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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Relativistic Electron Beams Accelerated By an Interplanetary Shock

Context: Collisionless shock waves have long been considered to be among the most prolific particle accelerators in the universe. Shocks alter the plasma they propagate through, and often exhibit complex evolution across multiple scales. Interplanetary (IP) traveling shocks have been recorded in situ for over half a century and act as a natural laboratory for experimentally verifying various aspects of large-scale collisionless shocks. A fundamentally interesting problem in both heliophysics and astrophysics is the acceleration of electrons to relativistic energies (> 300 keV) by traveling shocks. Aims: The reason for an incomplete understanding of electron acceleration at IP shocks is due to scale-related challenges and a lack of instrumental capabilities. This Letter presents the first observations of field-aligned beams of relativistic electrons upstream of an IP shock, observed thanks to the instrumental capabilities of Solar Orbiter. This study presents the characteristics of the electron beams close to the source and contributes to the understanding of their acceleration mechanism. Methods: On 25 July 2022, Solar Orbiter encountered an IP shock at 0.98 AU. The shock was associated with an energetic storm particle event, which also featured upstream field-aligned relativistic electron beams observed 14 min prior to the actual shock crossing. The distance of the beam’s origin was investigated using a velocity dispersion analysis (VDA). Peak-intensity energy spectra were analyzed and compared with those obtained from a semi-analytical fast-Fermi acceleration model. Results: By leveraging Solar Orbiter’s high temporal resolution Energetic Particle Detector (EPD), we successfully showcase an IP shock’s ability to accelerate relativistic electron beams. Our proposed acceleration mechanism offers an explanation for the observed electron beam and its characteristics, while we also explore the potential contributions of more complex mechanisms.

acceleration of particles↗
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

CLARREO Pathfinder (Cpf) State-of-the-Art Intercalibration Capabilities

NASA's Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission will deploy an Earth-observing reflected solar (RS) spectrometer, designed to measure Earth-reflected solar radiation from the International Space Station with a remarkable SI-traceable radiometric uncertainty of 0.3%-0.6% (k=1). The high-accuracy CPF measurements will provide an on-orbit reference for intercalibrating other spaceflight RS instruments. The CPF intercalibration team will showcase an innovative on-orbit intercalibration approach, wherein two other RS sensors—the shortwave (SW) channel of the Clouds and the Earth’s Radiant Energy System (CERES) and the Reflective Solar Bands (RSB) of the Visible Infrared Imager Radiometer Suite (VIIRS)—are intercalibrated against CPF benchmark measurements, with an unprecedented intercalibration methodology uncertainty of 0.3% (k=1).

climate↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and F1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

LSTM↗
NASA NTRSDate not supplied

Modeling NASA’s Procedural Requirement Processes – Implications for a 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).

NPR↗
NASA NTRS2023

Modeling the Formation and Eruption of Coronal Structures by Linking Data-Driven Magnetofrictional and MHD Simulations for AR 12673

Context .The data-driven and time-dependent modeling of coronal magnetic fields is crucial for understanding solar eruptions. These efforts are complicated by the challenges of finding a balance between physical realism and computing efficiency. One possible technique is to couple two modeling approaches. Aims . Our aim here is to showcase our progress in using time-dependent magnetofrictional model (TMFM) results as input to dynamical magnetohydrodynamic (MHD) simulations. However, due to the different evolution processes in these two models, using TMFM snapshots in an MHD simulation is nontrivial. We address these issues, both physically and numerically, discuss the incompatibility of the TMFM output to serve as the initial condition in MHD simulations, and show our methods of mitigating this. The evolution of the flux systems and the cause of the eruption are investigated. Methods . TMFM is a prevalent approach that has proven to be a very useful tool in the study of the formation of unstable structures in the solar corona. In particular, it is capable of incorporating observational data as initial and boundary conditions and requires shorter computational time compared to MHD simulations. To leverage the efficiency of data-driven TMFM and also to simulate eruptive events in the MHD framework, one can apply TMFM up to a certain time before the expected eruption(s) and then proceed with the simulation in the full or ideal MHD regime in order to more accurately capture the eruption process. Results . We show the results of a benchmark test case with a linked TMFM and MHD simulation to study the evolution of NOAA active region 12673. A rise of a twisted flux bundle through the MHD simulation domain is observed, but we find that the rate of the rise and the altitude reached depends on the time of the TMFM snapshot that was used to initialize the MHD simulation and the helicity injected into the system. The analysis suggested that torus instability and slip-running reconnection could play an important role in the eruption. Conclusions . The results show that the linkage of TMFM and zero-β MHD models can be successfully used to model the eruptive coronal magnetic fields.

