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At least 469 records · Page 26

Redwing: A MOOSE application for coupling MPACT and BISON

Fuel performance and whole core neutron transport programs are often used to analyze fuel behavior as it is depleted in a reactor. For fuel performance programs, internal models provide the local intra-pin power density, fast neutron flux, burnup, and fission rate density, which are needed for a fuel performance analysis. The fuel performance internal models have a number of limitations. These include effects on the intra-pin power distribution by nearby assembly elements, such as water channels and control rods, and the further limitation of applicability to a specified fuel type such as low enriched UO2. In addition, whole core neutron transport codes need an accurate intra-pin temperature distribution in order to calculate neutron cross sections. Fuel performance simulations are able to model the intra-pin fuel displacement as the fuel expands and densifies. These displacements must be accurately modeled in order to capture the eventual mechanical contact of the fuel and the clad; the correct radial gap width is needed for an accurate calculation of the temperature distribution of the fuel rod. Redwing is a MOOSE-based application that enables coupling between MPACT and BISON for transport and fuel performance coupling. MPACT is a 3D neutron transport and reactor core simulator based on the method of characteristics (MOC). The development of MPACT began at the University of Michigan (UM) and now is under the joint development of ORNL and UM as part of the DOE CASL Simulation Hub. MPACT is able to model the effects of local assembly elements and is able calculate intra-pin quantities such as the local power density on a volumetric mesh for any fuel type. BISON is a fuel performance application of Multi-physics Object Oriented Simulation Environment (MOOSE), which is under development at Idaho National Laboratory. BISON is able to solve the nonlinearly coupled mechanical deformation and heat transfer finite element equations that model a fuel element as it is depleted in a nuclear reactor. Redwing couples BISON and MPACT in a single application. Redwing maps and transfers the individual intra-pin quantities such as fission rate density, power density, and fast neutron flux from the MPACT volumetric mesh to the individual BISON finite element meshes. For a two-way coupling Redwing maps and transfers the individual pin temperature field and axially dependent coolant densities from the BISON mesh to the MPACT volumetric mesh. Details of the mapping are given. Redwing advances the simulation with the MPACT solution for each depletion time step and then advances the multiple BISON simulations for fuel performance calculations. Sub-cycle advancement can be applied to the individual BISON simulations and allows multiple time steps to be applied to the fuel performance simulations. Currently, only loose coupling where data from a previous time step is applied to the current time step is performed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Data trustworthiness signatures for nuclear reactor dynamics simulation

With the increased reliance on digitization in industrial control systems, the need for effective monitoring techniques has risen dramatically. Specifically, there is now a growing concern about the so-called false data injection (FDI) attacks. These attacks aim to alter the raw sensors’ data to cause malicious outcomes. Any serious FDI algorithm is based on an intimate knowledge of the system and its associated physics models, which renders conventional outlier/anomaly detection techniques almost obsolete in the face of such attacks. Thus, a critical need has emerged to develop a new class of defense methods that are capable of detecting FDI attacks under the assumption that the attacker has a strong familiarity with the system and its physics modeling. This class of defense methods are denoted by model-based defenses which are premised on the assumption that the attacker, while having a good understanding of the system, does not have full privileged access to all proprietary data and historical records of operation. However, (s)he is assumed to be capable of learning system behavior using self-learning techniques during an initial lie-in-wait period. To defend against this scenario, we propose a new model-based randomized window algorithm that searches time-series data for signatures that can serve as classifiers between normal and FDI scenarios. The classifiers are based on the correlations between the dominant degrees of freedom (DOFs) and the less-dominant DOFs (expected to be very sensitive to the system details that are unknown to the attacker). For demonstration, RELAP5 models are employed to calculate representative nuclear reactor behavior during a number of transient scenarios. Finally, falsified data are injected into the RELAP5-simulated behavior, and the proposed signature-identification algorithm is employed to detect the injected data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Research Program for Fission Product/Dust Transport in HTGR’s

