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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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Focal Area(s) Using artificial intelligence to understand the physics of hydrologic events across temporal and spatial scales, to assess their representation in climate models, and to predict their response to climate warming. This covers both the prescribed foci of (2) predictive modeling using a hierarchy of models and (3) insight gleaned from complex data.
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Motivated by the needs of the high-voltage power transmission industry, we use data from the high-latitude IMAGE magnetometer array to study characteristics of extreme geoelectric fields at regional scales. We use 10-s resolution data for years 1993-2013, and the fields are characterized using average horizontal geoelectric field amplitudes taken over station groups that span about 500-km distance. We show that geoelectric field structures associated with localized extremes at single stations can be greatly different from structures associated with regionally uniform geoelectric fields, which are well represented by spatial averages over single stations. Visual extrapolation and rigorous extreme value analysis of spatially averaged fields indicate that the expected range for 1-in-100-year extreme events are 3-8 V/km and 3.4-7.1 V/km, respectively. The Quebec reference ground model is used in the calculations.
The global energy system is undergoing significant changes, including a shift in energy generating technologies to more renewable energy sources. However, the dependence of renewable energy sources on local environmental conditions could also increase disruptions in service through exposures to compound, extreme weather events. By fusing three diverse datasets (operations and maintenance tickets, weather data, and production data), this analysis presents a novel methodology to identify and evaluate performance impacts arising from extreme weather events across diverse geographical regions. Text analysis of maintenance tickets identified snow, hurricanes, and storms as the leading extreme weather events affecting photovoltaic plants in the United States. Statistical techniques and machine learning were then implemented to identify the magnitude and variability of these extreme weather impacts on site performance. Impacts varied between event and non-event days, with snow events causing the greatest reductions in performance (54.5%), followed by hurricanes (12.6%) and storms (1.1%). Machine learning analysis identified key features in determining if a day is categorized as low performing, such as low irradiance, geographic location, weather features, and site size. The analysis improves our understanding of compound, extreme weather event impacts on photovoltaic systems, which can inform planning activities, especially as the industry continues to expand into new geographic and climatic regions around the world.
Extreme fast charging of electric vehicles technologies is coming. Heavy duty electric vehicles (HD-EVs) are in development and are expected to have multipliers bigger in battery capacity compared to the light duty counterparts. To meet short charging times, MW charging will be necessary. This paper presents a MW scale extreme DC fast charger with a communication and control architecture for HD-EVs. The system is validated in a controller hardware in the loop platform.
Realizing extreme fast charging (XFC) in lithium-ion batteries for electric vehicles is still challenging due to the insufficient lithium-ion transport kinetics, especially in the electrolyte. Herein, a novel high-performance electrolyte (HPE) consisting of lithium bis(fluorosulfonyl)imide (LiFSI), lithium hexafluorophosphate (LiPF 6 ) and carbonates is proposed and tested in pilot-scale, 2-Ah pouch cells. Moreover, the origin of improved electrochemical performance is comprehensively studied via various characterizations, suggesting that the proposed HPE exhibits high ionic conductivity and excellent electrochemical stability at high charging rate of 6-C. Furthermore, the HPE-based pouch cells deliver improved discharge specific capacity and excellent long-term cyclability up to 1500 cycles under XFC conditions, which is superior to the conventional state-of-the-art baseline electrolyte.
Electrode-scale heterogeneity can combine with complex electrochemical interactions to impede lithium-ion battery performance, particularly during fast charging. This research investigates the influence of electrode heterogeneity at different scales on the lithium-ion battery electrochemical performance under operational extremes. We employ image-based mesoscale simulation in conjunction with a three-dimensional electrochemical model to predict performance variability in 14 graphite electrode X-ray computed tomography data sets. Our analysis reveals that the tortuous anisotropy stemming from the variable particle morphology has a dominating influence on the overall cell performance. Cells with platelet morphology achieve lower capacity, higher heat generation rates, and severe plating under extreme fast charge conditions. On the contrary, the heterogeneity due to the active material clustering alone has minimal impact. Our work suggests that manufacturing electrodes with more homogeneous and isotropic particle morphology will improve electrochemical performance and improve safety, enabling electromobility.
For the last 5 years Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom line outcome would be to provide a state-of-the-art compression algorithm that surpasses those currently available in the ROOT framework, with the purpose of enabling substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4.In this contribution, we will present our concepts of “functionally lossless compression”, have a glance at examples and achievements in other communities, present the results and outcome of our current, ongoing R&D, as well as present a high-level view of our plan to move forward with a ROOT implementation that would deliver a basic solution readily integrated into HENP applications. As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility.
