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Angular momentum changes due to nuclear-plasma interactions on highly-excited nuclei in high energy density plasmas created at the National Ignition Facility can be measured through a change in isomer feeding following gamma emission. Here, we propose an experiment to detect these effects in 133 Xe* in exploding pusher capsules.
Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.
Designing magnets for three-dimensional plasma confinement is a key task for advancing the stellarator as a fusion reactor concept. Stellarator magnets must produce an accurate field while leaving adequate room for other components and being reasonably simple to construct and assemble. In this paper, a framework for coil design and optimization is introduced that enables the attainment of sparse magnet solutions with arbitrary restrictions on where coils may be located. The solution space is formulated as a 'wireframe' consisting of a mesh of interconnected wire segments enclosing the plasma. Two methods are developed for optimizing the current distribution on a wireframe: Regularized Constrained Least Squares, which uses a linear least-squares approach to optimize the currents in each segment, and Greedy Stellarator Coil Optimization, a fully discrete procedure in which loops of current are added to the mesh one by one to achieve the desired magnetic field on the plasma boundary. Examples are presented of solutions obtainable with each method, some of which achieve high field accuracy while obeying spatial constraints that permit easy assembly.
Surface area measurements are important for characterizing porous solids, but commonly used methods such as Brunauer–Emmett–Teller (BET) gas adsorption and computed nanotomography are lacking for certain applications such as the development of solid oxide fuel cell electrodes, which often have absolute surface areas <1 m 2 and contain nanoscale features. Presented is a novel method for the surface area determination of samples with total measurable areas of 1–1000 cm 2 with a standard deviation ± 1 cm 2 , utilizing the atomic layer deposition (ALD) of Al 2 O 3 over microstructurally complex internal porosity. The volume of alumina is then quantified using plasma spectroscopy and converted to an area using the known ALD layer thickness. Under the modest ALD reactor soak times used (8.5 s), the precursor penetration depth is found to be ~50 μm, exceeding the requirement for uniformly coating SOFC functional layers. A model system, (La 0.8 Sr 0.2 ) 0.98 MnO 3–δ /Ce 0.9 Gd 0.1 O 1.95 (LSM/GDC) scaffolds of ~2.7 m 2 g –1 , was measured using the technique and compared against the BET method, and comparable results were obtained but with 1000 times less material needed. The technique is demonstrated for measurements in two example areas of active SOFC research: exsolved (Ni, Fe) nanoparticles on an Sr(Ti, Fe, Ni)O 3–δ electrode and PrO x catalyst nanoparticles infiltrated onto LSM/GDC scaffolds. Finally, the technique may be broadly useful wherever the accurate surface area determination of small absolute quantities of porous ceramic structures on the order of 0.1–50 m 2 g –1 is sought.
The beam emission spectroscopy (BES) diagnostic is used to measure fluctuations of electron density in the edge and core of fusion plasmas, and is a key in understanding turbulence in a plasma reactor. A synthetic BES diagnostic for the turbulence simulation code XGC1 has been developed using a realistic neutral beam model and an optical system easily adaptable to different kinds of tokamaks. The beam is modeled using multiple beam energy components, each one with a fraction of the total energy and their own mass and energy (mono-energetic components). The optical system consists of a lens focusing a bundle of optical fibers and resulting in a 2D measurement. The synthetic diagnostic gives similar correlation functions and behaviour of the turbulences than the usual methods that do not take into account the full 3D optical effects. The results, based on a simulation of XGC1, contain an analysis of the correlation (in space and time), a comparison of different approximations possible and their importance in accurately modeling the BES diagnostic.
