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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Automation for System Safety Analysis

This presentation describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis and simulation to identify and evaluate possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations and scenarios; and 4) identify resulting candidate scenarios for software integration testing. There has been significant technical progress in model extraction from Orion program text sources, architecture model derivation (components and connections) and documentation of extraction sources. Models have been derived from Internal Interface Requirements Documents (IIRDs) and FMEA documents. Linguistic text processing is used to extract model parts and relationships, and the Aerospace Ontology also aids automated model development from the extracted information. Visualizations of these models assist analysts in requirements overview and in checking consistency and completeness.

Malin, Jane T.↗
NASA NTRS2018

Using a Knowledge Graph to Discover Earth Science Information

Knowledge graphs link key entities within a specific domain to other entities via relationships. Researchers are able to mine these relationships from numerous sources to infer new knowledge. Text extraction from peer-reviewed papers and scientific reports are untapped resources that can be leveraged by knowledge graphs to accelerate scientific discovery.

Freitag, Brian↗
NASA NTRSDate not supplied

Lunar Mega Project: Processes, Work Flow and Terminology of the Terrestrial Construction Industry versus the Space Industry

Recent developments around the world show an increased interest and international activity toward developing a lunar surface human and robotic presence with a long term, sustainable vision. In Europe, the construction of a "Moon Village" has been proposed, and China has stated its intention to build a research station with a crew at the lunar South Pole. Russia stated it will land cosmonauts on the Moon in the 2030's. India has sent an orbiter, a robotic lander, and rover to the Moon. The USA intends to land the first woman and a man on the Moon by 2024 to initiate a sustained human lunar presence.A lunar research station with associated commercial activities will require infrastructure to become a permanent capability. Landing and launch pads, propellant storage and distribution farms, spacecraft access and handling structures, cranes, blast protection berms or walls, roads, graded areas, dust stabilized areas, foundations, parking lots, radiation shelters, micro-meteorite protection hangars, habitats and other human shelters, greenhouse farms, utility trenches, power plants, industrial water and oxygen extraction plants, communications antenna towers, thermal protection, mining zones, crater access and sub-surface access will be required to create a safe and sustainable lunar operations capability. This infrastructure will require significant construction activities in an extreme environment, with risky and expensive operations. On Earth, there are similar large and expensive projects (>$1 Billion) in difficult locations that attract a lot of public attention. These are known as "Mega Projects" and examples include bridges, tunnels, highways, railways, airports, seaports, power plants, dams, wastewater projects, Special Economic Zones (SEZ), oil and natural gas extraction projects, public buildings, information technology systems, aerospace projects, and weapons systems. Large consortiums consisting of public and private entities typically implement these infrastructure Mega-Projects.This paper will compare the typical design process, project management process, and work flow in the terrestrial construction industry to the space industry in order to create a better understanding between the terrestrial construction industry and the space industry, to further enable collaboration on a lunar Mega Project to build infrastructure on the Moon. In addition, a glossary of respective industry terminology with annotated linkages and definitions has been compiled. This information will enable contracts and business practices to be formulated for generating requests for proposals (RFP) by governments to consortiums consisting of construction and space industry companies that will bid on Lunar Infrastructure Projects that could lead to contracts to build the permanent capabilities.

Robert P Mueller↗
DOE OSTI2025

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Marve: Measurement Context Extraction from Text

We propose Marve, a system for extracting measurement values, units, and related words from natural language text. Marve uses conditional random fields (CRF) to identify measurement values and units, followed by a rule-based system to find related entities, descriptors and modifiers within a sentence. Sentence tokens are represented by an undirected graphical model, and rules are based on part-of-speech and word dependency patterns connecting values and units to contextual words. Marve is unique in its focus on measurement context and early experimentation demonstrates Marve’s ability to generate high-precision extractions with strong recall. We also discuss Marve’s role in justifying NASA JPL’s proposed HyspIRI mission, a hyper spectral infrared imaging satellite that will study the world’s ecosystems. In general, our work with HyspIRI demonstrates the value of semantic measurement extractions in characterizing quantitative discussion contained in large corpuses of natural language text. These extractions accelerate broad-cross cu ing literature surveys and expose researchers and scientists new algorithmic approaches and experimental nuances. They also facilitate identification of scientific opportunities enabled by HyspIRI leading to more informed scientific investment and research.

