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At least 487 records · Page 27

Evidence for the 3D Radiative Effects of Boundary-Layer Clouds From Observations of Direct and Diffuse Surface Solar Fluxes

Numerical experiments have revealed the importance of horizontal transport of light in the presence of clouds (“3D effects”), with consequences for climate, weather, and solar resource availability predictions. Yet, analysis of 3D effects from observations remain sparse because of the difficulty to isolate the effect of horizontal transport in radiation measurements. In this study, we provide observational evidence for 3D effects based on the direct-diffuse partition of surface solar fluxes. It is compared to outputs from the ecRad radiative transfer scheme run on retrieved cloud profiles. Furthermore, the direct-beam calculation takes careful account of the field-of-view of the pyrheliometer to ensure consistency between observed and modeled direct fluxes. Only the solver that accounts for 3D effects is able to reproduce the observed mean direct-diffuse partition as a function of solar zenith angle and cloud cover, in particular at large solar zenith angles where cloud sides intercept most of the direct beam.

54 ENVIRONMENTAL SCIENCES↗

Retention of Long-period Gas Giant Planets: Type II Migration Revisited

During their formation, emerging protoplanets tidally interact with their natal disks. Proto–gas giant planets, with Hill radii larger than the disk thickness, open gaps and quench gas flow in the vicinity of their orbits. It is usually assumed that their type II migration is coupled to the viscous evolution of the disk. Although this hypothesis provides an explanation for the origin of close-in planets, it also encounters a predicament on the retention of long-period orbits for most gas giant planets. Moreover, numerical simulations indicate that the planets' migrations are not solely determined by the viscous diffusion of their natal disk. In this work, we carry out a series of hydrodynamic simulations combined with analytic studies to examine the transition between different paradigms of type II migration. We find a range of planetary mass for which gas continues to flow through a severely depleted gap so that the surface density distribution in the disk region beyond the gap is maintained in a quasi-steady state. The associated gap profile modifies the location of corotation and Lindblad resonances. In the proximity of the planet's orbit, high-order Lindblad and corotation torque are weakened by the gas depletion in the gap, while low-order Lindblad torques near the gap walls preserve their magnitude. Consequently, the intrinsic surface density distribution of the disk delicately determines both the pace and direction of the planets' type II migration. We show that this effect might stall the inward migration of giant planets and preserve them in disk regions where the surface density is steep.

79 ASTRONOMY AND ASTROPHYSICS↗

Synthetic Absorption Lines from Simulations of Multiphase Gas in Galactic Winds

Supernova-driven galactic winds are multiphase streams of gas that are often observed flowing at a range of velocities out of star-forming regions in galaxies. In this study, we use high-resolution 3D simulations of multiphase galactic winds modeled with the hydrodynamics code Cholla to investigate the connection between numerical studies and observations. Using a simulated interaction between a hot $T$ ~ 10 4 K supernova-driven wind and a cool $T$ ~ 10 7 K cloud of interstellar material, we create mock observables, including the optical depth ($\tau$) and covering fraction ($C$ $f$ ) of six commonly observed ions (Si II , C II , Si IV , C IV , N V , and O VI ) as a function of gas velocity. We compare our mock observables to surveys of galactic winds in the literature, finding good agreement with velocities and profiles of the low ions. We then compute "empirical" values for the optical depth and covering fraction following observational techniques and compare them to the values calculated directly from the simulation data. We find that the empirically computed values tend to underestimate the "true" value of $\tau$ for ions with high optical depth and overestimate the "true" value of $\tau$ for ions with low optical depth relative to the simulated data. In conclusion, the empirically estimated covering fractions match our direct calculations very well for the low-ionization ions; for the high-ionization ions, the empirical covering fractions underestimate the directly computed values by up to ~40%.

