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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Development of Multi-physics (Multiphase CFD + MCNP) simulation for generic solution vessel power calculation

The current study aims to predict the steady state power of a generic solution vessel and to develop a corresponding heat transfer coefficient correlation for a Moly99 production facility by conducting a fully coupled multi-physics simulation. A prediction of steady state power for the current application is inherently interconnected between thermal hydraulic characteristics (i.e. Multiphase computational fluid dynamics solved by ANSYS-Fluent 17.2) and the corresponding neutronic behavior (i.e. particle transport solved by MCNP6.2) in the solution vessel. Thus, the development of a coupling methodology is vital to understand the system behavior at a variety of system design and postulated operating scenarios. In this study, we report on the k-effective (keff) calculation for the baseline solution vessel configuration with a selected solution concentration using MCNP K-code modeling. The associated correlation of thermal properties (e.g. density, viscosity, thermal conductivity, specific heat) at the selected solution concentration are developed based on existing experimental measurements in the open literature. The numerical coupling methodology between multiphase CFD and MCNP is successfully demonstrated, and the detailed coupling procedure is documented. In addition, improved coupling methods capturing realistic physics in the solution vessel thermal-neutronic dynamics are proposed and tested further (i.e. dynamic height adjustment, mull-cell approach). As a key outcome of the current study, a multi-physics coupling methodology between MCFD and MCNP is demonstrated and tested for four different operating conditions. Those different operating conditions are determined based on the neutron source strength at a fixed geometry condition. The steady state powers for the generic solution vessel at various operating conditions are reported, and a generalized correlation of the heat transfer coefficient for the current application is discussed. The assessment of multi-physics methodology and preliminary results from various coupled calculations (power prediction and heat transfer coefficient) can be further utilized for the system code validation and generic solution vessel design improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Survey of Dynamic Mode Decomposition Methods

Dynamic mode decomposition (DMD) is a data-driven reduced order modeling (ROM) technique used for dynamic systems. The widely adopted algorithm was first introduced and demonstrated on fluid flow data by Schmid. In recent years, various other fields, such as nuclear engineering, have begun to adopt this method. For example, DMD has been used for estimating α-eigenvalues, as an ROM for pulsed neutron problems, for predicting isotopic composition in burnup calculations, as acceleration techniques for iterative methods, and in capturing dynamic behaviors in molten salt reactor transients. This report seeks to demonstrate the capabilities and limits of the standard DMD algorithm, and identify problem spaces where variants may be better suited. The primary variant this report considers is Multi-Resolution DMD (mrDMD). Because this serves as a survey, synthetically produced data is used in lieu of simulation results. The remainder of this report will go into detail on the DMD theory, outline the standard DMD and mrDMD algorithms, present test cases highlighting the applicability of each, and finally present a discussion on how to determine the best suited algorithm for a given problem. All calculations performed in this report are carried out using the open source DMD library, PyDMD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

User Guidelines and Best Practices for CASL VUQ Analysis Using Dakota

Sandia’s Dakota software (available at http://dakota.sandia.gov) supports science and engineering transformation through advanced exploration of simulations. Specifically it manages and analyzes ensembles of simulations to provide broader and deeper perspective for analysts and decision makers. This enables them to enhance understanding of risk, improve products, and assess simulation credibility. In its simplest mode, Dakota can automate typical parameter variation studies through a generic interface to a physics-based computational model. This can lend efficiency and rigor to manual parameter perturbation studies already being conducted by analysts. However, Dakota also delivers advanced parametric analysis techniques enabling design exploration, optimization, model calibration, risk analysis, and quantification of margins and uncertainty with such models. It directly supports verification and validation activities. Dakota algorithms enrich complex science and engineering models, enabling an analyst to answer crucial questions of - Sensitivity: Which are the most important input factors or parameters entering the simulation, and how do they influence key outputs?; Uncertainty: What is the uncertainty or variability in simulation output, given uncertainties in input parameters? How safe, reliable, robust, or variable is my system? (Quantification of margins and uncertainty, QMU); Optimization: What parameter values yield the best performing design or operating condition, given constraints? Calibration: What models and/or parameters best match experimental data? In general, Dakota is the Consortium for Advanced Simulation of Light Water Reactors (CASL) delivery vehicle for verification, validation, and uncertainty quantification (VUQ) algorithms. It permits ready application of the VUQ methods described above to simulation codes by CASL researchers, code developers, and application engineers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Proposed Semi-Analytic Benchmark for Coupled Neutronics/Thermal-Hydraulics Feedback in Multiphysics Simulations

