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At least 973 records · Page 54

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Natural switches in behaviour rapidly modulate hippocampal coding

Throughout their daily lives, animals and humans often switch between different behaviours. However, neuroscience research typically studies the brain while the animal is performing one behavioural task at a time, and little is known about how brain circuits represent switches between different behaviours. Here we tested this question using an ethological setting: two bats flew together in a long 135 m tunnel, and switched between navigation when flying alone (solo) and collision avoidance as they flew past each other (cross-over). Bats increased their echolocation click rate before each cross-over, indicating attention to the other bat. Hippocampal CA1 neurons represented the bat’s own position when flying alone (place coding). Notably, during cross-overs, neurons switched rapidly to jointly represent the interbat distance by self-position. This neuronal switch was very fast—as fast as 100 ms—which could be revealed owing to the very rapid natural behavioural switch. The neuronal switch correlated with the attention signal, as indexed by echolocation. Interestingly, the different place fields of the same neuron often exhibited very different tuning to interbat distance, creating a complex non-separable coding of position by distance. Theoretical analysis showed that this complex representation yields more efficient coding. Overall, our results suggest that during dynamic natural behaviour, hippocampal neurons can rapidly switch their core computation to represent the relevant behavioural variables, supporting behavioural flexibility.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Spin Vortex Resonance in Non-planar Ferromagnetic Dots

In planar structures, the vortex resonance frequency changes little as a function of an in-plane magnetic field as long as the vortex state persists. Altering the topography of the element leads to a vastly different dynamic response that arises due to the local vortex core confinement effect. In this work, we studied the magnetic excitations in non-planar ferromagnetic dots using a broadband microwave spectroscopy technique. Two distinct regimes of vortex gyration were detected depending on the vortex core position. The experimental results are in qualitative agreement with micromagnetic simulations.

36 MATERIALS SCIENCE↗

DOE OSTI2013

Multi-water-bag models of ion temperature gradient instability in cylindrical geometry

Ion temperature gradient instabilities play a major role in the understanding of anomalous transport in core fusion plasmas. In the considered cylindrical geometry, ion dynamics is described using a drift-kinetic multi-water-bag model for the parallel velocity dependency of the ion distribution function. In a first stage, global linear stability analysis is performed. From the obtained normal modes, parametric dependencies of the main spectral characteristics of the instability are then examined. Comparison of the multi-water-bag results with a reference continuous Maxwellian case allows us to evaluate the effects of discrete parallel velocity sampling induced by the Multi-Water-Bag model. Differences between the global model and local models considered in previous works are discussed. Using results from linear, quasilinear, and nonlinear numerical simulations, an analysis of the first stage saturation dynamics of the instability is proposed, where the divergence between the three models is examined.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

Effect of the minority concentration on ion cyclotron resonance heating in presence of the ITER-like wall in JET

The most recent JET campaign has focused on characterizing operation with the 'ITER-like' wall. One of the questions that needed to be answered is whether the auxiliary heating methods do not lead to unacceptably high levels of impurity influx, preventing fusion-relevant operation. In view of its high single pass absorption, hydrogen minority fundamental cyclotron heating in a deuterium plasma was chosen as the reference wave heating scheme in the ion cyclotron domain of frequencies. The present paper discusses the plasma behavior as a function of the minority concentration X[H] in L-mode with up to 4MW of RF power. It was found that the tungsten concentration decreases by a factor of 4 when the minority concentration is increased from X[H] ≈ 5% to X[H] % 20% and that it remains at a similar level when X[H] is further increased to 30%; a monotonic decrease in Beryllium emission is simultaneously observed. The radiated power drops by a factor of 2 and reaches a minimum at X[H] ≈ 20%. It is discussed that poor single pass absorption at too high minority concentrations ultimately tailors the avoidance of the RF induced impurity influx. The edge density being different for different minority concentrations, it is argued that the impact ICRH has on the fate of heavy ions is not only a result of core (wave and transport) physics but also of edge dynamics and fueling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Fluorescence relaxation dynamics of CdSe and CdSe/CdS core/shell quantum dots

