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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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At least 1,603 records · Page 89

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NASA NTRS1995

DRS: Derivational Reasoning System

The high reliability requirements for airborne systems requires fault-tolerant architectures to address failures in the presence of physical faults, and the elimination of design flaws during the specification and validation phase of the design cycle. Although much progress has been made in developing methods to address physical faults, design flaws remain a serious problem. Formal methods provides a mathematical basis for removing design flaws from digital systems. DRS (Derivational Reasoning System) is a formal design tool based on advanced research in mathematical modeling and formal synthesis. The system implements a basic design algebra for synthesizing digital circuit descriptions from high level functional specifications. DRS incorporates an executable specification language, a set of correctness preserving transformations, verification interface, and a logic synthesis interface, making it a powerful tool for realizing hardware from abstract specifications. DRS integrates recent advances in transformational reasoning, automated theorem proving and high-level CAD synthesis systems in order to provide enhanced reliability in designs with reduced time and cost.

Bose, Bhaskar↗

NASA NTRS1998

A Formal Model of Partitioning for Integrated Modular Avionics

The aviation industry is gradually moving toward the use of integrated modular avionics (IMA) for civilian transport aircraft. An important concern for IMA is ensuring that applications are safely partitioned so they cannot interfere with one another. We have investigated the problem of ensuring safe partitioning and logical non-interference among separate applications running on a shared Avionics Computer Resource (ACR). This research was performed in the context of ongoing standardization efforts, in particular, the work of RTCA committee SC-182, and the recently completed ARINC 653 application executive (APEX) interface standard. We have developed a formal model of partitioning suitable for evaluating the design of an ACR. The model draws from the mathematical modeling techniques developed by the computer security community. This report presents a formulation of partitioning requirements expressed first using conventional mathematical notation, then formalized using the language of SRI'S Prototype Verification System (PVS). The approach is demonstrated on three candidate designs, each an abstraction of features found in real systems.

DiVito, Ben L.↗

NASA NTRS2005

A Streaming Language Implementation of the Discontinuous Galerkin Method

We present a Brook streaming language implementation of the 3-D discontinuous Galerkin method for compressible fluid flow on tetrahedral meshes. Efficient implementation of the discontinuous Galerkin method using the streaming model of computation introduces several algorithmic design challenges. Using a cycle-accurate simulator, performance characteristics have been obtained for the Stanford Merrimac stream processor. The current Merrimac design achieves 128 Gflops per chip and the desktop board is populated with 16 chips yielding a peak performance of 2 Teraflops. Total parts cost for the desktop board is less than $20K. Current cycle-accurate simulations for discretizations of the 3-D compressible flow equations yield approximately 40-50% of the peak performance of the Merrimac streaming processor chip. Ongoing work includes the assessment of the performance of the same algorithm on the 2 Teraflop desktop board with a target goal of achieving 1 Teraflop performance.

Barth, Timothy↗

NASA NTRS2005

Space Physics Data Facility Web Services

The Space Physics Data Facility (SPDF) Web services provides a distributed programming interface to a portion of the SPDF software. (A general description of Web services is available at http://www.w3.org/ and in many current software-engineering texts and articles focused on distributed programming.) The SPDF Web services distributed programming interface enables additional collaboration and integration of the SPDF software system with other software systems, in furtherance of the SPDF mission to lead collaborative efforts in the collection and utilization of space physics data and mathematical models. This programming interface conforms to all applicable Web services specifications of the World Wide Web Consortium. The interface is specified by a Web Services Description Language (WSDL) file. The SPDF Web services software consists of the following components: 1) A server program for implementation of the Web services; and 2) A software developer s kit that consists of a WSDL file, a less formal description of the interface, a Java class library (which further eases development of Java-based client software), and Java source code for an example client program that illustrates the use of the interface.