It is demanded to find key issues and critical paths for verifying and monitoring a spent nuclear fuel cask or storage with a purpose of non-proliferation of nuclear weapon. However, unfortunately there are no reliable methods to verify the containment in a spent nuclear fuel cask or storage. Therefore, research and development (R and D) has been continuously required to develop new and alternative technologies for searching and verifying undeclared nuclear materials, activities, and facilities. Therefore, the present authors have developed a new safeguards technique of passively scanning a spent fuel cask or storage using pressurized He-4 scintillation neutron detectors. A new approach is to quickly verify content in a spent nuclear fuel cask or presence of all special nuclear materials in unknown packages by comparing experimental and computational results. For that, the present authors have developed a new algorithm and user-interface coupled ORIGEN-ARP and MCNP codes, and the prototype safeguards apparatus employing the array of He-4 fast neutron detectors has been designed, built, and tested. The feasibility test of this new apparatus has been performed with Cf-252 neutron sources and the laboratory scale model cask, minimized by a factor of ten compared to the actual dimension of a KN-21 cask. This technique has several advantages over current methods based on neutron and gamma detection; (1) incident neutron energy information is preserved, (2) disturbance of gamma-ray is excellently rejected (discriminated), and (3) much higher neutron counts and operational cost and space-effectiveness are expected since no moderator is required for fast neutrons. The final goal of this study will (1) conduct a prototype instrument and employ it to monitor a nuclear spent fuel cask or storage at a commercial nuclear power reactor facilities, (2) use spectral-specific measurement data to show proof of concept for measurable data successfully converted to quantifiable signatures, such as diversion/removal of fuel, and maintenance of fuel and cask integrity of fuel, and (3) develop a cask imaging capability. (authors)
This report documents a method for the quantitative identification of radionuclides of potential interest for accident consequence analysis involving advanced nuclear reactors. Based on previous qualitative assessments of radionuclide inventories for advanced reactors coupled with the review of a radiological inventory developed for a heat pipe reactor, a 1 Ci activity airborne release was calculated for 137 radionuclides using the MACCS 4.1 code suite. Several assumptions regarding release conditions were made and discussed herein. The potential release of a heat pipe reactor inventory was also modeled following the same assumptions. Results provide an estimation of the relative EARLY and CHRONC phase dose contribution from advanced reactor radionuclides and are normalized to doses from equivalent releases of I-131 and Cs-137, respectively. Ultimately, a list of 69 radionuclides with EARLY or CHRONC dose contributions at least 1/100th that of I-131 or Cs-137, respectively – 48 of which are currently considered for LWR consequence analyses – was identified of being of potential importance for analyses involving a heat pipe reactor.
The 3 H(d, n) 4 He reaction is of significant interest in nuclear astrophysics and nuclear applications. It is an important, early step in big-bang nucleosynthesis and a key process in nuclear fusion reactors. We use one- and two-level R-matrix approximations to analyze data on the cross section for this reaction at center-of-mass energies below 215 keV. We critically examine the data sets using a Bayesian statistical model that allows for both common-mode and additional point-to-point un- certainties. We use Markov Chain Monte Carlo sampling to evaluate this R-matrix-plus-statistical model and find two-level R-matrix results that are stable with respect to variations in the channel radii. The S factor at 40 keV evaluates to 25.36(19) MeV b (68% credibility interval). We discuss our Bayesian analysis in detail and provide guidance for future applications of Bayesian methods to R-matrix analyses. We also discuss possible paths to further reduction of the S-factor uncertainty.
A method for synthesizing an In(III) N,N'-diisopropylacetamidinate precursor including cooling a mixture comprised of diisopropylcarbodiimide and diethyl ether to approximately -30.degree. C., adding methyllithium drop-wise into the mixture, allowing the mixture to warm to room temperature, adding indium(III) chloride as a solid to the mixture to produce a white solid, dissolving the white solid in pentane to form a clear and colorless solution, filtering the mixture over a celite plug, and evaporating the solution under reduced pressure to obtain a solid In(III) N,N'-diisopropylacetamidinate precursor. This precursor has been further used to develop a novel atomic layer deposition technique for indium sulfide by dosing a reactor with the precursor, purging with nitrogen, dosing with dilute hydrogen sulfide, purging again with nitrogen, and repeating these steps to increase growth.
This paper presents the first gyrokinetic (GK) simulations of edge and scrape-off layer (SOL) turbulence accelerated by a velocity-space spectral approach in the full-f GK code GENE-X. Building upon the original grid velocity-space discretization, we derive and implement a new spectral formulation and verify the numerical implementation using the method of manufactured solution. We conduct a series of spectral turbulence simulations focusing on the TCV-X21 reference case (Oliveira et al., 2022 [26]) and compare these results with previously validated grid simulations (Ulbl et al., 2023 [25]). The spectral approach reproduces the outboard midplane (OMP) profiles (density, temperature, and radial electric field), dominated by trapped electron mode (TEM) turbulence, with excellent agreement and significantly lower velocity-space resolution. As a consequence, the spectral approach reduces the computational cost (CPUh) by at least an order of magnitude, of approximately 50 for the TCV-X21 case. This enables high-fidelity GK simulations to be performed within a few days on modern CPU-based supercomputers for medium-sized devices and establishes GENE-X as a powerful tool for studying edge and SOL turbulence, moving towards reactor-relevant devices like ITER.
