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At least 199 records · Page 11
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 OSTI2014

F3D Image Processing and Analysis for Many - and Multi-core Platforms

F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.

Source record↗
DOE OSTI2014

F3D Image Processing and Analysis for Many - and Multi-core Platforms

F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.

Source record↗
DOE OSTI2021

Utilizing the Dynamic Networks Data Processing and Analysis Experiment (DNE18) to Establish Methodologies for the Comparison of Automatic Infrasonic Signal Detectors

The Dynamic Networks Experiment 2018 (DNE18) was a collaborative effort between Los Alamos National Laboratory (LANL), Sandia National Laboratories (SNL), Lawrence Livermore National Laboratory (LLNL) and Pacific Northwest National Laboratory (PNNL) designed to evaluate methodologies for multi-modal data ingestion and processing. One component of this virtual experiment was a quantitative assessment of current capabilities for infrasound data processing, beginning with the establishment of a baseline for infrasound signal detection. To produce such baselines, SNL and LANL exploited a common dataset of infrasound data recorded across a regional network in Utah from December 2010 through February 2011. We utilize two automated signal detectors, the Adaptive F-Detector (AFD) and the Multivariate Adaptive Learning Detector (MALD) to produce automated signal detection catalogs and an analyst-produced catalog. Comparisons indicate that automatic detectors may be able to identify small amplitude, low SNR events that cannot be identified by analyst review. We document detector performance in terms of precision and recall, demonstrating that the AFD is more precise, but the MALD has higher recall. We use a synthetic dataset of signals embedded in pink noise in order to highlight shortcomings in assessing detection algorithms for low signal to noise ratio signals which are commonly of interest to the nuclear monitoring community. For comparisons utilizing the synthetic dataset, the AFD has higher recall while precision is equal for both detectors. These results indicate that both detectors perform well across a variety of background noise environments; however, both detectors fail to identify repetitive, short duration signals arriving from similar backazimuths. These failures represent specific scenarios that could be targeted for further detector development.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The SCALE/AMPX multigroup cross section processing for fast reactor analysis

The SCALE/AMPX multigroup (MG) cross section processing procedure has been updated to minimize reactivity differences for fast reactor designs and boiling water reactors (BWRs) with very high void fractions to provide excellent agreement with continuous-energy reference calculations. SCALE MG calculations are widely applied to thermal spectrum light-water reactor (LWR) systems as well as fast spectrum metallic systems of interest to National Nuclear Security Administration. With growing interest from industry and regulators in applying SCALE for the design of fast spectrum reactors, both sodium and molten salt, and in the licensing of power up rates for BWRs, it is desirable to review the SCALE/AMPX procedure for unresolved resonance self-shielded data and high energy neutron spectra. The data were improved by generating MG unresolved resonance data based on the analytic probability table method with the narrow resonance approximation as well as the use of a very fine group structure typically used in fast system analysis. This study focused on verifying the probability table and the SCALE/AMPX MG cross section processing procedure by performing reaction rate analysis and benchmark calculations for various fast reactor and high void BWR systems. Here, results indicate that the improved SCALE/AMPX MG cross section processing provides excellent results for the fast reactor analysis.

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.↗
DOE OSTI2016

Vehicle Lightweighting: Mass Reduction Spectrum Analysis and Process Cost Modeling

The U.S. Department of Energy’s Vehicle Technologies Office, Materials area commissioned a study to model and assess manufacturing economics of alternative design and production strategies for a series of lightweight vehicle concepts. In the first two phases of this effort examined combinations of strategies aimed at achieving strategic targets of 40% and a 45% mass reduction relative to a standard North American midsize passenger sedan at an effective cost of $3.42 per pound (lb) saved. These results have been reported in the Idaho National Laboratory report INL/EXT-14-33863 entitled Vehicle Lightweighting: 40% and 45% Weight Savings Analysis: Technical Cost Modeling for Vehicle Lightweighting published in March 2015. The data for these strategies were drawn from many sources, including Lotus Engineering Limited and FEV, Inc. lightweighting studies, U.S. Department of Energy-funded Vehma International of America, Inc./Ford Motor Company Multi-Material Lightweight Prototype Vehicle Demonstration Project, the Aluminum Association Transportation Group, many United States Council for Automotive Research’s/United States Automotive Materials Partnership LLC lightweight materials programs, and IBIS Associates, Inc.’s decades of experience in automotive lightweighting and materials substitution analyses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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↗
DOE OSTI2014

Charge-exchange coupling between pickup ions across the heliopause and its effect on energetic neutral hydrogen flux

Pickup ions (PUIs) appear to play an integral role in the multi-component nature of the plasma in the interaction between the solar wind (SW) and local interstellar medium (LISM). Three-dimensional (3D) MHD simulations with a kinetic treatment for neutrals and PUIs are currently still not viable. In light of recent energetic neutral atom (ENA) observations by the Interstellar Boundary EXplorer, the purpose of this paper is to illustrate the complex coupling between PUIs across the heliopause (HP) as facilitated by ENAs using estimates of PUI properties extracted from a 3D MHD simulation of the SW-LISM interaction with kinetic neutrals. First, we improve upon the multi-component treatment of the inner heliosheath (IHS) plasma from Zank et al. by including the extinction of PUIs through charge-exchange. We find a significant amount of energy is transferred away from hot, termination shock-processed PUIs into a colder, 'freshly injected' PUI population. Second, we extend the multi-component approach to estimate ENA flux from the outer heliosheath (OHS), formed from charge-exchange between interstellar hydrogen atoms and energetic PUIs. These PUIs are formed from ENAs in the IHS that crossed the HP and experienced charge-exchange. Our estimates, based on plasma-neutral simulations of the SW-LISM interaction and a post-processing analysis of ENAs and PUIs, suggest the majority of flux visible at 1 AU from the front of the heliosphere, between ∼0.02 and 10 keV, originates from OHS PUIs, indicating strong coupling between the IHS and OHS plasmas through charge-exchange.

79 ASTRONOMY AND ASTROPHYSICS↗
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↗