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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multi-objective automatic discovery of optimized metamaterials for varying velocity impact protection

Mechanical metamaterials have demonstrated exceptional impact performance while remaining lightweight. Impact resistance has traditionally been investigated using quasi-static simulations, often with the assumption that performance will translate to high-velocity impact scenarios. However, critical crash protection parameters—such as peak stress and absorbed energy—are highly sensitive to impact velocity, leading to inconsistent performance under dynamic loading. To address this, we introduce a strain-rate-aware, active deep learning framework that enables multi-objective optimization of impact protection metrics across a wide range of impact velocities. Our framework captures the strain-rate sensitivity of architected lattices by learning to control spatial gradation in cellular metamaterials, resulting in over 200 % enhancement in impact protection relative to state-of-the-art designs such as Voronoi and re-entrant lattices. We demonstrate its practical utility by designing next-generation lattice structures for automotive bumper systems that satisfy multiple, velocity-specific safety criteria—capabilities beyond those of conventional designs. More than just a predictive tool, this framework marks the first step towards enabling adaptable impact-resistant structures across dynamic regimes.

Deep learning↗
DOE OSTI2025

Alfvén mode spectrum in the advanced steady-state tokamak scenario with negative triangularity

In the earlier studies [Zheng et al. Fundam. Plasma Phys. 10, 100051 (2024)], the negative triangularity tokamak was shown to have a unique and outstanding feature for the steady-state confinement. In addition to relieving the divertor heat load concern, it can reach a much higher beta limit in the nearly steady-state confinement, about twice the Troyon limit in the positive triangularity case. In this work, we extend the investigation to the Alfvén spectrum and toroidal Alfvén eigenmodes (TAEs). This helps to evaluate the property of energetic particle confinement in this advanced scenario of a negative triangularity tokamak. We found that, because of the large safety factor and reversed magnetic shear in the core plasma region near the magnetic axis, the TAE gap tends to be closed or have only a short radial extension between the continua. in the on-axis core region and open primarily in the off-axis region, where TAEs are shown to be present. This indicates that energetic particle confinement in the core region near the magnetic axis, where nuclear fusion reactions prevail, is not seriously affected by the excitation of TAEs in this scenario. The configuration with off-axis TAEs helps the confinement of energetic particles as compared to the configuration with near-axis TAEs. The results show that the advanced steady-state tokamak scenario with negative triangularity, because of the rapid variation of the safety factor, also has a favorable feature for energetic particle confinement.

Fourier analysis↗
DOE OSTI2024

Analysis of AP1000 Small-Break Loss-of-Coolant Accident Using Reactor Transient Simulator

The Westinghouse Electric Company’s Advanced Passive Reactor (AP1000) is characterized by the incorporation of passive safety systems (PSSs) designed to ensure core cooling during transient events. The assessment of PSSs requires evaluation of their performance through a combination of experiments and simulations employing various thermal-hydraulic codes. In addition, detailed evaluation of PSSs for a specific reactor system transient analysis such as loss-of-coolant-accident analysis supports understanding representative integral effects test facility development and the further evolution model development and assessment process. Developing a reactor system code is a complex and time-consuming process that requires significant engineering expertise and effort. It can take several months to even years to complete in the early stages of reactor system design and analysis. However, this process can be expedited through the use of transient simulator models for similar reactor systems, which can be used for lesson learning and training purposes. This study uses the Personal Computer Transient Analyzer (PCTRAN) code. The main advantage of PCTRAN is its ease of use and ability to run faster than real time. This study presents the results obtained for a small-break loss-of-coolant accident (SBLOCA) for two breaks using the full version (licensed) of PCTRAN. The purpose of this investigation is to evaluate the overall system behavior during the postulated SBLOCA event as well as assess the capability of the PCTRAN code to reproduce the system response during transient events. The obtained results were compared with the Westinghouse NOTRUMP system code. The PCTRAN code proved to be reliable in predicting the qualitative behavior of the system in both transient cases. As for the system response, it was found that it is contingent on the activation time of the PSSs. The differences in reactor coolant system pressure between the two codes were attributed to the critical flow model and simplification of mass and energy balance. Despite PCTRAN’s limitations, it can still provide a reasonable prediction of various reactor parameters such as pressure, mass flow rate, and void fraction during a SBLOCA scenario. It is worth noting that PCTRAN currently employs a bulk approach similar to that of the Modular Accident Analysis Program (MAAP) and MELCOR codes. However, the upcoming version of PCTRAN will include an artificial intelligence–based detection and accident prevention system, as well as different models for different reactor components. Consequently, PCTRAN has the potential to be upgraded to match the system thermal-hydraulic codes of the U.S. Nuclear Regulatory Commission and become more widely used in cybersecurity to safeguard nuclear power plants from cyberattacks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

