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At least 1,567 records · Page 87

Structure of Self-Generated Magnetic Fields in Laser-Solid Interaction from Proton Tomography

Self-generated magnetic fields in laser-solid interactions are experimentally characterized to reveal the 3D location and local field strength, rather than path-integrated quantities, using multi-view proton radiography and tomographic inversion. We infer magnetic fields that extend several millimeters off the target into the hot, rarefied corona, sufficient to strongly magnetize the plasma (Ω e τ e ≫ 1). The data are compared to MHD simulations incorporating recent improvements in modeling magnetic field generation and transport; the volume-averaged coronal field strength and magnetic flux agree to within 25% using a model with magnetic re-localization of transport, although the near-target morphology is not reproduced. This work demonstrates tomographic proton radiography as a valuable tool for investigating magnetic fields in laser-produced plasmas.

High-energy-density plasmas↗

Flux balance analysis of the ammonia-oxidizing bacterium Nitrosomonas europaea ATCC19718 unravels specific metabolic activities while degrading toxic compounds

The ammonia-oxidizing bacterium Nitrosomonas europaea has been widely recognized as an important player in the nitrogen cycle as well as one of the most abundant members in microbial communities for the treatment of industrial or sewage wastewater. Its natural metabolic versatility and extraordinary ability to degrade environmental pollutants (e.g., aromatic hydrocarbons such as benzene and toluene) enable it to thrive under various harsh environmental conditions. Constraint-based metabolic models constructed from genome sequences enable quantitative insight into the central and specialized metabolism within a target organism. These genome-scale models have been utilized to understand, optimize, and design new strategies for improved bioprocesses. Reduced modeling approaches have been used to elucidate Nitrosomonas europaea metabolism at a pathway level. However, genome-scale knowledge about the simultaneous oxidation of ammonia and pollutant metabolism of N . europaea remains limited. Here, we describe the reconstruction, manual curation, and validation of the genome-scale metabolic model for N . europaea , i GC535. This reconstruction is the most accurate metabolic model for a nitrifying organism to date, reaching an average prediction accuracy of over 90% under several growth conditions. The manually curated model can predict phenotypes under chemolithotrophic and chemolithoorganotrophic conditions while oxidating methane and wastewater pollutants. Calculated flux distributions under different trophic conditions show that several key pathways are affected by the type of carbon source available, including central carbon metabolism and energy production.

59 BASIC BIOLOGICAL SCIENCES↗

Three-dimensional shock wave-turbulent boundary layer interactions generated by a sharp fin at Mach 4

This paper describes a combined experimental and theoretical study of three-dimensional swept shock wave-turbulent boundary layer interactions at Mach 4 generated by a sharp fin of angles alpha equals 16 and 20 degrees. The theoretical model is the three-dimensional compressible Reynolds-averaged Navier-Stokes equations with turbulence incorporated through the algebraic eddy viscosity model of Baldwin and Lomax. Previous computations have been performed by Horstman using the Baldwin-Lomax, Cebeci-Smith and Jones Launder models. Computed results for the surface pressure, skin friction and streamline angles are compared with experiment and previous numerical results. The present results display good agreement with experimental data for surface pressure and surface flow direction. All turbulence models fail to accurately predict the peak skin friction. The computed flowfields are in agreement with many of the features of the quasi-conical flowfield model of Settles.

Knight, Doyle D.↗

Code Benchmark of Depressurized Conduction Cooldown Transient in the High Temperature Test Facility

This paper presents results from modeling of a depressurized conduction cooldown (DCC) transient at the High Temperature Test Facility (HTTF) as part of the OECD-NEA Thermal Hydraulics Code Validation Benchmark for High-Temperature Gas-Cooled Reactors using HTTF Data . This paper briefly describes the benchmark and the models being used. It then presents a comparison of steady state and transient results based on the Problem 2 Exercise 1A and 1B definitions. We compare block and helium temperature distributions, mass flow distribution, and energy balance in steady state. All models show comparable mass flow distributions and energy balances. The temperatures within the core and outer regions are comparable in all models too, but inner reflector temperatures can vary significantly. Despite that, we find that the models are in good agreement for the full-power steady state. In the DCC, we look at block temperature at the core midplane and RCCS water exit temperature. The INL and ANL models are found to be in excellent agreement with one another on block temperature over time, while the agreement when the KAERI and NRG models are added into consideration is good. Differences in the transient heat removal from the RCCS cause the differences in block temperature over time in these models. The CNL models show similar trends to the INL, ANL, KAERI, and NRG models, but the temperatures are high because the volumes used in calculating the average temperature include the heater rods in the CNL models only. The HUN-REN model shows results that suggest significantly lower heat removal in the RCCS which merit further investigation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mining Product Reviews for Important Product Features of Refurbished iPhones

