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At least 181 records · Page 10

Effects of inter-pulse coupling on nanosecond pulsed high frequency discharge ignition in a flowing mixture

This work numerically investigates the effects of non-equilibrium nanosecond plasma discharge pulse rep- etition frequency, pulse number, and flow velocity on the critical ignition volume, minimum ignition energy, and chemistry in a plasma-assisted H 2 /air flow at 300 K and 1 atm using a multi-scale adaptive reduced chemistry solver for plasma assisted combustion (MARCS-PAC). The interactions between discharges/ignition kernels spanning decoupled, partially-coupled and fully-coupled regimes in a pulse train are studied. For a single pulse discharge, increased flow velocity increases the minimum ignition energy required due to the increase of convective heat loss and flame stretch. The results show that the minimum ignition kernel prop- agation speed at the critical ignition kernel volume increases with the flow velocity. The minimum critical ignition volume decreases with the increase of plasma discharge energy. For sequential two-pulse discharges, ignition fails at both decoupled and partially-coupled regimes even when the total discharge energy is above the minimum ignition energy, but succeeds only in the fully-coupled regime at a shorter inter-pulse time. Overlap of the OH radical pool between the sequential two-pulse discharges and the increase of the chemistry effect due to the increase of reduced electric field in the fully-coupled regime contribute to the ignition enhancement. In addition, for two-pulse discharges in the fully-coupled discharge regime, the mixture can be ignited at a total energy below the minimum ignition energy of a single pulse with the same flow conditions. Moreover, for a given total discharge energy with multiple pulsed discharges, the enhancement of the ignition kernel volume has a non-monotonic dependence on discharge frequency and pulse number. The effective ignition enhancement can be achieved with an optimal pulse repetition frequency and pulse number. Furthermore, this work provides a new understanding of the mechanism for repetitive plasma ignition and insights for the optimization of plasma ignition in a reactive flow.

42 ENGINEERING↗

Boiling-Water Reactor Testing Capability in the Advanced Test Reactor

I-Loop is an irradiation facility that is currently being installed at the Advanced Test Reactor. It is a two-loop test facility capable of performing Light Water Reactor (LWR) irradiations in prototypic coolant conditions. The two loops are being installed to be capable of both Boiling Water Reactor (BWR) and Pressurized Water Reactor (PWR) pressure, temperature, and chemistry environments. Each loop is nominally dedicated as a BWR or PWR for simplicity of operations. In-reactor water loop testing that an I-Loop provides is key to the deployment of new accident tolerant fuel technologies and other advanced LWR fuel concepts. Currently, pressurized water loops are the only testing facilities available to test BWR fuel concepts. Their test environments are non-prototypic at higher pressure/temperature and at single-phase fluid flow conditions. This void in the LWR test bed capabilities is one that the I-Loop is uniquely situated to provide. This report discusses the mechanical design, thermal hydraulic calculations, and neutronic calculations of a proposed standard experiment of accident tolerant BWR fuel concepts. Mechanical design examines the geometry and features of the main components. Thermal hydraulic calculations examine the modeling and results of the two-phase flow options available. Lastly, neutronic calculations examine the Monte Carlo analysis of enrichment, heat rates, and flux spectrum.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Overlapping Domain Coupling of Multidimensional and System Codes in NEAMS - Pronghorn and SAM

This report describes the implementation and testing of domain-overlapping coupling of the Pronghorn and SAM codes. Both Pronghorn and SAM are codes developed by the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program for analysis of advanced nuclear reactors. Pronghorn focuses on analyzing multi-dimensional core flow conditions, while SAM focuses on analysis of the entire system including, among other components, piping, pumps, and heat exchangers. It is desirable for many advanced reactor thermal-hydraulics simulations to couple Pronghorn and SAM to obtain self-consistent solutions in the core and the system. The domain-overlapping coupling approach provides a robust and numerically efficient candidate for this coupling. We describe the algorithm for obtaining self-consistent solutions between a SAM network of flow channels and an overlapped multi-dimensional Pronghorn domain. The algorithm is tested for a variety of simple canonical test problems and a model of the Molten Salt Reactor Experiment (MSRE). Results demonstrate that the domain overlapping coupling approach provides consistent pressure, mass flow rate, enthalpy, and passive scalar distributions between Pronghorn and SAM and converges reliably and efficiently (at most 15 iterations, usually much less than 10) for the considered test problems.

