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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Exact methods for modal transient response analysis including feedback control

This paper presents a modal method for the analysis of controlled structural systems that retains the uncoupled nature of the classical transient response analysis of a structure subjected to a prescribed time-varying load. The control force is expanded as a Taylor series that remains on the right side of the equations, and it does not lead to a computational approach that requires coupling between modes on the left side. Retaining a sufficient number of terms in the series produces a solution to the modal equations that is accurate to machine precision. The approach is particularly attractive for large problems in which standard matrix exponential methods become computationally prohibitive. Numerical results are presented to show the accuracy and efficiency of the proposed approach for dynamic feedback compensation of a truss structure with local member modes in the controller bandwidth.

Anderson, Melvin S.↗
NASA NTRS1994

Shortwave feedbacks and El Nino-Southern Oscillation: Forced ocean coupled ocean-atmosphere experiments

Changes in tropical sea surface temperature (SST) can produce changes in cloudiness that modify incoming solar shortwave (SW) radiation, which in turn affects SST. The effects of this negative feedback on Pacific interannual variability are examined in forced ocean model and hybrid coupled ocean-atmosphere model simulations. Two empirical schemes are used to model the large-scale, low-frequency response of surface SW to SST anomalies. The first scheme attempts to account for the nonlocal nature of the atmospheric response to SST based patterns of covariability analyzed through singular value decomposition. In the observations the primary coupled mode of variability is composed of a SW anomaly in the central Pacific that covaries with anomalous SST in the eastern Pacific. This is applied in the model as a nonlocal feedback. The second scheme examines the effects of a purely local feedback with a spatially varying coefficient of magnitude chosen similar to the first scheme. In almost all cases the second scheme behaved similarly to the first, presumably because the correlation scale of SST is large enough for El Nino-Southern Oscillation (ENSO) dynamics that there is little sensitivity to the local approximation in the SW feedback. In simulations forced by time series of observed wind stress the SW feedback induced very minor SST damping. Results for a simpified heat budget analysis showed that while the SW feedback increased the local heat flux damping on SST, it also induced a mean shallowing of the mixed layer. The resulting changes in both the local mean vertical temperature gradient and the zonal velocity response to the wind stress acted to oppose the local heat flux damping effects. When the observed SW anomalies were applied to forced simulations, the simulated SST anomalies were modified as expected, and agreement with observed SST improved. In coupled simulations the SW feedbacks had greater impact than in the case of specified stress. The main effects were to decrease the magnitude of the warm and cold SST anomalies in the central Pacific, while leaving the pattern and evolution of ENSO anomalies essentially unchanged elsewhere. The SW feedbacks thus produce a modest improvement of the model ENSO SST pattern compared with observations, although they tended to shorten the period of the model ENSO cycle. Overall the results suggest that large-scale SW feedbacks are of quantitative importance to simulating some aspects of the ENSO cycle but are not critical to the overall occurrence of the phenomenon.

Waliser, Duane E.↗
NASA NTRS1999

Elevation Change of the Southern Greenland Ice Sheet: Update

The overall focus of our research is to document long-term elevation change of the Greenland ice sheet using satellite altimeter data. In addition, we are investigating seasonal and interannual variations in the ice-sheet elevations to place the long-term measurements in context. Specific objectives of this research include: 1) Developing new techniques to significantly improve the accuracy of elevation-change estimates derived from satellite altimetry. 2) Measuring the elevation change of the Greenland ice sheet over a 10-year time period using Seasat (1978) and Geosat GM (1985-86) and Geosat ERM (1986-88) altimeter data. 3) Quantifying seasonal/interannual variations in the elevation-change estimates using the continuous time series of surface elevations from the Geosat GM and ERM datasets. 4) Extending the long-term elevation change analysis to two decades by incorporating data from the ERS-1/2 missions (1991-99) and, if available, the Geosat-Follow On (GFO) mission (1998-??).

Davis, C. H.↗
DOE OSTI2020

Reliable machine prognostic health management in the presence of missing data

Prognostics and health management enables the prediction of future degradation and remaining useful life (RUL) for in-service systems based on historical and contemporary data, showing promise for many practical applications. One major challenge for prognostics is the common occurrence of missing values in time-series data, often caused by disruptions in sensor communication or hardware/software failures. Another major concern is that the sufficient prior knowledge of critical component degradation with a clear failure threshold is often not readily available in practice. These issues can significantly hinder the application of advanced signal and data analysis methods and consequently degrade the health management performance. In this article, we propose a novel data-driven framework that is capable of providing accurate and reliable predictions of degradation and RUL. In this approach, one-hot health state indicators are appended to the historical time series so that the model learns end-of-life automatically. A modified gate recurrent unit based variational autoencoder is employed in generative adversarial networks to model the temporal irregularity of the incomplete time series. Furthermore, experiments on multivariate time-series datasets collected from real-world aeroengines verify that significant performance improvement can be achieved using the proposed model for robust long-term prognostics.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Data-Driven Modeling and Optimization of Building Energy Consumption: a Case Study