High and Very High Temperatures Gas Reactors (HTGRs/VHTRs) have five barriers to fission product (FP) release: the TRISO fuel coating, the fuel elements, the core graphite, the primary coolant system, and the reactor building. This project focused on measurements and computations of FP diffusion in graphite, FP adsorption on graphite and FP interactions with dust particles of arbitrary shape. Diffusion Coefficients of Cs and Iodine in two nuclear graphite were obtained by the release method and use of Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS) and Instrumented Neutron Activation Analysis (INAA). A new mathematical model for fission gas release from nuclear fuel was also developed. Several techniques were explored to measure adsorption isotherms, notably a Knudsen Effusion Mass Spectrometer (KEMS) and Instrumented Neutron Activation Analysis (INAA). Some of these measurements are still in progress. The results will be reported in a supplemental report later. Studies of FP interactions with dust and shape factors for both chain-like particles and agglomerates over a wide size range were obtained through solutions of the diffusion and transport equations. The Green's Function Method for diffusion and Monte Carlo technique for transport were used, and it was found that the shape factors are sensitive to the particle arrangements, and that diffusion and transport of FPs can be hindered. Several journal articles relating to the above work have been published, and more are in submission and preparation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

X-ray absorption spectroscopy characterization of embedded and extracted nano-oxides

Here, the chemistries and structures of both embedded and extracted Ysingle bondTisingle bondO nanometer-scale oxides in a nanostructured ferritic alloy (NFA) were probed by x-ray absorption spectroscopy (XAS). Y 2 Ti 2 O 7 is the primary embedded phase, while the slightly larger extracted oxides are primarily Y 2 TiO 5 . Analysis of the embedded nano-oxides is difficult partly due to the multiple Ti environments associated with different oxides and those still residing in matrix lattice sites. Thus, bulk extraction followed by selective filtration was used to isolate the larger Y 2 TiO 5 oxides for XAS, while the smaller predominant embedded phase Y 2 Ti 2 O 7 oxides passed through the filters and were analyzed using the log-ratio method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Numerical design of SiC bulk crystal growth for electronic applications

Presented study concerns numerical simulation of Physical Vapor Transport (PVT) growth of bulk Silicon Carbide (SiC) crystals. Silicon Carbide is a wide band gap semiconductor, with numerous applications due to its unique properties. Wider application of SiC is limited by high price and insufficient quality of the product. Those problems can be overcame by optimizing SiC production methods. Experimental optimization of SiC production is expensive because it is time consuming and requires large amounts of energy. Numerical modeling allows to learn more about conditions inside the reactor and helps to optimize the process at much lower cost. In this study several simulations of processes with different reactor geometries were presented along with discussion of reactor geometry influence on obtained monocrystal shape and size.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

New developments in ALCYONE 2.0 fuel performance code

ALCYONE is a multi-dimensional (1D, 2D or 3D) fuel performance code dedicated to pressurized water reactors (PWR). This code is co-developed in the PLEIADES platform by CEA, EDF and AREVA and simulates fuel pellets and cladding evolutions during base irradiation, power ramps and accidental situations. Sophisticated chemical and physical models are used. The thermal and mechanical behavior is solved with the finite element method based code CAST3M. ALCYONE 2.0 is the next release of the code and it includes several new features: improvements in incidental and accidental situations modeling, new models available for 2D and 3D schemes and an evolution of neutron model to simulate gadolinium fuel. ALCYONE 2.0 uses a new version of PLEIADES platform which allows the parallelized computation of rod axial slices in order to decrease computation times. To better simulate accidental situations, an axial transfer model for gases and a modeling of heaters for Loss Of Coolant Accident (LOCA) experiments have been added to the code. The axial transfer model can simulate an axial internal pressure gradient in the fuel rod. For power ramps simulations in the 1D scheme, a new model for dish filling is available. This version will be validated on more than 400 rods covering a wide range of irradiation conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tritium Control and Capture in Salt-Cooled Fission and Fusion Reactors: Status, Challenges, and Path Forward

