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At least 1,099 records · Page 61

DC Modeling of 4H-SiC nJFET Gate Length Reduction at 500°C

The development of robust, high-performance integrated circuits (ICs) will enable numerous potential NASA missions of current interest, including long-duration robotic missions exploring the 460°C surface of Venus. Currently, NASA is looking towards SiC-based devices to provide such a solution. However, the current NASA silicon carbide (SiC) JFET device with a channel length of 6 μm (recently fabricated Gen. 11 ICs) limits mission-relevant circuit capabilities. In this study, we combined experiments with simulations to explore two straightforward fabrication strategies (shallow n− and deep n+) to reduce the SiC JFET channel length while maintaining turn-off behavior needed to realize 500 °C circuit operation. First, the material properties for 4H-SiC were implemented in COMSOL and the Poisson equation was solved for twelve 2D device designs. Then, based on the insights gained from the distribution of the electron concentration, electrostatic potential, and electric field for twelve designs (with three fabrication strategies), simulation for a 1 μm gate length nJFET with the turn-off performance comparable to the state-of-the-art.

4H-SiC nJFET↗

Development of SAM Code Capabilities for Safety Analysis of GCR Air-ingress Events

Air-ingress following a depressurized loss-of-forced-cooling (DLOFC) event is a challenging, multiphysics safety scenario for High-Temperature Gas-Cooled Reactors (HTGRs), involving coupled gas composition transport, buoyancy-driven flow redistribution, graphite oxidation, and structural heat-up. Despite its importance — air ingress is a key scenario identified in the PIRT process for the HTGRs — existing system-level safety codes have lacked the integrated capability to simulate the complete event sequence with high confidence. This report documents the development, validation, and demonstration of three new capabilities in the SAM code to address this gap: (1) a multi-component gas mixture flow model with binary diffusion to track the helium-air composition and its effect on system density and flow; (2) a 0-D graphite oxidation model based on the Roes correlation, including oxygen consumption and exothermic heat release; and (3) an isentropic critical flow model for accurate representation of primary system depressurization through a break. These capabilities are validated against two benchmark experiments. The NSTF heavy-gas ingress experiment validates the multi-component flow model: SAM correctly reproduces the rapid buoyancydriven flow stagnation and subsequent natural circulation recovery driven by composition-dependent density changes. The NACOK graphite oxidation experiment validates the oxidation model: SAM predicts a bottom-level graphite weight loss of 25%, in close agreement with the measured 24%, and reproduces the strong axial nonuniformity and block-geometry dependence of oxidation, at a level comparable to the SPECTRA and TINTE codes. The validated capabilities are then exercised together in an integrated, reactor-scale simulation of a DLOFC air-ingress transient in a simplified HTR-PM pebble-bed reactor. In a single calculation spanning approximately 8 days, SAM reproduces the complete accident sequence: rapid depressurization, densityand diffusion-driven air ingress over ˜15 hours, onset of buoyancy-driven natural circulation, exothermic graphite oxidation with a peak fuel temperature at ˜62 hours, and eventual passive cooldown. These results demonstrate that SAM now provides the nuclear community with a preliminarily validated, modern systemlevel tool for HTGR air-ingress safety analysis, filling a recognized capability gap. Future extensions to broaden species tracking, improve oxidation chemistry, and refine the reactor model are discussed.

Yang, Gang↗

Uncertainty Quantification and Sensitivity Analysis for Coupled VERA-CS and FRAPCON

