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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 505 records · Page 28

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NASA NTRS1989

Observation of hydrological features with Nimbus-7 37 GHz data, applied to South America

The microwave polarization difference temperature (MPDT) prepared from 37 GHz Scanning Multifrequnecy Microwave Radiometer (SMMR) data from the Nimbus-7 satellite allows a unique vision of hydrological features, especially of humid areas. From the series of monthly images from 1979 to 1985 the major hydrological features of four major river basins of South America are briefly examined. These include rivers of the Amazon, La Plata, Orinoco and Sao Francisco, wetlands in the La Plata and Amazon basins and floods in the La Plata basin. Many hydrological features appear much as they do on conventional maps. An interesting prespective can be derived from the ways in which they differ from conventional maps.

Giddings, L.↗

NASA NTRS2017

Satellite Image Mapping of Tree Mortality in the Sierra Nevada Region of California from 2013 to 2016

Extreme drought from 2013 to 2015 has been linked to extensive tree dieback in the Sierra-Nevada region of California. Landsat satellite imagery was analysed for the region from Lake Tahoe to the southern Sequoia National Forest with the objective of understanding the patterns of tree mortality in the years of 2013 to 2015 and into the near-normal precipitation year of 2016. The main mapping results for Landsat moisture index differences from year-to-year showed that the highest coverage of tree dieback was located in the Sierra and Sequoia National Forests, at four to five times greater area each year than within any other National Park or National Forest unit. Since 2013, over 50% of the Sierra Nevada forest dieback area was detected in the mid elevation zone of 1000-2000 m. The total area of tree mortality in the lower elevation zone of 500-1000 m did not grow notably from 2015 to 2016. Within the largest California river drainages in the Sierra region, new tree mortality in 2015 was detected mainly below 1200 m elevation, whereas new tree mortality in 2016 was detected mainly at higher elevations, up to about 2200 m. In three out of the four years studied, results showed that about 60% of all new tree mortality areas were located on north-facing hill slopes.

Satellite↗

NASA NTRSDate not supplied

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves Response To Hurricane Forces

Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.

Samuel Perrello↗

NASA NTRS2022

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves in Response to Hurricane Forces

Remote sensing↗

DOE OSTI2026

Raman spectroscopic investigation of ianthinite [U$_2^{4+}$(UO$_2$)$_4$O$_6$(OH)$_4$(H$_2$O)$_4$]·$5$H$_2$O, a rare mixed-valence uranium oxide hydrate

Ianthinite ([[U$_2^{4+}$(UO$_2$)$_4$O$_6$(OH)$_4$(H$_2$O)$_4$]·$5$H$_2$O) is an exotic mineral that possesses U in both tetravalent and hexavalent oxidation states and is structurally related to the U 3 O 8 polymorphs, which are commonly encountered technogenic materials in the nuclear fuel cycle. Despite the similarities between U 3 O 8 and ianthinite, and the importance of ianthinite in U paragenesis, no Raman spectra have been reported for this mineral. Here, to gain a more complete understanding of how structural attributes of ianthinite give rise to observable spectroscopic features and how these may relate to important materials in the nuclear fuel cycle, we provide, for the first time, Raman spectra of ianthinite. Ianthinite readily oxidizes at ambient conditions, complicating analysis of phase-pure material. Several analytical methods are employed herein to decouple the Raman features of ianthinite from its alteration product(s). First, a simple difference spectrum is presented, then results of Raman spectroscopic mapping are employed, and finally, we use a novel processing and analysis method. Each analysis method provides different insight into structural features that are unique to ianthinite, in particular, features that are attributable to U(IV) in distorted octahedral coordination in both ianthinite and U 3 O 8 phases.

Spano, Tyler L. [Oak Ridge National Laboratory (OR↗

DOE OSTI2023

Inverse reinforcement learning control for building energy management

Reinforcement learning (RL) based control is widely considered a promising approach in building automation and control as it has demonstrated the potential to deal with complex objectives in adjacent domains like robotics, autonomous vehicles, gaming applications, and advertisement recommendations. When applied to any environment, model-free RL learns to improve its control performance over time without requiring a control model, by receiving and then analyzing feedback from the building environment after each control action. Operational objectives are becoming increasingly complex through the simultaneous consideration of thermal comfort, carbon emissions, grid services, and indoor air quality. In this context, conventional rule-based control approaches are proving sub-optimal, mostly heuristic, and inadequate. The model-free and self learning nature of RL appears promising and attractive as it may address the scalability issues associated with advanced control approaches. However, it suffers from long training times and unstable control behavior during the early stages of its learning process, which makes it unsuitable to be applied directly to buildings. This paper addresses these issues using an inverse reinforcement learning approach (IRL), a technique utilized to learn the objective of a controller agent which is considered an expert in its respective domain. Here, we consider a rule-based control as the expert demonstrator. IRL is different from a direct imitation (i.e., direct mapping of states to actions) of control actions as it tries to find the underlying intent of an expert's policy, providing the controller with a better-generalized policy for unseen states or environments with slightly different dynamics. This approach propels the RL controller's policy to levels similar to or better than that of a rule-based policy before it starts learning by interacting with the building. This makes RL for building energy management applications more practical as it prevents the erratic and exploratory behavior in the initial training period, simultaneously speeding up the learning process when compared to applying an untrained RL agent directly to a building environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1993

