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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series

Two dimensions of a dynamical system given by experimental time series are distinguished. Statistical dimension gives a theoretical upper bound for the minimal number of degrees of freedom required to describe the attractor up to the accuracy of the data, taking into account sampling and noise problems. The dynamical dimension is the intrinsic dimension of the attractor and does not depend on the quality of the data. Singular Spectrum Analysis (SSA) provides estimates of the statistical dimension. SSA also describes the main physical phenomena reflected by the data. It gives adaptive spectral filters associated with the dominant oscillations of the system and clarifies the noise characteristics of the data. SSA is applied to four paleoclimatic records. The principal climatic oscillations and the regime changes in their amplitude are detected. About 10 degrees of freedom are statistically significant in the data. Large noise and insufficient sample length do not allow reliable estimates of the dynamical dimension.

Vautard, R.↗
NASA NTRS1974

The use of multispectral difference data for urban change detection

The current work describes an experiment in which ERTS-1 digital multispectral scanner data from two times was used to detect change in an urban scene. The computer analysis implementation approach explored here was to register image data from the two times and to subtract the data to form multispectral difference images. The difference imagery was then analyzed using statistical pattern recognition to separate and classify different types of change. Construction was successfully detected.

Anuta, P. E.↗
NASA NTRS1982

Lightning and surface rainfall during Florida thunderstorms

Lightning and surface rainfall data are presented which were obtained during summer air mass thunderstorms at the NASA Kennedy Space Center. Attention is given to a computer algorithm which employed abrupt changes in the thundercloud electric fields to detect and count flashes. Statistics are given for the occurrence of lightning in 79 storms during the summer seasons of 1976-1980, as well as 28 lightning storms from the summers of 1977 and 1978. The relationship between lightning and rainfall is examined in the case of two thunderstorms whose locations allow a direct comparison of measurements. It is found that when meteorological conditions favor the production of lightning, there is an almost direct proportionality between the total rain volume and the total number of flashes.

Piepgrass, M. V.↗
DOE OSTI2021

Anomaly Detection, Localization and Classification using Drifting Synchrophasor Data Streams

With ongoing automation and digitization of the electric power system, several Phasor Measurement Units(PMUs) have been deployed for monitoring and control. PMU data can have multiple anomalies, and many of the researchers in the past have concentrated on training machine/deep learning algorithms offline for anomaly detection over PMU data (i.e., not in real time). These machine/deep learning algorithms, when trained offline on a sample rather than a population of the dataset, fail to consider the dynamic behavior of the power grid in real-time, resulting in low accuracy. Considering the dynamic behavior of the power grid (e.g., change in load, generation, distributed energy resources (DERs) switching, network, controls), the definition of data anomalies varies in time and requires online training. A fundamental challenge is to enable online (i.e., real-time) training of machine/deep learning algorithms for anomaly detection over streaming PMU data. While machine/deep learning is often desirable to manage data streams, training a deep learning algorithm over streaming PMU data is nontrivial due to changes in data statistics caused by dynamic streaming data. This paper proposes PMUNET: a novel device-level deep learning-based data-driven approach for anomaly detection, localization, and classification over streaming PMU data, using online learning and multivariate data-drift detection algorithm .Two variants of PMUNET, Dynamic data Change Driven Learning (DCDL) and Continuity Driven Learning (CDL), are proposed and compared. DCDL aims to train the deep learning algorithm whenever the definition of anomaly changes due to the power grid dynamics. On the other hand, CDL continuously trains the deep learning algorithm over the PMU data-stream. The experimental results verify that DCDL outperforms CDL and other efficient anomaly detection methods over multiple events such as faults and load/ generator/capacitor/DERs variations/switching for IEEE 14 and 39 Bus test system as well as real PMU industrial data. The result verifies that DCDL variant of PMUNET improves over existing approach with a gain of 2% - 10% in terms of accuracy, false-positive rate, and false-negative rate.

adversarial deep learning↗
DOE OSTI2021

The Relationship between Precipitation and Precipitable Water in CMIP6 Simulations and Implications for Tropical Climatology and Change