The current nuclear power plant fleet in the U.S. is facing numerous challenges economically ranging from low natural gas price to the rapidly growing renewable energy sources such as wind and solar power. In order for the nuclear industry to keep the viability of its operating fleet, new innovations have to be introduced to lower the costs to operate the fleet. One area that could contribute to the cost reduction is to lower the fuel cycle cost and improve the plant safety through initiatives such as higher burnup fuel and accident tolerant fuel. At the same time, the nuclear industry has to address future challenges on the horizon such as load following and other flexible operating strategies as well as those associated with new regulations such as 10 CFR 50.69 and 10 CFR50.46c etc. All these require coupled analysis of core neutronics, thermal hydraulics and fuel performance, which necessitates the development of a multi-physics toolkit. Since different models, assumptions, and fidelities have gone into various computer codes, how to consistently propagate uncertainties in a multi-physics environment warrants careful evaluation. The U.S. DOE's Light Water Reactor Sustainability (LWRS) Program initiated a project to develop analytical capabilities to support the industry to address these challenges. The general idea behind the initiative was the development of an integrated multiphysics evaluation model. This integrated evaluation model is called LOTUS which stands for LOCA Toolkit for the U.S. Light Water Reactors. The focus of LOTUS is to establish the automation of the interface between the five disciplines. LOTUS framework ensures that uncertainties can be easily propagated to solve the problems forward and backward (inverse) with large numbers of simulations. The objective of this work is to perform uncertainty quantification (UQ) and sensitivity analysis (SA) on a coupling of CASL's Virtual Environment for Reactor Applications-Core Simulator (VERA-CS) and NRC's fuel performance code FRAPCON. The work presented herein is a subset of the overall LOTUS framework. The figures of merit (FOM) selected for analysis are minimum departure from nucleate boiling ratio (MDNBR), maximum fuel centerline temperature (MFCT), and the gap conductance at peak power (GCPP). All FOM are obtained at the end of the of a depletion case for a half cycle lasting 263 days. The minimum is taken over all spatial location for each pin at the end of the half cycle. This value is calculated in VERACS alone and has been analyzed in previous work by Brown and Zhang. The MFCT is available in both VERA-CS and FRAPCON, but is calculated via different methods (see Model Inconsistencies section for more details). For this work, only the FRAPCON values are reported due to the code's maturity from extensive validation in fuel performance. Previous work includes SA on a standalone nuclear fuel performance code VTT-modified FRAPCON- 3.4 by Ikonen. The GCPP is the gap conductance at the location corresponding to maximum power in the fuel rod. This value is available in FRAPCON alone and highlights the capability of LOTUS to obtain unique fuel performance metrics for each pin in a core simulation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DC Modeling of 4H-SiC nJFET Gate Length Reduction at 500°C

The development of robust, high-performance integrated circuits (ICs) will enable numerous potential NASA missions of current interest, including long-duration robotic missions exploring the 460°C surface of Venus. Currently, NASA is looking towards SiC-based devices to provide such a solution. However, the current NASA silicon carbide (SiC) JFET device with a channel length of 6 μm (recently fabricated Gen. 11 ICs) limits mission-relevant circuit capabilities. In this study, we combined experiments with simulations to explore two straightforward fabrication strategies (shallow n− and deep n+) to reduce the SiC JFET channel length while maintaining turn-off behavior needed to realize 500 °C circuit operation. First, the material properties for 4H-SiC were implemented in COMSOL and the Poisson equation was solved for twelve 2D device designs. Then, based on the insights gained from the distribution of the electron concentration, electrostatic potential, and electric field for twelve designs (with three fabrication strategies), simulation for a 1 μm gate length nJFET with the turn-off performance comparable to the state-of-the-art.

4H-SiC nJFET↗

(Invited) Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO 2 R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. We specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

42 ENGINEERING↗

Transient and Steady-State Inverse Problems in Sierra/Aria

Inverse problems arise in a wide range of applications, whenever unknown model parameters cannot be measured directly. Instead, the unknown parameters are estimated using experimental data and forward simulations. Thermal inverse problems, such as material characterization problems, are often large-scale and transient. Therefore, they require intrusive adjoint-based gradient implementations in order to be solved efficiently. The capability to solve large-scale transient thermal inverse problems using an adjoint-based approach was recently implemented in SNL Sierra Mechanics, a massively parallel capable multiphysics code suite. This report outlines the theory, optimization formulation, and path taken to implement thermal inverse capabilities in Sierra within a unit test framework. The capability utilizes Sierra/Aria and Sierra/Fuego data structures, the Rapid Optimization Library, and an interface to the Sierra/InverseOpt library. The existing Sierra/Aria time integrator is leveraged to implement a time-dependent adjoint solver.

