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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Novel Parameterization of Ice Cloud Effective Diameter from Collocated CALIOP-IIR and CloudSat Retrievals

Satellite-based measurements of global ice cloud microphysical properties are sampled to develop a novel set of physical parameterizations, relating to cloud layer temperature and effective diameter D(e), that can be implemented for two separate applications: in numerical weather prediction models and lidar-based cloud radiative forcing studies. Ice cloud optical properties (i.e., spectral scattering and absorption) are estimated based on the effective size and habit mixture of the cloud particles. Historically, the ice cloud D(e) has been parameterized from aircraft in situ measurements. However, aircraft-based parameterizations are opportunistic in that they only represent specific types of clouds (e.g., convective anvil, tropopause-topped cirrus) in the regions in which they were sampled and, in some cases, are limited in fully resolving the entire vertical cloud layer. Breaking away from the aircraft-based parameterization paradigm, this study is the first of its kind to attempt a parameterization of D(e) as a function of temperature, ice water content (IWC), and lidar-derived extinction from satellite-based global oceanic measurements of ice clouds. Data from both active and passive remote sensing sensors from two of NASA’s A-Train satellites, CloudSat and CALIPSO, are collected to guide development of globally robust parameterizations of all ice cloud types and one exclusively for cirrus clouds.

Ice Cloud↗
NASA NTRSDate not supplied

AMSR-2 Daily Snow Depth Data Product Using a Neural Network Algorithm Trained by Collocated ICESat-2 Measurements

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu 1 et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu 2 et al. (2022,2024) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, a neural network (NN) algorithm, employing several channels from AMSR-2 and the humidity vertical profiles GMAO GEOS-IT, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained NN snow-depth was applied to 2014-2020 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. This paper used AMSR-2 data, a passive microwave instrument to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗
DOE OSTI2020

Establishing Regulatory Jurisdictional Boundaries at Collocated Advanced-Reactor Facilities

This white paper discusses establishing and applying nuclear facility jurisdictional boundaries at advanced-nuclear-reactor facilities. It was written for industry review and evaluation with possible consideration by the U.S. Nuclear Regulatory Commission (NRC) for subsequent regulatory action. The paper proposes a regulatory basis for establishing jurisdictional boundaries at operational advanced (i.e., non-light water) reactor installations at sites proximate to and sharing systems with non-NRC regulated facilities (e.g., users of process heat, fossil-plant retrofits, microgrid electrical power, desalination, etc.). Advanced-reactor technologies can be applied to support many industrial applications to replace the burning of fossil fuels as well as produce steam for electricity. The principal application of the current light-water reactor fleet is electricity generation. These varied industrial applications may involve an advanced-reactor design in combination with different site-specific energy-conversion systems. Some of these process-heat applications will require process-heat delivery systems to lie partially outside the advanced-reactor operator’s facility. Energy conversion systems are conventional, non-nuclear equipment and buildings. Given these varied applications, there should be a clear understanding between the advanced-reactor applicant and the NRC regarding a nominal demarcation between those systems that reside within the nuclear facility under the regulatory jurisdiction of the NRC (i.e., within the scope of a 10 Code of Federal Regulations (CFR) 50 operating license or Part 52 design certification and a combined license) and those that fall outside the scope of the NRC (e.g., an industrial facility). Additionally, it is important to have a clear understanding regarding the plant scope that should be addressed in an advanced-reactor facility Part 52, design certification application and the part of the plant scope that could be addressed as part of a site specific combined license application.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Multi-link spherical joint with collocated centers of rotation

A joint includes a shell that is hollow and at least partially spherical. The shell includes a plurality of shell rail sections including a first shell rail section. The first shell rail section includes a portion of an outer surface of the shell, a portion of an inner surface of the shell, and an opening edge section that defines a shell opening. The joint also includes a plurality of rotatable members including a first rotatable member. The first rotatable member includes an outer cup positioned at least partially outside of the shell and having an outer track surface, and an inner cup positioned at least partially inside of the shell and having an inner track surface. The first shell rail section is positioned at least partially between the outer and inner track surfaces.