Three advanced nuclear power systems use liquid salt coolants that generate tritium and thus face the common challenges of containing and capturing tritium to prevent its release to the environment. The fluoride salt–cooled high-temperature reactor (FHR) uses clean fluoride salt coolants and the same graphite-matrix coated-particle fuel as high-temperature gas-cooled reactors. Molten salt reactors (MSRs) dissolve the fuel in a fluoride or chloride salt with release of fission product tritium into the salt. In most FHR and MSR systems, the baseline salts contain lithium where isotopically separated 7 Li is proposed to minimize tritium production from neutron interactions with the salt. The Chinese Academy of Sciences plans to start operation of a 2-MW(thermal) molten salt test reactor by 2020. For high-magnetic-field fusion machines, the use of lithium enriched in 6 Li is proposed to maximize tritium generation—the fuel for a fusion machine. Advances in superconductors that enable higher power densities may require the use of molten lithium salts for fusion blankets and as coolants. Recent technical advances in these three reactor classes have resulted in increased government and private interest and the beginning of a coordinated effort to address the tritium control challenges in 700°C liquid salt systems. In this paper, we describe characteristics of salt-cooled fission and fusion machines, the basis for growing interest in these technologies, tritium generation in molten salts, the environment for tritium capture, models for high-temperature tritium transport in salt systems, alternative strategies for tritium control, and ongoing experimental work. Several methods to control tritium appear viable. Finally, limited experimental data are the primary constraint for designing efficient cost-effective methods of tritium control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Demonstration of Tokamak Discharge Shutdown with Shell Pellet Payload Impurity Dispersal

The first rapid tokamak discharge shutdown using dispersive core payload deposition with shell pellets has been achieved in the DIII-D tokamak. Shell pellets are being investigated as a possible new path toward achieving tokamak disruption mitigation with both low conducted wall heat loads and slow current quench. Conventional disruption mitigation injects radiating impurities into the outer edge of the tokamak plasma, which tends to result in poor impurity assimilation and creates a strong edge cooling and outward heat flow, thus requiring undesirable high-$Z$ impurities to achieve low conducted heat loads. The shell pellet technique aims to produce a hollow temperature profile by using a thin, low-ablation shell surrounding a dispersive payload, giving a greatly increased impurity ablation (and radiation) rate when the payload is released in the plasma core. This principle was demonstrated successfully using 3.6 mm outer diameter, 40 μ m thickness diamond shells holding boron powder. The pellets caused rapid (<10 ms) discharge shutdown with low conducted divertor heat fluence (~0.1 MJ/m 2 ). Confirmation of massive release of the boron powder payload into the plasma core was obtained spectroscopically. Some evidence for the formation of a hollow temperature profile during the shutdown was observed. Furthermore, these first results open a new avenue for disruption mitigation research, hopefully enabling development of highly effective methods of avoiding disruption wall damage in future reactor-scale tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Unstructured mesh-based multi-physics reactor transient simulation with iMC code

In this study, we present a time-dependent Monte Carlo simulation result about a complex fuel-loaded light water reactor system with thermal-hydraulic feedback using the KAIST iMC code. The intra-pin temperature distribution is calculated based on Monte Carlo-tallied detailed power distribution and the finite element heat transfer method. The temperature effect of fuel, absorber, and coolant are adequately reflected into the dynamic response by the on-the-fly Doppler broadened cross-section correction. For the time-dependent Monte Carlo transport simulation, the predictor-corrector quasi-static Monte Carlo method is used for this study. We tested the coupled analysis framework with a 17-by-17 fuel assembly loaded with the centrally-shielded burnable absorber (CSBA) fuel element. The temperature feedback effect on the material cross-section and the moderator density incurred negative reactivity in response to the external positive reactivity insertion, showing the inherent stability of the reactor system. The pin-wise power and temperature change during the system transient are presented and discussed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Hypothetical Nuclear Reactor Facility Modeling Simulation Data Scenario Comparison

