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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
DOE OSTI2015

GALAXY EVOLUTION IN THE MID-INFRARED GREEN VALLEY: A CASE OF THE A2199 SUPERCLUSTER

We study the mid-infrared (MIR) properties of the galaxies in the A2199 supercluster at z = 0.03 to understand the star formation activity of galaxy groups and clusters in the supercluster environment. Using the Wide-field Infrared Survey Explorer data, we find no dependence of mass-normalized integrated star formation rates of galaxy groups/clusters on their virial masses. We classify the supercluster galaxies into three classes in the MIR color-luminosity diagram: MIR blue cloud (massive, quiescent, and mostly early-type), MIR star-forming sequence (mostly late-type), and MIR green valley galaxies. These MIR green valley galaxies are distinguishable from the optical green valley galaxies in the sense that they belong to the optical red sequence. We find that the fraction of each MIR class does not depend on the virial mass of each group/cluster. We compare the cumulative distributions of surface galaxy number density and cluster/group-centric distance for the three MIR classes. MIR green valley galaxies show the distribution between MIR blue cloud and MIR star-forming (SF) sequence galaxies. However, if we fix galaxy morphology, early- and late-type MIR green valley galaxies show different distributions. Our results suggest a possible evolutionary scenario of these galaxies: (1) late-type MIR SF sequence galaxies → (2) late-type MIR green valley galaxies → (3) early-type MIR green valley galaxies → (4) early-type MIR blue cloud galaxies. In this sequence, the star formation of galaxies is quenched before the galaxies enter the MIR green valley, and then morphological transformation occurs in the MIR green valley.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Topographic Correction of Optical Remote Sensing Images in Mountainous Areas: A systematic review

Rugged terrain distorts optical remote sensing observations and subsequently impacts land cover classification and biophysical and biochemical parameter retrieval over mountainous areas. Therefore, topographic correction (TC) is a prerequisite for many remote sensing applications. Although various TC methods have been explored over the past four decades to mitigate topographic effects, a systematic and global review of these studies is still lacking. Using a multicomponent bibliometric approach, we extracted bibliometric metadata from 426 publications identified by searching titles, keywords, and abstracts for research on “topographic correction” and “topographic effects” in Scopus and Web of Science (WoS) from 1980 to 2022. Here this systematic review revealed a rapid growth in the number of TC studies since the 1980s, primarily driven by the availability of decametric-resolution remote sensing observations and digital elevation models (DEMs). Most of the research has focused on relatively low-elevation regions, with increasing attention beyond American and European regions, particularly in China. The seasonal distribution of satellite acquisition for TC showed considerable imbalance, mainly concentrated in months with favorable solar illumination conditions (e.g., May to October). Important themes emerged from the keyword analysis, including satellite sensors, DEMs, TC methods, evaluation criteria, and applications.

58 GEOSCIENCES↗
DOE OSTI2018

Rattlesnake Theory Manual

Rattlesnake is the MOOSE [1, 2] (Multiphysics Object-Oriented Simulation Environment) based application for simulating the physics of radiation transport. Radiation transport studies the motion of particles, usually neutrons, photons or electrons, etc. and their interactions with background materials [3, 4, 5, 6, 7, 8]. The fundamental quantity of interest in radiation transport is the statistically averaged radiation distribution or flux in space (dimentionality 3), time (1), direction of motion (2) and energy (or frequency) (1), forming a seven-dimensional phase space. Various reaction rates are secondary in the sense that they are computed from the primary flux and the background material properties; however, reaction rates are typically more interesting for the analyst or when coupling to other physics, e.g. heat conduction or thermo-hydraulics. Radiation transport calculations receive feedback within a multiphysics environment through temperature and density changes, which predominantly change how radiation particles interact with the background nuclei. Accurate prediction of the flux is essential to the design and operation of nuclear facilities for the purpose of safety and economics. For example in nuclear fission reactors, neutron-induced fissions and the accumulated radiative isotopes are the main heat source. Predicting whether the heat can be removed from the reactor core under all circumstances without violation of safety limits is critical to the safety of nuclear reactors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations

Cloud condensation nuclei (CCN) are mediators of aerosol–cloud interactions (ACIs), contributing to the largest uncertainties in the understandings of global climate change. We present a novel remote-sensing-based algorithm that quantifies the vertically resolved CCN number concentrations (N CCN ) using aerosol optical properties measured by a multiwavelength lidar. The algorithm considers five distinct aerosol subtypes with bimodal size distributions. The inversion used the lookup tables developed in this study, based on the observations from the Aerosol Robotic Network, to efficiently retrieve optimal particle size distributions from lidar measurements. The method derives dry aerosol optical properties by implementing hygroscopic enhancement factors in lidar measurements. The retrieved optically equivalent particle size distributions and aerosol-type-dependent particle composition are utilized to calculate critical diameters using κ-Köhler theory and N CCN at six supersaturations ranging from 0.07 % to 1.0 %. Sensitivity analyses indicate that uncertainties in extinction coefficients and relative humidity greatly influence the retrieval error in N CCN . The potential of this algorithm is further evaluated by retrieving N CCN using airborne lidar from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and is validated against simultaneous measurements from the CCN counter. The independent validation with robust correlation demonstrates promising results. Furthermore, the N CCN has been retrieved for the first time using a proposed algorithm from spaceborne lidar – Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) – measurements. The application of this new capability demonstrates the potential for constructing a 3D CCN climatology at a global scale, which helps to better quantify ACI effects and thus reduce the uncertainty in aerosol climate forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Quantum sensing effect of electron tunneling in DQD/analyte complex

We investigate electron tunneling between quantum dots and molecules to propose a quantum sensor. This sensor consists of double quantum dots (DQD) with energy levels specifically tailored to mirror those of the target analyte. By analyzing the spectral distribution of electron localizations in the DQD system, we can delineate the analyte’s spectrum and deduce its composition by comparing it with a reference sample. To understand electron tunneling dynamics within the DQD/analyte complex, we performed three-dimensional computational modeling applying the effective potential approach to the InAs/GaAs heterostructure. In this modeling, we mimicked the analyte spectrum by utilizing a quantum well characterized by a quasi-discrete spectrum. Our calculations reveal the inherent potential of utilizing this method as a highly sensitive and selective sensor.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Modeling Building Use and Population Distribution Opportunity Using Open Geosocial Data in Urban Areas

Knowing where people are and knowing how the land in urban areas is being used is critical for assessing human mobility patterns, monitoring population health, planning for transportation services, and responding to natural disasters and emergency situations. While geophysical phenomena like land cover are more easily observed through remote sensing, social phenomena like how a city block or building is being used by the population is generally unobservable through standard remote sensing practices. Current methods and land use data by their nature are also difficult to scale to national or global levels. While land use data are often available in large cities, there are abundant data gaps globally. Furthermore, land use data can often appear relatively coarse in its spatial and semantic resolution (i.e. 1km grid cells rather than building level, and "commercial" rather than "coffee shop"). In particular, there is a need to harvest scalable data and develop methods to create global land use maps. To this end, in this work we combine building footprints and Points of Interest (POI) to estimate land use at the building level, including its mixed-use intensity. Next, we propose a method for defining semantic temporal zones referring to Morning, Day, Evening, and Night times unique to a region, based on the cumulative hourly change in the POIs' hours of operation. We then use these POIs' hours of operation to estimate non-residential population distribution opportunity and land use change over a 24-hour period. We validate our results through manual checks of randomly sampled individual buildings using multiple sources. Finally, we discuss the impact of our results on identifying population distribution opportunity and the reliability of estimating building use.

