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At least 217 records · Page 12

Stochastic Modeling in a Multimaterial Continuum Mixture Shock Physics Code

Stochastic modelling approaches are presented to capture random effects at multiple time and length scales. Random processes that occur at the microscale produce nondeterministic effects at the macroscale. Here we present three stochastic modeling approaches that describe random processes at microscopic length scales and map these processes to the macroscopic length scale. The first stochastic modeling approach is based upon a particle based numerical technique to solve a Stochastic Differential Equation (SDE) using an arbitrary diffusion process to capture random processes at the microstructural level. The second approach prescribes a Probability Density Function (PDF) for the drift and diffusion of the random variable derived using the forward and backward Kolmogorov equations. This method requires mean and drift evolution PDF transport equations. The third approach is the coupling of multiple random variables which are dependent on each other. The relationship of the PDFs and a coupling function, known as a copula, produces a Joint Probability Density Function (JPDF). These stochastic modeling approaches are implemented into a Multiple Component (MC) shock physics computational code and used to model statistical fracture and reactive flow applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Compositionally and density stratified igneous terrain in Jezero crater, Mars

Before Perseverance, Jezero crater’s floor was variably hypothesized to have a lacustrine, lava, volcanic airfall, or aeolian origin. SuperCam observations in the first 286 Mars days on Mars revealed a volcanic and intrusive terrain with compositional and density stratification. The dominant lithology along the traverse is basaltic, with plagioclase enrichment in stratigraphically higher locations. Stratigraphically lower, layered rocks are richer in normative pyroxene. The lowest observed unit has the highest inferred density and is olivine-rich with coarse (1.5 millimeters) euhedral, relatively unweathered grains, suggesting a cumulate origin. This is the first martian cumulate and shows similarities to martian meteorites, which also express olivine disequilibrium. Alteration materials including carbonates, sulfates, perchlorates, hydrated silicates, and iron oxides are pervasive but low in abundance, suggesting relatively brief lacustrine conditions. Orbital observations link the Jezero floor lithology to the broader Nili-Syrtis region, suggesting that density-driven compositional stratification is a regional characteristic.

79 ASTRONOMY AND ASTROPHYSICS↗

Complex Langevin and other approaches to the sign problem in quantum many-body physics

In this work, we review the theory and applications of complex stochastic quantization to the quantum many-body problem. Along the way, we present a brief overview of a number of ideas that either ameliorate or in some cases altogether solve the sign problem, including the classic reweighting method, alternative Hubbard–Stratonovich transformations, dual variables (for bosons and fermions), Majorana fermions, density-of-states methods, imaginary asymmetry approaches, and Lefschetz thimbles. We discuss some aspects of the mathematical underpinnings of conventional stochastic quantization, provide a few pedagogical examples, and summarize open challenges and practical solutions for the complex case. Finally, we review the recent applications of complex Langevin to quantum field theory in relativistic and nonrelativistic quantum matter, with an emphasis on the nonrelativistic case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Long-term trends in urban NO 2 concentrations and associated paediatric asthma incidence: estimates from global datasets

Combustion-related nitrogen dioxide (NO 2 ) air pollution is associated with paediatric asthma incidence. We aimed to estimate global surface NO 2 concentrations consistent with the Global Burden of Disease study for 1990-2019 at a 1 km resolution, and the concentrations and attributable paediatric asthma incidence trends in 13 189 cities from 2000 to 2019. We scaled an existing annual average NO 2 concentration dataset for 2010-12 from a land use regression model (based on 5220 NO 2 monitors in 58 countries and land use variables) to other years using NO 2 column densities from satellite and reanalysis datasets. We applied these concentrations in an epidemiologically derived concentration-response function with population and baseline asthma rates to estimate NO 2 -attributable paediatric asthma incidence. We estimated that 1.85 million (95% uncertainty interval [UI] 0.93-2.80 million) new paediatric asthma cases were attributable to NO 2 globally in 2019, two thirds of which occurred in urban areas (1.22 million cases; 95% UI 0.60-1.8 million). The proportion of paediatric asthma incidence that is attributable to NO 2 in urban areas declined from 19.8% (1.22 million attributable cases of 6.14 million total cases) in 2000 to 16.0% (1.24 million attributable cases of 7.73 million total cases) in 2019. Urban attributable fractions dropped in high-income countries (-41%), Latin America and the Caribbean (-16%), central Europe, eastern Europe, and central Asia (-13%), and southeast Asia, east Asia, and Oceania (-6%), and rose in south Asia (+23%), sub-Saharan Africa (+11%), and north Africa and the Middle East (+5%). The contribution of NO 2 concentrations, paediatric population size, and asthma incidence rates to the change in NO 2 -attributable paediatric asthma incidence differed regionally. Despite improvements in some regions, combustion-related NO 2 pollution continues to be an important contributor to paediatric asthma incidence globally, particularly in cities. Mitigating air pollution should be a crucial element of public health strategies for children.

