approach, scope, parsing patterns applied, metamodel, and associated workflows for the As-Is modeling. It will also summarize the results and insights gleaned during that phase, including the review process. These insights have informed the analysis and will be discussed. The analysis modeling phase will also be summarized including how the stakeholders were engaged, how the common elements were handled and dispositioned, and will also describe some of the plans for the future of NASA NPDs and NPRs.

Systems Engineering↗

NASA NTRS2024

LTV-xEVA Applied Injury Biomechanics

Beginning in Artemis V, Lunar Terrain Vehicles (LTV) will be utilized to enable astronauts to explore the lunar south pole and conduct science farther from the landing site than during the Apollo program. However, LTV operation has the potential to cause injury to the suited crew member during their Extravehicular Activity (EVA). Injury risk caused by LTV acceleration and jerk combined with blunt loading from rigid suit components needs to be better understood. An effort began to create requirements for, model, and address the injury risk caused by the LTV combined with Exploration EVA (xEVA) suits. Mitigation of crew injury is a shared responsibility between LTV and the suit since neither can accomplish this independently. The modeling completed in Fiscal Year 2023 (FY23) helped to verify the fidelity of the requirements and parse out vendor responsibility (LTV, xEVAS, or NASA) for Artemis V and beyond. The scope of the modeling in FY23 used the LTV System Requirements Document (SRD) as worst-case inputs and modeled female 5th-, male 50th-, and male 95th-percentile subjects in hard-mounted seated and semi-standing postures. Soft-mounted (i.e., lap belt) and testing to validate the analysis was determined out of scope for FY23 work.

Spacesuit↗

NASA NTRSDate not supplied

NASA CARA Tools

Luis Baars↗

NASA NTRSDate not supplied

LTV-xEVA Applied Injury Biomechanics

Spacesuit↗

NASA NTRSDate not supplied

James Webb Space Telescope Fuel Slosh Estimation

The mitigation of fuel slosh in microgravity environments is a pressing matter for the control of both manned and unmanned spacecraft. This paper investigates the attitude perturbations caused by fuel slosh aboard the James Webb Space Telescope (JWST). We develop a dynamical model to parse these perturbations from slew telemetry data. This model uses special Euclidean group SE(3) as well as a novel, N-body variational integrator. The enhanced ability to validate fuel slosh models offers the reduction of settling time after slew operations and, accordingly, the maximization of available science time.

GN&C↗

NASA NTRSDate not supplied

James Webb Space Telescope Fuel Slosh Estimation

The mitigation of fuel slosh in microgravity environments is a pressing matter for the control of both manned and unmanned spacecraft. Recent work has investigated negative mass modeling of fuel slosh using Lie Group SE(3) . This paper applies Lie group SE(3) to the full body problem of spacecraft dynamics to investigate attitude perturbations caused by fuel slosh aboard the James Webb Space Telescope (JWST). We develop a dynamical model to parse these perturbations from slew telemetry data via residuals analysis. This model uses a novel, N-body Runge-Kutta integrator in the special Euclidean group SE(3). The enhanced ability to validate fuel slosh models reduces settling time after slew operations and, accordingly, maximizes available science time.

GN&C↗