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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Lattice QED in an external magnetic field: Evidence for dynamical chiral symmetry breaking

We simulate quantum electrodynamics (QED) in a strong constant homogeneous external magnetic field on a Euclidean space-time lattice using the rational hybrid Monte Carlo method, developed for simulating lattice quantum chromodynamics (QCD). Our primary goal is to measure the chiral condensate in the limit when the input electron mass m is zero. We observe a nonzero value, indicating that the external magnetic field catalyzes chiral symmetry breaking as predicted by approximate truncated Schwinger-Dyson methods. Such behavior is associated with dominance by the lowest Landau level which causes the effective dimensional reduction from 3 + 1 dimensions to 1 + 1 dimensions for charged particles (electrons and positrons) where the attractive forces of QED can produce chiral symmetry breaking with a dynamical electron mass and associated chiral condensate. Since our lattice simulations use bare (lattice) parameters, while the Schwinger-Dyson analyses work with renormalized quantities, direct numerical comparison will require renormalization of our lattice results. Published by the American Physical Society 2024

Kogut, J. B. (ORCID:000000030151548X)↗
DOE OSTI2022

Investigating Performance of Geothermal Reservoirs With Bi-Directional Heat Transfer for Seasonal Thermal Storage Using Thermal-Hydraulic Reservoir Simulations

This paper presents initial simulation results of deep subsurface seasonal thermal storage of waste heat from a natural gas-fired power plant during the summer months for providing heating during winter months at the Cornell University main campus in Ithaca, New York. An injection temperature profile is calculated with the MEnU tool and numerical reservoir simulations are conducted with the simulator FALCON. Both a porous medium and large single fracture geothermal reservoir are considered at about 3 km depth with initial reservoir temperature of 75 degrees C. Simulations indicate that a much smaller reservoir - which is technically easier and less risky to develop - is sufficient when operating the reservoir for seasonal thermal storage instead of for continuous heat production. For example, storing 13 GWh of heat seasonally in a 100 m thick porous medium based on the Galway formation requires about 65 m of well spacing to limit the yearly variation in production temperature to 10 degrees C. Operating this reservoir for continuous heat production would require a well spacing of 365 m to limit the thermal decline to 10 degrees C after 10 years. Neglecting wellbore heat losses and assuming uniform and homogeneous properties, a round-trip thermal efficiency of 100% can be obtained if the yearly averaged injection temperature matches the initial reservoir temperature.

district heating↗
DOE OSTI2023

Multi-fidelity Uncertainty Quantification for Homogenization Problems in Structure-Property Relationships from Crystal Plasticity Finite Elements

Crystal plasticity finite element method (CPFEM) has been an integrated computational materials engineering (ICME) workhorse to study materials behaviors and structure-property relationships for the last few decades. These relations are mappings from the microstructure space to the materials properties space. Due to the stochastic and random nature of microstructures, there is always some uncertainty associated with materials properties, for example, in homogenized stress-strain curves. For critical applications with strong reliability needs, it is often desirable to quantify the microstructure-induced uncertainty in the context of structure-property relationships. However, this uncertainty quantification (UQ) problem often incurs a large computational cost because many statistically equivalent representative volume elements (SERVEs) are needed. In this article, we apply a multi-level Monte Carlo (MLMC) method to CPFEM to study the uncertainty in stress-strain curves, given an ensemble of SERVEs at multiple mesh resolutions. By using the information at coarse meshes, we show that it is possible to approximate the response at fine meshes with a much reduced computational cost. We focus on problems where the model output is multi-dimensional, which requires us to track multiple quantities of interest (QoIs) at the same time. In conclusion, our numerical results show that MLMC can accelerate UQ tasks around 2.23x, compared to the classical Monte Carlo (MC) method, which is widely known as ensemble average in the CPFEM literature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Probing the Sustainable Reduction of CO 2 , N 2 and NO 3 to Fuels and Chemicals using Non-Traditional Porphyrinoid Catalysts

