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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 NTRS1992

A new programming metaphor for image processing procedures

Most image processing systems, besides an Application Program Interface (API) which lets users write their own image processing programs, also feature a higher level of programmability. Traditionally, this is a command or macro language, which can be used to build large procedures (scripts) out of simple programs or commands. This approach, a legacy of the teletypewriter has serious drawbacks. A command language is clumsy when (and if! it attempts to utilize the capabilities of a multitasking or multiprocessor environment, it is but adequate for real-time data acquisition and processing, it has a fairly steep learning curve, and the user interface is very inefficient,. especially when compared to a graphical user interface (GUI) that systems running under Xll or Windows should otherwise be able to provide. ll these difficulties stem from one basic problem: a command language is not a natural metaphor for an image processing procedure. A more natural metaphor - an image processing factory is described in detail. A factory is a set of programs (applications) that execute separate operations on images, connected by pipes that carry data (images and parameters) between them. The programs function concurrently, processing images as they arrive along pipes, and querying the user for whatever other input they need. From the user's point of view, programming (constructing) factories is a lot like playing with LEGO blocks - much more intuitive than writing scripts. Focus is on some of the difficulties of implementing factory support, most notably the design of an appropriate API. It also shows that factories retain all the functionality of a command language (including loops and conditional branches), while suffering from none of the drawbacks outlined above. Other benefits of factory programming include self-tuning factories and the process of encapsulation, which lets a factory take the shape of a standard application both from the system and the user's point of view, and thus be used as a component of other factories. A bare-bones prototype of factory programming was implemented under the PcIPS image processing system, and a complete version (on a multitasking platform) is under development.

Smirnov, O. M.↗
NASA NTRS2014

Complete Decoding and Reporting of Aviation Routine Weather Reports (METARs)

Aviation Routine Weather Report (METAR) provides surface weather information at and around observation stations, including airport terminals. These weather observations are used by pilots for flight planning and by air traffic service providers for managing departure and arrival flights. The METARs are also an important source of weather data for Air Traffic Management (ATM) analysts and researchers at NASA and elsewhere. These researchers use METAR to correlate severe weather events with local or national air traffic actions that restrict air traffic, as one example. A METAR is made up of multiple groups of coded text, each with a specific standard coding format. These groups of coded text are located in two sections of a report: Body and Remarks. The coded text groups in a U.S. METAR are intended to follow the coding standards set by National Oceanic and Atmospheric Administration (NOAA). However, manual data entry and edits made by a human report observer may result in coded text elements that do not follow the standards, especially in the Remarks section. And contrary to the standards, some significant weather observations are noted only in the Remarks section and not in the Body section of the reports. While human readers can infer the intended meaning of non-standard coding of weather conditions, doing so with a computer program is far more challenging. However such programmatic pre-processing is necessary to enable efficient and faster database query when researchers need to perform any significant historical weather analysis. Therefore, to support such analysis, a computer algorithm was developed to identify groups of coded text anywhere in a report and to perform subsequent decoding in software. The algorithm considers common deviations from the standards and data entry mistakes made by observers. The implemented software code was tested to decode 12 million reports and the decoding process was able to completely interpret 99.93 of the reports. This document presents the deviations from the standards and the decoding algorithm. Storing all decoded data in a database allows users to quickly query a large amount of data and to perform data mining on the data. Users can specify complex query criteria not only on date or airport but also on weather condition. This document also describes the design of a database schema for storing the decoded data, and a Data Warehouse web application that allows users to perform reporting and analysis on the decoded data. Finally, this document presents a case study correlating dust storms reported in METARs from the Phoenix International airport with Ground Stops issued by Air Route Traffic Control Centers (ATCSCC). Blowing widespread dust is one of the weather conditions when dust storm occurs. By querying the database, 294 METARs were found to report blowing widespread dust at the Phoenix airport and 41 of them reported such condition only in the Remarks section of the reports. When METAR is a data source for an ATM research, it is important to include weather conditions not only from the Body section but also from the Remarks section of METARs.

METAR Decoder/Parser↗
DOE OSTI2024

Optimization on Manifolds via Graph Gaussian Processes

This paper integrates manifold learning techniques within a Gaussian process upper confidence bound algorithm to optimize an objective function on a manifold. Our approach is motivated by applications where a full representation of the manifold is not available and querying the objective is expensive. We rely on a point cloud of manifold samples to define a graph Gaussian process surrogate model for the objective. Query points are sequentially chosen using the posterior distribution of the surrogate model given all previous queries. We establish regret bounds in terms of the number of queries and the size of the point cloud. Several numerical examples complement the theory and illustrate the performance of our method.