It is well documented that over the tropical oceans, column-integrated precipitable water (pw) and precipitation (P) have a nonlinear relationship. In this study moisture budget analysis is used to examine this P–pw relationship in a normalized precipitable water framework. It is shown that the parameters of the nonlinear relationship depend on the vertical structure of moisture convergence. Specifically, the precipitable water values at which precipitation is balanced independently by evaporation versus by moisture convergence define a critical normalized precipitable water, pw nc . This is a measure of convective inhibition that separates tropical precipitation into two regimes: a local evaporation-controlled regime with widespread drizzle and a precipitable water–controlled regime. Most of the 17 CMIP6 historical simulations examined here have higher pw nc compared to ERA5, and more frequently they operate in the drizzle regime. When compared to observations, they overestimate precipitation over the high-evaporation oceanic regions off the equator, thereby producing a ‘‘double ITCZ’’ feature, while underestimating precipitation over the large tropical landmasses and over the climatologically moist oceanic regions near the equator. The responses to warming under the SSP585 scenario are also examined using the normalized precipitable water framework. It is shown that the critical normalized precipitable water value at which evaporation versus moisture convergence balance precipitation decreases as a result of the competing dynamic and thermodynamic responses to warming, resulting in an increase in drizzle and total precipitation. Statistically significant historical trends corresponding to the thermodynamic and dynamic changes are detected in ERA5 and in lowintensity drizzle precipitation in the PERSIANN precipitation dataset.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Analysis of Co-Located MODIS and CALIPSO Observations Near Clouds

The purpose of this paper is to help researchers combine data from different satellites and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the Aqua satellite's MODIS instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO satellite's CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the satellite orbit by measuring the reflection of its pulses. In contrast, MODIS takes images of reflected sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the satellite track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that MODIS can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between MODIS and CALIOP observations have only a minor impact. The study also finds that MODIS data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when MODIS cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is closer than 5 km to clouds implies that pronounced near-cloud changes in aerosol properties have significant implications for overall clear-sky characteristics, including the radiative impact of aerosols.

Varnai, Tamas↗
DOE OSTI2021

Cyber-Physical System Implementation for Manufacturing With Analytics in the Cloud Layer

Effective and efficient modern manufacturing operations require the acceptance and incorporation of the fourth industrial revolution, also known as Industry 4.0. Traditional shop floors are evolving their production into smart factories. To continue this trend, a specific architecture for the cyber-physical system is required, as well as a systematic approach to automate the application of algorithms and transform the acquired data into useful information. This work makes use of an approach that distinguishes three layers that are part of the existing Industry 4.0 paradigm: edge, fog, and cloud. Each of the layers performs computational operations, transforming the data produced in the smart factory into useful information. Trained or untrained methods for data analytics can be incorporated into the architecture. A case study is presented in which a real-time statistical control process algorithm based on control charts was implemented. The algorithm automatically detects changes in the material being processed in a computerized numerical control (CNC) machine. The algorithm implemented in the proposed architecture yielded short response times. The performance was effective since it automatically adapted to the machining of aluminum and then detected when the material was switched to steel. The data were backed up in a database that would allow traceability to the line of g-code that performed the machining.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Optimal weighting of data to detect climatic change - Application to the carbon dioxide problem

It is suggested that a weighting of surface temperature data, using information about the expected level of warming in different seasons and geographical regions and statistical information about the amount of natural variability in surface temperature, can improve the chances of early detection of carbon dioxide concentration-induced climatic warming. A preliminary analysis of the optimal weighting method presented suggests that it is 25 per cent more effective in revealing surface warming than the conventional method, in virtue of the fact that 25 per cent more data must conventionally be analyzed in order to arrive at a similar probability of detection. An approximate calculation suggests that the warming ought to have already been detected, if the only sources of significant surface temperature variability had time scales of less than one year.

Bell, T. L.↗
NASA NTRS1978

X-ray observations of a flare in NGC 4151 from OSO 8

The 2-60-keV flux from NGC 4151 has been observed to change by a factor of 2 on a time scale of 1.5 days. No fluctuations in excess of a factor of 3 are detected on time scales less than 4 hours. During a total observation of approximately 11 days there were no statistically significant changes in spectral shape. The spectrum can be fitted by a power law with photon index of about 1.42 + or - 0.06 and a hydrogen column density of approximately 7.5 + or - 0.5 x 10 to the 22nd power atoms/sq cm. A 2-sigma residual to this fit implies fluorescent Fe line emission with an equivalent width of about 240 eV. Both synchrotron self-Compton and thermal Compton models are consistent with the X-ray data.

Mushotzky, R. F.↗
NASA NTRS1979

An evaluation of the Goddard Space Flight Center Library

The character and degree of coincidence between the current and future missions, programs, and projects of the Goddard Space Flight Center and the current and future collection, services, and facilities of its library were determined from structured interviews and discussions with various classes of facility personnel. In addition to the tabulation and interpretation of the data from the structured interview survey, five types of statistical analyses were performed to corroborate (or contradict) the survey results and to produce useful information not readily attainable through survey material. Conclusions reached regarding compatability between needs and holdings, services and buildings, library hours of operation, methods of early detection and anticipation of changing holdings requirements, and the impact of near future programs are presented along with a list of statistics needing collection, organization, and interpretation on a continuing or longitudinal basis.

