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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Emergence of many-body quantum chaos via spontaneous breaking of unitarity

It is suggested that many-body quantum chaos appears as the spontaneous symmetry breaking of unitarity in interacting quantum many-body systems. It has been shown that many-body level statistics, probed by the spectral form factor (SFF) defined as K(η,t)=$\langle$|Tr exp(-ηH+itH)| 2 $\rangle$, is dominated by a diffuson-type mode in a field theory analysis. The key finding of this Letter is that the “unitary” η = 0 case is different from the η → 0 ± limit, with the latter leading to a finite mass of these modes due to interactions. This mass suppresses a rapid exponential ramp in the SFF, which is responsible for the fast emergence of Poisson statistics in the noninteracting case, and gives rise to a nontrivial random matrix structure of many-body levels. The interaction-induced mass in the SFF shares similarities with the dephasing rate in the theory of weak localization and the Lyapunov exponent of the out-of-time-ordered correlators.

36 MATERIALS SCIENCE↗
DOE OSTI2020

From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world

Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon-climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool-based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool-based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. In this study, we propose a novel conceptual framework to explore controls on belowground carbon cycling: Probabilistic Representation of Organic Matter Interactions within the Soil Environment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction, such as Proper Orthogonal Decomposition. The limitation of the linear nature of such operators is typically tackled via a library of local reduction subspaces, which requires the assembly of numerous local ROMs to address parametric dependencies. Our work attempts to define a more generalisable mapping between parametric inputs and reduced bases for the purpose of generative modeling. We propose the use of Variational Autoencoders (VAEs) in place of the typically utilised clustering or interpolation operations, for inferring the fundamental vectors, termed as modes, which approximate the manifold of the model response for any and each parametric input state. The derived ROM still relies on projection bases, built on the basis of full-order model simulations, thus retaining the imprinted physical connotation. However, it additionally exploits a matrix of coefficients that relates each local sample response and dynamics to the global phenomena across the parametric input domain. The VAE scheme is utilised for approximating these coefficients for any input state. This coupling leads to a high-precision low-order representation, which is particularly suited for problems where model dependencies or excitation traits cause the dynamic behavior to span multiple response regimes. Moreover, the probabilistic treatment of the VAE representation allows for uncertainty quantification on the reduction bases, which may then be propagated to the ROM response. The performance of the proposed approach is validated on an open-source simulation benchmark featuring hysteresis and multi-parametric dependencies, and on a large-scale wind turbine tower characterised by nonlinear material behavior and model uncertainty.

Conditional VAEs↗
DOE OSTI2014

Inflationary power asymmetry from primordial domain walls

We study the asymmetric primordial fluctuations in a model of inflation in which translational invariance is broken by a domain wall. We calculate the corrections to the power spectrum of curvature perturbations; they are anisotropic and contain dipole, quadrupole, and higher multipoles with non-trivial scale-dependent amplitudes. Inspired by observations of these multipole asymmetries in terms of two-point correlations and variance in real space, we demonstrate that this model can explain the observed anomalous power asymmetry of the cosmic microwave background (CMB) sky, including its characteristic feature that the dipole dominates over higher multipoles. We test the viability of the model and place approximate constraints on its parameters by using observational values of dipole, quadrupole, and octopole amplitudes of the asymmetry measured by a local-variance estimator. We find that a configuration of the model in which the CMB sphere does not intersect the domain wall during inflation provides a good fit to the data. We further derive analytic expressions for the corrections to the CMB temperature covariance matrix, or angular power spectra, which can be used in future statistical analysis of the model in spherical harmonic space.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Thermal expansion of plasma-exposed tungsten

