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At least 1,027 records · Page 57

FFT-based model for irradiated aggregate microstructures in concrete

The concrete biological shield of light water reactors is exposed to neutron and gamma irradiation throughout its lifetime, which results in the long-term degradation of the concrete’s mechanical properties. Under neutron irradiation, the concrete’s aggregates are subjected to radiation-induced volumetric expansion (RIVE), which strongly depends on the mineral content of the aggregate and exhibits the largest expansion in silicate-bearing minerals. In this work, the authors used the fast Fourier transform-based code Microstructure-Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) in 2D to model the expansion of five different aggregates provided by the Japan Concrete Aging Management Program (JCAMP). Comparable rock specimens were irradiated at the JEEP-II test reactor. The model uses realistic aggregate microstructure reconstruction based on high-resolution characterization images. The model accounts for anisotropic RIVE, thermal expansion, and the associated initiation and propagation of damage. The RIVE models are calibrated based on expansion data in the literature. The authors assume that damage occurs exclusively at interfaces between the particles that compose an aggregate and that these interfaces also exhibit swelling. Using a micromechanical model, the evolution of Young’s modulus with RIVE is calculated for each aggregate and compared with Russian irradiation data. The modeled linear expansion agrees well with the experimentally measured expansion. Furthermore, the model also predicts that anisotropic RIVE and thermal expansion result in an earlier onset of damage with neutron fluence than in the isotropic case.

36 MATERIALS SCIENCE↗

Devising a framework to Couple Electromagnetic Geophysical Measurements with Reservoir Simulations to Monitor CO2 Plume Movement

Monitoring CO2 plume movement and extent is critical to any CO2 utilization and storage (CCUS) project but can present significant challenges. Downhole measurements (such as cross-well seismic) can give the resolution needed to track the CO2 plume. That resolution comes at a significant expense in equipment and lost production time, and the resolution is only in the vicinity of that well. Surface seismic is less expensive but has decreasing resolution with depth and may not be sensitive to changes in the CO2 plume. Conversely, electrical conductivity has been shown to be correlated with changes in phase saturation associated with CCUS operations. A novel approach for subsurface monitoring that can be applied with minimal expense and operation disruption is charged wellbore casing controlled-source electromagnetics (CWC-CSEM). This technique injects electrical current into two legacy wells. Surface measurements of the induced electric and magnetic fields are obtained with distributed data loggers. Time-lapse measurements are sensitive to changes in CO2 plume movement, but inversion requires the application of prior knowledge from prior characterization efforts. We propose a methodology where simulations are used to inform CWC-CSEM inversion while simultaneously being validated. As such, uncertainty is reduced, and more robust flow models can be devised. A three-year study is underway at the Bell Creek Field in southeast Montana (DOE-NETL Project DE-FE0028320) to evaluate the effectiveness of CWC-CSEM on an active CO2-EOR operation. Determining the relationship between electrical resistivity and phase saturations, and coupling that to a reservoir model is the thrust of this project. Initially, the relative permeability/capillary pressure relationship and the compositional oil model were identified as model parameters with high uncertainty. To elucidate the impact of these uncertain parameters, simulations were run for ten years with a single five-spot pattern. Final water saturation distributions were converted into resistivity using Archie’s Law and available fluid sampling data to provide an exploration of the time lapse electromagnetic anomaly which can be anticipated using CWC-CSEM methods. This technique has promise as an inexpensive and accurate way to monitor CO2 injection in a CCUS site.