Geologic mapping of Harmakhis and Reull Valles region, Mars: Evidence for multiple resurfacing and drainage events

Numerous mesas and irregular, channel-cut escarpments south of Harmakhis and Reull Valles suggesting at least two resurfacing events with subsequent periods of erosion are revealed from detailed geologic mapping of three adjacent 1:500,000-scale quadrangles (MTM-40262, -40267, -40272). Also, two distinct episodes of surface water runoff, each from different styles of water release, are evident. Geologic mapping is based on 1:500,000-scale photomosaics of the Harmakhis vallis region, and is an outgrowth of preliminary regional geologic mapping on a 1:2,000,000-scale on the east rim of Hellas Basin.

Price, Katherine H.↗

NASA NTRS1982

Workshop on the Use of Future Multispectral Imaging Capabilities for Lithologic Mapping: Workshop summary

Improved orbital imaging capabilities from the standpoint of different scientific disciplines, such as geology, botany, hydrology, and geography were evaluated. A discussion on how geologists might exploit the anticipated measurement capabilities of future orbital imaging systems to discriminate and characterize different types of geologic materials exposed at the Earth's surface is presented. Principle objectives are to summarize past accomplishments in the use of multispectral imaging techniques for lithologic mapping; to identify critical gaps in earlier research efforts that currently limit the ability to extract useful information about the physical and chemical characteristics of geological materials from orbital multispectral surveys; and to define major thresholds, resolution and sensitivity within the visible and infrared portions of the electromagnetic spectrum which, if achieved would result in significant improvement in our ability to discriminate and characterize different geological materials exposed at the Earth's surface.

Settle, M.↗

DOE OSTI2021

Dissolution of periodic arrays of grains: Upscaling of pore-scale simulations with fast reactions

Upscaling methods are frequently used to derive transport equations at the macroscopic scale from more fundamental equations formulated at the pore scale. These methods typically give a suitable structure for the macroscopic equations and can also provide explicit expressions for the constitutive parameters, such as permeability and dispersion coefficients. Introducing chemical reactions complicates upscaling in at least two important ways. First, the interplay between chemical reactions and transport processes introduces a new length scale, which can be much smaller than the convective or dispersive length scales. A small reactive length scale breaks one of the key assumptions in upscaling; that there is a significant separation in length between the pore-scale and macro-scale processes. The second complication is that if reactions take place at mineral surfaces (dissolution or precipitation) then the pore space itself is evolving in time. In this paper we suggest ways in which these difficulties can be approached, based on analysis of pore-scale simulation data. First, we noticed that the concentration field in successive unit cells has an almost identical spatial variation, with a single scaling factor for each unit cell that is proportional to the incoming reactant flux. Using pore-scale simulations to determine the mass transfer coefficient in a few unit cells, we can calculate the concentration field in the whole domain, even when dissolution is entirely transport limited. Second, we have noticed a time-dependent mapping of the grain shapes from different unit cells. From these observations, we can deduce constitutive relations where the only time-varying parameter is the porosity. Here, we show that a model based on these ideas can quantitatively account for the pore-scale simulation data.

58 GEOSCIENCES↗

DOE OSTI2020

Boltzmann machine modeling of layered MoS 2 synthesis on a quantum annealer

Two-dimensional layered materials are usually synthesized by chemical vapor deposition (CVD). Here we use the Restricted Boltzmann Machine (RBM) and its enhancement called Limited Boltzmann Machine (LBM) on a quantum computer to model the chemical vapor deposition (CVD) growth data for a MoS 2 monolayer. The CVD data for Boltzmann machines are generated by reactive molecular dynamics (RMD) simulations. The Boltzmann machines give insight into the semiconducting (2H) and metallic (1T) phases and defects generated during the CVD growth of MoS 2 . We compare the performances of the two types of Boltzmann machine models, i.e. RBM versus augmented topologies with limited intra-layer coupling between the hidden units (LBM). We show that limited topologies have a performance advantage over restricted topologies. We examine connectivity within our topological variants, explore hardware qubit mapping schemes, and discuss what performance differences may imply about locality within the data without prior knowledge.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space

