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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing

Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing

Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Data Processing and Analysis of Performance Measurements From Ingenuity Rotors in the Jet Propulsion Laboratory 25-Ft Space Simulator

The success of Ingenuity completing over 71 flights on Mars has resulted in the possible use of two further optimized Ingenuity-sized helicopters to retrieve samples for the planned Mars Sample Return campaign. Data to validate performance for several rotor speeds, densities, configurations, and collectives will aid in the design process and help in understanding Ingenuity’s current performance limitations. Tests were performed at the Jet Propulsion Laboratory (JPL) in the 25-foot Space Simulator, which include the Engineering Design Model 1 (EDM-1) with and without a cruciform box, and the Transonic Rotor Test (TRT) which is a single rotor setup featuring the same blade geometry as EDM-1 but designed to spin at much higher RPMs. The experimental setup, test matrix, data processing, data quality, and the performance results for EDM1 and TRT campaigns are presented.

Processing↗
NASA NTRS2018

Digital Image Correlation Data Processing and Analysis Techniques to Enhance Test Data Assessment and Improve Structural Simulations

The NASA Shell Buckling Knockdown Factor Project (SBKF) was established in 2007 by the NASA Engineering and Safety Center (NESC) with the primary goal to develop new analysis-based buckling design factors (a.k.a. knockdown factors) and high-fidelity buckling simulations for selected launch-vehicle-like cylindrical shell structures. A series of tests are being conducted on large-scale metallic and composite cylindrical shells in order to provide validation data for these new factors and simulations. However, the validation of these new factors and simulations is quite demanding and requires test data that is commensurate with their fidelity. Traditional instrumentation, such as linear variable displacement transducers (LVDTs) and electrical-resistance strain gages serve a critical role in providing accurate displacement and strain measurements in these tests, but only allow for data to be recorded at a select number of point locations and are not sufficient to provide all the necessary validation data. Advanced measurement technologies can be used effectively to complement traditional instrumentation and gather additional data required to validate these structural simulations. In particular, three-dimensional digital image correlation (DIC) was implemented during SBKF cylinder testing to characterize the full-field displacement and strain behavior. Commercially available VIC-3DTM software and user-written data processing scripts were used to generate valuable data and insight into the complex buckling response of the cylinders that otherwise would be impossible to gather using traditional instrumentation. In addition, the measured data from DIC was used to verify measured test data obtained from other instrumentation, enhance test and analysis correlation, and help identify the root cause of anomalous test results that may have gone unexplained if only traditional instrumentation was used. Selected test results that demonstrate the use of DIC on the SBKF cylinders are presented and a portion of the data processing methods are described.

Gardner, Nathaniel W.↗
NASA NTRS1998

Neural Networks for Rapid Design and Analysis

Artificial neural networks have been employed for rapid and efficient dynamics and control analysis of flexible systems. Specifically, feedforward neural networks are designed to approximate nonlinear dynamic components over prescribed input ranges, and are used in simulations as a means to speed up the overall time response analysis process. To capture the recursive nature of dynamic components with artificial neural networks, recurrent networks, which use state feedback with the appropriate number of time delays, as inputs to the networks, are employed. Once properly trained, neural networks can give very good approximations to nonlinear dynamic components, and by their judicious use in simulations, allow the analyst the potential to speed up the analysis process considerably. To illustrate this potential speed up, an existing simulation model of a spacecraft reaction wheel system is executed, first conventionally, and then with an artificial neural network in place.

Sparks, Dean W., Jr.↗
NASA NTRS1980

Systems analysis - Key to NASA's data system planning

Critical steps in the systems analysis process for NASA's data system planning are: (1) compilation of future user/mission requirements, (2) development of alternative overall data system concepts which satisfy requirements, (3) assessment of future development and availability of data system technology, and (4) cost/performance tradeoff studies of the alternative concepts for systems optimization. Tasks within the NEEDS (NASA End-to-End Data System) Program, which correspond to the critical steps in this systems analysis process are examined.

Nelson, R. W.↗
NASA NTRS1988

Space station synergetic RAM-logistics analysis

NASA's Space Station Maintenance Planning and Analysis (MP&A) Study is a step in the overall Space Station Program to define optimum approaches for on-orbit maintenance planning and logistics support. The approach used in the MP&A study and the analysis process used are presented. Emphasis is on maintenance activities and processes that can be accomplished on orbit within the known design and support constraints of the Space Station. From these analyses, recommendations for maintainability/maintenance requirements are established. The ultimate goal of the study is to reduce on-orbit maintenance requirements to a practical and safe minimum, thereby conserving crew time for productive endeavors. The reliability, availability, and maintainability (RAM) and operations performance evaluation models used were assembled and developed as part of the MP&A study and are described. A representative space station system design is presented to illustrate the analysis process.

Dejulio, Edmund T.↗
NASA NTRS2021

The First Global 883 GHz Cloud Ice Survey: IceCube Level 1 Data Calibration, Processing and Analysis

Sub-millimeter (sub-mm, 200 - 1000 GHz) wavelengths contribute a unique capability to fill-in the sensitivity gap between operational visible/infrared (VIS/IR) and microwave (MW) remote sensing for atmosphere cloud ice and snow. Being able of penetrating cloud to measure cloud ice mass and microphysical properties in the middle to upper troposphere, this is a critical spectrum range for us to understand the connection between cloud ice and precipitation processes.5As the first space-borne 883 GHz radiometer, IceCube mission was NASA’s latest effort in spaceflight demonstration of a commercial sub-mm radiometer technology. Successfully launched from the International Space Station, IceCube is essentially a free-running radiometer and collected valuable 15-month measurements of atmosphere and cloud ice. This paper describes the detailed procedures for Level 1 data calibration, processing and validation. The scientific quality and values of IceCube data are then discussed, including radiative transfer model validation and evaluation, as well as the unique spatial distribution10and diurnal cycle of cloud ice that are revealed for the first time on a quasi-global scale at this frequency.

