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DOE OSTI2022

Improvement of two-phase closure models in CTF using Bayesian inference

Under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, extensive capabilities have been developed in CTF to analyze light-water reactors (LWRs) for normal operating conditions, departure from nucleate boiling (DNB), and system transients. However, further improvements are required in the modeling and simulation of boiling water reactors (BWRs), which is a focus of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this work, CTF validation results were used to optimize selected modeling coefficients by calibrating to experimental data using a Bayesian inference approach. Here, calibration studies were conducted to improve (vapor) void fraction prediction without worsening the two-phase pressure drop prediction, as well as to improve the two-phase pressure drop prediction. Calibration was performed for interfacial drag and wall shear models. Surrogates were developed to alleviate the computational expense required for sampling the parameter space using Markov chain Monte Carlo (MCMC). An assessment performed with calibrated models demonstrated an improvement of CTF in its prediction of key parameters such as void fraction and two-phase pressure drop.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Upsampling Monte Carlo Reactor Simulation Tallies in Depleted Sodium-Cooled Fast Reactor Assemblies Using a Convolutional Neural Network

The computational demand of neutron Monte Carlo transport simulations can increase rapidly with the spatial and energy resolution of tallied physical quantities. Convolutional neural networks have been used to increase the resolution of Monte Carlo simulations of light water reactor assemblies while preserving accuracy with negligible additional computational cost. Here, we show that a convolutional neural network can also be used to upsample tally results from Monte Carlo simulations of sodium-cooled fast reactor assemblies, thereby extending the applicability beyond thermal systems. The convolutional neural network model is trained using neutron flux tallies from 300 procedurally generated nuclear reactor assemblies simulated using OpenMC. Validation and test datasets included 16 simulations of procedurally generated assemblies, and a realistic simulation of a European sodium-cooled fast reactor assembly was included in the test dataset. We show the residuals between the high-resolution flux tallies predicted by the neural network and high-resolution Monte Carlo tallies on relative and absolute bases. The network can upsample tallies from simulations of fast reactor assemblies with diverse and heterogeneous materials and geometries by a factor of two in each spatial and energy dimension. The network’s predictions are within the statistical uncertainty of the Monte Carlo tallies in almost all cases. This includes test assemblies for which burnup values and geometric parameters were well outside the ranges of those in assemblies used to train the network.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Understanding Anomalous Gas-Phase Peak Shifts in Dip-and-Pull Ambient Pressure XPS Experiments

Dip-and-pull ambient pressure X-ray photoelectron spectroscopy (AP-XPS) holds promise to uncover elementary processes of (photo)electrochemistry. We show, however, that the sample for such experiments should preferably be nonporous and the potential on the surface homogeneous. We carried out dip-and-pull AP-XPS experiments on a hematite thin film sample under the photoelectrochemical oxygen evolution reaction (OER) and find unexpected O 1s core level shifts. Upon electrochemical biasing under simulated solar light illumination, the gas-phase water peak shifted more than the electrolyte peak. To uncover the origin of the unexpected larger shift of the gas-phase peak, we performed electrostatic simulations using COMSOL, to map the potential field in the relevant volume between the sample and the first aperture of the XPS spectrometer. A number of geometric models were considered. We find that when the potential on the sample surface is inhomogeneous, e.g., with ionically isolated electrolyte patches, the gas-phase peak of the spectrum can shift more than the peak due to the electrolyte film. This suggests that at the measured sample position, the local potential was not as set by the potentiostat. Despite this, we find reversible consumption and replenishment of hydroxide in the spectra, which, due to OH– being the reactant of the OER in alkaline electrolyte, makes sense chemically. We propose that this is linked to OH– diffusion across the measured sample position, driven by the potential dependent consumption and replenishment of OH– at the nearby well-connected surface regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Digital quantum simulation of non-equilibrium quantum many-body systems

