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DOE OSTI2021

High-throughput ion irradiation of additively manufactured compositionally complex alloys

Several advanced nuclear reactor designs promise efficiency and safety improvements over the current reactor fleet but are limited by the current set of ASME code-qualified materials. Novel alloys including high-entropy alloys (HEAs), and more broadly compositionally complex alloys (CCAs), have shown promising irradiation-tolerance. However, the vast range of alloy compositions adds to an already time-consuming alloy development process. In this study, to accelerate the development of novel alloys for nuclear applications, a high-throughput (HTP) methodology has been employed. Additive manufacturing has been used to produce a compositional array of unary, binary, ternary, and quaternary alloys, including several CCAs, which span the Cr-Fe-Mn-Ni composition space. Additionally, the compositional array was homogenized at 1000°C for 24 hours and each sample was irradiated using 4-MeV Ni2+ ions at room temperature to a peak damage of 50 dpa, as estimated using SRIM, at the University of Wisconsin Ion Beam Laboratory. A custom XY stage was built to accommodate the large compositional array and half of each sample was masked during irradiation enabling both the irradiated and unirradiated properties of each alloy to be characterized side-by-side. Each alloy was characterized using X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and nanoindentation. CALPHAD simulations spanning the entire Cr-Fe-Mn-Ni composition space at 1000°C were performed to compare predicted equilibrium phases with phases identified experimentally from the unirradiated regions of each alloy. Nanoindentation measurements indicate radiation-induced hardening ranging from ~1-1.5 GPa in each of Cr-Fe-Mn-Ni CCAs, which is relatively insensitive to modest changes in alloy composition and comparable to hardening observed in neutron irradiated Cr-Fe-Mn-Ni CCAs in the literature. Overall, a substantial time savings was realized by employing HTP synthesis, irradiation, and characterization in this study compared to conventional techniques, the implications of which are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Low-Density Parity-Check Codes as Stable Phases of Quantum Matter

Phases of matter with robust ground-state degeneracy, such as the quantum toric code, are known to be capable of robust quantum information storage. Here, we address the converse question: given a quantum error-correcting code, when does it define a stable gapped quantum phase of matter, whose ground-state degeneracy is robust against perturbations in the thermodynamic limit? We prove that a low-density parity-check (LDPC) code defines such a phase, robust against all few-body perturbations, if its code distance grows at least logarithmically in the number of degrees of freedom, and it exhibits “check soundness.” Many constant-rate quantum LDPC expander codes have such properties, and define stable phases of matter with a constant zero-temperature entropy density, violating the third law of thermodynamics. Our results also show that quantum toric-code phases are robust to spatially nonlocal few-body perturbations. Similarly, phases of matter defined by classical codes are stable against symmetric perturbations. In the classical setting, we present improved locality bounds on the quasiadiabatic evolution operator between two nearby states in the same code phase.

quantum error correction↗

DOE OSTI2023

PNNL-CompBio/BoltzmannMFX

BoltzmannMFX is a biological simulation code that solves chemical reaction networks using maximum entropy methods. It uses modules from MFiX-Exa and is based on the AMReX framework for massively parallel block-structured adaptive mesh applications.

Palmer, Bruce↗

DOE OSTI2019

A boundary condition for Guderley’s converging shock problem

The Guderley model of a self-similar imploding shock based on the group invariance of the flow equations is a powerful tool in understanding the behavior of converging shock waves. Two modifications described here improve the predictions of observable quantities in spherical-shock wave experiments. First, a non-infinite boundary condition is established by the isentropic release of the outer pressure. Second, a two-temperature system of ions and electrons allows description of higher temperatures while conserving energy and without perturbing the overall hydrodynamics of the solution. Furthermore, these modifications of the Guderley model improve the prediction of the observables in laser driven spherical shock experiments in reference to a one dimensional (1-D) hydrodynamics code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