Candey, Robert M.↗

DOE OSTI2024

Towards Unlocking Insights from Logbooks Using AI

Electronic logbooks contain valuable information about activities and events concerning their associated particle accelerator facilities. However, the highly technical nature of logbook entries can hinder their usability and automation. As natural language processing (NLP) continues advancing, it offers opportunities to address various challenges that logbooks present. This work explores jointly testing a tailored Retrieval Augmented Generation (RAG) model for enhancing the usability of particle accelerator logbooks at institutes like DESY, BESSY, Fermilab, BNL, SLAC, LBNL, and CERN. The RAG model uses a corpus built on logbook contributions and aims to unlock insights from these logbooks by leveraging retrieval over facility datasets, including discussion about potential multimodal sources. Our goals are to increase the FAIR-ness (findability, accessibility, interoperability, and reusability) of logbooks by exploiting their information content to streamline everyday use, enable macro-analysis for root cause analysis, and facilitate problem-solving automation.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Interactive Corpus Analysis Tool

The Interactive Corpus Analysis Tool (ICAT) is an interactive machine learning dashboard for unlabeled text/natural language processing datasets that allows a user to iteratively and visually define features, explore and label instances of their dataset, and simultaneously train a logistic regression model. ICAT was created to allow subject matter experts in a specific domain to directly train their own models for unlabeled datasets visually, without needing to be a machine learning expert or needing to know how to code the models themselves. This approach allows users to directly leverage the power of machine learning, but critically, also involves the user in the development of the machine learning model.

Martindale, Nathan [Oak Ridge National Lab. (ORNL)↗

NASA NTRS2021

3D Simulations of the Early Martian Hydrological Cycle Mediated by a H2-CO2 Greenhouse

For decades, the scientific community has been trying to reconcile abundant evidence for fluvialactivity on Noachian and early Hesperian Mars with the faint young Sun and reasonableconstraints on ancient atmospheric pressure and composition. Recently, the investigation of H2-CO2 collision-induced absorption has opened up a new avenue to warm Noachian Mars. We usethe ROCKE-3D global climate model to simulate plausible states of the ancient Martian climatewith this absorptive warming and reasonable constraints on surface paleopressure. We find that1.5-2 bar CO2-dominated atmospheres with ≥3% H2 can produce global mean surfacetemperatures above freezing, while also providing sufficient warming to avoid surfaceatmospheric CO2 condensation at 0°-45° obliquity. Simulations conducted with both moderntopography and a paleotopography, before Tharsis formed, highlight the importance of Tharsis asa cold trap for water on the planet. Additionally, we find that low obliquity (modern and 0°) ismore conducive to rainfall over valley network locations than high (45°) obliquity. PLAIN LANGUAGE SUMMARY Much evidence tells us that ancient Mars had liquid water on its surface. But reconciling thatwith the fainter young Sun and reasonable constraints on Mars' early atmosphere is challenging.We use a 3D global climate model with an atmosphere containing some amount of hydrogen (apossible greenhouse gas) to study Mars' early hydrological cycle and compare it to the geologicalevidence of surface liquid water billions of years ago. We find that hydrogen and carbon dioxidetogether in an atmosphere twice as thick as modern Earth can warm early Mars above thefreezing point of water and that a low axial tilt produces rainfall patterns that best match thegeologic evidence

Scott D Guzewich↗

NASA NTRS1992

C++, objected-oriented programming, and astronomical data models

Contemporary astronomy is characterized by increasingly complex instruments and observational techniques, higher data collection rates, and large data archives, placing severe stress on software analysis systems. The object-oriented paradigm represents a significant new approach to software design and implementation that holds great promise for dealing with this increased complexity. The basic concepts of this approach will be characterized in contrast to more traditional procedure-oriented approaches. The fundamental features of objected-oriented programming will be discussed from a C++ programming language perspective, using examples familiar to astronomers. This discussion will focus on objects, classes and their relevance to the data type system; the principle of information hiding; and the use of inheritance to implement generalization/specialization relationships. Drawing on the object-oriented approach, features of a new database model to support astronomical data analysis will be presented.