Time-resolved fluorescence spectra for colloidal CdSe and CdSe/CdS core/shell quantum dots have been investigated to know their electron relaxation dynamics at the maximum steady state fluorescence intensity. CdSe core and CdSe/CdS type I core-shell materials with different shell (CdS) thicknesses have been synthesized using mercaptoacetic acid as a capping agent. Steady state absorption and emission studies confirmed successful synthesis of CdSe and CdSe/CdS core-shell quantum dots. The fluorescence shows a tri-exponential decay with lifetimes 57.39, 7.82 and 0.96 ns for CdSe quantum dots. The lifetime of each recombination decreased with growth of CdS shell over the CdSe core, with maximum contribution to fluorescence by the fastest transition.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Design, upgrade and characterization of the silicon photomultiplier front-end for the AMIGA detector at the Pierre Auger Observatory

AMIGA (Auger Muons and Infill for the Ground Array) is an upgrade of the Pierre Auger Observatory to complement the study of ultra-high-energy cosmic rays (UHECR) by measuring the muon content of extensive air showers (EAS). It consists of an array of 61 water Cherenkov detectors on a denser spacing in combination with underground scintillation detectors used for muon density measurement. Each detector is composed of three scintillation modules, with 10 m 2 detection area per module, buried at 2.3 m depth, resulting in a total detection area of 30 m 2 . Silicon photomultiplier sensors (SiPM) measure the amount of scintillation light generated by charged particles traversing the modules. In this paper, the design of the front-end electronics to process the signals of those SiPMs and test results from the laboratory and from the Pierre Auger Observatory are described. Compared to our previous prototype, the new electronics shows a higher performance, higher efficiency and lower power consumption, and it has a new acquisition system with increased dynamic range that allows measurements closer to the shower core. The new acquisition system is based on the measurement of the total charge signal that the muonic component of the cosmic ray shower generates in the detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

EVIDENCE OF LANDAU AND CYCLOTRON RESONANCE BETWEEN PROTONS AND KINETIC WAVES IN SOLAR WIND TURBULENCE

The wave–particle interaction processes occurring in the solar wind provide crucial information to understand the wave dissipation and simultaneous particle heating in plasma turbulence. One requires observations of both wave fluctuations and particle kinetics near the dissipation range, which have, however, not yet been analyzed simultaneously. Here we show new evidence of wave–particle interactions by combining the diagnosis of wave modes with the analysis of particle kinetics on the basis of measurements from the WIND spacecraft with a high cadence of about 3 s. Solar wind protons appear to be highly dynamic in their velocity distribution consisting of varying anisotropic core and beam components. The basic scenario of solar wind proton heating through wave–particle interaction is suggested to be the following. Left-handed cyclotron resonance occurs continuously, and is evident from the observed proton core velocity distribution and the concurrent quasi-parallel left-handed Alfvén cyclotron waves. Landau and right-handed cyclotron resonances are persistent and indicated by the observed drifting anisotropic beam and the simultaneous quasi-perpendicular right-handed kinetic Alfvén waves in a general sense. The persistence of non-gyrotropic proton distributions may cast new light on the nature of the interaction between particles and waves near and beyond the proton gyro-frequency.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Coupling coarse-mesh CFD with fine-mesh CFD for modeling molten-salt reactors in the Virtual Test Bed (VTB)

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims at developing a simulation tool kit to accelerate the development and deployment of nuclear power technologies. NEAMS multiphysics tools have been designed to provide numerical simulation support for the design and licensing of GEN IV reactors. Pronghorn is NEAMS's coarse-mesh computational fluid dynamics (CFD) tool, which is designed to run 3D core transients in GEN IV reactors at a reduced computational cost. To increase their accuracy, coarse-mesh CFD simulations require calibrated closure coefficients. One way of computing these coefficients is via the Nek5000, NEAMS's high-fidelity CFD tool. This article discusses our current research lines in informing Pronghorn closure coefficients via Nek5000 to enable multiphysics simulations of the core cavity of the molten-salt fast reactor. We present an application in which Pronghorn mixing length turbulent viscosity has been calibrated from Nek5000 simulations. The resulting Pronghorn thermal-hydraulics model is then coupled to Griffin, the NEAMS neutron transport solver, to solve for the steady-state configuration of the molten-salt fast reactor. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