We propose a spectral method for the 1D-1V Vlasov–Poisson system where the discretization in velocity space is based on asymmetrically-weighted Hermite functions, dynamically adapted via a scaling α and shifting u of the velocity variable. Specifically, at each time instant an adaptivity criterion selects new values of α and u based on the numerical solution of the discrete Vlasov–Poisson system obtained at that time step. Once the new values of the Hermite parameters α and u are fixed, the Hermite expansion is updated and the discrete system is further evolved for the next time step. The procedure is applied iteratively over the desired temporal interval. The key aspects of the adaptive algorithm are: the map between approximation spaces associated with different values of the Hermite parameters that preserves total mass, momentum and energy; and the adaptivity criterion to update α and u based on physics considerations relating the Hermite parameters to the average velocity and temperature of each plasma species. For the discretization of the spatial coordinate, we rely on Fourier functions and use the implicit midpoint rule for time stepping. The resulting numerical method possesses intrinsically the property of fluid-kinetic coupling, where the low-order terms of the expansion are akin to the fluid moments of a macroscopic description of the plasma, while kinetic physics is retained by adding more spectral terms. Moreover, the scheme features conservation of total mass, momentum and energy associated in the discrete, for periodic boundary conditions. A set of numerical experiments confirms that the adaptive method outperforms the non-adaptive one in terms of accuracy and stability of the numerical solution.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Benchmarking fast-neutron response of 7 Li-enriched C 7 LYC scintillators: Simulations and experiment

New insights into the fast neutron response of 7 Li-enriched C 7 LYC scintillators have been obtained through detailed Geant4 simulations of 35 Cl(n,p) and 35 Cl(n, α) reactions that are primarily responsible for the fast neutron response of C 7 LYC. The light output of a 1” x1” C 7 LYC detector was simulated using the Birks equation for light quenching in scintillators. The simulations were benchmarked against neutron scattering data from a 12 C target obtained with a white neutron beam at the Los Alamos LANSCE facility and fourteen 1”x1” C 7 LYC detectors. Incident neutron energies extracted from time-of-flight measurements, and appropriate recoil corrections for the different detector angles were used to map the response of C 7 LYC to mono-energetic neutrons. Resonances in the 35 Cl(n,p) reaction cross-section below 3 MeV incident neutron energy were directly observed in C 7 LYC. The experimental data and simulations are compared with ENDF databases, as well as recent direct cross-section measurements of neutrons scattered from a 35 Cl target. In conclusion, the results suggest a scrutiny of the 35 Cl(n,p) and 35 Cl(n, α) cross sections at low energy in the ENDF library.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Studying Transient Phenomena in Thin Films with Reinforcement Learning

Neutron reflectometry has long been a powerful tool to study the interfacial properties of energy materials. Recently, time-resolved neutron reflectometry has been used to better understand transient phenomena in electrochemical systems. Those measurements often comprise a large number of reflectivity curves acquired over a narrow q range, with each individual curve having lower information content compared to a typical steady-state measurement. In this work, we present an approach that leverages existing reinforcement learning tools to model time-resolved data to extract the time evolution of structure parameters. Further, by mapping the reflectivity curves taken at different times as individual states, we use the Soft Actor-Critic algorithm to optimize the time series of structure parameters that best represent the evolution of an electrochemical system. We show that this approach constitutes an elegant solution to the modeling of time-resolved neutron reflectometry data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Inducing Circularly Polarized Single-Photon Emission via Chiral-Induced Spin Selectivity

One of the central aims of the field of spintronics is the control of individual electron spins to effectively manage the transmission of quantized data. One well-known mechanism for controlling electronic spin transport is the chiral-induced spin-selectivity (CISS) effect in which a helical nanostructure imparts a preferential spin orientation on the electronic transport. One potential application of the CISS effect is as a transduction pathway between electronic spin and circularly polarized light within nonreciprocal photonic devices. Here in this work, we identify and quantify the degree of chiral-induced spin-selective electronic transport in helical polyaniline films using magnetoconductive atomic force microscopy (mcAFM). We then induce circularly polarized quantum light emission from CdSe/CdS core/shell quantum dots placed on these films, demonstrating a degree of circular polarization of up to ~21%. Utilizing time-resolved photoluminescence microscopy, we measure the radiative lifetime difference associated with left- and right-handed circular polarizations of single emitters. These lifetime differences, in combination with Kelvin probe mapping of the variation of surface potential with magnetization of the substrate, help establish an energy level diagram describing the spin-dependent transport pathways that enable the circularly polarized photoluminescence.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Data-driven based coordinated smart inverter control for distributed energy resources

