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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗
DOE OSTI2025

Assessment of RELAP5-3D Code with Molten Salt Heat Transfer Experiments

The accurate thermal-hydraulic assessment of thermal storage systems is crucial for addressing the integrity and performance of the storage system design. This is particularly important for thermal storage systems using molten salts as a heat transport and storage medium, as the chemical corrosion and erosion by the high-temperature molten salts can cause serious damage to the structural components of the storage system. To understand these effects for TerraPower’s Natrium® Demonstration Reactor design, the system thermal-hydraulic analysis code, RELAP5-3D, is utilized to analyze the thermal storage system. This study evaluates two heat transfer correlations implemented in the RELAP5-3D code—the Dittus-Boelter and Gnielinski correlations—using selected benchmark cases from two molten salt heat transfer experiments conducted at Xi’an Jiao Tong University and the German Aerospace Center. The Nusselt numbers calculated using the Gnielinski correlation agree with the experimental data within ±5% of the relative deviations at 300°C and 400°C. With the increasing Reynolds numbers, the Dittus-Boelter correlation underestimates the Nusselt numbers by up to 22% compared to the Gnielinski correlation. Comparison of the RELAP5-3D calculation results with experimental data at a high temperature of 550°C revealed that the thermo-chemical characteristics of solar salt at high temperatures surpassing the decomposition temperatures of nitrate salts reduce the accuracy of heat transfer model of the RELAP5-3D code. Specifically, it has been observed that the temperatures of the wall surface and liquid near the wall can surpass the decomposition temperatures, even though the bulk temperature of molten salts remains significantly lower than these decomposition temperatures. In summary, this study recommends the use of the Gnielinski correlation for the heat transfer analysis of molten salt, rather than the Dittus-Boelter correlation.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Triaxiality and shape dynamics in 70 Ge

The electromagnetic properties of low-lying states in 70 Ge were investigated via multi-step Coulomb excitation of a 70 Ge beam impinging on a 208 Pb target at the ATLAS facility of the Argonne National Laboratory. A total of 27 transitional elements and six diagonal matrix elements coupling 11 low-lying states, were extracted from the measured cross sections. These were used to calculate reduced transition probabilities, spectroscopic quadrupole moments, and rotational invariant shape parameters, providing enhanced precision and expanding on previous studies. The experimental data were compared within several theoretical frameworks, including the generalized triaxial rotor model, configuration interaction shell-model calculations, and computations within the combined frameworks of relativistic density functional theory and the five-dimensional collective Hamiltonian. The results demonstrate a good agreement with the experimental data and, in conjunction with calculations using a two-state mixing model, support significant triaxiality and strong mixing between the 0$^{+}_{1}$ and 0$^{+}_{2}$ states. This results in the magnitudes of their respective quadrupole deformations [β rms (0$^{+}_{1}$) = 0.228 (3), β rms (0$^{+}_{2}$) = 0.273 (1)] being more similar than previously observed. Furthermore, the implications of these results for understanding the complex shape coexistence phenomena, the role of triaxiality, and shape evolution along the Ge isotopic chain are discussed.

59 ≤ A ≤ 89↗
DOE OSTI2023

High-Fidelity Numerical Investigation on Elucidating Sodium Heat Transfer Characteristics for 37-Pin Wire-Wrapped Fuel Bundle in the PLANDTL Facility