Farris, A.↗

DOE OSTI2025

Arctic shrub expansion generates regional variation in litter decomposition by altering litter quality and the decomposition environment

Abstract The expansion of deciduous shrubs into the graminoid‐dominated arctic tundra is expected to alter litter decomposition by changing litter quality and local abiotic and biotic conditions. However, it remains unclear how shrub expansion will affect litter decomposition at regional scales, where macroclimate is expected to be the dominant regulator of decomposition. To determine the relative influence of macroclimate and local controls on regional patterns of litter mass loss and nitrogen release, we conducted two hierarchical litter decomposition experiments across spatial scales. We decomposed leaf and root litter from a prominent graminoid ( Eriophorum vaginatum ) and three genera of deciduous shrubs ( Betula , Alnus and Salix ) for 1 year within replicated plots at five sites spanning a 160 km latitudinal gradient in northern Alaska. Using Eriophorum litter as a substrate, we found that macroclimate was the primary regulator of mass loss but had opposing effects on leaf and root litter. As summer temperature increased along the latitudinal gradient (11.9 to 13.9°C), leaf litter mass loss increased by 20% whereas root litter mass loss decreased by 33%. Leaf nitrogen release also increased with summer temperature. Conversely, root nitrogen release was controlled by the vegetation type of the decomposition environment. Using different shrub litters as substrates, we found that litter quality and its interaction with soil microclimate and macroclimate controlled decomposition. Overall, shrub root litters decomposed faster than Eriophorum root litter, losing 53% more mass and 190% more nitrogen across all sites and decomposition environments. For leaf litter, however, patterns varied by litter genus, with Salix losing more mass and Betula and Alnus losing less mass than Eriophorum . Our findings demonstrate that shrub expansion in the Arctic can regulate leaf and root litter decomposition at the regional scale through its effects on local controls, primarily litter quality. Ongoing increases in shrub cover are likely to accelerate the turnover of root litter carbon and nitrogen pools in tundra ecosystems. Therefore, including shrub‐related processes in Earth system models will improve our ability to predict regional‐scale litter decomposition and its effects on carbon and nutrient cycling in a warming Arctic. Read the free Plain Language Summary for this article on the Journal blog.

Vozzo, Justin T. [Department of Natural Resources ↗

NASA NTRS1978

Simulation of mission timelines for the Spacelab program

The paper describes the structure of the Special Purpose Simulation Language (SPSL) designed to overcome certain problems encountered in the use of the General Purpose Simulation Language (GPSL) when applied to simulation and validation of Spacelab mission timelines. The current analysis system is GROPE (Ground Resource Operations Planning Executive), the main data base models of which are the ground operations model, the mission model, the resource model, and the traffic model. Some of the simulation problem areas are mentioned, and unique features of the SPSL are highlighted.

Roberts, J. S.↗

NASA NTRS1986

Ulysses: A functional description and simulation software system

Current design tools for digital circuits and systems are not well-integrated among the behavioral, gate, and transistor levels of design. Ulysses is a prototype software system that consists of a description language, a description compiler, and a simulator that make no distinction among these levels. The language is uniform over the entire range of logical descriptions, the description is hierarchical with no fundamental restrictions on depth or mixing of levels, and the simulator is fully integrated with the description. The structure of the language, compiler, and simulator are described in terms of their relationships to the abstractions of physical systems that are made in order to create logical descriptions and models of behavior.

Griswold, T. W.↗

NASA NTRS1993

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology, Volume 1

These proceedings are organized in the same manner as the conference's contributed sessions, with the papers grouped by topic area. These areas are as follows: VE (virtual environment) training for Space Flight, Virtual Environment Hardware, Knowledge Aquisition for ICAT (Intelligent Computer-Aided Training) & VE, Multimedia in ICAT Systems, VE in Training & Education (1 & 2), Virtual Environment Software (1 & 2), Models in ICAT systems, ICAT Commercial Applications, ICAT Architectures & Authoring Systems, ICAT Education & Medical Applications, Assessing VE for Training, VE & Human Systems (1 & 2), ICAT Theory & Natural Language, ICAT Applications in the Military, VE Applications in Engineering, Knowledge Acquisition for ICAT, and ICAT Applications in Aerospace.

