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At least 55 records · Page 3

Experimental validation of the mechanistic scale-up methodology of gas–solid spouted beds using radioactive particle tracking (RPT)

The very high-temperature reactors (VHTRs) are highly ranked among candidates of Generation IV of nuclear reactors due to their high efficiency, safety, the resistance to proliferation, and reliability. The VHTRs are preferentially fueled by Tristructural-isometric (TRISO) coated fuel particles which has fuel kernels of fissile material coated by four coating layers: a porous buffer pyrolysis carbon layer (buffer PyC), an inner dense pyrolysis carbon layer (IPyC), a silicon carbide layer (SiC) and an outer dense pyrolysis carbon layer (OPyC). The heart of the operation and safety of the VHTRs significantly depends on the reliability of the coating layers of TRISO particles to retain metallic and gaseous fission products within the particles. The technique used for coating TRISO particles are gas-solids spouted beds via chemical vapor deposition (CVD). Fabrication of high-quality low-defect TRISO fuel particles fuel at larger scale spouted beds is required to support the commercialization of the VHTRs. In this work, our new developed mechanistic scale-up methodology of gas-solids spouted beds based on matching the radial profile of gas-holdup has been demonstrated and validated using radioactive particle tracking (RPT). Two spouted beds of small and larger scales were used in the study. Three sets of conditions were carried out which include the conditions of the reference case in the large scale, conditions that provide similar gas holdup radial profile to that of the reference case and conditions that provided dissimilar gas holdup radial in the small-scale spouted beds. The results confirm the validation of the scale-up methodology in terms of the dimensionless values of the spout diameter, cumulative probability distribution of the solids particles penetration into the spout, fraction of cycle time in each region of the bed, the radial profiles of the dimensionless values of the root-mean-square particle velocities and solids eddy diffusivity. Finally, the results further advance the knowledge and understanding of the gas-solids spouted beds provide deeper insight into their solids dynamics and presenting important benchmarking data for validating computational fluid dynamics codes and models. At last, procedures are established for the implementation of the new scale-up methodology.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Study on Application of Distributed Network of Sensors with List Mode for NMAC Literature Review

Nuclear material accounting and control (NMAC) for nuclear security detects, deters, and resolves questions related to unauthorized removal (i.e. theft) or misuse of nuclear material. NMAC also serves as a key insider threat mitigation measure and aids in recovery of nuclear material that is missing. Effective nuclear security depends on NMAC for timely and accurate information about nuclear material types, quantities, and locations. Bulk nuclear material processing facilities, however, present unique challenges for effective NMAC due to the presence of large quantities of material in-process and the accumulation of residual material holdup within process equipment. These holdup accumulations can obscure accurate physical inventory taking and complicate efforts to resolve NMAC irregularities at the facility level. Bulk material monitoring systems often rely on material balance calculations and indirect measurement techniques, which may mask protracted theft of smaller amounts of nuclear material. These monitoring limitations have generated increased interest in continuous monitoring technologies, including distributed non-destructive assay (NDA) sensor networks capable of providing real-time or near-real-time measurement of material movement and accumulation within bulk processing environments. Recent advancements in distributed networks of NDA radiation detectors and sensing technologies provide an opportunity to address these limitations. Although such distributed sensor networks have been implemented in select facilities for IAEA Safeguards applications, their potential for supporting NMAC functions specifically tailored to nuclear security objectives remains largely unexplored. Furthermore, emerging list-mode data acquisition technologies have reached high technology readiness levels, enabling time-correlated detection of nuclear events across multiple temporal scales. These capabilities provide enhanced opportunities for accurate holdup measurement, continuous process monitoring, and improved detection of material theft or misuse over time. The increasing global expansion of civil nuclear power and development of related bulk material processing facilities, including those supporting high-assay low-enriched uranium (HALEU) and other advanced reactor fuel fabrication, further increases the need for advanced measurement and monitoring strategies for NMAC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging

Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.