F. Daei↗
NASA NTRSDate not supplied

Bayesian Symbolic Regression: Addressing Challenges in Estimating Fractional Bayes Factors and Application to Fatigue Crack Growth Modeling

This research pioneers advancements in computational mechanics by integrating Bayesian-based uncertainty quantification into symbolic regression, specifically focusing on the critical task of accurately estimating the fractional Bayes factor for selecting arbitrary equations. In our exploration, we rigorously study two prominent methods—sequential Monte Carlo and the Laplace approximation—employed for computing the fractional Bayes factor. Our findings underscore the limitations of the Laplace approximation, revealing its diminished accuracy in nonlinear and multimodal scenarios. Specifically, the Laplace approximation is shown to underpredict fractional Bayes factor on a wide set of equations associated with a symbolic regression benchmark. This comparative analysis sheds light on the nuanced performance of these techniques, guiding researchers toward more informed choices in uncertainty quantification within symbolic regression. Furthermore, we showcase the practical utility of these enhanced symbolic regression tools through their application to a real-world problem in fatigue crack growth modeling, emphasizing their efficacy in capturing the complexities of mechanical systems.

Geoffrey Bomarito↗
NASA NTRSDate not supplied

Equitable and Inclusive Public Outreach with the James Webb Space Telescope: Combining Art, Science, and Technology

This archived content may contain outdated information or references that may not reflect current policy or programs. NASA’s James Webb Space Telescope revealed its first images on July 12, 2022 and has been used for groundbreaking science since. Scientific exploration transcends international borders, making a mission like Webb feasible with collaborators including the European Space Agency (ESA), and Canadian Space Agency (CSA). Communication about NASA’s discoveries about the universe, so essential for involving the public, likewise needs to be inclusive to all. Art is a tool for cutting across the boundaries of language, culture, and ability, and serves as a bridge between the technical and non-technical communities. Art makes the beauty and nuance of science and engineering accessible in ways that may not be readily perceived to those outside of those communities of practice. Equitable and inclusive outreach endeavors are challenging to implement while considering language translations, culture context, sensory methods, and technology capabilities. Formats including “Unfolding the Universe'' virtual reality platform has allowed for a wider audience to interact with the Webb images including sounds, visual aids, and talks by the scientists and engineers who worked on Webb. This VR platform has been expanded to highlight the ESA contributors to the mission and will be showcased internationally. The Webb first images were also translated into sounds as a method of inclusion for anyone with sight disabilities. We will explore some successful outreach methods and suggestions for inclusivity in future.

Outreach↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and 𝐹1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

ATC↗
NASA NTRS2024

Building Identity and Community for Early Career Professionals in the Emerging Field of Astrobiology

To support training and foster retention in the emerging field of astrobiology, NASA has funded opportunities for graduate students and early career scientists to develop a community, foster interdisciplinarity, increase confidence, and showcase career options. The design of these opportunities builds on research on factors that increase retention, including feeling competent, having autonomy and a sense of purpose, having a sense of identity, and being connected to others in the field. Findings are reported from retrospective studies of two NASA career-building opportunities, the Astrobiology Graduate Conference and the International Astrobiology Summer School held in Santander, Spain. We present evidence that attendees gain confidence by presenting to, and working with, their peers, and feel competent to express their ideas and interests and build relationships in the field that continue after the experiences. Many say that they feel less isolated and go on to present or publish with colleagues they meet. Their career options also expand by meeting potential colleagues from different disciplines. Based on the findings, participating in either of these long-running programs shows clear positive impact on early career astrobiology professionals.

Early Career Researchers↗
NASA NTRS2024

Development of a Single Level Assessment Module for Simulating the Human Factors Concept Trade Space

This paper is a synopsis of the design and development of the Single Level Assessment Module (SLAM), a habitation mockup aimed at simulating volumetric conditions for astronauts in transit to Mars. Utilizing repurposed materials to enable low cost and constrained by various other design requirements from its parent vehicle, the SLAM embodies a critical step towards understanding human/habitat dynamics and interactions within the framework of the Mars Transit Habitat (TH) concept trade space. The synopsis begins by outlining the design constraints and goals, focusing on material availability and functional area volume requirements. Through various 3D design solutions, the SLAM emerges as a versatile habitat prototype, capable of accommodating various functional areas within its reconfigurable framework. The construction phase is then explored, highlighting the practical challenges and solutions encountered in assembling the SLAM's components. From panel assembly to outfitting functional areas, the construction process demonstrates a methodical approach to realizing the habitat's design intent. Looking ahead, the paper outlines future work, emphasizing the SLAM's adaptability for analysis and its potential to inform the design trade space future habitation concepts across the Moon to Mars architecture. By incorporating hinges for reconfigurability and facilitating volume assessments, the SLAM emerges as a crucial tool in advancing NASA’s ability to assess focused habitation configurations in conjunction with the development of the Moon to Mars architecture. In conclusion, this paper showcases the iterative process of habitat design, from conceptualization to construction.