Mattmann, Chris A.↗
NASA NTRSDate not supplied

Series Bosch Carbon Formation Reactor Trade Study and Down-Select

Human exploration missions to Mars and other destinations beyond low Earth orbit require highly robust, reliable, and maintainable life support systems that maximize the recovery of oxygen (O2). One process in development and under consideration is the Series-Bosch System (S-Bosch). This system is a two stage reactor process that reduces carbon dioxide (CO2) with hydrogen (H2) to produce water and solid carbon. Theoretically, the Bosch process can recover 100% of the O2 from CO2 in the form of water, making it an attractive option for long duration missions. The Series Bosch system includes a reverse water gas shift (RWGS) reactor, a carbon formation reactor (CFR), a H2 extraction membrane, and a CO2extraction membrane. To further the development of oxygen recovery systems, NASA awarded Phase I contracts to several entities under the Game Changing Development Program addressing Spacecraft Oxygen Recovery (SCOR). Two of the hardware deliverables were integrated into the Carbon Dioxide Reduction Test Stand (CORTS) as carbon formation reactors and performance evaluations were executed at Marshall Space Flight Center. A trade study was performed between these two reactors along with one developed at MSFC. This paper provided the necessary information for the Advanced Exploration Systems/Life Support Systems Project (AES/LSS) managers to select a CFR for further development and discusses the process of selection.

Bosch↗
NASA NTRSDate not supplied

Information Extraction on an Earth Science Knowledge Graphs with Semantic Parsing

Knowledge graphs are an important tool, both for representing knowledge and for retrieving information. Fundamentally, they are semantic networks that represent entities and relationships in the form of nodes and edges. A large corpus of natural language text can bebroken down into discrete entities and relationships to form a useful knowledge graph. Existing research breaks down text into a subject, object, and verb relationship triple. Although this is a useful first step, it loses much of the original contextual information encoded within the text. Our process uses a novel 7-tuple approach, in which elements of sentences are programmatically parsed into seven categories: initiator, impacted, receiver, beneficiary, result, and context. In this presentation, we show a knowledge graph built using this 7-tupleprocessing of an Earth science corpus. We explain the techniques used to create the graph and analyze its information retrieval capability while assessing the accuracy and limitations of the results.

Carson Davis↗
NASA NTRS2022

Scraping Unstructured Data to Explore the Relationship between Rainfall Anomalies and Vector-Borne Disease Outbreaks

According to the World Health Organization (WHO), vector-borne diseases such as malaria and dengue account for 17% of all infectious disease cases and lead to more than 700,000 deaths per year. Tracking and predicting the spread of vector-borne diseases is a vital task that could save hundreds of thousands of lives annually. Oftentimes, the first reports of vector-borne disease outbreaks occur through emails and online reporting systems long before they are officially documented. Tracking and predicting the emergence and spread of vector-borne disease outbreaks requires extracting data from these unstructured sources in combination with historical weather and climate data to understand the underlying background triggers and disease dynamics. In this work, we develop a data extraction pipeline for the online outbreak reporting website ProMED-mail that utilizes a web scraper, transformer neural network summarizer, and named entity recognizer to obtain a dataset of malaria, dengue, zika, and chikungunya outbreaks over the last 30 years. This scraped dataset was further analyzed in association with global rainfall anomalies derived from NASA’s Integrated Multi-satellitE Retrievals for GPM [Global Precipitation Mission] (IMERG) dataset. This preliminary analysis was to understand the effect of global rainfall patterns on the spread of vector-borne diseases. Analysis of the ProMED-mail and GPM data shows that vector-borne disease outbreaks are clustered towards the tropics and outbreaks are often amplified during the rainy seasons. Our scraped dataset can be a valuable tool in creating comprehensive georeferenced disease records for modeling and predicting future outbreaks.

Web scraping↗
DOE OSTI2017

Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast

People around the globe respond to major real world events through social media. To study targeted public sentiments across many languages and geographic locations, we introduce multilingual connotation frames: an extension from English connotation frames of Rashkin et al. (2016) with 10 additional European languages, focusing on the implied sentiments among event participants engaged in a frame. As a case study, we present large scale analysis on targeted public sentiments using 1.2 million multilingual connotation frames extracted from Twitter. We rely on connotation frames to build models to forecast country-specific connotation dynamics – perspective change over time towards salient entities and events. Our results demonstrate that connotation dynamics can be accurately predicted up to half a week in advance.

connotation frames↗
DOE OSTI2024

Double distributions and pseudodistributions

We describe the approach to lattice extraction of generalized parton distributions (GPDs) that is based on the use of the double distribution (DD) formalism within the pseudodistribution framework. The advantage of using DDs is that GPDs obtained in this way have the mandatory polynomiality property, a nontrivial correlation between x and ξ dependences of GPDs. Another advantage of using DDs is that the D -term appears as an independent entity in the DD formalism rather than a part of GPDs H and E . We relate the ξ dependence of GPDs to the width of the α profiles of the corresponding DDs and discuss strategies for fitting lattice-extracted pseudodistributions by DDs. The approach described in the present paper may be used in ongoing and future lattice extractions of GPDs. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Lithium Production in North America: A Review

