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DOE OSTI2021

Turbulent field fluctuations in gyrokinetic and fluid plasmas

A key uncertainty in the design and development of magnetic confinement fusion energy reactors is predicting edge plasma turbulence. An essential step in overcoming this uncertainty is the validation in accuracy of reduced turbulent transport models. Drift-reduced Braginskii two-fluid theory is one such set of reduced equations that has for decades simulated boundary plasmas in experiment, but significant questions exist regarding its predictive ability. To this end, using a novel physics-informed deep learning framework, we demonstrate the first ever direct quantitative comparisons of turbulent field fluctuations between electrostatic two-fluid theory and electromagnetic gyrokinetic modelling with good overall agreement found in magnetized helical plasmas at low normalized pressure. This framework is readily adaptable to experimental and astrophysical environments, and presents a new technique for the numerical validation and discovery of reduced global plasma turbulence models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Monte Carlo Analyses of the FOEHN Experiment

The FOEHN critical experiment, which has been carried out at Cadarache (France) in the reactor EOLE in the early 70s, was designed to verify RHF design analyses. This study focuses on the impact of the FOEHN experiment uncertainties on the calculation of the energy deposition. The latter has been obtained by the Monte Carlo codes Serpent and MCNP. In the calculation of the energy deposition, the first code relies on KERMA factors whereas the latter code relies on Q-values. The two Monte Carlo codes share the same geometry and material specifications. In addition to the design and experiment parameters uncertainties, nuclear data also impacts the calculation of the energy deposition. In this study, the MCNP simulations use three different nuclear data library sets: ENDF/B versions VII.0, VII.1, and VIII.0. Finally, the ksens card of MCNP, using perturbation theory, has been used to identify the cross sections and isotopes with largest impact on the effective multiplication factor. By showing that the use of different software and computational methodologies and design parameters uncertainties do not significantly impact the core power distribution, this work demonstrate the appropriateness of the tools and methods employed for the conversion of involute-plate reactors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

A percolation theory for designing corrosion-resistant alloys

Iron-chromium and nickel-chromium binary alloys containing sufficient quantities of chromium serve as the prototypical corrosion-resistant metals owing to the presence of a nanometre-thick protective passive oxide film. Should this film be compromised by a scratch or abrasive wear, it reforms with little accompanying metal dissolution, a key criterion for good passive behaviour. This is a principal reason that stainless steels and other chromium-containing alloys are used in critical applications ranging from biomedical implants to nuclear reactor components. Unravelling the compositional dependence of this electrochemical behaviour is a long-standing unanswered question in corrosion science. Herein, we develop a percolation theory of alloy passivation based on two-dimensional to three-dimensional crossover effects that accounts for selective dissolution and the quantity of metal dissolved during the initial stage of passive film formation. We validate this theory both experimentally and by kinetic Monte Carlo simulation. Our results reveal a path forward for the design of corrosion-resistant metallic alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2025

BlueCRAB Domain Overlapping Coupling: Theory & Verification

Coupling low- and high-fidelity codes is a useful way to model complex engineering systems. Thanks to the high-fidelity code, complex phenomena can be resolved in areas of the system where this is required, yet the efficiency of the lower-fidelity code is still retained in modeling the rest of the system. This document details the theory and implementation of coupling two different thermal-hydraulic codes: the system thermal-hydraulics (STH) code System Analysis Module (SAM) and the coarse-mesh computational fluid dynamics (CFD) code Pronghorn. Both applications are included in the Comprehensive Reactor Analysis Bundle (BlueCRAB) code suite and are based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. The domain overlapping (DO) coupling approach was adopted, as it offers proven advantages over more conventional domain decomposition methods. In the DO coupling, SAM provides Pronghorn with boundary conditions that depend on the system-level simulation of the entire plant. In return, the overlapping coupled SAM components–termed “surrogate components”–receive friction factors and source terms computed online based on the Pronghorn simulation. The framework is designed to be generic and enable coupling regardless of geometry and the number of inlet/outlet boundaries in the DO coupled domain. The developed method leads to consistent pressure drops, enthalpies, and scalar concentrations when comparing the coupled SAM and Pronghorn simulations. This document presents the DO coupling approach, along with two verification and two demonstration cases. The proposed problems explore different physical aspects relevant to nuclear reactor analysis, including buoyancy-driven flows, complex flow patterns, and multiple inlets and outlets. Periodically, new versions of this “BlueCRAB Domain Overlapping Coupling: Theory & Verification” report will be issued to reflect future developments and verification tests.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Chromium-doped uranium dioxide fuels: A review