Sparks, Kevin↗
DOE OSTI2016

Stem Inc. SunShot Incubator Program Final Technical Report

In this Energy Storage Control Algorithms project, Stem sought to develop tools and control algorithms to increase the value and reduce balance-of-system and grid integration costs associated with adding distributed solar generation to the grid. These advances fell under the headings SolarScope and SolarController. Stem sought to create initial market traction with a fully commercialized product for the solar industry to size storage systems (SolarScope) as well as a solar intermittency-mitigation framework for utilities (SolarController) in the course of the project. The company sought to align strategic growth plans and enable the rollout of the products to broader audiences in multiple geographic regions by leveraging the major solar companies in the national market as partners. Both final products were both intended to be commercialized. They are: SolarScope: Analysis tool to identify viable PV + storage projects and thereby expedite the sales and interconnection processes. SolarScope combines customer load data, PV production estimates, utility rate tariff, and simulated storage into a simple user interface for PV developers. Developers can easily identify viable solar + storage sites without the need for complex and time consuming, site-by-site spreadsheet modeling. SolarContoller: Tool to autonomously dispatch distributed storage in order to mitigate voltage fluctuation and reduce curtailment. SolarController co-optimizes, in real time, storage dispatch for circuit stability and curtailment reduction, enabling higher penetrations of PV. SolarController is automated, not requiring utility dispatch or management, as Stem hardware senses grid voltage, frequency, customer load, PV production, and power factor. In the end the two products met with different outcomes. SolarScope was tested by potential users, and continues to be used as a foundational platform for partnership with key solar industry partners. SolarController, on the other hand, was successful in lab testing but was not commercialized due to a lack of marketability and lack of interested customer base. Together the development of these two products marked a material step forward for Stem; and a new milestone along the pathway of integration for the solar and storage industries. SolarScope is leading to real, out-of-the-lab project development in storage + solar for the commercial customer sector. Meanwhile SolarController has opened the eyes of regulators and utility executives alike to the potential of distributed solar and by doing so, has moved the conversation forward for the integration of distributed energy resources more broadly on the grid.

25 ENERGY STORAGE↗
DOE OSTI2013

On-Ramp Wireless: Program Final Report

The objective of the project was to develop and demonstrate a centrally managed, wide area wireless distribution grid sensor and faulted circuit indicator system capable of monitoring underground and other hard-to-reach distribution circuits while delivering the reliability, ease of installation, security, battery life and low cost structure required to be a commercially viable product for the electric utility industry. This integrated wireless grid monitoring system enables utilities across the United States to enhance the reliability of their distribution grids, improve performance metrics (i.e., SAIFI, CAIDI, SAIDI), support dynamic load management and predictive maintenance, and enable future remote monitoring applications necessary to achieve the goals of the Smart Grid. This project scope included: conceptual design; trade studies focused on maximizing ease of installation, sensing capabilities, power budget analysis to reduce maintenance costs and time to replace; sensor product development; and field technology demonstration. The trade studies included Radio Frequency (RF) propagation. The RF Trade Study was completed for the 2.4 GHz ISM-band and not extended to 1 GHz band due to availability of suitable radio solutions and associated impacts to overall commercial value of the solution. The technology demonstrations/field trials were performed in partnership with Southern California Edison and San Diego Gas and Electric. The sensing systems included fault indicator and wireless analog sensor devices from Schweitzer Engineering Labs (SEL) and smart transformer monitoring devices from Gridsense. Both SEL and Gridsense worked with ORW during this project to During the demonstration phase, sensors were deployed in multiple locations. Resulting data was analyzed for the following: RF performance, communication systems reliability, sensor system capabilities, and system level analytics relative to the commercial value to the smart grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2010

Pb Isotopes as an Indicator of the Asian Contribution to Particulate Air Pollution in Urban California

