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At least 1,261 records · Page 70

Fast, High-fidelity Lyα Forests with Convolutional Neural Networks

Full-physics cosmological simulations are powerful tools for studying the formation and evolution of structure in the universe but require extreme computational resources. Here, we train a convolutional neural network to use a cheaper N-body-only simulation to reconstruct the baryon hydrodynamic variables (density, temperature, and velocity) on scales relevant to the Lyα forest, using data from Nyx simulations. We show that our method enables rapid estimation of these fields at a resolution of ~20 kpc, and captures the statistics of the Lyα forest with much greater accuracy than existing approximations. Because our model is fully convolutional, we can train on smaller simulation boxes and deploy on much larger ones, enabling substantial computational savings. Furthermore, as our method produces an approximation for the hydrodynamic fields instead of Lyα flux directly, it is not limited to a particular choice of ionizing background or mean transmitted flux.

79 ASTRONOMY AND ASTROPHYSICS↗

A Monte Carlo simulation technique for low-altitude, wind-shear turbulence

A case is made for including anisotropy in a Monte Carlo flight simulation scheme of low-altitude wind-shear turbulence by means of power spectral density. This study attempts to eliminate all flight simulation-induced deficiencies in the basic turbulence model. A full-scale low-altitude wind-shear turbulence simulation scheme is proposed with particular emphasis on low cost and practicality for near-ground flight. The power spectral density statistic is used to highlight the need for realistic estimates of energy transfer associated with low-altitude wind-shear turbulence. The simulation of a particular anisotropic turbulence model is shown to be a relatively simple extension from that of traditional isotropic (Dryden) turbulence.

Bowles, Roland L.↗

Use of TRMM Data to Test an Improved Parameterization of Stratiform Precipitation

By incorporating the TRMM satellite orbital information into the most recent geodesic version of the Colorado State University General Circulation Model (CSU GCM), we are able to fly a satellite in the GCM, and sample the simulated atmosphere in the same way as the TRMM sensors sample the real atmosphere. The TRMM sampling statistics of precipitation and radiative fluxes at annual, intra-seasonal, monthly-mean and composited diurnal time scales are evaluated by comparing the satellite-sampled against fully-sampled simulated atmospheres. This information provides a valuable guidance for efficient usage of TRMM data and future satellite mission planning. We have also evaluated the effects of TRMM sampling errors on the inferred tropical-mean hydrologic cycle and radiative fluxes. We have found that there are strong spurious oscillations associated with the TRMM orbital geometry, with periods of 23 days and 3-4 months, in tropical-mean daily and monthly precipitation. Caution must therefore be used when applying TRMM observations of tropical-mean precipitation to interpret climate variations at intraseasonal and interannual scales.

Randall, David A.↗

Higher-Order Spectral Analysis of a Nonlinear Pitch and Plunge Apparatus

Simulated aeroelastic responses of a nonlinear pitch and plunge apparatus are analyzed using various statistical signal processing techniques including higher-order spectral methods. A MATLAB version of the Nonlinear Aeroelastic Testbed Apparatus (NATA) at the Texas A&M University is used to generate various aeroelastic response data including limit cycle oscillations (LCO). Traditional and higher-order spectral (HOS) methods are applied to the simulated aeroelastic responses. Higher-order spectral methods are used to identify critical signatures that indicate the transition from linear to nonlinear (LCO) aeroelastic behavior.

Silva, Walter A.↗

Cross-scale covariance for material property prediction

A simulation can stand its ground against an experiment only if its prediction uncertainty is known. The unknown accuracy of interatomic potentials (IPs) is a major source of prediction uncertainty, severely limiting the use of large-scale classical atomistic simulations in a wide range of scientific and engineering applications. Here we explore covariance between predictions of metal plasticity, from 178 large-scale (~10 8 atoms) molecular dynamics (MD) simulations, and a variety of indicator properties computed at small-scales (≤10 2 atoms). All simulations use the same 178 IPs. In a manner similar to statistical studies in public health, we analyze correlations of strength with indicators, identify the best predictor properties, and build a cross-scale “strength-on-predictors” regression model. This model is then used to estimate regression error over the statistical pool of IPs. Small-scale predictors found to be highly covariant with strength are computed using expensive quantum-accurate calculations and used to predict flow strength, within the statistical error bounds established in our study.