UO 2 doped with parts per million CR 2 O 3 powder is considered a potential near term accident tolerant fuel candidate. Here, the results of decades of industry and academic research into Cr-doped UO 2 are analyzed and their shortcomings are critiqued. Focusing on the incorporation mechanisms of Cr into the fuel matrix, we explore a mechanistic understanding of the characteristic properties of Cr-doped UO 2 , notably, enhanced fission gas retention attributed to enlarged grain sizes following sintering, along with marginal improvements in the thermophysical properties. The findings of recent X-ray Adsorption Near Edge Spectroscopy studies were compared and put into conversation with historic data regarding the incorporation of Cr in UO 2 . On the basis of defect mechanisms, the case is made for the substitutional incorporation of Cr governing the lattice solubility but not the enhanced U diffusivity. Instead, Cr/CR 2 O 3 redox chemistry in a well-defined oxygen potential explains the differences in the U diffusivity and O/M ratio. The primary mechanism of doping enhanced grain growth is found to be liquid assisted sintering due to a CRO (1) eutectic phase at the grain boundaries. The role of inhomogeneities in Cr concentration in UO 2 at various length scales across the materials microstructure is highlighted and connected to promising experimental and modeling work to fill in the gaps in the current understanding of Cr-doped UO 2 . The review considers both the open scientific questions and engineering applications to illustrate the deep connections between the practice and theory in the design of accident tolerant nuclear fuels. In conclusion, the review ends with an outline of future works that combine meticulous irradiation studies and high resolution experiments with next generation modeling and simulations techniques empowered by machine learning advances to accelerate the fabrication and adoption of Cr-doped UO 2 light water reactors.

Cleveland, Mack Wesley [Massachusetts Inst. of Tec↗

DOE OSTI2020

Theory Manual for the Fuel Cycle Analysis Code REBUS

REBUS is a system of programs designed for the fuel cycle analysis of fast reactors and accelerator-driven systems. The first version of REBUS was developed in 1970 for calculating the equilibrium operating conditions of liquid metal fast breeder reactors. During the past five decades, various extensions and refinements have been made in the simulation of material motions in fuel cycle facilities and the solution of the neutronics and isotopic transmutation equations that govern the reactor behavior. The latest version complies with the standard code practices and interface dataset specifications of the committee on computer code coordination (CCCC). This report provides a detailed description of the physical processes and their mathematical models and solution methods of the current production version of REBUS. The models of the facilities and physical processes involved in fast reactor fuel cycle are first discussed. Then the mathematical formulation of these physical models is presented, followed by detailed discussions of solution methods of the resulting set of equations. Finally the output edit quantities are discussed along with their definitions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Machine learning assisted prediction of tungsten heavy alloy plasma facing component performance for fusion energy applications

Tungsten and tungsten heavy alloys (WHAs), known for their remarkably high hardness, durability, and corrosion resistance, play a critical role in the thriving development of nuclear fusion reactors in recent years. However, the exploration in tungsten alloys for the nuclear-related applications has been limited by the difficulty of manufacturing and the complexity of experiments to reproduce the environment of nuclear reaction. Therefore, this project aims to utilize nanoscale simulation methods such as density functional theory (DFT) and molecular dynamics (MD) with the help of machine learning techniques to not only understand the mechanisms of tungsten alloys but also allow us to computationally predict their mechanical behaviors under extreme environments. One critical problem of the application of WHAs in nuclear reactors is the surface melting. In the current design of the SPARC reactor, the WHA, W97Ni2.1Fe0.9 or W97NiFe, is chosen to be the first wall components to confine the plasma where the particles are fiercely moving and colliding into each other to create nuclear fusion reaction. This process will generate extremely high heat flux onto these WHA tiles, leaving high surface temperature that could possibly melt the surface of the WHA tiles, As illustrated in Fig. 1(a). a laser experiment previously done illustrates that a rough surface damage would be made after the surface melting where the matrix area mainly composed of nickel and iron as shown in Fig. 1(b), will first melt and then leave vacancies between these tungsten grains. Unfortunately, these kinds of roughness on the first-wall components could be deadly to the plasma inside a Tokmak reactor because the heat that is supposed to dissipate at a designed ratio through the tiles may in turn be excessively absorbed and accumulated on any uneven area of the surface, which will eventually make the whole nuclear reaction fail. In this project, we will introduce a machine learning potential, Allegro, based on DFT calculation and then build a MD model for W-Ni-Fe alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Unraveling the Ion Adsorption Kinetics in Microporous Carbon Electrodes: A Multiscale Quantum-Continuum Simulation and Experimental Approach

