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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 NTRS2006

Implementing EVM Data Analysis Adding Value from a NASA Project Manager's Perspective

Data Analysis is one of the keys to an effective Earned Value Management (EVM) Process. Project Managers (PM) must continually evaluate data in assessing the health of their projects. Good analysis of data can assist PMs in making better decisions in managing projects. To better support our P Ms, National Aeronautics and Space Administration (NASA) - Marshall Space Flight Center (MSFC) recently renewed its emphasis on sound EVM data analysis practices and processes, During this presentation we will discuss the approach that MSFC followed in implementing better data analysis across its Center. We will address our approach to effectively equip and support our projects in applying a sound data analysis process. In addition, the PM for the Space Station Biological Research Project will share her experiences of how effective data analysis can benefit a PM in the decision making process. The PM will discuss how the emphasis on data analysis has helped create a solid method for assessing the project s performance. Using data analysis successfully can be an effective and efficient tool in today s environment with increasing workloads and downsizing workforces

Counts, Stacy↗
NASA NTRS2004

High Altitude Long Endurance Remotely Operated Aircraft - National Airspace System Integration - Simulation IPT: Detailed Airspace Operations Simulation Plan. Version 1.0

The primary goal of Access 5 is to allow safe, reliable and routine operations of High Altitude-Long Endurance Remotely Operated Aircraft (HALE ROAs) within the National Airspace System (NAS). Step 1 of Access 5 addresses the policies, procedures, technologies and implementation issues of introducing such operations into the NAS above pressure altitude 40,000 ft (Flight Level 400 or FL400). Routine HALE ROA activity within the NAS represents a potentially significant change to the tasks and concerns of NAS users, service providers and other stakeholders. Due to the complexity of the NAS, and the importance of maintaining current high levels of safety in the NAS, any significant changes must be thoroughly evaluated prior to implementation. The Access 5 community has been tasked with performing this detailed evaluation of routine HALE-ROA activities in the NAS, and providing to key NAS stakeholders a set of recommended policies and procedures to achieve this goal. Extensive simulation, in concert with a directed flight demonstration program are intended to provide the required supporting evidence that these recommendations are based on sound methods and offer a clear roadmap to achieving safe, reliable and routine HALE ROA operations in the NAS. Through coordination with NAS service providers and policy makers, and with significant input from HALE-ROA manufacturers, operators and pilots, this document presents the detailed simulation plan for Step 1 of Access 5. A brief background of the Access 5 project will be presented with focus on Steps 1 and 2, concerning HALE-ROA operations above FL400 and FL180 respectively. An overview of project management structure follows with particular emphasis on the role of the Simulation IPT and its relationships to other project entities. This discussion will include a description of work packages assigned to the Simulation IPT, and present the specific goals to be achieved for each simulation work package, along with the associated deliverables necessary to achieve these goals and the needs of other Access 5 IPTs. The simulation environment chosen for this task is then outlined. This section includes a description of the system architecture, a list of the necessary assumptions made by the Simulation IPT, and the roles, responsibilities and interactions of simulation participants. The method of simulation conduct is presented in the next section with particular emphasis on scenario development and applicability to evaluation of Step 1 HALE-ROA operations. Following, data collection and analysis methods are discussed for air traffic specialists and air vehicle control station operators. Lastly, a schedule of Step 1 simulation activities is presented for reference.

Source record↗
NASA NTRS1985

Computerized data acquisition and analysis for measuring thermal diffusivity

JPL has been leading a concentrated effort to develop improved thermoelectric materials for space applications. Thermoelectric generators are an attractive source of electrical energy for space power because of lack of moving parts and slow degradation of performance. Thermoelectric material is characterized by: Seebeck coefficient, electrical resistivity and thermal conductivity. To measure the high temperature thermal conductivity is experimentally very difficult. However, it can be calculated from the specific heat and thermal diffusivity which are easier to measure at high temperatures, especially using the flash method. Data acquisition and analysis for this experiment were automated at JPL using inexpensive microcomputer equipment. This approach is superior to tedious and less accurate manual analysis of data. It is also preferred to previously developed systems utilizing expensive minicomputers or mainframes.