Bayesian optimization↗
DOE OSTI2025

Hierarchical Gaussian process-based Bayesian optimization for materials discovery in high entropy alloy spaces

Bayesian optimization (BO) is a powerful and data-efficient method for iterative materials discovery and design, particularly valuable when prior knowledge is limited, underlying functional relationships are complex or unknown, and the cost of querying the materials space is significant. Traditional BO methodologies typically utilize conventional Gaussian Processes (cGPs) to model the relationships between material inputs and properties, as well as correlations within the input space. However, cGP-BO approaches often fall short in multi-objective optimization scenarios, where they are unable to fully exploit correlations between distinct material properties. Leveraging these correlations can significantly enhance the discovery process, as information about one property can inform and improve predictions about others. Here, this study addresses this limitation by employing advanced kernel structures to capture and model multi-dimensional property correlations through multi-task (MTGPs) or deep Gaussian Processes (DGPs), thus accelerating the discovery process. We demonstrate the effectiveness of MTGP-BO and DGP-BO in rapidly and robustly solving complex materials design challenges that occur within the context of complex multi-objective optimization over FCC FeCrNiCoCu high entropy alloy (HEA) spaces, where traditional cGP-BO approaches fail. Furthermore, we highlight how the differential costs associated with querying various material properties can be strategically leveraged to make the materials discovery process more cost-efficient.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Modeling Active Region Evolution - A New LWS TR and T Strategic Capability Model Suite

In 2006 the LWS TR&T Program funded us to develop a strategic capability model of slowly evolving coronal active regions. In this poster we report on the overall design, and status of our new modeling suite. Our design features two coronal field models, a non-linear force free field model and a global 3D MHD code. The suite includes supporting tools and a user friendly GUI which will enable users to query the web for relevant magnetograms, download them, process them to synthesize a sequence of photospheric magnetograms and associated photospheric flow field which can then be applied to drive the coronal model innner boundary, run the coronal models and finally visualize the results.

MacNeice, Peter↗
DOE OSTI2020

Threat Reduction Research Networks: Fostering Sustainable Collaborations Through Trainings for Genomics for Biosurveillance

Scientific research communities can be represented as heterogeneous or multidimensional networks encompassing multiple types of entities and relationships. These networks might include researchers, institutions, meetings, and publications, connected by relationships like authorship, employment, and attendance. We describe a method for efficiently and flexibly capturing, storing, and extracting information from multidimensional scientific networks using a graph database. The database structure is based on an ontology that captures allowable types of entities and relationships. This allows us to construct a variety of projections of the underlying multidimensional graph through database queries to answer specific research questions. We demonstrate this process through a study of the U.S. Biological Threat Reduction Program (BTRP), which seeks to develop Threat Reduction Networks to build and strengthen a sustainable international community of biosecurity, biosafety, and biosurveillance experts to address shared biological threat reduction challenges. Networks like these create connectional intelligence among researchers and institutions around the world, and are central to the concept of cooperative threat reduction. Our analysis focuses on a series of seven BTRP genome sequencing training workshops, showing how they created a growing network of participants and countries over time, which is also reflected in coauthorship relationships among attendees. By capturing concept and relationship hierarchies, our ontology-based approach allows us to pose general or specific questions about networks within the same framework. This approach can be applied to other research communities or multidimensional social networks to capture, analyze, and visualize different types of interactions and how they change over time.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

Do-It-Yourself: A Special Library's Approach to Creating Dynamic Web Pages Using Commercial Off-The-Shelf Applications

Many librarians may feel that dynamic Web pages are out of their reach, financially and technically. Yet we are reminded in library and Web design literature that static home pages are a thing of the past. This paper describes how librarians at the Institute for Defense Analyses (IDA) library developed a database-driven, dynamic intranet site using commercial off-the-shelf applications. Administrative issues include surveying a library users group for interest and needs evaluation; outlining metadata elements; and, committing resources from managing time to populate the database and training in Microsoft FrontPage and Web-to-database design. Technical issues covered include Microsoft Access database fundamentals, lessons learned in the Web-to-database process (including setting up Database Source Names (DSNs), redesigning queries to accommodate the Web interface, and understanding Access 97 query language vs. Standard Query Language (SQL)). This paper also offers tips on editing Active Server Pages (ASP) scripting to create desired results. A how-to annotated resource list closes out the paper.