Digital quantum simulation uses the capabilities of quantum computers to determine the dynamics of quantum systems, which are beyond the computability of modern classical computers. A notoriously challenging task in this field is the description of non-equilibrium dynamics in quantum many-body systems. In this study, we used the IBM quantum computers to simulate the non-equilibrium dynamics of few spin and fermionic systems. Our results reveal that with a combination of error mitigation, noise extrapolation and optimized initial state preparation, one can tackle the most important drawbacks of modern quantum devices. The systems we simulate demonstrate the potential for large-scale quantum simulations of light–matter interactions in the near future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Multiscale Ecosystem for solving Maxwell-Schrodinger equations of open quantum systems (OpenMS)

Light-matter interactions play an important role in many branches of physics, chemistry, energy, and materials science. In the strong coupling regime, light-matter interactions are able to tune the materials properties via the formation of new quasiparticles, such as plasmons and polaritons. However, theoretical and numerical modeling of the light-matter interaction-mediated processes remain a big challenge because light-matter interactions are fundamentally multiscale and multiphysics problems involving multiple interactions between electrons, nuclei, and photons at different time/length scales. In the current community, light-matter interactions were treated at different levels of theoretical complexity in quantum chemistry and quantum optics. In quantum optics or quantum photonics, the matter is usually simplified as a few-level system, and the light is treated quantum-mechanically. On the other hand, quantum chemistry explores first-principles methods, including both single-particle and many-body-based techniques, to describe the electronic properties of matter in detail. However, light is usually prescribed as a classical electromagnetic field, and the light-matter interaction is taken into account as an external potential via classical approximations. This software is designed to fill current modeling shortcomings by delivering a first-ever scalable multiscale platform for simulating light-matter interactions in realistic electromagnetic environments. The software solves Maxwell and Schrodinger equations self-consistent on the heterogeneous platforms. It implements HF/DFT, TDDFT, and coupled-cluster counterparts for light-matter interactions and adopts modular programming to offload massively parallel algorithms on a large number of CPU/GPUs.

Zhang, Yu↗

DOE OSTI2022

Investigation of long-term light stability of negative charge injected into oxide-nitride-oxide passivation stack of crystalline silicon solar cells

A negatively charged oxide-nitride-oxide stack for field-effect passivation of crystalline silicon solar cells is discussed. The negative charge was injected into the stack by a plasma charge injection technology. Charge stability was studied by exposing samples to AM1.5 simulation visible light and full-spectrum light at temperatures ranging from 55 to 78 °C for up to 300 h. Charge injection and loss were quantified based on shifts in the flatband voltage of capacitance–voltage curves measured with a mercury probe. The most probable mechanism of charge loss was found to be diffusion of negative charged hydrogen atoms through nitride and bottom oxide. The optimum recipe for each layer of the stack was investigated to minimize the loss of injected charge. The flatband voltage decay of the optimized stack was found to fit a power-law trend, suggesting the dispersive transport of hydrogen atoms with a dispersion parameter of ~0.06–0.07. The optimized stack is projected to maintain a negative charge density of about 3.6 × 10 12 cm –2 or more after 25 years of field operation in an environment such as Arizona, which would be sufficient for field-effect passivation under one-sun illumination. Furthermore, the high stability of the negative injected charge makes the plasma charging technology a safer and lower cost alternative to Al 2 O 3 -passivation technology commonly used to passivate p-type surfaces.

