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NASA NTRSDate not supplied

Successes and Failures of Metal Additive Manufacturing for Rocket Engines

NASA has been developing additive manufacturing (AM) for various technical and programmatic advantages for complex rocket engine and aerospace components. This maturation has focused on various AM processes, new alloys, characterizing material properties, developing standards, producing demonstrator parts, and integrating AM hardware in liquid rocket engines through test-fail-fix cycles, as well as application and dissemination of lessons learned of the AM lifecycle. The importance of proper AM processing was made evident in the failure of a Laser Powder Bed Fusion (L-PBF) copper-alloy combustion chamber during a hot-fire test due to a degraded material quality. The hot-fire test aimed to demonstrate high duty cycle under a risk-tolerant development project, where consequences of component failure would be minimal. However, the unintentional component failure emphasized the necessity of robust material characterization and rigorous process control procedures for the safe use of AM components in critical applications. This presentation provides an overview of the development failure, a discussion on the evaluation of the failed chamber and supplemental chambers produced at the same time, a representative material samples that included intentional build witness lines, and a summary of the key results and recommendations from the evaluations. NASA continues to approach AM processes and designs with a level of risk and acceptance of failures that is appropriate for the project objectives, with the overall goal of safe implementation of AM technology and transferring AM technology into commercial space applications. This presentation with provide critical awareness to the community lessons learned on proper implementation of AM.

Additive Manufacturing↗

NASA NTRSDate not supplied

End-user Assessment of the NASA SPoRT GLM Stoplight Product

National Weather Service (NWS) offices monitor and forecast the threat for lightning within their County Warning Areas for various impact-based decision support services (IDSS). These forecasts are provided routinely for aviation operations, but irregularly for large-scale, outdoor events, which typically have varying safety requirements with regards to lightning. Lightning monitoring and forecasting can require synthesizing a plethora of data, so products that make this process more efficient and effective are sought by the operational community. The NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop several products to address these operational challenges during the lifecycle of lightning activity, and conduct evaluations in concentrated (Research-to-Operations/Operations-to-Research) efforts. The product evaluated for this study is the Geostationary Lightning Mapper (GLM) Stoplight product, which addresses lightning safety specifically with regards to lightning recency and cessation. The GLM Stoplight product displays the spatial extent of lightning and uses color-coded pixels to show the recency of lightning in 10-minute increments. This presentation highlights results from an assessment of the GLM Stoplight product by select NWS offices, as well as emergency managers, that took place over a 5-week period from May 1st to June 2nd. Feedback was collected on the GLM Stoplight product and on a new and interactive lightning viewer, which allowed participants to tailor visualization of the product based on their location and desired application. Results will help NASA SPoRT gain a better understanding of how forecasters and emergency managers use lightning data for safety applications. In addition, the assessment will inform research on any necessary modifications to this and future lightning products to assist end users.

Kelley Murphy↗

NASA NTRSDate not supplied

Looking Local: Milky Way Science with JWST

The James Webb Space Telescope has only been operating for a short time, but has already revolutionized multiple areas of astrophysics, including our understanding of our home Galaxy. With a 6.6 meter primary mirror and four infrared science instruments, JWST’s science mission includes measurements of exoplanet atmospheres, observations of the chemistry of molecular clouds, tracing the lifecycle of dust in the interstellar medium (ISM), investigations of galaxy mergers and probing the first galaxies and the cosmological history of the universe. By investigating the Milky Way with JWST astronomers can not only better understand the physics, chemistry and dynamics of our own backyard, but these results can be used to more accurately inform the interpretation of observations of the distant universe. This presentation will detail JWST’s capabilities for conducting observations and surveys in the Milky Way, as well as highlight some early results from the observatory.

Erin C. Smith↗

NASA NTRSDate not supplied

Managing HRP’S External Deliverables: The Process and the Customers

The Human Research Program’s (HRP) external deliverables (EDs) are the final outcomes of the research that the HRP Elements develop and execute. Four categories of HRP EDs exist: standards, requirements, countermeasures, and tools/technology. The NASA Human Health and Performance directorate’s primary stakeholders, i.e., the customers for the EDs, include the Office of the Chief Health and Medical Officer (OCHMO) (Standards Team, Chief Health and Performance Officers and Chief Medical Officers, Human System Risk Board), and the agency’s System Capability Leadership Teams. The EDs may address the need of a specific customer, a specific design reference mission, or a vehicle lifecycle milestone. HRP’s Maturation and Integration Office External Programs facilitates the process of delivering the EDs to the targeted customers according to the customer’s expectations. This presentation describes this coordinated process and provides an overview of the nature of different types of EDs and how they impact the customers’ products. Successful transfer of the EDs to the customers will help mitigate the health and performance risks that crewmembers will face during NASA’s future exploration missions.