This study involved a Reynolds-averaged Navier-Stokes- (RANS-) based computational fluid dynamics (CFD) analysis of the 37-pin wire-wrapped fuel bundle of the PNC Plant dynamics test loop (PLANDTL) facility. Previously, mainly the hydrodynamic phenomena of the wire-wrapped fuel bundle were analyzed, but the present study additionally included heat transfer analysis through conjugate heat transfer. The main purpose of the study was to benchmark the experimental data of the PLANDTL 37-pin wire-wrapped fuel bundle to investigate the heat transfer phenomena. In addition, the aim was to verify the accuracy of the RANS-based CFD analysis method using the STAR-CCM+ simulation software in comparison with the experimental data. The grid used for verification was an innovative grid system consisting of hexahedra using Fortran-based code. The development of the RANS-based CFD methodology included grid sensitivity analysis, turbulence model sensitivity analysis, and turbulent Prandtl number sensitivity analysis. Information on the temperature, mass flow rate, and area of the CFD results for each subchannel was provided for the top of the heated section and is expected to serve as a reference for future studies aiming to perform the validation and verification of a PLANDTL facility. In addition, the dependence of the peak temperature on the azimuth angle of each pin was analyzed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Demonstration of Pronghorn’s Subchannel Code Modeling of Liquid-Metal Reactors and Validation in Normal Operation Conditions and Blockage Scenarios

Pronghorn-SC is a subchannel code within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Initially designed to simulate flows in water-cooled, square lattice, subchannel assemblies, Pronghorn-SC has been expanded to simulate liquid-metal-cooled flows in triangular lattices, hexagonal subchannel assemblies. For this purpose, the algorithm of Pronghorn-SC was adapted to solve the subchannel equations as they are applicable to a hexagonal wire-wrapped sodium-cooled fast reactor. Cheng–Todreas models for pressure drop and cross-flow models were adopted and a coolant heat conduction term was added. To solve these equations, an improved implicit algorithm was developed robust enough to deal with the numerical issues, associated with low flow and recirculation phenomena. To confirm the prediction capability of Pronghorn-SC, calculations and comparisons with available experimental data of 19- and 37-pin assemblies were performed, as well as other subchannel codes. Finally, a flow blockage modeling feature was added. This capability was validated for both water-cooled square sub-assemblies and sodium-cooled hexagonal sub-assemblies, using experimental data of partially and fully blocked cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Predicting oxidation damage in ultra high-temperature borides: A machine learning approach

Ultra-high temperature (UHT) borides are ceramics materials with melting points above 3000 °C for structural applications in extreme environments. However, at temperatures exceeding 1600 °C and under oxidizing conditions, the material suffers from detrimental degradation. Optimized design and performance of diboride materials under such extreme conditions requires filling the missing composition-microstructure-oxidation gap. This study proposes a computational data-driven framework to connect the processing and microstructure of Ultra-high temperature borides with the oxidation damage. Random Forest Regressor (RFR) model is adopted to forecast the oxide scale thickness developed after oxidation testing based on processing variables and microstructural features. The model trained on a dataset consisting of 107 samples of experimental data extracted from the literature aims to predict oxidation damage. With proper data manipulation and fine model tuning, the predictor could forecast the oxide scale thickness of UHT diborides with a Mean Absolute Error of 37.45 μm and an R-square of 0.83. This model could be used as a high-throughput scheme to design and test new UHT diborides materials computationally. Furthermore, a model with larger composition capabilities could also be developed in the future as more experimental data become available.

36 MATERIALS SCIENCE↗
DOE OSTI2025

MOSCATO Development and Integration in Fiscal Year 2025: Implementation of Multiphase, Multiphysics Modeling Capabilities for Molten Salt Systems