We report results from a systematic analysis of thermal expansion of plasma-exposed tungsten based on molecular-dynamics simulations using models of tungsten with distributions of helium (He) bubbles in the tungsten matrix. We distinguish between two approaches of filling the bubbles with He, where the amount of He in the bubble can or cannot vary with temperature. In the former case, the thermal expansion coefficient decreases monotonically with the porosity and He content of the tungsten matrix, while in the latter case, the thermal expansivity increases monotonically with increasing porosity and He content. The latter condition, where the He content in the bubble is determined at the implantation temperature and remains constant with varying temperature in the tungsten matrix, is consistent with He species transport in tungsten used as a plasma-facing component (PFC) in nuclear fusion reactors and implies the development of biaxial compressive thermal strains in the PFC material that contribute to accelerating the growth of a nanostructure on PFC tungsten surfaces. Furthermore our analysis advances the fundamental understanding of thermal expansion in PFC tungsten and contributes to the development of a thermophysical property database for properly incorporating effects of realistic heat loads into modeling the dynamical response of PFC tungsten under fusion reactor operating conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples

Terrestrial ecosystems absorb roughly 30% of anthropogenic CO 2 emissions since preindustrial era, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling, experimental, and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under climate change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Furthermore, this and our other studies have demonstrated that one matrix equation can exactly replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. Moreover, the emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. We also propose that the C storage potential be the targeted variable for research, market trading, and government negotiation for C credits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Active learning emulators for nuclear two-body scattering in momentum space

In this work we extend the active learning emulators for two-body scattering in coordinate space with error estimation, recently developed by Maldonado et al. [Phys. Rev. C 112, 024002], to coupled-channel scattering in momentum space. Our full-order model (FOM) solver is based on the Lippmann-Schwinger integral equation for the scattering t-matrix as opposed to the radial Schrödinger equation. We use (Petrov-)Galerkin projections and high-fidelity calculations at a few snapshots across the parameter space of the interaction to construct efficient reduced-order models (ROMs), trained by a greedy algorithm for locally optimal snapshot selection. Both the FOM solver and the corresponding ROMs are implemented efficiently in Python using Google's JAX library. We present results for emulating scattering phase shifts in coupled and uncoupled channels and cross sections, and assess the accuracy of the developed ROMs and their computational speedup factors. We also develop emulator error estimation for both the t-matrix and the total cross section. The software framework for reproducing and extending our results is publicly available. Together with our recent advances in developing active-learning emulators for three-body scattering, these emulator frameworks set the stage for full Bayesian calibrations of chiral nuclear interactions and optical models against scattering data with quantified emulator errors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Optical Properties of Planar and Annular Ternary Superconducting Photonic Crystals in Near-Zero-Permittivity Operation Range

Optical properties of ternary superconducting planar/annular photonic crystals composed of a high-temperature superconductor and two dielectrics were theoretically investigated based on transfer matrix methods in Cartesian and cylindrical coordinates. Electrodynamics of superconductor were modelled using two-fluid model. It is of interest to observe that, for a planar structure, there exists an additional high reflectance band termed as superpolariton gap near the superconducting threshold wavelength for the TM wave at oblique incidences and some reflection dips also were found in the TM reflectance. However, the superpolariton gap and reflection dips were seen for an annular geometry at higher order azimuthal number. For an annular structure, the size of superpolariton gap can be controlled by simply adjusting the starting radius. Moreover, the superpolariton gap in both structures strongly depends on the operating temperature, different combinations of dielectric refractive indices, and thicknesses of dielectric materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

A Sparse Tableau Formulation for Node-Breaker Representations in Security-Constrained Optimal Power Flow

Realistic representations of contingencies in AC optimal power flow (ACOPF) often challenge traditional bus-branch network models. Derived from nodal analysis, such approaches represent network constraints in terms of the familiar bus admittance matrix, Ybus. A fixed Ybus is unable to represent common circuit breaker actions such as bus splitting. Work-arounds for Ybus-based analysis typically rely on topology processing, switching between different Ybus matrices depending on breaker settings. In this paper, we propose a very general node-breaker approach, employing multi-port element models and using a sparse tableau formulation (STF) for network constraints. Instead of treating breaker action as altering network topology, and hence changing the structure of Kirchhoff’s voltage law (KVL) and Kirchhoff’s current law (KCL) equations, this approach represents a breaker’s position as impacting only constraints associated with a single component, thereby maintaining fixed structure in the KVL and KCL constraints. While larger numbers of variables are required, STF proves sparser than Ybus formulations. Numerical case studies herein demonstrate that STF provides computational efficiency comparable to a Ybus-based ACOPF at the scale of several hundred buses, and lower computational cost in an example of over one thousand buses.