MONTE CARLO POPULATION SYNTHESIS OF POST-COMMON-ENVELOPE WHITE DWARF BINARIES AND TYPE Ia SUPERNOVA RATE

Binary population synthesis (BPS) studies provide a comprehensive way to understand the evolution of binaries and their end products. Close white dwarf (WD) binaries have crucial characteristics for examining the influence of unresolved physical parameters on binary evolution. In this paper, we perform Monte Carlo BPS simulations, investigating the population of WD/main-sequence (WD/MS) binaries and double WD binaries using a publicly available binary star evolution code under 37 different assumptions for key physical processes and binary initial conditions. We considered different combinations of the binding energy parameter ( λ {sub g}: considering gravitational energy only; λ {sub b}: considering both gravitational energy and internal energy; and λ {sub e}: considering gravitational energy, internal energy, and entropy of the envelope, with values derived from the MESA code), CE efficiency, critical mass ratio, initial primary mass function, and metallicity. We find that a larger number of post-CE WD/MS binaries in tight orbits are formed when the binding energy parameters are set by λ {sub e} than in those cases where other prescriptions are adopted. We also determine the effects of the other input parameters on the orbital periods and mass distributions of post-CE WD/MS binaries. As they contain at least one CO WD, double WD systems that evolved from WD/MS binaries may explode as type Ia supernovae (SNe Ia) via merging. In this work, we also investigate the frequency of two WD mergers and compare it to the SNe Ia rate. The calculated Galactic SNe Ia rate with λ = λ {sub e} is comparable to the observed SNe Ia rate, ∼8.2 × 10{sup 5} yr{sup 1} – ∼4 × 10{sup 3} yr{sup 1} depending on the other BPS parameters, if a DD system does not require a mass ratio higher than ∼0.8 to become an SNe Ia. On the other hand, a violent merger scenario, which requires the combined mass of two CO WDs ≥ 1.6 M {sub ⊙} and a mass ratio >0.8, results in a much lower SNe Ia rate than is observed.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used to reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Internally cooled membrane-based absorber for dehumidification and water heating: Validated model and simulation study

This report presents a comprehensive model for advanced membrane-based absorber components accounting for three separate fluid streams, one of them providing internal cooling, with complex flow patterns. The model was implemented with various liquid desiccants and their properties (including LiCl, CaCl 2 , and [emim][OMS] ionic liquid [IL]). The model has been validated using data from two laboratory prototype absorbers, one with CaCl 2 as the working fluid and one with an IL as the working fluid. Entropy analysis was further carried out to verify the model and understand effect of internal cooling on the entropy variation of three fluid streams. The developed model and codes are expected to enable detailed configuration optimization and provide in-depth understanding of three-fluid heat and mass exchanger (HMX) performance. The paper also describes parametric studies of the HMX components in utilizing the latent heat removed in space cooling to heat water and numerically explores the unique benefit of its application in a semi-open absorption heat pump water heater. The results show that a single three-fluid HMX has the potential to achieve simultaneous dehumidification and water heating efficiently at cost effectiveness, particularly in hot and humid climates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

The interactional foundations of MaxEnt: Open questions

One of the simplest and potentially most useful techniques to be developed in the 20{sup th} century, a century noted for an ever more mathematically sophisticated formulation of the sciences, is that of maximising the entropy of a system in order to generate a descriptive, stochastic model of that system in closed form, often abbreviated to MaxEnt. The extension of MaxEnt to systems beyond the physics from which it originated is hampered by the fact that the microscopic physical interactions that are not justified or justifiable within the MaxEnt framework need to be falsifiably evaluated in each new field of application. It is not obvious that such justification exists for many systems in which the interactions are not directly based on physics. For example what is the justification for the use of MaxEnt in biology, climate modelling or economics? Is it simply a useful heuristic or is there some deeper connection with the foundations of some systems? Without further critical examination of the microscopic foundations that give rise to the success of the MaxEnt principle it is difficult to motivate the use of such techniques in other fields except through theoretically an practically unsatisfying analogical arguments. This article briefly presents the basis of MaxEnt principles as originally introduced in statistical mechanics in the Jaynes form, the Tsallis form and the Rényi form. Several different applications are introduced including that of ecological diversity where maximising the different diversity measures is equivalent to maximising different entropic functionals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