60 APPLIED LIFE SCIENCES↗

An Open‐Source, Physics‐Based, Tropical Cyclone Downscaling Model With Intensity‐Dependent Steering

Abstract An open‐source, physics‐based tropical cyclone (TC) downscaling model is developed, in order to generate a large climatology of TCs. The model is composed of three primary components: (a) a random seeding process that determines genesis, (b) an intensity‐dependent beta‐advection model that determines the track, and (c) a non‐linear differential equation set that determines the intensification rate. The model is entirely forced by the large‐scale environment. Downscaling ERA5 reanalysis data shows that the model is generally able to reproduce observed TC climatology, such as the global seasonal cycle, genesis locations, track density, and lifetime maximum intensity distributions. Inter‐annual variability in TC count and power‐dissipation is also well captured, on both basin‐wide and global scales. Regional TC hazard estimated by this model is also analyzed using return period maps and curves. In particular, the model is able to reasonably capture the observed return period curves of landfall intensity in various sub‐basins around the globe. The incorporation of an intensity‐dependent steering flow is shown to lead to regionally dependent changes in power dissipation and return periods. Advantages and disadvantages of this model, compared to other downscaling models, are also discussed.

Meteorology & Atmospheric Sciences↗

Modeling ablator defects as a source of mix in high-performance implosions at the National Ignition Facility

Recent indirect drive inertial confinement fusion implosions on the National Ignition Facility (NIF) [Spaeth et al., Fusion Sci. Technol. 69, 25 (2016)] have crossed the threshold of ignition. However, performance has been variable due to several factors. One of the leading sources of variability is the quality of the high-density carbon (HDC) shells used as ablators in these experiments. In particular, these shells can have a number of defects that have been found to correlate with the appearance of ablator mix into the hot spot and a degradation in nuclear yield. These defects include pits on the ablator surface, voids in the ablator bulk, high-Z debris from the Hohlraum wall that adheres to the capsule surface, and finally the inherent granular micro-structure of the crystalline HDC itself. This paper summarizes high-resolution modeling of each of these mix sources in two recent high-performance NIF implosion experiments. The simulated impact from a range of individual capsule defects is found to be broadly consistent with the trends seen in experiment, lending credence to the modeling results and the details of the mixing process that they reveal. Interestingly, modeling of the micro-structure inherent to HDC shows that this perturbation source results in considerable mixing of the deuterium–tritium fuel with ablator material during the implosion. The reduction in fuel compression from this mix results in an approximately factor of two reduction in neutron yield in current implosions and emphasizes the importance of mitigating this significant performance degradation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Er : Li Nb O 3 with High Optical Coherence Enabling Optical Thickness Control

Integrated photonics capable of incorporating rare-earth ions with high optical coherence is desirable for realizing efficient quantum transducers, compact quantum memories, and hybrid quantum systems. Here we describe a photonic platform based on the SmartCut erbium-doped lithium niobate thin film, and explore its stable optical transitions at telecom wavelength in a dilution refrigerator. Optical coherence time of up to 180μs, rivaling the value of bulk crystals, is achieved in optical ridge waveguides and ring resonators. With this integrated platform, we demonstrate tunable light-ion interaction and flexible control of optical thickness by exploiting long waveguides, whose lengths are in principle variable. This unique ability to obtain high optical density using low-concentration ions further leads to the observation of multiecho pulse trains in centimeter-long waveguides. Our results establish a promising photonic platform for quantum information processing with rare-earth ions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

H2OI95: A Stand-Alone Fortran Code for Evaluating the IAPWS-95 Equation-of-State Model for Water

