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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗
NASA NTRSDate not supplied

MAGIC Mission Science and Applications Related to Cryosphere, Solid Earth and Neutral Atmosphere

The GRACE and GFO missions have revolutionised our understanding of mass movement at and below the surface of the Earth but they, nonetheless, have restrictions related to spatial and temporal resolution and instrument sensitivity that limits our ability to resolve certain processes. In this presentation we focus on the advances and capabilities that the proposed Mass change And Geosciences International Constellation (MAGIC) mission will deliver for cryosphere and solid Earth applications and will also consider the potential it will have for studying the neutral atmosphere. The time-varying gravity missions to date have had an effective spatial resolution of ~300 km, which is larger than the scale of any glacier or ice caps and larger than most catchments on the Greenland Ice Sheet. Even over Antarctica, the limited spatial resolution is a major limitation for regions such as the Antarctic Peninsula. Tectonic process, such as Earthquakes, volcanic activity and even viscous mantle flow can take place on scales smaller than can be resolved currently. The target resolution and accuracy for MAGIC over ice is 170 km at 2.6 mm/yr EWH over the long term and 250 km at 5.5 mm EWH at monthly resolution plus lower accuracy daily to weekly capabilities. We consider here what this means for understanding and observing ice mass exchange with the oceans and improving our ability to measure the manometric contribution to sea level rise. Based on similar targets, we also explore the improvements this offers for monitoring different types of solid Earth processes including geohazards, crustal evolution and deep interior properties and dynamics. We also consider what contributions MAGIC will be able to make to observations of thermosphere neutral density and related atmospheric parameters.

Jonathan Bamber↗
NASA NTRSDate not supplied

Lunar Lander Landing Modeling and Simulation in Simscape

The landing gear is a critical subsystem of a lander for a successful landing on the moon or a planet. During a landing event, structural loading, energy absorption and toppling stability are important factors for the landing gear development. These aspects can be studied using simulations. The landing gear comprising the primary struct, secondary structs, footpad, and joints, is easily modeled using Simscape Multibody toolbox. The energy absorption mechanisms in the structs is readily modeled using Simulink and Multibody blocks based on the relative motions of the inner and outer cylinder of the structures. During touchdown, the footpads strike the lunar surface, and the contact forces can be modeled including the soil mechanical properties. Slosh dynamics are included using a mechanical pendulum model. Tip-over controllers are developed using Simulink blocks and toolboxes. This model was intensively tested manually then additionally with Monte Carlo simulation. It offers the opportunity for landing stability study, i.e. the max slope a lander can land without tipping over in 3D realistic landing situations.

Wei Wu↗
DOE OSTI2013

Simulations of Microchannel Plate Sensitivity to <20 keV X-rays as a Function of Energy and Incident Angle

We present results of Monte Carlo simulations of microchannel plate (MCP) response to x-rays in the 250 eV to 20 keV energy range as a function of both x-ray energy and impact angle. The model is based on the model presented in Rochau et al. (2006). However, while the Rochau et al. (2006) model was two-dimensional, and their results only went to 5 keV, our results have been expanded to 20 keV, and our model has been incorporated into a three-dimensional Monte Carlo MCP model that we have developed over the past several years (Kruschwitz et al. 2011). X-ray penetration through multiple MCP pore walls is increasingly important above 5 keV. The effect of x-ray penetration through multiple pores on MCP performance was studied and is presented.

materials properties, dynamic shock, equation of s↗
DOE OSTI2014

MLCT excited states at interfaces and in rigid media: Applications in energy conversion

In this proposal for continued support from the DOE, we propose to build on our understanding of light-driven electron transfer by molecules and molecular assemblies on oxide surfaces. We will conduct a systematic investigation of injection and back electron transfer dynamics on the surfaces of thin (1-10 μm), mesoporous, transparent conducting oxide films consisting of 10-20 nm tin-doped indium oxide (Sn:In2O3, ITO)) nanoparticles. These materials are unique because they mimic the morphology, surface area, and oxide nature of conventional mesoporous, nanocrystalline metal oxide thin films such as TiO 2 , SnO2, and NiO used in DSSC and DSPEC applications but they are conductive with high electron mobilities (0.1-10 cm2 V-1 s-1) and conductivities (101-104 Ω-1 cm-1) over a wide range of applied potentials. Their high conductivities and metallic behavior allow the Fermi level at nanoparticle surfaces to be tuned systematically by varying an applied bias. We will investigate injection, intra-assembly, and back electron transfer dynamics on nanoITO by transient absorption measurements on the picosecond to millisecond timescales. One series of experiments will build on initial results from DOE-supported research and focus on the bias- and medium-dependence of interfacial electron transfer by surface-bound molecular chromophores to investigate: i) the bias dependence of injection and back electron transfer, ii) injection by short-lived, otherwise inaccessible excited-states, and iii) medium effects. In parallel, we will investigate the dynamic interfacial properties of nanoITO-bound molecular assemblies designed for photogalvanic solar energy conversion. These studies will focus on surface-prepared, layer-by-layer donor-chromophore-acceptor assemblies in which inter-molecular excited-state quenching leads to redox separation as opposed to interfacial electron transfer quenching by the semiconductor material. Transient absorption measurements performed on nanoITO|-acceptor-chromophore-donor (photogalvanic anode) and nanoITO|-donor-chromophore-acceptor (photogalvanic cathode) assemblies will be used to explore: i) light-induced intermolecular electron transfer in layer-by-layer assemblies and ii) bias dependence on transient redox energy storage and long range (>5 nm) electron transfer reactions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Role of Cyclic Phase Transitions in Additive Manufacturing of Metals and Alloys - Lessons Learned from Welding Science