IceCube↗
NASA NTRS2021

The First Global 883 GHz Cloud Ice Survey: IceCube Level 1 Data Calibration, Processing and Analysis

Sub-millimeter (sub-mm, 200 - 1000 GHz) wavelengths contribute a unique capability to fill-in the sensitivity gap between operational visible/infrared (VIS/IR) and microwave (MW) remote sensing for atmosphere cloud ice and snow. Being able of penetrating cloud to measure cloud ice mass and microphysical properties in the middle to upper troposphere, this is a critical spectrum range for us to understand the connection between cloud ice and precipitation processes.5As the first space-borne 883 GHz radiometer, IceCube mission was NASA’s latest effort in spaceflight demonstration of a commercial sub-mm radiometer technology. Successfully launched from the International Space Station, IceCube is essentially a free-running radiometer and collected valuable 15-month measurements of atmosphere and cloud ice. This paper describes the detailed procedures for Level 1 data calibration, processing and validation. The scientific quality and values of IceCube data are then discussed, including radiative transfer model validation and evaluation, as well as the unique spatial distribution10and diurnal cycle of cloud ice that are revealed for the first time on a quasi-global scale at this frequency

Jie Gong↗
NASA NTRS2009

Software Development to Assist in the Processing and Analysis of Data Obtained Using Fiber Bragg Grating Interrogation Systems

A fiber Bragg grating is a portion of a core of a fiber optic strand that has been treated to affect the way light travels through the strand. Light within a certain narrow range of wavelengths will be reflected along the fiber by the grating, while light outside that range will pass through the grating mostly undisturbed. Since the range of wavelengths that can penetrate the grating depends on the grating itself as well as temperature and mechanical strain, fiber Bragg gratings can be used as temperature and strain sensors. This capability, along with the light-weight nature of the fiber optic strands in which the gratings reside, make fiber optic sensors an ideal candidate for flight testing and monitoring in which temperature and wing strain are factors. The purpose of this project is to research the availability of software capable of processing massive amounts of data in both real-time and post-flight settings, and to produce software segments that can be integrated to assist in the task as well.

Hicks, Rebecca↗
NASA NTRSDate not supplied

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized. Video is an mp4 download, with a play time of 9 min 35 secs.

Natural Language Processing↗
NASA NTRS1972

ERTS computer compatible tape data processing and analysis. Appendix 1: The utility of imaging radars for the study of lake ice

There are no author-identified significant results in this report. Remotely sensed multispectral scanner and return beam vidicon imagery from ERTS-1 is being used for: (1) water depth measurements in the Virgin Islands and Upper Lake Michigan areas; (2) mapping of the Yellowstone National Park; (3) assessment of atmospheric effects in Colorado; (4) lake ice surveillance in Canada and Great Lakes areas; (5) recreational land use in Southeast Michigan; (6) International Field Year on the Great Lakes investigations of Lake Ontario; (7) image enhancement of multispectral scanner data using existing techniques; (8) water quality monitoring of the New York Bight, Tampa Bay, Lake Michigan, Santa Barbara Channel, and Lake Erie; (9) oil pollution detection in the Chesapeake Bay, Gulf of Mexico southwest of New Orleans, and Santa Barbara Channel; and (10) mapping iron compounds in the Wind River Mountains.

Polcyn, F. C.↗
NASA NTRS1974

Results of geodetic processing and analysis of Skylab altimetry data

A geodetic analysis of Skylab S-193 altimeter preliminary data from mission SL/2 and EREP pass 9 is considered. The overall objective of the investigation was a demonstration of the feasibility of a use of altimeter data for the determination of the geoid in ocean areas. The geoid is the equipotential surface that would coincide with an 'undisturbed' mean sea level of the earth's gravity field. Analytical data handling formulations are discussed.

Fubara, D. M. J.↗
NASA NTRS1979

Coal conversion processes and analysis methodologies for synthetic fuels production

Information to identify viable coal gasification and utilization technologies is presented. Analysis capabilities required to support design and implementation of coal based synthetic fuels complexes are identified. The potential market in the Southeast United States for coal based synthetic fuels is investigated. A requirements analysis to identify the types of modeling and analysis capabilities required to conduct and monitor coal gasification project designs is discussed. Models and methodologies to satisfy these requirements are identified and evaluated, and recommendations are developed. Requirements for development of technology and data needed to improve gasification feasibility and economies are examined.

Source record↗
NASA NTRS1990

Processing and analysis of radiometer measurements for airborne reconnaissance

This paper describes selected results of airborne, radiometric imaging measurements at 90 GHz and 140 GHz relevant for the application in reconnaissance. Using a temperature resolution below 0.5 K and an angular resolution of about 1-degree high-quality images show the capability of discriminating between many brightness temperature classes within our natural environment and man-made objects. Measurement examples are given for cloud and fog penetration at 90 GHz, for the detection of vehicles on roads, and for the detection and classification of airports and airplanes. The application of different contour enhancement methods (Marr-Hildreth and Canny) shows the possibility of extracting lines and shapes precisely in order to improve automatic target recognition. The registration of the passive images with corresponding X-band synthetic aperture images from the same area is carried out and the high degree of correlation is discussed.

Suess, Helmut↗