H2OI95 is a stand-alone Fortran code for evaluating the IAPWS-95 equation-of-state model (Wagner and Pruss, 2002) for the thermodynamic properties of water. It further evaluates the corresponding thermochemical properties of water consistent with the CODATA recommendations (Cox et al., 1989). The IAPWS-95 model is based on a model equation for the dimensionless Helmholtz energy for which the primary variables are the inverse reduced temperature and reduced density. Here is the absolute temperature (K), is density (kg/m3), and the subscript refers to the critical point of water (647.096 K and 22.064 MPa pressure in this model, for which is 322 kg/m3). The code solves four basic types of problems, distinguished by the specified inputs: 1, Temperature (K) and density (kg/m3) or reduced density 2. Temperature (K) and pressure (MPa). 3. Temperature (K) on the saturation (liquid-vapor equilibrium) curve 4. Pressure (MPa) on the saturation curve Each type of problem is run using a corresponding input (text) file. All but the first type of problem require iteration. For example, to solve for desired temperature and pressure, the reduced density must be adjusted to give the desired pressure. Iteration is accomplished using the Newton-Raphson method, though the secant method is also used in solving the fourth type of problem. H2OI95 has been used to conduct numerical studies of convergence and the problem of multiple numerical solutions, only some of which correspond to valid results. Obtaining valid results depends mainly on appropriate choice of starting values. The default values in H2OI95 appear to consistently lead to generally desired results. With modification (not addressed here), H2OI95 can be used to support SUPCRT92 (Johnson et al., 1992) and similar codes that compute chemical thermodynamic properties of species and reactions over a wide range of temperature and pressure (273.16-1273K and 0-1000 MPa).

Wolery, ThomasJ.↗

Evaluation of High Level Waste Sludge Processing Behavior

The U.S. Department of Energy’s (DOE) Hanford Site has 177 underground storage tanks that contain wastes from past nuclear fuel reprocessing and waste-management operations. Over 20% of this waste is in the form of an insoluble sludge that will require slurry modification before its transfer to the Waste Treatment and Immobilization Plant (WTP). Specific WTP acceptance criteria for waste feed delivery describe the physical and chemical characteristics of the waste that must be met before the waste is transferred to the WTP. One challenging requirement relates to the undissolved solids (UDS) composition in a waste feed because the waste contains solid particles that settle, and their concentration and relative proportion can change during the transfer of the waste in individual batches. A key uncertainty is the ability to transfer and mix wastes with large variations in UDS concentrations and resulting settling rates. To address this uncertainty, a number of small scale mixing and settling tests have been conducted to determine the mobilization performance of variable chemistry simulants. Comparison of the size and density of the particulate for each simulant to that of southeast area Hanford sludge was made using metrics for particle mobilization, suspension, settling, and pipeline transfer where dependance on particle size and density may be different, including: 1. Settling velocity, 2. Critical shear stress for erosion, 3. Just-suspended impeller speed, and 4. Pipeline critical transport velocity. Existing high-level waste sludge data has shown the effect that increasing Al concentration has on resulting settled solids. This differential settling of particles in the sludge has the possibility of resulting in solids segregation during feed preparation and uneven particle distribution during pipeline transportation or mixer jet pump operations. Understanding the predictive capabilities of HLW solids settling and transport as well as potential remedies for addressing disparate sludge behaviors can help provide technical guidance during HLW flowsheet planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Thermal management of a high temperature sodium sulphur battery stack

The sodium sulfur battery is an advanced secondary battery with high potential for grid-level storage due to their high energy density, low cost of the reactants, and high open-circuit voltage. However, as the operating temperature of the battery is high (about 300 °C), effective thermal management is required to prevent thermal runaway under high current density operation. Here, to develop efficient thermal management strategies, a detailed, thermo-electrochemical, non-isothermal, distributed dynamic model of a sodium-sulfur battery stack is developed. Models of three thermal management strategies are developed and analyzed in this work: active cooling, passive cooling, and hybrid cooling. The active cooling strategy uses air as the cooling medium whereas, the passive cooling strategy uses a phase change material. In the hybrid cooling strategy, both active and passive cooling strategies are used. Due to the high operating temperature of the sodium sulfur batteries, the rejected heat can be utilized effectively and consequently a high variability in the heat rejection rate may not be acceptable. Performance of these strategies is analyzed under high current density operation by evaluating the variability in the cell temperature during charge/discharge cycles, temperature difference between the cells based on their locations, and variability in the heat rejection rate. The phase change-based hybrid thermal management strategy with an embedded controller maintained the temperature variation within ±/- 2.8 °C. Considering the tradeoff between the capital cost for PCM, fan power requirement, and variability in the heat rejection rate, the optimal quantity of the PCM and the maximum air velocity for the maximum current density of 260 mA/cm 2 (0.55 C-rate) were found be 0.74 g/Wh and 3 m/s, respectively.