On the hot surface ignition of a wall-stagnating spray flame

The ignition of fuel sprays due to interaction with hot surfaces is an important phenomenon in the safety analysis of many engineering systems. We perform a parametric study of the hot surface ignition (HSI) of a fuel spray approaching a heated surface caused by the accidental leakage of a fuel line. Here, to this end, we employ a one-dimensional Eulerian-Eulerian formulation with a non-equilibrium evaporation model and a realistic chemical mechanism to describe $n$-dodecane fuel chemistry. We first describe and analyze the phenomenology of the unsteady processes leading to ignition using non-dimensionalized quantities. Through consideration of the temporal development of the most reactive mixture, we demonstrate that ignition occurs at a fuel-lean composition in a premixed region near the hot surface. Using non-dimensional parameters identified from the governing equations, we perform a parametric study of the time, location and local mixture composition at ignition and determine the ignition limits. We then identify the most important parametric sensitivities for physical analysis using a data-driven classification method. Our analysis demonstrates a contraction of the ignition limits with increased Stokes number and a regime of parametric insensitivity of igniting mixture composition. We also show that at high Damköhler numbers, the ignition location conforms to the parametric behavior of the thermal boundary layer, whereas at low Damköhler numbers approaching the ignition limit it reaches a near-unity value of the quenching Peclet number. We then compare the demonstrated parametric dependencies to the results of the quasi-steady asymptotic ignition literature, showing that our results are consistent with those obtained analytically within the limitations imposed by the simplified formulation of the latter.

42 ENGINEERING↗
DOE OSTI2020

A review of composite solid-state electrolytes for lithium batteries: fundamentals, key materials and advanced structures

All-solid-state lithium ion batteries (ASSLBs) are considered next-generation devices for energy storage due to their advantages in safety and potentially high energy density. As the key component in ASSLBs, solid-state electrolytes (SSEs) with non-flammability and good adaptability to lithium metal anodes have attracted extensive attention in recent years. Among the current SSEs, composite solid-state electrolytes (CSSEs) with multiple phases have greater flexibility to customize and combine the advantages of single-phase electrolytes, which have been widely investigated recently and regarded as promising candidates for commercial ASSLBs. Based on existing investigations, herein, we present a comprehensive overview of the recent developments in CSSEs. Initially, we introduce the historical development from solid-state ionic conductors to CSSEs, and then summarize the fundamentals including mechanisms of lithium ion transport, key evaluation parameters, design principles, and key materials. Finally, four main types of advanced structures for CSSEs are classified and highlighted according to the recent progress. Moreover, advanced characterization and computational simulation techniques including machine learning are reviewed for the first time, and the main challenges and perspectives of CSSEs are also provided for their future development.

25 ENERGY STORAGE↗
DOE OSTI2021

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Film condensation with high heat fluxes and scaled experiments using pure steam for reactor containment cooling

Condensation tests were performed using a newly developed test facility for scaling the passive containment cooling system (PCCS) to a small modular reactor (SMR). The PCCS of the SMR plays a pivotal role in ensuring greater safety, reliability, and compactness than what is afforded by traditional reactors. Therefore, a well-designed PCCS is essential to SMRs. However, previous studies and test data were unsuitable for scaling, due to high variation in the test geometry and operating conditions. This study intends to close this research gap by using a novel designed scaled test facility consisting of vertical condensing test sections featuring 1-, 2-, and 4-inch-diameter condensing tubes with annular water cooling, and by applying superheated and saturated steam with different steam mass flow ranges of 5–25 g/s. Further, the primary test data, including axial temperatures, mass flow rates, and pressures, were used in conjunction with a standard data reduction method to estimate critical parameters such as heat fluxes, heat transfer coefficients, and condensation rates. These scaled test data would support improving empirical correlations and validating condensation models to identify scaling distortion for SMR PCCSs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Innovative laser-based methods for monitoring fuel retention in ITER