This assessment explores the current analysis methodologies of various external and MOOSE-based tools available at the Idaho National Laboratory to model pebble bed reactor multiphysics phenomena. The study involves three MOOSE-based, coupled codes: 1) MAMMOTH for reactor physics, 2) Rattlesnake for neutron transport and 3) Pronghorn for thermal fluids and strongly coupled conjugate heat transfer. These advanced tools are being developed under DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS). They currently contain a collection of advanced modeling capabilities that allow high-fidelity simulations of advanced reactor concepts including gas and fluoride-salt cooled pebble bed reactors. Software development of these tools follows NQA-1 standards ensuring software quality that many of the currently deployed legacy codes lack. In this work, the MAMMOTH Pronghorn tools are compared to the legacy codes PEBBED-THERMIX-KONVEK. The external codes in use are LAMMPS for pebble mechanics and Serpent for cross section preparation. The coupling under MOOSE enables significant flexibility for modern engineering tools since MOOSE applications can be seamlessly coupled with various levels of resolution. This report focuses on low-resolution (r-z) and midresolution (3-D) homogenized geometries. The high-resolution Pebble Tracking Transport solution is not pursued herein and is postponed to future work. The results from this assessment show that the new MOOSE-based tools compare well with the results from legacy tools (r-z) and produce reasonable accuracy limited by the methods in the legacy tools. In the 3-D studies, the PJFNK-SPH methodology available in MAMMOTH allows the reproduction of Monte Carlo results with a transport-corrected diffusion solution. This has implications for the coupled solutions since without the SPH correction the temperature coefficient of reactivity is under-predicted and leads to lower temperature feedback and a significantly higher eigenvalue showing a difference of 2000 pcm.
Molten salt electrochemical reduction (MSER) is the dominant production method for aluminum and titanium, and emerging technologies for producing other commodity metals with these highly electrified techniques have demonstrated promising results. However, the scale up of MSER of materials such as iron and silicon are limited by the challenging issues of materials compatibility and impurity control. This work describes an experimental MSER setup using both chloride and carbonate salts. This setup is designed for operations outside of a glovebox, which is practical from an industrial perspective, but creates unique challenges. This work serves as a practical guide to discuss some key operational difficulties such as temperature control, air and humidity, material compatibility, developing strong electrical measurements and techniques, and safety.
The mission of the Nuclear Energy Enabling Technologies (NEET) program is to develop crosscutting technologies for nuclear energy applications. Advanced structural materials with superior performance at elevated temperatures are always desired for nuclear reactors, which can improve reactor economics, safety margins, and design flexibility. They benefit not only new reactors, including advanced light water reactors (LWRs) and fast reactors such as the sodium-cooled fast reactor (SFR) that is primarily designed for management of high-level wastes, but also life extension of the existing fleet when component exchange is needed. Developing and utilizing the modern materials science tools (experimental, theoretical, and computational tools) is an important path to more efficient alloy development and process optimization. The ultimate goal of this project is, with the aid of computational modeling tools, to accelerate the development of Zr-bearing ferritic alloys that can be fabricated using conventional steelmaking methods. The new alloys are expected to have superior high-temperature creep performance and excellent radiation resistance as compared to Grade 91. The designed alloys were fabricated using arc-melting and drop-casting, followed by hot rolling and conventional heat treatments. Comprehensive experimental studies have been conducted on the developed alloys to evaluate their hardness, tensile properties, creep resistance, Charpy impact toughness, and aging resistance, as well as resistance to proton and heavy ion (Fe 2+ ) irradiation.
The control of electron energy probability functions (EEPFs) in low pressure partially ionized plasmas is typically accomplished through the format of the applied power. For example, through the use of pulse power, the EEPF can be modulated to produce shapes not possible under continuous wave excitation. This technique uses internal control. In this paper, we discuss a method for external control of EEPFs by transport of electrons between separately powered inductively coupled plasmas (ICPs). The reactor incorporates dual ICP sources (main and auxiliary) in a tandem geometry whose plasma volumes are separated by a grid. The auxiliary ICP is continuously powered while the main ICP is pulsed. Langmuir probe measurements of the EEPFs during the afterglow of the main ICP suggests that transport of hot electrons from the auxiliary plasma provided what is effectively an external source of energetic electrons. The tail of the EEPF and bulk electron temperature were then elevated in the afterglow of the main ICP by this external source of power. Results from a computer simulation for the evolution of the EEPFs concur with measured trends.
The purpose of this paper is to apply our improved method for calculating sensitivities and uncertainties of reactivity responses for UO{sub 2} and MOX fueled pressurized water reactor cells. The improved method has been used to calculate sensitivity coefficients relative to infinite dilution cross-sections, where the self-shielding effect is taken into account. Two types of reactivities are considered: Doppler reactivity and coolant void reactivity, for each type of reactivity, the sensitivities are calculated for small and large perturbations. The results have demonstrated that the reactivity responses have larger relative uncertainty than eigenvalue responses. In addition, the uncertainty of coolant void reactivity is much greater than Doppler reactivity especially for large perturbations. The sensitivity coefficients and uncertainties of both reactivities were verified by comparing with SCALE code results using ENDF/B-VII library and good agreements have been found.