For the last several decades, numerous strategies have been proposed to be able to interconvert electricity and commodity fuels for transportation and other applications. Even as solar and wind energy become more widely available, these renewable energy sources are not always available where the population is most dense or during peak times of energy demand. One plausible solution to the issue of electricity storage and transport is to use electricity to drive the formation of high-energy compounds and chemical fuels. As a result, the electrochemical conversion of CO 2 into chemical fuels has received major attention as a multi-pronged approach for electricity coversion, storage, and transport. Similar strategies are also attractive for conversion of N 2 and NO x into value added compounds such as ammonia. Metalloporphyrin and metallocorrole complexes are comprised of aromatic tetrapyrrole scaffolds and have been extensively studied as homogeneous catalysts for critical catalytic processes like the electrochemical CO 2 reduction reaction (eCO 2 RR) to generate CO as feedstock for the Fischer–Tropsch process to generate a variety of hydrocarbons as chemical fuels. Despite their significance and impact, efficiently driving such catalytic reduction processes is challenging for multiple reasons. Such processes require multiple-electron transfer events, as opposed to single-electron redox chemistry that forms high-energy singly-reduced intermediates. In addition, these electron transfer events must be coupled to proton-transfer steps and avoid application of high overpotentials where proton (H + ) reduction to generate H 2 (as well as other side-reactions) can lower the selectivity and energy efficiency of the eCO 2 RR process. Certain Fe(III) aromatic tetrapyrroles (e.g., porphyrins and corroles) have been reported to overcome these challenges, but are often difficult to synthesize and modify, and have a tendency to support single-electron redox chemistry at the metal as opposed to multielectron redox involving the ligand and metal in concert. Other families of tetrapyrroles in which all four meso-carbons are reduced (i.e., sp 3 -hybridized) are also known in the literature. These non-aromatic tetrapyrroles are known as porphyrinogens and support multi-electron redox chemistry which has been elaborated by several groups, prompting researchers to consider whether these scaffolds may improve the kinetics and efficiencies of multi-electron steps attendant to activation of thermodynamically stable small-molecule substrates such as CO 2 , N 2 , NO 3 − , and NO 2 − . Although porphyrinogens support multi-electron redox properties, the four sp 3 -hybridized meso-carbons inherent to the tetrapyrrole core completely disrupt π-conjugation between pyrrolic units, which compromises the photochemical properties of porphyrinogens in comparison to that of traditional porphyrinoids. Moreover, the highly reducing nature of porphyrinogens predisposes these platforms to extreme air and water sensitivity. Accordingly, such metalated porphyrinogens are often pyrophoric and/or incompatible with many common organic solvents (CH 2 Cl 2 , CHCl 3 , CH 3 CN, EtOAc, etc.). Hence, reports of efficient small-molecule activation or catalysis supported by porphyrinogens have been limited. To overcome the instability of porphyrinogens while retaining the scaffold’s attractive multi-electron redox properties, we have directed attention to establishing less-well studied groups of non-aromatic tetrapyrroles (i.e., phlorins, biladienes, and isocorroles). These non-traditional tetrapyrroles each contain just a single sp 3 -hybridized meso-carbon, which ablates the platforms aromaticity but still provides an extended π-framework. In addition to developing innovative platforms that may be used to sustainably generate value-added chemicals, fuels, and ammonia via either photo- or electrocatalytic approaches our work also has significantly broadened our understanding of how to prepare and modulate the properties of non-aromatic tetrapyrroles for other applications. Our efforts entailed a synergistic partnership and active collaborations with Drs. David C. Grills and Mehmed Z. Ertem (both of Brookhaven National Lab) to better characterize isocorroles (and related non-aromatic tetrapyrroles) using a variety of advanced spectroscopic and theoretical methods. Our combined efforts have shown that the combination of properties that isocorroles (and related tetrapyrroles) provide results in good chemical stability paired with unique redox and photochemical characteristics that are not typically supported by simple and/or unadorned aromatic tetrapyrroles. Beside redox chemistry, the photochemistry of isocorroles and other non-aromatic tetrapyrroles containing one sp 3 -hybridized meso-carbon is also appealing due to their absorption in the long-visible to near-IR regions, which are essential for photocatalysis and related applications that benefit from direct excitation at these wavelengths. The results reported vastly improve our understanding of non-aromatic tetrapyrrole synthesis, properties and utility for activation of small molecule substrates such as O 2 and CO 2 in the presence of weak cationic organic acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