During the last two decades, expanding industrial activity in east Asia has led to increased production of airborne pollutants that can be transported to North America. Previous efforts to detect this trans-Pacific pollution have relied upon remote sensing and remote sample locations. We tested whether Pb isotope ratios in airborne particles can be used to directly evaluate the Asian contribution to airborne particles of anthropogenic origin in western North America, using a time series of samples from a pair of sites upwind and downwind of the San Francisco Bay Area. Our results for airborne Pb at these sites indicate a median value of 29 Asian origin, based on mixing relations between distinct regional sample groups. This trans-Pacific Pb is present in small quantities but serves as a tracer for airborne particles within the growing Asian industrial plume. We then applied this analysis to archived samples from urban sites in central California. Taken together, our results suggest that the analysis of Pb isotopes can reveal the distribution of airborne particles affected by Asian industrial pollution at urban sites in northern California. Under suitable circumstances, this analysis can improve understanding of the global transport of pollution, independent of transport models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Battery management system with distributed wireless sensors

A system for monitoring parameters of an energy storage system having a multiplicity of individual energy storage cells. A radio frequency identification and sensor unit is connected to each of the individual energy storage cells. The radio frequency identification and sensor unit operates to sense the parameter of each individual energy storage cell and provides radio frequency transmission of the parameters of each individual energy storage cell. A management system monitors the radio frequency transmissions from the radio frequency identification and sensor units for monitoring the parameters of the energy storage system.

25 ENERGY STORAGE↗
DOE OSTI2010

Reference priors for high energy physics

Bayesian inferences in high energy physics often use uniform prior distributions for parameters about which little or no information is available before data are collected. The resulting posterior distributions are therefore sensitive to the choice of parametrization for the problem and may even be improper if this choice is not carefully considered. Here we describe an extensively tested methodology, known as reference analysis, which allows one to construct parametrization-invariant priors that embody the notion of minimal informativeness in a mathematically well-defined sense. We apply this methodology to general cross section measurements and show that it yields sensible results. A recent measurement of the single-top quark cross section illustrates the relevant techniques in a realistic situation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Reflective ghost imaging through turbulence

Recent work has indicated that ghost imaging may have applications in standoff sensing. However, most theoretical work has addressed transmission-based ghost imaging. To be a viable remote-sensing system, the ghost imager needs to image rough-surfaced targets in reflection through long, turbulent optical paths. We develop, within a Gaussian-state framework, expressions for the spatial resolution, image contrast, and signal-to-noise ratio of such a system. We consider rough-surfaced targets that create fully developed speckle in their returns and Kolmogorov-spectrum turbulence that is uniformly distributed along all propagation paths. We address both classical and nonclassical optical sources, as well as a computational ghost imager.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Validation and Calibration of Nuclear Thermal Hydraulics Multiscale Multiphysics Models - Subcooled Flow Boiling Study

In addition to validation data plan, development of advanced techniques for calibration and validation of complex multiscale, multiphysics nuclear reactor simulation codes are a main objective of the CASL VUQ plan. Advanced modeling of LWR systems normally involves a range of physico-chemical models describing multiple interacting phenomena, such as thermal hydraulics, reactor physics, coolant chemistry, etc., which occur over a wide range of spatial and temporal scales. To a large extent, the accuracy of (and uncertainty in) overall model predictions is determined by the correctness of various sub-models, which are not conservation-laws based, but empirically derived from measurement data. Such sub-models normally require extensive calibration before the models can be applied to analysis of real reactor problems. This work demonstrates a case study of calibration of a common model of subcooled flow boiling, which is an important multiscale, multiphysics phenomenon in LWR thermal hydraulics. The calibration process is based on a new strategy of model-data integration, in which, all sub-models are simultaneously analyzed and calibrated using multiple sets of data of different types. Specifically, both data on large-scale distributions of void fraction and fluid temperature and data on small-scale physics of wall evaporation were simultaneously used in this work’s calibration. In a departure from traditional (or common-sense) practice of tuning/calibrating complex models, a modern calibration technique based on statistical modeling and Bayesian inference was employed, which allowed simultaneous calibration of multiple sub-models (and related parameters) using different datasets. Quality of data (relevancy, scalability, and uncertainty) could be taken into consideration in the calibration process. This work presents a step forward in the development and realization of the “CIPS Validation Data Plan” at the Consortium for Advanced Simulation of LWRs to enable quantitative assessment of the CASL modeling of Crud-Induced Power Shift (CIPS) phenomenon, in particular, and the CASL advanced predictive capabilities, in general. This report is prepared for the Department of Energy’s Consortium for Advanced Simulation of LWRs program’s VUQ Focus Area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Distributed Fiber Optic Sensor for On-Line Monitoring of Coal Gasifier Refractory Health