With the understanding that sorption in porous carbon electrodes is crucial to many environmental and energy technologies, such as capacitive deionization (CDI), supercapacitor energy storage, and activated carbon filters. In each of these examples, a practical model that can describe ion electrosorption kinetics is highly desirable for accelerating material design. Here, we proposed a multiscale model to study the ion electrosorption kinetics in porous carbon electrodes by combining quantum mechanical simulations with continuum approaches. Our model integrates the Butler-Volmer (BV) equation for sorption kinetics and a continuously stirred tank reactor (CSTR) formulation with atomistic calculations of ion hydration and ion-pore interactions based on density functional theory (DFT). We validated our model experimentally by using ion mixtures in a flow-through electrode CDI device and developed an in-line UV absorption system to provide unprecedented resolution of individual ions in the separation process. We showed that the multiscale model captures unexpected experimental phenomena that cannot be explained by the traditional ion electrosorption theory. The proposed multiscale framework provides a viable approach for modeling separation processes in systems where pore sizes and ion hydration effects strongly influence the sorption kinetics, which can be leveraged to explore possible strategies for improving carbon-based and, more broadly, pore-based technologies

36 MATERIALS SCIENCE↗

DOE OSTI2021

BETO 2021 Peer Review - Biochemical Process Modeling and Simulation (BPMS)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗

DOE OSTI2022

Impact of nuclear data covariance libraries on uncertainty quantification of sodium cooled fast reactor simulation

Uncertainty quantification in core modelling to assess reactor performance is a regular practice to identify design safety limits. Best-estimate plus uncertainty (BEPU) methods are commonly used to propagate uncertainties to core responses from input parameters, characterized by variance-covariance libraries. This study evaluates the impact of different covariance libraries on the uncertainty associated with core safety parameters and their propagation through reactor transient modelling for a metallic core (ABR-1000). The COMAC-1.0, COMMARA-2.0, and COMMARA-2.1 covariance libraries are used to propagate nuclear data uncertainties to neutron feedback coefficients using the Generalized Perturbation Theory, then through transient safety analyses to establish the confidence interval for safety performance of the reactor using stochastic sampling. The considered transients include Unprotected Transient Over Power and Unprotected Loss Of Flow. Most influential nuclide and reaction pairs in different variance-covariance libraries are identified and their impact on the uncertainty of safety parameters are evaluated. Significant differences were observed between uncertainties from COMAC compared to COMMARA libraries. Uncertainties from COMMARA libraries were consistently larger than COMAC for all cases. For structure, coolant density feedback coefficients and control rod worth, total nuclear data uncertainties were approximately 50% larger for COMMARA than COMAC. Differences were also observed in identification of top contributors of uncertainty in terms of reaction-cross sections. For instance, largest contribution to total uncertainty of radial expansion coefficient from COMMARA-2.0 and 2.1 originates from Na{sup 23} P1 Elastic cross section (0.81%) but from Pu{sup 239} Fission (0.53%) with COM C-1.0. Such differences are evaluated in this research for all quantities of interest. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Advanced Modeling and Simulation Methods for Evaluation of Thermal Neutron Scattering Materials