14 SOLAR ENERGY↗

DOE OSTI2025

A High-Fidelity Model of the Peach Bottom 2 Turbine-Trip Benchmark Using VERA

This work presents a high-fidelity simulation of the Peach Bottom turbine trip (PBTT) benchmark using the Virtual Environment for Reactor Applications (VERA), a multiphysics reactor modeling tool developed by the U.S. Department of Energy’s Consortium for Advanced Simulation of Light Water Reactors energy innovation hub. The PBTT benchmark, based on a 1977 transient event at the end of cycle 2 in a General Electric Type-4 boiling water reactor (BWR), is a critical test case for validating core physics models with thermal feedback during rapid reactivity events. VERA was employed to perform end-to-end, pin-resolved simulations from conditions at the beginning of cycle 1 through the turbine-trip transient, incorporating detailed neutron transport, fuel depletion, and subchannel thermal hydraulics. The simulation reproduced key benchmark observables with high accuracy: the peak power excursion occurred at 0.75 s, matching the scram time and closely aligning with the benchmark average of 0.742 s; the simulated maximum power spike was approximately 7600 MW, which is within 3% of the benchmark average of 7400 MW; and void-collapse dynamics were consistent with benchmark expectations. Reactivity predictions during cycles 1 and 2 remained within 1500 pcm and 400 pcm of criticality, respectively. These results confirm VERA’s ability to model complex coupled neutronic and thermal hydraulic behavior in a BWR turbine-trip transient, which will support its use in future studies of modeling dryout, fuel performance, and uncertainty quantification for transients of this type.

BWR↗

DOE OSTI2020

Development of the MPACT 69-group Library for Magnox Reactor Analysis using CASL VERA

The Consortium for Advanced Simulation of Light Water Reactors (CASL) has developed the CASL toolset, Virtual Environment for Reactor Analysis (VERA), for pressurized water reactor (PWR) analysis. Recently the CASL VERA was improved for Magnox reactor analysis, which required the development of a new cross section library and new geometrical and thermal feedback capabilities for graphite-moderated Magnoxreactors. The MPACT neutronics module of the CASL core simulator is a 3D whole core transport code, which requires a new cross section library with a different energy group structure due to the different neutronic characteristics of Magnox compared with PWR. A new 69-group structure was developed based on the MPACT 51-group structure to have more thermal energy groups and to be a subset of the SCALE 252-group structure. The ENDF/B-VII.1 MPACT 69-group library was developed for Magnox reactor analysis using the SCALE/AMPX and VERA-XSTools for which a super-homogenization method was applied, and transport cross sections were generated for graphite using a neutron leakage conservation method. Benchmark results show that new MPACT 69-group library works reasonably well for Magnox reactor analysis.

Kim, Kang Seog↗

DOE OSTI2026

A Nonparametric Method for the Inference of Halo Occupation Distributions

The galaxy–halo connection traces processes by which galaxies form and evolve. The halo occupation distribution (HOD) describes the relationship between galaxies and their host dark matter haloes. Measurements of the galaxy two-point correlation function (2PCF) allow us to extract information about the HODs of observed galaxy samples. Several parametric HOD models have been proposed in the literature, but the choice of parameterization restricts the space of possible HODs. To resolve this issue, we introduce a nonparametric HOD fitting method in which we train an emulator to learn the mappings among the galaxy 2PCF, physical properties used to select galaxy samples, and the HOD, all obtained from simulated past light cones constructed with the Santa Cruz semianalytic model. Implementing this emulator within a likelihood analysis framework, we derive constraints on the HOD of a galaxy sample when provided with a measurement of its 2PCF. Using the emulator to accelerate likelihood evaluations, we test the nonparametric HOD approach on a set of 2PCFs for mock galaxy samples drawn from the TNG100-1 simulation and selected above threshold values of stellar mass and star formation rate. Our framework is able to recover TNG100-1 HODs within 0.2 dex. We use the TNG100-1 mocks to tune the reported uncertainties to estimate those expected in the analysis of observations. Comparing to parametric HOD modelling routines applied to the same mock galaxy samples, our approach consistently infers the HOD with comparable or greater precision and accuracy.

Kennedy, Jacob [Rutgers Univ., Piscataway, NJ (Uni↗

DOE OSTI2020

Subchannel codes: CTF and VIPRE-01

In this chapter, two state-of-the-art and well-used subchannel codes are presented: CTF and VIPRE-01. As part of the Consortium for Advanced Simulation of Light Water Reactors, CTF is being used for single- and two-phase flow analysis under light-water reactor normal and anticipated transient operating conditions. Accurate determination of flow distribution, pressure drop, and void content is crucial for predicting margins to thermal crisis and ensuring more efficient nuclear power plant performance. In preparation for the intended applications, CTF is extensively validated against data from experimental facilities. Meanwhile, the licensed commercial code VIPRE-01 is used to generate a baseline set of simulations for the targeted tests and the solution parameters are compared to CTF results. The closure models in CTF that are in the greatest need of improvement are highlighted and discussed.

