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The Seven Percent Critical Experiment, or 7uPCX, is a system that mimics the physics of light water nuclear reactor systems by using uranium dioxide fuel pins at an enrichment of approximately 7%. 7uPCX is often used for benchmarking and nuclear data purposes. As part of a collaboration between Lawrence Livermore National Laboratory, Los Alamos National Laboratory, Sandia National Laboratories, and the Institut de Radioprotection et de Sûreté Nucléaire, measurements were performed in support of a high-multiplication, subcritical benchmark candidate for a thermal system. The measurements were completed by making subcritical configurations using the fuel loading pattern of a well-documented configuration of the Seven Percent Critical Experiment at Sandia National Laboratories, which exists as a benchmark in the International Criticality Safety Benchmark Evaluation Project handbook. These measurements, which aimed to capture multiplications ranging from approximately 10 to 1,000, also serve as an intercomparison between both the fielded detector systems and analysis methodologies with the goal of better characterizing the detectors and their ability to capture the state of the criticality these types of systems. Los Alamos National Laboratory’s measurements for this collaboration were made with five linked helium-3 based neutron multiplicity detectors placed on the periphery of the reactor tank beyond the infinite reflector thickness of water, and four organic scintillators placed in dry-wells in-reactor near the edge of the upper fuel grid plate. This work captures the Los Alamos National Laboratory measurements, the Rossi-α and Feynman-Y results, provides an intercomparison between the results of the 3 He neutron detectors and the organic scintillators, compares to simulation where possible, and expands on future work.
Protocols play an essential role in Advance Reactor systems. A diverse set of protocols are available to these reactors. Advanced Reactors benefit from technologies that can minimize their resource utilization and costs. Evaluation frameworks are often used when assessing protocols and processes related to cryptographic security systems. The following report discusses the various characteristics associated with these protocol evaluation frameworks, and derives a novel evaluative framework.
Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.
In this work we introduce a manifold learning-based surrogate modeling framework for uncertainty quantification in high-dimensional stochastic systems. Our first goal is to perform data mining on the available simulation data to identify a set of low-dimensional (latent) descriptors that efficiently parameterize the response of the high-dimensional computational model. To this end, we employ Principal Geodesic Analysis on the Grassmann manifold of the response to identify a set of disjoint principal geodesic submanifolds, of possibly different dimension, that captures the variation in the data. Since operations on the Grassmann require the data to be concentrated, we propose an adaptive algorithm based on Riemannian K-means and the minimization of the sample Fréchet variance on the Grassmann manifold to identify “local” principal geodesic submanifolds that represent different system behavior across the parameter space. Polynomial chaos expansion is then used to construct a mapping between the random input parameters and the projection of the response on these local principal geodesic submanifolds. Here, the method is demonstrated on four test cases, a toy-example that involves points on a hypersphere, a Lotka-Volterra dynamical system, a continuous-flow stirred-tank chemical reactor system, and a two-dimensional Rayleigh-Bénard convection problem.
Noncontact pressure generating pump seals for heat space-power systems noting types, characteristics and use in Snap 8 reactor system
Irradiation system for experiments with Plum Brook Reactor in nuclear rocket program, noting cryogenic system, dynamic testing, etc
Ensuring the efficient removal of decay heat from the reactor vessel is essential for the safety of advanced reactor technologies. Several Generation-IV concepts incorporate variations in the reactor vessel cooling systems to achieve this objective. High-temperature gas-cooled reactors utilize a reactor cavity cooling system (RCCS), a passive ex-vessel system designed to operate without active components or external power during accident conditions. The RCCS removes decay heat primarily through radiative and convective heat transfer mechanisms. Here, this study presents a comprehensive validation of a computational fluid dynamics Reynolds-averaged Navier-Stokes model for the University of Wisconsin-Madison air-cooled RCCS facility. Validation was conducted for both high- and low-power natural convection cases under a uniform heating profile. Near-wall resolution was found to be critical for accurately modeling natural convection in the RCCS; employing an all-𝑦 + wall treatment resulted in wall temperature discrepancies exceeding 50 °𝐶 compared to a wall-resolved mesh. Thermal-hydraulic behaviors under natural and forced convection conditions were compared within the heated cavity and RCCS. A turbulence model sensitivity analysis indicated that low-Reynolds number k-ɛ, k-ω shear stress transport (SST), and Reynolds stress transport models produce similar wall temperature predictions. A buoyancy modeling sensitivity study revealed that the Boussinesq approximation significantly underpredicted thermal-hydraulic behavior in the RCCS. Based on these findings, modeling recommendations are provided. The validated data set along with identified sensitivities refine the modeling of natural convection in the RCCS. The information produced by this study supports RCCS design, optimization, and safety evaluations, enabling the calibration and verification of reduced-order thermal-hydraulic models.