Laminack, Alex↗

Computational Analysis of Different Sparging Systems and their Influence in the Fluid-Dynamic Behavior of Bubble Column Reactors

Bubble column bioreactors are being actively considered for gas fermentation applications, specifically for CO2 utilization, and sugars to fuels conversion. Their main advantages include good mass transfer without any moving parts and low-cost of operation and maintenance. However, the design and scale-up of such reactors is challenging specifically for carbon capture applications where a mixture of gases (e.g. CO2/CO/H2) with variable solubilities is used. The overall performance of scaled-up bioreactors (e.g., mass transfer rate) is largely affected by gas holdup, bubble size distribution (BSD), and multiphase hydrodynamics. We investigate the effect of gas sparger designs on the performance of these large-scale bioreactors using computational fluid dynamics simulations in this work, so as to improve CO2 conversion at scale. The gas distribution systems in bubble column reactors not only determines operational regime, but also affects the evolution of the BSD, which in turn influences interfacial mass transfer and ultimately the efficiency of the gas-liquid exchange process. In addition to the BSD, uniformity in gas sparging affects gas holdup and bubble residence time which constitute important metrics of performance in gas-liquid systems. In this work, we use computational models to simulate high fidelity representations of different sparger designs and their effect on the operation of a bubble column reactor. Four different types of spargers have been selected for the computational study (Fig. 1): ladder, multi-ring, single-ring and toroidal. Their effect on superficial velocity, gas holdup mixing efficiency, and BSD will be evaluated in this work. The model uses a multiphase Eulerian framework similar to [1] and include a composition of mixtures of H2/CO/CO2 gases, common in fermentation applications.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗

Possible impacts of molten salt reactors on the International Monitoring System

Molten salt reactors (MSRs) are gaining support as many countries look for ways to increase power generation and replace aging nuclear energy production facilities. MSRs have inherently safe designs, are scalable in size, can burn transuranic wastes from traditional solid fuel nuclear reactors, can store excess heat in thermal reservoirs for water desalination, and can be used to produce medical isotopes as part of the real-time liquid-fuel recycling process. The ability to remove 135 Xe in real time from the fuel improves the power production in an MSR because 135 Xe is the most significant neutron-absorbing isotope generated by nuclear fission. Xenon-135, and other radioactive gases, are removed by sparging the fuel with an inert gas while the liquid fuel is recirculated from the reactor inner core through the heat exchangers. Without effective abatement technologies, large amounts of radioactive gas could be released during the sparging process. This work examines the potential impact of radioxenon releases on samplers used by the International Monitoring System (IMS) to detect nuclear explosions. Here, atmospheric transport simulations from seven hypothetical MSRs on different continents were used to evaluate the holdup time needed before release of radioxenon so IMS samplers would register few detections. Abatement technologies that retain radioxenon isotopes for at least 120 d before their release will be needed to mitigate the impacts from a molten salt breeder reactor used to replace a nuclear power plant. A holdup time of about 150 d is needed to reduce emissions to the average level of current nuclear power plants.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Trade Study of Nondestructive Assay Technologies

The purpose of this report is to summarize the capabilities of currently existing NDA technologies that can be applied to holdup measurements. Cataloguing the strengths and weaknesses of the existing state of the art is a necessary step towards setting goals for new technology development. The NDA technologies evaluated in this report include gamma imaging, non-imaging gamma detectors, and neutron coincidence counting. These technologies were chosen based on their potential for technological improvement or to be applied in different settings. Each technology will be analyzed on a set of evaluation criteria chosen to represent the most salient features of a detector system for holdup measurements. These criteria include sensitivity, energy resolution, angular resolution (for imaging technologies only), ease of use, and cost.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Studies of Helium Behavior in Uranium Hexafluoride