This document evaluates a hypothetical nuclear powerplant and associated protective force personnel using modern modeling and simulation tools. The facility incorporates security early in the design to consider and integrate methods to resolve security issues and vulnerabilities via the facility’s inherent design characteristics before construction. The evaluation in this document is an example only. It is not intended to recommend or evaluate the effectiveness of existing physical security requirements or identify any method that the U.S. Nuclear Regulatory Commission staff may find acceptable for complying with existing requirements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Review of recent activities with MOOSE, an open-source finite element & finite volume multi-fidelity simulation framework

Modeling and simulation are an increasing part of engineering. This is undoubtedly driven by the high costs of constructing experimental facilities, but also enabled by the exponential increase in computing powers over the last decades, which allows computational models to be closer than ever to reality. One of the main drivers for the development of MOOSE is supporting advanced nuclear reactor simulations. A challenging aspect of modeling advanced nuclear reactors is the plurality of physics involved, including neutronics, thermal hydraulics and fuel performance. These physics are all coupled to some extent and are generally solved in a sequential but iterative fashion. The United States (U.S.) national laboratories have been developing MOOSE, an open source multiphysics framework since its inception at the Idaho National Laboratory (INL) in 2008. This framework enables seamless coupling of multiphysics simulations and facilitates the implementation of new physics and material governing laws. It is continuously expanded with novel numerical methods and new pre-implemented physics module. Numerous applications, developed within the Department of Energy (DOE) laboratories, academia, and industry, including outside of nuclear engineering, have been developed to study specialized physics problems. International collaborations are welcome on this open-source modeling and simulation project.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Physics and technology considerations for the deuterium–tritium fuel cycle and conditions for tritium fuel self sufficiency