Two figures are shown: Pressure dependence of the shear modulus of Ta for two fundamental curves: the 300 K isotherm and the Hugoniot; and, Scaling of the high pressure strength (Y) of Ta with shear modulus (G). The dashed curve represents a hypothetical G which is fit such that the linear scaling approximation matches the data.
Echoes from the near-earth object 1986 DA show it to be significantly more reflective than other radar-detected asteroids. This result supports the hypothesis that 1986 DA is a piece of NiFe metal derived from the interior of a much larger object that melted, differentiated, cooled, and subsequently was disrupted in a catastrophic collision. This 2-kilometer asteroid, which appears smooth at centimeter to meter scales but extremely irregular at 10- to 100-meter scales, might be (or have been a part of) the parent body of some iron meteorites.
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Abstract While extreme precipitation is expected to increase in a warming climate, its scaling with temperature at weather timescales often produces puzzling results. Here, we focus on the summer months over the central U.S. to investigate the scaling of extreme precipitation intensity (EPI) with local temperature and determine the contribution of mesoscale convective systems (MCSs) to the EPI scaling. Using an observational data set that differentiates precipitation associated with MCS and non‐MCS storms, we find that MCS storms contribute to 70% of EPI samples at temperatures lower than 298 K where EPI increases with temperature. However, at temperatures of 298–305 K, MCSs' contribution to EPI decreases as the predominant storm type shifts from MCS to non‐MCS storms, causing EPI to decrease with temperature due to the weaker rainfall intensity associated with non‐MCS storms compared with MCS storms. Our findings underscore the important role of different storm types in affecting the EPI scaling relationships.
Simulating black hole (BH) accretion and feedback from the BH horizon to galactic scales is extremely challenging, as it involves a vast range of scales. Recently, our multizone method has successfully achieved global dynamical steady states of hot accretion flows in 3D general relativistic magnetohydrodynamic simulations by tracking the bidirectional interaction between a nonspinning BH and its host galaxy. In this paper, we present technical improvements to the method and apply it to spin a * = 0.9 BHs, which power relativistic jets. We first test the new multizone setup with a smaller Bondi radius, R B ≈ 400 r g , where r g is the gravitational radius. The strongly magnetized accretion launches a relativistic jet with an intermediate feedback efficiency η ∼ 30%, in between that of a prograde (η ∼ 100%) and retrograde (η ∼ 10%) torus. Interestingly, both prograde and retrograde simulations also eventually converge to the same intermediate efficiency when evolved long enough, as accumulated magnetic fields remove gas rotation. We then extend strongly magnetized simulations to larger Bondi radii, R B ≈ 2 × 10 3 , 2 × 10 4 , 2 × 10 5 r g . We find that the BH accretion rate $\dot{M}$ is suppressed with respect to the Bondi rate as $\dot{M}_{\textrm{B}}$ as $\dot{M}/\dot{M}_{\textrm{B}} ∝ R_{\textrm{B}}^{-1/2}$. However, despite some variability, the time-averaged feedback efficiency remains at η ∼ 30%, independent of R B . This suggests that BH feedback efficiency in hot accretion flows is mainly governed by the BH spin (a * ) rather than by the galactic properties (R B ). From these first-principles simulations, we provide a feedback subgrid prescription for cosmological simulations: $\dot{E}_{\textrm{fb}} = 2$ x $10^{-3}[R_{\textrm{B}}/(2$ x $10^5 r_g)]^{-1/2}$ $\dot{M}_{\textrm{B}}c^2$ for BH spin a * = 0.9.
The number of radar detected asteroids has climbed from 6 to 40 (27 mainbelt plus 13 near-Earth). The dual-circular-polarization radar sample now comprises more than 1% of the numbered asteroids. Radar results for mainbelt asteroids furnish the first available information on the nature of these objects at macroscopic scales. At least one object (2 Pallas) and probably many others are extraordinarily smooth at centimeter-to-meter scales but are extremely rough at some scale between several meters and many kilometers. Pallas has essentially no small-scale structure within the uppermost several meters of the regolith, but the rms slope of this regolith exceeds 20 deg., much larger than typical lunar values (approx. 7 deg.). The origin of these slopes could be the hypervelocity impact cratering process, whose manifestations are likely to be different on low-gravity, low-radius-of-curvature objects from those on the terrestrial planets. The range of mainbelt asteroid radar albedoes is very broad and implies big variations in regolith porosity or metal concentration, or both. The highest albedo estimate, for 16 Psyche, is consistent with a surface having porosities typical of lunar soil and a composition nearly completely metallic. Therefore, Psyche might be the collisionally stripped core of a differentiated small plant, and might resemble mineralogically the parent bodies of iron meteorites.