Moodie, Nathan↗

Capture and migration of Jupiter and Saturn in mean motion resonance in a gaseous protoplanetary disc

Here, we study the dynamical evolution of Jupiter and Saturn embedded in a gaseous, solar nebula-type disc by means of hydrodynamics simulations with the FARGO2D1D code. We study the evolution for different initial separations of the planets’ orbits, Δa SJ , to investigate whether they become captured in mean motion resonance (MMR) and the direction of the subsequent migration of the planet (inwards or outwards). We also provide an assessment of the planet’s orbital dynamics at different epochs of Saturn’s growth. We find that the evolution of initially compact orbital configurations is dependent on the value of Δa SJ . This implies that an evolution as that proposed in the Grand Tack model depends on the precise initial orbits of Jupiter and Saturn and on the time-scales for their formation. Capture in the 1:2 MMR and inward or (nearly) stalled migration are highly favoured. Within its limits, our work suggests that the reversed migration, associated with the resonance capture of Jupiter and Saturn, may be a low-probability evolutionary scenario, so that other planetary systems with giant planets are not expected to have experienced a Grand Tack-like evolutionary path.

79 ASTRONOMY AND ASTROPHYSICS↗

Is Radioactive Tank Waste a Bingham Fluid?

Slurries and sludges across the United States Department of Energy (DOE) complex rank among the most rheologically interesting. Their composition is heterogeneous, spanning a very broad range of particle sizes, densities, and interparticle forces. All exhibit shear thinning, some have yield stresses, and many are thixotropic. Despite the variety, these complex fluids are often represented using the historic Bingham fluid model, which fits higher shear rate data to a simple straight line. The intercept provides a yield stress, which has been a key design parameter in construction of large-scale waste processing facilities. However, many radioactive wastes are simply not Bingham fluids, which extrapolate but poorly across low to intermediate shear rates that are characteristic of typical processing conditions. Indeed, processing shear rates as high as 200 1/s, which has been a typical minimum shear rate used in fitting, are seldom encountered in nuclear waste processing. Therefore, more realistic rheological models are necessary to accurately predict waste processing performance. PNNL recently re-evaluated the rheology of reconstituted Hanford REDOX sludge waste against a wide variety of rheological models including the Bingham, Cross, Cross with yield stress, Carreau, biviscous, Herschel-Bulkley (which includes a power law dependence), Casson, and Gay models. They found that all of the models provided a closer fit than the Bingham model and that the biviscous model and Cross with yield stress model were convincing. However, reconstituted Hanford REDOX sludge waste is but one type of DOE waste and a direct contrast and comparison of these three models against undiluted, unmixed tank waste (actual not simulant) has not been performed previously. Therefore, the purpose of this paper is to evaluate the rheology of actual tank waste with these more accurate rheological models. In this paper, we evaluate select rheological data for slurry samples from Hanford’s AZ-101, AZ-102, and SY-101 waste tanks. In each of these cases, we find that Cross’ model with yield stress and the biviscous model significantly outperform the Bingham fluid model. Furthermore, the AZ-101 data also shows that the shear stress peak that startup significantly exceeds the Bingham yield stress, which is commonly observed in the incipient moments of rheological measurements on simulants. In contrast, Cross’ model may empirically accommodate an initial spike in shear stress at modest shear rates. These are important observations because computational and analytical fluid dynamics simulations rely on rheological constitutive models for accurately and conservatively predict waste processing performance. These findings suggest the need for better rheological modeling of and validation against radioactive waste.

Rheology, Radioactive Waste↗

Investigation of an octupole breathing mode of 208 Pb as a resolution to the elliptical-to-triangular azimuthal anisotropy puzzle in ultracentral relativistic heavy ion collisions

Relativistic heavy ion collisions provide a unique opportunity to probe the nuclear structure by taking an instantaneous snapshot of the colliding nuclei and converting it into momentum anisotropies of final emitted hadrons. A long-standing puzzle of too large a ratio of the elliptical-to-triangular (𝑣 2 -to-𝑣 3 ) anisotropies in ultracentral 208 Pb + 208 Pb collisions at the Large Hadron Collider (LHC) cannot be solved simply by hydrodynamic simulations with initial conditions containing the spherical or certain deformed shape of 208 Pb. Here, in this Letter, using the iEBE-VISHNU relativistic viscous hydrodynamic hybrid model simulations with the TR⁢ENTo initial condition, we show that a dynamic octupole deformation—a shape-breathing mode of 208 Pb —could potentially solve the 𝑣2-to-𝑣3 puzzle and simultaneously describe the 𝑣 3 ⁡{4} data measured in experiment. Our results highlight the unique capability of capturing transient collective properties of nuclei on yoctosecond (10 −24 s) timescales, unfeasible with low-energy nuclear reactions.