On hydromagnetic wave interactions in collisionless, high- β plasmas

We describe the interaction of parallel-propagating Alfvén waves with ion-acoustic waves and other Alfvén waves, in magnetized, high- β collisionless plasmas. This is accomplished through a combination of analytical theory and numerical fluid simulations of the Chew–Goldberger–Low (CGL) magnetohydrodynamic (MHD) equations closed by Landau-fluid heat fluxes. An asymptotic ordering is employed to simplify the CGL-MHD equations and derive solutions for the deformation of an Alfvén wave that results from its interaction with the pressure anisotropy generated either by an ion-acoustic wave or another, larger-amplitude Alfvén wave. The difference in time scales of acoustic and Alfvénic fluctuations at high- β means that interactions that are local in wavenumber space yield little modification to either mode within the time it takes the acoustic wave to Landau damp away. Instead, order-unity changes in the amplitude of Alfvénic fluctuations can result after interacting with frequency-matched acoustic waves. Additionally, we show that the propagation speed of an Alfvén-wave packet in an otherwise homogeneous background is a function of its self-generated pressure anisotropy. This allows for the eventual interaction of separate co-propagating Alfvén-wave packets of differing amplitudes. The results of the CGL-MHD simulations agree well with these predictions, suggesting that theoretical models relying on the interaction of these modes should be reconsidered in certain astrophysical environments. Applications of these results to weak Alfvénic turbulence and to the interaction between the compressive and Alfvénic cascades in strong, collisionless turbulence are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Two-dimensional Thomson scattering measurements of misaligned electron density and temperature gradients and associated Biermann battery produced fields

We present optical Thomson scattering measurements of electron density and temperature in high Mach number laser-driven blast waves in homogeneous gases. Taylor–Sedov blast waves are launched in nitrogen (N2) or helium (He) at pressures between 0.4 mTorr and 10 Torr by ablating a solid plastic target with a high energy laser pulse (10 J, 1012 W/cm2). Experiments are performed at high repetition rate (1 Hz), which allows one-dimensional and two-dimensional Thomson scattering measurements over an area of several cm2 by automatically translating the scattering volume between shots. Electron temperature and density in the blast wave fronts were seen to increase with increasing background gas pressure. Measured electron density and temperature gradients were used to calculate ∂B/∂t∝∇Te×∇ne. The experimentally measured ∂B/∂t showed agreement with the magnetic field probe (B-dot) measurements, revealing that magnetic fields are generated in the observed blast waves via the Biermann battery effect. The results are compared to numerical three-dimensional collisional magnetohydrodynamic simulations performed with FLASH, and are discussed in the context of spontaneous magnetic field generation via the Biermann battery effect.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Resolve the Clear-Sky Continuous Diurnal Cycle of High-Resolution ECOSTRESS Evapotranspiration and Land Surface Temperature

