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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Litter removal impacts on soil biodiversity and eucalypt plantation development in the seasonal tropics

The little layer of tree plantations provides primary nutrients for uptake, buffers changes in soil moisture, and provides habitat and substrate to soil epigeic fauna. However, this layer in eucalypt plantations is often removed to reduce fuel load during the fire season in the Brazilian savanna (Cerrado). Therefore, it is necessary to quantify the effects of changes in litter dynamics on the function of these plantations, on key nutrient cycling processes and on epigeic fauna diversity and abundance. In two adjacent stands (one juvenile and one mature), the consequences of two years of litter removal were quantified as monthly litterfall, leaf and fine wood litter decomposition, epigeic fauna abundance and diversity, soil biogeochemical variables, and tree diameter and basal area increments. Monthly litterfall rates in juvenile and mature stands did not change with litter removal over the study period. Annual litterfall ranged from 4.1 to 4.9 Mg ha -1 a -1 in litter removal plots and from 3.9 to 4.8 Mg ha -1 a -1 in control plots. Fine wood litter decomposition was slower in litter removal plots compared to controls, while leaf decomposition rates were similar in both. Two years of litter removal in the juvenile stand did not affect topsoil biogeochemical parameters but decreased available phosphorus at 20–40 cm depth relative to controls. In the mature stand, total cation exchange capacity (0–20 cm) was higher in controls (6.4 cmol c dm -3 ) relative to litter removal plots (6.3 cmol c dm -3 ), while soil moisture (0–40 cm depth) was lower in litter removal (25.45 m 3 m -3 ) compared to control plots (26 m 3 m -3 ) in the dry season. A non-metric multidimensional scaling ordination revealed an increased homogeneity in epigeic fauna where litter was removed. Litterfall, decomposition, diameter increment, four soil physical parameters and fourteen chemical parameters at 0–20 and 20–40 cm depth explained the differences in soil epigeic fauna composition between litter removal and control plots. Diameter increment decreased with litter removal only in the juvenile stand, which had reached its growth peak. The results indicate that removing excess litter to decrease fuel volume can alter soil biodiversity and edaphic conditions that negatively affect nutrient cycling and tree growth.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Confinement of radio galaxies in rich clusters

X-ray observations obtained with the Einstein Observatory are presented for the Abell clusters A 98, A 160, A 278, and A 569, which are characterized by the presence of an extended radio source associated with the brightest cluster galaxy. The X-ray brightness profiles are fitted with a hydrostatic-thermal model to determine the physical parameters of the X-ray emitting gas and the behavior of the thermal pressure in each cluster. The gas thermal pressure is then compared with the nonthermal pressure within the radio sources, and the conditions for pressure balance are analyzed. The radio source components show a minimum pressure lower than the pressure of the ambient gas. Balance between internal and external pressure is obtained in the case that the usual assumptions for the computation of the energy density in the radio source components are not valid (Phi less than 1, k greater than 1) or that physical conditions are out of equipartition.

Feretti, L.↗
DOE OSTI2021

Surrogate approximation of the Grad–Shafranov free boundary problem via stochastic collocation on sparse grids

In magnetic confinement fusion devices, the equilibrium configuration of a plasma is determined by the balance between the hydrostatic pressure in the fluid and the magnetic forces generated by an array of external coils and the plasma itself. The location of the plasma is not known a priori and must be obtained as the solution to a free boundary problem. The partial differential equation that determines the behavior of the combined magnetic field depends on a set of physical parameters (location of the coils, intensity of the electric currents going through them, magnetic permeability, etc.) that are subject to uncertainty and variability. The confinement region is in turn a function of these stochastic parameters as well. In this work, we consider variations on the current intensities running through the external coils as the dominant source of uncertainty. This leads to a parameter space of dimension equal to the number of coils in the reactor. With the aid of a surrogate function built on a sparse grid in parameter space, a Monte Carlo strategy is used to explore the effect that stochasticity in the parameters has on important features of the plasma boundary such as the location of the x-point, the strike points, and shaping attributes such as triangularity and elongation. Furthermore, the use of the surrogate function reduces the time required for the Monte Carlo simulations by factors that range between 7 and over 30.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Plasma performance and operational space without ELMs in DIII-D