97 MATHEMATICS AND COMPUTING↗

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗

The Effect of Flow on CO2 Corrosion of Self-Healing Metallic Coatings

Internal corrosion is an issue that affects natural gas pipelines, a significant part of the United States’ energy infrastructure. Over time, this corrosion has worn away longstanding pipelines due to the original construction materials used for the lines and impurities in the gas and liquid streams flowing through them. The main impurities in natural gas are H2O, CO2, H2S, and O2. One of the leading causes of corrosion is the CO2 dissolved in water, giving rise to carbonic acid formation, which can further dissolve the steel pipe. The National Energy Technology Laboratory (NETL) has been studying different solutions to this problem. One potential answer is a self-healing sacrificial metallic coating applied by a novel cold spray technique. This study explored the impact of flow on corrosion with this coating and carbon steel when exposed to a saturated CO2 environment by simulating the pipeline flow profile in a small-scale lab setting. The samples were evaluated using multiple electrochemical techniques that found corrosion rates and were backed up with surface analysis to conclude the behavior of the corrosion mechanisms. The cold spray coating exhibited steel corrosion protection under flow conditions. This study has significantly advanced our understanding of CO2 corrosion, particularly in the context of natural gas pipelines and coating design.

carbon steel↗

River–aquifer interactions enhancing evapotranspiration in a semiarid riparian zone: A modelling study

The hydrologic flows across the river–aquifer interface play an important role in groundwater dynamics and biogeochemical reactions within the subsurface; however, little is known about the effects of river–aquifer interactions on land surface processes. In this study, we developed a fully coupled three-dimensional (3D) land surface and subsurface model at a high resolution (~1 km) that accounts for high-frequency hydrologic exchange flow conditions to investigate how river–aquifer interactions modulate surface water budgets in the Upper Columbia-Priest Rapids watershed, a typical semiarid watershed located in the northwestern United States where river stage fluctuates in response to reservoir releases changing. Our results show that the spatiotemporal dynamics of river–aquifer interactions are highly heterogeneous, driven mainly by river-stage fluctuations. Adding 6.64 × 10 6 m 3 year –1 of water over the watershed from the river to groundwater owing to the lateral flow, river–aquifer interactions led to an increase in soil evaporation and transpiration supplied by higher soil moisture content, particularly in deeper subsurface. In a hypothetic future scenarios where a 5-m rise in river stage was assumed, the hydrologic flow exchange rates were intensified, resulting in higher surface water over the entire watershed. Overall, lateral flow induced by river–aquifer exchanges leads to an increase in evapotranspiration of ~75% in the historical period and of ~83% in the hypothetical future scenario. Finally, our study demonstrates the potential of coupled model as an effective tool for understanding river–aquifer–land surface interactions, and indicates that river–aquifer interactions fundamentally alter the water balance of the riparian zone for the semiarid watershed and will likely become more frequent and intense in the future under the effects of climate change.

54 ENVIRONMENTAL SCIENCES↗

Validation of Calibrated k–ε Model Parameters for Jet-in-Crossflow

Previous efforts determined a set of calibrated, optimal model parameter values for Reynolds-averaged Navier–Stokes (RANS) simulations of a compressible jet in crossflow (JIC) using a $k–ε$ turbulence model. These parameters were derived by comparing simulation results to particle image velocimetry (PIV) data of a complementary JIC experiment under a limited set of flow conditions. Here, a $k–ε$ model using both nominal and calibrated parameters is validated against PIV data acquired from a much wider variety of JIC cases, including a realistic flight vehicle. The results from the simulations using the calibrated model parameters showed considerable improvements over those using the nominal values, even for cases that were not used in the calibration procedure that defined the optimal parameters. This improvement is demonstrated using a number of quality metrics that test the spatial alignment of the jet core, the magnitudes of multiple flow variables, and the location and strengths of vortices in the counter-rotating vortex cores on the PIV planes. These results suggest that the calibrated parameters have applicability well outside the specific flow case used in defining them and that with the right model parameters, RANS solutions for the JIC can be improved significantly over those obtained from the nominal model.