Problem: Remanufacturers want to increase consumer interest in refurbished products, which motivates the need to understand which product features are important to buyers of refurbished products such as mobile phones. Research Questions: This study addresses two questions. First, which product features are most important for buyers of refurbished iPhones? Second, how do those preferences differ from the preferences of buyers of new iPhones? Methods: Online reviews of iPhones are obtained and converted into a document–term matrix. Using this text model, three subsets of features are identified using statistical analysis of frequency of mention: most frequent, average, and least frequent. A logistic regression (LR) model is then used to identify which features are most predictive of whether a review is for a new or refurbished phone. Results: Buyers of refurbished phones mention battery health, screen/display, shell condition, and brand significantly more often than other features. Directly contrasting reviews of refurbished versus new phones shows that shell condition, brand, speaker, and charger are found to be the most predictive product features indicated in reviews for refurbished phones. Of those, the shell condition is significantly more predictive than the others. Implications: The results identify product features that remanufacturers of iPhones can emphasize to increase customer demand.

Anisi, Atefeh↗

Near earth magnetic disturbance in total field at high latitudes. 2: Interpretation of data from OGO's 2, 4, and 6

Variations in the scalar magnetic field (delta B) from the polar orbiting OGO 2, 4, and 6 spacecraft, with supporting vector magnetic field data from surface observatories, were analyzed at dipole latitudes above 55 deg. Although individual satellite passes, at low altitudes, confirm the existence of electrojet currents, neither individual satellite passes nor contours of average delta B are consistent with latitudinally narrow electrojet currents as the principal source of delta B at the satellite. The ratio of delta B magnitudes in positive and negative regions is variable. The characteristics of the negative delta B region indicate a latitudinally broad ionospheric source. Comparison of the surface magnetic disturbance caused by the equivalent current with the measured average surface disturbance shows good agreement except in localized details. Because delta B decreases very slowly with altitude in the positive delta B region, it is not possible to account for this disturbance in terms of ionospheric currents. The contribution to the satellite delta B due to a model electrojet, which reproduced the measured average surface horizontal disturbance, was computed. Definitive identification of all sources of positive delta B is not possible at this time.

Langel, R. A.↗

A three-dimensional time-dependent model of the plasmasphere

A three-dimensional, time-dependent, nonlinear, hydrodynamic model of the plasmasphere has been developed which includes the self-consistent coupling of conjugate hemispheres within the plasmasphere as well as the effects of cross-L drifts due to convection electric fields. The inner region of the plasmasphere was modeled from an L of 1.5 to an L of 3.5 to 4.5, depending on local time. In this first study of the global plasmasphere, the model was run for solar minimum conditions until diurnally reproducible results were obtained, indicating that the plasmasphere was fully filled. The results of the model were then compared with applicable measurements of the plasmasphere. It was found that the model tends to overestimate densities somewhat, although it is within a factor of 2 of an average of June and December whistler observations. The model predicts densities within a factor of 2 of most of the satellite observations as well. As anticipated, the diurnal variation of the plasmasphere was found to depend on magnetic latitude. At low latitudes the diurnal variation in density was relatively small, with the largest densities occurring in the afternoon time sector. However, near the plasmapause, the effects of changes in volume of drifting tubes of plasma due to cross-L drifts led to a factor of 3 variation in equatorial density, with the highest densities occurring near local midnight where the volume was lowest. Various limitations of the current model and suggested improvements are also discussed.

Rasmussen, C. E.↗

Numerical simulation of crossing/turbulent boundary layer interaction at Mach 8.3 comparison of zero and two-equation turbulence models

A 3D hypersonic crossing shock wave/turbulent boundary layer interaction is examined numerically. The test geometry consists of a pair of opposing sharp fins of angle alpha = 15 deg mounted on a flat plate. The freestream Mach number is 8.28. Two theoretical models are evaluated. The full 3D Reynolds-averaged Navier-Stokes equations are solved using the Baldwin-Lomax algebraic turbulent eddy viscosity model and the Rodi turbulence model. Computed results for both cases show good agreement with experiment for flat plate surface pressure and for pitot pressure and yaw angle profiles in the flowfield. General agreement is obtained for surface flow direction. Fair to poor agreement is obtained for surface heat transfer, indicating a need for more accurate turbulence models. The overall flowfield structure is similar to that observed in previous crossing shock interaction studies.