Worldwide energy independence is reliant on the ability to leverage locally available resources for fuel production. Recently, syngas produced through gasification of carbonaceous materials provided a gateway to a host of processes for the production of various chemicals including transportation fuels. The basis of the production of gasoline and diesel-like fuels is the Fischer Tropsch Synthesis (FTS) process: A catalyzed chemical reaction that converts a mixture of carbon monoxide (CO) and hydrogen (H 2 ) into long chain hydrocarbons. Until now, it has been argued that only transition metal catalysts (usually Co or Fe) are active toward the CO hydrogenation and subsequent chain growth in the presence of hydrogen. In this paper, we demonstrate that carbon nanotube (CNT) surfaces are also capable of hydro-deoxygenating CO and producing long chain hydrocarbons similar to that obtained through the FTS but with orders of magnitude higher conversion efficiencies than the present state-of-the-art FTS catalysts. We have used advanced experimental tools such as XPS and microscopy techniques to characterize CNTs and identify C-O functional groups as the active sites for the enhanced catalytic activity. Furthermore, we have conducted quantum Density Functional Theory (DFT) calculations to confirm that C-O groups (inherent on CNT surfaces) could indeed be catalytically active towards reduction of CO with H 2 , and capable of sustaining chain growth. The DFT calculations have shown that the kinetically and thermodynamically feasible route for CO insertion and hydro-deoxygenation are different from that on transition metal catalysts. Experiments on a continuous flow tubular reactor with various nearly metal-free CNTs have been carried out and the products have been analyzed. CNTs functionalized by various methods were evaluated under different conditions. Reactor tests revealed that the hydrogen pre-treatment reduced the activity of the catalysts to negligible levels. Without the pretreatment, the activity for CO conversion as found to be 7 µmol CO/g CNT/s. The O-functionalized samples showed very activities greater than 85 µmol CO/g CNT/s with nearly 100% conversion. Analyses show that CO hydro-deoxygenation occurred at the C-O/O-H functional groups. It was found that while the products were similar to FT products, differences in selectivities were observed which, in turn, was a result of a different catalytic mechanism. Furthermore, these findings now open a new paradigm for CNT-based hydrogenation catalysts and constitute a defining point for obtaining clean, earth abundant, alternative fuels through the use of efficient and renewable catalyst.
Current approaches to improve the efficiency of Spark-Ignition (SI) gasoline engines have been focusing on turbocharging, increasing the compression ratio, and pursuing advanced low-temperature combustion concepts. In order to maximize these strategies, it is important to optimize the knock resistance of the fuel, and therefore knowledge of the sensitivity of the ignition process under a wide range of engine operating conditions is required. Octane sensitivity (OS), which is defined as the difference between Research Octane Number (RON) and Motored Octane Number (MON), has been introduced to represent how fuel's ignition reactivity changes relative to the primary reference fuels (n-heptane/iso-octane) within RON/MON conditions. Previous works have indicated that OS is intimately related to low temperature reactivity of the fuel, which can be revealed as two-stage heat release characteristics during an ignition event. Prompted by these findings, in this paper, we investigate the relationship between two-stage ignition behavior and OS, using chemical kinetic simulations of 24 Toluene Reference Fuels (TRFs)/ethanol blends. TRFs are ternary mixtures of n-heptane/iso-octane/toluene, which is capable of capturing aromatic content and positive values of OS of real gasoline fuels. Simulation results show that fuels with weak or no two-stage ignition behavior tend to have high OS, due to their lack of Negative Temperature Coefficient (NTC) effect and high sensitivity in ignition delay time. Leveraging such observations, we develop a correlation between two-stage behavior and OS as an OS prediction method. Two metrics that represent the strength of the two-stage ignition behavior are proposed and used as OS predictors, which are Low Temperature Heat Release percentage (LTHR%) and Heat Release Rate at the end of first stage (HRR inf ) calculated from a simple kinetic simulation. Regression analysis shows a clear trend between decreases in the proposed two-stage behavior metrics and increases in the value of OS of the fuel. We also test the new metric (LTHR%) using simulation results of 0-D reactors with imposed pressure time histories obtained from engine experiments, as well as using different TRF kinetic mechanisms. Here, the results demonstrate the effectiveness of the metric as a representation of the two-stage ignition behavior in practical combustion systems, highlighting the importance of the proposed relationship, and its potential as a simple and effective OS predictor.
We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure three-electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate ~ 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.