Additive manufacturing (also known as 3D printing) of metals is considered to be a disruptive technology, able to produce limited number of high value components with topologically optimized geometries and functionalities. Realization of the above potential for real-world applications is stifled by lack of standard computational design tools; component certifications, varied starting powder feed stock compositions, methods to probe thermomechanical processes, microstructural homogeneity, residual stress, as well as, anisotropic static- and dynamic-material properties. Detailed research of direct energy deposition, laser- and electron-powder bed additive manufacturing demonstrates that the underlying physics of these processes are very similar to welding, except for complex boundary conditions. This paper will review published literature and on-going research with reference to fundamental aspects of heat and mass transfer, solidification under large (103 to 105 K/m) thermal gradients and (10-3 to 100 m/s) liquid solid-interface velocities, as well as, solid->solid transformation under repeated thermal excursions. Case studies on model based qualification of Ni- and Ti- alloy builds made by additive manufacturing (AM), based on the above fundamental knowledge will be discussed.

Babu, Sudarsanam Suresh↗
DOE OSTI2021

Electron-Ion Collider - science and concept

Quantum Chromodynamics (QCD) is the fundamental quantum theory of quarks and gluons that make up almost all the visible matter in the universe. Quarks interact by exchanging gluons, but gluons also interact with gluons, a unique feature of QCD. Despite being so central to QCD, the properties and dynamics of gluons remain largely unexplored. The inspiration to solve the profound mysteries surrounding this ‘glue’ drives the development of a next-generation facility, the Electron-Ion Collider (EIC).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Machine learning-enabled model-data integration for predicting subsurface water storage

Subsurface water storage (SWS) is a key variable of the climate system and a storage component for precipitation and radiation anomalies, inducing persistence in the climate system. It plays a critical role in climate-change projections and can mitigate the impacts of climate change on ecosystems. However, because of the difficult accessibility of the underground, hydrologic properties and dynamics of SWS are poorly known. Direct observations of SWS are limited, and accurate incorporation of SWS dynamics into Earth system land models remains challenging. We propose a machine learning-enabled model-data integration framework to improve the SWS prediction at local to conus scales in a changing climate by leveraging all the available observation and simulation resources, as well as to inform the model development and guide the observation collection. The accurate prediction will enable an optimal decision of water management and land use and improve the ecosystem's resilience to the climate change.

Lu, Dan↗
DOE OSTI2022

SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning

While cycle-accurate simulators are essential tools for architecture research, design, and development, their practicality is limited by an extremely long time-to-solution for realistic applications under investigation. This work describes a concerted effort, where machine learning (ML) is used to accelerate microarchitecture simulation. First, an ML-based instruction latency prediction framework that accounts for both static instruction properties and dynamic processor states is constructed. Then, a GPU-accelerated parallel simulator is implemented based on the proposed instruction latency predictor, and its simulation accuracy and throughput are validated and evaluated against a state-of-the-art simulator. Leveraging modern GPUs, the ML-based simulator outperforms traditional CPU-based simulators significantly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Assessing Melting and Solid–Solid Transition Properties of Choline Chloride via Molecular Dynamics Simulations

Choline chloride (ChCl) is used extensively as a hydrogen bond donor in deep eutectic solvents (DESs). However, determining its melting properties experimentally is challenging due to decomposition upon melting, leading to widely varying literature values. Accurate melting properties are crucial for understanding the solid–liquid phase behavior of ChCl-containing DESs. Here, we employ molecular dynamics simulations to compute the phase transitions of ChCl, testing a variety of atomistic force fields. We find that the results are sensitive to the choice of force field, but a melting temperature of 627 K and a melting enthalpy of 7.8 kJ/mol seem most reasonable, in good agreement with some literature values. Furthermore, we suggest these as the likely melting properties of ChCl, though the results are tentative due to limited experimental data for the liquid ChCl phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Experimental evidence for dynamic friction on rock fractures from frequency-dependent nonlinear hysteresis and harmonic generation: Low-Frequency Torsional Dynamic Friction