36 MATERIALS SCIENCE↗

Uncertainty propagation in pore water chemical composition calculation using surrogate models

Performance assessment in deep geological nuclear waste repository systems necessitates an extended knowledge of the pore water chemical conditions prevailing in host-rock formations. In the last two decades, important progress has been made in the experimental characterization and thermodynamic modeling of pore water speciation, but the influence of experimental artifacts and uncertainties of thermodynamic input parameters are seldom evaluated. In this respect, we conducted an uncertainty propagation study in a reference geochemical model describing the pore water chemistry of the Callovian-Oxfordian clay formation. Nineteen model input parameters were perturbed, including those associated to experimental characterization (leached anions, exchanged cations, cation exchange selectivity coefficients) and those associated to generic thermodynamic databases (solubilities). A set of 13 quantities of interest were studied by the use of polynomial chaos expansions built non-intrusively with a least-squares forward stepwise regression approach. Training and validation sets of simulations were carried out using the geochemical speciation code PHREEQC. The statistical results explored the marginal distribution of each quantity of interest, their bivariate correlations as well as their global sensitivity indices. The influence of the assumed distributions for input parameters uncertainties was evaluated by considering two parametric domain sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward quantum Monte Carlo forces on heavier ions: Scaling properties

Quantum Monte Carlo (QMC) forces have been studied extensively in recent decades because of their importance with spectroscopic observables and geometry optimization. Here, we benchmark the accuracy and computational cost of QMC forces. The zero-variance zero-bias (ZVZB) force estimator is used in standard variational and diffusion Monte Carlo simulations with mean-field based trial wavefunctions and atomic pseudopotentials. Statistical force uncertainties are obtained with a recently developed regression technique for heavy tailed QMC data [P. Lopez Rios and G. J. Conduit, Phys. Rev. E 99, 063312 (2019)]. By considering selected atoms and dimers with elements ranging from H to Zn (1 ≤ Z eff ≤ 20), we assess the accuracy and the computational cost of ZVZB forces as the effective pseudopotential valence charge, Z eff , increases. We find that the costs of QMC energies and forces approximately follow simple power laws in Zeff. The force uncertainty grows more rapidly, leading to a best case cost scaling relationship of approximately Z e ff 6.5 ( 3 ) for diffusion Monte Carlo. We find that the accessible system size at fixed computational cost scales as Z e ff − 2 , insensitive to model assumptions or the use of the “space warp” variance-reduction technique. Our results predict the practical cost of obtaining forces for a range of materials, such as transition metal oxides where QMC forces have yet to be applied, and underscore the importance of further developing force variance-reduction techniques, particularly for atoms with high Z eff .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TRISO SiC Failure Probability for Reactivity Initiated Accidents in High-Temperature Gas-Cooled Reactors