Narayanswami, N.↗

Properties of radar backscatter of forests measured with a multifrequency polarimetric SAR

Fully polarimetric airborne synthetic aperture radar (AIRSAR) data, collected in Germany during the MAC Europe campaign, are calibrated using software packages developed at the Joint Research Center (JRC) in Italy for both L- and C-bands. During the period of the overflight dates, extensive ground truth was collected in order to describe the physical and statistical parameters of the canopy, the understory, and the soil. These parameters are compiled and converted into electromagnetic parameters suitable for input to the new polarimetric three-layer canopy model developed at the Wave Scattering Research Center (WSRC) at the University of Texas at Arlington. Comparisons between the theoretical predictions from the model and the calibrated data are carried out. Initial results reveal that the trend of the average phase difference can be predicted by the model, and that the backscattering ratio *shh/ svv is sensitive to the distribution of the primary branches.

Amar, F.↗

Characterizing and Mitigating Intraday Variability: Reconstructing Source Structure in Accreting Black Holes with mm-VLBI

The extraordinary physical resolution afforded by the Event Horizon Telescope has opened a window onto the astrophysical phenomena unfolding on horizon scales in two known black holes, M87* and Sgr A*. However, with this leap in resolution has come a new set of practical complications. Sgr A* exhibits intraday variability that violates the assumptions underlying Earth aperture synthesis, limiting traditional image reconstruction methods to short timescales and data sets with very sparse (u, v) coverage. We present a new set of tools to detect and mitigate this variability. We develop a data-driven, model-agnostic procedure to detect and characterize the spatial structure of intraday variability. This method is calibrated against a large set of mock data sets, producing an empirical estimator of the spatial power spectrum of the brightness fluctuations. We present a novel Bayesian noise modeling algorithm that simultaneously reconstructs an average image and statistical measure of the fluctuations about it using a parameterized form for the excess variance in the complex visibilities not otherwise explained by the statistical errors. These methods are validated using a variety of simulated data, including general relativistic magnetohydrodynamic simulations appropriate for Sgr A* and M87*. We find that the reconstructed source structure and variability are robust to changes in the underlying image model. We apply these methods to the 2017 EHT observations of M87*, finding evidence for variability across the EHT observing campaign. The variability mitigation strategies presented are widely applicable to very long baseline interferometry observations of variable sources generally, for which they provide a data-informed averaging procedure and natural characterization of inter-epoch image consistency.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluation of Industry Standard Turbulence Models on an Axisymmetric Supersonic Compression Corner

Reynolds-averaged Navier-Stokes computations of a shock-wave/boundary-layer interaction (SWBLI) created by a Mach 2.85 flow over an axisymmetric 30-degree compression corner were carried out. The objectives were to evaluate four turbulence models commonly used in industry, for SWBLIs, and to evaluate the suitability of this test case for use in further turbulence model benchmarking. The Spalart-Allmaras model, Menter's Baseline and Shear Stress Transport models, and a low-Reynolds number k- model were evaluated. Results indicate that the models do not accurately predict the separation location; with the SST model predicting the separation onset too early and the other models predicting the onset too late. Overall the Spalart-Allmaras model did the best job in matching the experimental data. However there is significant room for improvement, most notably in the prediction of the turbulent shear stress. Density data showed that the simulations did not accurately predict the thermal boundary layer upstream of the SWBLI. The effect of turbulent Prandtl number and wall temperature were studied in an attempt to improve this prediction and understand their effects on the interaction. The data showed that both parameters can significantly affect the separation size and location, but did not improve the agreement with the experiment. This case proved challenging to compute and should provide a good test for future turbulence modeling work.