Frictional properties affect the propagation of high-amplitude seismic waves across rock fractures and faults. Laboratory evidence suggests that these properties can be measured in active seismic surveys, potentially offering a route to characterizing friction in situ. Here, we present experimental results from a subresonance torsional modulus and attenuation apparatus that utilizes micron-scale sinusoidal oscillations to probe the nonlinear stress-strain relation at a range of strain amplitudes and rates. Nonlinear effects are further quantified using harmonic distortion; however, time series data best illuminate underlying physical processes. The low-frequency stress-strain hysteretic loops show stiffening at the sinusoid's static ends, but stiffening is reduced above a threshold frequency. This shape is determined by harmonic generation in the strain; the stress signal has no harmonics, confirming that the fractured sample is the source of the nonlinearity. These qualitative observations suggest the presence of rate-dependent friction and are consistent between fractures in three different rock types. We propose that static friction at the low strain rate part of the cycle, when given sufficient “healing” time at low oscillation frequencies, causes this stiffening cusp shape in the hysteresis loop. While rate-and-state friction is commonly used to represent dynamic friction, it cannot capture static friction or negative slip velocities. So we implement another dynamic friction model, based on the work of Dahl, which describes this process and produces similar results. Since the two models have a similar form, parameterizations of field data could constraint fault model inputs, such as specific location velocity strengthening or weakening properties.

58 GEOSCIENCES↗
DOE OSTI2021

Predicting the Dissolution Rate of Borosilicate Glasses using QSPR analysis based on molecular dynamics simulations

Quantitative Structure Property Relationship (QSPR) analysis based on molecular dynamics (MD) simulations is a promising approach for establishing the composition-property relationships of glass and other materials with complex structures. A series of 20 borosilicate and boroaluminosilicate glasses have been modeled by using MD simulations with recently developed effective potentials. Short- and medium-range structures of these glasses were analyzed and, based on these structural information, QSPR analysis of the initial dissolution rate (r0) was made and compared with measured r0 at 90°C and pH 9 using various structural descriptors such as percentage of bridging oxygen species, network connectivity and average ring size. The structural descriptors, Fnet, containing energetic information such as single bond strength and other structural information were also used. It was found that overall network connectivity, average ring size and Fnet give reasonable predictions of the r0 of studied glasses, given the conditions that the glasses are homogeneous and dissolve congruently. Modifying glass compositions to account preferential release of modifiers gives a better prediction for incongruently dissolving glasses. The results were compared with our recent work of predicting glass dissolution behavior from compositions using the topological-constraints-based models.

Du, Jincheng↗
NASA NTRS1986

Chaos and nonlinear dynamics of single-particle orbits in a magnetotaillike magnetic field

The properties of charged-particle motion in Hamiltonian dynamics are studied in a magnetotaillike magnetic field configuration. It is shown by numerical integration of the equation of motion that the system is generally nonintegrable and that the particle motion can be classified into three distinct types of orbits: bounded integrable orbits, unbounded stochastic orbits, and unbounded transient orbits. It is also shown that different regions of the phase space exhibit qualitatively different responses to external influences. The concept of 'differential memory' in single-particle distributions is proposed. Physical implications for the dynamical properties of the magnetotail plasmas and the possible generation of non-Maxwellian features in the distribution functions are discussed.

Chen, J.↗
DOE OSTI2020

Elastic Properties of Plasma-Exposed Tungsten Predicted by Molecular-Dynamics Simulations

We report results of systematic molecular-dynamics computations of the elastic properties of single-crystalline tungsten containing structural defects, voids and overpressurized He nanobubbles, related to plasma exposure of tungsten serving as a plasma- facing component (PFC) in nuclear fusion devices. Our computations reveal that the empty voids are centers of dilatation resulting in development of tensile stress in the tungsten matrix, whereas He-filled voids (nanobubbles) introduce compressive stress in the plasma-exposed tungsten. We find that the dependence of the elastic moduli of plasma-exposed tungsten, namely, the bulk, Young, and shear modulus, on its void fraction follows a universal exponential scaling relation. We also find that the elastic moduli of plasma-exposed tungsten soften substantially as a function of He content in the tungsten matrix, following an exponential scaling relation; this He-induced exponential softening is in addition to the softening caused in the matrix with increasing temperature. A systematic characterization of the dependence of the elastic moduli on the He bubble size reveals that He bubble growth affects significantly both the bulk modulus and the Poisson ratio of plasma-exposed tungsten, while its effect on the Young and shear moduli of the plasma-exposed material is weak. Our findings contribute directly to the development of a structure-properties database that is required for the predictive modeling of the dynamical response of PFCs in nuclear fusion devices.

36 MATERIALS SCIENCE↗