Installing sensors and Building Automation Systems (BAS) allows controlling the facility operations while generating data that can be analyzed for model development. This work focuses on data-driven modeling of the building to optimize energy consumption. The City of Orlando aims to reduce its energy consumption so, they provided us access to their BAS for data and studying the operation of its facilities. We selected a mid-size pilot building to conduct data analysis and modeling. We develop an Application Programming Interface (API) to login to the servers and scrape data. The scraped data contains features ranging from environmental conditions to equipment activity. This dataset is a time series so, it's handled in accordance and analyzed to investigate patterns and relations between data points that help choose parameters for predictive models for building and equipment. Finally, the models are optimized to reduce the energy consumption of the facility.

Grover, Divas↗
NASA NTRS1993

Voyager 2 Test Of The Radar Time-Delay Effect

Report presents analysis of radio range measurements generated during superior solar conjunction of Voyager 2 spacecraft in December 1985. One in continuing series of studies directed toward verifying prediction, according to theory of general relativity, that electromagnetic signal propagating near Sun is delayed by solar gravitational field.

Krisher, Timothy P.↗
NASA NTRS1994

Time-series photometric spot modeling. 2: Fifteen years of photometry of the bright RS CVn binary HR 7275

We present a time-dependent spot modeling analysis of 15 consecutive years of V-band photometry of the long-period (P(sub orb) = 28.6 days) RS CVn binary HR 7275. This baseline in time is one of the longest, uninterrupted intervals a spotted star has been observed. The spot modeling analysis yields a total of 20 different spots throughout the time span of our observations. The distribution of the observed spot migration rates is consistent with solar-type differential rotation and suggests a lower limit of the differential-rotation coefficient of 0.022 +/-0.004. The observed, maximum lifetime of a single spot (or spot group) is 4.5 years, the minimum lifetime is approximately one year, but an average spot lives for 2.2 years. If we assume that the mechanical shear by differential rotation sets the upper limit to the spot lifetime, the observed maximum lifetime in turn sets an upper limit to the differential-rotation coefficient, namely 0.04 +/- 0.01. This would be differential rotation just 5 to 8 times less than the solar value and one of the strongest among active binaries. We found no conclusive evidence for the existence of a periodic phenomenon that could be attributed to a stellar magnetic cycle.

Strassmeier, K. G.↗
NASA NTRS2014

Evaluating an Automated Approach for Monitoring Forest Disturbances in the Pacific Northwest from Logging, Fire and Insect Outbreaks with Landsat Time Series Data

Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they change through time is critical to reduce our C-cycle uncertainties. We investigated a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 1991 in Pacific Northwest forests, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometers (AVHRRs). To understand the causal factors of this decline, we evaluated an automated classification method developed for Landsat time series stacks (LTSS) to map forest change. This method included: (1) multiple disturbance index thresholds; and (2) a spectral trajectory-based image analysis with multiple confidence thresholds. We produced 48 maps and verified their accuracy with air photos, monitoring trends in burn severity data and insect aerial detection survey data. Area-based accuracy estimates for change in forest cover resulted in producer's and user's accuracies of 0.21 +/- 0.06 to 0.38 +/- 0.05 for insect disturbance, 0.23 +/- 0.07 to 1 +/- 0 for burned area and 0.74 +/- 0.03 to 0.76 +/- 0.03 for logging. We believe that accuracy was low for insect disturbance because air photo reference data were temporally sparse, hence missing some outbreaks, and the annual anniversary time step is not dense enough to track defoliation and progressive stand mortality. Producer's and user's accuracy for burned area was low due to the temporally abrupt nature of fire and harvest with a similar response of spectral indices between the disturbance index and normalized burn ratio. We conclude that the spectral trajectory approach also captures multi-year stress that could be caused by climate, acid deposition, pathogens, partial harvest, thinning, etc. Our study focused on understanding the transferability of previously successful methods to new ecosystems and found that this automated method does not perform with the same accuracy in Pacific Northwest forests. Using a robust accuracy assessment, we demonstrate the difficulty of transferring change attribution methods to other ecosystems, which has implications for the development of automated detection/attribution approaches. Widespread disturbance was found within AVHRR-negative anomalies, but identifying causal factors in LTSS with adequate mapping accuracy for fire and insects proved to be elusive. Our results provide a background framework for future studies to improve methods for the accuracy assessment of automated LTSS classifications.