The tritium aspects of the DT fuel cycle embody some of the most challenging feasibility and attractiveness issues in the development of fusion systems. The review and analyses in this paper provide important information to understand and quantify these challenges and to define the phase space of plasma physics and fusion technology parameters and features that must guide a serious R&D in the world fusion program. We focus in particular on components, issues and R&D necessary to satisfy three 'principal requirements': (1) achieving tritium self-sufficiency within the fusion system, (2) providing a tritium inventory for the initial start-up of a fusion facility, and (3) managing the safety and biological hazards of tritium. A primary conclusion is that the physics and technology state-of-the-art will not enable DEMO and future power plants to satisfy these principal requirements. We quantify goals and define specific areas and ideas for physics and technology R&D to meet these requirements. A powerful fuel cycle dynamics model was developed to calculate time-dependent tritium inventories and flow rates in all parts and components of the fuel cycle for different ranges of parameters and physics and technology conditions. Dynamics modeling analyses show that the key parameters affecting tritium inventories, tritium start-up inventory, and tritium self-sufficiency are the tritium burn fraction in the plasma (f b ), fueling efficiency (η f ), processing time of plasma exhaust in the inner fuel cycle (t p ), reactor availability factor (AF), reserve time (tr) which determines the reserve tritium inventory needed in the storage system in order to keep the plant operational for time t r in case of any malfunction of any part of the tritium processing system, and the doubling time (t d ). Results show that η f f b > 2% and processing time of 1–4 h are required to achieve tritium self-sufficiency with reasonable confidence. For η f f b = 2% and processing time of 4 h, the tritium start-up inventory required for a 3 GW fusion reactor is ~11 kg, while it is <5 kg if η f f b = 5% and the processing time is 1 h. To achieve these stringent requirements, a serious R&D program in physics and technology is necessary. The EU-DEMO direct internal recycling concept that carries fuel directly from the plasma exhaust gas to the fueling systems without going through the isotope separation system reduces the overall processing time and tritium inventories and has positive effects on the required tritium breeding ratio (TBR R ). A significant finding is the strong dependence of tritium self-sufficiency on the reactor availability factor. Simulations show that tritium self-sufficiency is: impossible if AF < 10% for any η f f b , possible if AF > 30% and 1% ≤ η f f b ≤ 2%, and achievable with reasonable confidence if AF > 50% and η f f b > 2%. These results are of particular concern in light of the low availability factor predicted for the near-term plasma-based experimental facilities (e.g. FNSF, VNS, CTF), and can have repercussions on tritium economy in DEMO reactors as well, unless significant advancements in RAMI are made. There is a linear dependency between the tritium start-up inventory and the fusion power. The required tritium start-up inventory for a fusion facility of 100 MW fusion power is as small as 1 kg. Since fusion power plants will have large powers for better economics, it is important to maintain a 'reserve' tritium inventory in the tritium storage system to continue to fuel the plasma and avoid plant shutdown in case of malfunctions of some parts of the tritium processing lines. But our results show that a reserve time as short as 24 h leads to unacceptable reserve and start-up inventory requirements. Therefore, high reliability and fast maintainability of all components in the fuel cycle are necessary in order to avoid the need for storing reserve tritium inventory sufficient for continued fusion facility operation for more than a few hours. The physics aspects of plasma fueling, tritium burn fraction, and particle and power exhaust are highly interrelated and complex, and predictions for DEMO and power reactors are highly uncertain because of lack of experiments with burning plasma. Fueling by pellet injection on the high field side of tokamak has evolved to be the preferred method to fuel a burning plasma. Extrapolation from the DIII-D penetration scaling shows fueling efficiency expected in DEMO to be <25%, but such extrapolations are highly uncertain. The fueling efficiency of gas in a reactor relevant regime is expected to be extremely poor and not very useful for getting tritium into the core plasma efficiently. Gas fueling will nonetheless be useful for feedback control of the divertor operating parameters. Extensive modeling has been carried out to predict burn fraction, fueling requirements, and fueling efficiency for ITER, DEMO, and beyond. The fueling rate required to operate Q = 10 ITER plasmas in order to provide the required core fueling, helium exhaust and radiative divertor plasma conditions for acceptable divertor power loads was calculated. If this fueling is performed with a 50–50 DT mix, the tritium burn fraction in ITER would be ~0.36%, which is too low to satisfy the self-sufficiency conditions derived from the dynamics modeling for fusion reactors. Extrapolation to DEMO using this approach would also yield similarly low burn fraction. Extensive analysis presented shows that specific features of edge neutral dynamics in ITER and fusion reactors, which are different from present experiments, open possibilities for optimization of tritium fueling and thus to improve the burn fraction. Using only tritium in pellet fueling of the plasma core, and only deuterium for edge density, divertor power load and ELM control results in significant increase of the burn fraction to 1.8–3.6%. These estimates are performed with physics models whose results cannot be fully validated for ITER and DEMO plasma conditions since these cannot be achieved in present tokamak experiments. Thus, several uncertainties remain regarding particle transport and scenario requirements in ITER and DEMO. The safety standard requirements for protection of the public and release guidelines for tritium have been reviewed. General safety approaches including minimizing tritium inventories, reducing tritium permeation through materials, and decontaminating material for waste disposal have been suggested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The thermodynamic and kinetic interactions of He interstitial clusters with bubbles in W

Due to its enviable properties, tungsten is a leading candidate plasma facing material in nuclear fusion reactors. However, like many other metals, tungsten is known to be affected by the high doses of helium atoms incoming from the plasma. Indeed, the implanted interstitial helium atoms cluster together and, upon reaching a critical cluster size, convert into substitutional nanoscale He bubbles. These bubbles then grow by absorbing further interstitial clusters from the matrix. This process can lead to deleterious changes in microstructure, degradation of mechanical properties, and contamination of the plasma. In order to better understand the growth process, we use traditional and accelerated molecular dynamics simulations to investigate the interactions between interstitial He clusters and pre-existing bubbles. These interactions are characterized in terms of thermodynamics and kinetics. We show that the proximity of the bubble leads to an enhancement of the trap mutation rate and, consequently, to the nucleation of satellite bubbles in the neighborhood of existing ones. We also uncover a number of mechanisms that can lead to the subsequent annihilation of such satellite nanobubbles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Basic Energy Sciences Roundtable: Foundational Science to Accelerate Nuclear Energy Innovation