This paper addresses the challenge of tritium inventory management in ITER and future fusion reactors, highlighting the importance of accurate tritium measurement and its spatial distribution within the vacuum vessel. Given ITER’s operational constraints, especially the limit on tritium retention, precise measurement is essential for both safety and regulatory compliance. To tackle these questions, the paper presents the T-monitor diagnostic system developed by Forschungszentrum Jülich, which uses Laser-Induced Desorption (LID) in combination with Diagnostic Residual Gas Analysis (DRGA) to measure hydrogen isotope concentrations on the surface of divertor tiles. The system integrates a high-power laser, advanced optical components, and a Fast Scanning Mirror Unit (FSMU) for accurate laser spot positioning with rapid response. Designed to measure in situ tritium retention, the diagnostic provides high-resolution spatial mapping, vital for evaluating detritiation strategies. The laser heating process increases the divertor surface temperature to 1600 K within the laser spot, promoting hydrogen isotope desorption. Accurate measurements require the precise control of laser parameters, including pulse duration and spot size, with a target relative accuracy of 20%. The optical design includes both in-vessel and ex-vessel components, such as durable high-reflectivity mirrors made of gold and copper, selected not only for their infrared performance but also for their transmission of visible wavelengths for observation purposes. To protect optical components from contamination, a pneumatic shutter is used.

Hydrogen isotopes↗
DOE OSTI2023

Sensitivity of UO 2 fuel performance to microstructural evolutions driven by dilute additives

Use of dilute additives to nuclear fuel is being considered to increase the security of commercial fuel management through traceability of fabricated fuel elements. Taggants, as additives are denoted when included for traceability purposes, may also improve fuel performance, as demonstrated in Cr-containing uranium dioxide as described in the literature, and they may also improve fuel safety. In fact, studies have shown that some additives affect fuel material properties such as grain size and density after sintering. Given the possible range of elements that could be used as additives, the impact of such fuel property variations on the fuel’s thermomechanical behavior becomes relevant. These effects can be evaluated through a sensitivity study of standard fuel models to analyze changes in these properties using a fuel performance code. In this work, the BISON code is being used to investigate these effects through a 2D axisymmetric model of smeared UO 2 fuel pellets and ZIRLO® cladding under realistic pressurized water reactor core irradiation conditions. Here, randomly sampled densities and grain sizes within specified ranges are used as input parameters in the simulations, and several fuel model-related outputs are evaluated. The thermomechanical response of the cladding is also addressed in this study. The simultaneous variation of both input parameters offers a more comprehensive path to identify key sensitivities. Outputs explored include temperature, fission gas release, creep, and radial stress. Results show that although most of these outputs are sensitive to grain size to a certain extent, density mainly affects fuel temperature and elastic strain. Furthermore, sensitivities can vary depending on the radial position within the fuel pellet.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Comparative study between experimental measurements and model predictions of bubble rise velocity in molten LiCl-KCl

This research investigated the shape and rise velocities of gas bubbles (helium, nitrogen, argon, and krypton) in molten LiCl-KCl at 500 °C using a specialized optical visualization apparatus. The apparatus features a custom quartz rectangular prism cell housed in a furnace, enabling the application of the shadowgraph measurement technique. Bubbles with diameters between 0.45 and 3.2 mm were produced via a capillary, and their equivalent diameters and rise velocities were analyzed using high-resolution imaging and centroid tracking algorithms. Important non-dimensional parameters were calculated to characterize behavior. Bubbles with 0.03 < Eo < 1.32, 17 < Re < 718, and Mo order of 10 -11 were generated in the molten LiCl-KCl, revealing that bubbles with diameters less than 1.46 mm remain spherical, whereas those with larger diameters are ellipsoidal. The transition and oscillation onset for bubble shape occurred at larger diameters than those previously observed in air–water systems. Comparative analysis of the gas-molten salt data against existing air–water bubble rise velocity correlations highlighted inaccuracies in predictions, particularly across the different bubble regimes. An existing correlation was calibrated to the molten salt data to improve the bubble velocity predictions. In conclusion, this study contributes essential experimental data for the design and safety evaluation of molten salt reactors and offers insights for the optimization of sparge systems for fission product removal.