Xu, Hao-jie [Huzhou University, Zhejiang (China)] ↗

Bounded-Confidence Models of Multidimensional Opinions with Topic-Weighted Discordance

People’s opinions on a wide range of topics often evolve over time through their interactions with others. Models of opinion dynamics primarily focus on one-dimensional opinions, which represent opinions on one topic. However, opinions on various topics are rarely isolated; instead, they can be interdependent and correlated. In a bounded-confidence model (BCM) of opinion dynamics, agents are receptive to each other only if their opinions are sufficiently similar. Here, we extend classical agent-based BCMs—namely, the Hegselmann–Krause BCM, which has synchronous interactions, and the Deffuant–Weisbuch BCM, which has asynchronous interactions—to a multidimensional setting, in which the opinions are multidimensional vectors representing opinions of different topics and opinions on different topics are interdependent. To measure opinion differences between agents, we introduce topic-weighted discordance functions that account for opinion differences in all topics. We define regions of receptiveness for our models, and we use them to characterize the steady-state opinion clusters and provide an analytical approach to compute these regions. In addition, we numerically simulate our models on various networks with initial opinions drawn from a variety of distributions. When initial opinions are correlated across different topics, our topic-weighted BCMs yield significantly different results in both transient and steady states compared to baseline models, where the dynamics of each opinion topic are independent.

Mathematics and Computing↗

Heavy flavor quenching and flow: the roles of initial condition, pre-equilibrium evolution, and in-medium interaction

Within an advanced Langevin-hydrodynamics framework coupled to a hybrid fragmentation-coalescence hadronization model, we study heavy flavor quenching and flow in relativistic heavy-ion collisions. We investigate how the initial heavy quark spectrum, the in-medium energy loss and hadronization mechanisms of heavy quarks, the evolution profile of the pre-equilibrium stage, the medium flow, and the temperature dependence of heavy quark diffusion coefficients influence the suppression and elliptic flow of heavy mesons at the RHIC and the LHC. Our results show that the different modeling of initial conditions, pre-equilibrium evolution, and in-medium interactions can individually yield uncertainties of approximately 10-40% in D meson suppression and flow at a low transverse momentum. Furthermore, we also find that proper combinations of collisional versus radiative energy loss, coalescence versus fragmentation in hadronization, and the inclusion of medium flow are the most important factors for describing the suppression and elliptic flow of heavy mesons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Enzymatic cleavage of model lignin dimers depends on pH, enzyme, and bond type

Lignin is composed of phenylpropanoid monomers linked by ether and carbon-carbon bonds to form a complex heterogeneous structure. Bond-specific studies of lignin-modifying enzymes (LMEs; e.g., laccases and peroxidases) are limited by the polymerization of model lignin substrates and repolymerization of cleavage products. Here we present a high throughput platform to screen LME activities on four tagged model lignin compounds that represent the β-O-4’, β-β’, 5–5’, and 4-O-5’ linkages in lignin. We utilized nanostructure-initiator mass spectrometry (NIMS) and model lignin compounds with tags containing perfluorinated and cationic moieties, which effectively limit polymerization and condensation of the substrates and their degrading products. Sub-microliter sample droplets were printed on the NIMS chip with a novel robotics method. This rapid platform enabled characterization of LMEs across a range of pH 3–10 and relative quantification of modified (typically oxidized), cleaved, and polymerized products. All tested enzymes oxidized the four substrates and cleaved the β-O-4’ and β-β’ substrates to monomeric products. We discovered that the active pH range depended on both the substrate and the enzyme type. This has important applications for biomass conversion to biofuels and bioproducts, where the relative percentages of different bond types in lignin varies depending on feedstock and chemical pretreatment methods.

