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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

REVISED STELLAR PROPERTIES OF KEPLER TARGETS FOR THE QUARTER 1-16 TRANSIT DETECTION RUN

We present revised properties for 196,468 stars observed by the NASA Kepler mission and used in the analysis of Quarter 1-16 (Q1-Q16) data to detect and characterize transiting planets. The catalog is based on a compilation of literature values for atmospheric properties (temperature, surface gravity, and metallicity) derived from different observational techniques (photometry, spectroscopy, asteroseismology, and exoplanet transits), which were then homogeneously fitted to a grid of Dartmouth stellar isochrones. We use broadband photometry and asteroseismology to characterize 11,532 Kepler targets which were previously unclassified in the Kepler Input Catalog (KIC). We report the detection of oscillations in 2762 of these targets, classifying them as giant stars and increasing the number of known oscillating giant stars observed by Kepler by ∼20% to a total of ∼15,500 stars. Typical uncertainties in derived radii and masses are ∼40% and ∼20%, respectively, for stars with photometric constraints only, and 5%-15% and ∼10% for stars based on spectroscopy and/or asteroseismology, although these uncertainties vary strongly with spectral type and luminosity class. A comparison with the Q1-Q12 catalog shows a systematic decrease in radii of M dwarfs, while radii for K dwarfs decrease or increase depending on the Q1-Q12 provenance (KIC or Yonsei-Yale isochrones). Radii of F-G dwarfs are on average unchanged, with the exception of newly identified giants. The Q1-Q16 star properties catalog is a first step toward an improved characterization of all Kepler targets to support planet-occurrence studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Compact representation and long-time extrapolation of real-time data for quantum systems using the ESPRIT algorithm

Representing real-time data as a sum of complex exponentials provides a compact form that enables both denoising and extrapolation. As a fully data-driven method, the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm is agnostic to the underlying physical equations, making it broadly applicable to various observables and experimental or numerical setups. In this work, we consider applications of the ESPRIT algorithm primarily to extend real-time dynamical data from simulations of quantum systems. We evaluate ESPRIT's performance in the presence of noise and compare it to other extrapolation methods. We demonstrate its ability to extract information from short-time dynamics to reliably predict long-time behavior and determine the minimum time interval required for accurate results. We discuss how this insight can be leveraged in numerical methods that propagate quantum systems in time, and we show how ESPRIT can predict infinite-time values of dynamical observables, offering a purely data-driven approach to characterizing quantum phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Scalable Performance Awareness for In Situ Scientific Applications

Part of the promise of exascale computing and the next generation of scientific simulation codes is the ability to bring together time and spatial scales that have traditionally been treated separately. This enables creating complex coupled simulations and in situ analysis pipelines, encompassing such things as "whole device" fusion models or the simulation of cities from sewers to rooftops. Unfortunately, the HPC analysis tools that have been built up over the preceding decades are ill suited to the debugging and performance analysis of such computational ensembles. In this paper, we present a new vision for performance measurement and understanding of HPC codes, MonitoringAnalytics (MONA). MONA is designed to be a flexible, high performance monitoring infrastructure that can perform monitoring analysis in place or in transit by embedding analytics and characterization directly into the data stream, without relying upon delivering all monitoring information to a central database for post-processing. It addresses the trade-offs between the prohibitively expensive capture of all performance characteristics and not capturing enough to detect the features of interest. We demonstrate several uses of MONA; capturing and indexing multi-executable performance profiles to enable later processing, extraction of performance primitives to enable the generation of customizable benchmarks and performance skeletons, and extracting communication and application behaviors to enable better control and placement for the current and future runs of the science ensemble. Relevant performance information based on a system for MONA built from ADIOS and SOSflow technologies is provided for DOE science applications and leadership machines.

