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At least 145 records · Page 8

An Automated Approach to Labelling Datasets in Earth Science Publications

NASA Data Active Archive Centers, orDAACs, ingest, store, and distribute dataacquired from satellites, ground systems as well asreanalysis models. Many authors use this datain their research. However, most of the datasets usedin Earth Science Publications are not citedcorrectly or not cited at all. Thus, there is no directlink between the datasets used and thescientific publications which reference them. Thisleads to issues with reproducibility of theresults, attribution of the research results, anddiscovery of new datasets. This project began byexploring various methods of automatically labellingGoddard Earth Sciences Data andInformation Services Center (GES DISC) datasets usingSupervised Machine Learning and EarthData Search Common Metadata Repository (CMR) queries.The ultimate goal was to create alibrary of citations that utilized automated citationlabeling to directly link the researchpublications to the data they use. Supervised MachineLearning approaches struggled due to thelimited amount of labelled training data to learnfrom. Increasing the volume of training data isdifficult as it requires subject matter experts todevote time to manually reviewing journalarticles and determining the datasets used. The CMRqueries were inconsistent because theunderlying metadata is continuously being updated.Thus, it is hard to generalize theeffectiveness of the CMR results as they are dependenton the internal state of CMR. Theseapproaches helped inform the decision to transitionthe project into using a Knowledge Graph.Another key aspect of this project focused on theautomated extraction of features (platform,instrument, variables, etc) and explicit citationsfrom within Earth Science Publications. Theseautomated extractions were used to classify researchpapers based on their platform/instrumentcouples. This information was input into the CitationManagement System for GES DISC. Theseplatform/instrument couples also provide an additionalfacet that can be searched on the GESDISC website.

Edward Jahoda↗

Lunar Gateway Charging and Effects on Low-Energy Electron Measurements

The Electron Electrostatic Analyzer (EEA) is part of the HERMES instrument suite on Lunar Gateway and is designed to measure electrons in the energy range from 1 eV to 18 keV. Electrons in this range can be deflected or blocked from entering a detector by electric fields from a charged spacecraft platform, so many heliophysics missions (MMS, Cluster, etc.) use active potential control to minimize stray electric fields which would corrupt low-energy plasma measurements. Gateway, however, does not have such capabilities so the surface charging effects will influence the electron data. Further, some elements of Gateway partially block the instrument’s field of view to space. The effects of the Gateway platform on the low-energy electron population must be understood to maximize the accuracy of the EEA data. To investigate the electrostatic environment near Gateway and its effects on the EEA measurements, we use Nascap-2K to model the expected charging of Gateway under representative solar wind, magnetosheathic, and magnetospheric conditions. Next, we use the potential and electric field outputs from Nascap-2K along with in-house particle tracing codes to investigate how low-energy electrons are perturbed, blocked, or deflected by the spacecraft. We discuss how these perturbations impact the plasma moments computed from the EEA data and possible approaches for correcting the charging effects including application of advanced methods such as neural networks. In addition to electrons from the space environment being influenced by the electrostatic environment around Gateway, photoelectrons generated on Gateway surfaces will also be measured by EEA. We are investigating how knowledge of the potentials of various Gateway surfaces can be extracted from these measured photoelectrons using advanced numerical modeling and analysis. Such information would be valuable for validating charging models and planning mission operations around the platform. Finally, we discuss how the specific workflow developed for Gateway can be extended to a generalized process that is applicable to other future missions. As the space industry prepares for human exploration beyond low-Earth orbit, the need to obtain accurate space weather data from rideshare science payloads is critical. Our process for removing platform effects from the science data serves as a pathfinder for leveraging advanced simulations to maximize science returns and ensure the safety and success of future crewed missions.

Miles Bengtson↗

Better Spectrometers, Beautiful Spectra and Confusion for All

The confluence of enormous improvements in submillimeter receivers and the development of powerful large scale observatories is about to force astrophysics and the sciences that support it to develop novel approaches for interpretation of data. The historical method of observing one or two lines and carefully analyzing them in the context of a simple model is now only applicable for distant objects where only a few lines are strong enough to be observable. Modern observatories collect many GHz of high signal-to-noise spectra in a single observation and in many cases, at sufficiently high spatial resolution to start resolving chemically distinct regions. The observatories planned for the near future and the inevitable upgrades of existing facilities will make large spectral data sets the rule rather than the exception in many areas of molecular astrophysics. The methodology and organization required to fully extract the available information and interpret these beautiful spectra represents a challenge to submillimeter astrophysics similar in magnitude to the last few decades of effort in improving receivers. The quality and abundance of spectra effectively prevents line-by-line analysis from being a time efficient proposition, however, global analysis of complex spectra is a science in its infancy. Spectroscopy at several other wavelengths have developed a number of techniques to analyze complex spectra, which can provide a great deal of guidance to the molecular astrophysics community on how to attack the complex spectrum problem. Ultimately, the challenge is one of organization, similar to building observatories, requiring teams of specialists combining their knowledge of dynamical, structural, chemical and radiative models with detailed knowledge in molecular physics and gas and grain surface chemistry to extract and exploit the enormous information content of complex spectra. This paper presents a spectroscopists view of the necessary elements in a tool for complex spectral analysis.