Landsat↗
DOE OSTI2020

High Resolution Data Analysis: Plans and Prospects [Book Chapter]

Herein, a report on the progress on the high resolution data analysis of the ADMX experimental results is presented. In this paper, tools are developed and tested on a blind injection mimicking a Maxwellian like signal in the frequency domain. This blind injection will be used as a test bed which can be later implemented on all the high resolution data. The high resolution data is stored in the Fermilab server. In this analysis a PostgreSQL query was made to ensure the blind injection is in the middle of the frequency spectrum and 19 such files were found. The time series data is read using a c++ program. An apodization function is applied on the time series data and zero filled to reduce the frequency spacing in order to achieve a better interpolation. A FFTW header is used to compute the Fourier transform of the time series data. A Savitzky–Golay filter is applied on the unnormalized power which then can be used to remove the spectral shape. Each frequency spectrum has a bandwidth of 50 kHz.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Electrical-Discharge-Machining Contamination Removal from Metal Additively Manufactured Components

The use of an electrochemical dissolution process is shown to remove the recast layer contamination from the surfaces of electrical-discharge-machining cut components, as well as the interior exposed surfaces of the structure. The solution chemistry, cell potential, and exposure time are all relevant interdependent variables. Optimization of the electrode geometry should be made for each type of component. For the case of Cu-Zn recast contamination of 300-series alloy components, surface composition analysis indicates that complete electrochemical dissolution is achieved using a dilute solution of nitric acid (HNO 3 ). For example, electrochemical dissolution of the Cu-Zn recast is accomplished at 1.2 V cell potential using a 20% nitric solution and an exposure time of 4 h. The use of a nitric acid bath was specifically chosen since it’s chemically compatible and will not degrade the host alloy or the component. In sum, an electrochemically driven dissolution process can be tailored to remove of the recast contamination without affecting the integrity of the host component structure and its dimensional tolerances.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Variability of pigment biomass in the California Current system as determined by satellite imagery. II - Temporal variability

Characteristics of temporal variability in the California Current system are analyzed using a 30-month time series of CZCS imagery. About 20-25 percent of the variance is produced by a periodic annual cycle with peak values in winter. Analysis of ship-based chlorophyll measurements indicates that the winter peak is only characteristic of the upper portion of the euphotic zone and that total water column chlorophyll peaks during the spring upwelling season. Satellite studies of intraannual variability are modulated by strong 5- to 6-day oscillation in the availability of usable imagery, resulting from a combination of satellite orbital dynamics, which produces images of the study area roughly 4 out of every 6 days, and an oscillation in cloud cover, which controls the availability of clear imagery. The cloud cover oscillation, which is also present in coastal winds, undoubtedly affects the ocean surface and biases the data obtained by satellites. Analysis of data using a 5-day time step indicates that the predominant mode of nonseasonal variability is characterized by in-phase fluctuations throughout the southern and central California coastal region.

Michaelsen, Joel↗
DOE OSTI2023

Deep neural operators can predict the real-time response of floating offshore structures under irregular waves

The use of neural operators in a digital twin model of an offshore floating structure holds the potential for a significant shift in the prediction of structural responses and health monitoring, offering valuable real-time control insights. In this work, we investigate the effectiveness of three neural operators, namely the deep operator network (DeepONet), the Fourier neural operator (FNO), and the Wavelet neural operator (WNO), to accurately capture the responses of a floating structure under six different sea state codes (3 − 8) based on the wave characteristics described by the World Meteorological Organization (WMO). To further enhance the accuracy of the vanilla architecture of the neural operators, novel extensions, such as wavelet-DeepONet and self-adaptive WNO, are proposed in this paper. The results demonstrate that these high-precision neural operators can deliver structural responses more efficiently, up to two orders of magnitude faster than a dynamic analysis using conventional numerical solvers. Additionally, compared to gated recurrent units (GRUs), a commonly used recurrent neural network for time-series estimation, neural operators are both more accurate and efficient, especially in situations with limited data availability. Taken together, our study shows that FNO outperforms all other operators for approximating the mapping of one input functional space to the output space as well as for responses that have small bandwidth of the frequency spectrum. Conversely, DeepONet, with historical states, proves most accurate in learning the mapping of multiple input functions to the output space and capturing responses within a broad frequency spectrum.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Performance analysis and comparison of data-driven models for predicting indoor temperature in multi-zone commercial buildings