A database of DIII-D plasmas without ELMs compares the operating space and plasma performance of stationary no-ELM regimes: RMP-ELM suppression, QH-mode, I-mode, EDA H-mode, L-mode, and negative triangularity L-mode (Neg-D). Here, operational space is documented in terms of engineering and physics parameters, revealing divergent constraints. Some operational space discriminants (like pedestal collisionality) are well known, while others, such as low torque & safety factor, or high power & density, are less commonly emphasized. Normalized performance (H-factor and betan) also discriminate the no-ELM regimes and favor regimes tolerant to power in DIII-D: RMP, QH, and Neg-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1996

Interplanetary and Interstellar Dust Particles: Reentry Heating and Capture in Aerogel

Studies of interplanetary and interstellar dust can provide significant information on the evolution of the solar system or stars, respectively. However, for reliable analysis it is crucial to know how the particles have been modified during reentry (in the case of interplanetary dust particles, or [DP's) and impact into the capture medium. In the case of stratospheric capture, particles will be heated by atmospheric drag. Subsequent capture of the particles will result in heating, ablation, accretion of the capture medium and possible fragmentation. Modeling of these processes is a useful way of assessing their effects on the interpretation of the compositional data for these particles. Previous work on reentry heating has shown that heat diffusion alone cannot adequately account for temperature gradients observed in IDP's. In fact, for any reasonable thermal parameters, calculations show the particles to be nearly isothermal. Here we extend those studies to include phase transitions. These preliminary results are promising and show a significant temperature gradient for a 100 micron (diameter) particle. The actual capture of the particles in silica aerogel is being modeled using a comprehensive shock hydrodynamic code (called CTH). Various options of this code were investigated to attempt to make the most appropriate choice of methods of impact, equations of state, and processes of energy transfer from capture material to particle. The initial calculations with the code used only 'reasonable' estimates for the physical parameters of silica aerogel. Through the literature searches and personal contacts with the knowledgeable scientists, the best possible mechanical and thermal data have been made available for these computations.

Szydlik, Paul P.↗
NASA NTRS2001

Gridded Hourly Text Products: A TRMM Data Reduction Approach

The quantity of precipitation data from satellite-based observations is a blessing and a curse. The sheer volume of the data makes it difficult for many researchers to use in targeted applications. This volume increases further as algorithm improvements lead to the reprocessing of mission data. In addition to the overall volume of data, the size and format complexity of orbital granules contribute to the difficulty in using all the available data. Finally, the number of different instruments available to measure rainfall and related parameters further contributes to the volume concerns. In summary, we have an embarrassment of riches. The science team of the Tropical Rainfall Measuring Mission (TRMM) recognized this dilemma and has developed a strategy to address it. The TRMM Science Data and Information System (TSDIS) produces, at the direction of the Joint TRMM Science Team, a number of instantaneous rainfall products. The TRMM Microwave Imager (TMI), the Precipitation Radar and a Combined TMI/PR are the key "instruments" used in this production. Each of these products contains an entire orbit of data. The algorithm code computes not just rain rates but a large number of other physical parameters as well as information needed for monitoring algorithm performance. That makes these products very large. For example, a single orbit of TMI rain rate product is 99 MB, a single orbit of the combined product yields a granule that is 158 MB, while the 80 vertical levels of rain information from the PR yields an orbital product of 253 MB. These are large products that are often difficult for science users to electronically transfer to their sites especially if they want a large period of time. Level 3 gridded products are much smaller, but their 5 or 30 day temporal resolution is insufficient for many researchers. In addition, TRMM standard products are produced in the HDF format. While a large number of user-friendly tools are available to hide the details of the format (including a toolkit developed at TSDIS for the TRMM science team), many potential users shy away

Stocker, Erich↗
NASA NTRSDate not supplied

TPSAS-NF1676L-29139-DND

The Arctic has been warming at a rate outpacing globally-averaged warming by 2-3 times, a phenomenon known as "Arctic Amplification" (AA). AA is evident in observations of Arctic surface temperature over the last century as well as in model predictions. The accuracy of model predictions is crucial to determine our response to climate change, as Arctic changes have consequences for the atmospheric circulation, sea level rise, and the carbon cycle. Unfortunately, models show a wide range of possible futures and intermodel spread in projections of Arctic temperature is larger than for any other region: a 2°C global temperature increase- the limit set by the Paris Climate Agreement- would lead to an Arctic temperature change between 3-7°C according to Coupled Model Intercomparison 5 (CMIP5) models. This intermodel spread represents a key deficiency in the understanding of Arctic feedback processes and how changes in various physical parameters (e.g. sea ice cover, clouds, heat transport and surface fluxes) affect the temperature response. Using a process-oriented decomposition of the simulate Arctic surface energy budget, we attribute the largest contribution to the CMIP5 intermodel spead in projected Arctic warming to the Barents-Kara Sea region. Our results reveal that the increasing seasonal fluxing of ocean heat content is a significant part of the intermodel spread in AA and relates strongly to change in surface turbulent fluxes. Our results indicate that if we are to significantly reduce the intermodel spread in projected AA we must focus on understanding the behavior and physical processes that drive surface energy flows in the B-K sea region.