25 ENERGY STORAGE↗

Geostatistical interpolation of streambed hydrologic attributes with addition of left censored data and anisotropy

Spatial geostatistical interpolation of point measurements of streambed attributes in the hyporheic zone may be constrained by the streambed anisotropy, and data density and spatial distribution may significantly impact the results. Spatial clustering and low spatial data density can be caused by bedrock outcropping at the streambed limiting installation of in-stream piezometers. This study examines parameter error variability of the geostatistical interpolation using anisotropic interpolation methods and increasing the data density by adding left censored values (i.e., data below measurement limit) to locations where measurements were limited by exposed bedrock lining the streambed. The reduction in relative standard error of the interpolation was determined for the spatial distributions of streambed attributes including hydraulic conductivity, seepage flux, and mercury solute flux measured in two different years along a study reach in East Fork Poplar Creek, Tennessee, USA. Here, two methods to impute the left censored values were compared including the conventional half the detection limit substitution method, and the Stochastic Approximation of Expectation-Maximization (SAEM) algorithm, which both had comparable results. Imputing left censored data increased the data density to recommended ranges, reduced data clustering, increased the spatial dependence for some attributes, and reduced the standard error for each of the three attributes. For the reach considered herein, addition of the left censored values resulted in a larger error reduction than the consideration of anisotropy within the interpolation, which confirms the benefit of data addition to increase data density within data-limited river corridors.

58 GEOSCIENCES↗

A simple introduction to the SiMPL method for density-based topology optimization

We introduce a novel method for solving density-based topology optimization problems: Sigmoidal Mirror descent with a Projected Latent variable (SiMPL). The SiMPL method (pronounced as “the simple method”) optimizes a design using only first-order derivative information of the objective function. The bound constraints on the density field are enforced with the help of the (negative) Fermi–Dirac entropy, which is also used to define a non-symmetric distance function called a Bregman divergence on the set of admissible designs. This Bregman divergence leads to a simple update rule that is further simplified with the help of a so-called latent variable. Because the SiMPL method involves discretizing the latent variable, it produces a sequence of pointwise-feasible iterates, even when high-order finite elements are used in the discretization. Numerical experiments demonstrate that the method outperforms other popular first-order optimization algorithms. In conclusion, to outline the general applicability of the technique, we include examples with (self-load) compliance minimization and compliant mechanism optimization problems.

Calculus of Variations and Optimization↗

Role of Ocean and Atmosphere Variability in Scale-Dependent Thermodynamic Air-Sea Interactions

This study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air-sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy-resolving high-resolution (HR) and eddy-parameterized low-resolution (LR) ocean components. Here, in this work, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co-variability over scales between 50 and 10,000 km and 60 days to 80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper-ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ~2,000–2,500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (R 1 , ~600–2,000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean forcing also induces oscillations in SST and THF with periods ranging from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that driven by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR.

54 ENVIRONMENTAL SCIENCES↗

First Sagittarius A* Event Horizon Telescope Results. IV. Variability, Morphology, and Black Hole Mass

In this paper we quantify the temporal variability and image morphology of the horizon-scale emission from Sgr A*, as observed by the EHT in 2017 April at a wavelength of 1.3 mm. We find that the Sgr A* data exhibit variability that exceeds what can be explained by the uncertainties in the data or by the effects of interstellar scattering. The magnitude of this variability can be a substantial fraction of the correlated flux density, reaching ~100% on some baselines. Through an exploration of simple geometric source models, we demonstrate that ring-like morphologies provide better fits to the Sgr A* data than do other morphologies with comparable complexity. We develop two strategies for fitting static geometric ring models to the time-variable Sgr A* data; one strategy fits models to short segments of data over which the source is static and averages these independent fits, while the other fits models to the full data set using a parametric model for the structural variability power spectrum around the average source structure. Both geometric modeling and image-domain feature extraction techniques determine the ring diameter to be 51.8 ± 2.3 μas (68% credible intervals), with the ring thickness constrained to have an FWHM between ~30% and 50% of the ring diameter. To bring the diameter measurements to a common physical scale, we calibrate them using synthetic data generated from GRMHD simulations. This calibration constrains the angular size of the gravitational radius to be ${4.8}_{-0.7}^{+1.4}$ μas, which we combine with an independent distance measurement from maser parallaxes to determine the mass of Sgr A* to be ${4.0}_{-0.6}^{+1.1}\times {10}^{6}$ M⊙.