Wolf, Matthew D.↗
DOE OSTI2022

Data-Driven PMU Noise Emulation Framework using Gradient-Penalty-Based Wasserstein GAN

Availability of phasor measurement unit (PMUs) data has led to research on data-driven algorithms for event monitoring, control and ensuring stability of the grid. Unavailability of infrequent critical event field PMU data with component failures is driving the need to generate realistic synthetic PMU data for research. The synthetic data from power system simulation software often neglect noise profiles of received phasors, thus creating some discrepancies between real PMU data and synthetic ones. To address this issue, this work presents an initial study on the noise characteristics of PMUs, as well as presenting models for recreating their unique noise signatures. The proposed method, utilizing the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) architecture, provides an excellent benchmark for matching the noise distribution. One can use a well-learned GAN model to draw noise signatures from a distribution that seemingly mirrors the real PMU noise distribution, while also being able to be detached from the PMU data once the training is done. Based on the observed results and employed data-driven methodology, it is expected that the proposed methods can be adapted to replicate the behavior of other sensors, providing research and other applications with a tool for data synthesis and sensor characterization.

PMU↗
DOE OSTI2018

Assessment of the National Solar Radiation Database (NSRDB 1998-2016)

Applying traceable and standardized uncertainty characterization for solar resource data provides confidence in the dataset for use by financiers, developers and site operators of solar energy conversion systems, and ultimately reduces deployment cost. Performance guarantees of solar energy conversion systems are based on the available solar resource from measurement stations or modeled dataset such as the National Solar Radiation Database (NSRDB). In this study we implemented a comprehensive uncertainty determination approach [1]. The study also analyzed how the NSRDB (19982016) - Version 3 compares with the previous NSRDB (19982015) - Version 2. The study also attempted to estimate the uncertainty differences derived by comparing theNSRDB data to the seven measurement stations from the National Oceanic and Atmospheric Administration's Surface Radiation Budget Network (SURFRAD) and University of Oregon Solar Radiation Monitoring Laboratory (SRML). The evaluation was conducted for hourly values, daily totals, monthly mean daily totals, and annual mean monthly mean daily totals and demonstrate the qualityof the new datasets currently available from the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2015

Spectral and Spatial Classification of Hyperspectral Images Based on ICA and Reduced Morphological Attribute Profiles

The availability of hyperspectral images with improved spectral and spatial resolutions provides the opportunity to obtain accurate land-cover classification. In this paper, a novel methodology that combines spectral and spatial information for supervised hyperspectral image classification is proposed. A feature reduction strategy based on independent component analysis is the main core of the spectral analysis, where the exploitation of prior information coupled to the evaluation of the reconstruction error assures the identification of the best class-informative subset of independent components. Reduced attribute profiles (APs), which are designed to address well-known issues related to information redundancy that affect the common morphological APs, are then employed for the modeling and fusion of the contextual information. Four real hyperspectral data sets, which are characterized by different spectral and spatial resolutions with a variety of scene typologies (urban, agriculture areas), have been used for assessing the accuracy and generalization capabilities of the proposed methodology. The obtained results demonstrate the classification effectiveness of the proposed approach in all different scene typologies, with respect to other state-of-the-art techniques.

42 ENGINEERING↗
DOE OSTI2017

A Comprehensive Set of Impact Data for Common Aerospace Metals

Our results for the two sets of impact experiments are reported here. In order to assist with model development using the impact data reported, the materials are mechanically characterized using a series of standard experiments. The first set of impact data comes from a series of coefficient of restitution experiments, in which a 2 meter long pendulum is used to study "in context" measurements of the coefficient of restitution for eight different materials (6061-T6 Aluminum, Phosphor Bronze alloy 510, Hiperco, Nitronic 60A, Stainless Steel 304, Titanium, Copper, and Annealed Copper). The coefficient of restitution is measured via two different techniques: digital image correlation and laser Doppler vibrometry. Due to the strong agreement of the two different methods, only results from the digital image correlation are reported. The coefficient of restitution experiments are "in context" as the scales of the geometry and impact velocities are representative of common features in the motivating application for this research. Finally, a series of compliance measurements are detailed for the same set of materials. Furthermore, the compliance measurements are conducted using both nano-indentation and micro-indentation machines, providing sub-nm displacement resolution and uN force resolution. Good agreement is seen for load levels spanned by both machines. As the transition from elastic to plastic behavior occurs at contact displacements on the order of 30 nm, this data set provides a unique insight into the transitionary region.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine-learning-assisted analysis of transition metal dichalcogenide thin-film growth