42 ENGINEERING↗

Evaluating Transfer and Pumping of Slurries from Pulsed Jet Mixed Vessels

Due to gravity, solids in slurries will settle if density differences between the solids and liquid are positive (i.e., particle has a negative buoyant force) unless rheological properties and flow conditions are adequate to overcome the gravitational effects. The rate of settling depends on the force balance of the particle, which includes the surface forces associated with fluid rheology. Given the same fluid and solid properties, particles that are larger and denser tend to settle faster. When pumping slurry into a vessel at concentrations precluding hindered settling with insufficient mixing, particle and density distributions can result in preferential settling, creating stratification in the solids concentration within the vessel. For vessels with transfer line inlets located in the lower portion of the tank, the stratified solids concentration may be detrimental to the transfer system performance. Elevated concentrations of solids in the slurry entrained at the inlet to the transfer line can result in the effective viscosity or slurry bulk density exceeding the design limits of the pump. These conditions could result in plugging of the transfer line or onset of cavitation of the pumps because of excessive pressure drop. These conditions can be exacerbated with periodic inlet conditions existing at the transfer line inlet. Periodic conditions can result when vessel mixing is intermittent such as with pulsed jet mixers (PJM). The transfer line inlet conditions are impacted by the periodic nature of the PJM operations with respect to suspension of solids and their transport to the inlet of the transfer line. A scaling approach is presented, and corresponding test requirements are developed for assessing the prevention of plugging the pipeline. Line plugging mechanisms are addressed that do not include plugging due to steady-state high-density slurry entering the transfer line and reducing the net positive suction head available (NPSHA) at the pump inlet to below that required for pump operation. Items considered include the transition to reduced relative flow velocities, such that the critical pipe velocity for solids deposition, Ucd, is not maintained, and segregation of heavy solids during the transport. The recommended requirements to prevent plugging include: • Limits for viscosity and density for entrained slurry to prevent the pressure drop in the pipeline from exceeding pump capacity. • Limits for viscosity and density for entrained slurry to prevent the net positive suction head available (NPSHA) from falling below the net positive suction head required (NPSHR) for operating the pump. • Transfer line velocity and flow rate requirements to maintain solids in suspension, while avoiding line plugging that results from deposition of solids within the transfer line. This paper describes the development of the scaling and testing requirements to verify that proposed approaches for transfer and pump out are appropriately developed

periodic flow, mixing, pipeline plugging, scaling,↗

Validation study of RWM stability in DIII-D high- β N plasmas

The n = 1 (n is the toroidal mode number) resistive wall mode (RWM) stability is numerically investigated for two DIII-D high-β N discharges 176440 and 172461, utilizing the MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) and MARS-K (Liu et al 2008 Phys. Plasmas 15 112503) codes. Systematic validation efforts are attempted, for the first time, for discharges with very slow or vanishing toroidal flow for a large fraction of the plasma volume. While gaining physics insights in accessing stable operation regime at β N exceeding the Troyon no-wall limit in these slow-rotation experiments, the predictive capability of fluid and non-perturbative magnetohydrodynamic-kinetic hybrid models for the RWM is further confirmed. The MARS-F fluid model, with a strong but numerically tunable viscosity mimicking ion Landau damping of parallel sound waves, finds complete stabilization of the n = 1 RWM in the considered DIII-D plasmas under the experimental flow conditions. Similarly, either full stabilization (for discharge 176440) or marginal stability (for discharge 172461) of the mode is computed by the MARS-K hybrid model, which is first-principle based without free model parameters. In particular, all drift kinetic resonances, including those of thermal and energetic particles, are found to synergistically act to marginally stabilize the RWM in discharge 172461. These MARS-F/K modeling results explain the experimentally observed stable operational regime in DIII-D, as far as the RWM stability is concerned. Extensive numerical sensitivity studies, with respect to the plasma toroidal flow speed as well as the radial location of the resistive wall, are also carried out to further support the validation study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reynolds-Averaged Turbulence Modeling Using Deep Learning with Local Flow Features: An Empirical Approach