MOSCATO (Molten Salt Chemistry and Transport) is a multiphysics code that provides high-fidelity, coupled simulations of fluid flow, heat transfer, mass transfer, chemistry, electrochemical phenomena, and alloy corrosion for molten salt systems. In FY25, significant developments were made to the code package, enhancing its capabilities for modeling all relevant phenomena within operating moltens salt reactors (MSRs). The developments and activities in FY25 included: 1. Implementation of Level-Set methods to enable modeling of single-bubble behavior in molten salts. In FY25, the Level-Set two-phase flow modeling implementation was improved to simulate single bubble behavior with molten salt media. The large density and viscosity ratios between typical gases and molten salt liquids present challenges for these types of numerical solvers. With enhancements to the pressure projection method, MOSCATO’s Level-Set solver was able to be successfully validated to experiments related to helium bubble rise in stagnant molten salt. The simulated bubble rising velocity showed reasonable good agreement with experimental measurements. The bubble shape and dynamics were also visually compared with experimental snapshots, demonstrating a good qualitative match. 2. Generation of mass transfer correlations for multiphase flow systems. To enable calculations of the tritium transport across the interface between gas bubbles and salt, we modeled high- Schmidt-number mass transfer around a sphere across a broad range of Reynolds numbers. The mesh near the sphere surface was highly refined to resolve steep concentration gradients caused by the low diffusion coefficient. Literature-based mass transfer correlations were compared with the numerical results, and modifications were proposed to improve agreement, particularly at higher Schmidt numbers. These mass transfer correlations were subsequently provided to other national laboratories to help enable high quality mass transfer simulations using lower-order solvers under development within the NEAMS program. 3. Preliminary implementation of a bubbly flow solver. To model bubbly flow in molten salt, we implemented a bubbly flow solver for void fractions less than 5%. To do so, an algebraic relative velocity model that assumes small bubbles with rapid momentum equilibration was added to MOSCATO to compute bubble velocities. Preliminary comparisons with experimental data showed reasonable agreement, and further improvements are underway. 4. Generation of mass transfer correlations for MSRE subchannel The Molten-Salt Reactor Experiment (MSRE) was a landmark historical project that demonstrated the feasibility of molten-salt reactor technology. The MSRE campaign also generated a significant body of experimental data and reports that continue to support molten-salt–related research. In this report, the MSRE core subchannel was used as the reference geometry for a mass transfer study performed with MOSCATO. The geometry and computational mesh were adapted from a previous study, providing adequate resolution for the relatively low Reynolds number in this case. Additional mesh refinement was applied to reach higher Schmidt numbers, enabling the derivation of a reliable mass-transfer correlation for the present scenario. 5. Simulations of oxygen ingressions into molten salt. In the previous fiscal year, we initiated a study to simulate oxygen ingression in stagnant salt. As oxygen enters the salt through its surface, it reacts with Ce 3+ to form solid CeO 2 and other reaction products. To more fully capture the complex diffusion-convection-reaction mechanisms, capabilities for modeling natural convection in the salt vessel were added. These were needed as the flow of the ingressed gas induced flow in the salt caused by surface shear and non-isothermal effects. With these updated physics in place, we were able to successfully reproduce the experimental results for the rate of change of CeCl 3 concentrations versus time. 6. Flow corrosion model validation. In FY24, MOSCATO’s corrosion model was validated against static corrosion experiments. In FY25, this work was extended to a flow corrosion experiment, where FLiNaK salt was driven by natural convection, with initial salt impurities to initiate corrosion. Despite uncertainties in parameters such as elemental diffusion coefficients in the alloy and unknown H + concentrations, the simulations achieved good agreement with experimental results, especially in predicting sample mass losses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Computational and experimental study of different brines in temperature swing solvent extraction desalination with amine solvents

Rapid global urbanization and high-salinity wastewater disposal from industrial activities have exerted significant pressure on water resources. Over the past few years, temperature swing solvent extraction (TSSE) has been identified as a promising technique to desalinate hypersaline brines. Despite its potential, the TSSE desalination literature has been mainly based on empirical insights, and the limited molecular simulation studies have primarily focused on NaCl brines. Herein, we use molecular dynamics (MD) simulations to study the TSSE desalination of four different brines, namely, KCl, KBr, NaCl, and NaBr using diisopropylamine as the solvent. Based on both bulk and interfacial brine-diisopropylamine MD results, here we investigate the qualitative and quantitative performance of the simulations by benchmarking these results against our experimental evaluations of these same systems. MD results provide satisfactory qualitative agreement with the experimental data of water solubilization in the organic phase and amine solubilization in the aqueous phase for the KBr, KCl, and NaBr brines. Also, the molecular mechanism of solvation of ionic species by water molecules over diisopropylamine suggested by the MD simulations is in agreement with our experimental data. However, larger qualitative and quantitative deviations were observed for the NaCl brines, and this is likely due to polarization and charge transfer effects, as quantified by our quantum chemical calculations.