97 MATHEMATICS AND COMPUTING↗

Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO2R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. Here, we specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Mechanics Support to National Highway Traffic Safety Administration (NHTSA), Progress Report, August 2012

The Transportation Research and Analysis Computing Center (TRACC) with the National Highway Safety Administration (NHTSA) Vehicle Safety Research has established an interagency agreement between the U.S. Department of Transportation and the U.S Department of Energy to provide assistance to NHTSA’s ongoing projects. The work will be performed in FY 2013 by the Transportation Research and Analysis Computing Center at Argonne National Laboratory. The project will be performed under the “Work for Others” (WFO) clause of the prime contract between the operator of Argonne National Laboratory (UChicago Argonne LLC) and the U.S Department of Energy. For the past five years, NHTSA has been using TRACC’s HPC computer and participating in computational structural mechanics training classes. NHTSA mainly used the LS-DYNA software package including: LS-DYNA (multiphysics solvers), LS-OPT (optimization tool) and LS-PrePost (pre- and post-processing tool). NHTSA crash analysis researchers were early users of the TRACC cluster and have become the most active users of TRACC’s 500 core LS-DYNA software license. The large core-license-pool allows NHTSA to minimize the time needed to obtain simulation results and, thus, expand modeling variations that must be considered to ensure credible treatment of crash events while meeting critical project deadlines. The purposes of this project are (1) to enhance future cooperation between NHTSA and TRACC and (2) to secure NHTSA’s access to TRACC’s high performance cluster, LS-DYNA and TRACC’s staff expertise.

Ley, H.↗

Meshfree Multiphysics Damage Modeling of Li-ion Battery Materials

Through repeated charging and discharging cycles, the electrodes of a Li-ion battery experience significant swelling and contraction due to the movement of lithium, also known as intercalation. This research focuses specifically on the chemo-mechanical cracking in the cathode. Because cathode particles are comprised of many randomly-oriented grains, which have highly anisotropic material properties, the expansion and contraction is very non-uniform. As a result, stress concentrations tend to form between grains, which necessitates the modeling of crack propagation largely along grain boundaries and material interfaces. Chemo-mechanical damage models are generally simulated by one of two methods: the cohesive zone model (CZM) and the continuous damage model (CDM). The CZM is more accurate at capturing the sharp discontinuities of a crack but is very computationally expensive and intractable for large-scale models as a result. Conversely, the CDM is easily computed but not well-suited to easily allow for discontinuous field variables, which are inherent across a crack. This study aims to improve the CDM's ability to capture discontinuous cracks. Current versions of the CDM use the finite element method (FEM), which is one of the most widely used approaches for spatial discretization. This research investigates the use of the Reproducing Kernel Particle Method (RKPM), a meshfree method, for spatial discretization and aims to achieve a coupled chemo-mechanical crack propagation model that enhances accuracy while maintaining high computational efficiency. This model features a fully coupled, iterative electrochemistry solution, which informs the meshfree damage model of impending crack formation. To gain a better understanding of how the meshfree model compares to the current FEM model in capturing cathode crack propagation, further investigation is needed.

damage modeling↗

Demonstration of a new unstructured mesh IMC x-ray transport capability in LAP codes

In this document, the Advanced Simulation and Computing (ASC) Transport Project’s Jayenne team presents evidence that the Los Alamos National Laboratory (LANL) Level 2 milestone statement, Demonstrate a new unstructured mesh IMC x-ray transport capability in LAP codes, due Q4 FY20, has been satisfied with the release and integration of the Jayenne team’s Implicit Monte Carlo (IMC) solver libraries into the lumos multiphysics solver. The Jayenne project’s software includes the algorithms and features prescribed by the milestone description. The lumos software is maintained by the Lagrangian Applications Project (LAP) along with the hydrodynamics code flag and operates under the same ASC program as Jayenne. A set of demonstration problems has been specified, executed, and analyzed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗

A Fundamentally New Coupled Approach to Contact Mechanics via the Dirichlet‐Neumann Schwarz Alternating Method