59 BASIC BIOLOGICAL SCIENCES↗

Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring

Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life. To address this need for rim seal performance monitoring, the present study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modelling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within three percent of measured values.

Compressors↗

Electroelastic investigation of drying rate in the direct contact ultrasonic fabric dewatering process

Ultrasonic vibrations, used to atomize liquids into a fine mist, are a promising solution for the future of efficient clothes drying technology. The world’s first ultrasonic dryer—demonstrated by researchers at Oak Ridge National Laboratory—successfully applies the scientific principles behind ultrasonic drying, and several working prototypes have been demonstrated. This technology is based on direct mechanical coupling between mesh piezoelectric transducers and wet fabric. During the atomization process, vertical oscillations of a contained liquid, called Faraday excitations, result in the formation of standing waves on the liquid surface. At increasing amplitudes and frequencies of oscillation, wave peaks become extended and form “necks” connecting small secondary droplets to the bulk liquid. When the oscillation reaches an acceleration threshold, the droplet momentum is sufficient to break the surface tension of the neck and enable the droplets to travel away from the liquid. In this work, we investigate the atomization process using an ultrasonic transducer as it pertains to moisture retained within a fabric. An experimentally validated electromechanical analytical-numerical model is proposed. This model bridges the vibrations of a piezoelectric mesh transducer to the critical acceleration needed for fabric drying to occur. Then, the drying rate model is developed, consisting of an initial nonlinear region due to atomization, followed by a linear thermal evaporation region. The models developed identify the influence of key parameters on ultrasonic drying and will aid in improving atomizer design for efficient, timely fabric drying. This study is the first proposed model for the ultrasonic atomization of fabrics saturated with water, applicable to any type of transducer. The results present a non-dimensional equation for the ultrasonic dewatering of fabrics, dependent only on transducer acceleration and the surface area of the cloth. Furthermore, the development of this technology using the proposed physical models will allow for global reductions in electrical demand related to clothes drying.

42 ENGINEERING↗

Relating CMIP5 Model Biases to Seasonal Forecast Skill in the Tropical Pacific

Abstract We examine links between tropical Pacific mean state biases and El Niño/Southern Oscillation forecast skill, using model‐analog hindcasts of sea surface temperature (SST; 1961–2015) and precipitation (1979–2015) at leads of 0–12 months, generated by 28 different models from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Model‐analog forecast skill has been demonstrated to match or even exceed traditional assimilation‐initialized forecast skill in a given model. Models with the most realistic mean states and interannual variability for SST, precipitation, and 10‐m zonal winds in the equatorial Pacific also generate the most skillful precipitation forecasts in the central equatorial Pacific and the best SST forecasts at 6‐month or longer leads. These results show direct links between model climatological biases and seasonal forecast errors, demonstrating that model‐analog hindcast skill—that is, how well a model can capture the observed evolution of tropical Pacific anomalies—is an informative El Niño/Southern Oscillation metric for climate simulations.

Ding, Hui↗

Species Transport Framework Development in SAM for System-Level Tritium Source Term Analysis