Spectral Analysis↗

Extraction of Thruster Plume Ion Population Trends From Retarding Potential Analyzer Data

Characterization of ion plume impingement effects on spacecraft surfaces requires knowledge of the ion energy distributions in the thruster plume. Retarding potential analyzers are a convenient diagnostic that provide measurements of the ion voltage distributions. This work presents an attempt to extract additional information via fitting multiple Maxwellian distributions to the diagnostic traces. Tracking the trends of the fitted ion populations across varying facility pressure, angular location, and thruster operating conditions offers further insight into the makeup of the plume plasma and the behavior of the ion energies as a function of those parameters. This approach provides supporting evidence in establishing margins and building further confidence in the plume modeling validation process.

John T. Yim↗

Influence of Water Sorption on Ionic Conductivity in Polyether Electrolytes at Low Hydration

Ion-containing polymers are subject to a wide range of hydration conditions across electrochemical and water treatment applications. Significant work on dry polymer electrolytes for batteries and highly swollen membranes for water purification has informed our understanding of ion transport under extreme conditions. However, knowledge of intermediate conditions (i.e., low hydration) is essential to emerging applications (e.g., electrolyzers, fuel cells, and lithium extraction). Ion transport under low levels of hydration is distinct from the extreme conditions typically investigated, and the relevant physics cannot be extrapolated from existing knowledge, stifling materials design. In this study, we conducted ion transport measurements in LiTFSI-doped polyethers that were systematically hydrated from dry conditions. A semiautomated apparatus that performs parallel measurements of water uptake and ionic conductivity in thin-film polymers under controlled humidity was developed. For the materials and swelling range considered in this study (i.e., <0.07 g water/g dry polymer electrolyte), ionic conductivity depends nonlinearly on water uptake, with the initial sorbed water weakly affecting conductivity. With additional increases in swelling, more significant increases in conductivity were observed. Remarkably, changes in conductivity induced by water sorption were correlated with the number of water molecules per lithium ion, with the normalized molar conductivity of different samples effectively collapsing onto one another until this unit of hydration exceeded the solvation number of lithium ions under aqueous conditions. Furthermore, these results provide important knowledge regarding the effects of trace water contamination on conductivity measurements in polymer electrolytes and demonstrate that the lithium-ion solvation number marks a key transition point regarding the influence of water on ion transport in ion-containing polymers.

36 MATERIALS SCIENCE↗

Concepts of Operations for Asteroid Rendezvous Missions Focused on Resources Utilization

Several asteroids are the targets of international robotic space missions currently manifested or in the planning stage. This global interest reflects a need to study these celestial bodies for the scientific information they provide about our solar system, and to better understand how to mitigate the collision threats some of them pose to Earth. Another important objective of these missions is providing assessments of the potential resources that asteroids could provide to future space architectures. In this paper, we examine a series of possible mission operations focused on advancing both our knowledge of the types of asteroids suited for different forms of resource extraction, and the capabilities required to extract those resources for mission enhancing and enabling uses such as radiation protection, propulsion, life support, shelter and manufacturing. An evolutionary development and demonstration approach is recommended within the framework of a larger campaign that prepares for the first landings of humans on Mars. As is the case for terrestrial mining, the development and demonstration approach progresses from resource prospecting (understanding the resource, and mapping the 'ore body'), mining/extraction feasibility and product assessment, pilot operations, to full in-situ resource utilization (ISRU). Opportunities to gather specific knowledge for ISRU via resource prospecting during science missions to asteroids are also examined to maximize the pace of development of needed ISRU capabilities and technologies for deep space missions.

radiation protection↗

Modelisation of the optical scattering behaviour of the vegetation canopies

The three dimensional model of Kimes (1984) which can treat three dimensional variability in heterogeneous scenes, was used to test and expand physical scattering mechanisms involved in reflectance distribution dynamics by analyzing modeling and field data. The major physical phenomena causing the directional scattering behavior of vegetation canopies are presented. These include the strong anisotropic properties of the soil, and the anisotropic scattering properties of the vegetation as described by the phase function of the leaves and the geometric effects caused by vertical layers of leaves. This knowledge serves as a basis for defining optimum directional view angles for remote sensing strategies. An example on using knowledge of the scattering behavior of vegetation to develop techniques for extracting vegetation parameters (spectral albedo) from directional reflectance data is presented.