In situ reflective high-energy electron diffraction (RHEED) is widely used to monitor the surface crystalline state during thin-film growth by molecular beam epitaxy (MBE) and pulsed laser deposition. With the recent development of machine learning (ML), ML-assisted analysis of RHEED videos aids in interpreting the complete RHEED data of oxide thin films. The quantitative analysis of RHEED data allows us to characterize and categorize the growth modes step by step, and extract hidden knowledge of the epitaxial film growth process. In this study, we employed the ML-assisted RHEED analysis method to investigate the growth of 2D thin films of transition metal dichalcogenides (ReSe2) on graphene substrates by MBE. Principal component analysis (PCA) and K-means clustering were used to separate statistically important patterns and visualize the trend of pattern evolution without any notable loss of information. Using the modified PCA, we could monitor the diffraction intensity of solely the ReSe2 layers by filtering out the substrate contribution. These findings demonstrate that ML analysis can be successfully employed to examine and understand the film-growth dynamics of 2D materials. Further, the ML-based method can pave the way for the development of advanced real-time monitoring and autonomous material synthesis techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhanced Attenuation of Uranium in the Subsurface

Over time, the focus for the Hanford Site has moved from production to decommissioning and site remediation. Several hundred metric tons of near-surface vadose zone sediment have been excavated from the 300 Area in an effort to remove the source of the uranium contamination (DOE/RL, 2011). Despite remediation efforts, uranium continues to be problematic with concentrations greater than the maximum contaminant level (MCL, which is 30 µg/L) for drinking water. Due to the close proximity of the Columbia River, the uranium continues to be a focus of investigation and remediation. After finding that the uranium concentrations were not decreasing as quickly as expected (based on the 1996 ROD) the Tri-Parties set new milestones, including an update of the conceptual model for the 300 Area uranium plume (Williams et al., 2007). In order to more accurately complete a feasibility study and identify how to remediate the uranium in the groundwater, the DOE authorized a remedial investigation/feasibility study (RI/FS). RI/FSs are designed to screen technologies to determine effectiveness, implementability, and cost (see Chapter 2b). These studies are designed to be conducted concurrently as part of the CERCLA process, so the data collected during site characterization (part of the RI) can inform the treatability studies and field tests conducted under the FS (EPA 1988). For the 300 Area, this study included laboratory, field, and modeling components as well as additional sediment and groundwater characterization to determine a suitable remediation strategy to reduce the uranium concentration in the groundwater plume within the expected time frame and cost.

300 area, uranium, polyphosphate, Hanford book pro↗
DOE OSTI2016

Utah FORGE: Groundwater Data

This submission includes two modeled drawdown scenarios with new supply well locations, a total dissolved solids (TDS) concentration grid (raster dataset representing the spatial distribution of TDS), and an excel spreadsheet containing well data.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Deep Direct-Use Feasibility Study Numerical Modeling and Uncertainty Analysis using iTOUGH2 for West Virginia University

To reduce the geothermal exploration risk, a feasibility study is performed for a deep direct-use system proposed at the West Virginia University (WVU) Morgantown campus. This study applies numerical simulations to investigate reservoir impedance and thermal production. Because of the great depth of the geothermal reservoir, few data are available to characterize reservoir features and properties. As a result, the study focuses on the following three aspects: 1. model choice for predicting reservoir impedance and thermal breakthrough: after investigating three potential models (one single permeability model and two dual permeability models) for flow through fractured rock, it is decided to use single permeability model for further analysis; 2. well placement (horizontal vs. vertical) options: horizontal well placement seems to be more robust to heterogeneity and the impedance is more acceptable; 3. Prediction uncertainty: the most influential parameters are identified using a First-Order-Second-Moment uncertainty propagation analysis, and the uncertain range of the model predictions is estimated by performing a Monte Carlo simulation. Heterogeneity has a large impact on the perdition, therefore, is considered in the predictive model and uncertainty analysis. The numerical model results and uncertainty analysis are used for economic analysis. The dataset submitted here support the described study. Manuscript is submitted to Geothermics, will be linked once paper is accepted.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