Energy security, availability, and reliability are among the greatest challenges facing the nation and the planet. An abundant potential source of energy resides in the fundamental atomic building blocks of the universe in the form of nuclear fission and fusion reactions. In fact, energy from nuclear fission currently provides the majority of the world’s zero-carbon electricity, and future fusion energy systems offer great promise; carbon-free nuclear energy technologies can be key to the world’s decarbonized energy future. Although contemporary fission systems use well-established technologies to supply safe and efficient baseload power, they could be more fuel efficient and less costly. Moving beyond massive light-water fission reactors to a variety of advanced nuclear systems—which will vary in size and operate in extremes of temperature, corrosivity, and other parameters—will place stringent conditions on materials and chemical systems. New demands will be placed on the coolants and solvents, the materials, and the monitoring tools used in these reactors. Fusion-based nuclear energy will require superior materials to withstand extremely high temperatures, plasma exposure, radiation damage, and implanted gases. The advantages associated with these new fission and fusion technologies will be realized only through continued advancements in the fundamental science underpinning our knowledge of the physics and chemistry of nuclear systems gained via improved experimental and computational methods. In July 2022, the U.S. Department of Energy’s Office of Basic Energy Sciences—in coordination with the Offices of Nuclear Energy, Fusion Energy Sciences, and Advanced Scientific Computing Research—held a virtual roundtable titled “Foundational Science to Accelerate Nuclear Energy Innovation” to discuss the scientific and technical barriers for advanced nuclear energy systems. Five priority research opportunities were identified to address these scientific and technical challenges and to accelerate progress toward the realization of next-generation fusion and fission energy systems. The foundational science gaps inhibiting the advancement of nuclear energy technologies are identified and tackled in five priority research opportunities. These opportunities pave the way to accelerate the development and ultimately the adoption of new nuclear energy systems. They include the fundamental aspects of ion-electron interactions; novel properties of next-generation coolants and solvents; interfacial dynamics, not only in solids, but in other aspects of nuclear reactors; novel operando and in situ monitoring and sensing; and artificial intelligence to accelerate condensed phases discovery. Building on the foundation established by previous Basic Energy Sciences workshops, these opportunities encompass recent advances in fundamental knowledge and focus on the experimental and computational methods needed to resolve major technical challenges for nuclear energy technologies. Through developing fundamental scientific insight as well as pushing the frontiers of modeling complex systems and probing the operation of materials and chemical systems in extreme environments, research motivated by the priorities identified here will further develop the promise, potential, and utilization of nuclear energy for a clean energy future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Automatic Volume Balancing for Online Refueling in Molten Salt Reactor Simulations with SCALE

This work introduces recently implemented capabilities in the SCALE code system’s TRITON reactor physics sequence that improve molten salt reactor (MSR) modeling: (1) a volume balancing option, which automatically balances the volumes of the fed material with a corresponding material removal to maintain fixed mixture volumes in the neutron transport model and accurate densities, and (2) continuous feed from mixtures, which enables users to define material feed streams directly from salt mixture definitions rather than individual nuclides. The new capabilities were demonstrated via SCALE/TRITON simulations of two representative MSR concepts. Simulations of the 180 MWth molten chloride fast reactor—a system with a fixed fuel salt volume in the reactor core—applied continuous refueling with fresh fuel salt. The results confirm approximately constant reactivity when the new volume balancing capability is used. Additionally, excellent agreement with a manual feed-and-drain method for volume balancing further verified the new implementation. Simulations of the 400 MWth EIRENE reactor, an integral MSR in which the salt volume may grow over time within the reactor core, demonstrated the capability to represent growing salt volume within the TRITON depletion calculation. Compared with reference solutions, the results show consistent trends in reactivity and isotopic evolution, confirming that these new user-friendly capabilities provide accurate, physically consistent approaches for modeling MSRs in SCALE.