Kimes, D. S.↗

Supporting Hazard Analysis for Wildfire Response Using fmdtools and MIKA

The System Wide Safety (SWS) Safety Demonstrator (SD) Series drives development of an increasingly capable In-Time Aviation Safety Management System (IASMS) focusing on humanitarian applications, starting with wildfire response (SD-1). The goals of this report are to (1) provide an early hazard analysis and mitigation evaluation of wildfire response to support these efforts and (2) provide a demonstration of capabilities of the Fault Model Design Tools (fmdtools) and Manager for Intelligent Knowledge Access (MIKA) tools. fmdtools provides a modeling, simulation, and resiliency analysis framework in which a wildfire response model, the System Modeling and Analysis of Resiliency in Scalable Traffic Management for Emergency Response Operations (SMARt-STEReO), is built. MIKA is an intelligent knowledge manager with several capabilities, including assisting in hazard analysis by extracting and analyzing hazards from historical incident reports. The following topics are covered in the report: Understanding Wildfire Hazard Dynamics. We provide a description and simulated examples of how hazards occur in the SMARt-STEReO model of wildfire response and their effect on its outcome. This provides a common mental model and focuses the analysis presented in the remainder of the report. Wildfire Hazard Identification. MIKA identifies wildfire hazards from three relevant datasets: the ICS-209-PLUS, SAFECOM, and SAFENET. Hazards are manually organized into a taxonomy and MIKA analyzes each hazard’s effects, likelihood, severity, and risk. Evaluating Mitigation Strategies. The SMARt-STEReO wildfire response model built in fmdtools evaluates a subset of identified hazards. Specifically, we simulate the effect of communications faults and equipment faults on operator safety, the effect of changing winds and flammability, and a scenario with multiple ignition points and heavy smoke. Tool Limitations and Usage Considerations. We provide a discussion of appropriate tool use cases as well as limitations and considerations for usage. The tool findings are used to synthesize recommendations for wildfire response operations, which can be captured as part of an IASMS. Key recommendations are as follows: Hazards are identified from a broad spectrum of sources including aircraft subsystems, operational sources, and ground crew operations. Highest risk operational environment hazards identified are Evacuations. The highest risk manned aerial operations hazard categorized is Jumper Operations Mishap. Ground crew hazards that are highest risk are Burns, Cargo Operations Overhead, Dehydration, Entrapment, Falling Objects, Heart Attacks, Heat Exhaustion, Inadequate Training or Certification, Vehicle Breakdown, and Vehicle Collision. Modelled containment failures arise from a mismatch between the difficulty of the firefighting scenario and the capacity (e.g., speed, effectiveness, awareness) of the response. In firefighting scenarios where containment is possible (e.g., because the fire does not spread too quickly), these mismatches can occur because of a change in environmental conditions (e.g., wind, flammability, etc) or because of planning, equipment, or communications faults. Improvements to communications increase the capacity of the firefighting response by reducing the time needed to respond to the fire. While surveillance does not increase this capacity by itself, it increases operator safety by increasing state awareness, enabling firefighters to evade approaching fires. Increasing both has a synergistic effect. In general, these performance and resilience increases generalize over fault scenarios as well as unforeseen changes to circumstances (i.e., wind, aridity, etc.). However, these improvements need to be designed so as not to make the system prone to persistent large-scale communications outages, which can reduce performance.

Hazard analysis↗

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

A Rapid Approach to Modeling Species-Habitat Relationships

A growing number of species require conservation or management efforts. Success of these activities requires knowledge of the species' occurrence pattern. Species-habitat models developed from GIS data sources are commonly used to predict species occurrence but commonly used data sources are often developed for purposes other than predicting species occurrence and are of inappropriate scale and the techniques used to extract predictor variables are often time consuming and cannot be repeated easily and thus cannot efficiently reflect changing conditions. We used digital orthophotographs and a grid cell classification scheme to develop an efficient technique to extract predictor variables. We combined our classification scheme with a priori hypothesis development using expert knowledge and a previously published habitat suitability index and used an objective model selection procedure to choose candidate models. We were able to classify a large area (57,000 ha) in a fraction of the time that would be required to map vegetation and were able to test models at varying scales using a windowing process. Interpretation of the selected models confirmed existing knowledge of factors important to Florida scrub-jay habitat occupancy. The potential uses and advantages of using a grid cell classification scheme in conjunction with expert knowledge or an habitat suitability index (HSI) and an objective model selection procedure are discussed.