79 ASTRONOMY AND ASTROPHYSICS↗

Anisotropic fluid dynamical simulations of heavy-ion collisions

We present VAH, a (3+1)–dimensional simulation that evolves the far-from-equilibrium quark-gluon plasma produced in ultrarelativistic heavy-ion collisions with anisotropic fluid dynamics. We solve the hydrodynamic equations on an Eulerian grid using the Kurganov–Tadmor algorithm in combination with a new adaptive Runge–Kutta method. Our numerical scheme allows us to start the simulation soon after the nuclear collision, largely avoiding the need to integrate it with a separate pre-equilibrium dynamics module. We test the code's performance by simulating on the Eulerian grid conformal and non-conformal Bjorken flow as well as conformal Gubser flow, whose (0+1)–dimensional solutions are precisely known. Finally, we compare non-conformal anisotropic hydrodynamics to second-order viscous hydrodynamics in central Pb+Pb collisions and find that the former's longitudinal flow profile responds more consistently to the fluid's gradients along the spacetime rapidity direction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Deprojection of X-ray data in galaxy clusters: confronting simulations with observations

ABSTRACT Numerical simulations with varying realism indicate an emergent principle−multiphase condensation and large cavity power occur when the ratio of the cooling time to the free-fall time (tcool/tff) falls below a threshold value close to 10. Observations indeed show cool-core signatures when this ratio falls below 20–30, but the prevalence of cores with tcool/tff ratio below 10 is rare as compared to simulations. In X-ray observations, we obtain projected spectra from which we have to infer radial gas density and temperature profiles. Using idealized models of X-ray cavities and multiphase gas in the core and 3D hydro jet-ICM simulations, we quantify the biases introduced by deprojection based on the assumption of spherical symmetry in determining tcool/tff. We show that while the used methods are able to recover the tcool/tff ratio for relaxed clusters, they have an uncertainty of a factor of 2−3 in systems containing large cavities (≳ 20 kpc). We also show that the mass estimates from these methods, in the absence of X-ray spectra close to the virial radius, suffer from a degeneracy between the virial mass (M200) and the concentration parameter (c) in the form of M200c2 ≈ constant. Additionally, the lack of soft-X-ray (≲ 0.5 keV) coverage and poor spatial resolution makes us overestimate min(tcool/tff) by a factor of few in clusters with min(tcool/tff) ≲ 5. This bias can largely explain the lack of cool-core clusters with min(tcool/tff) ≲ 5.

Sarkar, Kartick C. (ORCID:0000000277678472)↗

Computational Fluid Dynamics Simulations to Support Efficiency Improvements in Aluminum Smelting Process

Smelting is broadly described as the extraction of a metal from its ore. In the United States, aluminum is commonly produced by smelting alumina in bauxite using the Hall-Héroult process. Optimization of equipment and processes in conventional smelting is crucial to enhancing process efficiency and productivity, is necessary for improving the techno-economic feasibility, which directly manifests as the growth of the American economy. To achieve optima, insightful data on the multiphysics phenomena that are inherent to the process must be obtained through physical investigation or high-fidelity numerical simulations. The resolution of relevant scales in time and space for smelting operations requires intensive, high-performance computing (HPC) simulations. Hostile operating conditions limit physical data acquisition to specific techniques; therefore, these data do not describe the multiscale interaction of simultaneous effects. Fortunately, in recent decades, significant advancements in computing hardware and computational methods have made the numerical resolution of such a complex process possible. In this study, a high-fidelity simulation of aluminum smelting was performed using an open-source tool, OpenFOAM, which analyzed many parameters characteristic to underlying phenomena. A multiphysics model based on the Eulerian-Eulerian multifluid approach was adopted. This model can resolve critical issues in the electrolytic smelting of aluminum, such as bubbling of carbon dioxide from the anode(s), magnetohydrodynamics from electromagnetic effects, ionic dissolution of the alumina in the electrolyte, and the evolution of thermal profiles. This study provides valuable connectivity for characteristic data that can direct the future designs of efficient smelters. A basic framework to model and simulate the smelting process using OpenFOAM is presented for user modification in keeping with process development. Of relevance to the flow field, a detailed investigation of vortices produced by bubble motion and electromagnetics is discussed, along with their impact on the evolution of thermal profiles. The predictions show small-scale vortices in the clearance between the anode and cathode caused by magnetic forces. Predictions also indicate relatively large-scale vortices in the inter-anode space resulting from carbon dioxide rising through the electrolytic flow field. The formation of vortices at the edges of anodes was shown to direct alumina charged by the feeder to the bottom of the anodes, thus preventing the entrapment of gas bubbles in the periphery of the bottom of the anode. Symmetry was observed in the location of cold spots in the electrolytic mixture in the vicinity of the feeder. Cold spots were also observed in the clearance between the anode and cathode due to the flow’s transmission of unconverted alumina to this region.