Patrick Taylor↗
NASA NTRSDate not supplied

3d Particle Geometry Characterization of Apollo Regolith Samples Via Laser Diffraction and Dynamic Image Analysis

Establishing a fundamental understanding of regolith mechanics hinges on the characterization of the foundational physical parameters that dictate granular particle interactions both on micro- and macro-scales. Specifically, particle size distribution, particle geometry and grain density govern the geotechnical properties, including compressibility, shear strength, hydraulic conductivity (i.e., permeability), void ratio (i.e., porosity), and thermal conductivity of the lunar regolith. The absence of terrestrial geologic processes on the lunar surface, a lack of water, clay minerals, and organic material in lunar soils, and the narrow compositional range in terms of mineral diversity of the regolith produces a unique problem when attempting to project terrestrial soil mechanics concepts to the lunar surface. Additionally, the occurrence of agglutinates, exclusive to the lunar surface, further disassociates the physical behavior (e.g., particle crushability, flowability, etc.) of regolith from that observed in terrestrial soils.

R. Kovtun↗
DOE OSTI2020

Achievements and Ongoing Challenges for advanced CFD Boiling Closure Model Development using Physical Insights from Validation-Oriented High-Fidelity Boiling Experiment

The fundamental understanding of the boiling-associated heat transfer, including sliding bubble effect, is still challenging despite the intensive research for decades in both experimental and computational boiling research communities. One of the main difficulties of boiling experiment come from the fact that direct observation of the underlying principle through experiment is very difficult due to the high complexity of the boiling phenomenon. Also, since the heat transfer characteristics associated with boiling is the result of non-linear interaction of various physical parameters coupled to each other, it is challenging to find the relationship between the parameters for modeling. This paper discusses the authors’ past and ongoing boiling research under CASL (Consortium for Advanced Simulation of Light Water Reactors) program, including the efforts to overcome the difficulties of boiling measurement and model development. In particular, we focus on describing the major achievements, lessons learnt, and ongoing challenges for the CFD boiling closure model development based on the high-fidelity subcooled flow boiling experiment at Texas A&M University (TAMU). The major research achievements discussed through this paper include (i) novel boiling measurement strategy and high-fidelity validation data production, (ii) dedicated effort to identify the critical measurement issues in boiling experiment, (iii) new physical insight into sliding bubble heat transfer mechanisms, and (iv) new boiling closure model development. Discussion is also made on the ongoing challenges for the boiling closure model development and the future research plan based on the lessons learnt.

42 ENGINEERING↗
NASA NTRSDate not supplied

Curvature, Variable Density and Compressibility Effects in Turbulent Shear Layers

The combined effects of variable density, curvature, and convective Mach number on turbulence in time-developing free shear layers are studied using turbulence-resolving simulations. The range of parameters considered include the convective Mach number at 0.2 and 0.8, the density ratio at 1/7, 1 and 7, and the level of streamwise curvature, measured by the shear layer thickness ratio to the radius of curvature at 0.001 and 0.01. Simulations at the limit of zero curvature exhibit mean profiles and turbulent stresses comparable with previously simulated planar (non-curved) shear layers. Growth rate changes depending on compressibility, curvature and density ratio are compared with expected behavior and unexpected trends due to combined effects are investigated. Standard turbulent shear layer statistics are presented, including spreading rates, turbulent stresses, and stress budgets to characterize individual and combined effects of the selected physical parameters.

shear layer↗
DOE OSTI2025

Quantum‐Classical Simulation of Quantum Field Theory by Quantum Circuit Learning

Abstract Quantum circuit learning is employed to simulate quantum field theories (QFTs). Typically, when simulating QFTs with quantum computers, significant challenges are encountered due to the technical limitations of quantum devices when implementing the Hamiltonian using Pauli spin matrices. To address this challenge, quantum circuit learning is leveraged, employing a compact configuration of qubits and low‐depth quantum circuits to predict real‐time dynamics in quantum field theories. The key advantage of this approach is that a single‐qubit measurement can accurately forecast various physical parameters, including fully‐connected operators. To demonstrate the effectiveness of this method, it is used to predict quench dynamics, chiral dynamics and jet production in a 1+1‐dimensional model of quantum electrodynamics. It is found that our predictions closely align with the results of rigorous classical calculations, exhibiting a high degree of accuracy. This hybrid quantum‐classical approach illustrates the feasibility of efficiently simulating large‐scale QFTs on cutting‐edge quantum devices.