Contact phenomena are crucial for understanding the behavior of mechanical systems. However, existing computational approaches for simulating mechanical contact often face numerical challenges, such as inaccurate physical predictions, energy conservation errors, and unwanted oscillations. Here, we introduce an alternative technique for simulating dynamic contact based on the non‐overlapping Schwarz alternating method, originally developed for domain decomposition. In multibody contact scenarios, this method treats each body as a separate, non‐overlapping domain and prevents interpenetration using an alternating Dirichlet–Neumann iterative process. This approach has a strong theoretical foundation, eliminates the need for contact constraints, and offers flexibility, making it ideal for multiscale and multiphysics applications. We conducted a numerical comparison between the Schwarz method and traditional methods, such as the Lagrange multiplier and penalty methods, focusing on a benchmark impact problem. Our results indicate that the Schwarz alternating method outperforms traditional methods in several key areas: it provides more accurate predictions for various measurable quantities and demonstrates exceptional energy conservation capabilities. To address unwanted oscillations in contact velocities and forces, we explored various algorithms and stabilization techniques, ultimately opting for the naïve‐stabilized Newmark scheme for its simplicity and effectiveness. Additionally, we validated the efficiency of the Schwarz method in a three‐dimensional impact problem, highlighting its inherent capacity to accommodate different mesh topologies, time‐integration schemes, and time steps for each interacting body.

Schwarz alternating method↗

Serpent and MCNP Calculations of the Energy Deposition in the Transformational Challenge Reactor

This paper focuses on the calculation of the energy deposition in the Transformational Challenge Reactor by two major Monte Carlo codes: Serpent and MCNP. The first software computation relies on Kinetic Energy Released per unit Mass (KERMA) factors while the second one relies on Q-values. The results from these two independent computation methodologies are in very good agreement; however, Serpent runs much faster than MCNP (for the same computational model) and allows for a detailed energy deposition distribution from a 1-mm-side square mesh with a relative statistical error between 0.5% and 1%. This detailed energy deposition is suitable for multiphysics analyses aimed at design optimizations. In order to calculate the energy deposition, Serpent needs enhanced ACE files (distributed by the software developers). Unlike other Monte Carlo software that uses inputs based on Python or Java languages, the Serpent input syntax is very similar to that of MCNP; a Python script can convert a MCNP input to a Serpent input in seconds. For simulations not requiring the calculation of the energy deposition, Serpent can also read nuclear data from MCNP ACE files, which eventually improves the comparison of the results of the two codes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Experimental and numerical study on the impacts of various long carbon fiber inserts on the thermal performance of phase change materials

In thermal energy storage systems, phase change materials (PCMs) are widely used to provide efficient storing and extraction of thermal energy. However, most PCMs have low thermal conductivities, which limit the heat transfer of the latent energy inward/outward. In this study, the impacts of various fiber inserts on the solidification and melting processes with PCM were investigated by experiments and simulations. It was found that long anisotropic carbon fibers with high thermal conductivities can not only increase the heat transfer within PCM by enlarging hot-cold interface areas, but also act as crystallization nuclei and increase the solidification of PCM during the charging process. Recalescence of PCM during solidification was observed. COMSOL models were used to understand the thermal transfer mechanisms. COMSOL Multiphysics models of a single carbon fiber filament in PCM showed that the anisotropy in thermal conductivities controlled the radial and axial heat transfer ratios along its fiber axis and can enhance both the solidification and melting processes.

Zhou, Xinzhang↗

Image-Based Digital Twin for Assessing the Coupled Electro-Chemo-Mechanical Behavior of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The discrete nature of the images' pixel points is employed throughout the model and approximation construction. The mechanical model is verified using an image-based microstructure under tensile loading. A transient electro-chemo-mechanical coupled simulation is performed to evaluate the potential micro-cracking induced degradation of the battery cathode material subjected to charge/discharge cycling.