Although numerous evapotranspiration (ET) estimates have been developed from remote sensing measurements, a diurnally resolved product with high spatial resolution (<100 m) is still lacking, which is critically needed for agricultural and ecological monitoring. The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides, for the first time, ET at 70 m resolution with diurnal samplings, enabling a step toward filling this data gap. This study developed the first framework to resolve the full diurnal cycle of ET and Land Surface Temperature (LST) from sporadic ECOSTRESS measurements. We first constructed 70 m diurnal LST utilizing a diurnal temperature cycle (DTC) model that fused ECOSTRESS and Geostationary Operational Environmental Satellite (GOES) LST. Next, we derived 70 m diurnal ET from the diurnally resolved LST, along with ancillary meteorological and reflectance data sets, using the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) algorithm. This framework was tested in two regions: A relatively homogeneous semiarid grassland landscape (centered at the US-Seg Ameriflux site) and a heterogeneous humid cropland landscape (centered at US-ARM). Our diurnally resolved LST and ET successfully reproduced the spatial patterns in the native ECOSTRESS measurements during overpasses for both landscapes (LST: r > 0.97, RMSE ~2°C; ET: r > 0.99, and RMSE = 1–7 W m -2 ). The constructed time series also well captured the temporal variability of the in situ measurements (especially under clear-sky conditions) at both US-Seg and US-ARM, albeit performance varying with availability and quality of ECOSTRESS samples. This study sets the stage for testing and applying our framework to broader climates, biomes, and landscapes toward eventually generating diurnally resolved 70 m global operational LST/ET products to enhance ecological/agricultural applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tilted lidar profiling: Development and testing of a novel scanning strategy for inhomogeneous flows

The most common profiling techniques for the atmospheric boundary layer based on a monostatic Doppler wind lidar rely on the assumption of horizontal homogeneity of the flow. This assumption breaks down in the presence of either natural or human-made obstructions that can generate significant flow distortions. The need to deploy ground-based lidars near operating wind turbines for the American WAKE experimeNt (AWAKEN) spurred a search for novel profiling techniques that could avoid the influence of the flow modifications caused by the wind farms. With this goal in mind, two well-established profiling scanning strategies have been retrofitted to scan in a tilted fashion and steer the beams away from the more severely inhomogeneous region of the flow. Results from a field test at the National Renewable Energy Laboratory's 135-m meteorological tower show that the accuracy of the horizontal mean flow reconstruction is insensitive to the tilt of the scan, although higher-order wind statistics are severely deteriorated at extreme tilts mainly due to geometrical error amplification. A numerical study of the AWAKEN domain based on the Weather Research and Forecasting Model and large-eddy simulation are also conducted to test the effectiveness of tilted profiling. It is shown that a threefold reduction of the error on inflow mean wind speed can be achieved for a lidar placed at the base of the turbine using tilted profiling.

17 WIND ENERGY↗
DOE OSTI2024

A Particle Method for the Multispecies Landau Equation

Abstract The multispecies Landau collision operator describes the two-particle, small scattering angle or grazing collisions in a plasma made up of different species of particles such as electrons and ions. Recently, a structure preserving deterministic particle method (Carrillo et al. in J. Comput. Phys. 7:100066, 2020) has been developed for the single species spatially homogeneous Landau equation. This method relies on a regularization of the Landau collision operator so that an approximate solution, which is a linear combination of Dirac delta distributions, is well-defined. Based on a weak form of the regularized Landau equation, the time dependent locations of the Dirac delta functions satisfy a system of ordinary differential equations. In this work, we extend this particle method to the multispecies case, and examine its conservation of mass, momentum, and energy, and decay of entropy properties. We show that the equilibrium distribution of the regularized multispecies Landau equation is a Maxwellian distribution, and state a critical condition on the regularization parameters that guarantees a species independent equilibrium temperature. A convergence study comparing an exact multispecies Bobylev-Krook-Wu (BKW) solution to the particle solution shows approximately 2nd order accuracy. Important physical properties such as conservation, decay of entropy, and equilibrium distribution of the particle method are demonstrated with several numerical examples.