Ikeda, Kazuki [Department of Physics University of↗
DOE OSTI2022

Size Effect of Local Current-Voltage Characteristics of MX 2 Nanoflakes: Local Density of States Reconstruction from Scanning Tunneling Microscopy Experiments

Local current-voltage characteristics for low-dimensional transition-metal dichalcogenides (LDTMD), as well as the reconstruction of their local density of states (LDOS) from scanning tunneling microscopy (STM) experiments, are of fundamental interest and can be useful for advanced applications. Most of the existing models either have limited applicability for complex-shaped LDTMDs (e.g., those based on the Simmons approach) or require solving of an ill-defined integral equation to deconvolute the unknown LDOS (e.g., those based on the Tersoff approach). Using a serial expansion of the Tersoff formulas, we propose a flexible method to reconstruct the LDOS from local current-voltage characteristics measured in STM experiments. We establish a set of key physical parameters, which characterize the tunneling current of a STM-probe–sample contact and the sample LDOS expanded in Gaussian functions. Using a direct variational method coupled with probabilistic analysis, we determine these parameters from the STM experiments for MoS2 nanoflakes with different numbers of layers. The main result is the reconstruction of the LDOS in a relatively wide energy range around the Fermi level, which allows us to gain insight into the local band structure of LDTMDs. The reconstructed LDOS reveal pronounced size effects for the single-layer, two-layer, and three-layer MoS 2 nanoflakes, which we relate to the low dimensionality and strong bending or corrugation of the nanoflakes. We hope that the proposed elaboration of the Tersoff approach, allowing LDOS reconstruction, will be of critical interest for the quantitative description of STM experiments and also of use to better understand the microscopic physical aspects of the surface, strain, and bending contributions to the LDTMDs’ electronic properties.

42 ENGINEERING↗
DOE OSTI2021

Effects of negative triangularity shaping on energetic particle driven Alfvén eigenmodes in DIII-D

Shape variations from positive to negative triangularity may lead to improved performance regimes in a tokamak with a reduction in microturbulence as well as improved thermal confinement. The motivation of this investigation is to model and compare the neutral beam driven Alfvén eigenmode (AE) activity in two DIII-D discharges with positive and negative triangularity shaping of plasma. The simulations are performed using the linear version of the FAR3d code, which solves the reduced MHD equations for thermal plasma with addition of moment equations for the energetic ion density and parallel velocity with appropriate Landau closure relations. Overall, our numerical results indicate that for similar physical parameters, the unstable AEs observed in the negative triangularity case have lower growth rates as compared to the positive triangularity regime. Our findings may be useful to analyze the influence of the reverse-D like geometry on the AE instabilities in DIII-D and may lead to better configurations for minimizing fast ion losses in a tokamak device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

H i -rich but low star formation galaxies in MaNGA: physical properties and comparison to control samples

ABSTRACT Gas-rich galaxies are typically star forming. We make use of H i-MaNGA, a programme of H i follow-up for the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey of the Sloan Digital Sky Surveys, to construct a sample of unusual neutral hydrogen (H i, 21 cm)-rich galaxies that have low star formation rates (SFRs), using infrared colour from the Wide-field Infrared Survey Explorer as a proxy for specific SFR. Out of a set of 1575 MaNGA galaxies with H i-MaNGA detections, we find that 83 (5 per cent) meet our selection criteria to be H i rich with low SFR. We construct two stellar mass-matched control samples: H i-rich galaxies with typical SFR (high SF control) and H i-poor galaxies with low SFR (low H i control). We investigate the properties of each of these samples, comparing physical parameters such as ionization state maps, stellar and ionized gas velocity and dispersion, environment measures, metallicity, and morphology to search for the reasons why these unusual H i-rich galaxies are not forming stars. We find evidence for recent external accretion of gas in some galaxies (via high counter-rotating fractions), along with some evidence for active galactic nucleus (AGN) feedback (from a high central low-ionization emission-line region and/or red geyser fraction), and bar quenching (via an enhanced strong bar fraction). Some galaxies in the sample are consistent with simply having their H i in a high angular momentum, large-radius, low-density disc. We conclude that no single physical process can explain all H i-rich, low-SFR galaxies.