battery degradation↗

Effect of Laser-Matter Interaction on Molten Pool Flow and Keyhole Dynamics

Laser-induced keyholing occurs in additive manufacturing and welding processes, but the keyhole dynamics have not been well understood. A multiphase and multiphysics numerical model is used to predict the keyhole shapes recorded in the experimental observations and to predict transient and nonuniform distributions of laser absorption, temperature, and flow velocity in the process. When compared against data from a state-of-the-art dynamic x-ray radiography technique, good agreement is found for the keyhole shapes and fluctuation of the gas-liquid interface, thereby validating the simulation method. A detailed discussion is then given to elucidate the effects of laser absorption on the dynamic behavior of the front and rear keyhole walls. In conclusion, a quantitative comparison of different driving forces on the keyhole is also given to evaluate their significance to the keyhole dynamics.

42 ENGINEERING↗

INL Poster - Juan Barrera Salazar

Generation IV nuclear reactors introduce several advantages and benefits in terms of safety and efficiency when compared with their predecessors from previous generation. This is due, among many things, to the use of innovative forms of fuel and coolant, different from the conventional ones used in the last decades. Given that these upcoming designs utilize emerging technologies, the related instrumentation is also in the process of being developed; therefore, it is necessary to establish the sensitivity requirements and the effects of uncertainty on different properties of the components and elements of the reactor designs. This report presents the results of simulations that quantify the impacts of the uncertainties of four thermophysical properties of the refrigerant salt (LiF-BeF2) for the Kairos Power benchmark model (g-FHR) for steady state making use of the Sobol’ method through polynomial chaos surrogate modeling. The properties of the salt to which uncertainty was evaluated were density, dynamic viscosity, thermal conductivity and heat capacity. This study was carried out using the Griffin/Pronghorn multiphysics model under the computational resources of the Idaho National Laboratory (INL) High Performance Computing (HPC). The results indicate a weak dependence of the uncertainty of thermal conductivity on the quantities of core pressure drop and core outlet temperature.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

The Influence of Environment on Post-Detonation Chemistry and Debris Formation (Abbreviated Final Report: 20-SI-006)

Predicting, responding to, or interpreting the chemical record preserved in debris derived from nuclear events can be challenging due to chemical fractionation. Chemical fractionation is where different species of the evolving radionuclide inventory segregate and/or are lost from the system over the timescales of debris formation. Both historic data and recent research suggest that the interaction and character of the local environment may exert controls on chemical fractionation by influencing the cooling and evolution of the associated fireball as well as the composition of the vapor term and resultant speciation. Prior to this work, an integrated platform permitting dynamic and concurrent consideration of physical and chemical evolution of early time post-detonation event environments did not exist. Our work merged historic data and experimental approaches to support development of a computational framework able to simulate fundamental processes (e.g., entrainment of local environment, oxidation chemistry, and cooling time scales) that may perturb the radionuclide inventory captured in post-detonation debris. Work with historic debris confirmed that entrained environmental material affect debris composition, structure, and radionuclide incorporation. Complementary work utilizing a readily controllable and tunable benchtop setup (a plasma flow reactor) simulated the late cooling of a nuclear fireball (e.g., T < 6000 K) and bounded the sensitivity of actinide speciation and particle size distribution to variations in oxygen concentration and cooling rates. Concurrent laser ablation and laser heating experiments were used to investigate the chemistry and physics of processes occurring in vaporized and/or rapidly heated actinides and other elements in the presence of oxygen. A more computationally efficient microphysical model was developed for predicting and evolving size distributions of particles forming from mixed vapor terms and simulating particle formation processes under a variety of extreme conditions. Continued study of historic nuclear event film confirmed that shockwave data and physics codes agree to within the uncertainty of the data. Good agreement was achieved for thermal emission from an airburst, however the paucity of low-temperature molecular opacity data for mixtures of air, bomb debris, entrained dirt, and water vapor complicate agreement for more elaborate scenarios. A multiphysics code (ALE3D) was modified to bring the necessary physics and chemistry, including these new data and insights, onto a single platform. Code development included improved initialization of large physical systems, modernization of chemistry capabilities, and modifications to enable inclusion of particle transport.

07 ISOTOPE AND RADIATION SOURCES↗