Zhao, Xingang↗

DOE OSTI2021

The Effect of Spectral Resolution of Light Sources on Photopic and a-opic Quantities

There is a growing interest in including light source spectrum in advanced lighting software tools and simulations. Given that traditional lighting software tools have been used primarily for calculating photometric quantities, their simplifying assumptions may not be suitable for calculating other a-opic quantities. Commonly used simulation tools use three values to represent the three primary colors (red, green, and blue), but others have expanded the number of bands (i.e., the spectral resolution) to 9, 27, or 81 in an attempt to more accurately represent variations in light source spectrum and downstream spectrally-derived quantities. It remains unclear, however, to what extent spectral resolution affects calculated quantities. To address this gap, a numerical analysis was completed using a large spectral power distribution database (n = 1,302 light sources). Calculated illuminance, a-opic irradiance, luminous efficacy of radiation (LER), melanopic efficacy of radiation (MER), and melanopic to photopic (M/P) ratio were compared for spectral resolutions of 3 and 9 bands compared to a baseline of 81 bands. Across all examined lighting quantities, considerable errors—a mean absolute percent error of 18.4%—were found when using 3 band calculations. These were reduced to 4% for 9 band calculations. The errors varied by metric and light source type. The results suggest that the use of 9 bands can more accurately characterize performance of different light source types across a range of metrics compared to using 3 bands.

Abboushi, Belal K.↗

DOE OSTI2024

Complex-valued universal linear transformations and image encryption using spatially incoherent diffractive networks

As an optical processor, a diffractive deep neural network (D2NN) utilizes engineered diffractive surfaces designed through machine learning to perform all-optical information processing, completing its tasks at the speed of light propagation through thin optical layers. With sufficient degrees of freedom, D2NNs can perform arbitrary complex-valued linear transformations using spatially coherent light. Similarly, D2NNs can also perform arbitrary linear intensity transformations with spatially incoherent illumination; however, under spatially incoherent light, these transformations are nonnegative, acting on diffraction-limited optical intensity patterns at the input field of view. Here, we expand the use of spatially incoherent D2NNs to complex-valued information processing for executing arbitrary complex-valued linear transformations using spatially incoherent light. Through simulations, we show that as the number of optimized diffractive features increases beyond a threshold dictated by the multiplication of the input and output space-bandwidth products, a spatially incoherent diffractive visual processor can approximate any complex-valued linear transformation and be used for all-optical image encryption using incoherent illumination. The findings are important for the all-optical processing of information under natural light using various forms of diffractive surface-based optical processors.

36 MATERIALS SCIENCE↗

DOE OSTI2022

CTF: A modernized, production-level, thermal hydraulic solver for the solution of industry-relevant challenge problems in pressurized water reactors

CTF is a thermal hydraulic (T/H) subchannel tool that has been extensively developed over the past ten years as part of the Consortium for Advanced Simulation of Light Water Reactors (CASL) program. The code was selected early in the CASL program for support of high-impact challenge problems that were found to be relevant to the nuclear industry and its currently operating fleet of pressurized water reactors (PWRs), including issues such as departure from nucleate boiling (DNB), crud-induced power shifts (CIPSs), and reactivity-insertion accidents (RIAs). By incorporating CTF into the multiphysics Virtual Environment for Reactor Application (VERA) core simulator software developed by CASL, CTF has become the primary means of providing fluid and fuel thermal feedback, as well as T/H figure-of-merits (FOMs) in large-scale reactor simulations. With the goal of solving industry challenge problems, CASL placed great emphasis on developing high-quality, high-performance, validated software tools that offer higher fidelity than what is currently possible with current industry methods. In support of this effort, CTF was developed from a research tool into an nuclear quality assurance (NQA-1)–compliant, production-level software tool that is capable of addressing the stated challenge problems and goals of CASL. This work presents a review of the major technological achievements that were realized in developing CTF over the past decade of the CASL program and presents an overview of the code solution approach and closure models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