Mathematics↗
DOE OSTI2022

Simulating self-powered neutron detector responses to infer burnup-induced power distribution perturbations in next-generation light water reactors

Understanding how 3D power distribution will be monitored throughout reactor core volumetric space in next-generation nuclear power reactors is crucial to the design, deployment, and licensing of these reactors. Although numerous techniques exist for 3D power distribution monitoring based on the response of both in situ and ex situ sensors currently implemented or proposed for use in the US reactor fleet, crucial details about these techniques are often unclear. The publicly available documentation does not include information such as how well these techniques are characterized and optimized in their implementations and the levels of uncertainty in the inferred 3D power distribution. The work described herein investigated a recently developed 3D power distribution inferencing method as applied to two next-generation reactor simulations: (1) the NuScale small modular reactor design and (2) the Westinghouse AP1000 design, both of which contain in-core strings of vanadium self-powered neutron detectors (SPNDs). This investigation considered a range of SPND string sensor densities, as well as a range of 3D power distribution axial segment sizes. In this work, SPND response simulation is informed by neutron flux calculations in representative homogenized cores. For the different sensor densities and power distribution axial segment sizes in these simulations, the average solution error, solver iterations, and run time were tracked to parameterize the sensor-core configuration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Intrinsic Elastic Anisotropy of Westerly Granite Observed by Ultrasound Measurements, Microstructural Investigations, and Neutron Diffraction

Westerly granite (WG) has been generally accepted as an isotropic homogeneous rock. Here, we return to WG and observe significant elastic anisotropy using multidirectional ultrasonic sounding on spherical samples at pressures up to 400 MPa. Thermal treatment of WG leads to formation of microcracks that reduce elastic wave velocities and increase its elastic anisotropy. The 3D distribution of P-wave velocities at low pressure is close to orthorhombic symmetry. Application of hydrostatic pressure closes most of thermally induced microcracks and decreases elastic anisotropy of WG, but at high pressure the anisotropy is practically reversed compared to low pressure: maximum P-wave velocity direction at low pressures is near minimum velocity direction at high pressure and vice versa. To understand this effect, microstructures of the rock were investigated by optical and scanning electron microscopy. Preferred orientations of four major rock-forming minerals—quartz, orthoclase, plagioclase, and biotite—were measured by time-of-flight neutron diffraction, which confirms significant crystal alignment. All these data were used to numerically model anisotropic elastic properties of WG. It is shown that WG possesses weak intrinsic elastic anisotropy related mainly to the preferred orientation of feldspars formed during igneous crystallization. Observed microcracks are mostly related to the cleavage planes of feldspars and biotite, and thus also demonstrate preferred orientation. Higher preheating temperatures produce larger quantity of longer microcracks. A numerical model shows that these microcracks act against the weak intrinsic elastic anisotropy of WG, and define the elastic anisotropy at low pressures.

58 GEOSCIENCES↗
DOE OSTI2026

Machine learning for seismic low-frequency extrapolation

The cycle-skipping problem that plagues full waveform inversion (FWI) can be at least partially mitigated if low frequencies (which encode the kinematics of wave propagation in seismic data) are recorded. However, seismic sources and receivers are band-limited, so seismic data does not generally include signals down to 0 Hz. To improve our ability to solve the seismic inverse problem, one can synthesize this missing low-frequency (LF) content from the recorded high-frequency (HF) data using machine learning (ML) models. Deep learning models such as convolutional neural networks (CNNs) demonstrate impressive ability to perform low frequency extrapolation. However, such models require powerful hardware (GPU machines) and careful training. We assess the extrapolation capabilities of three different ML models that do not require GPU machines, namely, random forest, Gaussian process regression and gradient boosting, on both synthetic and real data. Experimental results on two synthetic data sets (generated from a low velocity lens embedded in a homogeneous medium, and the Marmousi model) demonstrate that FWI applied to the extrapolated data consistently improves inversion accuracy relative to FWI applied to the original data sets that do not contain low frequencies. Application of low-frequency extrapolation to real data from the Northwest Shelf of Australia demonstrates that tree-based ML models such as gradient boosting can outperform CNNs in terms of both accuracy and computational cost on non-GPU architectures.