Herner, S.↗
NASA NTRS1970

Introductory comments on the USGS geographic applications program

The third phase of remote sensing technologies and potentials applied to the operations of the U.S. Geological Survey is introduced. Remote sensing data with multidisciplinary spatial data from traditional sources is combined with geographic theory and techniques of environmental modeling. These combined imputs are subject to four sequential activities that involve: (1) thermatic mapping of land use and environmental factors; (2) the dynamics of change detection; (3) environmental surveillance to identify sudden changes and general trends; and (4) preparation of statistical model and analytical reports. Geography program functions, products, clients, and goals are presented in graphical form, along with aircraft photo missions, geography test sites, and FY-70.

Gerlach, A. C.↗
NASA NTRS1977

90-GHz flux-density measurements of variable radio sources

Results are presented for measurements of the flux densities of 10 variable extragalactic sources at 85.2 or 90 GHz, which were made over a period of almost seven years with the NRAO 36-ft millimeter-wave antenna. The primary flux-density calibration standards used include Jupiter, Saturn, Mars, and the small-diameter Galactic source DR 21. Measured flux densities are given as a function of time (in years) for the sources 3C 84, NRAO 150, 3C 120, OJ 287, 4C 39.25, 3C 273, 3C 279, 3C 345, BL Lac, and 3C 454.3. No statistically meaningful flux-density changes during an observing interval (1 to 3 days) are detected for any source, and a high degree of correlation between flux-density variations at 85.2 or 90 GHz and those observed at lower frequencies is found in all 10 sources. Some variations observed at different frequencies in several individual sources are briefly discussed.

Hobbs, R. W.↗
NASA NTRS1981

Urban area update procedures using Landsat data

Landsat digital enhancements and classification maps are shown to be useful for updating the urban expansion of standard metropolitan statistical areas on a macro scale. Automated procedures for detecting nonurban to urban land coverage change using multitemporal Landsat data are investigated for five metropolitan areas, showing an overall delineation similar to that obtained from large scale aerial photography. The evaluated change detection procedures include image differencing, principal component transformation prior to differencing, and post classification comparison. Results show that image differencing techniques in MSS band 5 provide the most accurate land cover change detections.

Toll, D. L.↗
NASA NTRS2003

Monitoring of Observation Errors in the Assimilation of Satellite Ozone Data

The stratospheric ozone layer protects life on Earth from the harmful effects of solar ultravioiet radiation. The ozone layer is currently in a fragile state because of depletion caused by man-made chemicals, especially chlorofluorocarbons. The state of the ozone layer is being monitored and evaluated by scientific experts around the world, in order to help policy makers assess the impacts of international protocols that control the production and release of ozone depleting chemicals. Scientists use a variety ozone measurements and models in order to form a comprehensive picture about the current state of the ozone layer, and to predict the future behavior (expected to be a recovery, as the abundance of the depleting chemicals decreases). Among the data sets used, those from satellite-borne instruments have the advantage of providing a wealth of information about the ozone distribution over most of the globe. Several instruments onboard American and international satellites make measurements of the properties of the atmosphere, from which atmospheric ozone amounts are estimated; long-term measurement programs enable monitoring of trends in ozone. However, the characteristics of satellite instruments change in time. For example, the instrument lenses through which measurements are made may deteriorate over time, or the satellite orbit may drift so that measurements over each location are made later and later in the day. These changes may increase the errors in the retrieved ozone amounts, and degrade the quality of estimated ozone amounts and of their variability. Our work focuses on combining the satellite ozone data with global models that capture atmospheric motion and ozone chemistry, using advanced statistical techniques: this is known as data assimilation. Our method provides a three-dimensional global ozone distribution that is consistent with both the satellite measurements and with our understanding of processes (described in the models) that control ozone distribution. Through the monitoring of statistical properties of the agreement between the data and the model, this approach also enables us to detect changes in the quality of ozone data retrieved from satellite-borne instrument measurements. This paper demonstrates that calculations of the changes in satellite data quality, and the impact these changes on the estimates of the global ozone distribution, can assist in maintaining the uniform quality of the satellite ozone data throughout the lifetime of these instruments, thus contributing to our understanding of long-term ozone change.