42 ENGINEERING↗
DOE OSTI2022

Semi-empirical simulation of in-motion radiation detection systems

The Replicative Assessment of Spectroscopic Equipment (RASE) is an open-source software that uses experimental data as the basis to simulate the response of commercial radiation detectors to sources in various situations, particularly in the context of nuclear security and safeguards applications. Dynamic RASE introduces the capability to simulate scenarios where sources and detector are in relative motion. Position-dependent experimentally acquired gamma spectra are ingested by Dynamic RASE to build maps that describe the detector response over all space. These response maps are used to replicate the time-dependent energy spectra collected as sources move on a path near the detector. Here, a Gaussian process is used to build each map, incorporating a novel kernel adapted to the special case of radiation detection. The approach has been validated against experimental data acquired using a NaI-based detector for 137 Cs and 54 Mn sources. The capability to create accurate simulations using either long-dwell static measurements or dynamic pass-by measurements as source data has been demonstrated. Quantitative relative performance, benefits, and shortcomings are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Generation, dynamics, and correlations of the fission fragments' angular momenta

The generation of angular momentum in fissioning nuclei is not well understood. The predictions of different models disagree, particularly concerning the correlation between the fragments' angular momenta. In this article, a time-dependent collective Hamiltonian model is proposed to treat the generation of the angular momentum in the fission fragments due to the quantum uncertainty principle as well as the dynamics of the collective wave function during and after scission. The model is constructed in the framework of the frozen Hartree-Fock approximation using a Skyrme energy functional to extract deformations of the fission fragments as well as the interactions in a derived collective Hamiltonian. The fission reactions studied are $^{240}$Pu $\rightarrow$ $^{132}$Sn+$^{108}$Ru and $^{240}$Pu $\rightarrow$ $^{144}$Ba+$^{96}$Sr. The model can account for a large part of the angular momentum found in experimental data. The orientation of the angular momentum of each fragment is found to be mainly in the plane perpendicular to the fission axis, in agreement with the experiment. The magnitudes of the angular momenta in the two fragments are nearly uncorrelated, in agreement with the recent experimental data of Wilson et al., Nature (London) 590, 566 (2021). Some of the conclusions of the traditional collective vibration model are supported by the present model but some are not. Surprisingly, it is found that the angular momenta of the fragments are slightly correlated positively as in a wriggling mode. As a result, it is also found that the presence of an octupole deformation in a fragment can significantly increase the generated angular momentum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

The Viscosity and Atomic Structure of Volatile-Bearing Melilititic Melts at High Pressure and Temperature and the Transport of Deep Carbon

Understanding the viscosity of mantle-derived magmas is needed to model their migration mechanisms and ascent rate from the source rock to the surface. High pressure–temperature experimental data are now available on the viscosity of synthetic melts, pure carbonatitic to carbonate–silicate compositions, anhydrous basalts, dacites and rhyolites. However, the viscosity of volatile-bearing melilititic melts, among the most plausible carriers of deep carbon, has not been investigated. In this study, we experimentally determined the viscosity of synthetic liquids with ~31 and ~39 wt% SiO 2 , 1.60 and 1.42 wt% CO 2 and 5.7 and 1 wt% H 2 O, respectively, at pressures from 1 to 4.7 GPa and temperatures between 1265 and 1755 °C, using the falling-sphere technique combined with in situ X-ray radiography. Our results show viscosities between 0.1044 and 2.1221 Pa·s, with a clear dependence on temperature and SiO 2 content. The atomic structure of both melt compositions was also determined at high pressure and temperature, using in situ multi-angle energy-dispersive X-ray diffraction supported by ex situ microFTIR and microRaman spectroscopic measurements. Our results yield evidence that the T–T and T–O (T = Si,Al) interatomic distances of ultrabasic melts are higher than those for basaltic melts known from similar recent studies. Based on our experimental data, melilititic melts are expected to migrate at a rate ~from 2 to 57 km·yr -1 in the present-day or the Archaean mantle, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neutrinoless Double-Beta Decay Investigations of 82Se Using Three Shell Model Hamiltonians