Smart inverters (SI) for distributed energy resources (DER) are becoming popular since they have the ability to stabilize as well as restore the voltage and frequency of power systems. Aiming at establishing the mathematical models combined with SI control methods, multiple optimization methods are developed. However, the computational complexity of solving such a mathematical model with various uncertainties limits the real-time application of the SI control. To conquer this challenge, a data-driven-based SI control approach is developed to achieve coordinated control in the high penetration DER system. First, an optimization problem for maximizing the active power generation and minimizing the power loss is designed using the Volt/VAR control. To reduce the time consumption, the recurrent neural network (RNN) is proposed to model the relationship between the uncertainties and control actions during the offline site. The RNN with different sub-structures such as the long short-term memory cell and gated recurrent unit cell are included to enrich the diversity of features. In the last stage, different experiment comparisons, including multiple uncertainties maps and stateof- art machine learning methods, are conducted to verify the effectiveness of the proposed method based on the IEEE 123 bus power system. The results demonstrate that the proposed method can effectively achieve a rapid and coordinated control with a lower error rate.

Qiu, Wei↗

DOE OSTI2020

Displacement of carbon atoms in few-layer graphene

Molecular dynamics simulations were performed to study the susceptibility of carbon atom displacement under electron irradiation. The mapping of threshold displacement energies at different recoiling directions showed that the energies are very sensitive to the layer configurations and positions of neighboring atoms. Carbon atoms on the top and the bottom layers of few-layer graphene are most vulnerable to irradiation damage due to lack of constraints from the neighboring graphene layers. As indirect experiment evidence, transmission electron microscopy was performed on the edge of folded few-layer graphene, which made it possible to reveal “the inside” and compare irradiation tolerance of atoms at different layers, by using an electron analysis beam for both displacement creation and in situ characterization.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

The star-formation history in the last 10 billion years from CIB cross-correlations

ABSTRACT The cosmic infrared background (CIB) traces the emission of star-forming galaxies throughout all cosmic epochs. Breaking down the contribution from galaxies at different redshifts to the observed CIB maps would allow us to probe the history of star formation. In this paper, we cross-correlate maps of the CIB with galaxy samples covering the range z ≲ 2 to measure the bias-weighted star-formation rate (SFR) density 〈bρSFR〉 as a function of time in a model independent way. This quantity is complementary to direct measurements of the SFR density ρSFR, giving a higher weight to more massive haloes, and thus provides additional information to constrain the physical properties of star formation. Using cross-correlations of the CIB with galaxies from the DESI Legacy Survey and the extended Baryon Oscillation Spectroscopic Survey, we obtain high signal-to-noise ratio measurements of 〈bρSFR〉, which we then use to place constraints on halo-based models of the star-formation history. We fit halo-based SFR models to our data and compare the recovered ρSFR with direct measurements of this quantity. We find a qualitatively good agreement between both independent data sets, although the details depend on the specific halo model assumed. This constitutes a useful robustness test for the physical interpretation of the CIB, and reinforces the role of CIB maps as valuable astrophysical probes of the large-scale structure. We report our measurements of 〈bρSFR〉 as well as a thorough account of their statistical uncertainties, which can be used to constrain star-formation models in combination with other data.

Astronomy & Astrophysics↗

DOE OSTI2024

Extending evolutionary forecasts across bacterial species

Improving evolutionary forecasting requires progressing from studying repeated evolution of a single genotype under identical conditions to formulating broad principles. These principles should enable predictions of how similar species will adapt to similar selective pressures. Evolve-and-resequence experiments with multiple species allow testing forecasts on different biological levels and elucidating the causes for failed predictions. Here, we show that forecasts for adaptation to static culture conditions can be extended to multiple species by testing previous predictions for Pseudomonas syringae and Pseudomonas savastanoi. In addition to sequence divergence, these species differ in their repertoire of biofilm regulatory genes and structural components. Consistent with predictions, both species repeatedly produced biofilm mutants with a wrinkly spreader phenotype. Predominantly, mutations occurred in the wsp operon, with less frequent promoter mutations near uncharacterized diguanylate cyclases. However, mutational patterns differed on the gene level, which was explained by a lack of conservation in relative fitness of mutants between more divergent species. The same mutation was the most frequent for both species suggesting that conserved mutation hotspots can increase parallel evolution. This study shows that evolutionary forecasts can be extended across species, but that differences in the genotype–phenotype–fitness map and mutational biases limit predictability on a detailed molecular level.

59 BASIC BIOLOGICAL SCIENCES↗