Relational databases↗
DOE OSTI2026

Component-Level Inverse Design of Transmon Qubits Using Neural Networks

Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer chooses a layout geometry, simulates it, extracts circuit parameters such as capacitances, and refines the geometry. We study the inverse version of this task using a neural-network workflow that maps target Hamiltonian parameters directly to component-level layout parameters, which we subsequently demonstrate on a planar transmon layout. During training, we pair the inverse model with a frozen forward surrogate model and evaluate the loss in Hamiltonian space rather than in layout-parameter space. In validation against a conventional EM solver, 97% of generated designs produce usable geometries, and the inverse-plus-surrogate pipeline reaches mean percent errors of 0.73% for qubit frequency and 1.58% for anharmonicity, comparable to or below the fabrication and simulation-to-measurement uncertainty expected for academic-process transmon devices of this type. A single pipeline query takes ~60 ms on CPU, versus ~2 min for a conventional EM capacitance extraction on the same hardware, a speedup of approximately 2,000x. Batching minimizes the AI model inference overhead, reducing the runtime to 3.1 microseconds per sample on CPU and 2.6 microseconds per sample on GPU at a batch size of 2048, resulting in speedups of 3.9 x 10^7 and 4.6 x 10^7, respectively, relative to a single conventional CPU EM extraction. Our results indicate that component-level inverse design usefully extends and complements conventional EM simulation, including for small datasets on the order of 1,000 samples.

Seidel, Olivia [Fermilab; Texas U., Arlington]↗
DOE OSTI2020

Performance and usability enhancements for continuous subgraph matching queries on graph-structured data

A query graph, which includes vertices and edges, represents a query on graph-structured data. The query graph is decomposed into query subgraphs. A network analysis tool performs continuous subgraph matching queries to facilitate analysis of computer network traffic, social media events, or other streams of data represented as a dynamic data graph (graph-structured data). This can help identify emerging trends in the data. Some features of the network analysis tool enhance performance by effectively utilizing distributed computing resources (including processing cores and memory at different nodes of a cluster) to speed up the process of updating the dynamic data graph and detecting matches of query subgraphs. Features of a query graph building tool enhance usability by providing intuitive ways to specify query graphs and their subgraphs. Features of a results visualization tool enhance usability by providing an intuitive way to present the results of continuous subgraph matching queries.

Choudhury, Sutanay↗
NASA NTRS1994

The NIST Internet time service

We will describe the NIST Network Time Service which provides time and frequency information over the Internet. Our first time server is located in Boulder, Colorado, a second backup server is under construction there, and we plan to install a third server on the East Coast later this year. The servers are synchronized to UTC(NIST) with an uncertainty of about 0.8 ms RMS and they will respond to time requests from any client on the Internet in several different formats including the DAYTIME, TIME and NTP protocols. The DAYTIME and TIME protocols are the easiest to use and are suitable for providing time to PC's and other small computers. In addition to UTC(NIST), the DAYTIME message provides advance notice of leap seconds and of the transitions to and from Daylight Saving Time. The Daylight Saving Time notice is based on the US transition dates of the first Sunday in April and the last one in October. The NTP is a more complex protocol that is suitable for larger machines; it is normally run as a 'daemon' process in the background and can keep the time of the client to within a few milliseconds of UTC(NIST). We will describe the operating principles of various kinds of client software ranging from a simple program that queries the server once and sets the local clock to more complex 'daemon' processes (such as NTP) that continuously correct the time of the local clock based on periodic calibrations.

Levine, Judah↗
DOE OSTI2021

Matrix-Based Process Modeling in Microsoft Excel

The purpose of this document is to describe the theory and methodology of matrix-based process modeling and demonstrate its use through a generic process model within Microsoft Excel. This type of model allows a modeler to quickly query various metrics, such as total production time, for a specified production run. These matrix models tend to be quick to build and use, but come with certain limitations and are more suited for smaller processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Online Interactive Platform for COVID-19 Literature Visual Analytics: Platform Development Study

Background Papers on COVID-19 are being published at a high rate and concern many different topics. Innovative tools are needed to aid researchers to find patterns in this vast amount of literature to identify subsets of interest in an automated fashion. Objective We present a new online software resource with a friendly user interface that allows users to query and interact with visual representations of relationships between publications. Methods We publicly released an application called PLATIPUS (Publication Literature Analysis and Text Interaction Platform for User Studies) that allows researchers to interact with literature supplied by COVIDScholar via a visual analytics platform. This tool contains standard filtering capabilities based on authors, journals, high-level categories, and various research-specific details via natural language processing and dozens of customizable visualizations that dynamically update from a researcher’s query. Results PLATIPUS is available online and currently links to over 100,000 publications and is still growing. This application has the potential to transform how COVID-19 researchers use public literature to enable their research. Conclusions The PLATIPUS application provides the end user with a variety of ways to search, filter, and visualize over 100,00 COVID-19 publications.</:p>

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

SMART-COM – Scalable Multi-Agent Adaptive Resolution Tools for Collaborative Outage Management