Keith Lindsey↗
NASA NTRS2024

Enhancing Metal Additive Manufacturing Training with the Advanced Vision Language Model: A Pathway to Immersive Augmented Reality Training for Non-Experts

This paper introduces an innovative training system for the Renishaw AM400 metal printer, leveraging the synergy of the advanced Vision Language Model (VLM) with Augmented Reality (AR) within the Digital Twins (DT) framework. Aimed at overcoming the limitations of conventional training methods in metal additive manufacturing (AM), our system integrates AR to provide an immersive learning environment, enhancing the real-world experience with interactive digital overlays. The core of the system lies in its use of VLM, which, pre-trained on diverse datasets, excels in processing multi-modal data, thereby offering nuanced and contextually relevant guidance for trainees. Key experiments demonstrate the system’s effectiveness, particularly highlighting the usage of VLM as an Artificial Intelligence (AI) agent to integrate external tools like YOLO-v7 for valve state classification and CRAFT for control panel text recognition. This approach significantly improves recognition accuracy, operational understanding, and human–machine interaction, especially for non-expert users, making complex metal AM operations more accessible. The research not only showcases the potential of AR and VLM in industrial training but also sets a new standard for smart manufacturing practices, indicating broader applications in various industrial domains.

Metal additive manufacturing↗
NASA NTRS2024

Hawaiʻi Urban Development: Mapping Urban Infrastructure and Linkages to Wastewater Impacts across Hawaiʻi

Coastal ecosystems and human health across the Hawaiʻian islands are under threat from cesspools and other unpermitted wastewater infrastructure. Cesspools, or home sewage systems that hold wastewater effluent in porous concrete containers underground, discharge raw, untreated sewage directly into waterways. In fact, it is estimated that approximately 88,000 cesspools release 55 million gallons of raw sewage into Hawaiʻi’s waterways each day. Our partners, The Nature Conservancy, Hawaiʻi Regional Office (TNC) and University of Hawaiʻi, Mānoa (UHM), are heavily involved with the implementation and impact of Act 125, which was passed in 2017 by Hawaiʻi State Legislature to help combat these effects. This requires the conversion of cesspools to be upgraded and either converted to approved onsite disposal systems or connected to a sewer system so that the wastewater may be treated and to avoid leaching into the groundwater. Thus, identifying and locating cesspool and other unpermitted wastewater infrastructure is key to state and partner goals. Utilizing NASA Earth observations including Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 OLI-2 imagery, as well as pre-classified Sentinel-2 Multispectral Instrument (MSI) imagery in Esri’s Living Atlas, our team showcased the various perspectives that wastewater pollution research can use to assist in identifying and tracking urban development and concrete condition. This process was demonstrated by utilizing supervised object-based classification models, calculating various urban indices, and finding building size estimates to calculate effluent levels. Additionally, providing our partners with a GIS Methodology that can be built on to reach their future needs.

urban classification↗
NASA NTRSDate not supplied

Space Nuclear Propulsion 101

The Fission Surface Power (FSP) project is a NASA effort to demonstrate a tens of kilowatt class nuclear fission reactor power system on the Moon in next decade. Fission technology promises a class of long-duration Sun-independent scalable power systems with applications across the Solar System. The FSP project is just the beginning of the journey for this technology. This presentation will showcase the current state of the project, technical goals and accomplishments, future plans, and how this technology may find exciting future applications.

fission↗
NASA NTRSDate not supplied

Quantum Leap: Evaluating the Feasibility of Quantum Machine Learning Using NASA Earth Observational Data

This study explores the feasibility of leveraging quantum machine learning (QML) to analyze NASA Earth Observational (EO) data for climate change research, with a particular focus on the phenomenon of ”crop frosting” which has become more prevalent due to climate change. We implemented and evaluated two QML models, the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC), in both simulated and real quantum computing environments using a 127 qubit IBM quantum processor. Our study emphasizes the scientific rigor in comparing these quantum models with a classical Support Vector Machine (SVM) classifier, highlighting their performance in processing climate data. The results offer valuable insights into the potential scientific advantages, limitations, and scalability of QML for analyzing EO datasets, thus paving the way for more advanced climate modeling and predictive analytics using quantum computing. We showcased how Environmental Interaction Knowledge Graphs (EIKGs) and Digital Twins (DTs) can be integrated into this study. This research underscores the transformative potential of Classical and QML leveraging KGs and DT to address the multifaceted challenges posed by climate change.