Chmielewski, A.↗
NASA NTRSDate not supplied

From Formal Errors Towards Realistic Uncertainties

Evaluation of uncertainties of geodetic parameter estimates is the problem that is not yet solved in a satisfactory way. A direct evaluation of the uncertainties derived from a least square solution is labeled "formal" and is usually biased, sometimes up to an order of magnitude. Customary, the use of formal errors for scientific analysis is discouraged. We claim that the root of the problem is neglecting off-diagonal elements in the variance-covariance matrix of the noise in the data. A careful reconstruction of the full variance-covariance matrix, including the off-diagonal terms greatly improves realism of uncertainty estimates derived from least squares. We processed the dataset of VLBI group delays and built a prior variance-covariance of the atmosphere-driven noise based on analysis of the output of NASA high-resolution numerical weather models. We found that the uncertainties of parameter estimates derived from this least square solution that uses such variance-covariance matrices become much closer to realistic errors. We consider approaches for implementation of this method in routine data analysis of space geodesy data.

Leonid Petrov↗
DOE OSTI2019

Search for Low-Mass Dark Matter with CDMSlite Using a Profile Likelihood Fit

The Cryogenic Dark Matter Search low ionization threshold experiment (CDMSlite) searches for interactions between dark matter particles and germanium nuclei in cryogenic detectors. The experiment has achieved a low energy threshold with improved sensitivity to low-mass (<10 GeV/c2) dark matter particles. We present an analysis of the final CDMSlite data set, taken with a different detector than was used for the two previous CDMSlite data sets. This analysis includes a data "salting" method to protect against bias, improved noise discrimination, background modeling, and the use of profile likelihood methods to search for a dark matter signal in the presence of backgrounds. We achieve an energy threshold of 70 eV and significantly improve the sensitivity for dark matter particles with masses between 2.5 and 10 GeV/c2 compared to previous analyses. We set an upper limit on the dark matter-nucleon scattering cross section in germanium of 5.4×10-42 cm2 at 5 GeV/c2, a factor of ~2.5 improvement over the previous CDMSlite result.

Agnese, R↗
DOE OSTI2023

Machine-learning-assisted automation of single-crystal neutron diffraction

Neutron scattering is a powerful but expensive technique to study materials and discover new matter. Advanced detector technology has significantly improved the efficiency of neutron experiments, increasing the complexity of neutron data reduction and analysis. Machine learning (ML) brings new directions for neutron diffraction data reduction and experiment operation. Here, this work presents an ML-assisted data reduction and analysis method for precise recognition of Bragg peaks and the corresponding regions of interest; it can then automatically screen and align a measured crystal using the recognized peaks, and subsequently plan and optimize the data collection with user-provided information and uncertainty quantification values of detected peaks. This method shows robust performance in different complex sample environments and enables automated single-crystal neutron diffraction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Dynamical Components Analysis (DCA) v1.0.0

Dynamical Components Analysis is a Python implementation of the method described in "Unsupervised discovery of temporal structure in noisy data with dynamical components analysis". It implements the method as well as related data analysis functions.

Livezey, Jesse↗
DOE OSTI2021

Dynamical Components Analysis (DCA) v1.0.0

Dynamical Components Analysis is a Python implementation of the method described in "Unsupervised discovery of temporal structure in noisy data with dynamical components analysis". It implements the method as well as related data analysis functions.

