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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Principal Component Analysis of Nuclear Cable Insulation Subjected to Elevated Temperature and Gamma Radiation

In nuclear power plants (NPPs), the aging of electrical cable insulation occurs due to elevated temperature, ionizing radiation, and other environmental factors. To ensure the safe and efficient operation of NPPs, determination of key indicators of cable aging is critical to predict the remaining useful lifetime of electrical cable insulation. In this work, the effects of simultaneous and sequential thermal and gamma radiation on the aging of cross-linked polyethylene (XLPE) electrical cable insulation are investigated. The chemical changes of the insulation were monitored non-destructively through the use of Fourier transform infrared (FTIR) spectroscopy. The FTIR spectra were measured stepwise after predetermined exposure intervals, with a total irradiation dose up to 320 kGy at a dose rate of 300 Gy/hr in two exposure scenarios; simultaneously aged samples were heated at 150 °C during irradiation, while sequentially aged samples were heated at 150 °C for designated durations followed by corresponding times of irradiation at ambient temperature. A data-driven approach using principal component analysis (PCA) was developed to highlight changes in the carbonyl region of the infrared spectra of the aged samples due to oxidation and to differentiate oxidation rates under the simultaneous and sequential exposure conditions. Findings indicate that the sequential aging scenario may be more conservative than the simultaneous aging scenario for XLPE electrical cable insulation.

Li, Donghui↗
DOE OSTI2020

Video Summarization Using Deep Action Recognition Features and Robust Principal Components Analysis

In an instance where desired pre-defined actions, behaviors, or other categories are known a priori, various video classification and recognition models can be trained to discover those classifications and their location within the video. Absent that information, one might still be tasked with identifying interesting portions within a video, a process which—if done manually—is onerous and time-consuming as it requires manual inspection of the video itself. Recognizing high-level interesting segments within a whole video has been a general area of interest due to the ubiquity of video data. However the size of the data makes storage, retrieval, and inspection of large collections of videos cumbersome. This problem motivates the task of generating shortened clips highlighting the primary content of a video, relieving the burden of having to watch the entire video. This paper presents an unsupervised method of creating shortened clips of videos, enabling the rapid review of the most interesting content within a video. Our method uses features extracted from pre-trained action recognition models as input to online moving window robust principal component analysis to generate summaries. The procedure is tested on a publicly available video summarization dataset and demonstrates comparable performance to state-of-the-art in an un-augmented setting while requiring no training.

Claborne, Daniel M.↗
DOE OSTI2021

A software package for plasma facing component analysis and design: the Heat flux Engineering Analysis Toolkit (HEAT)

The engineering limits of plasma facing components (PFCs) constrain the allowable operational space of tokamaks. Poorly managed heat fluxes that push the PFCs beyond their limits not only degrade core plasma performance via elevated impurities, but can also result in PFC failure due to thermal stresses or melting. Simple axisymmetric assumptions fail to capture the complex interaction between 3D PFC geometry and 2D or 3D plasmas. This results in fusion systems that must either operate with increased risk or reduce PFC loads, potentially through lower core plasma performance, to maintain a nominal safety factor. High precision 3D heat flux predictions are necessary to accurately ascertain the state of a PFC given the evolution of the magnetic equilibrium. A new code, the Heat flux Engineering Analysis Toolkit (HEAT), has been developed to provide high precision 3D predictions and analysis for PFCs. HEAT couples many otherwise disparate computational tools together into a single open source python package. Magnetic equilibrium, engineering CAD, finite volume solvers, scrape off layer plasma physics, visualization, high performace computing, and more, are connected in a single web-based user interface. Linux users may use HEAT without any software prerequisites via an appImage. This manuscript introduces HEAT, discusses the software architecture, presents first HEAT results, and outlines physics modules in development.

divertor physics↗
DOE OSTI2019

Tectonic tremor characterized by principal-component analysis in the vicinity of central Chile and Argentina

No conclusive evidence has been presented to date for tectonic tremor (TT) in the vicinity of central Chile, where the Nazca Plate is subducting beneath the South American Plate. Subduction in our experimental location (roughly 35.5° S, 70.5° W) is steep and fairly unobstructed compared to the flattened and more seismogenic behavior to the north. We seek to identify TT in our experimental area, whose geodynamics are comparable to tremor-rich subduction zones such as Cascadia and the Nankai Trough. Our method combines time-series visual inspection, frequency-spectrum analysis, waveform cross-correlation, and 3-component (3C) signal covariance to explore the presence of TT in this region. We have identified TT using stations in central Chile and the Malargüe region, Argentina. The TT exhibits similar features to other TT observations worldwide. Waveform characteristics for the TT in our study, particularly dimension of the 3C signal covariance, vary as a function of apparent source location. The duration of one episode of identified TT was about 10 h, which may indicate that the plate interface where tremor generates is strongly coupled. Here, we conclude that our observations reflect features of the local propagation, rather than the tremor source itself.