Bubble rise velocity↗
DOE OSTI2020

Stability of a tokamak plasma with diffuse toroidal rotation

The present work considers the stability of a high- $\beta$ , large aspect ratio, circular plasma with diffuse profiles for the safety factor and the angular toroidal frequency (López & Guazzotto, Phys. Plasmas , vol. 24, 032501). An application of the Frieman–Rotenberg formalism results in a system of scalar eigenmode equations whose coupling is retained at the plasma–vacuum transition but is disregarded across the plasma column, which is a standard practice. The solution technique consists of a multidimensional shooting method for the poloidal harmonics; robust initial guesses are constructed by solving the dispersion relation in the static scenario with vanishing magnetic shear. Flow shear appears as a high- $\beta$ toroidal contribution, and we illustrate its destabilizing influence on $n=1$ external kink modes in the presence of ideal and resistive walls. Internal resonances are avoided by means of the selection of appropriate equilibrium parameters. The stabilizing influence of a finite positive average magnetic shear is also exemplified.

Physics↗
DOE OSTI2023

Small Reactors in Microgrids: Technology Modeling and Selection (Net-Zero Microgrid Program Project Report)

This report demonstrates the capabilities of the net-zero microgrid (NZM) Xendee platform for modeling an SR module with electricity, heat extraction and thermal storage in microgrids configurations. The model effectively captures the most important technical and economic considerations for SR technology specific analysis: cost and operational characteristics of SR technology and financial costs and incentives. The model can analyze multiple scenarios to establish metrics for cost-competitive and zero-carbon microgrids connected to the grid or completely isolated. The model is fully integrated within the Xendee platform for modeling and analysis of clean energy microgrids with storage and generation from renewable energy sources. The model captures the capabilities, constraints, and nuances of SR by incorporating parameters related to plant economics, design efficiency and performance, plant operation and component and fuel lifespan. The cost and operational parameters modeled in the SR module are specific to the technology selected for integration in the microgrid. Cost parameters recognize advanced nuclear technology for modular production and installation based on economies of scale from factory manufacture and related commissioning, and cost reduction through technology maturation—first-of-a-kind (FOAK) and nth-of-a-Kind (NOAK). The cost parameters include installation, operations and maintenance (O&M), fuel refueling cycle, and reactor life. Installation cost reflects economies of scale due to unit sizing at scale and colocation. O&M economies of scale for both fixed- and variable-cost fuel life-cycle costs are incurred at every refueling interval, with separate front- and back-end fuel costs, as well as waste-handling and disposition costs. This report investigates key characteristics of different SR technologies suitable for microgrid applications, including design principles, sizing, coolant properties, temperature ratings, fuel structures, and life-cycle considerations. This also includes fuel technologies applicable to these SR systems, alongside strategies for nuclear-waste and spent-fuel management and approaches to address safety, security, and proliferation challenges. Four primary groups of SR technologies are examined: water-cooled, liquid-metal-cooled, high-temperature gas-cooled, and molten-salt-cooled systems. In this report, an initial guideline for technology selection is established, aligning the characteristics of the technologies with the requirements of microgrids. The selection of technology in a microgrid is influenced by various factors, including financial capacity, location and accessibility, demand type and characteristics, reliability and resilience requirements, area constraints, and the lifespan of the microgrid. The types of electrical and non-electrical applications within the microgrid also play a significant role in technology selection. The characteristics of SRs, such as their smaller size, modularity, transportability, long refueling interval, improved safety features, ability to operate in autonomous or semi-autonomous mode, and provision of high-grade heat, are particularly appealing for microgrids. Furthermore, a list of considerations for implementing SRs in microgrids is outlined. The SR model is created to be continuously improved with the acquisition of actual data on investment and operational costs, experience with supply chains, production at scale, and field deployments. In the near term, performance data on applications in microgrids will become available from lessons learned from laboratory tests, such as those planned for the Microreactor Applications Research Validation and Evaluation Project (MARVEL), led by Idaho National Laboratory (INL). The SR model incorporates scenario data and known SR design specifications, enabling technoeconomic analysis for SR deployment in microgrids. It specifically considers the distinctive attributes of SRs as generators in technoeconomic studies. SRs can be modeled and analyzed with generation from renewable-energy sources, energy storage, and flexible loads over a range of functionality and applications. This offers a comprehensive tool for feasibility studies, scenario development, and sensitivity analysis for “what-if” consideration of any range of assumptions about SRs in microgrids and other aggregations of distributed-energy resources, including virtual power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

