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At least 1,081 records · Page 60

Estimating Watershed Subsurface Permeability From Stream Discharge Data Using Deep Neural Networks

Subsurface permeability is a key parameter in watershed models that controls the contribution from the subsurface flow to stream flows. Since the permeability is difficult and expensive to measure directly at the spatial extent and resolution required by fully distributed watershed models, estimation through inverse modeling has had a long history in subsurface hydrology. The wide availability of stream surface flow data, compared to groundwater monitoring data, provides a new data source to infer soil and geologic properties using integrated surface and subsurface hydrologic models. As most of the existing methods have shown difficulty in dealing with highly nonlinear inverse problems, we explore the use of deep neural networks for inversion owing to their successes in mapping complex, highly nonlinear relationships. We train various deep neural network (DNN) models with different architectures to predict subsurface permeability from stream discharge hydrograph at the watershed outlet. The training data are obtained from ensemble simulations of hydrographs corresponding to an permeability ensemble using a fully-distributed, integrated surface-subsurface hydrologic model. The trained model is then applied to estimate the permeability of the real watershed using its observed hydrograph at the outlet. Our study demonstrates that the permeabilities of the soil and geologic facies that make significant contributions to the outlet discharge can be more accurately estimated from the discharge data. Their estimations are also more robust with observation errors. Compared to the traditional ensemble smoother method, DNNs show stronger performance in capturing the nonlinear relationship between permeability and stream hydrograph to accurately estimate permeability. Our study sheds new light on the value of the emerging deep learning methods in assisting integrated watershed modeling by improving parameter estimation, which will eventually reduce the uncertainty in predictive watershed models.

54 ENVIRONMENTAL SCIENCES↗

Tectonic motion in the western United States inferred from very long baseline interferometry measurements, 1980-1986

Over six years of mobile very long baseline interferometry (VLBI) baseline measurements between 12 sites in the western U.S. were used to infer their velocities relative to the North American plate. These velocities were found to be generally consistent with those determined from geologic data and contemporaneous satellite laser ranging measurements in the same region. The discrepancy between the largest velocities determined from the VLBI measurements of 40-48 mm/yr and the relative plate velocity of 50-56 mm/yr predicted from plate motion models is found to be consistent with a broadened distribution of interseismic strain from cyclic activity on the San Andreas and subsidiary faults. The VLBI data are best explained by a cumulative rate of strike-slip motion near the plate boundary of approximately 48 mm/yr, although exclusion of competing values of 56 and 41 mm/yr is based upon very few data. The rates of offshore fault slip inferred from this study range from about 15 mm/yr in central California to negligible amounts in the San Francisco region. Finite element calculations of multiple fault strain distributions show good agreement with systematic variations in the distribution of shear strain along the San Andreas system, as revealed by previous geodetic measurements.

Kroger, Peter M.↗

Tomographic optical emission spectroscopy of an atmospheric pressure plasma jet and surface ionization waves on planar and structured surfaces

Here in this paper, an approach for 3D plasma structure diagnostics using tomographic optical emission spectroscopy (Tomo-OES) of a nanosecond pulsed atmospheric pressure plasma jet (APPJ) is presented. In contrast to the well-known Abel inversion, Tomo-OES does not require cylindrical symmetry to recover 3D distributions of plasma light emission. Instead, many 2D angular projections are measured with intensified cameras and the multiplicative algebraic reconstruction technique is used to recover the 3D distribution of light emission. This approach solves the line-of-sight integration problem inherent to optical diagnostics, allowing recovery of localized OES information within the plasma that can be used to better infer plasma parameters within complex plasma structures. Here, Tomo-OES was applied to investigate an APPJ operated with helium in ambient air and impinging on planar and structured dielectric surfaces. Surface charging caused the guided streamer from the APPJ to transition to a surface ionization wave (SIW) that propagated along the surface. The SIW experienced variable geometrical and electrical material properties as it propagated, leading to 3D configurations that were non-symmetric and spatially complex. Light emission from He, N$_2^+$, and N2 were imaged at ten angular projections and the respective time-resolved 3D emission distributions in the plasma were then reconstructed. The spatial resolution of each tomographic reconstruction was 7.4 µm and the temporal resolution was 5 ns, sufficient to observe the guided streamer and the effects of the structured surface on the SIW. Emission from He showed the core of the jet and emission from N$_2^+$ and N2 indicated effects of entrainment of ambient air. Penning ionization of N2 created a ring or outer layer of N$_2^+$ that spatially converged to form the 'plasma bullet' or spatially diverged across a surface as part of a SIW. The SIW entered trenches of size 150 µm, leading to decreases in plasma light emission in regions above the trenches. The plasma light emission was higher in some regions with trenches, possibly due to effects of field enhancement.