Neutrinoless double-beta decay is considered one of the most promising processes that would help clarify some of the symmetry-breaking problems in our understanding of the observable universe. Recent studies of neutrinoless double-beta decay matrix elements have employed statistical approaches based on modified shell model effective Hamiltonians for 48Ca (Phys. Rev. C 106, 054302 (2022)) and 136Xe (Phys. Rev. C 107, 045501 (2023)). The analyses rely on inducing perturbations in the starting effective Hamiltonians to observe the behavior of a wide range of observables, besides the 0νββ) NME, that are compared with experimental data. Following a Bayesian model averaging approach, the range of probable values for the neutrinoless double-beta decay matrix elements is presented. In this paper, we present a similar study for 82Se, which is described in the same model space as 76Ge that is under experimental observation. Due to its faster calculation time compared to 76Ge, 82Se can be used as an appropriate substitute in our complex statistical study. Using the calculations performed for the statistical analysis of the neutrinoless double-beta decay matrix elements, we also search for the correlations between the observables that we can compare to experimental data.

Science & Technology - Other Topics↗
DOE OSTI2020

Investigation of Mixing Law Efficacy for Gaseous Hydrodynamic Simulations

A computational simulation of various mixing laws for gaseous equations of state using planar traveling shocks for multiple mixtures in three dimensions is analyzed against nominal experimental data. Numerical simulations utilize the Sandia National Laboratories shock hydrodynamic code CTH and other codes including the thermochemical equilibrium code TIGER and the uncertainty qualification and sensitivity analysis code DAKOTA. The mixtures are a 1:1 and a 1:3 molar mixture of helium and sulfur hexafluoride. The mixing laws to be analyzed are the ideal gas law, Amagat's Law, Dalton's Law, the BKW EOS, the EXP6 EOS, and the JCZ3 EOS. Examination of the experimental data with TIGER revealed that the shock strength should not be strong enough to turn the mixture non-ideal as the compressibility factor z was essentially unity (z ≈ 1.02). Experimental results show that none of the equations of state are able to accurately predict the properties of the shocked mixture; similar discrepancies have been observed in previous works. Kinetic molecular theory appears to introduce a parameter which offers an explanation regarding the discrepancies. Implementation of the KMT pararneter into the EOS is left for future work.

42 ENGINEERING↗
DOE OSTI2023

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗
DOE OSTI2025

Modeling Pb(II) Adsorption on Mineral Surfaces: Bridging Density Functional Theory and Experiment with Thermodynamic Insights

Despite decades of work on aqueous lead (Pb) adsorption on a-Fe2O3 (hematite) and a-Al2O3 (alumina), gaps between measurements and modeling obscure molecular-level understanding. Achieving well-matched geometries between theory and experimental for mineral-water interfaces is a hurdle, as surface functional group type and distribution must be accounted for in determining mechanisms. Additionally, computational methods that can describe the substrate are often not appropriate to capture aqueous effects. Progress requires focusing on well-studied and relevant systems, such as key facets (001),(012), and (110) of hematite and alumina, and ubiquitous contaminants such as aqueous Pb. In the past, bulk-parametrized bond-valence principles were used to rationalize Pb(II) adsorption trends. These approaches can break down at surfaces, where flexible bonding environments and adsorption-induced surface relaxations play a critical role. Here, we adapt and apply a density functional theory (DFT) and thermodynamics framework, integrating DFT-calculated energies with experimental data and electrochemical principles, to predict Pb(II) adsorption. Our model results capture trends across the full set of surfaces and predict that inner-sphere Pb(II) sorption on (001) alumina varies from unfavorable to weakly favorable across a range of pH conditions. This aligns with experiment insights that Pb(II) interacts at that surface through outer-sphere interactions. Extending to Fe(II) adsorption, we demonstrate a coverage-dependent site preference, potentially explaining disorder in overlayers grown by the oxidative adsorption of Fe(II) on hematite (001).