79 ASTRONOMY AND ASTROPHYSICS↗

Semiclassical shell-structure micro-macroscopic approach for the level density

Level density ρ(E,A) is derived for a one-component nucleon system with a given energy E and particle number A within the mean-field semiclassical periodic-orbit theory beyond the saddle-point method of the Fermi gas model. We obtain ρ∝I ν (S)/S ν , with I ν (S) being the modified Bessel function of the entropy S. Within the micro-macro-canonical approximation (MMA), for a small thermal excitation energy U, with respect to rotational excitations E rot , one obtains ν = 3/2 for ρ(E,A). In the case of excitation energy U larger than E rot but smaller than the neutron separation energy, one finds a larger value of ν = 5/2. A role of the fixed spin variables for rotating nuclei is discussed. The MMA level density ρ reaches the well-known grand-canonical ensemble limit (Fermi gas asymptote) for large S related to large excitation energies, and also reaches the finite micro-canonical limit for small combinatorial entropy S at low excitation energies (the constant “temperature” model). Fitting the ρ(E,A) of the MMA to the experimental data for low excitation energies, taking into account shell and, qualitatively, pairing effects, one obtains for the inverse level density parameter K a value which differs essentially from that parameter derived from data on neutron resonances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Spatiotemporal Variability of Electric System Reliability Metrics

As urbanization continues to grow, urban density also rises, placing significant stress on critical infrastructure. Cities often face challenges in investing in new infrastructure or upgrading existing ones. One area of infrastructure that has come under strain is the electric grid, leading to prolonged power outages. According to data from the U.S. Energy Information Administration, the average duration of power outages has steadily doubled from 2013 to 2021, primarily due to extreme weather events. The IEEE has developed a series of reliability metrics to assess the reliability of the electric system. However, these metrics are only applied at the utility level, making it challenging to comprehend the variations in these indices at finer spatial resolutions and, consequently, evaluate reliability at the non-utility level. In this study, we leveraged electric outage data collected at 15-minute intervals at the county level to estimate electric system reliability over a six-year period using a novel data analysis approach. Our findings reveal a gradual decline in reliability in the U.S. Southwest compared to national averages. Furthermore, the duration of outages per customer per event has significantly decreased in large portions of California and Florida. These discoveries can be valuable for utility companies as they seek to pinpoint regional anomalies and plan for prioritized remediation efforts.

Singh, Nagendra↗

Methodology for Sensitivity Analysis of Homogenized Cross-Sections to Instantaneous and Historical Lattice Conditions with Application to AP1000® PWR Lattice

In the two-step method for nuclear reactor simulation, lattice physics calculations are performed to compute homogenized cross-sections for a variety of burnups and lattice configurations. A nodal code is then used to perform full-core analysis using the pre-calculated homogenized cross-sections. One source of uncertainty introduced in this method is that the lattice configuration or depletion conditions typically do not match a pre-calculated one from the lattice physics simulations. Therefore, some interpolation model must be used to estimate the homogenized cross-sections in the nodal code. This current study provides a methodology for sensitivity analysis to quantify the impact of state variables on the homogenized cross-sections. This methodology also allows for analyses of the historical effect that the state variables have on homogenized cross-sections. An application of this methodology on a lattice for the Westinghouse AP1000® reactor is presented where coolant density, fuel temperature, soluble boron concentration, and control rod insertion are the state variables of interest. The effects of considering the instantaneous values of the state variables, historical values of the state variables, and burnup-averaged values of the state variables are analyzed. Using these methods, it was found that a linear model that only considers the instantaneous and burnup-averaged values of state variables can fail to capture some variations in the homogenized cross-sections.

Price, Dean (ORCID:0000000309990111)↗

Quantitative assessment of distant recurrence risk in early stage breast cancer using a nonlinear combination of pathological, clinical and imaging variables

Abstract Use of genomic assays to determine distant recurrence risk in patients with early stage breast cancer has expanded and is now included in the American Joint Committee on Cancer staging manual. Algorithmic alternatives using standard clinical and pathology information may provide equivalent benefit in settings where genomic tests, such as OncotypeDx, are unavailable. We developed an artificial neural network (ANN) model to nonlinearly estimate risk of distant cancer recurrence. In addition to clinical and pathological variables, we enhanced our model using intraoperatively determined global mammographic breast density (MBD) and local breast density (LBD). LBD was measured with optical spectral imaging capable of sensing regional concentrations of tissue constituents. A cohort of 56 ER+ patients with an OncotypeDx score was evaluated. We demonstrated that combining MBD/LBD measurements with clinical and pathological variables improves distant recurrence risk prediction accuracy, with high correlation ( r = 0.98) to the OncotypeDx recurrence score.

Nichols, Brandon S.↗