Hunsaker, Dakota↗
DOE OSTI2023

Cantilever with a collocated piezoelectric actuator-sensor pair

Illustrative embodiments provide an apparatus comprising a substrate comprising a cantilever, a bottom electrode on the substrate, a bottom piezoelectric transducer on the bottom electrode such that the bottom electrode is between the substrate and the bottom piezoelectric transducer, a middle electrode on the bottom piezoelectric transducer such that the bottom piezoelectric transducer is between the bottom electrode and the middle electrode, a top piezoelectric transducer on the middle electrode such that the middle electrode is between the bottom piezoelectric transducer and the top piezoelectric transducer, and a top electrode on the top piezoelectric transducer, such that the top piezoelectric transducer is between the middle electrode and the top electrode. Illustrative embodiments also provide a method of making the apparatus and a method of using the apparatus for atomic force microscopy.

Moheimani, Seyed Omid Reza↗
DOE OSTI2024

HybridSystemsSimulations.jl - Solving the Merchant Collocated Facilities with JuMP

The development of new clean-generation technologies also leads to new plant-level architectures that combine several generation and storage assets behind the point of connection. These co-located generation resources (Hybrid Systems) primarily operate as merchant assets that employ automated market bidding models and internal Energy Management Systems (EMS) to comply with the operator's signals. Formulating an optimal bidding model requires embedding the EMS control model into the bidding algorithm, resulting in a bi-level optimization problem. In this presentation, we first showcase using JuMP to formulate and solve this problem effectively for multiple merchant systems and the bidding outcomes considering different model formulations. Second, the bidding outcomes are later integrated into a PowerSimulations.jl (also built with JuMP) simulation to study the system-level effects of the various merchant bidding and the interactions between market-clearing models and the embedded EMS model. We will showcase simulations conducted in the RTS system considering different levels of merchant hybrid systems participation. The presentation provides the following specific insights on JuMP usage: 1) the Formulation of specialized bi-level problems with custom cuts to solve the merchant hybrid system bidding problem; 2) the integration of a modular model within a complex simulation workflow supported by JuMP in PowerSimulations.jl; 3) Accelerating the solution of power systems operations simulation that employ agent optimization problems using JuMP.

energy markets↗
NASA NTRS2023

Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network

The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (AEs) measured with the aerosol robotic network (AERONET) are considered as the ground truth for satellite validations. AERONET AEs are used to collocate the wavelength of the AERONET AODs to those of the satellite AODs when there is a discordancy in their wavelengths. However, numerous validation studies have proposed different strategies by applying the AERONET AODs and AEs, and spatiotemporal collocation criteria. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The estimated AERONET AODs at 550 nm varied from 5.18% to 11.73% depending on the selection of AOD and AE, and the spatial collocation radii from 0 to 40 km, respectively. The longer the collocation radius and the higher the AODs, the greater the variability observed in the validation results. Overall, the selection of the spatial collocation radius had a stronger impact on the variability in the validation results obtained compared to the selection of the wavelength. The variability was also found in seasonal analysis. Therefore, it is recommended to carefully select the data wavelength and spatial collocation radius, consider seasonal effects, and provide this information when validating satellite AODs using AERONET.

GOCI↗
DOE OSTI2016

New Approach to Eccentric Positioning of Fuel Assemblies in a Spent Fuel Pool

Criticality analyses of a spent fuel pool (SFP) typically assume the fuel assemblies are centered in the cells. In reality fuel assemblies are not constrained to be centered but can be placed anywhere within the available space. For SFPs with absorber panels it has been shown that the most reactive condition is with the fuel assemblies centered. However, for SFPs without absorber panels eccentric positioning of assemblies increases reactivity. Historically, it was common practice to analyze eccentric positioning by modeling a 2x2 arrangement of the fuel where each assembly is positioned toward the center (with reflective or periodic bounding conditions). The delta k between the eccentric model and the center model was taken as an uncertainty which was then statistically combined with other uncertainties. This historical approach had two problems. First, arrangement of more than 4 assemblies placed toward the center of the model produced higher k's. Second, in a large pool it was likely that 4 assemblies collocated toward each other would exist so asymmetry should be treated as a bias rather than an uncertainty. The number of collocated assemblies is important to the magnitude of the effect. Since spent fuel pools are large it is expected that some collocated eccentrically placed assemblies will occur so the eccentric placement reactivity should be accounted for by a bias. The magnitude of this bias depends greatly on the number of eccentrically placed assemblies that are collocated. A simple probability model assuming random placement can be used to establish the number of collated eccentric assemblies. It has been shown that for a SFP with 800 cells there is less than a 5% probability that more than 16 eccentric assemblies will be collocated. The eccentricity bias using 16 eccentric assemblies collocated is small (on the order of 0.001 in delta k or less) and should be easy to add as a bias in the SFP criticality analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