58 GEOSCIENCES↗
DOE OSTI2022

Online Learning and Pricing for Service Systems with Reusable Resources

We consider a price-based revenue management problem with finite reusable resources over a finite time horizon T. Customers arrive following a price-dependent Poisson process, and each customer requests one unit of c homogeneous reusable resources. If there is an available unit, the customer gets served within a price-dependent exponentially distributed service time; otherwise, the customer waits in a queue until the next available unit. In this paper, we assume that the firm does not know how the arrival and service rates depend on posted prices, and thus it makes adaptive pricing decisions in each period based only on past observations to maximize the cumulative revenue. Given a discrete price set with cardinality P, we propose two online learning algorithms, termed batch upper confidence bound (BUCB) and batch Thompson sampling (BTS), and prove that the cumulative regret upper bound is O˜(√PT) , which matches the regret lower bound. In establishing the regret, we bound the transient system performance upon price changes via a novel coupling argument, and also generalize bandits to accommodate subexponential rewards. Here, we also extend our approach to models with balking and reneging customers and discuss a continuous price setting. Our numerical experiments demonstrate the efficacy of the proposed BUCB and BTS algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Learning constitutive relations using symmetric positive definite neural networks

In this work, we present a new neural-network architecture, called the Cholesky-factored symmetric positive definite neural network (SPD-NN), for modeling constitutive relations in computational mechanics. Instead of directly predicting the stress of the material, the SPD-NN trains a neural network to predict the Cholesky factor of the tangent stiffness matrix, based on which the stress is calculated in incremental form. As a result of this special structure, SPD-NN weakly imposes convexity on the strain energy function, satisfies the second order work criterion (Hill's criterion) and time consistency for path-dependent materials, and therefore improves numerical stability, especially when the SPD-NN is used in finite element simulations. Depending on the types of available data, we propose two training methods, namely direct training for strain and stress pairs and indirect training for loads and displacement pairs. We demonstrate the effectiveness of SPD-NN on hyperelastic, elasto-plastic, and multiscale fiber-reinforced plate problems from solid mechanics. The generality and robustness of SPD-NN make it a promising tool for a wide range of constitutive modeling applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Implementation of a High-Fidelity Interface Resolving Method in Nek5000

The development and utilization of computational fluid dynamics (CFD) models for large, high-temperature electric melters in the Waste Treatment and Immobilization Plant (WTP) in eastern Washington State have proven to be valuable for various purposes. These models allow for a better understanding of the physio-chemical processes occurring within the melter vessels and can contribute to improving operational efficiency, throughput, and addressing operational issues related to vitrification. The CFD models employed for these melter vessels incorporate multiphase fluid flow and heat transfer simulations in different regions, including the plenum, cold cap, and molten glass regions. As the tank waste and glass formers are introduced into the melter, a reacting batch layer known as the cold cap forms on top of the molten glass. To enhance the melt rate, forced convection bubblers located at the bottom of the melters generate convection currents that help homogenize the molten glass and provide heat to the cold cap. As the bubbles rise through the highly viscous glass, they adopt a spherical-cap shape [1]. Meanwhile, the conversion of the batch to glass generates significant amounts of gases (such as water vapor, carbon dioxide, sulfur dioxide, and NOx) due to thermal decomposition [2]. These gases become trapped between the cold cap and molten glass, forming a foam layer [3]. For modeling multiphase flow in CFD and heat transfer simulations of waste glass melters at different scales, efforts are underway to augment the capabilities of the Nek5000 [4] and NekRS [5] open-source codes [6]. Nek5000/NekRS is a scalable and efficient spectral element code that has been successfully applied to a wide range of fluid dynamics problems. By leveraging the Nek5000/NekRS software, it becomes possible to model the melter systems more affordably and with lower computational requirements compared to currently utilized commercial CFD software. The specific objectives of this ongoing effort include: 1. Implementation of a level set method in Nek5000/NekRS: The level set method is a numerical technique commonly employed in CFD simulations to track and represent the interface between different phases or materials accurately. By incorporating this method into Nek5000/NekRS, the ability to simulate multiphase flows in waste glass melters at a high level of fidelity can be achieved. 2. Demonstration of capability for air bubbling through molten glass: As part of the development process, a specific case of air bubbling through molten glass will be simulated using the augmented Nek5000/NekRS code. This demonstration aims to showcase the ability of the software to accurately capture and analyze the complex phenomena involved in the multiphase flow within waste glass melters. By achieving these objectives, the improved Nek5000/NekRS code will offer a powerful computational tool for simulating and analyzing waste glass melter systems, enabling better understanding, optimization, and troubleshooting of these vitrification processes. The ability to accurately model and simulate multiphase flows has broad relevance across many industries and scientific domains, and the improved functionality can contribute to advancements in various fields beyond waste glass melter simulations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