Theoretical models predict that, in the absence of moisture limitation, extreme precipitation intensity could exponentially increase with temperatures at a rate determined by the Clausius-Clapeyron (C-C) relationship. Climate models project a continuous increase of precipitation extremes for the twenty-first century over most of the globe. However, some station observations suggest a negative scaling of extreme precipitation with very high temperatures, raising doubts about future increase of precipitation extremes. Here we show for the present-day climate over most of the globe,the curve relating daily precipitation extremes with local temperatures has a peak structure, increasing as expected at the low medium range of temperature variations but decreasing at high temperatures. However, this peak-shaped relationship does not imply a potential upper limit for future precipitation extremes. Climate models project both the peak of extreme precipitation and the temperature at which it peaks (T(sub peak)) will increase with warming; the two increases generally conform to the C-C scaling rate in mid- and high-latitudes,and to a super C-C scaling in most of the tropics. Because projected increases of local mean temperature (T(sub mean)) far exceed projected increases of T(sub peak) over land, the conventional approach of relating extreme precipitation to T(sub mean) produces a misleading sub-C-C scaling rate.
Recent progress in the development of dynamic strength experimental platforms is allowing for unprecedented insight into the assumptions used to construct constitutive models operating in extreme conditions. In this work, we make a quantitative assessment of how tantalum strength scales with its shear modulus to pressures of hundreds of gigapascals through a cross-platform examination of three dynamic strength experiments. Specifically, we make use of Split–Hopkinson pressure bar and Richtmyer–Meshkov instability experiments to assess the low-pressure strain and strain rate dependence. Concurrent examination of magnetically driven ramp-release experiments up to pressures of 350GPa allows us to examine the pressure dependence. In this work, using a modern description of the shear modulus, validated against both ab initio theory and experimental measurements, we then assess how the experimentally measured pressure dependence scales with shear modulus. Furthermore, we find that the common assumption of scaling strength linearly with the shear modulus is too soft at high pressures and offer discussion as to how descriptions of slip mediated plasticity could result in an alternative scaling that is consistent with the data.
The morphology, distribution, geologic environment and relative age of large-scale polygonal trough systems on Mars are examined. The troughs are steep-walled, flat-floored, sinuous depressions typically 200-800 m wide, 20-120 m deep and spaced 5-10 km apart. The mechanics of formation of tension cracks is reviewed to identify the factors controlling the scale of tension crack systems; special emphasis is placed on thermal cracking in permafrost. It is shown that because of the extremely large scale of the Martian fracture systems, they could not have formed by thermal cracking in permafrost, dessication cracking in sediments or contraction cracking in cooling lava. On the basis of photogeologic evidence and analog studies, it is proposed that polygonal troughs on the northern plains of Mars are grabens.
Transient, narrow plumes of strong water vapor transport, referred to as Atmospheric Rivers (ARs) are responsible for much of the precipitation along the west coast of the United States. Along the coast of Oregon and Washington, the most intense cool season precipitation events are almost always induced by an AR and can result in detrimental impacts on society due to mudslides and flooding. It is therefore important to understand the large scale influence on extreme AR events so that they can be accurately predicted on timescales ranging from numerical weather prediction to seasonal forecasts. Here, characteristics of ARs that result in observed extreme precipitation events are compared to typical ARs on the coast of Washington State using data from the Modern Era Retrospective analysis for Research and Applications, Version 2. In addition to more intense water vapor transport, notable differences in the synoptic scale forcing are present during extreme precipitation events that are not present during typical AR events. In particular, an anomalously deep low pressure system is stationed to the west in the Gulf of Alaska, alongside a jet streak overhead. Attention will also be given to subseasonal and seasonal teleconnection patterns that are known to influence the weather in the Pacific Northwest of the United States. While little influence can be seen from the phase of the El Nino Southern Oscillation, Pacific Decadal Oscillation, and Pacific North American Pattern, the Madden Julian Oscillation (MJO) can play a role in determining the strength of precipitation associated with in AR on the Washington Coast. Lastly, interactions between the MJO and other teleconnection patterns will be explored to determine key features that should be investigated when making subseasonal predictions for AR activity and the associated precipitation in the Pacific Northwest.