Astronomy & Astrophysics↗
DOE OSTI2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network

Solar energetic particles (SEPs) are an essential source of space radiation, and are hazardous for humans in space, spacecraft, and technology in general. In this paper, we propose a deep-learning method, specifically a bidirectional long short-term memory (biLSTM) network, to predict if an active region (AR) would produce an SEP event given that (i) the AR will produce an M- or X-class flare and a coronal mass ejection (CME) associated with the flare, or (ii) the AR will produce an M- or X-class flare regardless of whether or not the flare is associated with a CME. The data samples used in this study are collected from the Geostationary Operational Environmental Satellite's X-ray flare catalogs provided by the National Centers for Environmental Information. We select M- and X-class flares with identified ARs in the catalogs for the period between 2010 and 2021, and find the associations of flares, CMEs, and SEPs in the Space Weather Database of Notifications, Knowledge, Information during the same period. Each data sample contains physical parameters collected from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Experimental results based on different performance metrics demonstrate that the proposed biLSTM network is better than related machine-learning algorithms for the two SEP prediction tasks studied here. We also discuss extensions of our approach for probabilistic forecasting and calibration with empirical evaluation

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Integrated package of electron cyclotron emission imaging data processing and forward modeling in OMFIT

An Electron Cyclotron Emission Imaging (ECEI) data analysis module has been developed for the OMFIT platform to accommodate the needs of users at the DIII-D tokamak for physics applications. The user can easily access the ECEI spatial observation windows in the plasma that are calculated based on the automatically retrieved hardware setup and available DIII-D equilibria, perform spectral analysis, and make 2D electron temperature fluctuation images. The module provides a powerful data post processing package for extracting important physics parameters from the 2D measurements, including the radial structure and poloidal mode number of Alfven Eigenmodes, as well as the frequency-vs-wavenumber dispersion relationship of broadband MHD. Lastly, the module propagates characterized synthetic fluctuations for the user, so one can perform forward modeling tasks with simple analytical fluctuations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2009

Physics of Reconnection and MMS Mission

Reconnection is the most important process driving the Earth's magnetosphere. Key to the success of the MMS science plan is the coupling of theory and observation. Determining the kinetic processes occurring in the diffusion region and physical parameters that control the rate of magnetic reconnection are among primary objectives of the MMS mission. Analysis of the role played by particle inertial effects in the diffusion region where the plasma is unmagnetized will be presented. The reconnection electric field in he diffusion region is supported primarily by particle non-gyrotropic effects. At the quasi-steady stage the reconnection electric field serves to accelerate and heat the incoming plasma population to maintain the current flow in the diffusion region the pressure balance. The primary mechanism controlling the dissipation in the vicinity of the reconnection site is incorporated into the fluid description in terms of non-gyrotropic corrections to the. induction and energy equations. The results of kinetic and fluid simulations illustrating the physics of magnetic reconnection will be presented. We will dem~:tistrate that kinetic nongyrotropic effects can significantly alter the global magnetosphere evolution and location of reconnection sites.

Kuznetsova, M. M.↗
DOE OSTI2023

Anisotropic magneto-resistivity and magnetocaloric effect in DyAl 2

Here, in this study, we experimentally and theoretically investigate the correlation between the anisotropic magnetic resistivity and magnetocaloric effect in DyAl 2 single crystals. DyAl 2 crystallizes in the C15 Laves phase structure with cubic symmetry. While some earlier studies revealed that the isothermal entropy change in dialuminides follows a similar trend as the electrical resistivity change as a function of temperature and magnetic field, the correlation between anisotropic behavior of these two physical parameters is yet to be explored to the best of our knowledge. To address this gap, we measured electrical resistivity of DyAl 2 single crystals along two different directions in zero and applied magnetic fields and compared the experimental results with our theoretical model. For the theoretical analysis, we employed a model Hamiltonian in the mean-field approximation, considering the exchange interaction, Zeeman effect, and crystalline electric field associated with the cubic symmetry. Our findings reveal a significant dependence of DyAl 2 resistivity on the direction of the applied magnetic field, in agreement with our theoretical results. These outcomes emphasize the interplay between magnetocaloric effect and magneto-resistivity, underscoring the potential of the magnetocaloric effect as a valuable tool for gaining deeper insights into basic physical properties including electron transport behavior.

36 MATERIALS SCIENCE↗