This report summarizes technical progress on the program “Distributed Fiber Optic Sensor for On-Line Monitoring of Coal Gasifier Refractory Health,” funded by the National Energy Technology Laboratory of the U.S. Department of Energy, and performed by the Center for Photonics Technology of the Bradley Department of Electrical and Computer Engineering at Virginia Tech. The scope of work entails analyses of traveling grating generation technologies in an optical fiber, as well as the interrogation of the gratings to infer a distributed temperature along the fiber, for the purpose of developing a real-time refractory health condition monitoring technology for coal gasifiers. During the project period, which is from 2011-2015, three different sensing principles were studied, including four-wave mixing (FWM), coherent optical time-domain reflectometer (C-OTDR) and Brillouin optical time-domain analysis (BOTDA). By comparing the three methods, the BOTDA was selected for further development into a complete bench-top sensing system for the proposed high-temperature sensing application. Based on the input from Eastman Chemical, the industrial collaborator on this project, a cylindrical furnace was designed and constructed to simulate typical gasifier refractory temperature conditions in the laboratory, and verify the sensor’s capability to fully monitor refractory conditions on the back-side at temperatures up to 1000°C. In the later stages of the project, the sensing system was tested in the simulated environment for its sensing performance and high-temperature survivability. Through theoretical analyses and experimental research on the different factors affecting the sensor performance, a sensor field deployment strategy was proposed for possible future sensor field implementations.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Limitations of Bin and Bulk Microphysics in Reproducing the Observed Spatial Structure of Light Precipitation

Abstract Coarse-gridded atmospheric models often account for subgrid-scale variability by specifying probability distribution functions (PDFs) of process rate inputs such as cloud and rainwater mixing ratios ( q c and q r , respectively). PDF parameters can be obtained from numerous sources: in situ observations, ground- or space-based remote sensing, or fine-scale modeling such as large-eddy simulation (LES). LES is appealing to constrain PDFs because it generates large sample sizes, can simulate a variety of cloud regimes/case studies, and is not subject to the ambiguities of observations. However, despite the appeal of using model output for parameterization development, it has not been demonstrated that LES satisfactorily reproduces the observed spatial structure of microphysical fields. In this study, the structure of observed and modeled microphysical fields are compared by applying bifractal analysis, an approach that quantifies variability across spatial scales, to simulations of a drizzling stratocumulus field that span a range of domain sizes, drop concentrations (a proxy for mesoscale organization), and microphysics schemes (bulk and bin). Simulated q c closely matches observed estimates of bifractal parameters that measure smoothness and intermittency. There are major discrepancies between observed and simulated q r properties, though, with bulk simulated q r consistently displaying the bifractal properties of observed clouds (smooth, minimally intermittent) rather than rain while bin simulations produce q r that is appropriately intermittent but too smooth. These results suggest fundamental limitations of bulk and bin schemes to realistically represent higher-order statistics of the observed rain structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Assessing chromophoric dissolved organic matter (CDOM) distribution, stocks, and fluxes in Apalachicola Bay using combined field, VIIRS ocean color, and model observations