Stajner, Ivanka↗
DOE OSTI2021

Parsing Weather Variability and Wildfire Effects on the Post-Fire Changes in Daily Stream Flows: A Quantile-Based Statistical Approach and Its Application

Determining wildland fire impacts on streamflow can be problematic as the hydrology in burned watersheds is influenced by post-fire weather conditions. Here, this study presents a quantile-based analytical framework for assessing fire impacts on low and peak daily flow magnitudes, while accounting for post-fire weather influences. This framework entails (a) the bootstrap method to compute the relative change in the post-fire annual flow and weather statistics, (b) double mass analysis to detect if post-fire baseflow and quick-flow yield ratios are significantly altered, and (c) a quantile regression method to parse fire effects on flow at a specific quantile. We illustrate the applicability of this analytical framework using 44 western US streams with at least 5% of their watershed area burned. Results indicate that large, high-severity burns in upland watersheds can raise the streamflow magnitude at the 0. 05 th and 0. 95 th quantiles for at least the five post-fire years. Quantile regression results show that the median fire-related increase in flow for the five post-fire years can be up to 5,000% (Standard Error; S.E. < 2%) at the 0. 05 th E quantile and 161% (S.E. < 10%) at the 0. 95 th quantile. The fire-related increase in flow was often pronounced at the 0. 05 th quantile for streams in the Pacific Northwest and California regions. The difference in fire effects on flow (at both quantiles) across streams was related to post-fire weather, pyrology, physiography, and land cover. The proposed analytical framework can be useful for detecting and quantifying fire effects on the low and peak stream flows in burned watersheds without overlapping disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The impact of detection rate changes and correlations on random-coincidence background measurements

Coincidence detection of multiple particles emitted during an experiment can yield a new depth of understanding of the underlying process under study. However, the probability of detecting particles that are generated from the same physical event within a given coincidence time window is generally much lower than that of detecting particles that appear in the same coincidence time window, but were not created from the same physical event, and are therefore detected randomly in coincidence with each other. Thus, accurate and precise methods of measuring this random-coincidence background are essential for a wide variety of fields of science. A method to determine this background directly using the data themselves without any additional experimental run time or fake signals introduced in the data was recently established (O’Donnell, 2016). This method yields a statistical uncertainty on the random-coincidence background that is orders of magnitude smaller than that of the true coincidence data, though the potential for systematic errors of backgrounds from this method was never explored. In this work, we discuss common varieties of correlated and uncorrelated changes in the detection rates of each particle detected in an experiment. Here we demonstrate here that a correlation between particle detection rates from, for example, an incident particle beam that initiates a physical process of interest, creates systematic errors in the random-coincidence background measurement. We also discuss the impact of a variety of other realistic scenarios for rate changes in experiments. Lastly, a method is introduced to correct for errors in the random-coincidence background from any source, yielding an optimization between statistical precision and eliminating potential lingering systematic errors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1978

Measurement and analysis of magnetic field variation during a class 2b flare

A digital analysis of high-time-resolution videomagnetograms taken during a class 2b flare that occurred at 60 deg east is reported. The data were obtained at the Big Bear Observatory and calibrated by a Mt. Wilson magnetogram. Changes of weak magnetic fields (less than 100 G) with an amplitude of 30% to 100% have been detected over 55% of the optical flare region, apparently taking place at the initial phase of the flare. Statistical considerations suggest a real flare association with most of these changes. H-alpha observations show that large changes took place over the footpoints of heavily inclined structures like penumbral fibrils, while smaller changes took place over the plage region. An apparent polarity reversal was found at the feet of erupted fibrils. Based on force-free field calculations these changes can be reasonably explained as a transformation of the current-carrying fields to potential fields which produced large changes in the field-line inclination and rotation.

Tanaka, K.↗
NASA NTRS1978

X-ray observations of a flare in NGC4151 from OSO-8

The 2-60 keV flux from NGC4151 changed by a factor of two on a timescale of 1.5 days. No fluctuations were detected in excess of a factor of three on timescales less than four hours. During a total observation of approximately 11 days there were no statistically significant changes in spectral shape. The spectrum was fitted by a power law with photon index alpha approximately 1.42 + or - 0.06 and column density N sub H approximately 7.5 + or - 0.5 x 10 to the 22d power at/cu cm. A 2 sigma residual to this fit implies fluorescent Fe line emission with E. W. approximately 240 eV. Both synchrotron self-Compton and thermal Compton models are consistent with the X-ray data.

Mushotzky, R. F.↗