36 MATERIALS SCIENCE↗

Can reanalysis products outperform mesoscale numerical weather prediction models in modeling the wind resource in simple terrain?

Mesoscale numerical weather prediction (NWP) models are generally considered more accurate than reanalysis products in characterizing the wind resource at heights of interest for wind energy, given their finer spatial resolution and more comprehensive physics. However, advancements in the latest ERA-5 reanalysis product motivate an assessment on whether ERA-5 can model wind speeds as well as a state-of-the-art NWP model – the Weather Research and Forecasting (WRF) Model. We consider this research question for both simple terrain and offshore applications. Specifically, we compare wind profiles from ERA-5 and the preliminary WRF runs of the Wind Integration National Dataset (WIND) Toolkit Long-term Ensemble Dataset (WTK-LED) to those observed by lidars at a site in Oklahoma, United States, and in a United States Atlantic offshore wind energy area. We find that ERA-5 shows a significant negative bias (~-1ms-1) at both locations, with a larger bias at the land-based site. WTK-LED-predicted wind speed profiles show a limited negative bias (~-0.5ms-1) offshore and a slight positive bias (~+0.5ms-1) at the land-based site. On the other hand, we find that ERA-5 outperforms WTK-LED in terms of the centered root-mean-square error (cRMSE) and correlation coefficient, for both the land-based and offshore cases, in all atmospheric stability conditions. We find that WTK-LED's higher cRMSE is caused by its tendency to overpredict the amplitude of the wind speed diurnal cycle. At the land-based site, this is partially caused by wind plant wake effects not being accurately captured by WTK-LED.

17 WIND ENERGY↗

Experimental Investigation of Vapor Formation in Liquid CO2 Flow Through a Converging-Diverging Nozzle

Carbon dioxide is an attractive working fluid for many cycles, including for pumped thermal energy storage (PTES). A challenge with some proposed sCO2 PTES cycles is the operation of sCO2 machinery outside the typical bounds of experience, with local phase change from the liquid state being particularly unknown. Presently, there is insufficient data in the literature regarding multiphase CO2 to adequately design a multiphase-tolerant turbine, so generation of foundational data is required. This experimental study investigates the flow characteristics of sub-sonic liquid CO2 undergoing expansion and phase change in a converging-diverging nozzle. The nozzle is instrumented to measure static pressure, unsteady pressure, temperature, and density. The static pressure transducers are located at 27 axial locations to accurately characterize the pressure profile in the nozzle. High-accuracy RTDs are located at the entrance and exit of the nozzle, and three dynamic pressure transducers are strategically located to capture any unsteady phenomena. During testing, values of mass flow and nozzle inlet pressure are swept to vary the pressure drop and fluid properties. The measured total pressure drop in the nozzle is compared to a homogenous model and the Lockhart-Martinelli correlation method, with the latter predicting loss quite closely. The resulting data set is valuable for validating multiphase numerical models in a simple geometry before implementation of these models in turbomachinery design.

25 ENERGY STORAGE↗

Quantitative interpretation of time-lapse seismic data at Farnsworth field unit: Rock physics modeling, and calibration of simulated time-lapse velocity responses

Here, this study investigates the contribution of fluid saturation variation to the time-lapse velocity response by performing fluid substitution modeling. The methodology is exemplified by the time-lapse seismic monitoring of carbon dioxide at Farnsworth field unit (FWU). In order to evaluate the fluid distribution in a matured oil reservoir, the Southwest Regional Partnership (SWP) acquired multiple vertical seismic profile (VSP) surveys at different times during the CO 2 –water alternatinggas (WAG) injection period. In this work, we present a thorough methodology for computing the elastic response of the saturated rock for different fluid saturations using a site-specific petro-elastic model (PEM). The output from the PEM was combined with results from a fluid compositional model to compute the seismic velocities at times corresponding to each VSP survey. To produce a calibrated simulated response, the measured time-lapse seismic velocities were integrated into the numerical simulation model. The mismatches between the predicted and measured time-lapse velocities were minimized through an iterative calibration process using a trained artificial neural network proxy (ANN) coupled with a particle swarm optimizer (PSO). Our study indicates that the hybrid optimization workflow can effectively perform the history matching. With an accurate prediction of the hydrodynamic properties, the migration of CO 2 within the subsurface was modeled by predicting the spatial velocity distribution for a radius of 305 m around the injection well. The technology demonstrated and the expertise gained from this study can guide similar CO 2 -WAG projects.