plasma interactions with complex surfaces↗

Neural simulation-based inference approach for characterizing the Galactic Center γ-ray excess

The nature of the Fermi γ-ray Galactic Center Excess (GCE) has remained a persistent mystery for over a decade. Although the excess is broadly compatible with emission expected due to dark matter annihilation, an explanation in terms of a population of unresolved astrophysical point sources e.g., millisecond pulsars, remains viable. The effort to uncover the origin of the GCE is hampered in particular by an incomplete understanding of diffuse emission of Galactic origin. This can lead to spurious features that make it difficult to robustly differentiate smooth emission, as expected for a dark matter origin, from more “clumpy” emission expected from a population of relatively bright, unresolved point sources. Here, we use recent advancements in the field of simulation-based inference, in particular density estimation techniques using normalizing flows, in order to characterize the contribution of modeled components, including unresolved point source populations, to the GCE. Compared to traditional techniques based on the statistical distribution of photon counts, our machine learning-based method is able to utilize more of the information contained in a given model of the Galactic Center emission, and in particular can perform posterior parameter estimation while accounting for pixel-to-pixel spatial correlations in the γ-ray map. This makes the method demonstrably more resilient to certain forms of model misspecification. On application to Fermi data, the method generically attributes a smaller fraction of the GCE flux to unresolved point sources when compared to traditional approaches. We nevertheless infer such a contribution to make up a non-negligible fraction of the GCE across all analysis variations considered, with at least $38^{+9}_{-19}$% of the excess attributed to unresolved point sources in our baseline analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Thermal Experiments for Fractured Rock Characterization: Theoretical Analysis and Inverse Modeling

Abstract Field‐scale properties of fractured rocks play a crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion technique to infer two such parameters, fracture density and fractal dimension, from cross‐borehole thermal experiments data. It is based on a particle‐based heat‐transfer model, whose evaluation is accelerated with a deep neural network (DNN) surrogate that is integrated into a grid search. The DNN is trained on a small number of the heat‐transfer model runs and predicts the cumulative density function of the thermal field. The latter is used to compute fine posterior distributions of the (to be estimated) parameters. Our synthetic experiments reveal that fracture density is well constrained by data, while fractal dimension is harder to determine. Adding nonuniform prior information related to the DFN connectivity improves the inference of this parameter.

Zhou, Zitong↗

Evaluation of silicon carbide as a divertor armor material in DIII-D H-mode discharges

Silicon carbide (SiC) represents a promising but largely untested plasma-facing material (PFM) for next-step fusion devices. In this work, an analytic mixed-material erosion model is developed by calculating the physical (via SDTrimSP) and chemical (via empirical scalings) sputtering yield from SiC, Si, and C. The Si content in the near-surface SiC layer is predicted to increase during D plasma bombardment due to more efficient physical and chemical sputtering of C relative to Si. Silicon erosion from SiC thereby occurs primarily from sputtering of the enriched Si layer, rather than directly from the SiC itself. SiC coatings on ATJ graphite, manufactured via chemical vapor deposition, were exposed to repeated H-mode plasma discharges in the DIII-D tokamak to test this model. The qualitative trends from analytic modeling are reproduced by the experimental measurements, obtained via spectroscopic inference using the S/XB method. Quantitatively the model slightly under-predicts measured erosion rates, which is attributed to uncertainties in the ion impact angle distribution, as well as the effect of edge-localized modes. After exposure, minimal changes to the macroscopic or microscopic surface morphology of the SiC coatings were observed. Compositional analysis reveals Si enrichment of about 10%, in line with expectations from the erosion model. Extrapolating to a DEMO-type device, an order-of-magnitude decrease in impurity sourcing, and up to a factor of 2 decrease in impurity radiation, is expected with SiC walls, relative to graphite, if low C plasma impurity content can be achieved. Furthermore, these favorable erosion properties motivate further investigations of SiC as a low-Z, non-metallic PFM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The effects of varying colour–luminosity relations on Type Ia supernova science