Carter, Geoffrey M.↗

Mechanism of Lithium Ion Exchange Into Spinel Manganese Oxide

Lithium manganese oxide (LMO) is an effective absorbent for lithium recovery from brines, characterized by its high adsorption capacity, excellent regeneration performance, and selectivity. Here, this study investigates the mechanisms of material degradation during lithium loading and unloading in LMO, employing a combination of time‐resolved Raman spectroscopy, X‐ray diffraction, and X‐ray photoelectron spectroscopy. Key findings reveal that the A 1g vibrational mode wavenumber shifts from 635 cm −1 at the onset of lithium ion exchange to 656 cm −1 after 12 min, indicating local symmetry loss and manganese (Mn) loss during lithium intercalation. The proposed lithium exchange mechanism involves initial occupation of tetrahedral interstitial voids, followed by migration into interstitial sites between Mn octahedral sites. Computational modeling suggests that the loss of symmetry in MnO cubane‐like groups occurs as lithium migrates, significantly affecting the Raman spectra. Importantly, the study demonstrates that after 100 cycles of lithium/hydrogen loading, a 24% loss in Mn is observed, which correlates with decreased structural stability; however, the structural integrity of LMO is enhanced when subjected to multiple cycles without complete loading. Here, these insights contribute to the understanding of LMO's performance in lithium recovery applications and highlight potential strategies to optimize its use in future technologies.

15 GEOTHERMAL ENERGY↗

Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1

Abstract. Groundwater plays a key role in meeting water demands, supplying over 40 % of irrigation water globally, with this role likely to grow as water demands and surface water variability increase. A better understanding of the future role of groundwater in meeting sectoral demands requires an integrated hydro-economic evaluation of its cost and availability. Yet substantial gaps remain in our knowledge and modeling capabilities related to groundwater availability, recharge, feasible locations for extraction, extractable volumes, and associated extraction costs, which are essential for large-scale analyses of integrated human–water system scenarios, particularly at the global scale. To address these needs, we developed Superwell, a physics-based groundwater extraction and cost accounting model that operates at sub-annual temporal and at the coarsest 0.5° (≈50 km × 50 km) gridded spatial resolution with global coverage. The model produces location-specific groundwater supply–cost curves that provide the levelized cost to access different quantities of available groundwater. The inputs to Superwell include recent high-resolution hydrogeologic datasets of permeability, porosity, aquifer thickness, depth to water table, recharge, and hydrogeological complexity zones. It also accounts for well capital and maintenance costs, as well as the energy costs required to lift water to the surface. The model employs a Theis-based scheme coupled with an amortization-based cost accounting formulation to simulate groundwater extraction and quantify the cost of groundwater pumping. The result is a spatiotemporally flexible, physically realistic, economics-based model that produces groundwater supply–cost curves. We show examples of these supply–cost curves and the insights that can be derived from them across a set of scenarios designed to explore model outcomes. The supply–cost curves produced by the model show that most (90 %) nonrenewable groundwater in storage globally is extractable at costs lower than USD 0.57 m−3, while half of the volume remains extractable at under USD 0.108 m−3. The global unit cost is estimated to range from a minimum of USD 0.004 m−3 to a maximum of USD 3.971 m−3. We also demonstrate and discuss examples of how these cost curves could be used by linking Superwell's outputs with other models to explore coupled human–environmental system challenges, such as water resources planning and management, or broader analyses of multisectoral feedbacks.

Global Change Analysis Model (GCAM)↗

Nonhydrodynamic Characteristics of the Oscillating Screen Viscometer

Extraction of the viscosity from the oscillating screen's response function requires knowledge of it resonance frequency omega(sub 0) and of the prefactor k(sub tr)/k(theta), where k(sub tr) is a transducer coefficient and k(sub theta) is the torsion spring constant. The determination of these parameters is described. The effect of a possible anomaly in the dielectric constant near the critical point of xenon will be negligible.

Berg, Robert F.↗

Recognition of object domain by color distribution

For the image processing of an object in its natural image, it is necessary to extract in advance the object to be processed from its image. To accomplish this the outer shape of an object is extracted through human instructions, which requires a great deal of time and patience. A method involving the setting of a model of color distribution on the surface of an object is described. This method automatically provides color recognition, a piece of knowledge that represents the properties of an object, from its natural image. A method for recognizing and extracting the object in the image according to the color recognized is also described.