This work analyzes the failure process of the silicon carbide (SiC) layer in tristructural isotropic (TRISO) during reactivity-initiated accident scenarios for a high-temperature gas-cooled reactor (HTGR) with BISON. Two cases are considered—a group control rod withdrawal (CRW) and a control rod ejection (CRE)—reproduced from a previous study. Failure probability is modeled using Weibull statistics, and worst-case scenario Weibull parameters are adopted to simulate the envelopes in BISON with a one-dimensional TRISO model. CRW scenario results are characterized by higher values of maximum energy deposition and final temperature and volumetric strain with respect to the CRE ones, but the latter have remarkably higher SiC failure probability, mainly due to the offset in strain rates between the two cases. This work also confirms the validity and conservatism of the performance envelopes produced in a previous work by replicating the envelope formulation using RELAP5-3D and RAVEN with a different sampling technique and obtaining consistent results. A sensitivity analysis using the Sobol variance decomposition method on SiC failure probability is then performed involving a set of inputs on both CRW and CRE. The two most important parameters are Weibull modulus and characteristic stress, and their relative importance depends on the specific case. The proposed interpretation of the results is that both energy deposition and strain rate influence the relative degree of importance of the failure parameters. Computation of 95% confidence intervals around worst-case scenario SiC failure probability values is also carried out for four different sets of Weibull parameters. Heren a new criterion for SiC TRISO quality classification built upon safety-based ranges of Weibull parameters is proposed to be integrated in future Fuel-Production Quality Assurance Plans.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An Open-Source Frequency-Domain Model for Floating Wind Turbine Design Optimization

A new frequency-domain dynamics model has been developed that uses open-source components to efficiently represent a complete floating wind turbine system. The model, called RAFT (Response Amplitudes of Floating Turbines), incorporates quasi-static mooring reactions, strip-theory and potential-flow hydrodynamics, blade-element-momentum aerodynamics, and linear turbine control. The formulation is compatible with a wide variety of support structure configurations and no manual or time-domain preprocessing steps are required, making RAFT very practical in design and optimization workflows. The model is applied to three reference floating wind turbine designs and its predictions are compared with results from time-domain OpenFAST simulations. There is good agreement in mean offsets as well the statistics and spectra of the dynamic response, verifying RAFT’s general suitability for floating wind analysis. Follow-on work will include verification of potential-flow and turbine-control features and application to optimization problems.

17 WIND ENERGY↗

The beyond-halo mass effects of the cosmic web environment on galaxies

ABSTRACT Galaxy properties primarily depend on their host halo mass. Halo mass, in turn, depends on the cosmic web environment. We explore if the effect of the cosmic web on galaxy properties is entirely transitive via host halo mass, or if the cosmic web has an effect independent of mass. The secondary galaxy bias, sometimes referred to as ‘galaxy assembly bias’, is the beyond-mass component of the galaxy–halo connection. We investigate the link between the cosmic web environment and the secondary galaxy bias in simulations. We measure the secondary galaxy bias through the following summary statistics: projected two-point correlation function, $w_{\mathrm{p}}(r_{\mathrm{p}})$, and counts-in-cylinders statistics, $P(N_{\mathrm{CIC}})$. First, we examine the extent to which the secondary galaxy bias can be accounted for with a measure of the environment as a secondary halo property. We find that the total secondary galaxy bias preferentially places galaxies in more strongly clustered haloes. In particular, haloes at fixed mass tend to host more galaxies when they are more strongly associated with nodes or filaments. This tendency accounts for a significant portion, but not the entirety, of the total secondary galaxy bias effect. Secondly, we quantify how the secondary galaxy bias behaves differently depending on the host halo proximity to nodes and filaments. We find that the total secondary galaxy bias is relatively stronger in haloes more associated with nodes or filaments. We emphasize the importance of removing halo mass effects when considering the cosmic web environment as a factor in the galaxy–halo connection.

Astronomy & Astrophysics↗

Local primordial non-Gaussian bias from time evolution

Primordial non-Gaussianity (PNG) is a signature of fundamental physics in the early Universe that is probed by cosmological observations. Here, it is well known that the local type of PNG generates a strong signal in the two-point function of large-scale structure tracers, such as galaxies. This signal, often termed “scale-dependent bias” is a generic feature of modulation of gravitational structure formation by a large-scale mode. It is less well appreciated that the coefficient controlling this signal, b ϕ , is closely connected to the time evolution of the tracer number density. This correspondence between time evolution and local PNG can be simply explained for a universal tracer whose mass function only depends on peak height and, more generally, for nonuniversal tracers in the separate universe picture, which we validate in simulations. We also describe how to recover the bias of tracers subject to a survey selection function and perform a simple demonstration on simulated galaxies. Since the local PNG amplitude in n-point statistics ($f$ NL ) is largely degenerate with the coefficient b ϕ , this proof of concept study demonstrates that Galaxy survey data can allow for more optimal and robust extraction of local PNG information from upcoming surveys.