Park, Byungkwon (ORCID:000000033189816X)↗
DOE OSTI2017

Heat Source Characterization in a TREAT Fuel Particle Using Coupled Neutronics-BCMC Calculations

This work presents a multi-physics, multi-scale approach to modeling the Transient Test Reactor (TREAT) currently prepared for restart at the Idaho National Laboratory. TREAT fuel is made up of microscopic fuel grains (r ˜ 20µm) dispersed in a graphite matrix. The novelty of this work is in coupling a binary collision Monte-Carlo (BCMC) model to the Finite Element based code Moose for solving a microsopic heat-conduction problem whose driving source is provided by the BCMC model tracking fission fragment energy deposition. This microscopic model is driven by a transient, engineering scale neutronics model coupled to an adiabatic heating model. The macroscopic model provides local power densities and neutron energy spectra to the microscpic model. Currently, no feedback from the microscopic to the macroscopic model is considered. TREAT transient 15 is used to exemplify the capabilities of the multi-physics, multi-scale model, and it is found that the average fuel grain temperature differs from the average graphite temperature by 80 K despite the low-power transient. The large temperature difference has strong implications on the Doppler feedback a potential LEU TREAT core would see, and it underpins the need for multi-physics, multi-scale modeling of a TREAT LEU core.

36 MATERIALS SCIENCE↗
DOE OSTI2016

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemble forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.

58 GEOSCIENCES↗
DOE OSTI2018

Complex magnetic order in nickelate slabs

Here, magnetic ordering phenomena have a profound influence on the macroscopic properties of correlated-electron materials, but their realistic prediction remains a formidable challenge. An archetypical example is the ternary nickel oxide system RNiO 3 (R = rare earth), where the period-four magnetic order with proposals of collinear and non-collinear structures and the amplitude of magnetic moments on different Ni sublattices have been subjects of debate for decades. Here we introduce an elementary model system—NdNiO 3 slabs embedded in a non-magnetic NdGaO 3 matrix—and use polarized resonant X-ray scattering (RXS) to show that both collinear and non-collinear magnetic structures can be realized, depending on the slab thickness. The crossover between both spin structures is correctly predicted by density functional theory and can be qualitatively understood in a low-energy spin model. We further demonstrate that the amplitude ratio of magnetic moments in neighbouring NiO 6 octahedra can be accurately determined by RXS in combination with a correlated double cluster model. Targeted synthesis of model systems with controlled thickness and synergistic application of polarized RXS and ab initio theory thus provide new perspectives for research on complex magnetism, in analogy to two-dimensional materials created by exfoliation.

25 ENERGY STORAGE↗
DOE OSTI2017

Use of multiscale zirconium alloy deformation models in nuclear fuel behavior analysis