Reynolds-Averaged Navier-Stoke (RANS) models offer an alternative avenue in predicting flow characteristics when the corresponding experiments are difficult to achieve due to geometry complexity, limited budget, or knowledge. RANS models require the knowledge of subgrid scale physics to solve conservation equations for mass, energy, and momentum. Mechanistic turbulence models, such as k-epsilon, are generally evaluated and calibrated for specific flow conditions with various degrees of uncertainty. These models have limited capability to assimilate a substantial amount of data due to model form constraints. Meanwhile, deep learning (DL) has been proven to be universal approximators with the potential to assimilate available, relevant, and adequately evaluated data. Moreover, deep neural networks (DNNs) can create surrogate models without knowing function forms. Such a data-driven approach can be used in updating fluid models based on observations as opposed to hard-wiring models with precalibrated correlations. The paper presents progress in applying DNNs to model Reynolds stress using two machine learning (ML) frameworks. A novel flow feature coverage mapping is proposed to quantify the physics coverage of DL-based closures. It can be used to examine the sufficiency of training data and input flow features for data-driven turbulence models. The case of a backward-facing step is formulated to demonstrate that not only can DNNs discover underlying correlation behind fluid data but also they can be implemented in RANS to predict flow characteristics without numerical stability issues. Finally, the presented research is a crucial stepping-stone toward the data-driven turbulence modeling, which potentially benefits the design of data-driven experiments that can be used to validate fluid models with ML-based fluid closures.

42 ENGINEERING↗

Automated bubble analysis of high-speed subcooled flow boiling images using U-net transfer learning and global optical flow

Capturing and analyzing the bubble dynamics is crucial to improving the understanding of boiling heat transfer mechanisms and predicting boiling heat transfer coefficient and boiling crisis. High speed video (HSV) imaging has been used for decades towards this end. Still, there is no universal approach to quantitatively analyze bubble dynamics from HSV images. In this study, we propose a data-driven post-processing approach to segment, track, and identify wall-attached vapor bubbles from HSV images of the boiling process in subcooled flow conditions. Firstly, we employ a transfer learning framework with a U-Net-based convolution neural network (CNN) architecture to detect and segment bubbles in HSV images of diverse contrast and surface texture using very little data (e.g., 10 images) for training. Then, we evaluate the trained CNN model with 100 ground-truth images, and the validation results show that the model accuracy and precision in detecting the optical footprint of bubbles are higher than 90%. Finally, we suggest a criterion to identify a condensing bubble based on the divergence of the bubble displacement, which is calculated from sequential segmented bubble images using a global optical flow code. Using this combination of machine learning and optical flow, we can identify nucleation sites and track the growth of bubbles nucleating at each site to quantify nucleation site density, nucleation frequency, and other fundamental boiling parameters. The proposed system is validated using results obtained on a special heater, which enables both infrared (IR) thermometry and HSV imaging on a metallic surface. We compare the fundamental boiling parameters obtained by the two different diagnostics. The results show good agreement. In conclusion, the difference between the measurements of nucleation site density, averaged nucleation frequency, and averaged growth time performed with the two techniques is always within ± 20% and mostly ± 10% of the values measured with IR thermometry.

42 ENGINEERING↗

Simulation and Analysis on Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS) under SBLOCA scenario by using Cardinal to support the fracture mechanics analyses

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended durations or under accident condition. As one of the most significant components of a Reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Ageing degradation mechanisms (e.g. thermos-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary. The multi-physics simulations are performed using Cardinal, a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and other multi-physics sub-modules within the MOOSE framework. Cardinal now fully supports MOOSE stochastic perturbations of NekRS models with varying boundary conditions, initial conditions, material properties, and any other quantity which is defined by a kernel (such as coefficients in a momentum source model). The implementation is designed in a flexible manner so that scalar values are sent from MOOSE into a user scratch space in NekRS, which can then be applied for any purpose within the NekRS case files (both on the host and device). When modeling PTS, several factors can impact the results significantly. In this report, the impacts of the geometry of the model, Reynolds number and buoyancy effect are investigated. Two geometry, i.e., a simplified model and a realistic RPV model, with both laminar and turbulent flow condition are adopted for the PTS simulation with and without buoyancy effect. The purpose of the investigation is to understand the impact of these factors on the prediction of temperature history of RPV. The accurate prediction on the temperature evolution, which will be exported to Grizzly code for further analyses on the progression of aging mechanisms and their effects on the integrity of RPV structures, is very crucial. Based on the understanding of these factors, a more sophisticated model is built to analysis the PTS under SBLOCA scenario. A literature survey is conducted to pick the SBLOCA scenario for the multi-physics simulation. The analysis helps to explain the form and the transformation of the cold plum when the ECC is activated under SBLOCA. This model can be can be applied to study the PTS effect for different RPV configurations. The results can help to assess structural component degradation for advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