The purpose of this grant was to conduct scientific research and prototype applications to support NPP outage staff in their adaptive decision-making in efficient scheduling and resource allocation while preventing violation of safety technical specifications. The project contributed to scientific knowledge and engineering methods in (1) user interface design, (2) scheduling optimization and risk estimation, and (2) natural language processing that would benefit the nuclear power plants in minimizing schedule overruns and even unexpected shutdowns. The research team conducted site visits at a test reactor facility and an operating nuclear power plant to gather necessary information and inputs for research and development of a software application to support NPP staff in executing their outages. The final software application consisted of three modules. First, the natural language processing module supports interactive processing of technical documentation to build a database for outage staff to query non-permissible actions on system components. This module can alleviate outage staff from reviewing extensive documentation and minimize violation of technical specifications, especially in time-sensitive situations. Second, the schedule optimization module schedules outage activities and compute risk indices that outperform existing software and current practice. This module can reduce completion time of an outage that typically have too many activities for human to optimize based on current practice that does not apply the latest operations research. Finally, the visualization module presents progress and risk information of the overall outage and individual activities, as well as enabling access to the natural language processing and schedule optimization modules. This module can provide outage staff with situation awareness that are necessary to make risk-informed decisions in response to unexpected events during the execution of an outage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2019

Citizen Science Twitter Data Management for Earth Science Applications

Social media data can provide useful real-time and historical information relating to the natural world, but managing this data poses challenges. Scientists at GES DISC are exploring the potential of Twitter data to augment precipitation data from the Global Precipitation Measurement (GPM) mission. However, the format of Twitter data is unconventional in the context of NASA data centers, resulting in frustration for scientists who need to work with the data. This study investigated procedures and standards needed to properly manage Twitter data to make them compatible with these data centers. After comparing databases, the study found that the MongoDB database was best suited for the storage of raw Twitter data due to its flexibility, ability to be accessed by multiple users, and querying functionality. The study used the Python package Zarr to transform processed Twitter data into a gridded format similar to that of satellite data. Each Tweet was mapped onto a time-space grid; each grid location contained information about Tweet attributes and precipitation. The study developed a pipeline for downloading, storing, and gridding Twitter data and transformed Twitter data into an understandable format for users of NASA satellite data.

Li, Rachel↗
DOE OSTI2022

Sharing tuples across independent coordination namespace systems

A system and method for federating a tuple storage database across multiple coordinated namespace (CNS) extended memory storage systems allowing the sharing of tuples and tuple data across independent systems. The method provides a federation service for multiple coordination namespace systems. The method retrieves a tuple from connected independent CNS systems wherein a local CNS Controller sends a read request to the local gatekeeper to retrieve a first tuple and creates a local pending remote record. The local gatekeeper at a requesting node sends a broadcast query to a plurality of remote gatekeepers for the tuple and Remote gatekeepers at remote nodes query in its local CNS for the tuple. The Local gatekeeper process at the requesting node receives results from a plurality of remote gatekeepers for the said tuple and selects one remote gatekeeper to receive the requested tuple and broadcasts a read for tuple data with selected gatekeeper.

Jacob, Philip↗
NASA NTRS2001

A Stream lined Approach for the Payload Customer in Identifying Payload Design Requirements

NASA payload developers from across various disciplines were asked to identify areas where process changes would simplify their task of developing and flying flight hardware. Responses to this query included a central location for consistent hardware design requirements for middeck payloads. The multidisciplinary team assigned to review the numerous payload interface design documents is assessing the Space Shuttle middeck, the SPACEHAB Inc. locker, as well as the MultiPurpose Logistics Module (MPLM) and EXpedite the PRocessing of Experiments to Space Station (EXPRESS) rack design requirements for the payloads. They are comparing the multiple carriers and platform requirements and developing a matrix which illustrates the individual requirements, and where possible, the envelope that encompasses all of the possibilities. The matrix will be expanded to form an overall envelope that the payload developers will have the option to utilize when designing their payload's hardware. This will optimize the flexibility for payload hardware and ancillary items to be manifested on multiple carriers and platforms with minimal impact to the payload developer.

Miller, Ladonna J.↗
NASA NTRS1990

CLIPS enhanced with objects, backward chaining and explanation facilities

In this project we extend C Language Production System (CLIPS), an existing Expert System shell, by creating three new options. Specifically, first we create a compatible with CLIPS environment that allows for defining objects and object hierarchies, second we provide means to implement backward chaining in a pure forward chaining environment, and finally we give some simple explanation facilities for the derivations the system has made. Objects and object hierarchies are extended so that facts can be automatically inferred, and placed in the fact base. Backward chaining is implemented by creating run time data structures which hold the derivation process allowing for a depth first search. The backward chaining mechanism works not only with ground facts, but also creates bindings for every query that involves variables, and returns the truth value of such a query as well as the relevant variable bindings. Finally, the WHY and HOW explanation facilities allow for a complete examination of the derivation process, the rules triggered, and the bindings created. The entire system is integrated with the original CLIPS code, and all of its routines can be invoked as CLIPS commands.

Aldrobi, M.↗