Several issues have arisen from experimental observations and/or theoretical postulation related to the behavior of helium in uranium hexafluoride (UF 6 ) matrices and how it may impact the ability to use this noble gas to quantify the fill date of the cylinder. A series of experiments was conducted to address several such issues, and the results and implications are reported here. Two issues relate to bias in the helium measurement due to ambient air from extraneous sources such as atmospheric air or from potential holdup in a large, activated alumina chemical trap. These issues are really a question of differential retention of helium versus three other inert gas isotopes (representative of other noble gases found in air) used as a calibration for air in leakage. Discernable bias was not detected in either case. Another issue had to do with helium potentially brought into the cylinder by a liquid UF 6 fill and subsequently released as the material solidifies and/or during storage. The solubility of helium in liquid UF 6 was measured to investigate this theory. The experiment quantified the potential magnitude of the initial helium contribution if present. The final issue was that of retention of helium in solid UF 6 . Investigation of this theory necessitated quantifying both the solubility and the diffusivity of helium in UF 6 . In one experiment, the solubility was measured at cryogenic temperature, allowing quantification of helium in solid UF 6 such as would be found in a cold trap. In a second experiment, transport of helium into and through a macroscopic plug of solid UF 6 was examined. The transport was very slight although apparently detectible. Effectively, only an upper limit to the transport could be determined, but that limit implied that helium holdup in solid UF 6 is a real possibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of a Triple Bubbler Inside Molten Salt for Pyroprocessing Safeguards Purposes

The application of a triple bubbler system within molten salt environments, specifically a eutectic mixture of LiCl-KCl, is explored for nuclear safeguards purposes, focusing on nuclear material accountancy (NMA) and holdup accountancy in pyroprocessing techniques. Traditional holdup accountancy methods, which involve periodic sampling and lengthy lead times, are being supplemented by the development of actinide sensors using electrochemistry. However, these methods alone are insufficient to meet regulatory requirements set by agencies like NRC and IAEA. The triple bubbler device measures salt level, density, and surface tension simultaneously using three dip tubes of varying diameters and heights. This study investigates the accuracy and robustness of the triple bubbler in molten salt conditions at temperatures ranging from 450-550°C. The updated bubbler design, utilizing tantalum metal and larger tube geometry, demonstrated minimal plugging and maintained measurement accuracy within acceptable uncertainties: 0.611% for depth, 1.34% for density, and approximately 40% for surface tension. Results indicate that the triple bubbler system is effective for real-time, accurate measurements in pyroprocessing environments, making it a promising tool for ensuring compliance with nuclear safeguards and supporting nuclear non-proliferation efforts.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Passive Neutron Instrumentation and Applications

This chapter presents a description of most of the instruments that are currently in use for the measurement of plutonium and uranium using passive methods (without an external source). This includes the acquisition electronics as well as Singles counting methods, coincidence counting methods and multiplicity counting methods. The Singles counting applications include the measurement of waste and curium bearing materials. The coincidence counting applications include bulk plutonium, bulk uranium, waste and holdup measurements and fresh fuel assemblies. The multiplicity application description includes advantages and disadvantages and multiplicity detector design. There is also a description of some non-3He systems. The chapter concludes with a description of additional concepts: neutron imagers, list-mode data analysis, distributed source term analysis, unattended monitoring and MCNP modeling for detector design.

Coincidence shift register↗

Plasma Bubble Column Reactor: A High Throughput Reactor Design for Water Treatment

Plasma-based water treatment (PWT) is a promising technology that can degrade various emerging contaminants. However, PWT application on an industrially viable scale is hindered by the lack of an efficient reactor design that combines enhanced plasma-liquid contact with high liquid throughput. This work investigates the applicability of a bubble column gas-liquid contactor to PWT. A pulsed plasma bubble column reactor (PBCR) with a concentric rod-cylinder electrode configuration was used to correlate contaminant removal performance with the gas-liquid contact parameters of the bubble column. A surfactant, rhodamine B dye, and a nonsurfactant, caffeine, were used as model contaminants at µM concentration levels. The bubble column characteristics, i.e., gas holdup, bubble size distribution, and gas-liquid area, were measured as a function of superficial gas velocity using image-based methods. Degradation rates of both contaminants increased with gas flowrate. For caffeine, the increase was attributed to intensified bulk liquid mixing, while dye degradation increased due to the increased gas-liquid area. Ultimately, we show that bubble column contactors significantly improve the utilization of plasma-generated reactive species toward contaminant degradation by distributing them over a large contact area. As a result, a better match between the plasma species interfacial flux and the interfacial contaminant concentration leads to improved treatment energy efficiency. Furthermore, typical degradation energy efficiencies were ~10 g/kWh for caffeine and ~60 g/kWh for rhodamine B.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experiments and CFD simulation of mass transfer and hydrodynamics in a cylindrical bubble column