TEAMER: Experimental performance characterization of a shrouded axial-flow turbine

Sitkana has developed a shrouded hydrokinetic turbine with a modular, low-cost design that can be scaled to meet the needs of remote communities. With technical support from the University of Washington, Sitkana sought to experimentally characterize the mechanical power and structural loads of various 1:3.3 scale rotor geometries. In all, 11 different rotor geometries were characterized with variations in height-to-diameter ratio, blade number, and blade type (foiled versus flat). All tests were conducted in Reynolds-independent flow conditions in the Alice C. Tyler Flume at the University of Washington. Results allow Sitkana to (1) refine the optimal rotor geometry, (2) validate numerical models, and (3) predict power output for a full-scale system. This project is part of the TEAMER RFTS 8 (request for technical support) program.

16 TIDAL AND WAVE POWER↗

Performance Characterization of a Natural Gas–Air Rotating Detonation Engine

An experimental study of a rotating detonation engine (RDE) operating with natural gas and air at elevated chamber pressures and air preheat temperatures was conducted to quantify its performance at conditions representative of land-based power generation gas turbine engines. Here, the thrust produced by the combustor was measured to characterize its work output potential. High-frequency pressure transducers and broadband chemiluminescence measurements of the flame provided information about the wave structure and dynamics. Analysis of common performance metrics demonstrated the necessity of normalizing any RDE performance parameter by the driving system potential, typically the reactant manifold pressure. Application of a thermodynamic performance model to a generic RDE identified the area ratio between the RDE exhaust and injection throats as the primary parameter affecting delivered pressure gain. The model was further applied to draw comparison with experimental measurements of net pressure gain for identical flow conditions. Only one of the two tested injector configurations followed the predicted trends, suggesting that performance of the second was governed by physical processes other than the reactant thermodynamics. Although an absolute pressure gain was not demonstrated, it is promising that the natural gas–air RDE delivered up to 90% of the theoretical performance.

20 FOSSIL-FUELED POWER PLANTS↗

Connecting particle interactions to agglomerate morphology and rheology of boehmite nanocrystal suspensions

Rheology imposes significant challenges on processing of complex suspensions such as nuclear waste slurries at the Hanford and Savannah River sites. Understanding rheology connecting to microstructures and underlying particle interactions in complex slurries is therefore important for both fundamental knowledge and practical applications. Here, we use suspensions of aluminum oxyhydroxide minerals in the form of boehmite as an analog of the radioactive waste slurry to gain physical insights on the correlation between particle interactions, microstructures, and slurry rheology. Specifically, we use a combination of Couette rheometry and small-angle scattering techniques (independently and simultaneously) to understand how the slurry microstructure changes under flow and how these structural changes manifest themselves in the bulk rheology of the suspensions. Our experiments show that the boehmite slurries are thixotropic, with the rheology and structure of the suspensions changing with increasing exposure to flow. In the slurries, particle aggregates begin as loose, system-spanning clusters, but exposure to moderate shear rates causes the aggregates to irreversibly consolidate into denser clusters of finite size. The microstructural changes directly influence the rheological properties of the slurries such as viscosity and viscoelasticity. More importantly, our study shows that solution pH affects the amount of structural rearrangement and the kinetics of the rearrangement process, with an increase in pH leading to faster and more dramatic changes in the bulk rheology. Such dynamic microstructural changes and resultant rheology are understood via correlations between particle interactions and strength of particle network, coupled with surface chemistry and anisotropic nature of particle interactions. Nearly identical structural changes are also observed in Poiseuille flow geometries, implying that the observed changes are relevant in the pipe flow conditions present during waste processing.