The evolution of gas giant entropy during formation by runaway accretion

We calculate the evolution of gas giant planets during the runaway gas accretion phase of formation, to understand how the luminosity of young giant planets depends on the accretion conditions. We construct steady-state envelope models, and run time-dependent simulations of accreting planets with the code Modules for Experiments in Stellar Astrophysics. We show that the evolution of the internal entropy depends on the contrast between the internal adiabat and the entropy of the accreted material, parametrized by the shock temperature T {sub 0} and pressure P {sub 0}. At low temperatures (T{sub 0}≲300–1000 K, depending on model parameters), the accreted material has a lower entropy than the interior. The convection zone extends to the surface and can drive a high luminosity, leading to rapid cooling and cold starts. For higher temperatures, the accreted material has a higher entropy than the interior, giving a radiative zone that stalls cooling. For T{sub 0}≳2000 K, the surface–interior entropy contrast cannot be accommodated by the radiative envelope, and the accreted matter accumulates with high entropy, forming a hot start. The final state of the planet depends on the shock temperature, accretion rate, and starting entropy at the onset of runaway accretion. Cold starts with L≲5×10{sup −6} L{sub ⊙} require low accretion rates and starting entropy, and the temperature of the accreting material needs to be maintained close to the nebula temperature. If instead the temperature is near the value required to radiate the accretion luminosity, 4πR{sup 2}σT{sub 0}{sup 4}∼(GM M-dot /R), as suggested by previous work on radiative shocks in the context of star formation, gas giant planets form in a hot start with L∼10{sup −4} L{sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

OpenMC In Situ Source Convergence Detection

We designed and implemented an in situ version of particle source convergence for the OpenMC particle transport simulator. OpenMC is a Monte Carlo based-particle simulator for neutron criticality calculations. For the transport simulation to be accurate, source particles must converge on a spatial distribution. Typically, convergence is obtained by iterating the simulation by a user-settable, fixed number of steps, and it is assumed that convergence is achieved. We instead implement a method to detect convergence, using the stochastic oscillator for identifying convergence of source particles based on their accumulated Shannon Entropy. Using our in situ convergence detection, we are able to detect and begin tallying results for the full simulation once the proper source distribution has been confirmed. Our method ensures that the simulation is not started too early, by a user setting too optimistic parameters, or too late, by setting too conservative a parameter.

42 ENGINEERING↗

DOE OSTI2023

Turbulence Modeling with Nek5000/RS, SOD2D and Alya

We present Validation and Verification (V & V) study of two high-order spectral element method (SEM) based Computational Fluid Dyanimcs (CFD) codes that we will utilize for work on turbulence modeling: Nek5000 and SOD2D. While the former solves the incompressible form of Navier-Stokes equation, the latter works with compressible set of equations and uses an entropy-viscosity formulation to account for the discontinuities for high Mach number flows. We demonstrate the accuracy of these codes for two benchmark sub-sonic turbulent flows: periodic channel and pipe flow, by carrying out first and second order statistical analysis, grid convergence and turbulent structure analysis using wall-resolved large eddy simulations (WRLES). Later, we report on the implementation and testing of various wall-modeling strategies for large eddy simulation of turbulent flows in Nek5000. These include both classical log-law based and decision-tree based machine-learning models. Accuracy of these closure strategies are analyzed and necessary future work is outlined.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Variational approach to relative entropies with an application to QFT

Abstract We define a new divergence of von Neumann algebras using a variational expression similar in nature to Kosaki’s formula for Umegaki’s relative entropy. Our divergence satisfies several of the usual desirable properties, upper bounds the sandwiched Renyi entropy and reduces to the fidelity in a limit. As an illustration, we use the formula in quantum field theory to compute our divergence between the vacuum in a bipartite system and an “orbifolded”—in the sense of a conditional expectation—system in terms of the Jones index. We take the opportunity to point out an entropic certainty relation associated with an inclusion of von Neumann factors related to the relative entropy. This certainty relation has an equivalent formulation in terms of error correcting codes.

Hollands, Stefan↗

DOE OSTI2023

Interaction models and configurational entropies of binary MoTa and the MoNbTaW high entropy alloy

We introduce a simplified method to model the interatomic interactions of high entropy alloys based on a lookup table of cluster energies. Furthermore, these interactions are employed in replica exchange Monte Carlo simulations with histogram analysis to obtain thermodynamic properties across a broad temperature range. Kikuchi's cluster variation method entropy formalism is applied to directly calculate entropy from statistics on short- and long-range chemical order, and we discuss the convergence of the entropy as clusters of differing size are included. A high temperature series expansion aids in our understanding of the convergence. Computer codes implementing these methods, and supporting data, are freely available on the internet.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Nemchinov-Dyson Solutions of the Two-Dimensional Axisymmetric Inviscid Compressible Flow Equations [Review]

We investigate the two-dimensional (2D) inviscid compressible flow equations in axisymmetric coordinates, constrained by an ideal gas equation of state (EOS). Beginning with the assumption that the 2D velocity field is space-time separable and linearly variable in each corresponding spatial coordinate, we proceed to derive an in nite family of elliptic or hyperbolic, uniformly expanding or contracting \gas cloud" solutions. Construction of specific example solutions belonging to this family is dependent on the solution of a system of nonlinear, coupled, second-order ordinary differential equations, and the prescription of an additional physical process of interest (e.g., uniform temperature or uniform entropy flow). The physical and computational implications of these solutions as pertaining to quantitative code verification or model qualification studies are discussed in some detail.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Diagnosing Undersampling in Monte Carlo Eigenvalue and Flux Tally Estimates