PNNL Report on the Development of Bench-scale CFD Simulations for Gas Absorption across a Wetted Wall Column

This report is prepared for the demonstration of hierarchical prediction of carbon capture efficiency of a solvent-based absorption column. A computational fluid dynamics (CFD) model is first developed to simulate the core phenomena of solvent-based carbon capture, i.e., the CO 2 physical absorption and chemical reaction, on a simplified geometry of wetted wall column (WWC) at bench scale. Aqueous solutions of ethanolamine (MEA) are commonly selected as a CO 2 stream scrubbing liquid. CO 2 is captured by both physical and chemical absorption using highly CO 2 soluble and reactive solvent, MEA, during the scrubbing process. In order to provide confidence bound on the computational predictions of this complex engineering system, a hierarchical calibration and validation framework is proposed. The overall goal of this effort is to provide a mechanism-based predictive framework with confidence bound for overall mass transfer coefficient of the wetted wall column (WWC) with statistical analyses of the corresponding WWC experiments with increasing physical complexity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Fast and accurate learned multiresolution dynamical downscaling for precipitation

Abstract. This study develops a neural-network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computational cost. The key idea is to use combination of low- and high-resolution simulations (that differ not only in spatial resolution but also in geospatial patterns) to train a neural network to map from the former to the latter. Specifically, we define two types of CNNs, one that stacks variables directly and one that encodes each variable before stacking, and we train each CNN type both with a conventional loss function, such as mean square error (MSE), and with a conditional generative adversarial network (CGAN), for a total of four CNN variants. We compare the four new CNN-derived high-resolution precipitation results with precipitation generated from original high-resolution simulations, a bilinear interpolater and the state-of-the-art CNN-based super-resolution (SR) technique. Results show that the SR technique produces results similar to those of the bilinear interpolator with smoother spatial and temporal distributions and smaller data variabilities and extremes than the original high-resolution simulations. While the new CNNs trained by MSE generate better results over some regions than the interpolator and SR technique do, their predictions are still biased from the original high-resolution simulations. The CNNs trained by CGAN generate more realistic and physically reasonable results, better capturing not only data variability in time and space but also extremes such as intense and long-lasting storms. The new proposed CNN-based downscaling approach can downscale precipitation from 50 to 12 km in 14 min for 30 years once the network is trained (training takes 4 h using 1 GPU), while the conventional dynamical downscaling would take 1 month using 600 CPU cores to generate simulations at the resolution of 12 km over the contiguous United States.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

Interferometric Radar Observations of Glaciar San Rafael, Chile

Interferometric radar observations of Glaciar San Rafael, Chile, were collected in October 1994 by NASA's Spaceborne Imaging Radar C (SIR-C) at both L- (24cm) and C-band frequency (5.6cm), with vertical transmit and receive polarization. The C-band data did not yield good geophysical products, because the temporal coherence of the signal was significantly reduced after 24h. The L-band data were, however, successfully employed to map the surface topography of the icefield with a 10m uncertainty in height, and measure ice velocity with a precision of 4 mm/d or 1.4 m/a. The corresponding error in strain rates is 0.05/a at a 30 m horizontal spacing. The one-dimensional interferometric velocities were subsequently converted to horizontal displacements by assuming a flow direction and complemented by feature-tracking results near the calving front. The results provide a comprehensive view of the ice-flow dynamics of Glaciar San Rafael. The glacier has a core of rapid flow, 4.5 km in width and 3.5 degrees in average slope,surrounded by slower moving ice, not by rock. Ice velocity is 2.6 m/d or 0.95 km/a near the equilibrium line altitude (1200m), increasing rapidly before the glacier enters the narrower terminal valley, to reach 17.5 m/d or 6.4 km/a at the calving front. Strain rates are dominated by lateral shearing at the glacier margins (0.4-0.7/a), except for the terminal-valley section, where longitudinal strain rates average close to 1/a. This spectacular longitudinal increase in ice velocity in the last few kilometers may be a fundamental feature of tidewater glaciers.