VULCAN: A “hammer” for high-temperature materials research

Understanding changes in chemistry, microstructure, and physical properties during synthesis, processing, testing, and even service is vital for materials design and performance. Compared to traditional postmortem material characterization tools, in situ crystallographic characterization can provide considerable data and information on evolution of chemistry, dislocations, twinning, texture, and strains when a material is under external stimuli. Neutrons especially are able to probe material bulk properties and behaviors in extreme environments, thanks to their deep penetrating power and unique sensitivity to differentiate elements from lightweight to transition-metal atoms. In this article, we introduce and describe a diffractometer named VULCAN, which is located at Oak Ridge National Laboratory. Finally, this represents a powerful tool to understand materials properties and behaviors under complex environments, in particular, at high temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

RokBase - Beta

Web based tool and portal to explore and download data associated with Core Characterization Technical Report Series .

Core Characterization↗
DOE OSTI2015

High Temperature Transducers for Online Monitoring of Microstructure Evolution

A critical technology gap exists relative to online condition monitoring (CM) of advanced nuclear plant components for damage accumulation; there are not capable sensors and infrastructure available for the high temperature environment. The sensory system, monitoring methodology, data acquisition, and damage characterization algorithm that comprise a CM system are investigated here. Thus this work supports the DOE mission to develop a fundamental understanding of advanced sensors to improve physical measurement accuracy and reduce uncertainty. The research involves a concept viability assessment, a detailed technology gap analysis, and a technology development roadmap.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Irradiation Assisted Stress Corrosion Cracking of Austenitic Stainless Steel in BWR Conditions

As a first step toward full scale utilization of the Advanced Test Reactor (ATR) and associated post irradiation examination (PIE) equipment at INL, the NRC and INL staffs have formulated a test program that is designed to help to establish INL and the Nuclear Science User Facilities (NSUF) as a viable destination for irradiation and PIE of reactor structural materials. This initial research program utilized two materials (304 Stainless Steel weld Heat Affected Zone (HAZ) and sensitized 304L stainless steel) that have previously been irradiated at the Halden reactor in Norway and tested at Argonne National Laboratory (ANL) so that test results may be compared, thereby establishing a measure of comparability between Halden and ATR irradiations. A secondary objective of this test program was to characterize the quality of data produced using INL’s newly constructed irradiation assisted stress corrosion cracking (IASCC) test cells. The specimens were be tested in typical boiling water reactor (BWR) conditions to measure stress corrosion cracking (SCC) and fracture toughness of un-irradiated specimens and then IASCC and fracture toughness of specimens irradiated to a fluence equal to approximately 1.0 X 10 21 n/cm 2 (E > 1 MeV).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Deep Borehole Laboratory and Borehole Testing Strategy: Generic Drilling and Testing Plan

This report presents a generic (i.e., site-independent) preliminary plan for drilling, testing, sampling, and analyzing data for a deep characterization borehole drilled into crystalline basement for the purposes of assessing the suitability of a site for deep borehole disposal (DBD). This research was performed as part of the deep borehole field test (DBFT). Based on revised U.S. Department of Energy (DOE) priorities in mid-2017, the DBFT and other research related to a DBD option was discontinued; ongoing work and documentation were closed out by the end of fiscal year (FY) 2017. This report was initiated as part of the DBFT and documented as an incomplete draft at the end of FY 2017. The report was finalized by Sandia National Laboratories in FY2018 without DOE funding, subsequent to the termination of the DBFT, and published in FY2019. This report presents a possible sampling, testing, and analysis campaign that could be carried out as part of a future project to quantify geochemical, geomechanical, geothermal, and geohydrologic conditions encountered at depths up to 5 km in crystalline basement.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Making Coal Relevant for Small Scale Applications: Modular Gasification for Syngas/Engine CHP Applications in Challenging Environments