Sullivan, James M. [University of California, Berk↗

Microscopic theory of onset of decaging and bond-breaking activated dynamics in ultradense fluids with strong short-range attractions

We theoretically study thermally activated “in cage” elementary dynamical processes that precede full structural relaxation in ultra-dense particle liquids interacting via strong short range attractive forces. The analysis is based on a microscopic theory formulated at the particle trajectory level built on the dynamic free energy concept and an explicit treatment of how attractive forces control the formation and lifetime of physical bonds. Mean time scales for bond breaking, the early stage of cage escape, and non-Fickian displacement by a fixed amount are analyzed in the repulsive glass, bonded repulsive (attractive) glass, fluid, and dense gel regimes. The theory predicts a strong length-scale-dependent growth of these time scales with attractive force strength at fixed packing fraction, a much weaker slowing down with density at fixed attraction strength, and a strong decoupling of the shorter bond breaking time with the other two time scales that are controlled mainly by perturbed steric caging. All results are in good accord with simulations, and additional testable predictions are made. In conclusion, the classic statistical mechanical projection approximation of replacing all bare attractive and repulsive forces with a single effective force determined by pair structure incurs major errors for describing processes associated with thermally activated escape from transiently localized states.

36 MATERIALS SCIENCE↗

Kinetic Monte Carlo simulations of aging in δ -Pu

We have developed a first-passage kinetic Monte Carlo approach for materials aging to investigate the sensitivity of void swelling to model parameters, including helium bubble density and size distribution. In addition to explicitly accounting for the spatial distribution of individual point defects, bubbles, and voids, our approach can simulate total doses equivalent to 100 years of natural aging on statistically representative volumes of materials. This technique enables us to study the effects on swelling and radiation damage evolution due to temperature and dose rate (as altered in artificially aged experiments), differences in effective interaction radii between vacancies and interstitials, and varying defect diffusion activation energies, while providing more detailed information than previous rate-equation based approaches. In conclusion, our results indicate that spatial effects that are not modeled in mean-field rate theories could play a significant role in void swelling initiation and growth for certain regimes of model parameters.

Actinides↗

Surface Pressure Fluctuations Induced by a Hypersonic Turbulent Boundary Layer on a Sharp Cone at Angle of Attack

High-fidelity simulations are performed to characterize the turbulence-induced wall pressure fluctuations on a sharp cone at a 5.5° angle-of-attack in a Mach 8 flow. Wall-resolved large-eddy simulation (LES) and wall-modeled large-eddy simulation (WMLES) results are compared to measurements at several locations on the cone body, where comparisons with high-frequency PCB sensors are good, while comparison with low-frequency kulite sensors varies depending on the location. For a given streamwise location, simulation results show significant azimuthal variation in the wall pressure fluctuation statistics. Comparisons between LES and WMLES results indicate that WMLES can accurately reproduce the low-frequency component of the autospectra quite well, while slight sensitivity is apparent in the coherence. A grid sensitivity study for WMLES further demonstrated sensitivity in the wall pressure fluctuation coherence, but not in the autospectra.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An Algorithm to Calibrate and Correct the Response to Unpolarized Radiation of the X-Ray Polarimeter Onboard IXPE