Building thermal models, which characterize the properties of a building’s envelope and thermal mass, are essential for accurate indoor temperature and cooling/heating demand prediction. Because of their flexibility and ease of use, data-driven models are increasingly used. Here, this study compared and analyzed the performance of gray-box (resistance-capacitance) and black-box (recurrent neural network) models for predicting indoor air temperature in a real multi-zone commercial building. The developed resistance-capacitance model served as a benchmark model for which full sets of temporal data and building information were used as inputs. The recurrent neural network models were trained and tested assuming various available types and amounts of temporal data and known building physical information to investigate the effects of data and information availability. Feature importance analysis was conducted to select the key variables for different prediction targets under different scenarios. This research provides guidance in selecting an appropriate building thermal response modeling method based on the measured data availability, building physical information, and application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

PSTN-019: The LSST Science Pipelines Software: Optical Survey Pipeline Reduction and Analysis Environment

The NSF-DOE Vera C. Rubin Observatory is executing the Legacy Survey of Space and Time (LSST) as its prime mission, producing a series of data releases over the ten-year survey. The LSST Science Pipelines Software will be used to create these data releases and to perform the nightly prompt processing and alert production. This paper provides an overview of the LSST Science Pipelines Software, describing the components and their integration into pipelines that generate science-ready data products.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

Evaluation of Three Constitutive Models for the Prediction of Hastelloy X Elevated Temperature Cyclic Response

The approach for the method development assumes that, for a thermally loaded structure, the overall strain history is defined by linear elastic analysis. The local stress history at a fatigue critical location is then determined from a one dimensional material behavior model and the local strain and temperature conditions. Three material models are currently being evaluated to assess their ability to predict relevant high temperature cyclic material response characteristics. They are: a time independent classical plasticity and creep representation, a time dependent viscoplastic model capable of predicting combined creep and plasticity effects, and an approximate elastic analysis approach that uses a series of stress-strain curves and a cyclic hardening model to determine reverse plasticity.

Moreno, V.↗
NASA NTRS1991

Intraseasonal oscillation of convective activity in the tropical Southern Hemisphere - May 1984-April 1986

This paper studies the intraseasonal oscillation of convection and related variables in the Southern Hemisphere tropics utilizing European Centre for Medium-range Weather Forecasts analyses of 1984 to 1986. One aspect of the research was that the original, unfiltered, time series of various variables was first analyzed to determine if a statistically significant signal occurred on the intraseasonal time scale. The analysis showed that two variables, outgoing longwave radiation and velocity potential at 200 hPa, provided the best evidence of an intraseasonal oscillation. The oscillation propagated eastward, and the convective activity for both years was more intense over the Indian Ocean-Indonesia-western Pacific region than elsewhere.

Vincent, Dayton G.↗
NASA NTRS2015

The Legacy of Episodic Climatic Events in Shaping Temperate, Broadleaf Forests

In humid, broadleaf-dominated forests where gap dynamics and partial canopy mortality appears to dominate the disturbance regime at local scales, paleoecological evidence shows alteration at regional-scales associated with climatic change. Yet, little evidence of these broad-scale events exists in extant forests. To evaluate the potential for the occurrence of large-scale disturbance, we used 76 tree-ring collections spanning approx. 840 000 sq km and 5327 tree recruitment dates spanning approx. 1.4 million sq km across the humid eastern United States. Rotated principal component analysis indicated a common growth pattern of a simultaneous reduction in competition in 22 populations across 61 000 km2. Growth-release analysis of these populations reveals an intense and coherent canopy disturbance from 1775 to 1780, peaking in 1776. The resulting time series of canopy disturbance is so poorly described by a Gaussian distribution that it can be described as ''heavy tailed,'' with most of the years from 1775 to 1780 comprising the heavy-tail portion of the distribution. Historical documents provide no evidence that hurricanes or ice storms triggered the 1775-1780 event. Instead, we identify a significant relationship between prior drought and years with elevated rates of disturbance with an intense drought occurring from 1772 to 1775. We further find that years with high rates of canopy disturbance have a propensity to create larger canopy gaps indicating repeated opportunities for rapid change in species composition beyond the landscape scale. Evidence of elevated, regional-scale disturbance reveals how rare events can potentially alter system trajectory: a substantial portion of old-growth forests examined here originated or were substantially altered more than two centuries ago following events lasting just a few years. Our recruitment data, comprised of at least 21 species and several shade-intolerant species, document a pulse of tree recruitment at the subcontinental scale during the late-1600s suggesting that this event was severe enough to open large canopy gaps. These disturbances and their climatic drivers support the hypothesis that punctuated, episodic, climatic events impart a legacy in broadleaf-dominated forests centuries after their occurrence. Given projections of future drought, these results also reveal the potential for abrupt, meso- to large-scale forest change in broadleaf-dominated forests over future decades.

Climatology↗