With the rise of interest in thermal neutron scattering data for advanced reactor, criticality safety, and shielding applications, new experimental data are required for evaluation of new materials or for re-evaluation (or validations) of previously evaluated materials. New experimental data are evaluated in a three-step process: (1) computing the phonon characteristics, (2) computing the dynamic structure factor (DSF) from the data, and (3) using the experimental setup to simulate the experimental data. All three steps have challenges, ranging from the need for a sufficiently general material simulation code—a processing code that can compute the corresponding DSF—to having a detailed layout of the instrument/beamline/facility where the data were measured. Whereas phonon characteristics of materials can be computed using various methods (molecular dynamics, density functional theory, etc.), a high-fidelity computation of the DSF and the simulation of the experiment based on the DSF is vital to the accuracy of the evaluation. The latter two steps can be achieved by using the two corresponding code systems developed by instrument scientists at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory: (1) OCLIMAX, a program that calculates the dynamic structure factor from DFT and MD simulation results, and (2) MCViNE, a Monte Carlo neutron ray-tracing program designed to simulate neutron scattering experiments. Recently, polyethylene and yttrium hydride were measured at the Wide Angular-Range Chopper (ARCS) and SEQUOIA instrument stations of the SNS. These experiments are simulated using the density functional theory code, the Cambridge Serial Total Energy Package (CASTEP), to compute its phonon characteristics (eigenvalues/vectors and PDOS), which is then processed using OCLIMAX to yield the DSF, and finally the data at each instrument station are simulated by the MCViNE for comparison to the measured data for evaluation. For comparison to conventional evaluation methods, the scattering data processed from OCLIMAX are compared against those processed from the LEAPR module of NJOY, and the results from MCViNE simulations are compared against previously used simplified beamline models implemented in the Monte Carlo N-Particle (MCNP) code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Disruption avoidance via island suppression: the crucial roles of DIII-D and foundational research

The FESAC long range plan calls out disruption avoidance and mitigation as key remaining technical gaps. In discussing the roles of DIII-D and NSTX-U, the FESAC long range plan says “Additional research on these facilities, in combination with private and international collaborations, continuing support of existing university tokamak programs, and utilization of US expertise in theory and simulation, is needed to find solutions to remaining technical gaps. These gaps include disruption prediction, avoidance, and mitigation …”. Disruptions pose an existential threat to ITER and to FPPs. For a fusion reactor, unplanned shutdowns caused by disruptions will be a significant barrier to connecting such a reactor to the electric grid, even if disruption mitigation is successful. Disruption studies for ITER in recent years have largely focused on disruption mitigation (e.g., pellet injection), motivated by near-term deadlines for finalizing the design of the mitigation hardware. It is recognized, however, that mitigation alone will not suffice. The 2022 U.S. ITER Research Needs Workshop Report states that ”[d]isruptions are considered the largest threat to the ITER Research Program”, and that “[m]itigation should be a last resort”. As we discuss below, there are unresolved foundational issues that play a critical role in avoidance, and DIII-D is an ideal device for generating the data needed to address these issues.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Nanoprecipitates to Enhance Radiation Tolerance in High-Entropy Alloys

The growth of advanced energy technologies for power generation is enabled by the design, development, and integration of structural materials that can withstand extreme environments, such as high temperatures, radiation damage, and corrosion. High-entropy alloys (HEAs) are a class of structural materials in which suitable chemical elements in four or more numbers are mixed to typically produce single-phase concentrated solid solution alloys (CSAs). Many of these alloys exhibit good radiation tolerance like limited void swelling and hardening up to relatively medium radiation doses (tens of displacements per atom (dpa)); however, at higher radiation damage levels (>50 dpa), some HEAs suffer from considerable void swelling limiting their near-term acceptance for advanced nuclear reactor concepts. In this study, we developed a HEA containing a high density of Cu-rich nanoprecipitates distributed in the HEA matrix. The Cu-added HEA, NiCoFeCrCu 0.12 , shows excellent void swelling resistance and negligible radiation-induced hardening upon irradiation up to high radiation doses (i.e., higher than 100 dpa). The void swelling resistance of the alloy is measured to be significantly better than NiCoFeCr CSA and austenitic stainless steels. Density functional theory simulations predict lower vacancy and interstitial formation energies at the coherent interfaces between Cu-rich nanoprecipitates and the HEA matrix. The alloy maintained a high sink strength achieved via nanoprecipitates and the coherent interface with the matrix at a high radiation dose (~50 dpa). From our experiments and simulations, the effective recombination of radiation-produced vacancies and interstitials at the coherent interfaces of the nanoprecipitates is suggested to be the critical mechanism responsible for the radiation tolerance of the alloy. Furthermore, the materials design strategy based on incorporating a high density of interfaces can be applied to high-entropy alloy systems to improve their radiation tolerance.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Selective and Stable Ethanol Synthesis via Electrochemical CO 2 Reduction in a Solid Electrolyte Reactor