This report provides a detailed literature review and preliminary life cycle inventory for producing lithium (Li) chemicals—lithium carbonate (Li 2 CO 3 ) and lithium hydroxide (LiOH)—from sedimentary clays in the North America, as was incorporated into the GREET® 2023 model release. It also updates the status and life cycle inventory of Li chemical production from low Li content brines via direct lithium extraction (DLE) from our previous work in GREET 2022. All life cycle inventory updates are based on preliminary economic assessment studies conducted by various commercial entities engaged in this industry. If produced successfully, Li chemicals from North American reserves can be significant in meeting the United States’ strategic goal of ensuring a robust and secure supply of a strategic mineral that is critical to its decarbonization initiatives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2001

Organic Protomolecule Assembly in Igneous Minerals

C-H stretching bands in the infrared spectrum of single crystals of nominally high purity, laboratory-grown MgO and of natural upper mantle olivine provide an "organic" signature that closely resembles the symmetrical and asymmetrical C-H stretching modes of aliphatic -CH2- units. The C-H stretching bands indicate that H20 and CO2, dissolved in the matrix of these minerals, converted to form H2 and chemically reduced C, which in turn formed C-H entities, probably through segregation into defects such as dislocations. Heating causes the C-H bonds to pyrolyze and the C-H stretching bands to disappear, but annealing at 70 C causes them to reappear within a few days or weeks. Modeling dislocations in MgO suggests that the segregation of C can lead to Cx chains, x less than or equal to 4, with the terminal C atoms anchored to the MgO matrix by bonding to two U. Allowing H2 to react with such Cx chains leads to [O2C(CH2)2CO2] or similar precipitates. It is suggested that such Cx-Hy-Oz entities represent protomolecules from which derive the short-chain carboxylic and dicarboxylic and of the medium-chain fatty acids that have been solvent-extracted from crushed MgO and olivine single crystals, respectively. Thus it appears that the hard, dense matrix of igneous minerals represents a medium in which protomolecular units can be assembled. During weathering of rocks the protomolecular units turn into complex organic molecules. These processes may have provided stereochemically constrained organics to the early Earth that were crucial to the emergence of Life.

Freund, Friedemann↗
DOE OSTI2020

System and methods for automated detection, reasoning and recommendations for resilient cyber systems

A method for securing an IT (information technology) system using a set of methods for knowledge extraction, event detection, risk estimation and explanation for ranking cyber-alerts which includes a method to explain the relationship (or an attack pathway) from an entity (user or host) and an event context to another entity (a high-value resource) and an event context (attack or service failure).

Choudhury, Sutanay↗
NASA NTRSDate not supplied

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗
DOE OSTI2014

Automatic identification of abstract online groups

Online abstract groups, in which members aren't explicitly connected, can be automatically identified by computer-implemented methods. The methods involve harvesting records from social media and extracting content-based and structure-based features from each record. Each record includes a social-media posting and is associated with one or more entities. Each feature is stored on a data storage device and includes a computer-readable representation of an attribute of one or more records. The methods further involve grouping records into record groups according to the features of each record. Further still the methods involve calculating an n-dimensional surface representing each record group and defining an outlier as a record having feature-based distances measured from every n-dimensional surface that exceed a threshold value. Each of the n-dimensional surfaces is described by a footprint that characterizes the respective record group as an online abstract group.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Structural organization of space polymers

Extraterrestrial polymers of glycine with iron have been characterized by mass spectrometry to have a core mass of 1494 Da with dominant rod-like variants at mass to charge ratios of 1567 and 1639 [McGeoch et al., “Meteoritic proteins with glycine, iron and lithium,” arXiv:2102.10700 (2021)]. Several principal macro-structural morphologies are observed in solvent extracts from a chondritic Vigarano class alteration type 3 meteoritic material. The first is an extended sheet of linked (three-legged) triskelia containing the 1494 Da core entity that encloses gas bubbles in the solvent. A second is of fiber-like crystals found here, via x-ray diffraction, to be multiple-walled nanotubes made from a square lattice of the 1494 Da polymer. A third is a dispersion of floating phantom-like short tubes of up to 100 μm length with characteristic angled bends that suggest the influence of a specific underlying protein structure. Here, it is proposed that the angled tubes are the observable result of a space-filling superpolymerization of 1638 Da polymer subunits guided by the tetragonal symmetry of linking silicon bonds. Distorted hexagonal sheets are linked by perpendicular subunits in a three-dimensional hexagonal diamond structure to fill the largest possible volume. This extended very low-density structure is conjectured to have dominated in a process of chemical selection because it captured a maximum amount of molecular raw material in the ultra-low density of molecular clouds or of the proto-solar nebula. This could have led ultimately to the accretion of the earliest planetary bodies.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