Rignot, Eric↗

NASA NTRS2017

Update on the NASA GEOS-5 Aerosol Forecasting and Data Assimilation System

GEOS-5 is the Goddard Earth Observing System model. GEOS-5 is maintained by the NASA Global Modeling and Assimilation Office. Core development is within GMAO,Goddard Atmospheric Chemistry and Dynamics Laboratory, and with external partners. Primary GEOS-5 functions: Earth system model for studying climate variability and change, provide research quality reanalyses for supporting NASA instrument teams and scientific community, provide near-real time forecasts of meteorology,aerosols, and other atmospheric constituents to support NASA airborne campaigns.

GEOS-5↗

NASA NTRS2020

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗

NASA NTRSDate not supplied

Assimilation of microwave satellite observations over the rainbands of tropical cyclones

The potential of microwave observations in improving the weather forecasts is limited by the accuracy of all-sky radiative transfer calculations. We introduce a novel Bayesian MonteCarlo technique to improve the assimilation of microwave observations over the rainbands of tropical cyclones. The BMCI technique eliminates the need for a forward model in the data assimilation system. The technique includes three steps, (i) generating a comprehensive dataset using in-situ cloud measurements and atmospheric profiles, (ii) generating synthetic ATMS observations from the training dataset, and (iii) using real observations to estimate the geophysical variables over the rainbands of tropical cyclones. The retrieved profiles of temperature, relative humidity, and cloud water content as well assurface information such as SST were then assimilated into the model. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns.

Monte Carlo↗

NASA NTRSDate not supplied

Informing the Space Launch System Booster Separation Initial CFD Run Matrix with Observed Parametric Sensitivity

It currently requires significant computational cost to simulate the flow physics of the booster separation event on the Space Launch System. This comes from the large parametric space in which the event occurs, as pre-separation flight conditions and separated booster core-relative trajectories can vary. Functionally removing the risk of core-booster collision mandates careful assessment of the fluid dynamics in terms of several trajectory parameters. However, simulating the entire trajectory envelope is computationally intractable given the high parametric dimension. In order to reduce the uncertainty in the resulting low-parametric-resolution aerodynamic booster separation database, a data-driven approach was developed to select which breakpoints should be studied by simulations and experiments and which should be relegated to a regression-based interpolation procedure. This technique works by simulating cases where the flow physics are most sensitive to changes in the parameters and leaving the less parametrically sensitive regions for interpolation. The result is a booster separation run matrix whose computational cost is comparable to that of previous database generations but has lower interpolation errors.

SLS↗

NASA NTRSDate not supplied

Informing the Space Launch System Booster Separation Initial CFD Run Matrix with Observed Parametric Sensitivity

SLS↗

NASA NTRSDate not supplied

Investigating the Applications of In-Situ Resource Utilization for Future Crewed Mars Missions

There are significant gaps in knowledge regarding the water ice on Mars and future preparation for human missions. So far, six rovers have traversed Mars’ rocky surface, aiming to understand the planet’s composition and search for signs of life. A rover mission set to explore the high northern latitudes of Mars with the goal of analyzing ice cores could greatly advance scientific knowledge to better understand Mars’s ancient climate and geochemistry. As of now, little has been accomplished in the exploration of colder regions and the extraction of water ice apart from the Phoenix lander and the Viking 2 mission; however, the science potential of the Phoenix and Viking landers was limited due to their inability to explore terrain like rovers. The exploration of the near-polar region Arcadia Planitia and its water ice deposits could reveal signs of past microbial life through preserved biosignatures. Additionally, to prepare for permanent human habitation on Mars, this proposed rover could continue the characterization of Mars’s current land and mineral composition, and search for materials that future humans may need on Mars (such as water for habitation, basalt for construction, and olivine for manufacturing purposes). This would increase understanding of the potential for in-situ resource utilization (ISRU) on Mars. The use of ISRU will reduce the amount of material needed on the initial flight, and similarly will reduce fuel costs. The mission to Arcadia Planitia incorporates the use of various mineral-extracting and imaging instruments (Martian Ice Core Analyzer, ground-penetrating radar, NavCam, Mars Environmental Dynamics Analyzer, SuperCam, etc.) to collect data from water ice and geologic samples. A near-polar rover mission to Mars would illuminate Mars’ past and present, while learning more about martian resources to benefit human explorers in the future.

Annika Sachdeva↗