Electrochemical CO 2 reduction to ethanol faces challenges such as low selectivity, a product mixture with liquid electrolyte, and poor catalyst/reactor stability. Here, we developed a grain-rich zinc-doped Cu 2 O precatalyst that presented a high ethanol Faradaic efficiency of over 40% under a current density of 350 mA·cm –2 . Our density functional theory (DFT) simulation suggested that Zn atoms inside the structure have a greater carbophilicity than the Cu atoms to help facilitate *CHCHO formation, a key reaction intermediate toward ethanol instead of other C 2 products. Here, a high Faradaic efficiency ratio between ethanol and ethylene (FE EtOH /FE C2H4 ) reached 2.34 in the zinc-doped Cu 2 O precatalyst, representing an over 4-fold improvement compared to bare Cu 2 O precatalyst. By integrating this Cu-based catalyst into a porous solid electrolyte (PSE) reactor with a salt-managing design, we achieved stable ethanol production for over 180 h under a current density of 250 mA·cm –2 while maintaining ethanol selectivity at ~30%.

09 BIOMASS FUELS↗

DOE OSTI2022

Accelerated statistical failure analysis of multifidelity TRISO fuel models

Statistical nuclear fuel failure analysis is critical for the design and development of advanced reactor technologies. Although Monte Carlo Sampling (MCS) is a standard method of statistical failure analysis for fuels, the low failure probabilities of some advanced fuel forms and the correspondingly large number of required model evaluations limit its application to low-fidelity (e.g., 1-D) fuel models. In this paper, we present four other statistical methods for fuel failure analysis in Bison, considering tri-structural isotropic (TRISO)-coated particle fuel as a case study. The statistical methods considered are Latin hypercube sampling (LHS), adaptive importance sampling (AIS), subset simulation (SS), and the Weibull theory. Using these methods, we analyzed both 1-D and 2-D representations of TRISO models to compute failure probabilities and the distributions of fuel properties that result in failures. The results of these methods compare well across all TRISO models considered. Overall, SS and the Weibull theory were deemed the most efficient, and can be applied to both 1-D and 2-D TRISO models to compute failure probabilities. Moreover, since SS also characterizes the distribution of parameters that cause TRISO failures, and can consider failure modes not described by the Weibull criterion, it may be preferred over the other methods. Finally, a discussion on the efficacy of different statistical methods of assessing nuclear fuel safety is provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Status of EM Pump Modeling Capability for VTR

SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. Most recently, SAS4A/SASSYS-1 has been selected as the safety analysis software for the Versatile Test Reactor (VTR), a new materials testing Sodium Fast Reactor (SFR) to be built by the Department of Energy. In order to support analysis of the VTR, which will utilize ElectroMagnetic (EM) pumps as the primary coolant pumps, the development of new EM pump modeling capabilities has been initiated for SAS4/SASSYS-1. The new physics-based EM pump model captures systems-level transient performance based on equivalent circuit theory and is highly flexible to model a wide range of electromagnetic pumps of the three-phase linear induction type subject to changes in power supply and plant conditions. Within the equivalent circuit framework, two sub-models are developed to provide options for analysts both with and without a detailed geometric characterization of their pump such that minimal information is required to achieve a realistic working model, but specific details of a particular pump design may be captured if sufficient information is provided. In addition, heat generated from pump operation and its transport through the plant system can be modeled to better capture the behavior of certain transients. This paper will outline the model and derive the governing equations of the new EM pump model. An initial comparison between the simple EM pump model and experimental data is made. This comparison shows that the equivalent circuit model can capture pump performance, with greater accuracy near the rated conditions. In order to demonstrate the transient behavior of the new model, a simple transient with an EM pump replacing the centrifugal pumps in the Advanced Burner Test Reactor is included.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Status of EM Pump Modeling Capability for VTR

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