HRP research external deliverables↗

NASA NTRSDate not supplied

Machine Learning Airport Surface Model

Future needs of the National Airspace System require decision support tools to adopt a service-oriented architecture in alignment with the FAA’s vision for an Info-Centric NAS. To achieve this, many existing systems will need to undergo a digital transformation from a monolithic decision support tool to a service-oriented architecture where individual services are exposed through well defined Application Programming Interfaces (APIs). To enable this transformation, NASA has developed the Digital Information Platform as a cloud based foundation for development of aviation services with a special focus towards Artificial Intelligence and Machine Learning (ML) services. This paper describes the work required for the transformation of NASA’s legacy surface management system to a real-time ML based decision support system deployed in the cloud. Details of the Machine Learning Operations (MLOps) infrastructure and best practices are described which enabled the end-toend lifecycle management of ML within an integrated software system. Validation results are provided from an operational field evaluation where performance was benchmarked against the legacy approach.

Jeremy Coupe↗

NASA NTRSDate not supplied

Metadata Entry Optimization for NASA's Biological Institutional Scientific Collection (NBISC)

The NASA Biological Institutional Sample Collection (NBISC) at NASA’s Ames Research Center is a critical resource housing non-human samples collected from spaceflight missions and ground analog studies, primarily consisting of specimens from rats, mice, and select microbes. The primary objective of NBISC is to systematically receive, document, preserve, and facilitate access to these samples for the global scientific community. NBISC promotes international collaboration and maximizes the return on investment for precious tissues from spaceflight and analog experiments. Researchers can request physical samples through an online request form and subsequent written proposal review process. This study addresses two core research objectives: streamlining the NBISC sample lifecycle processes and strategizing for managing an influx of 50,000 tissue samples from a series of cosmic radiation analog experiments carried out at the NASA Space Radiation Laboratory (NSRL) by Drs. Eleanor Chang (Lawrence Berkeley Laboratory) and Polly Blakely (SRI). The Chang/Blakely studies investigated Harderian gland (HG) tumorigenesis in mice exposed to low dose and LET radiation comprising 8 different exposure protocols in over 4000 mice. NBISC sample metadata is stored in a Laboratory Information Management System (SLIMS). To streamline sample data entry, we customize python scripts using information extracted from the individual experimental protocols. The scripts automate entry into multiple SLIMS data fields including protocol name, unique sample barcode, tissue and sub-tissue information, freezer location, sample preservation method, etc. The semi-automated procedure significantly decreases the time spent on data entry by several orders of magnitude. Automation and data organization are essential, as they free up time for curation and promotion of the collection which, in turn, increase the accessibility of samples to the broader research community. NBISC benefits from streamlined data ingestion, and the methodologies developed here are applicable to other projects which use SLIMS including the NASA Biospecimen Sharing Program and GeneLab. As of Fall 2023, plans include transferring sample data from SLIMS to public facing repositories (OSDR and NLSP), expanding the reach of the Chang/Blakely sample collection. The Human Research Program Space Radiation Element plans to transfer non-human tissues from many more investigations to NBISC in the coming year.

Sample Repository↗

NASA NTRSDate not supplied

Metadata Entry Optimization For NASA's Biological Institutional Scientific Collection (NBISC)

Biospecimen↗

NASA NTRSDate not supplied

Simulating Sulfate Aerosol Size in the Hunga Tonga Plume: Comparisons with Observations

Using the NASA GEOS Chemistry Climate Model (CCM) coupled to a detailed sectional aerosol microphysical model, we have simulated the January 2022 Hunga Tonga-Hunga Ha’apai (HTHH) plume. We have developed a version of the Global Modeling Initiative (GMI) chemistry mechanism to include the requisite sulfur chemistry and coupled it to the Community Aerosol and Radiation Model for Atmospheres (CARMA) sectional aerosol microphysics within the GEOS CCM. Our simulations focus on the lifecycle of stratospheric sulfur injected by the eruption–from the oxidation of the injected sulfur dioxide to the nucleation, growth, coagulation, hydration, and eventual settling of the volcanic sulfate aerosol particles. In order to constrain the simulated microphysics, we focus on comparing our model to observations with aerosol size information, namely in-situ particle counter observations and multi-wavelength satellite observations from OMPS-LP and SAGE-III. This eruption provides an interesting test case for our model; both the modeled gas-phase chemistry as well as the modeled aerosol microphysics are perturbed by the massive injection of water that accompanied the primary sulfur emissions from the eruption.