Understanding the role of estuarine-carbon fluxes is essential to improve estimates of the global carbon budget. Dissolved organic matter (DOM) plays an important role in aquatic carbon cycling. Here, the chromophoric fraction of DOM (CDOM) can be readily detected via in situ and remotely-sensed optical measurements. DOM properties, including CDOM absorption coefficient at 412 nm (a g 412) and dissolved organic carbon (DOC) concentrations were examined in Apalachicola Bay, a national estuarine research reserve located in the northeast Gulf of Mexico, using in situ and satellite observations during the spring and fall of 2015. Synoptic and accurate representation of estuarine-scale processes using satellite ocean color imagery necessitates the removal of atmospheric contribu- tion (~90%) to signals received by satellite sensors to successfully link to in situ observations. Three atmospheric correction schemes (e.g., Standard NIR correction, Iterative NIR correction, and SWIR correction) were tested first to find a suitable correction scheme for the VIIRS imagery in low to moderately turbid Apalachicola Bay. The iterative NIR correction performed well, and validation showed high correlation (R 2 = 0.95, N = 25) against in situ light measurements. A VIIRS-based CDOM algorithm was developed (R 2 = 0.87, N = 9) and validated (R 2 = 0.76, N = 20, RMSE = 0.29 m -1 ) against in situ observations. Subsequently, ag412 was used as a proxy of DOC in March (DOC = 1.08 + 0.94 × a g 412,R 2 =0.88, N = 13)and in November (DOC= 1.61 + 1.33 × a g 412, R 2 = 0.83, N = 24) to derive DOC maps that provided synoptic views of DOC distribution, sources, and their transport to the coastal waters during the wet and dry seasons. The estimated DOC stocks were ~3.71 × 10 6 kg C in March and ~4.07 × 10 6 kg C in November over an area of ~560 km2. Volume flux (out of the bay) almost doubled for March 24 (735 m 3 s -1 ) relative to November 4 (378 m 3 s -1 ). However, estimates of DOC fluxes exported out of the bay from model-derived currents and satellite-derived DOC were only marginally greater in March (0.163 × 10 6 kg C d -1 ) than in November (0.124 × 10 6 kg C d -1 ) and reflected greater DOC stocks in the fall. Finally, the combination of satellite-, field-, and model-based observations revealed the strong linkage between the Apalachicola River plume, a major source of DOM, and the overall hydrodynamic forcing that controlled distributions of CDOM abundance, DOC concentration, stocks, and fluxes in the bay.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Network-Cognizant Design of Decentralized Volt/VAR Controllers

This paper considers the problem of designing decentralized Volt/VAR controllers for distributed energy resources (DERs). The voltage-reactive power characteristics of individual DERs are obtained by solving a convex optimization problem, where given performance objectives (e.g., minimization of the voltage deviations from a given profile) are specified and stability constraints are enforced. The resultant Volt/VAR characteristics are network-cognizant, in the sense that they embed information on the location of the DERs and, consequently, on the effect of reactive-power adjustments on the voltages throughout the feeder. Bounds on the maximum voltage deviation incurred by the controllers are analytically established. Numerical results are reported to corroborate the technical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Generalized hydrodynamics, quasiparticle diffusion, and anomalous local relaxation in random integrable spin chains

We report on the nonequilibrium dynamics of random spin chains that remain integrable (i.e., solvable via Bethe ansatz): because of correlations in the disorder, these systems escape localization and feature ballistically spreading quasiparticles. We derive a generalized hydrodynamic theory for dynamics in such random integrable systems, including diffusive corrections due to disorder, and use it to study nonequilibrium energy and spin transport. We demonstrate that diffusive corrections to the ballistic propagation of quasiparticles can arise even in noninteracting settings, in sharp contrast to clean integrable systems. This suggests that operator fronts broaden diffusively in random integrable systems. By tuning parameters in the disorder distribution, one can drive this model through an unusual phase transition, between a phase where all wave functions are delocalized and a phase in which low-energy wave functions are quasilocalized (in a sense we specify). Both phases have ballistic transport; however, in the quasilocalized phase, local autocorrelation functions decay with an anomalous power law, and the density of states diverges at low energy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