Mugitani, Takako↗

Issues in knowledge representation to support maintainability: A case study in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and runtime estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks. Because the scientific data processing modules (called fittings) evolve to match scientists' needs, issues regarding maintainability are of prime importance in PIPE. This paper describes the PIPE system and describes how issues in maintainability affected the knowledge representation used in PIPE to capture knowledge about the behavior of fittings.

Chien, Steve↗

Reaction Wheel Disturbance Model Extraction Software - RWDMES

The RWDMES is a tool for modeling the disturbances imparted on spacecraft by spinning reaction wheels. Reaction wheels are usually the largest disturbance source on a precision pointing spacecraft, and can be the dominating source of pointing error. Accurate knowledge of the disturbance environment is critical to accurate prediction of the pointing performance. In the past, it has been difficult to extract an accurate wheel disturbance model since the forcing mechanisms are difficult to model physically, and the forcing amplitudes are filtered by the dynamics of the reaction wheel. RWDMES captures the wheel-induced disturbances using a hybrid physical/empirical model that is extracted directly from measured forcing data. The empirical models capture the tonal forces that occur at harmonics of the spin rate, and the broadband forces that arise from random effects. The empirical forcing functions are filtered by a physical model of the wheel structure that includes spin-rate-dependent moments (gyroscopic terms). The resulting hybrid model creates a highly accurate prediction of wheel-induced forces. It accounts for variation in disturbance frequency, as well as the shifts in structural amplification by the whirl modes, as the spin rate changes. This software provides a point-and-click environment for producing accurate models with minimal user effort. Where conventional approaches may take weeks to produce a model of variable quality, RWDMES can create a demonstrably high accuracy model in two hours. The software consists of a graphical user interface (GUI) that enables the user to specify all analysis parameters, to evaluate analysis results and to iteratively refine the model. Underlying algorithms automatically extract disturbance harmonics, initialize and tune harmonic models, and initialize and tune broadband noise models. The component steps are described in the RWDMES user s guide and include: converting time domain data to waterfall PSDs (power spectral densities); converting PSDs to order analysis data; extracting harmonics; initializing and simultaneously tuning a harmonic model and a wheel structural model; initializing and tuning a broadband model; and verifying the harmonic/broadband/structural model against the measurement data. Functional operation is through a MATLAB GUI that loads test data, performs the various analyses, plots evaluation data for assessment and refinement of analysis parameters, and exports the data to documentation or downstream analysis code. The harmonic models are defined as specified functions of frequency, typically speed-squared. The reaction wheel structural model is realized as mass, damping, and stiffness matrices (typically from a finite element analysis package) with the addition of a gyroscopic forcing matrix. The broadband noise model is realized as a set of speed-dependent filters. The tuning of the combined model is performed using nonlinear least squares techniques. RWDMES is implemented as a MATLAB toolbox comprising the Fit Manager for performing the model extraction, Data Manager for managing input data and output models, the Gyro Manager for modifying wheel structural models, and the Harmonic Editor for evaluating and tuning harmonic models. This software was validated using data from Goodrich E wheels, and from GSFC Lunar Reconnaissance Orbiter (LRO) wheels. The validation testing proved that RWDMES has the capability to extract accurate disturbance models from flight reaction wheels with minimal user effort.

Blaurock, Carl↗

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Text-based information about past engineering failures presents one possible solution by facilitating the retrieval of information that can inform new designs. However, identifying documents containing relevant information and extracting required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing-based framework is proposed to discover relevant knowledge from documents containing failure-related design information. Documents containing usable information are filtered using sentiment analysis based on a custom lexicon specialized for engineering design and by filtering out documents containing only irrelevant topics. Next, from the identified usable documents, information relating to engineering failures, contributing factors that can be controlled at design time (“risk factors”), and recommended preventative actions are extracted. Semantic similarity is then used to group similar pieces of extracted information for improved generalizability. The proposed framework is applied to NASA’s Lessons Learned Information System (LLIS). The framework can be used to identify documents containing usable failure-related design information from other databases, extract relevant information from these documents, and generalize the acquired knowledge such that it can be applied to novel systems.

Sequoia R. Andrade↗

Orbital transfer vehicle launch operations study: Automated technology knowledge base, volume 4

A simplified retrieval strategy for compiling automation-related bibliographies from NASA/RECON is presented. Two subsets of NASA Thesaurus subject terms were extracted: a primary list, which is used to obtain an initial set of citations; and a secondary list, which is used to limit or further specify a large initial set of citations. These subject term lists are presented in Appendix A as the Automated Technology Knowledge Base (ATKB) Thesaurus.

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