Hyde, Patricia R.↗

NASA NTRS2012

A Study of Planetary Nebulae using the Faint Object Infrared Camera for the SOFIA Telescope

A planetary nebula is formed following an intermediate-mass (1-8 solar M) star's evolution off of the main sequence; it undergoes a phase of mass loss whereby the stellar envelope is ejected and the core is converted into a white dwarf. Planetary nebulae often display complex morphologies such as waists or torii, rings, collimated jet-like outflows, and bipolar symmetry, but exactly how these features form is unclear. To study how the distribution of dust in the interstellar medium affects their morphology, we utilize the Faint Object InfraRed CAmera for the SOFIA Telescope (FORCAST) to obtain well-resolved images of four planetary nebulae--NGC 7027, NGC 6543, M2-9, and the Frosty Leo Nebula--at wavelengths where they radiate most of their energy. We retrieve mid infrared images at wavelengths ranging from 6.3 to 37.1 micron for each of our targets. IDL (Interactive Data Language) is used to perform basic analysis. We select M2-9 to investigate further; analyzing cross sections of the southern lobe reveals a slight limb brightening effect. Modeling the dust distribution within the lobes reveals that the thickness of the lobe walls is higher than anticipated, or rather than surrounding a vacuum surrounds a low density region of tenuous dust. Further analysis of this and other planetary nebulae is needed before drawing more specific conclusions.

infrared sensors↗

DOE OSTI2022

SplitML

SplitML (Signal Processing Library for Interference rejecTion by Machine Learning) is a code repository for a set of tools for interference rejection in complex time-domain signals. The goal of the tools is to provide machine learning modeling capabilities for rejecting interference. Recent related machine learning algorithms for signal processing have focused mostly on speech enhancement or multi-speaker speech separation; the tools in SplitML will extend these innovations to generic time-domain signals of interest. SplitML includes tools for generating synthetic noisy signals, code for customized machine learning models applicable to interference rejection, and tools for evaluating such algorithms against standard signal processing techniques. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.

Klein, Natalie↗

NASA NTRS1993

Expanding the KATE toolbox

KATE (Knowledge-based Autonomous Test Engineer) is a model-based software system developed in the Artificial Intelligence Laboratory at the Kennedy Space Center for monitoring, fault detection, and control of launch vehicles and ground support systems. In order to bring KATE to the level of performance, functionality, and integratability needed for firing room applications, efforts are underway to implement KATE in the C++ programming language using an X-windows interface. Two programs which were designed and added to the collection of tools which comprise the KATE toolbox are described. The first tool, called the schematic viewer, gives the KATE user the capability to view digitized schematic drawings in the KATE environment. The second tool, called the model editor, gives the KATE model builder a tool for creating and editing knowledge base files. Design and implementation issues having to do with these two tools are discussed. It will be useful to anyone maintaining or extending either the schematic viewer or the model editor.

Thomas, Stan J.↗

DOE OSTI2021

Feature Extraction: Improving Remote Sensor Classification of Non-Proliferation

This research focuses on developing algorithms for nuclear non-proliferation detection using remote sensor modeling. To improve the performance of classification models, we implemented a data pipeline with feature extraction. This pipeline takes raw data and transforms it into smaller data points called features that still describe the model. Improving this classification works towards the departments of energy’s missions of ensuring American’s security and prosperity by creating technology that addresses nuclear challenges. To conduct this analysis, we used the Python programming language and some key packages, including tsfresh and TSFEL. Originally tsfresh was selected because it has the most statistical features out of all the packages. Later TSFEL was incorporated due to the additional features it can extract from data, such as temporal and spectral. However, feature extraction becomes challenging in the presence of missing values. In this case, two additional Python packages were added to our workflow, NumPy and pandas, allowing for the feature extraction process to handle unknown values. Our data pipeline was tested on data collected from a simulation that describes the process state of a physical example. The results show the pipeline’s capability to consume and extract a total 17 features from tabular data. Future work includes producing classifications using decision tree-based models such as XGBoost and improving data collection by analyzing feature importance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

From Machine Learning to Machine Reasoning: A Model-based Approach to Analyze Equipment Reliability Data

In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.

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.↗