Turbulent Boundary Layer↗

Kepler and TESS Observations of PG 1159-035

Abstract PG 1159-035 is the prototype of the PG 1159 hot (pre-)white dwarf pulsators. This important object was observed during the Kepler satellite K2 mission for 69 days in 59 s cadence mode and by the TESS satellite for 25 days in 20 s cadence mode. We present a detailed asteroseismic analysis of those data. We identify a total of 107 frequencies representing 32 ℓ = 1 modes, 27 frequencies representing 12 ℓ = 2 modes, and eight combination frequencies. The combination frequencies and the modes with very high k values represent new detections. The multiplet structure reveals an average splitting of 4.0 ± 0.4 μ Hz for ℓ = 1 and 6.8 ± 0.2 μ Hz for ℓ = 2, indicating a rotation period of 1.4 ± 0.1 days in the region of period formation. In the Fourier transform of the light curve, we find a significant peak at 8.904 ± 0.003 μ Hz suggesting a surface rotation period of 1.299 ± 0.002 days. We also present evidence that the observed periods change on timescales shorter than those predicted by current evolutionary models. Our asteroseismic analysis finds an average period spacing for ℓ = 1 of 21.28 ± 0.02 s. The ℓ = 2 modes have a mean spacing of 12.97 ± 0.4 s. We performed a detailed asteroseismic fit by comparing the observed periods with those of evolutionary models. The best-fit model has T eff = 129, 600 ± 11 100 K, M * = 0.565 ± 0.024 M ⊙ , and log g = 7.41 − 0.54 + 0.38 , within the uncertainties of the spectroscopic determinations. We argue for future improvements in the current models, e.g., on the overshooting in the He-burning stage, as the best-fit model does not predict excitation for all of the pulsations detected in PG 1159-035.

79 ASTRONOMY AND ASTROPHYSICS↗

An evaluation of the Tsyganenko magnetic field model

A data set of more than 22,000 vector averages of the magnetosphere magnetic field over 0.5 R(E) regions is used to evaluate Tsyganenko's 1982 and 1987 magnetospheric magnetic field models. The magnetic field predicted by the model in various regions is compared to observations to find systematic discrepancies which future models might address. While agreement is generally good, discrepancies are noted which include: (1) a lack of adequate field line stretching in the tail and ring current regions; (2) an inability to predict weak enough fields in the polar cusps; and (3) a deficiency of Kp as a predictor of the field configuration.

Fairfield, D. H.↗

Visible-infrared remote-sensing model and applications for ocean waters

Remote sensing has become important in the ocean sciences, especially for research involving large spatial scales. To estimate the in-water constituents through remote sensing, whether carried out by satellite or airplane, the signal emitted from beneath the sea surface, the so called water-leaving radiance (L(w)), is of prime importance. The magnitude of L(w) depends on two terms: one is the intensity of the solar input, and the other is the reflectance of the in-water constituents. The ratio of the water-leaving radiance to the downwelling irradiance (E(d)) above the sear surface (remote-sensing reflectance, R(sub rs)) is independent of the intensity of the irradiance input, and is largely a function of the optical properties of the in-water constituents. In this work, a model is developed to interpret r(sub rs) for ocean water in the visible-infrared range. In addition to terms for the radiance scattered from molecules and particles, the model includes terms that describe contributions from bottom reflectance, fluorescence of gelbstoff or colored dissolved organic matter (CDOM), and water Raman scattering. By using this model, the measured R(sub rs) of waters from the West Florida Shelf to the Mississippi River plume, which covered a (concentration of chlorophyll a) range of 0.07 - 50 mg/cu m, were well interpreted. The average percentage difference (a.p.d.) between the measured and modeled R(sub rs) is 3.4%, and, for the shallow waters, the model-required water depth is within 10% of the chart depth. Simple mathematical simulations for the phytoplankton pigment absorption coefficient (a(sub theta)) are suggested for using the R(sub rs) model. The inverse problem of R(sub rs), which is to analytically derive the in-water constituents from R(sub rs) data alone, can be solved using the a(sub theta) functions without prior knowledge of the in-water optical properties. More importantly, this method avoids problems associated with a need for knowledge of the shape and value of the chlorophyll-specific absorption coefficient. The simulation was tested for a wide range of water types, including waters from Monterey Bay, the West Florida Shelf, and the Mississippi River plume. Using the simulation, the R(sub rs)-derived in-water absorption coefficients were consistent with the values from in-water measurements (r(exp 2) greater than 0.94, slope approximately 1.0). In the remote-sensing applications, a new approach is suggested for the estimation of primary production based on remote sensing. Using this approach, the calculated primary production (PP) values based upon remotely sensed data were very close to the measured values for the euphotic zone (r(exp 2) = 0.95, slope 1.26, and 32% average difference), while traditional, pigment-based PP model provided values only one-third the size of the measured data. This indicates a potential to significantly improve the accuracy of the estimation of primary production based upon remote sensing.