LAMP Technical Readiness Evaluation Report

An internal preliminary evaluation of Critical Technology Elements (CTEs) for the LANSCE Modernization Project (LAMP) was completed in 2023. This included determining corresponding Technical Readiness Levels (TRLs) for all subsystems using the criteria of DOE G 413.3-4A, Technical Readiness Assessment Guide. This revised report includes a summary of the recent design modifications required to meet the project Key Performance Requirements (KPPs), some of which may reduce technical risk to the project. These recent design modifications include: • Further optimization of the low-energy and medium-energy beam transport regions (LEBT and MEBT, respectively), including relocation of various functional elements (ie choppers, kickers, and bunchers). • An additional H - ion source to separate ion-source function based on beam delivery requirements. • A high-repetition-rate pulsed kicker magnet to select/merge the two H ion beams into a common low-energy beam transport. • Modification and further optimization to a more conventional RFQ design. Performance of the RFQ has been optimized to deliver the required three types of beams while meeting the project KPPs. • The addition of a second chopper in the medium-energy beam transport (MEBT) line to reduce the required pulser voltages. The scope of the evaluation was limited to the project Work Breakdown Structure (WBS) elements as defined for the RFQ Injector and Drift Tube Linac (DTL) systems only. Integration of Instrumentation and Controls (I&C) and Safety Systems was not considered, although specific technologies as related to the RFQ and DTL systems were included. Other elements of the project such as Shielding, System Design, Technical Management, and additional facility integration needed to enable off-line testing and pre-installation commissioning were also not evaluated. Each technical subsystem element was evaluated for technical readiness, however, not all were found to meet the criteria for a CTE. Three subsystem elements were determined to meet the CTE criteria. Their associated TRLs are summarized in the table below. These subsystem elements of the project have the lowest technical readiness due to either being new, novel or modified, requiring additional R&D before being capable of meeting the project Key Performance Parameters (KPPs) and subsystem requirements, or present technology exists but has not yet been demonstrated in a relevant environment. All other subsystems were determined to have a TRL of 8, indicating that actual operating systems exist having similar performance requirements as needed for LAMP. Details of the technical readiness evaluation for each subsystem is given in the following sections of this report.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Godiva-IV Dosimetry Exercise 2022 Preliminary Results

Integral Experiment Request (IER) 538 is part of a series of dose characterization and nuclear accident dosimetry (NAD) exercises performed under the Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP). This is the second NAD exercise using the Godiva-IV critical assembly and the third NAD exercise overall. The participating laboratories provided their own dosimeters that were mounted on the Lawrence Livermore National Laboratory (LLNL) BOttle Manikin ABsorption (BOMAB) phantoms and aluminum plates. The BOMABs and plates were placed at two, three, and four meters away from the center of Godiva. Alongside the NADs, there was a LLNL Passive Neutron Spectrometer (PNS), Atomic Weapons Establishment (AWE) PNS, and Y-12 Sphere present to measure the neutron dose from Godiva. Two irradiations were conducted to test the NAD performance from each laboratory and assesses their performance to the DOE-STD-1098-2017 part 515 criteria. Neutron and gamma doses were measured prior to this exercise. This work presents a model for the neutron and gamma dose respectively to serve as the reference value. A code written in C/C++/ROOT was used to fit the measured neutron and gamma dose with the new models. It was assumed that the neutron and gamma doses are proportional to the change in temperature of Godiva after a burst irradiation. Uncertainties for the reference values were calculated using error propagation of the model’s parameters. Preliminary results (within twenty-four hours) and final results were compared for each laboratory. On average of all the participating laboratories, 32% of neutron doses and 78% of gamma doses were outside the DOE standards. One laboratory did not report their dose readings and were not included in this average. There is a bias for a lower neutron dose and a higher gamma dose based on the distribution of results. In comparison with the past Godiva-IV NAD exercise, there is an improvement in neutron dose readings by 20%.