BISON capability and validation for U3Si2, Cr2O3-doped UO2, FeCrAl, and Cr-coated Zircaloy ATF concepts

Development, implementation, and validation of material and behavior models for accident tolerant fuel (ATF) concepts in the BISON fuel performance code began in 2014 in response to the events that occurred at the Fukushima Daichii nuclear power plant in March 2011. Early on, the focus was on U3Si2 fuel and FeCrAl cladding as part of a high-impact problem through the Nuclear Energy and Advanced Model- ing Simulation program [1]. Then, developments for Cr2O3- doped UO2 fuel, as well as SiC-SiC and Cr-coated Zircaloy cladding began based upon industry interests. Near the end of fiscal year 2018 the Consortium for Advanced Simulation of Light Water Reactors took over further Accident Tolerant Fuel (ATF) work in BISON in support of Nuclear Regulatory Commission (NRC) engagement. Discussions with the NRC clarified their list of priority fuel and cladding concepts, which included Cr2O3-doped UO2 and U3Si2 fuels, as well as Cr-coated Zircaloy and FeCrAl claddings. Further, reports similar in form to NUREG/CR-7024 [2] that was developed for traditional light water reactor (LWR) materials, UO2 fuel with Zircaloy claddings were created for the priority fuel and cladding concepts. In this paper select details from the reports entitled "ATF material model development and validation for priority fuel concepts" [3] and "ATF material model development and validation for priority cladding concepts" [4] are presented. First, a brief overview of the available models and their associated uncertainty are provided for the priority fuel and cladding concepts. Then, for the concepts with experimental data, comparisons between simulation and experiment are shown taking into account forward uncertainty quantification (UQ) techniques. For the concepts without publicly available experimental data, parametric studies incorporating forward UQ are completed to verify claims made about the materials’ behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Coupled fuel performance calculations in VERA and demonstration on Watts Bar unit 1, cycle 1

As the core simulator capabilities in the Virtual Environment for Reactor Applications (VERA) have become more mature and stable, increased attention has been focused on coupling Bison to provide fuel performance simulations. This technique has been a very important driver for the pellet-clad interaction challenge problem being addressed by the Consortium for Advanced Simulation of Light Water Reactors (CASL). Here, two coupling approaches are demonstrated on quarter core problems based on Watts Bar Nuclear Plant Unit 1, Cycle 1: (1) an inline approach in which a one-way coupling is used between neutronics/thermal hydraulics (through MPACT/CTF) and fuel performance (through Bison) but no fuel temperature information is passed back to MPACT/CTF, and (2) a two-way approach (coupled) in which the fuel temperature is passed from Bison to MPACT/CTF. In both approaches, power and temperature distributions from MPACT/CTF are used to inform the Bison simulations for each rod in the core.The demonstrations presented here are the first integrated fuel performance simulations in VERA, which opens many possibilities for future work, including applications to accident-tolerant fuel efforts and transient simulations, which are of critical importance to CASL. These demonstrations also highlight the potential to move away from the current Bison-informed fuel temperature lookup table approach, which is the default in MPACT/CTF simulations, if performance improvements are made in the near future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Influence of Superlattice Structure on V-Defect Distribution, External Quantum Efficiency and Electroluminescence for Red InGaN Based µLEDs on Silicon

Achieving high quantum efficiency in long-wavelength LEDs has posed a significant challenge to the solid-state lighting and display industries. In this article, we use V-defect engineering as a technique to achieve higher efficiencies in red InGaN LEDs on (111) Si through lateral injection. We investigate the effects of superlattice structure on the V-defect distribution, the electroluminescence properties, and the external quantum efficiency. Increasing the relative thickness of In in the InGaN/GaN superlattice and the total superlattice thickness correlate with a reduction of active region defects and increased external quantum efficiencies. The highest measured on-chip EQE was 0.15% and based on Monte-Carlo ray tracing simulations for light extraction we project this would correspond to a flip-chip EQE of ~2.5%.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Progress Toward Simulating Departure from Nucleate Boiling at High-Pressure Applications with Selected Wall Boiling Closures