Livezey, Jesse↗
DOE OSTI2020

AFIP6-MkII and RERTR-12 Porosity Data Collection and Analysis for Modeling and Simulation

Gathering data for the improvement of nuclear fuel modeling and simulation efforts is the primary driver for this work. Mechanistic models allow for a better understanding of the material on a micro- and macrostructural level while saving time and money over traditional experiment efforts. Historically, summarized data and correlations are the inputs for empirical material models and model validation. When improving these models for nuclear fuels with experimental results, there is a lack of reliable data readily available. Experiments - RERTR-12 and AFIP6-MkII - were conducted to understand the irradiation behavior of metallic U-10Mo monolithic fuels for use in extreme reactor environments such as research reactors like the Advanced Test Reactor (ATR) or the High Flux Isotope Reactor (HFIR). Microstructural characteristics of fission gas pores (FGP) in each experiment are collected using an automated image analysis technique developed at the University of Florida and presented here. A series of statistical tests are performed to explore the reliability of the results, as well as understand where the data is lacking and what future data collection is necessary to provide sufficient information to assist modeling efforts. The focus is on the porosity, pore size, and eccentricity of FGPs formed during irradiation in three AFIP6-MkII samples and one RERTR-12 sample. From the analysis, it is clear there are substantial impacts of fission density on the pore structure, but there also exist also underlying connections between each sample and the behavior observed in the pores. Further analyses of the pre- and post-irradiation microstructure are needed to improve the understanding of these connections. An early method for microstructural data analysis is presented within and is currently being expanded to include other microstructure data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

DASSA v0.0.1

DASSA (Parallel DAS Data Storage and Analysis) provides a data storage engine and analysis engine for data from distributed acoustic sensing and other methods. It supports various data analysis operations, from FFT , signal filter, cross-correlation, compression, stacking etc.

Dong, Bin↗
NASA NTRS2009

Simulating and Detecting Radiation-Induced Errors for Onboard Machine Learning

Spacecraft processors and memory are subjected to high radiation doses and therefore employ radiation-hardened components. However, these components are orders of magnitude more expensive than typical desktop components, and they lag years behind in terms of speed and size. We have integrated algorithm-based fault tolerance (ABFT) methods into onboard data analysis algorithms to detect radiation-induced errors, which ultimately may permit the use of spacecraft memory that need not be fully hardened, reducing cost and increasing capability at the same time. We have also developed a lightweight software radiation simulator, BITFLIPS, that permits evaluation of error detection strategies in a controlled fashion, including the specification of the radiation rate and selective exposure of individual data structures. Using BITFLIPS, we evaluated our error detection methods when using a support vector machine to analyze data collected by the Mars Odyssey spacecraft. We found ABFT error detection for matrix multiplication is very successful, while error detection for Gaussian kernel computation still has room for improvement.

data analysis↗
DOE OSTI2015

A Bayesian method to estimate the neutron response matrix of a single crystal CVD diamond detector

Detectors made from artificial chemical vapor deposition (CVD) single crystal diamond are very promising candidates for applications where high resolution neutron spectrometry in very high neutron fluxes is required, for example in fusion research. We propose a Bayesian method to estimate the neutron response function of the detector for a continuous range of neutron energies (in our case, 10 MeV ≤ E{sub n} ≤ 16 MeV) based on a few measurements with quasi-monoenergetic neutrons. This method is needed because a complete set of measurements is not available and the alternative approach of using responses based on Monte Carlo calculations is not feasible. Our approach uses Bayesian signal-background separation techniques and radial basis function interpolation methods. We present the analysis of data measured at the PTB accelerator facility PIAF. The method is quite general and it can be applied to other particle detectors with similar characteristics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

EP-DRAFT-1.1 2014-01-19 OSI-GAM-SOP-00x In Situ High-resolution Gamma Spectroscopy

The standard operating procedure is described for in situ high-resolution gamma spectroscopy, including operational readiness, planning, preparation, conduct, and reporting. Data analysis of in situ gamma spectrum files will be performed together with those of other gamma assay methods by a dedicated Data Analysis process, documented in companion OSI procedures.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2005