RELAP-7 Application and Enhancement for FLEX Strategies and ATF Behavior under Extended Loss of AC Power Conditions

This report summarizes the results of a three-year research project sponsored by the U.S. Department of Energy (DOE) Nuclear Energy University Program (NEUP) to enhance and apply the RELAP-7 code by adding and improving several important components (e.g., a mechanistic Reactor Core Isolation Cooling (RCIC) system model) for thermal hydraulic studies of LWRs under ELAP conditions and evaluating the time available for transition to portable FLEX equipment. The project team included University of Massachusetts–Lowell, The Ohio State University, Texas A&M University, Idaho National Laboratory and Oak Ridge National Laboratory. In the Fukushima accident, it was found that the RCIC system played a crucial role in delaying core meltdown by almost three days in Fukushima Daiichi Unit 2, because of self-regulated operation of the steam driven RCIC turbine-pump injection system. Steam flow in the convergent-divergent nozzles of the RCIC Terry turbine is two-phase non-equilibrium transonic flow with homogenous nucleation condensation. To more accurately predict the dynamic process and behavior of the transonic compressible steam flow, a one-dimensional transient two-phase analytical model is presented. A simplified four-fluid model was employed in the present work with the consideration of four separate fluid fields: vapor, liquid film, entrained droplets and condensed droplets. The mass, momentum and energy interactions between the fluids were considered and modeled. An extended seven-equation non-equilibrium critical flow model was developed to obtain the critical pressure and velocities of each phase at the nozzle throat. To predict the wetness in the divergent section, a mechanistic nucleation condensation model was integrated in the nozzle analysis model, considering the generation and consequent growth of droplets. The governing differential equations on a staggered grid were discretized using the second-order Lax-Wendroff scheme with a flux limiter, and the Semi-Implicit Method for Pressure-Linked Equation (SIMPLE) algorithm was employed to solve the discrete linear system. To demonstrate the predictability and reliability of the physical models and the numerical method proposed in the present work, three representative nozzles were modeled and simulated. The results show good agreement with the available experimental data, even for condensation shock. Then, the 1D nozzle model was employed to obtain nozzle flow tables of the Terry turbine nozzle for different working pressures which can cover the operation pressure range of the RCIC system. A mechanistic RCIC turbine-pump system model was developed and implemented in the system code TRACE to simulate dynamic responses of the RCIC system under Beyond Design Basis Accident (BDBA) conditions. The turbine-pump governing equations are based on the control volume approach of the angular momentum balance. The physics based mechanistic RCIC model was developed using the TRACE control system components (i.e., signal variables, control blocks, and tables), and incorporated into a TRACE boiling water reactor (BWR) model. The TRACE model in this report has a detailed nodalization of the reactor pressure vessel (RPV), and all of the major flow paths and system components, including the safety relief valves (SRVs) and the containment suppression pool and drywell. Based on the nozzle flow tables generated from the 1D nozzle model developed, the turbine drive torque can be calculated from table lookup. Since the detailed specifications of the RCIC pump are unavailable, the homologous curves for a Bingham pump were used in the current pump component. A station black-out (SBO) accident test problem was selected to demonstrate the TRACE RCIC model. The short-term SBO simulations were performed for two cladding materials: Zircaloy and FeCrAl, to demonstrate the effect of the accident tolerant fuel cladding on fuel heat-up under BDBA accident conditions. The wetwell plays a vital safety role in SBO and other BWR accident scenarios in that it can reduce containment pressure and supply additional core make-up water. The suppression pool temperature distribution has a very large impact on both RPV and containment pressure. Thus, another novel contribution of the project comes mainly from an improved, systems-level wetwell model which can capture buoyancy-induced thermal stratification effects due to steam injection and condensation. A two-zone stratified wetwell model has been implemented in RELAP-7 and some results from that model are presented. This wetwell model is capable of simulating thermal stratification due to a low steam mass injection rate. With a low mass flow rate, the model assumes that all the steam condenses within the pipe and the resulting plume can be approximated with a purely buoyant, heat-source driven model. The wetwell model developed with these assumptions is adequate to simulate slow transients such as extended SBO transients.