BOttle Manikin ABsorption (BOMAB)↗
DOE OSTI2024

A Review of Online Monitoring within Used Nuclear Fuel Recycling Processes

The processing of used nuclear fuels and related materials is often complex and variable. The ability to quickly optimize conditions to the material being processed can aid in increasing efficiency and safety, but requires very quick determination of the conditions present in the feedstock, the process, and the product. Furthermore, accurate quantification of materials such as enriched uranium and plutonium aids in maintaining material accountancy and avoiding nuclear proliferation risks. Traditional analytical methods require process samples to be collected and analyzed in a laboratory, which often takes days to weeks. Online monitoring is suitable for collecting this information nearly instantaneously, enabling much faster optimization of the process or detection of material diversion. Online monitoring is also beneficial as it is typically based on robust and nondestructive analytical methods, so no material is removed as samples. This review examines online monitoring relevant to used nuclear fuel processing for the determination of both chemical and physical parameters. The chemical parameters include quantities such as concentration, isotopic composition, and speciation. These values are often well suited to spectroscopic or spectrometric measurements as they are fast, nondestructive, and easily implemented in an online manner. Physical quantities are often more varied and include temperature, pressure, tank fill levels, and others. Due to the specificity of these quantities, specialized instrumentation is often used. However, this instrumentation is often amendable to online monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Simulation of Helium Flow Visualization Apparatus for Studies of Blanket Cooling in Fusion Reactors

Flow visualization is essential to understanding helium cooling performance. This article investigates helium flow visualization in an apparatus to support the design of the blanket first wall for a fusion reactor. Helium’s safety advantages make it an attractive coolant, but effective cooling and flow visualization remain challenging. Sophisticated simulations are conducted in different test sections to address three key areas in the design of a test apparatus and cooling channel enhancements: the influence of viewing glass windows on flow patterns, the impact of increased heating, and the effectiveness of cooling structures like baffles. Viewing glass windows introduce flow recirculation region bifurcation and flow asymmetry, affecting flow patterns and necessitating careful analysis in future experiments. Increased heating results in helium flow detachment from the heated surface, leading to hot spots. Cooling structures, particularly baffles, prove effective in maintaining consistent attachment to the heated surface, improving the heat transfer performance. Further, this study also examines a tunable parameter in the turbulence model, highlighting the importance of accurate model tuning for future fusion reactor cooling designs. With an imminent helium flow visualization facility, these simulations will be used to optimize cooling structures on the heated wall to improve flow attachment and heat transfer efficiency. This work serves as a first investigation of the helium flow visualization apparatus for blanket cooling enhancement in fusion reactor design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Overview of Nuclear Data Measurement and Analysis at RPI [Slides]

This presentation discusses the experimental, simulation, and nuclear data methods that were validated for the RPI γ-Multiplicity Detector. When the neutron capture γ-cascade data is well-known, the γ-emission spectra can be accurately calculated using the modified simulation tools. The RPI γ-Multiplicity Detector system is now ready for analysis and recommendations for isotopes with deficiencies in γ-ray data. The presentation also discusses future work which includes developing a method for analyzing and adjusting nuclear data for 59 Co, 55 Mn and other measured isotopes including 181 Ta. Additionally, future work includes comparing experimental γ-emission spectra with MCNP-6.2/DICEBOX simulations for 238 U and 235 U. In summation, new capture and transmission measurements for 54 Fe will help improve resonance parameter evaluation. Neutron capture gamma cascade spectra and yields were measured in the resolved resonance region and compared to evaluations. In addition, the pulsed neutron die-away method was developed as a tool to provide data for validation of TSLs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