This Front-End Engineering Design (FEED) study is funded by the US Department of Energy (DOE), and managed by the National Energy Technology Laboratory (NETL) through a Cooperative Agreement awarded to the University of Alaska Fairbanks (UAF) to perform a technical and cost study for the design and installation of a Hamilton-Maurer International (HMI) gasifier for generating a clean syngas for firing in reciprocating engines. An existing diesel engine generator (DEG) and a commercially available spark ignition engine are used to generate electricity with the low-Btu syngas. Other than the HMI gasifier, only commercially available technologies were assumed for this study. An important objective of this design study was to estimate capital and operating costs of small modular coal and coal/biomass fired generating units to provide wind regulation services. Although this study is based on retrofitting an existing coal fired power plant with the HMI gasifier, sufficient data was developed to characterize greenfield units. The original concept was to provide clean syngas and tars/oils from the gasification process to the existing Colt-Pielstick PC2.6B diesel engine generator (9.6 MWe) installed at the UAF Atkinson Power Plant. The intent was to convert the diesel engine to operate in a dual fuel mode, firing both syngas and tars/oils. As the project progressed, Fairbanks Morse Engine (FME), current licensee for the Colt-Pielstick engine line, was not able to develop a modification package for the engine to allow for syngas firing. Although this type of modification is available for firing natural gas, the capability does not extend to syngas. Western Energy Systems, distributor for Innio Jenbacher, was able to offer the Jenbacher Model JMS620 engine. After review of available options, the project team selected a design configuration using two Jenbacher engines rated at 1965 kWe each to fire the syngas, with the oils/tars directed to the Colt Pielstick diesel to be blended with ultra-low sulfur diesel oil (ULSD). The Jenbacher engines are expected to operate at continuous base load, with some load-following ability, while the existing diesel engine will operate in grid support service, with loads varying from a nominal 25% to 100%. An annual capacity factor for the diesel engine is projected to be between 50% and 60%. The overall gasifier and gas clean-up system is sized to produce enough syngas to adequately fuel three Jenbacher Engines for a nominal power output of 5.9 MWe, but this study assumes that only two Jenbacher engines will be installed due to space constraints in the Atkinson Power Plant, and because of expected air emission permit limitations. There is still potential that the excess syngas capacity equivalent to about 2 MWe could be used as supplemental fuel for the DEG. The exhaust from the Jenbacher engines is passed through heat recovery units to generate low pressure steam, thereby providing a significant portion of the steam required for operating the gasifier. The overall performance of the HMI gasifier/engine configuration is summarized as follows: 1) Overall electric efficiency, Jenbacher and diesel engines, based on gasifier fuel production (syngas and pyrolysis liquids) is 35.2% LHV, 2) Overall cogenerating efficiency (electricity plus steam), based on gasifier fuel production (syngas and pyrolysis liquids) is 54.8% LHV, 3) Overall electric efficiency, Jenbacher and diesel engines, based on coal input, is 29.6% LHV, and 4) Overall cogenerating efficiency, electricity plus steam, based on coal input is 46.0%. This project is estimated to have a Bare Erected Cost (BEC) of $\$$ 33.4 million and a Total Plant Cost (TPC) of $\$$ 45.7 million. Based on the original scope, sending both the clean syngas and the oils and tars to the existing diesel engine, the BEC and TPC values would have been $\$$ 23.3 million and $\$$ 32.1 million, respectively. A variable Cost of Electricity (COE) is calculated to reflect only those costs that will be incurred by incremental operation of the system for the HMI gasifier/Jenbacher engine combination. Operation of the diesel engine is determined separately. The variable COE values are: Case 1: 100% Usibelli Coal: (a) HMI gasifier/Jenbacher Engines -- 8.3 cents/kWh; (b) Diesel Engine -- 20.2 cents/kWh, and Case 2: 80% Usibelli Coal + 20% wood chips (proportion based on Btu input, LHV basis): (a) HMI Gasifier/Jenbacher -- 13.7 cents/kWh; (b) Diesel Engine -- 20.2 cents/kWh. The incremental cost of operating the gasifier/Jenbacher system increases with co-firing of wood chips due to the high cost of this material, over five times as costly as Usibelli coal delivered to the Atkinson Power building. The diesel cost is constant as the oils and tars are priced at the same value as the ULSD for the purposes of fueling the diesel engine. Section 8 of this report provides details of the O&M costs. The overall power system is configured to be modular and scalable to provide a wide range of generating capacity using the same components. This allows for reduction in cost, risk, schedule time to engineer and construct, and provides some degree of repeatability for air permitting.

01 COAL, LIGNITE, AND PEAT↗