aerosols↗

NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗

NASA NTRSDate not supplied

End-User Assessment of the NASA SPoRT Lightning AI Product

The NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop products to address operational challenges and enhance safety during the lifecycle of lightning activity, and conduct evaluations in concentrated R2O/O2R efforts. The product evaluated for this study is Lightning Artificial Intelligence (A.I.), which predicts the probability of lightning out to 15 minutes in advance and spatially maps it using filled color contours. Lightning A.I. uses reflectivity, differential reflectivity, and correlation coefficient data from a subset of radars within the NEXRAD network to generate lightning probabilities at approximately 2 km resolution. The domains, spanning 145 x 145 km are centered over NASA-affiliated centers across the CONUS and use radar data which are closest in proximity. Lightning A.I. was developed with intended use by emergency managers at NASA centers. However, National Weather Service (NWS) offices are also often tasked with monitoring and forecasting the threat for lightning within their County Warning Areas for various impact-based decision support services. These forecasts are typically provided for aviation operations and large-scale, outdoor events, which may have varying safety requirements for decision-making based on lightning proximity and recency. The NASA SPoRT center conducted an assessment of the operational uses of Lightning A.I by various collaborative NWS Offices from late July into early September. This assessment included feedback from participants on both the product itself as well as its accessibility within the new, interactive NASA SPoRT Lightning Viewer. This presentation will include background information about Lightning A.I. and highlight results from this assessment. The feedback from the assessment will be used to inform research on any necessary modifications to this and future lightning products to assist end users.

Kelley Murphy↗

NASA NTRSDate not supplied

An Overview of NASA’s Airborne and Field Data Resource Center

A key recommendation from NASA’s 2022 Airborne and Field Data Workshop called for the development of a virtual Resource Center for all stakeholders across the data lifecycle of airborne and field Earth observations. The agency’s Earth Science Data and Information System (ESDIS) Project and Airborne Data Management Group (ADMG) have worked in concert to establish the newly launched NASA Airborne and Field Data Resource Center (AFDRC) to provide a single entry point for a wide assortment of information on and the effective, responsible stewardship of non-satellite observational data. The AFDRC compiles access to many existing resources, but does so in a newly organized way that integrates availability to increase efficiency and holistic understanding while simplifying users’ experience. Initially launched in fall of 2023, the AFDRC is a NASA Earthdata domain website that clarifies several previously disparate resources and provides newly updated information, including: Learning Resources: Educational resources to broaden understanding of the role airborne and field observations play in advancing understanding of our planet and NASA’s role in collecting and archiving these data. Support for data users to Find and Access Data: Advanced contextual browse/search capabilities that efficiently link researchers to data products suitable for their science objectives - this includes linking to NASA’s Catalog of Archived Suborbital Earth Science Investigations (CASEI). Working with Data: Tools specific to individual types of suborbital Earth Science data and their (inter-)disciplinary communities to provide access as well as guidance for their application. Stewardship Responsibilities: Resources for data producers with to lessen requirement burdens at the time of data transfer, and information for data stewards with consistent, authoritative guidance on best practices and agency- and/or community- specific archival procedures. This presentation will give an overview of the motivation for NASA’s AFDRC, approach for the design and content, iterative community-driven improvements, promote the use of the AFDRC, and solicit additional feedback from airborne and field data user communities.