Elzohery, Rabab [ORNL] (ORCID:0000000160043633)↗

Augmenting machine learning of Grad–Shafranov equilibrium reconstruction with Green's functions

This work presents a method for predicting plasma equilibria in tokamak fusion experiments and reactors. The approach involves representing the plasma current as a linear combination of basis functions using principal component analysis of plasma toroidal current densities (J t ) from the EFIT-AI equilibrium database. Then utilizing EFIT's Green's function tables, basis functions are created for the poloidal flux (ψ) and diagnostics generated from the toroidal current (J t ). Similar to the idea of a physics-informed neural network (NN), this physically enforces consistency between ψ, J t , and the synthetic diagnostics. First, the predictive capability of a least squares technique to minimize the error on the synthetic diagnostics is employed. The results show that the method achieves high accuracy in predicting ψ and moderate accuracy in predicting J t with median R 2 = 0.9993 and R 2 = 0.978, respectively. A comprehensive NN using a network architecture search is also employed to predict the coefficients of the basis functions. The NN demonstrates significantly better performance compared to the least squares method with median R 2 = 0.9997 and 0.9916 for J t and ψ, respectively. The robustness of the method is evaluated by handling missing or incorrect data through the least squares filling of missing data, which shows that the NN prediction remains strong even with a reduced number of diagnostics. Additionally, the method is tested on plasmas outside of the training range showing reasonable results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Metal ion extraction from brines

A material includes a porous particle that includes a metal ion imprinted polymer. The metal ion imprinted polymer is formed from a hydrophilic co-monomer, a metal containing polymerizable compound, and a cross-linking agent. The metal containing polymerizable compound includes at least one metal chelating ligand. The metal ion imprinted polymer includes a plurality of metal ion selective binding sites. A method includes flowing brine containing a metal ion through a reactor that includes the material. The method further includes discharging the brine from the reactor, contacting the porous particles with water, and pressurizing the reactor with carbon dioxide. The carbon dioxide reacts with the adsorbed metal ions to form a metal carbonate solution. The method further includes depressurizing the reactor to precipitate metal carbonate from the metal carbonate solution and discharging the metal carbonate solution from the reactor.

36 MATERIALS SCIENCE↗

Detailed biomass fast pyrolysis kinetics integrated to computational fluid dynamic (CFD) and discrete element modeling framework: Predicting product yields at the bench-scale

Fast pyrolysis is an intricate process due to the variability and anisotropy of lignocellulosic biomass and the complicated chemistry and physics during conversion in a bubbling fluidized bed reactor (BFBR). The complexity of biomass fast pyrolysis lends itself well to computational fluid dynamics (CFD) and discrete element (DEM) analysis, which promises to reduce experimental time and its associated cost. This work investigated switchgrass fast pyrolysis simulated by computational fluid dynamics coupled with a discrete element method to track individual reacting biomass particles throughout a bench-scale BFBR reactor. We accounted for the fast pyrolysis chemistry through a comprehensive reaction scheme with secondary cracking reactions. We performed a three-step reduction for secondary cracking reactions to convert the full cracking scheme into a reduced scheme easily incorporated into our model. We assessed the impact of operational conditions on the steady-state yields of liquid bio-oil, non-condensable gases (NCG), at 550 °C over a range of fluidization numbers (2 – 6 Umf), reported as a ratio to the minimum fluidization velocity (Umf). At steady-state, the volatile bio-oil yield had a range of 49.3–50.4 wt%. Levoglucosan was the primary volatile component present with 21 wt% of the bio-oil while water was the second largest with 20 wt%. The reduction of the secondary reaction schemes did not appreciably affect the overall yields of switchgrass pyrolysis compared to the full secondary scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