This study explored the impact of undersampling on the accuracy of tally estimates in Monte Carlo (MC) calculations. Steady-state MC simulations were performed for models of several critical systems with varying degrees of spatial and isotopic complexity, and the impact of undersampling on eigenvalue and fuel pin flux/fission estimates was examined. This study observed biases in MC eigenvalue estimates as large as several percent and biases in fuel pin flux/fission tally estimates that exceeded tens, and in some cases hundreds, of percent. This study also investigated five statistical metrics for predicting the occurrence of undersampling biases in MC simulations. Three of the metrics (the Heidelberger-Welch RHW, the Geweke Z-Score, and the Gelman-Rubin diagnostics) are commonly used for diagnosing the convergence of Markov chains, and two of the methods (the Contributing Particles per Generation and Tally Entropy) are new convergence metrics developed in the course of this study. These metrics were implemented in the KENO MC code within the SCALE code system and were evaluated for their reliability at predicting the onset and magnitude of undersampling biases in MC eigenvalue and flux tally estimates in two of the critical models. Of the five methods investigated, the Heidelberger-Welch RHW, the Gelman-Rubin diagnostics, and Tally Entropy produced test metrics that correlated strongly to the size of the observed undersampling biases, indicating their potential to effectively predict the size and prevalence of undersampling biases in MC simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Diagnosing undersampling in Monte Carlo eigenvalue and flux tally estimates - 14515

42 ENGINEERING↗

DOE OSTI2024

Diagnostics of Mixed-State Topological Order and Breakdown of Quantum Memory

Topological quantum memory can protect information against local errors up to finite error thresholds. Such thresholds are usually determined based on the success of decoding algorithms rather than the intrinsic properties of the mixed states describing corrupted memories. Here we provide an intrinsic characterization of the breakdown of topological quantum memory, which both gives a bound on the performance of decoding algorithms and provides examples of topologically distinct mixed states. We employ three information-theoretical quantities that can be regarded as generalizations of the diagnostics of ground-state topological order, and serve as a definition for topological order in error-corrupted mixed states. We consider the topological contribution to entanglement negativity and two other metrics based on quantum relative entropy and coherent information. In the concrete example of the two-dimensional (2D) Toric code with local bit-flip and phase errors, we map three quantities to observables in 2D classical spin models and analytically show they all undergo a transition at the same error threshold. This threshold is an upper bound on that achieved in any decoding algorithm and is indeed saturated by that in the optimal decoding algorithm for the Toric code. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Non-isobaric Thermal Instability

Multiphase media have very complex structure and evolution. Accurate numerical simulations are necessary to make advances in our understanding of this rich physics. Because simulations can capture both the linear and nonlinear evolution of perturbations with a relatively wide range of sizes, it is important to thoroughly understand the stability of condensation and acoustic modes between the two extreme wavelength limits of isobaric and isochoric instability as identified by Field. Partially motivated by a recent suggestion that large non-isobaric clouds can "shatter" into tiny cloudlets, we revisit the linear theory to survey all possible regimes of thermal instability. We uncover seven regimes in total, one of which allows three unstable condensation modes. Using the code Athena++, we determine the numerical requirements to properly evolve small amplitude perturbations of the entropy mode into the nonlinear regime. Here, our 1D numerical simulations demonstrate that for a typical AGN cooling function, the nonlinear evolution of a single eigenmode in an isobarically unstable plasma involves increasingly larger amplitude oscillations in cloud size, temperature, and density as the wavelength increases. Such oscillations are the hallmark behavior of non-isobaric multiphase gas dynamics and may be observable as correlations between changes in brightness and the associated periodic redshifts and blueshifts in systems that can be spatially resolved. Intriguingly, we discuss regimes and derive characteristic cloud sizes for which the saturation process giving rise to these oscillations can be so energetic that the cloud may indeed break apart. However, we dub this process "splattering" instead of "shattering," as it is a different fragmentation mechanism that is triggered when the cloud suddenly "lands" on the stable cold branch of the equilibrium curve.

79 ASTRONOMY AND ASTROPHYSICS↗