Weston, Javen S.↗

Cesium Removal and Hydraulic Performance Comparisons of CST Ion Exchange Media Batches in Support of the Tank Closure Cesium Removal Project - 20522

Three batches of Crystalline Silicotitanate (CST) ion exchange media have been evaluated for cesium removal efficiency from a Savannah River Site (SRS) High Level Waste (HLW) supernate simulant in support of the Tank Closure Cesium Removal (TCCR) Project, which involves at-tank column waste treatment. Results will be utilized to select the CST media batch to be added to the next TCCR unit columns. Two of the CST media samples were recent production batches and the third was an archived batch studied extensively at SRS nearly two decades ago. The archived CST batch had a significantly smaller average particle diameter than more recent batches. Small-scale (∼23 mL), side-by-side column tests were conducted at 35 deg. C with each of the CST batches using the same simulant at flow rates near 1.2 mL/min (3.0-3.4 CST bed volumes/hr). The cesium ion exchange column performance results were lower than expected for all three CST batches, but the data indicated that 30% more simulant volume and 40% more equivalent CST bed volumes of solution can be processed with the older CST batch prior to reaching the 50% cesium breakthrough point than can be processed with the newer CST batches. Hydraulic evaluations of the CST columns were also conducted in simulant at 24 deg. C to determine the impact of the different particle size distributions and associated bed porosities on frictional pressure drop under dynamic flow conditions. Higher differential pressure drops were observed with the archived CST batch relative to recent production batches, due to the smaller particle size distribution and the packing characteristics of the archived batch. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

In Situ Electrochemical Study of the Coexistence of Eu 3+ and Eu 2+ in Molten LiCl-KCl by Rotating Disc Electrode

In this study, a graphite rotating disc electrode was successfully designed and applied to conduct electrochemical measurements under flow conditions in molten LiCl-KCl at 773 K. The concentration and diffusion coefficients of Eu 3+ and Eu 2+ in molten salt were quantitatively measured with this electrode by applying in situ cyclic voltammetry and chronoamperometry techniques. The initial concentration ratio of Eu 3+ /Eu 2+ in LiCl-KCl-0.5 wt% EuCl 3 was calculated to be 2.37. The calculated diffusion coefficients of Eu 3+ and Eu 2+ in the salt were 9.31 ± 0.06 × 10 -5 cm 2 s -1 and 9.65 ± 0.6 × 10 -5 cm 2 s -1 , respectively. A decrease of the diffusion coefficient of Eu 3+ and Eu 2+ was observed at a higher concentration of EuCl 3 , which implies the enhanced Eu-Eu ion interaction. This electrode design is expected to be utilized for the concentration measurement of multivalent ions in a flowing molten salt.

Electrochemistry↗

Reactive Capture and Conversion of Carbon Dioxide to Methanol with ZnZrO 2 and Alkali-Promoted Mg 3 AlO x Mixed Oxide Catalytic Sorbents

Reactive capture and conversion (RCC) explores the use of a single-unit process to capture CO 2 and produce a product, in this case, methanol (MeOH). In this study, different configurations of a catalytic sorbent (CS) composed of ZnZrO 2 catalyst and Mg 3 AlO x sorbent with and without alkali modification are evaluated for CO 2 adsorption, steady-state catalysis with cofed CO 2 and H 2 , and transient RCC performance. A catalyst composed of a physical mixture of Mg 3 AlO x with ZnZrO 2 resulted in a slight increase in CO 2 uptake, with a low impact on the catalytic activity and RCC of the materials compared to ZnZrO 2 alone. In contrast, Na impregnation significantly increased the level of CO 2 uptake from 0.28 mmol/g (ZnZrO 2 alone) to 0.6 and 1.1 mmol/g for the CS with Na on the catalyst or Mg 3 AlO x , respectively. However, Na impregnation reduced the CO 2 conversion rate and MeOH selectivity during steady-state cofeed experiments at 300 °C and 6 bar. In contrast to steady-state catalysis conditions, RCC, which is a cyclic capture and conversion process, creates dynamic CO 2 and H 2 surface coverages, favoring CH 4 in the early stages of the conversion step and then CO and MeOH as the catalyst CO 2 coverage reduces. The highest MeOH productivity during RCC was achieved with CS that balanced the CO 2 uptake with only moderate catalyst rate reductions caused by Na addition. The optimal material, ZnZrO 2 +10%Na/Mg 3 AlO x , achieved a CO 2 uptake of 0.8 mmol/g and a MeOH productivity of 0.5 mmol/g with 100% selectivity at 260 °C and 6 bar during RCC. This marks the highest RCC MeOH productivity reported to date, although the process needs further optimization and even with optimization, may remain impractical. The results further demonstrate that optimization of catalytic sorbents under steady-state flow conditions does not easily correlate to transient capture and conversion cycles for methanol synthesis from CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