The results of this testing indicate that the agitated low-temperature plasma reactor system successfully converted carbon, hydrogen, and nitrogen into gaseous products at residence times that were about ten times shorter than those achieved by stationary processing. The inorganic matrix present was virtually unchanged by the processing technique. It was concluded that this processing technique is feasible for use as part of a close-looped processing resource management system.
Pseudomonads were adapted to grow in phosphate-buffered water and on stainless steel surfaces to study the iodine sensitivity of attached and planktonic cells. Cultures adapted to low nutrient growth were incubated at room temperature in a circulating reactor system with stainless steel coupons to allow biofilm formation on the metal surfaces. In some experiments, the reactor was partially emptied and refilled with buffer at each sampling time to simulate a "fill-and-draw" water system. Biofilms of attached bacteria, resuspended biofilm bacteria, and reactor suspension, were exposed to 1 mg l-1 iodine for 2 min. Attached bacterial populations which established on coupons within 3 to 5 days displayed a significant increase in resistance to iodine. Increased resistance was also observed for resuspended cells from the biofilm and planktonic bacteria in the system suspension. Generally, intact biofilms and resuspended biofilm cells were most resistant, followed by planktonic bacteria and phosphate buffer cultures. Thus, biofilm formation on stainless steel surfaces within water systems can result in significantly increased disinfection resistance of commonly-occurring water-borne bacteria that may enhance their ability to colonise water treatment and distribution systems.
Gas core reactors and MHD generator to solve problems of growing demand for electric power without thermal pollution
Additively manufactured methanol conversion reactor was designed and fabricated for high throughput fuel production while capturing carbon dioxide. Here, the reactor designed is part of large effort in integrating electrolyzer and catalytic reactor system. Processing in fabricating the steel, titanium, and nickel alloy reactors were optimized to improve the catalyst deposition process and reaction efficiency. Microstructure of the additively manufactured reactors were characterized. General design is utilized to improve the performance of the reactor while exploring the benefit of freeform in additive manufacturing.
Eden Radioisotopes, LLC is developing a TRIGA* -sized, 2 MW all-target reactor system licensed from Sandia National Laboratories. This all-target reactor uses up to 60 Argonne-designed annular LEU-foil targets to produce fission-produced 99 Mo. The Eden low-enriched uranium (LEU) target contains ~137 g of uranium and will be irradiated at up to 30 kW, with a target burnup determined by the number of targets processed each week. The annular target utilizes metallic uranium foils 400 mm long by 72 mm wide by 250±25 -µm-thick covered by a thin (10 µm on each face) nickel fission barrier. The foil is placed between two 35 mil aluminum tubes that form the outer and inner walls of the cladding cylinder, which is hydroformed to provide high thermal conductivity within the target. Eden expects to process between three and five targets per process batch, to maintain the process batch 99 Mo inventory at or below 5000 curies to maintain high 99 Mo recovery, within a few hours of discharge from the reactor. Eden expects to meet full U.S. demand by processing 30 targets per week, with each target operated for two weeks at 30 kW. To meet less than full U.S. demand, both the target power and the number of targets processed weekly will be adjusted. With increased 99 Mo production and given the size of U targets processed in a single batch (up to ~750g-U), it is important to identify whether any modifications are needed to the LEU-modified Cintichem process.