Quantum Computing↗
NASA NTRSDate not supplied

Anticipating Hazard Impacts through Capacity Building and Co-development

Improving forecast accuracy, extending lead time, understanding hazard susceptibility, and integrating exposure and vulnerability data to generate impact-based forecasts are critical in mitigating disaster impacts. These efforts enable anticipatory action through enhancing the efficacy of early warning systems to assess potential multi-dimensional hazard impacts. In response to this need, SERVIR has co-developed a series of hazard services providing vital information from national to regional scales. This poster showcases examples of geospatial services co-developed with partners through a capacity building approach, supporting the establishment of hazard early warning / early action systems. These services integrate multidimensional vulnerability and exposure data to comprehensively assess impacts. Furthermore, these services demonstrate how co-development and capacity building can advance the development of impact-based forecasts and multi-hazards services. By prioritizing collaboration, human insights, local knowledge, capacity building, and employing applied science approaches in geospatial service development, this work has helped create inclusive and customized solutions. These solutions are tailored to meet the needs of local communities and are readily adaptable into decision-making processes.

weather↗
NASA NTRSDate not supplied

Integrated Multi-Satellite Retrievals for GPM (IMERG)

The Integrated Multi-satellitE Retrievals for GPM (IMERG) product from the U.S. Science Team of the NASA-JAXA Global Precipitation Measurement (GPM) mission provides global satellite precipitation estimates for a wide range of scientific research and societal applications. By adopting a constellation approach using low-Earth orbit passive microwave and geosynchronous-orbit infrared observations from domestic and international partners, IMERG is able to achieve a high resolution of 0.1° every half-hour globally, with three Runs to cater to applications with different latency requirements. With the completion of the reprocessing of the latest version, IMERG V07 now provides improved global satellite precipitation estimates for a period of more than 20 years. This presentation summarizes background on retrievals, the IMERG algorithm, and access to the data. As well, it showcases select results from the data, which might give participants ideas about how they can analyze the data themselves. The presentation ends with a prospectus for the timeline for the upcoming Version 08 and provides a list of references.

IMERG↗
NASA NTRSDate not supplied

Developing Mars-Based Clinical Scenarios for an Earth Independent Medical Operations (EIMO) – Based Decision Support Service

As crewed missions move beyond Low-Earth Orbit, pre-mission planning cannot fully buy down the medical risks of exploration-class missions. Martian missions, where increased hazards exist, (such as long-duration spaceflight, surface-level EVA operations, and communications delays) will require a paradigm shift in the structure of a medical system. An Earth-Independent Medical Operations-based Medical System (EIMO-MS) will need to optimize four critical domains to help provide medical care: utilization of Pre-Mission Planning, augmentation of Acute and Prolonged Medical Decision Making, automated tracking of Resource Management, and assistance in Task Load Balance. The ideal EIMO-MS will be able to accomplish this goal by having an interactive, adaptable interface that will be able to provide real-time medical services. It must respond based on the level of crewmember training, medical situation, and available medical and non-medical resources. To showcase the capabilities and requirements of such a sophisticated automated MS, a series of clinical scenarios of escalating complexity were developed with clinical and systems engineering input. These scenarios describe in clinical detail what a theoretical future medical system, enhanced with multiple information streams (such as a medical database, an AI-based Decision Support System, real-time monitoring, enhanced in-situ laboratory imaging, etc.) can achieve in conjunction with a trained and experienced crew. Scenarios are comprised of: a context section including objectives and applicable spaceflight environment, a highlighted assumptions section, a clinical narrative section, and a systems engineering activity diagram demonstrating the integrated Medical System (MS). The “swim lanes” of the activity diagram act as the logistical core of each scenario and show how the MS will interact with the crew, ground support, and other in-flight systems. The Design Reference Mission that is used for the scenarios is based on existing reference mission profiles [1] with a projected 30-sol stay on the Martian surface. Scenarios span the spectrum from planned evaluations, minor medical care, urgent care, surgical guidance, critical and expectant management, and behavioral health care. Mission complexity will exponentially increase during deep space and Mars exploration-class missions, and medical support for these missions will likewise need to increase in autonomy and adaptability. The integrated system that will support these missions will need to provide assistance in a variety of anticipated and unforeseen scenarios. These medical scenarios, guided by clinician input, are initial steps in crafting the requirements for an EIMO-based medical system. By working in a systems engineering framework, requirements and capabilities can be extracted and mapped while maintaining a clinical core.

Prashant Parmar↗