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The forced-convection heat-transfer characteristics of lead-bismuth eutectic were experimentally investigated. Experimental values of Nusselt number for lead-bismuth fell considerably below predicted values. The addition of a wetting agent did not change the heat transfer characteristics.
Heavy liquid metals (HLMs) are promising candidates as coolants of Generation IV fast reactors due to their thermophysical properties. In the last decade, experimental work has been proposed as part of research and development efforts to develop such systems. In this context, researchers from the Brasimone Research Center have conducted many experiments using the Natural Circulation Experiment Upgrade (NACIE-UP) facility to study the thermofluid dynamic behavior of HLMs in rod bundle configurations with or without wire wrappers. This facility consists of a rectangular loop operated with lead-bismuth eutectic. Sensors across the loop monitor relevant parameters, i.e. temperatures, heat transfer, and flow conditions. Here, in the present work, we carefully select published data from NACIE-UP to validate the System Analysis Module (SAM), a modern system analysis code developed at Argonne National Laboratory. We developed one SAM model using specifications of the facility geometry and materials existing in relevant papers and reports. On top of that, these references provided the boundary conditions for simulating natural circulation and forced convection experiments in either steady or transient conditions. The SAM model simulates five test cases with diverse operating conditions. Ultimately, the code is proven to predict temperatures and mass flow rates that closely match the experiments. The discrepancies between numerical predictions and diverse transients are limited to a few degrees Celsius, showcasing that SAM is well suited for analyzing nuclear systems relying on HLM coolants.
Here, this article describes the design and analysis of an electromagnetic level sensor for use in high-temperature liquid metal systems. The mutual inductance level sensor (MILS) described in this work was fabricated using two single-conductor mineral insulated cables wrapped in a bifilar fashion around a stainless steel tube core and was housed in an isolating thimble that preserved the pressure boundary of the test vessel. Two sensor variations were fabricated that differ only in active length, 1016 and 1778 mm. Experimental data were collected using the 1016-mm sensor (MILS-MKII-040) that demonstrated a sensitivity of 9.2 μ V/mm in a room temperature testing stand that used solid aluminum as a surrogate for liquid metal. Experimental data were collected using the 1778-mm sensor (MILS-MKII-070) that demonstrated a sensitivity of 6.9 μ V/mm in the high-temperature (300 ° C) liquid sodium environment at the mechanisms engineering test loop (METL) of Argonne National Laboratory. The sensor performance was found to be repeatable over the course of several months, with roughly ±1% deviation from nominal output. Finite element models were developed in COMSOL Multiphysics that fully describe each test setup, and the models were validated using experimental data. The validated COMSOL models were used to perform an array of analyses that examined the performance of the sensor in differing environments. Maximizing the coil diameter inside the isolating thimble was found to maximize the signal and sensitivity of the sensor. An optimal operating frequency was found near 1000 Hz using both experimental data and COMSOL. The influence of a metallic thimble surrounding the sensor and a metallic sensor core was quantified and found to be negligible at the optimal operating frequency. The sensitivity of the sensor was quantified when monitoring the level of additional liquid metals. These include lead, lead-bismuth eutectic (LBE), sodium-potassium alloy (NaK), and lithium (in addition to sodium). The sensitivities were quantified using liquid metal properties at 350 ° C and 650 ° C. The geometry of the test stand model, all material properties used in the model, and the results are presented in a manner that allows the reader can replicate the model and perform additional analyses.
The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. This report summarizes two major efforts in addressing the modeling gaps in SAM for liquid-metal-cooled fast reactor (LMFR) applications, i.e. thermal mixing and stratification phenomena in large pools and corrosion-oxidation of components in flowing lead. A new one-dimensional model for thermal mixing and stratification effects in large pools and enclosures is developed and implemented. Thermal mixing and stratification occur when fluid enters a pool at a temperature different than the bulk fluid itself, a scenario often encountered during transients in pool-type systems. These phenomena are critical for the safety of reactors, impacting phenomena like natural circulation, which is essential for passive cooling. The improved model in SAM addresses limitations of state-of-the-art approaches by combining one-dimensional (1D) channels, representing the coolant jet flow, with lumped-parameter zero-dimensional (0D) pools, representing the rest of coolant in the tank. Energy exchange between the 1D jet and the 0D pools is based on heat transfer correlations calibrated against 3D simulations. It is verified that this model can handle various flow configurations, including hot jets in colder pools, cold jets in hotter pools, and the presence of features like ceilings, free surfaces, and obstacles. Additionally, validation against experimental data demonstrates the ability of the model to capture mixing and stratification effects in a wide range of conditions. The flexibility and improved accuracy of the new model make it a valuable tool for reactor safety analysis, allowing for the simulation of different geometries encountered in advanced reactors. A system-level corrosion modeling capability is developed and implemented in SAM to support Lead Fast Reactor (LFR) development. Although the initial focus of this capability will be on LFR application, this can later be expanded to include other liquid metals such as Lead-Bismuth Eutectic (LBE) and PbLi. This report summarizes the common corrosion mitigation strategies and outlines the progress on implementing and validating a corrosion-oxidation model in SAM. Verification and validation of the corrosion-oxidation portion of the model was performed using analytical solution and measured data from samples tested in the non-isothermal pumped lead loop at IPPE Obninsk. The iron transport and corrosion/precipitation portion of the model was assessed using an analytical model and measured corrosion depths from a natural convection lead loop experiment performed at CEA. It is demonstrated that the model implemented in SAM performed well in these assessments.
Molybdenum-99 is a high-value radionuclide commonly used for medical purposes within the United States. The National Nuclear Security Administration (NNSA) seeks to reliably produce the radioisotope 99 Mo without the use of highly enriched uranium. NNSA’s Office of Material Management and Minimization (M3) provides funding and government laboratory expertise to private companies to expedite the production process domestically and currently funds designs that use low-enriched uranium or other 99 Mo production pathways. Several production designs are being explored across the industry, including uranium fission and photonuclear conversion of 100 Mo targets. Niowave Inc. seeks to produce 99 Mo via a high-energy electron accelerator that strikes a lead-bismuth eutectic target that ultimately produces a consistent neutron flux. The neutron flux then interacts in a subcritical reactor core configuration to produce fission in low-enriched or natural uranium targets. These fissionable targets are then processed to extract 99 Mo. The purpose of this work is to estimate the neutron and photon dose response across Niowave’s proposed facility for worker safety during operation. Owing to the size of the proposed Niowave facility and necessary shielding, unbiased Monte Carlo radiation transport is impractical, and variance reduction methods are required. This work focuses on the weight window variance reduction method to produce high confidence dose response results within a Monte Carlo radiation transport code. Specifically, an adjoint-informed weight window methodology was created to improve the dose response estimates for accelerator-driven subcritical reactor designs. This adjoint-informed methodology was implemented for Niowave’s proposed design and improved dose results at far-field locations across the facility. Acceptable dose rate contours for the proposed facility were generated across the facility and are presented in this work.