Sara Lubkin↗

NASA NTRSDate not supplied

Managing HRP's External Deliverables: The Process and the Customers

The Human Research Program’s (HRP) external deliverables (EDs) are the final outcomes of the research that the HRP Elements develop and execute. The NASA Human Health and Performance directorate’s primary stakeholders, i.e., the customers for the EDs, include the Office of the Chief Health and Medical Officer (OCHMO) (Standards Team, Chief Health and Performance Officers and Chief Medical Officers, Human System Risk Board), and the agency’s System Capability Leadership Teams. The EDs may address the need of a specific customer, a specific design reference mission, or a vehicle lifecycle milestone. HRP’s Maturation and Integration Office External Programs facilitates the process of delivering the EDs to the targeted customers according to the customer’s expectations. This presentation describes this coordinated process and provides an overview of the nature of different types of EDs and how they impact the customers’ products. Successful transfer of the EDs to the customers will help mitigate the health and performance risks that crewmembers will face during NASA’s future exploration missions.

research↗

NASA NTRSDate not supplied

Scoping, Tailoring, and Abstraction Refinement in Hazard Assessment Processes

Hazard assessment is an engineering activity that produces insight into which states of thing being engineered might be hazardous. In aviation contexts, it is often performed for certification credit at both the aircraft and system levels during the early design phase of the system’s lifecycle. However, novel aircraft paradigms such as urban air mobility (UAM)operations might either violate assumptions on which traditional aviation hazard assessment is based or simply possess attributes that would make other approaches more effective. In this paper, we define the key concepts under pinning hazard assessment and identify the limitations and assumptions inherent in hazard analysis. We analyze popular techniques to show how they embody these key concepts. We identify ways in which hazard assessment may be scoped and tailored to an application. And, using worked examples, we discuss how, where, and why such tailoring might be needed, especially in novel contexts.

aviation safety↗

NASA NTRSDate not supplied

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗

NASA NTRSDate not supplied

Scoping, Tailoring, and Abstraction Refinement in the Hazard Assessment Process

Hazard assessment is an engineering activity that produces insight into which states of thing being engineered might be hazardous. In aviation contexts, it is often performed for certification credit at both the aircraft and system levels during the early design phase of the system’s lifecycle. However, novel aircraft paradigms such as urban air mobility (UAM) operations might either violate assumptions on which traditional aviation hazard assessment is based or simply possess attributes that would make other approaches more effective. In this paper, we define the key concepts underpinning hazard assessment and identify the limitations and assumptions inherent in hazard analysis. We analyze popular techniques to show how they embody these key concepts. We identify ways in which hazard assessment may be scoped and tailored to an application. And, using worked examples, we discuss how, where, and why such tailoring might be needed, especially in novel contexts.

Aviation Safety↗

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 NTRSDate not supplied

Towards a Marine Stratus Climatology on Drizzle Occurrence from CALIPSO

Marine stratus are a predominant feature of our planet with the annual mean coverage exceeding 20%. They strongly reflect sunlight, yet exert only a modest effect on outgoing infrared radiation, providing a significant net cooling to the Earth’s radiative balance. Their formation is coupled to boundary layer circulations that are driven, in part, by cloud top radiative cooling and evaporative cooling from precipitation in downdrafts. Understanding how these cloud systems evolve as the climate changes is a key question that requires additional information on their lifecycle and microphysical properties to accurately represent their behavior in global circulation models. From a large-scale perspective, insight into the microphysical properties of marine stratus at cloud top can be realized through estimates of the effective radius (Re) of the droplet size distributions derived from MODIS observations. Estimates on the occurrence of rain/drizzle are available from CloudSat. Together these observations indicate that precipitation frequently occurs in clouds with higher cloud top Re. This relationship is consistent with the well documented shift in cloud top droplet size distributions towards fewer, yet larger droplets prior the onset of precipitation. Here we report on a new and complementary set observations from the CALIPSO mission. The approach derives an extinction-to-backscatter ratio (Sc, also known as the cloud lidar ratio) using an established relationship that depends on observations of the lidar attenuated backscatter and volume depolarization ratio within the cloud. Because Sc is strongly and inversely related to Re, a change in the derived Sc from higher to lower values corresponds to a change in the droplet size distribution as seen by MODIS. This change in the lidar signals at cloud top clearly identifies clouds that are capable of precipitation. The presentation provides a brief overview of the approach for deriving Sc and compares CALIOP-derived Sc with observations from other techniques. CALIOP classifications of drizzling clouds, based on the retrieved values Sc, are compared to independent, collocated assessments of drizzle occurrence reported in the standard CloudSat data products. Regional and seasonal comparisons highlight the strengths and weaknesses of the two sensors. A machine learning approach that combines information from both CALIOP and CloudSat showcases possible improvements in the global identification of scenes likely to contain rain-bearing clouds.

CALIPSO↗

NASA NTRSDate not supplied

Modeling NASA’s Procedural Requirement Processes – Implications for a Digital Future

NPR↗