58 GEOSCIENCES↗

On the Interplay Between Distributed Bulk Plasticity and Local Fault Slip in Evolving Fault Zone Complexity

Abstract We numerically investigate the role of plastic strain accumulation on the mechanical response of a planar strike‐slip fault. Our models show that fault‐zone strength significantly impacts the ensuing sequence of earthquakes. Weaker fault zones accumulating more plastic strain promote more complexity in the seismicity pattern through aperiodic earthquake occurrences and intermittent episodes of rupture and arrest. However, if the fault zone strength is high enough, the overall earthquake sequence is characterized by periodic fault‐spanning events. We find that both the fault normal stress and the fault geometric profile evolve throughout the earthquake sequence, suggesting a self‐roughening mechanism. Despite the significant impact of plasticity on the fault response, the width of the plastically deforming region in the fault zone is small compared to the fault length. Our results suggest a rich behavior in dynamically evolving fault zones and support the need for further high‐resolution studies of the highly non‐linear near‐fault region.

Geology↗

Measurements of TRACER pre-convective conditions and mesoscale circulations using small unmanned aircraft systems (sUAS)

Improved comprehension of the physical processes governing convective cloud formation and lifecycle are of critical importance for understanding and predicting future climate states. The influence of these clouds on the planetary energy budget, including on precipitation, is significant. Things are particularly complex in coastal regimes, where gradients in aerosol particle properties, localized circulations such as sea breezes, and large population centers are found. To date, numerical models struggle to accurately represent these critical clouds and are therefore challenged to provide a realistic view on the planetary energy budget. Through the proposed research, we deployed two uncrewed aircraft systems (UAS) equipped with a variety of instruments alongside sensors deployed by the US Department of Energy Atmospheric Radiation Measurement (ARM) program for the TRACER (Tracking Aerosol Convection Interactions Experiment) field campaign. The two small UAS platforms consisted of a CU RAAVEN fixed-wing airplane and an OU CopterSonde system, with the copter collecting frequent vertical profiles of thermodynamic and kinematic variables such as temperature, pressure, wind and humidity. At the same time, the fixed-wing captured horizontal gradients of these quantities and aerosol size distribution. These systems were deployed south of the Houston metro area, in an area that is impacted by the Gulf of Mexico sea breeze on a daily basis. These observations offer enhanced and complementary perspectives to those provided by the DOE ARM Mobile Facility (AMF) which is was deployed in southeast Houston, and an ancillary site in a more rural location west of the urban Houston area. Quality-controlled versions of the UAS data were collected and posted on the DOE ARM data archive after the conclusion of the campaign where they are accessible by the research community and general public. The UAS perspective offers revolutionary insight into key spatial and temporal effects that have not been evaluated previously.

54 ENVIRONMENTAL SCIENCES↗

Relaxations of the steady optimal gas flow problem for a non-Ideal gas

Natural gas ranks second in U.S. primary energy consumption. Because most production sites are remote, gas must be transported through pipeline networks equipped with compressors, valves, and other components. For both economic efficiency and system reliability, it is desirable to operate these networks optimally. The governing physics across pipeline components entails nonlinear, non-convex equality and inequality constraints, and the most general steady-flow operations problem is a Mixed-Integer Nonlinear Program (MINLP).This work focuses on one such steady-flow problem-the Optimal Gas Flow (OGF) for a natural gas pipeline network-which minimizes production cost subject to the steady-flow physics. For day-to-day operations, the ability to quickly compute a globally optimal solution and a strong lower bound for varying demand profiles is crucial. A promising strategy is to build tight relaxations of the OGF’s nonlinear constraints. However, many nonlinearities arising from non-ideal equations of state either lack relaxations or have relaxations that do not scale to realistic network sizes. We address this gap by combining recent advances in polyhedral relaxations for univariate functions to construct tight, computationally efficient relaxations of the OGF with a non-ideal equation of state. These relaxations solve within seconds on a standard laptop. In conclusion, we demonstrate their quality through extensive numerical experiments on very large-scale test networks from the literature and find that the proposed approach proves optimality in 92% of tested instances.