NASA Taxonomies for Searching Problem Reports and FMEAs

Many types of hazard and risk analyses are used during the life cycle of complex systems, including Failure Modes and Effects Analysis (FMEA), Hazard Analysis, Fault Tree and Event Tree Analysis, Probabilistic Risk Assessment, Reliability Analysis and analysis of Problem Reporting and Corrective Action (PRACA) databases. The success of these methods depends on the availability of input data and the analysts knowledge. Standard nomenclature can increase the reusability of hazard, risk and problem data. When nomenclature in the source texts is not standard, taxonomies with mapping words (sets of rough synonyms) can be combined with semantic search to identify items and tag them with metadata based on a rich standard nomenclature. Semantic search uses word meanings in the context of parsed phrases to find matches. The NASA taxonomies provide the word meanings. Spacecraft taxonomies and ontologies (generalization hierarchies with attributes and relationships, based on terms meanings) are being developed for types of subsystems, functions, entities, hazards and failures. The ontologies are broad and general, covering hardware, software and human systems. Semantic search of Space Station texts was used to validate and extend the taxonomies. The taxonomies have also been used to extract system connectivity (interaction) models and functions from requirements text. Now the Reconciler semantic search tool and the taxonomies are being applied to improve search in the Space Shuttle PRACA database, to discover recurring patterns of failure. Usual methods of string search and keyword search fall short because the entries are terse and have numerous shortcuts (irregular abbreviations, nonstandard acronyms, cryptic codes) and modifier words cannot be used in sentence context to refine the search. The limited and fixed FMEA categories associated with the entries do not make the fine distinctions needed in the search. The approach assigns PRACA report titles to problem classes in the taxonomy. Each ontology class includes mapping words - near-synonyms naming different manifestations of that problem class. The mapping words for Problems, Entities and Functions are converted to a canonical form plus any of a small set of modifier words (e.g. non-uniformity NOT + UNIFORM.) The report titles are parsed as sentences if possible, or treated as a flat sequence of word tokens if parsing fails. When canonical forms in the title match mapping words, the PRACA entry is associated with the corresponding Problem, Entity or Function in the ontology. The user can search for types of failures associated with types of equipment, clustering by type of problem (e.g., all bearings found with problems of being uneven: rough, irregular, gritty ). The results could also be used for tagging PRACA report entries with rich metadata. This approach could also be applied to searching and tagging failure modes, failure effects and mitigations in FMEAs. In the pilot work, parsing 52K+ truncated titles (the test cases that were available), has resulted in identification of both a type of equipment and type of problem in about 75% of the cases. The results are displayed in a manner analogous to Google search results. The effort has also led to the enrichment of the taxonomy, adding some new categories and many new mapping words. Further work would make enhancements that have been identified for improving the clustering and further reducing the false alarm rate. (In searching for recurring problems, good clustering is more important than reducing false alarms). Searching complete PRACA reports should lead to immediate improvement.

Malin, Jane T.↗
DOE OSTI2016

Vibration energy harvesting in a small channel fluid flow using piezoelectric transducer

This work is aimed at developing a way to harvest energy from a fluid stream with the application of piezoelectric transducers in a small channel. In this COMSOL Multiphysics based simulation study, it is attempted to harvest energy from the abundant renewable source of energy available in the form of kinetic energy of naturally occurring flow of fluids. The strategy involves harnessing energy from a fluid-actuator through generation of couples, eddies and vortices, resulting from the stagnation and separation of flow around a semi-circular bluff-body attached to a cantilever beam containing a piezoceramic layer. Fluctuation of fluidic pressure impulse on the beam due to vortex shedding and varying lift forces causes the flexible cantilever beam to oscillate in the direction normal to the fluid flow in a periodic manner. The periodic application and release of a mechanical strain upon the beam effected a generation of electric potential within the piezoelectric layer, thus enabling extraction of electrical energy from the kinetic energy of the fluid. The piezoelectric material properties and transducer design are kept unchanged throughout the study, whereas the configuration is tested with different fluids and varying flow characteristics. The size and geometry of the obstructing entity are systematically varied to closely inspect the output from different iterations and for finding the optimum design parameters. The intermittent changes in the generated forces and subsequent variation in the strain on the beam are also monitored to find definitive relationship with the electrical energy output.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