ABSTRACT The success of Type Ia supernova (SN Ia) distance standardization for cosmology relies on a single global linear relationship between their peak luminosity and colour, the β parameter. However, there are several pieces of evidence and physical reasons to believe that this relation is not universal and may change within different subgroups, or even among individual objects. In this work, we allow β to vary among subpopulations with different observed properties in the cosmological fits. Although the inferred cosmological parameters are consistent with previous studies that assume a single colour–luminosity relation, we find that the SN data favour non-universal distributions of β when split according to SN colour and/or host-galaxy mass. For galaxy mass, we obtain a β-step relation in which low β values occur in more massive galaxies, a trend that can be explained by differing dust reddening laws for two types of environments. For colour, we find that bluer/redder SNe Ia are consistent with a lower/larger β. This trend is explained with β being a combination of a low intrinsic colour–luminosity relation dominant in bluer SNe and a higher extrinsic reddening relation dominant at redder colours. The host-galaxy mass-step correction always provides better distance calibration, regardless of the multiple β approaches, and we suggest that it may come from a difference in intrinsic colour–luminosity properties of SNe Ia in two types of environments. Additionally, we find that blue SNe in low-mass environments are better standard candles than the others.

González-Gaitán, S. (ORCID:0000000195410317)↗

β − decay of exotic P and S isotopes with neutron number near 28

β - decay of very neutron-rich isotopes of P and S, studied at the National Superconducting Cyclotron Laboratory (NSCL) using the Beta Counting Station (BCS) consisting of a Double Sided Strip Detector surrounded by clovers detectors for observing delayed γ transitions is reported here. β-decay half-lifes and delayed neutron emission probabilities were extracted for 42,43,44 P and 44,46 S by analyzing spatial and temporal correlations between implants and decay events in the Si detector with further coincidence with γ transitions. Detection of delayed γ rays allowed for the identification of negative parity 1p1h states in 42 S for the first time, also constraining the parent ( 42 P) spin/parity to 2 - or 3 - . For the most exotic isotope studied, 46 S, no strong γ transition was observed unlike lighter even-even S isotopes, thus implying the shift of Gamow Teller (GT) strength distribution to higher energies. In conclusion, comparison of experimental observations to detailed shell-model calculations using the SDPFSDG-MU interaction allowed us to infer the importance and role of First Forbidden (FF) β transitions as the neutron number approaches and then exceeds N = 28.

39 ≤ A ≤ 58↗

Monte Carlo control loops for cosmic shear cosmology with DES Year 1 data

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control of systematic errors. Monte Carlo control loops (MCCL) is a forward modeling method designed to tackle this problem. It relies on the ultra fast image generator (UFig) to produce simulated images tuned to match the target data statistically, followed by calibrations and tolerance loops. Here, we present the first end-to-end application of this method, on the Dark Energy Survey (DES) Year 1 wide field imaging data. We simultaneously measure the shear power spectrum $C_ℓ$ and the redshift distribution $n(z)$ of the background galaxy sample. The method includes maps of the systematic sources, point spread function (PSF), an approximate Bayesian computation (ABC) inference of the simulation model parameters, a shear calibration scheme, and a fast method to estimate the covariance matrix. We find a close statistical agreement between the simulations and the DES Y1 data using an array of diagnostics. In a nontomographic setting, we derive a set of $C_ℓ$ and $n(z)$ curves that encode the cosmic shear measurement, as well as the systematic uncertainty. Following a blinding scheme, we measure the combination of $Ω_m$, $σ_8$, and intrinsic alignment amplitude $A_{IA}$, defined as $S_8D_{IA}=σ_8(Ω_m/0.3)^{0.5}D_{IA}$, where $D_{IA}=1-0.11(A_{IA}-1)$. We find $S_8D_{IA}=0.8954_{-0.039}^{+0.054}$, where systematics are at the level of roughly 60% of the statistical errors. We discuss these results in the context of earlier cosmic shear analyses of the DES Y1 data. Our findings indicate that this method and its fast runtime offer good prospects for cosmic shear measurements with future wide-field surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Elastic properties of Apollo 14 and 15 rocks.