03 NATURAL GAS↗

Quantitative proteomics reveals extensive lysine ubiquitination and transcription factor stability states in Arabidopsis

Abstract Protein activity, abundance, and stability can be regulated by post-translational modification including ubiquitination. Ubiquitination is conserved among eukaryotes and plays a central role in modulating cellular function; yet, we lack comprehensive catalogs of proteins that are modified by ubiquitin in plants. In this study, we describe an antibody-based approach to enrich ubiquitinated peptides coupled with isobaric labeling to enable quantification of up to 18-multiplexed samples. This approach identified 17,940 ubiquitinated lysine sites arising from 6,453 proteins from Arabidopsis (Arabidopsis thaliana) primary roots, seedlings, and rosette leaves. Gene ontology analysis indicated that ubiquitinated proteins are associated with numerous biological processes including hormone signaling, plant defense, protein homeostasis, and metabolism. We determined ubiquitinated lysine residues that directly regulate the stability of three transcription factors, CRYPTOCHROME-INTERACTING BASIC-HELIX-LOOP-HELIX 1 (CIB1), CIB1 LIKE PROTEIN 2 (CIL2), and SENSITIVE TO PROTON RHIZOTOXICITY1 (STOP1) using in vivo degradation assays. Furthermore, codon mutation of CIB1 to create a K166R conversion to prevent ubiquitination, via CRISPR/Cas9-derived adenosine base editing, led to an early flowering phenotype and increased expression of FLOWERING LOCUS T (FT). These comprehensive site-level ubiquitinome profiles provide a wealth of data for future functional studies related to modulation of biological processes mediated by this post-translational modification in plants.

Biochemistry & Molecular Biology↗

PyJMAK: An Open-Source Python Toolkit for Modeling Solid-State Metallurgical Phase Transformations

Accurate prediction of metallurgical phase transformations is an essential basis for autonomous optimization and rapid part qualification. Several methods can be used to estimate the evolution of phase fractions such as JMAK kinetics-based models, phase-field models, thermodynamic models, and data-driven machine learning models. Thermodynamic and phase-field-based methodologies solve multiphysics equations requiring numerous calibration parameters and significant computational resources. As a result, the computation domain is limited to a point or on order of micron-meters. The data-driven models rely on large datasets from experiments and simulations. While the JMAK model only provides information about phase fraction evolution, it can predict this evolution in near real-time using thermal history and thermodynamic data without restriction on the domain. JMAK models have been popularly used by researchers to model phase transformations occuring during additive manufacturing or over arbitrary temperature profiles. Commercial proprietary software such as Abaqus and Ansys or closed-source in-house implementations offer the ability to model JMAK based kinetics to predict phase transformation. However, these software packages are not open-source or freely available for use and development in conjunction with manufacturing machines, sensors, and machine learning algorithms. In addition, the use of the model is restricted by a license token. In contrast, given temperature profiles at multiple points in the domain, this Python-based PyJMAK model can compute phase evolution in parallel due to its stand-alone modular, voxel-based structure, and it can be executed on high-performance computing resources without any license restrictions.

Prabhune, Bhagya [Oak Ridge National Laboratory (O↗

Investigation of Thermal Radiation under Pressurized Oxy-combustion Conditions

Thermal radiation of the gaseous and particle phases in a pilot-scale pressurized oxy-combustor is computationally studied. In particular, the radiation characteristics of gases and particles are estimated by employing the statistical narrow-band model and the large-particle model. It is found that thermal radiation of the particle cloud dominates in the combustor under a furnace temperature of 1500 K and when there is no substantial loss of particles to the walls. Another important observation is that radiation from the gas and particles can be approximately treated as a graybody under these conditions. More specifically, the results on the spectral radiation intensity of a gas comprising 40% (vol) H 2 O and 60% CO 2 show that when the pressure is increased to 15 bar, and the radiation pathlength is 100 cm, the spectral radiation profile of the gas phase approaches that of a blackbody at the respective temperature. In addition, the emissivity of the particulate cloud has been evaluated as a function of the particle concentration and diameter by employing the large-particle model. It is shown that the emissivity grows with the particle concentration but decreases with the particle size for the same mass of the particles. Finally, this outcome of the present study is expected to be used to validate the assumption of the gray-gas model adopted in the numerical simulations of pressurized oxy-combustion.