The SAM code is under development as a modern system-level modeling and simulation tool for advanced non–light water reactor safety analyses, with recent efforts to add capabilities to evaluate radiological source term risks in these novel reactor concepts. By leveraging the established system-level multiphysics thermal-hydraulic models in SAM, a framework for tightly coupled species transport modeling has been integrated into the code for engineering-scale source term evaluation. This species transport framework was first applied to the simulation of tritium, which is a well-known source term in conventional light water reactors. Tritium poses a unique risk in salt-cooled reactors, especially those with lithium-bearing salts such as the fluoride salt–cooled high-temperature reactor (FHR) concept, as tritium is generated in the salt coolant in significant quantities due to neutron interactions. A compounding factor is the increased mobility of tritium at high temperatures, which is able to permeate through metals while also potentially being retained in graphite pebbles and structures. Engineering-scale models for the tritium transport pathways in a FHR have been developed using the new species transport framework in SAM. The capabilities are assessed through analytical verification problems and validated with data from a graphite retention experiment. In conclusion, the system-level model is demonstrated by performing an initial estimate of baseline tritium generation and flows in a generic reference SAM FHR model, setting a foundation for future studies of source term transient analysis with the potential for further multiscale and multiphysics integration.

SAM↗

Coupling Constant Corrections in a Holographic Model of Heavy Ion Collisions

We initiate a holographic study of coupling-dependent heavy ion collisions by analyzing, for the first time, the effects of leading-order, inverse coupling constant corrections. In the dual description, this amounts to colliding gravitational shock waves in a theory with curvature-squared terms. Here, we find that, at intermediate coupling, nuclei experience less stopping and have more energy deposited near the light cone. When the decreased coupling results in an 80% larger shear viscosity, the time at which hydrodynamics becomes a good description of the plasma created from high energy collisions increases by 25%. The hydrodynamic phase of the evolution starts with a wider rapidity profile and smaller entropy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ground Level Integrated Diverse Energy Storage (GLIDES) Cost Analysis

With the increasing penetration of renewable energy, the need for advanced flexible/scalable energy storage technologies with high round-trip efficiency (RTE) and high energy density has become critical. In this paper, a techno-economic model of a novel energy storage technology developed by the Oak Ridge National Laboratory (ORNL) is presented and used to estimate the technology’s capital cost. Ground-Level Integrated Diverse Energy Storage (GLIDES) is an energy storage technology with high efficiency which can store energy via input of electricity and heat and supply dispatchable electricity. GLIDES stores energy by compressing and expanding a gas using a liquid piston. GLIDES performance has been extensively studied analytically and experimentally. This study aims to develop a comprehensive combined performance and cost modeling environment. With the desired system storage capacity kilowattage, storage time (hours), and an initial RTE guess as inputs, the model optimizes the selection of system components to minimize the capital cost. The techno-economic model described in this paper can provide preliminary cost estimates and corresponding performance for various system sizes and storage times.

Kassaee, Saiid↗

Cold-Season Precipitation Sensitivity to Microphysical Parameterizations: Hydrologic Evaluations Leveraging Snow Lidar Datasets

Abstract Cloud microphysical processes are an important facet of atmospheric modeling, as they can control the initiation and rates of snowfall. Thus, parameterizations of these processes have important implications for modeling seasonal snow accumulation. We conduct experiments with the Weather Research and Forecasting (WRF V4.3.3) Model using three different microphysics parameterizations, including a sophisticated new scheme (ISHMAEL). Simulations are conducted for two cold seasons (2018 and 2019) centered on the Colorado Rockies’ ∼750-km 2 East River watershed. Precipitation efficiencies are quantified using a drying-ratio mass budget approach and point evaluations are performed against three NRCS SNOTEL stations. Precipitation and meteorological outputs from each are used to force a land surface model (Noah-MP) so that peak snow accumulation can be compared against airborne snow lidar products. We find that microphysical parameterization choice alone has a modest impact on total precipitation on the order of ±3% watershed-wide, and as high as 15% for certain regions, similar to other studies comparing the same parameterizations. Precipitation biases evaluated against SNOTEL are 15% ± 13%. WRF Noah-MP configurations produced snow water equivalents with good correlations with airborne lidar products at a 1-km spatial resolution: Pearson’s r values of 0.9, RMSEs between 8 and 17 cm, and percent biases of 3%–15%. Noah-MP with precipitation from the PRISM geostatistical precipitation product leads to a peak SWE underestimation of 32% in both years examined, and a weaker spatial correlation than the WRF configurations. We fall short of identifying a clearly superior microphysical parameterization but conclude that snow lidar is a valuable nontraditional indicator of model performance.