Liquid-fueled molten salt fast reactors and nuclear-powered integrated energy systems (IESs) have the potential to play a pivotal role in the green energy transition. However, these systems have little to no operating experience. There is therefore increased interest and value in modeling and simulating these systems. The IES dynamic model developed in this work utilizes a lumped-parameter control volume methodology to investigate the behavior of the IES in a variety of accident scenarios. The results provide initial evidence for the potential inherent safety of the advanced reactor because of temperature-dependent reactivity feedback and the efficiency of hydrogen and electricity production at the high temperatures provided by the advanced reactor.
The project formulates a technical basis for, and preliminary development of, a Nearly Autonomous Management and Control (NAMAC) system in advanced reactors. The system is intended to provide recommendations to operators during plant operation. The NAMAC system utilizes simulation-informed, data/knowledge-driven, AI-guided, plant-data-assimilated real-time operating procedures to effectively support the operator in risk-informed management of plant operations.
Chemical looping combustion research has been a topic of great interest since the mid-1990s, although the concept can be traced much further back. It is a combustion technology for fuel utilization that uses a two-reactor system to produce a carbon free effluent stream from the air reactor and a carbon dioxide rich stream from the fuel reactor with oxygen shuttled between the reactors with an oxygen carrier. Chemical looping combustion has been studied extensively because of this inherent separation of the carbon dioxide combustion product from the atmospheric nitrogen over that past 25 years with hundreds of research papers and tens of books. The oxygen carrier is, in general, a solid such as naturally occurring hematite or an engineered carrier like a copper and iron oxide supported on alumina. System technical and economic research activities conducted at the National Energy Technology Laboratory have shown that the costs associated with the carrier, initial and replacement, are a significant factor in the economic viability of the technology. To overcome this economic challenge, the work reported on in this paper investigates the use of a waste iron oxide as the chemical looping oxygen carrier. This waste material is quite unique as it has a particle size of 0.7 um. Given the particle size, the reactions are quite fast. However, the development of a contactor reactor to mix the fuel with the carrier is a fluidization challenge as the material is a Geldart group C material and highly cohesive. Normally, Geldart group C materials are fluidized with either a vibrating bed. This technique is acceptable for low temperature pharmaceuticals production but does not lend itself to much larger reactors used for power production or operation at temperatures in the order of 1100 to 1200 C. Therefore, a hydrodynamic solution was needed to break up the cohesive structures to replace the vibration. In this instance, it was hypothesized that a spouting bed of large Geldart group B or Geldart group D particles could provide the necessary energy to break up the cohesive structures of the Geldart group C material. This paper presents the reduction performance for this novel carrier material in a laboratory spouting bed reactor.
The System Analysis Module (SAM) is under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report summarizes major progress in SAM code development, capability enhancements, demonstration, and validation to support transient safety analysis of advanced non-LWRs. Rapid developments continued in fiscal year 2020 (FY20) to support various needs of the advanced reactor community, especially the NRC and industry on the licensing safety analysis of advanced reactor designs. Significant code changes were made to provide various capability enhancements, bug fixes, and user friendliness improvements. Major code updates are summarized in Section 1, while four important enhancements are detailed in Sections 2-5, including a multi-dimension flow model; reactivity feedback and decay heat models; control and trip system modeling, and additional fluid and solid thermophysical property models. Code validation activities in FY20 include using test data from the Fast Flux Test Facility (FFTF), the High Temperature Test Facility (HTTF), and several separate effects test facilities for pebble-bed modeling.
An integration study was performed by Rocketdyne under contract to NASA-LeRC. The study was concerned with coupling an SP-0100 reactor to either a Brayton or Stirling power conversion system. The application was for a surface power system to supply power requirements to a lunar base. A power level of 550 kWe was selected based on the NASA Space Exploration Initiative 90-day study. Reliability studies were initially performed to determine optimum power conversion redundancy. This study resulted in selecting three operating engines and one stand-by unit. Integration design studies indicated that either the Brayton or Stirling power conversion systems could be integrated with the PS-100 reactor. The Stirling system had an integration advantage because of smaller piping size and fewer components. The Stirling engine, however, is more complex and heavier than the Brayton rotating unit, which tends to off-set the Stirling integration advantage. From a performance consideration, the Brayton had a 9 percent mass advantage, and the Stirling had a 50 percent radiator advantage.