Accurate prediction of cladding mechanical behavior is a key aspect of modeling nuclear fuel behavior, especially for conditions of pellet-cladding interaction (PCI), reactivity-initiated accidents (RIA), and loss of coolant accidents (LOCA). Current approaches to fuel performance modeling rely on empirical constitutive models for cladding creep, growth and plastic deformation, which are limited to the materials and conditions for which the models were developed. To improve upon this approach, a microstructurally-based zirconium alloy mechanical deformation analysis capability is being developed within the United States Department of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL). Specifically, the viscoplastic self-consistent (VPSC) polycrystal plasticity modeling approach, developed by Lebensohn and Tomé [1], has been coupled with the BISON engineering scale fuel performance code to represent the mechanistic material processes controlling the deformation behavior of light water reactor (LWR) cladding. A critical component of VPSC is the representation of the crystallographic nature (defect and dislocation movement) and orientation of the grains within the matrix material and the ability to account for the role of texture on deformation. A future goal is for VPSC to obtain information on reaction rate kinetics from atomistic calculations to inform the defect and dislocation behavior models described in VPSC. The multiscale modeling of cladding deformation mechanisms allowed by VPSC far exceed the functionality of typical semi-empirical constitutive models employed in nuclear fuel behavior codes to model irradiation growth and creep, thermal creep, or plasticity. This paper describes the implementation of an interface between VPSC and BISON and provides initial results utilizing the coupled functionality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Overcoming photobleaching in imaging of single barium atoms in a solid xenon matrix

Neutrinoless double beta decay is one of the most sensitive probes for new physics beyond the Standard Model of particle physics. One of the isotopes under investigation is 136 Xe, which would double beta decay into 136 Ba. Detecting the single 136 Ba daughter provides a sort of ultimate tool in the discrimination against backgrounds. Previous work demonstrated the ability to perform single atom imaging of Ba atoms in a single-vacancy site of a solid xenon matrix. In this paper, the effort to identify signal from individual barium atoms is extended to Ba atoms in a hexa-vacancy site in the matrix and is achieved despite increased photobleaching in this site. Abrupt fluorescence turn-off of a single Ba atom is also observed. Significant recovery of fluorescence signal lost through photobleaching is demonstrated upon annealing of Ba deposits in the Xe ice. Following annealing, it is observed that Ba atoms in the hexa-vacancy site exhibit antibleaching while Ba atoms in the tetra-vacancy site exhibit bleaching. This may be evidence for a matrix site transfer upon laser excitation. Our findings offer a path of continued research toward tagging of Ba daughters in all significant sites in solid xenon.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Isolated Single-stage Three-phase AC/DC Converter using Bidirectional Switches

The advent of the SiC Bidirectional FET (BiDFET), a monolithic 1.2 kV bidirectional switch, has rendered the single-stage three-phase AC/DC converter topology a promising approach for implementing AC/DC converters. This topology, which integrates a full-bridge converter with a single-phase to three-phase matrix converter via a high-frequency transformer, is particularly suitable for applications requiring galvanic isolation, buck-boost functionality, and bidirectional power flow. The single-stage design eliminates the need for bulky and unreliable electrolytic capacitors, and utilizes a single magnetic component for power transfer. In the matrix converter, bidirectional switches, which were traditionally implemented using combinations of multiple semiconductor devices such as MOSFETs, IGBTs, and diodes, can now be realized using the single-chip solution, BiDFET. This advancement leads to a lower switch count, compact converter implementation, with lower inductance commutation cells, thereby enhancing the overall efficiency and compactness of the system. The paper presents a unified model of the converter, considering all control parameters, including the duty cycles and phase shift of transformer voltages. Detailed expressions for power transfer, transformer currents, and currents at AC and DC ports are provided. Additionally, the paper outlines the conditions necessary for soft-switching of all switches and the commutation schemes required for the practical implementation of the matrix converter modulation scheme. A hardware prototype of a 10 kW, 480 VRMS, LL/ 800 V AC/DC system has been developed, and experimental results are presented to demonstrate its performance.