58 GEOSCIENCES↗
DOE OSTI2025

Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest

ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Spatiotemporal Patterns of Precipitation-Modulated Landslide Deformation From Independent Component Analysis of InSAR Time Series

We present that long-term landslide deformation is disruptive and costly in urbanized environments. We rely on TerraSAR-X satellite images (2009–2014) and an improved data processing algorithm (SqueeSAR™) to produce an exceptionally dense Interferometric Synthetic Aperture Radar ground deformation time series for the San Francisco East Bay Hills. Independent and principal component analyses of the time series reveal four distinct spatial and temporal surface deformation patterns in the area around Blakemont landslide, which we relate to different geomechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore pressure changes controlled by annual seasonal cycles and multiyear drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings. Lastly, high-resolution characterization of landslide response to precipitation is a first step toward improved hazard forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Energy efficiency evaluation of a stationary lithium-ion battery container storage system via electro-thermal modeling and detailed component analysis

Energy efficiency is a key performance indicator for battery storage systems. A detailed electro-thermal model of a stationary lithium-ion battery system is developed and an evaluation of its energy efficiency is conducted. The model offers a holistic approach to calculating conversion losses and auxiliary power consumption. Sub-models for battery rack, power electronics, thermal management as well as the control and monitoring components are developed and coupled to a comprehensive model. The simulation is parametrized based on a prototype 192 kWh system using lithium iron phosphate batteries connected to the low voltage grid. The key loss mechanisms are identified, thoroughly analyzed and modeled. Generic profiles featuring various system operation modes are evaluated to show the characteristics of stationary battery systems. Typically the losses in the power electronics outweigh the losses in the battery at low power operating points. The auxiliary power consumption dominates for low system utilization rates. For estimation of real-world performance, the grid applications Primary Control Reserve, Secondary Control Reserve and the storage of surplus photovoltaic power are evaluated. Conversion round-trip efficiency is in the range of 70-80%. Finally, overall system efficiency, which also considers system power consumption, is 8-13 percentage points lower for Primary Control Reserve and the photovoltaic-battery application. However, for Secondary Control Reserve, the total round-trip efficiency is found to be extremely low at 23% due to the low energy throughput of this application type.

25 ENERGY STORAGE↗
DOE OSTI2018

Component Analysis and Identification of Black Tahitian Cultured Pearls From the Oyster Pinctada margaritifera Using Spectroscopic Techniques

Raman spectroscopy, ultraviolet, visible, and near infrared (UV–Vis–NIR) reflectance spectroscopy, and X-ray fluorescence (XRF) spectroscopy were used to characterize black Tahitian cultured pearls and imitations of these saltwater cultured pearls produced by γ-irradiation, and by coloring of cultured pearls with silver nitrate or organic dyes. Raman spectra indicated that aragonite was the major constituent of these four types of pearl. Using Raman spectroscopy at an excitation wavelength of 514 nm, black Tahitian cultured pearls exhibited characteristic 1100–1700 cm{sup –1} bands. These bands were attributed to various organic components, including conchiolin and other black biological pigments. The peaks shown by saltwater cultured pearls colored with organic dyes varied with the type of dye used. Tahitian cultured and organic-dye-treated saltwater cultured pearls were easily identified by Raman spectroscopy. UV–Vis–NIR reflectance spectra showed bands at 408, 497, and 700 nm derived from porphyrin pigment and other black pigments. The spectra of dye-treated black saltwater pearls showed absorption peaks at 216, 261, 300, and 578 nm. The 261-nm absorption band disappeared from the spectra of γ-irradiated saltwater cultured pearls. This suggests the degradation of conchiolin in the γ-irradiated saltwater cultured pearls. XRF analysis revealed the presence of Ag on the surface of silver nitrate-dyed saltwater cultured pearls.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Uncertainty quantification of an empirical shell-model interaction using principal component analysis

Recent investigations have emphasized the importance of uncertainty quantification (UQ) in nuclear theory. Here, we carry out UQ for configuration-interaction shell-model calculations in the 1$\textit{s}$–0$\textit{d}$ valence space, investigating the sensitivity of observables to perturbations in the 66 parameters (matrix elements) of a high-quality empirical interaction. The large parameter space makes computing the corresponding Hessian numerically costly, so we compare a cost-effective approximation, using the Feynman-Hellmann theorem, to the full Hessian and find it works well. Diagonalizing the Hessian yields the principal components of the interaction: linear combinations of parameters ordered by sensitivity. This approximately decoupled distribution of parameters facilitates theoretical uncertainty propagation onto structure observables: electromagnetic transitions, Gamow-Teller decays, and dark matter-nucleus scattering matrix elements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