large-particle model↗

Assessing the numerical stability of physics models to equilibrium variation through database comparisons on DIII-D

High fidelity kinetic equilibria are crucial for tokamak modeling and analysis. Manual workflows for constructing kinetic equilibria are time consuming and subject to user error, motivating development of automated equilibrium reconstruction tools to provide accurate and consistent reconstructions for downstream physics analysis. These automated tools also provide access to kinetic equilibria at large database scales, which enables the quantification of general uncertainties arising from equilibrium reconstruction techniques. In this paper, we compare a large database of DIII-D kinetic equilibria generated manually by physics experts to equilibria from automated kinetic reconstruction tools, assessing the impact of reconstruction method on equilibrium parameters and resulting magnetohydrodynamic stability calculations. We find agreement among scalar parameters, whereas profile quantities, such as the bootstrap current, show larger disagreements. We analyze ideal kink and classical tearing stability with DCON and STRIDE respectively, finding that the kink stability calculation is generally more robust than the tearing index Δ' calculation. We find that in 90% of cases, both kink stability classifications are unchanged between the manual expert and automated kinetic equilibria.

CAKE↗

Numerical simulation of asteroid geometry variance on airburst threat

For an atmospheric airburst the primary source of concern when assessing uncertainty is the size and velocity. Determining these properties provides the basis for threat assessment, as the total energy of the asteroid may then be estimated, and the threat investigated thoroughly. Even with clarity as to how much energy an asteroid may deposit, a great deal of uncertainty still exists for the actual energy deposition process. One such source of uncertainty is the geometry of the incoming asteroid. The geometry of an asteroid will alter the stress distribution during entry, which adds uncertainty to when fracture will occur. Here, in this study, we use Smoothed Particle Hydrodynamics to model the atmospheric airburst of Tunguska-scale asteroids with varying geometric profiles, including a sphere, ellipsoid, binary and superellipsoid. Each asteroid is modeled as a homogenous structure with strength. We assess uncertainty through a series of planar 2D simulation cases for each geometry, comparing the source of stochasticity across geometries. A single 3D airburst simulation for each geometry is also analyzed. Additionally, the 3D cases are compared to the highly uncertain Tunguska event, predicting variance in burst height across geometries, but all bounded by theoretical burst heights proposed for Tunguska.

Airburst↗

The Dark Energy Survey Bright Arcs Survey: Candidate Strongly Lensed Galaxy Systems from the Dark Energy Survey 5000 Square Degree Footprint

We report the combined results of eight searches for strong gravitational lens systems in the full 5000 square degrees of Dark Energy Survey (DES) observations. The observations accumulated by the end of the third observing season fully covered the DES footprint in five filters (grizY), with an i-band limiting magnitude (at 10σ) of 23.44. In four searches, a list of potential candidates was identified using a color and magnitude selection from the object catalogs created from the first three observing seasons. Three other searches were conducted at the locations of previously identified galaxy clusters. Cutout images of potential candidates were then visually scanned using an object viewer. An additional set of candidates came from a data-quality check of a subset of the color–coadd tiles created from the full DES six-season data set. A short list of the most promising strong-lens candidates was then numerically ranked according to whether or not we judged them to be bona fide strong gravitational lens systems. These searches discovered a diverse set of 247 strong-lens candidate systems, of which 81 are identified for the first time. We provide the coordinates, magnitudes, and photometric properties of the lens and source objects, and an estimate of the Einstein radius for 81 new systems and 166 previously reported systems. This catalog will be of use for selecting interesting systems for detailed follow up, studies of galaxy cluster and group mass profiles, as well as a training/validation set for automated strong-lens searches.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