Quantitative Electron Probe Microanalysis: State of the Art

Quantitative electron-probe microanalysis (EPMA) has improved due to better instrument design and X-ray correction methods. Design improvement of the electron column and X-ray spectrometer has resulted in measurement precision that exceeds analytical accuracy. Wavelength-dispersive spectrometer (WDS) have layered-dispersive diffraction crystals with improved light-element sensitivity. Newer energy-dispersive spectrometers (EDS) have Si-drift detector elements, thin window designs, and digital processing electronics with X-ray throughput approaching that of WDS Systems. Using these systems, digital X-ray mapping coupled with spectrum imaging is a powerful compositional mapping tool. Improvements in analytical accuracy are due to better X-ray correction algorithms, mass absorption coefficient data sets,and analysis method for complex geometries. ZAF algorithms have ban superceded by Phi(pz) algorithms that better model the depth distribution of primary X-ray production. Complex thin film and particle geometries are treated using Phi(pz) algorithms, end results agree well with Monte Carlo simulations. For geological materials, X-ray absorption dominates the corretions end depends on the accuracy of mass absorption coefficient (MAC) data sets. However, few MACs have been experimentally measured, and the use of fitted coefficients continues due to general success of the analytical technique. A polynomial formulation of the Bence-Albec alpha-factor technique, calibrated using Phi(pz) algorithms, is used to critically evaluate accuracy issues and can be also be used for high 2% relative and is limited by measurement precision for ideal cases, but for many elements the analytical accuracy is unproven. The EPMA technique has improved to the point where it is frequently used instead of the petrogaphic microscope for reconnaissance work. Examples of stagnant research areas are: WDS detector design characterization of calibration standards, and the need for more complete treatment of the continuum X-ray fluorescence correction.

Carpernter, P. K.↗
DOE OSTI2014

RISMC Advanced Safety Analysis Project Plan – FY 2015 - FY 2019

In this report, a project plan is developed, focused on industry applications, using Risk-Informed Safety Margin Characterization (RISMC) tools and methods applied to realistic, relevant, and current interest issues to the operating nuclear fleet. RISMC focuses on modernization of nuclear power safety analysis (tools, methods and data); implementing state-of-the-art modeling techniques (which include, for example, enabling incorporation of more detailed physics as they become available); taking advantage of modern computing hardware; and combining probabilistic and mechanistic analyses to enable a risk informed safety analysis process. The modernized tools will maintain the current high level of safety in our nuclear power plant fleet, while providing an improved understanding of safety margins and the critical parameters that affect them. Thus, the set of tools will provide information to inform decisions on plant modifications, refurbishments, and surveillance programs, while improving economics. This set of tools will also benefit the design of new reactors, enhancing safety per unit cost of a nuclear plant. The proposed plan will focus on application of the RISMC toolkit, in particular, solving realistic problems of important current issues to the nuclear industry, in collaboration with plant owners and operators to demonstrate the usefulness of these tools in decision making.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1983

Validation of structural analysis methods using burner liner cyclic rig test data

The objectives of the hot section technology (HOST) burner liner cyclic rig test program are basically threefold: (1) to assist in developing predictive tools needed to improve design analyses and procedures for the efficient and accurate prediction of burner liner structural response; (2) to calibrate, evaluate and validate these predictive tools by comparing the predicted results with the experimental data generated in the tests; and (3) to evaluate existing as well as advanced temperature and strain measurement instrumentation, both contact and noncontact, in a simulated engine cycle environment. The data generated will include measurements of the thermal environment (metal surface temperatures) as well as structural (strain) and life (fatigue) responses of simulated burner liners and specimens under controlled boundary and operating conditions. These data will be used to calibrate, compare and validate analytical theories, methodologies and design procedures, as well as improvements in them, for predicting liner temperatures, stress-strain responses and cycles to failure. Comparison of predicted results with experimental data will be used to show where the predictive theories, etc. need improvements. In addition, as the predictive tools, as well as the tests, test methods, and data acquisition and reduction techniques, are developed and validated, a proven, integrated analysis/experiment method will be developed to determine the cyclic life of a simulated burner liner.

Thompson, R.↗