Ultrasonic P- and S-wave velocities of lunar samples 14310,72 and 15418,43 and P-wave velocities of sample 15015,18 were measured at room temperature to 5 kb confining pressure. The velocities of both igneous and breccia samples increased sharply over this pressure range. At low confining pressures, the shape of velocity-pressure curves of rocks is determined by the distribution function of crack aspect ratios. We suggest that analogue studies on terrestrial rocks having a wide assortment of crack parameters may be used to infer the nature of cracks in lunar rocks.

Todd, T.↗

Does the upper main sequence extend across the whole H-R diagram

The effect of using Carson's (1976) radiative opacities in evolutionary sequences of stellar models has been studied over the mass range from 7 to 60 solar masses. The opacities are very large in the outer part of the envelope and induce such enormous radii for masses greater than about 30 solar masses for a heavy-element fraction of 0.02 or about 20 solar masses for a heavy-element fraction of 0.04 that the evolutionary tracks during the phase of core hydrogen burning extend across the whole H-R diagram. The choice of the Schwarschild or Ledoux criterion for convection makes very little difference for the behavior of the tracks. Evolution through the effective-temperature range (in logarithms) of 3.6 to 4.0 occurs in all cases on a rapid (secular) time scale. Core helium burning takes place exclusively in the red-supergiant configuration for stellar masses exceeding 8 solar masses (heavy-element fraction of 0.02) or 6 solar masses (heavy-element fraction of 0.04). These stellar models seem to be in significantly better agreement with the observed distribution of bright stars on the H-R diagram than are the older models based on the Cox-Stewart opacities. It can be inferred that a large envelope opacity (e.g., Carson's) exists and that substantial mass loss takes place in very massive late-type supergiants.

Stothers, R.↗

Noble gas trapping by laboratory carbon condensates

Trapping of noble gases by carbon-rich matter was investigated by synthesizing carbon condensates in a noble gas atmosphere. Laser evaporation of a solid carbon target yielded submicron grains which proved to be efficient noble gas trappers (Xe distribution coefficients up to 13 cu cm STP/g-atm). The carbon condensates are better noble gas trappers than previously reported synthetic samples, except one, but coefficients inferred for meteoritic acid-residues are still orders of magnitude higher. The trapped noble gases are loosely bound and elementally strongly fractionated, but isotopic fractionations were not detected. Although this experiment does not simulate nebular conditions, the results support the evidence that carbon-rich phases in meteorites may be carriers of noble gases from early solar system reservoirs. The trapped elemental noble gas fractionations are remarkably similar to both those inferred for meteorites and those of planetary atmospheres for earth, Mars and Venus.

Niemeyer, S.↗

The planetary distribution of heat sources and sinks during FGGE

Heating distributions from analysis of the National Meteorological Center and European Center for Medium Range Weather Forecasts data sets; methods used and problems involved in the inference of diabatic heating; the relationship between differential heating and energy transport; and recommendations on the inference of heat soruces and heat sinks for the planetary show are discussed.

Johnson, D. R.↗

Temporal patterns of phytoplankton abundance in the North Atlantic

A time series of CZCS images is being developed to study phytoplankton distribution patterns in the North Atlantic. The goal of this study is to observe temporal variability in phytoplankton pigments and other organic particulates, and to infer from these patterns the potential flux of biogenic materials from the euphotic layer to the deep ocean. Early results of this project are presented in this paper. Specifically, the satellite data used were 13 monthly composited images of CZCS data for the North Atlantic from January 1979 to January 1980. Results are presented for seasonal patterns along the 20 deg W meridian.