lead contamination↗
DOE OSTI2022

Development of a high fidelity model of the CROCUS experimental reactor

Measurements of scalar flux distributions with fine spatial and energy resolutions are needed to remedy one of the validation shortcomings of the novel neutronics full core solvers, such as MPACT and nTRACER. While a very detailed resolution of the flux can be calculated with such codes, only a limited experimental data set is available to check their accuracy. Such type of measurements are on-going at the zero power reactor CROCUS, operated at the Laboratory for Reactor Physics and System Behaviours of the EPFL, thanks to the development of advanced miniature neutron detection systems. This kind of experimental data would provide the community with a suitable benchmark for the validation of high fidelity neutronics solvers. In parallel, a multi-physics solver for steady-state and transient analysis of nuclear reactors, named GeN-Foam, has been developed. Based on the finite-volume OpenFOAM library, GeN-Foam provides us with enough flexibility to analyze non-conventional reactor geometries such as that of CROCUS. While CROCUS heterogeneities cannot be modeled by MPACT and nTRACER for the moment, GeN-Foam offers a unique opportunity to build a high fidelity model which mimics these codes' method to reach sub-pin simulation resolution. This document aims at describing the work achieved to get from the existing GeN-Foam model of the CROCUS reactor based on a structured mesh and using the neutron diffusion, the first high-fidelity model using discrete ordinates method as an approximation to neutron transport and an unstructured mesh for inter lattice water gap description and sub-pin heterogeneous modeling. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Dynamics of deuterium retention and desorption from plasma-facing materials in fusion reactor-relevant conditions

Hydrogen isotopes retention and desorption during and after discharges in fusion devices are still not well understood due to the complex device conditions and limitations of in-situ diagnostics and measurements. Here, we simulated well-diagnosed recent experiments at the DIII-D facility to benchmark our ITMC-DYN integrated package of modeling deuterium diffusion, retention, and desorption during and after D discharge irradiation. Modeling results were compared with detail experimental data of D desorption fluxes for various irradiation conditions. We predicted the temporal evolution of free and trapped D distribution in tungsten (W) plasma-facing material (PFM). Effects of key parameters namely diffusion coefficient, recombination rate, trapping energies against different defect types, were examined in these simulations. Existing experimental data of these parameters in literature varies significantly which makes it harder to identify key mechanisms and physics responsible for hydrogen isotope retention and desorption. The purpose of this work is to accurately simulate recent well-diagnosed reactor experiments given the uncertainties in such parameters and identify mechanisms responsible for the retention and desorption. We implemented the best identified diffusion, recombination, and trapping parameters in ITMC-DYN package that integrate both various collisional and thermal processes. We predicted, for example, that sample cooling between discharges in DIII-D operations can significantly affect the spatial distribution of trapped D in W under reactor irradiation conditions. Correct prediction of desorption spectra from samples irradiated during 10 DIII-D discharges showed that up to 35% of D can be retained in high binding energy defects such as vacancy clusters or voids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Tailoring critical Al concentration to form external Al 2 O 3 scale on Ni–Al alloys by computational approach

Abstract Nickel (Ni)‐based superalloys for high‐temperature applications are often designed to form a continuous and slow‐growing oxide scale by adding Al and Cr and other beneficial elements. In the present work, the critical Al concentration in Ni–Al alloys needed to establish an α‐Al 2 O 3 scale in contrast to internal oxide formation is predicted as a function of temperature by means of the CALPHAD approach coupled with models in the literature, which account for the thermodynamics and kinetics of oxidation. The present thermodynamic remodeling of the Ni–O system results in a better agreement with experimental data of oxygen solubility in Ni at high temperatures. The oxygen solubility is combined with kinetic parameters to determine oxygen permeability in Ni, and the critical Al concentration needed to establish an α‐Al 2 O 3 scale at a given exposure temperature. Good agreement is found with available experimental data for both oxygen permeability and critical Al concentration, indicating the capacity of the CALPHAD approach to tailor oxidation resistance for materials of interest using thermodynamic and kinetic knowledge.

Ross, Austin↗