Lee, Zhongping↗

Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments

Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Three-Dimensional Navier-Stokes Method with Two-Equation Turbulence Models for Efficient Numerical Simulation of Hypersonic Flows

A new computational efficient 3-D compressible Reynolds-averaged implicit Navier-Stokes method with advanced two equation turbulence models for high speed flows is presented. All convective terms are modeled using an entropy satisfying higher-order Total Variation Diminishing (TVD) scheme based on implicit upwind flux-difference split approximations and arithmetic averaging procedure of primitive variables. This method combines the best features of data management and computational efficiency of space marching procedures with the generality and stability of time dependent Navier-Stokes procedures to solve flows with mixed supersonic and subsonic zones, including streamwise separated flows. Its robust stability derives from a combination of conservative implicit upwind flux-difference splitting with Roe's property U to provide accurate shock capturing capability that non-conservative schemes do not guarantee, alternating symmetric Gauss-Seidel 'method of planes' relaxation procedure coupled with a three-dimensional two-factor diagonal-dominant approximate factorization scheme, TVD flux limiters of higher-order flux differences satisfying realizability, and well-posed characteristic-based implicit boundary-point a'pproximations consistent with the local characteristics domain of dependence. The efficiency of the method is highly increased with Newton Raphson acceleration which allows convergence in essentially one forward sweep for supersonic flows. The method is verified by comparing with experiment and other Navier-Stokes methods. Here, results of adiabatic and cooled flat plate flows, compression corner flow, and 3-D hypersonic shock-wave/turbulent boundary layer interaction flows are presented. The robust 3-D method achieves a better computational efficiency of at least one order of magnitude over the CNS Navier-Stokes code. It provides cost-effective aerodynamic predictions in agreement with experiment, and the capability of predicting complex flow structures in complex geometries with good accuracy.

Bardina, J. E.↗

Non-linear relationships between daily temperature extremes and US agricultural yields uncovered by global gridded meteorological datasets

Global agricultural commodity markets are highly integrated among major producers. Prices are driven by aggregate supply rather than what happens in individual countries in isolation. Furthermore, estimating the effects of weather-induced shocks on production, trade patterns and prices hence requires a globally representative weather data set. Recently, two data sets that provide daily or hourly records, GMFD and ERA5-Land, became available. Starting with the US, a data rich region, we formally test whether these global data sets are as good as more fine-scaled country-specific data in explaining yields and whether they estimate similar response functions. While GMFD and ERA5-Land have lower predictive skill for US corn and soybeans yields than the fine-scaled PRISM data, they still correctly uncover the underlying non-linear temperature relationship. All specifications using daily temperature extremes under any of the weather data sets outperform models that use a quadratic in average temperature. Correctly capturing the effect of daily extremes has a larger effect than the choice of weather data. In a second step, focusing on Sub Saharan Africa, a data sparse region, we confirm that GMFD and ERA5-Land have superior predictive power to CRU, a global weather data set previously employed for modeling climate effects in the region.

54 ENVIRONMENTAL SCIENCES↗

Climate Change and Fetal Health: The Impacts of Exposure to Extreme Temperatures in New York City

Background: Climate change is projected to increase the frequency, intensity, and duration of heat waves while reducing cold extremes, yet few studies have examined the relationship between temperature and fetal health. Objectives: We estimate the impacts of extreme temperatures on birth weight and gestational age in Manhattan, a borough in New York City, and explore differences by socioeconomic status (SES). Methods: We combine average daily temperature from 1985 to 2010 with birth certificate data in Manhattan for the same time period. We then generate 33 downscaled climate model time series to project impacts on fetal health. Results: We find exposure to an extra day where average temperature 25 F and 85 F during pregnancy is associated with a 1.8 and 1.7 g (respectively) reduction in birth weight, but the impact varies by SES, particularly for extreme heat, where teen mothers seem most vulnerable. We find no meaningful, significant effect on gestational age. Using projections of temperature from these climate models, we project average net reductions in birth weight in the 2070- 2099 period of 4.6 g in the business-as-usual scenario. Conclusions: Results suggest that increasing heat events from climate change could adversely impact birth weight and vary by SES.

climate change↗