Flow visualization, Particle Image Velocimetry (PIV) and dissolved oxygen charging experiments are carried out in a small-scale cylindrical air-water bubble column at different superficial gas velocities. Void fraction profile, total gas holdup, liquid phase velocity field and volumetric mass transfer coefficient are obtained. Details of each experiment are given, with a new procedure for obtaining a 2D void fraction profile from flow visualization by image processing and time averaging which could provide useful information for CFD model validation. The experimental results are analyzed and compared with simulations where good agreement is found for both local and global flow patterns. The averaged governing equations and constitutive relations used in the simulation are discussed briefly, with emphasis on the proper comparison between simulations and experiments based on the derivation of the two-fluid model. Finally, by conducting three sets of experiments related to phase distribution, velocity field and mass transfer in the same apparatus, a validated CFD model for multiphase mass transfer is established and can be used in the future design of a multi-phase reactor.

42 ENGINEERING↗

Efficient carbon capture using sub-textured polymer packing surfaces via 3D printing

Gas absorption is a common unit operation whose performance deeply relies on the gas liquid contact behavior. In this work, we report a solid polymeric surface feature containing microscale striation to improve the solid-liquid and gas-liquid contact and facilitate mass transfer. As a proof of concept, the surface feature is adopted for CO 2 capture absorber packing via 3D printing. Besides traditional embossing texture, an additional laminar striation is applied to the packing surface as a sub-texture. The packing shows notable CO 2 mass transfer increase without interfering with other key operating characteristics including pressure drop and liquid holdup. The improvement is based on the synergy of favorable wettability, thin liquid film and increased liquid mixing from rougher surface. In the demonstration test, the packing height could decrease by 33% using the advanced packing with same CO 2 removal, leading to a significant decrease in equipment size and capital expense for commercial CO 2 capture systems.

3D printing↗

Bayesian calibration of bubble size dynamics applied to CO 2 gas fermenters

To accelerate the scale-up of gaseous CO 2 fermentation reactors, computational models need to predict gas-to-liquid mass transfer which requires capturing the bubble size dynamics, i.e. bubble breakup and coalescence. However, the applicability of existing models beyond air–water mixtures remains to be established. Here, an inverse modeling approach, accelerated with a neural network surrogate, calibrates the breakup and coalescence closure models, that are used in class methods for population balance modeling (PBM). The calibration is performed based on experimental results obtained in a CO 2 -air–water-coflowing bubble column reactor. Bayesian inference is used to account for noise in the experimental dataset and bias in the simulation results. To accurately capture gas holdup and interphase mass transfer, the results show that the breakage rate needs to be increased by one order of magnitude. In conclusion, the inferred model parameters are then used on a separate configuration and shown to also improve bubble size distribution predictions.

09 BIOMASS FUELS↗

Logical approach to tritium vacuum pump selection for fusion applications

Vacuum pumps have been used for tritium processing since the 1940s following the isolation of pure tritium. The largest problem facing tritium vacuum pumps is the tritium radioactive decay. The beta particles, recoil energy, and subsequent radical formations are detrimental to most carbon-based materials. Carbon materials, such as plastics, elastomers, carbon fiber, activated carbon, etc., react with tritium to form methane and in the process strip material from the carbonbased material. Other reactions can be self-catalyzing, as is the case with nitrogen and tritium forming tritiated ammonia at room temperature and pressure. Tritium also readily isotopically exchanges with surface -OH groups, increasing the amount of protium in the gas stream while creating a tritium holdup on the surface. Metals are the preferred material when working with tritium, but tritium will permeate into and through almost all metals at some point. The entrapped tritium can decay inside the metal, creating local helium distortions that can impact the structural properties above and beyond the hydrogen embrittlement issue tritium can cause.