42 ENGINEERING↗
DOE OSTI2024

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have spurred growing interest in using CO 2 electrolysis to produce chemicals and fuels as an alternative to conventional petrochemical processes. High-temperature (>800 °C) solid oxide electrolyzers that convert CO 2 into CO and O 2 have recently become commercially available. Low-temperature electrolysis cells offer the prospect of more convenient and flexible operation, which is critical for utilizing intermittent solar energy, and provide access to more valuable C 2+ products such as ethylene, ethanol, and propanol. Over the past 10 years, research in this area has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices. Leveraging insights from fuel cells and membrane water electrolyzers, researchers have developed electrolysis cells with gas diffusion electrodes (GDE) that have demonstrated high CO 2 electrolysis current densities (>100 mA cm –2 ) as well as promising selectivity and stability. Despite these advances, the energy efficiency (electrical energy-to-product) and carbon efficiency (CO 2 -to-product) of low-temperature CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal source of efficiency losses is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH – ) to form carbonate (CO 3 2– ). Carbonate formation imposes steady-state electrolysis conditions that result in large voltage and CO 2 losses for all known (photo)electrochemical CO 2 cells. While much current research remains focused on CO 2 reduction catalyst design, this largely overlooked CO 3 2– problem presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels. The project pursues an integrated, multi-PI research effort that establishes a fundamental science of CO 3 2– management. PI Kanan and Co-PI Mani’s contribution to the project is to evaluate strategies to mitigate the CO 3 2– problem by changing the properties of the electrolyte and the environment in which CO 2 reduction catalysis takes place. Experimental studies showed that electrolytes composed of a high concentration of both CO 3 2– and HCO 3 – , which serve as moderately alkaline buffers, improved the cell voltage by compared to all-HCO 3 – electrolytes, but these buffered systems still show substantial CO 2 uptake that reduces pH over time. Computational studies developed a homogenized model of a CO 2 reduction catalyst layer that permits a low-cost exploration of the high-dimensional parameter space associated with catalyst layers on gas diffusion electrodes. The model was validated by accurately reproducing experimental data for the related but simpler reaction of CO reduction and then used to probe the effects of catalyst layer architecture on CO 2 reduction. Minimizing the size of catalyst and hydrophobic domains in the catalyst layer is predicted to mitigate CO 3 2– formation and thereby enable prolonged operation at elevated pH. In support of the CO 2 electrolysis studies, a new method for rapidly prototyping electrochemical cells was developed and validated. The method uses a combination of 3D printing and electroless plating to generate conductive cell components for evaluating new cell designs. The carbonate problem encompasses mass transport processes and acid-base reactions that are relevant to many other electrochemical systems. Investigation of strategies to address the carbonate problem led to an additional line of inquiry into the physicochemical phenomena that determine the efficiency of electrochemical acid-base production, which has numerous applications in the broader field of carbon management. New strategies for using the supporting electrolyte to inhibit H + /OH – recombination in electrochemical acid-base production were evaluated, leading to the development of a novel acid-base producing system that eliminates the need for ion exchange membranes and exhibits promising efficiency and current densities for scalable applications.

25 ENERGY STORAGE↗