The Gas Pixel Detector (GPD) is an X-ray polarimeter to fly onboard IXPE and other missions. To correctly measure the source polarization, the response of IXPE’s GPDs to unpolarized radiation has to be calibrated and corrected. In this paper, we describe the way such response is measured with laboratory sources and the algorithm to apply such correction to the observations of celestial sources. The latter allows to correct the response to polarization of single photons, therefore allowing great flexibility in all the subsequent analysis. Our correction approach is tested against both monochromatic and nonmonochromatic laboratory sources and with simulations, finding that it correctly retrieves the polarization up to the statistical limits of the planned IXPE observations.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Measuring the Speed of Sound Using Cumulants of Baryon Number

Here, we show that the values of the first three cumulants of the baryon number distribution can be used to calculate the isothermal speed of sound and its logarithmic derivative with respect to the baryon-number density. We discuss applications of this result to heavy-ion collision experiments and address possible challenges, including effects due to baryon-number conservation, differences between proton and baryon cumulants, and the influence of finite-number statistics on fluctuation observables in both ex periment and hadronic transport simulations. In particular, we investigate the relation between quantities calculated in infinite, continuous matter, and observables obtained in simulations using a finite number of particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

RTN-056: Study of the Photon Transfer Curve in the CCD detectors of the Vera C. Rubin Observatory

The RECA internship program provides Colombian students with an opportunity to enhance their research skills in Astronomy, Astrophysics, and Cosmology. During this three-month program, our main objective was to study the Photon Transfer Curves (PTC) of the Vera C. Rubin Observatory, specifically the gain, and to compare it with the gain obtained through pairs of flats. Overall, the study of PTCs is crucial in understanding the performance of detectors and instruments used in Astronomy. The Vera C. Rubin Observatory is an important facility that will enable researchers to carry out a wide range of studies in this field, making it essential to investigate its gain performance. We used run 13144 to construct the PTCs and 13186 to analyze the crosstalk. We employed the LSST Science Pipelines (also known as the DM stack), a software under development for this observatory, which performs all the necessary reductions for the construction of the PTCs. We also used simulations to replicate the observed effects. Initially, we found a 5% difference between the gain calculated by PTC and pairs of flats for a flow range between 5000 and 10000 ADU. Simulations showed that this difference was due to the handling of statistics and the assumption that the distribution following the Lupton equation is Gaussian. We found an error interval for this flow region based on the vendor, with (1.8 ± 0.7, 4.1 ± 0.9) % for E2V and (0.85 ± 0.7, 2.2 ± 0.9) % for ITL. From the PTC, we also obtained the average Full Well Capacity of LSSTCam as 130000 ± 10000$ electrons. We identified a list of segments where we found differences with the results obtained by SLAC National Acceleration Laboratory in PTC parameters, low saturation level, or other defects. We detected and corrected the effect of statistics in the gain calculation using pairs of flats and proposed a code change, which was implemented in the pipeline software. We do not recommend correcting for crosstalk as it does not significantly affect the parameters and does not change the shape of the PTC. However, the opposite is true for the nonlinearity correction.

79 ASTRONOMY AND ASTROPHYSICS↗

The effects of correlation on goodness of fit

Autocorrelated normal random variates were generated via computer and the effects of various levels of correlation on goodness of fit problems were studied. The results are useful in determining the distribution or estimating the parameters of populations that correlate observations such as wind speeds and temperature. The model used to generate the autocorrelated data is an autoregressive process of order 1. The Kolmogorov-Smirnov and chi-square statistics are used in the analysis. It was observed in the simulation that high positive correlations tend to shift the sample mean away from the population mean and negative correlations tend to shift the sample mean towards the population mean. In many cases, it was observed that positive and negative correlations tend to decrease the standard deviation. However, since this did not occur in all cases, no definite conclusion can be made regarding the standard deviation. Since the autoregressive process is a linear transformation, it is not surprising that normality was preserved. However, a possible extension of this problem could be to generate non-normal data and observe how the distribution is affected by correlation. Another extension might utilize another model such as autoregressive of order k or a moving average process of order k.

Kitchens, L. J.↗