Angelette, Lucas M. [Savannah River National Labor↗

Development of an innovative process for post-combustion CO 2 capture to produce high-value NaHCO 3 nanomaterials

An innovative post-combustion process using aqueous sodium glycinates solutions (SGS) for CO 2 capture from a split flue gas stream emitted from the 600 MWe coal power plant, used in the Wolverine Clean Energy Venture (WCEV) project, was developed in Aspen Plus v.10. The flue gas flow rate used in the process was 12.43 kg/s (at 353.15 K and 101.33 kPa) and contained 0.0023 and 13.33 mol% of SO 2 and CO 2 , respectively. The overall process includes 5 main units designed to remove all SO 2 and capture more than 90 mol% of CO 2 in the flue gas stream, while producing high-value, salable sodium bicarbonate (NaHCO 3 ) nanomaterials to offset the total process costs. The hydraulics, mass transfer characteristics, and process performance obtained using Aspen Plus were discussed. Also, the capital expenditure (CAPEX), operating expenditure (OPEX), and Levelized cost of CO 2 capture (LCOC) were calculated to assess the feasibility of this process. Further, the hydraulics in the SO 2 washing and CO 2 capture units showed a pressure drop of 12 and 1 kPa, respectively, and the behaviors of the liquid holdup and normalized packing specific wetted surface area were similar in both units. The gas-side mass transfer coefficients were orders of magnitude greater than the liquid-side mass transfer coefficients. The process was able to capture 2.352 kg/s of CO 2 and produce 4.486 kg/s of valuable NaHCO 3 nanomaterials. Also, the calculated CAPEX, OPEX, and LCOC of the process for a 30-year plant lifetime were ($\$ $4,450,552), (233.00 $\$ $/h) and (35.49 $\$ $/ton of CO 2 captured), respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data

The paper presents the development of algorithms for mass and energy constrained neural network models that can exactly conserve the overall mass and energy of distributed chemical process systems, even though the noisy transient data used for optimal model training violate the same. In contrast to approximately satisfying mass and energy balance constraints of a system by soft penalization of objective function, algorithms have been developed for solving equality-constrained nonlinear optimization problems, thus providing the guarantee of exactly satisfying the system mass and energy conservation laws. For developing dynamic mass-energy constrained network models for distributed systems, hybrid series and parallel dynamic-static neural networks have been leveraged. The developed algorithms for solving both the training and forward problems are validated using both steady-state and dynamic data in the presence of various noise characteristics. The developed data-driven algorithms are flexible to exactly satisfy mass and energy balance constraints for dynamic chemical processes if the system holdup information is available. The proposed network structures and algorithms are applied to the development of data-driven lumped and distributed models of an adiabatic superheater/reheater system, a nonisothermal continuous stirred tank reactor, as well as an electrically heated plug-flow reactor system where one form of energy gets transformed to another. It has been observed that the mass-energy constrained neural networks yield a root mean squared error of <1% with respect to the system truth for the case studies evaluated in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isotope Exchange of ND 3 on Pt Catalyst–Loaded 5A Molecular Sieve

Recollecting and purifying unburned tritium is a preferred process for D-T fusion operations. However, tritium containing byproducts act as a potential holdup for the material, requiring additional processing to liberate the tritium. Furthermore, using deuterium as a surrogate for tritium, this work demonstrates the capture and isotope exchange of deuterated ammonia using a Pt catalyst–loaded 5A molecular sieve, performed at ambient temperatures, verified by the analysis of the effluent gas streams and desorbed ammonia isotopologues post exchange.

5A↗

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