54 ENVIRONMENTAL SCIENCES↗

Effects of Void Morphology on Detonation Initiation of PBX 9502

Accurate predictive modeling of high explosives in abnormal conditions, such as a fire, is critical to personnel safety. Modeling depends heavily on precise physical characterization of the high explosive in question. The aim of this thesis was to characterize the detonation response to shock and the microstructure at high-temperature (250°C) of PBX 9502 and use these data to attempt to model these results using a new reactive burn model called SURF (Scaled Uniform Reactive Front). In order to characterize the shock response of PBX 9502 at high-temperature a 1D gas gun experiment was designed and executed that provided shock to detonation transition data. These data were then used to do a preliminary calibration of SURF for PBX 9502 at 250°C. Small-angle neutron scattering (SANS) was employed to characterize the void morphology of PBX 9502 as a function of temperature. This was done in order to feed a modified version of SURF called physically informed - SURF (π-SURF) which uses the void size and quantity distribution data as measured by SANS along with the deflagration and detonation characteristics of a high explosive to inform the SURF model. The π-SURF model was then used to model both ambient and high-temperature PBX 9502 SDT response and the results were compared to the physically measured results. It was found that π-SURF works in ambient cases. At high-temperature, however, it was determined that not enough information is known about hot spot formation to use the π-SURF model for high-temperature scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Allometric, Growth, and Biomass Estimation Models for Acacia dealbata Link.: A Case Study in Serra da Estrela Natural Park (Portugal)

Allometric, growth, and biomass estimation models for the quantification of missing parameters in trees are widely used to estimate the productivity of a stand. However, regarding species with lower economic interest, or exotic invasive species, the creation of these tools did not occur in the same way as for other species, lacking the development of relationships to allow a deeper study of these species. Thus, data were collected in a settlement of Acacia dealbata Link. in Portugal, in an area known for the current infestation of this species. After a bibliographic review, some of the identified models were tested to select those who best fit the characteristics of this stand, which were used to develop relationships that, based on the data collected, would be able to estimate parameters, such as height, volume, or mass. It was found that the models established, at least for the initial 20 years of the life of the trees, followed close to a linear model. However, the model still presents some weaknesses. For being considered an invasive species in Portugal, A. dealbata is frequently controlled, and for this reason it is very difficult to find trees older than 20 years.

Nunes, Leonel J. R. (ORCID:0000000154048163)↗

Ocean Energy Systems Wave Energy Modelling Task: Modelling, Verification and Validation of Wave Energy Converters

The International Energy Agency Technology Collaboration Programme for Ocean Energy Systems (OES) initiated the OES Wave Energy Conversion Modelling Task, which focused on the verification and validation of numerical models for simulating wave energy converters (WECs). The long-term goal is to assess the accuracy of and establish confidence in the use of numerical models used in design as well as power performance assessment of WECs. To establish this confidence, the authors used different existing computational modelling tools to simulate given tasks to identify uncertainties related to simulation methodologies: (i) linear potential flow methods; (ii) weakly nonlinear Froude–Krylov methods; and (iii) fully nonlinear methods (fully nonlinear potential flow and Navier–Stokes models). This article summarizes the code-to-code task and code-to-experiment task that have been performed so far in this project, with a focus on investigating the impact of different levels of nonlinearities in the numerical models. Two different WECs were studied and simulated. The first was a heaving semi-submerged sphere, where free-decay tests and both regular and irregular wave cases were investigated in a code-to-code comparison. The second case was a heaving float corresponding to a physical model tested in a wave tank. We considered radiation, diffraction, and regular wave cases and compared quantities, such as the WEC motion, power output and hydrodynamic loading.

16 TIDAL AND WAVE POWER↗