Campbell, Janet W.↗

A computationally efficient model for turbulent droplet dispersion in spray combustion

A novel model for turbulent droplet dispersion is formulated having significantly improved computational efficiency in comparison to the conventional point source stochastic sampling methodology. In the proposed model, a computational parcel representing a group of physical particles is considered to have a normal (Gaussian) probability density function (PDF) in three-dimensional space. The mean of each PDF is determined by Lagrangian tracking of each computational parcel, either deterministically or stochastically. The variance is represented by a turbulence-induced mean squared dispersion which is based on statistical inferences from the linearized direct modeling formulation for particle/eddy interactions. Convolution of the computational parcel PDF's produces a single PDF for the physical particle distribution profile. The validity of the new model is established by comparison with the conventional stochastic sampling method, where in each parcel is represented by a delta function distribution, for non-evaporating particles injected into simple turbulent air flows.

Litchford, Ron J.↗

The distribution of hydrocarbons in Neptune's upper atmosphere

The distribution of hydrocarbons in the upper atmosphere of Neptune is determined on the basis of data from the Voyager UVS solar occultation experiment. Densities are inferred from the transmission properties of the atmosphere measured by the UVS. The CH4 mole fraction in the lower stratosphere is between 0.0006 and 0.005. It is inferred that CH4 in Neptune's lower stratosphere is oversaturated by at least a factor of 10, and possibly by as much as a factor of 100. The density of C2H6 reaches values of 3 x 10 exp 9/cu cm near 100 microbar; a C2H6 production efficiency of 35 +15/-5 percent is derived. The eddy diffusion coefficient is approximately constant at a value of 10,000 sq cm/s at altitudes below 300 km and increases at higher altitudes as the pressure to the 0.75 power. A mole fraction of 0.001 is found to be consistent with the CH4 vapor pressure at 3.4 mbar; consequently, CH4 ice particles must reach this level to produce the inferred oversaturation.

Yelle, Roger V.↗

Chemical fractionations in group IIIAB iron meteorites - Origin by dendritic crystallization of an asteroidal core

Results of an investigation of the crystallization history of the asteroidal core that produced nearly 200 iron meteorites of group IIIAB are presented. The accuracy of the published distribution of coefficients between solid and liquid metal for seven elements and their dependence on the concentrations of S and P are critically assessed to develop a nonideal fractional crystallization model that reproduces all of the major features of the overall chemical trends in group IIIAB. It is suggested that the apparent distribution coefficient of S was was much higher than its equilibrium value (not greater than 0.01) and that it increased during crystallization. In the present preferred model the apparent distribution coefficient for S increases from 0.6 to 0.8, while the S concentration of the liquid increases from 6 to 13 wt pct. It is inferred that light S-rich liquid accumulates preferentially at the top of the core and in structural traps formed by the advancing solid.

Haack, Henning↗

Impact of Assimilating GOES-Derived Land Surface Variables into the PSU/NCAR MM5

Land surface processes are known to have a profound impact on the overlying atmosphere over a wide range of spatial and temporal scales. Many atmospheric numerical models include special parameterizations to improve the specification and partitioning of surface fluxes which are critical to the accurate prediction of warm season boundary layer behavior, organized mesoscale circulations, and convective precipitation. However, the added degrees of freedom resulting from the inclusion of vegetation and soil schemes require the specification of additional surface parameters such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, and the vertical distribution of soil moisture. As satellite data have become more readily available in recent years, many investigations have attempted to use these new measurements to infer missing components of the surface energy budget. Sensitivity studies have shown land-skin temperature (LST) tendencies during the mid-morning hours are strongly sensitive to the surface moisture availability (a function of soil wetness and vegetation) and less sensitive to other parameters such as surface roughness. Based upon results from these and other studies, developed a simple technique that dynamically assimilates Geostationary Operational Environmental Satellite (GOES) derived land-surface products into the surface energy budget of a mesoscale model. The purpose of this paper is to demonstrate that assimilating the GOES satellite data has the potential to improve the representation of land surface characteristics within the model without prior knowledge of the land surface characteristics. The assimilation technique is presented in Section 2 and the numerical experiments are detailed in Section 3. Preliminary results and conclusions are presented in Sections 4 and 5, respectively.

Lapenta, William M.↗