BiDFET↗
DOE OSTI2021

Development of CTF modeling of interfacial drag, wall shear, and interfacial heat transfer for bubbly and annular-mist flow regimes

This milestone report discusses improvements to CTF closure models for modeling of bubbly and annular mist two-phase flow conditions, which are important for accurate modeling and simulation for boiling water reactor (BWR) conditions. Models that were improved include the two-phase wall shear, wall boiling, and phase mass and heat transfer. A new flow regime map was implemented to improve on the prediction of transition to annular flow, which was generally largely over-predicted by the legacy CTF flow regime map. The annular mist interfacial drag models were also reviewed and new models were proposed for implementation into the code. In addition to implementing new models, an activity was performed to calibrate these new models to experimental data using a Markov Chain Monte Carlo technique, thus further improving their accuracy. Finally, new experiments were implemented into the CTF validation matrix which add more two-phase pressure drop and void measurements for the assessment of CTF for modeling of BWRs. The results show that the Chisholm model, which was implemented and then calibrated, results in significantly improved comparison against the Riso two-phase pressure drop data. Furthermore, improvements in the implicit heat transfer and wall boiling models resulted in good agreement with the void measurement data.

42 ENGINEERING↗
DOE OSTI2016

An efficient computational approach to model statistical correlations in photon counting x-ray detectors

Purpose: To introduce and evaluate an increment matrix approach (IMA) describing the signal statistics of energy-selective photon counting detectors including spatial–spectral correlations between energy bins of neighboring detector pixels. The importance of the occurring correlations for image-based material decomposition is studied. Methods: An IMA describing the counter increase patterns in a photon counting detector is proposed. This IMA has the potential to decrease the number of required random numbers compared to Monte Carlo simulations by pursuing an approach based on convolutions. To validate and demonstrate the IMA, an approximate semirealistic detector model is provided, simulating a photon counting detector in a simplified manner, e.g., by neglecting count rate-dependent effects. In this way, the spatial–spectral correlations on the detector level are obtained and fed into the IMA. The importance of these correlations in reconstructed energy bin images and the corresponding detector performance in image-based material decomposition is evaluated using a statistically optimal decomposition algorithm. Results: The results of IMA together with the semirealistic detector model were compared to other models and measurements using the spectral response and the energy bin sensitivity, finding a good agreement. Correlations between the different reconstructed energy bin images could be observed, and turned out to be of weak nature. These correlations were found to be not relevant in image-based material decomposition. An even simpler simulation procedure based on the energy bin sensitivity was tested instead and yielded similar results for the image-based material decomposition task, as long as the fact that one incident photon can increase multiple counters across neighboring detector pixels is taken into account. Conclusions: The IMA is computationally efficient as it required about 10{sup 2} random numbers per ray incident on a detector pixel instead of an estimated 10{sup 8} random numbers per ray as Monte Carlo approaches would need. The spatial–spectral correlations as described by IMA are not important for the studied image-based material decomposition task. Respecting the absolute photon counts and thus the multiple counter increases by a single x-ray photon, the same material decomposition performance could be obtained with a simpler detector description using the energy bin sensitivity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Search for heavy Majorana neutrinos in e ± e ± and e ± μ ± final states via WW scattering in pp collisions at s = 13 TeV with the ATLAS detector

A search for heavy Majorana neutrinos in scattering of same-sign W boson pairs in proton–proton collisions at $\sqrt{s}$ = 13 TeV at the LHC is reported. The dataset used corresponds to an integrated luminosity of 140 fb -1 , collected with the ATLAS detector during 2015–2018. The search is performed in final states including a same-sign ee or eμ pair and at least two jets with large invariant mass and a large rapidity difference. No significant excess of events with respect to the Standard Model background predictions is observed. The results are interpreted in a benchmark scenario of the Phenomenological Type-I Seesaw model. New constraints are set on the values of the |V eN | 2 and |V eN V$^{*}_{μN}$| parameters for heavy Majorana neutrino masses between 50 GeV and 20 TeV, where V ℓN is the matrix element describing the mixing of the heavy Majorana neutrino mass eigenstate with the Standard Model neutrino of flavour ℓ = e,μ. The sensitivity to the Weinberg operator is investigated and constraints on the effective ee and eμ Majorana neutrino masses are reported. The statistical combination of the ee and eμ channels with the previously published μμ channel is performed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