Recently, a Eulerian-based two-fluid computational fluid dynamics (CFD) framework with a wall heat flux partitioning approach has been intensively investigated for departure from nucleate boiling (DNB) simulation under the U.S. Department of Energy–funded Consortium for Advanced Simulation of Light Water Reactors (CASL) program. Understanding of the DNB characteristics over a range of pressurized water reactor–like operating conditions and accurate prediction of boiling crisis in the nuclear power system have been grand challenges because of the large impact of DNB on reactor safety and operational economics. The ultimate goal of this task in the CASL program is to introduce a robust multiphase CFD–based DNB modeling framework that is capable of characterizing an entire boiling history in which the wall boiling mode experiences the following through multiple stages of heat transfer mode: (1) single-phase convective heat transfer, (2) nucleate boiling heat transfer, and (3) identification of the departure of nucleate boiling. To validate the CASL boiling model, we have benchmarked simulated DNB over three different flow channel configurations (pipe flow, 5 × 5 fuel bundle with mixing vane tests, and 5 × 5 fuel bundle without mixing vane tests) against experimental measurements, and the validation result with open literature is reported. The DNB detection criteria in the simulation are checked by monitoring the peak wall temperature, wall dryout factor, and net energy balance. In addition to the DNB performance test, some preliminary sensitivity results on closure model selection are reported to address the prediction capability of local void profile against measurements. The boiling simulation tested in this study exhibits a maximum deviation of 24% from the measured DNB value in a high-pressure (i.e., 138 bars) subcooled pipe flow test. The ranges of operating conditions are as follows: 1650 to 2650 kg/m 2 ·s for mass flux and 8.5 to 96 K for subcooled inlet temperature. The deviation is even reduced to 7% when the subcooled temperature is less than 40 K. Besides accuracy, base practice guidelines for DNB detection criteria are tested by monitoring three simulation variables: (1) maximum wall temperature, (2) wall dryout factor (i.e., K-value), and (3) energy balance. Numerical robustness of DNB simulation is largely achieved in most of the validation test except for a few high subcooled test cases.

42 ENGINEERING↗

DOE OSTI2020

Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States

Abstract With projected expansion of biofuel production at a global scale, there is a pressing need to develop adequate representation of bioenergy crops in land surface models to help effectively quantify the biogeophysical and biogeochemical effects of its associated land use changes. This study implements two new perennial bioenergy crops, Miscanthus and switchgrass, into the Community Land Model Version 5 based on site‐level observations from the midwestern United States by modifying parameters associated with photosynthesis, phenology, allocation, decomposition, and carbon cost of nitrogen uptake and integrating concomitantly land management practices. Sensitivity analyses indicate that carbon and energy fluxes of the perennial crops are most sensitive to photosynthesis and phenology parameters. Validation of simulated fluxes against site‐level measurements demonstrates that the model is capable of capturing the overall patterns of energy and carbon fluxes, as well as physiological transitions from leaf emergence to senescence. Compared to annual crops, perennial crops feature longer growing season, greater leaf areas, and higher productivity, leading to increased transpiration, lower annual runoff, and larger carbon uptake. The model simulations suggest that with higher CO 2 assimilation rates and lower demands for nutrients and water, high‐yielding perennial crops are promising alternatives of bioenergy feedstocks compared to traditional annual crops not only for mitigating climate change but also for environmental conservation purposes by reducing fertilizer application and therefore alleviating surface‐ and ground‐water contaminations. Although the local‐scale simulations shed light on potential benefits of using perennial grasses as bioenergy feedstocks, quantifying consequences of their plantations at larger scales warrants additional investigation.

Cheng, Yanyan↗