The past decade has seen considerable advancements in multiscale and multiphysics simulations that account for nonlinear effects of feedback between different physical processes within a single calculation. One area of particular interest has been multiphysics simulations that include both neutronics and thermal-hydraulics effects to accurately model the thermal feedback effects present in nuclear reactors. During this time, many groups have successfully modeled thermal feedback effects by coupling a variety of different types of neutron transport and thermal-hydraulic solvers together. However, formal verification and validation of these coupled code systems has proven challenging due to a lack of benchmark problems with well-characterized reference solutions. One approach is to confirm gross energy balance using bulk coolant properties (outlet temperature/enthalpy) for code verification purposes. Alternatively, code-to-code comparisons of results for a predefined reference/challenge problem have been used to establish reasonability of local results (neutron flux, heating, enthalpy rise) for various implementations, for example the VERA Core Physics Progression Problems. While community solutions are valuable for assessing the relative performance and fidelity of different implementations, they are not guaranteed to provide a measure of the absolute accuracy of a given implementation. In fact, these code-to-code comparisons can give a false sense of confidence by masking the effects of errors or approximations that are common to all of the solution methods tested. This is a particular concern when many methods derive from a common approach, such as Picard iteration. To this end, an analytical benchmark would be very valuable for verifying individual coupled physics implementations, as well as for providing a formal assessment of algorithm accuracy and sensitivity to model approximations such as mesh size and number of convergence iterations. However, creation of an analytical benchmark is difficult due to the complex nature of the eigenvalue form of the neutron transport equation (which does not permit a simple analytical solution for non-trivial cases) as well as the variety of different empirical closure relationships used in thermal-hydraulic modeling. In this paper we propose a benchmark for coupled neutronics/thermal-hydraulics simulations. The proposed benchmark overcomes the challenges associated with a multiphysics benchmark problem by using a fixed-source (rather than eigenvalue) formulation of the neutron transport equation and limiting fluid properties to the single-phase regime where the density and temperature of the coolant are related to enthalpy by a known relationship, while still preserving significant nuclear/thermal feedback effects within the simplified problem. The new benchmark is easy to simulate using existing coupled physics implementations, and allows for a direct comparison with a reference solution, as provided in this summary.

42 ENGINEERING↗
DOE OSTI2020

Crossing the Streams – Sampler and the TemplateEngine [Slides]

This presentation discusses Sampler, which is a versatile UQ and parametric study tool that can be applied to any SCALE Sequence. Sampler can perturb any quantity in any SCALE input. Recent work at ORNL has developed new types of covariance data that allow Sampler UQ to be applied to nearly all SCALE applications, including reactor depletion, UNF fuel characterization, source term analysis, and decay heat calculation. In SCALE 6.2 releases, CE data in transport cannot be perturbed. Sampler was originally designed for stochastic sampling with any sequence within SCALE and Parametric capability added in SCALE 6.2.2. Sampler can be used for uncertainty quantification, including sample data in static or depletion calculations and sample inputs for uncertainties in compositions and dimensions. The SCALE TemplateEngine allows for expanding templates to full inputs and the combination provides a powerful UQ tool.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Autonomous sputter synthesis of thin film nitrides with composition controlled by Bayesian optimization of optical plasma emission

Autonomous experimentation has emerged as an efficient approach to accelerate the pace of material discovery. Although instruments for autonomous synthesis have become popular in molecular and polymer science, solution processing of hybrid materials, and nanoparticles, examples of autonomous tools for physical vapor deposition are scarce yet important for the semiconductor industry. Here, we report the design and implementation of an autonomous workflow for sputter deposition of thin films with controlled composition, leveraging a highly automated sputtering reactor custom-controlled by Python, optical emission spectroscopy (OES), and a Bayesian optimization algorithm. We modeled film composition, measured by x-ray fluorescence, as a linear function of plasma emission lines monitored during co-sputtering from elemental Zn and Ti targets in an N 2 and Ar atmosphere. A Bayesian control algorithm, informed by OES, navigates the space of sputtering power to fabricate films with user-defined compositions by minimizing the absolute error between desired and measured optical emission signals. We validated our approach by autonomously fabricating Zn x Ti 1-x N y films that deviate from the targeted cation composition by a relative ±3.5%, even for 15 nm thin films, demonstrating that the proposed approach can reliably synthesize thin films with a specific composition and minimal human interference. Moreover, the proposed method can be extended to more difficult synthesis experiments where plasma intensity lines depend non-linearly on pressure, or the elemental sticking coefficients strongly depend on the substrate temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

0D Modeling of Reactor Networks Within Zuzax

We report on progress in developing macroscopic balance equations for combustion and electrochemistry systems. A steady state solution capability is described for the macroscopic reactor network, with an associated steady state continuation method and solution storage capability added in. An example is provided of continuation of a hydrogen flame versus the equivalence ratio. The reactor modeling capability is extended to charged fluid systems, with a description of the new ChargedFluidReactor, SubstrateElement, and MetalCurrentElement reactor classes and novel setup of unknowns within these reactors that preserve charge neutrality. Zuzax's setup for electrochemistry is explained including the specification of the electron chemical potential and the adherence to the SHE Reference electrode specification. The description of the different ways to enter electrochemical reaction rates are described, contrasted, and their derivations with respect to one another are derived. An example of using the ChargedFluidReactor within corrosion problems is provided. We present a description of calculations to understand the phenomena of corrosion of copper from a micron sized droplet of NaCl water droplet, where secondary spreading occurs. An analysis of the discrepancies with experiment is carried out, demonstrating that macroscopic balances can be an important tool for understanding what major factors need to be addressed for a better understanding of a physical system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Symmetric spectrum current drive due to finite radial drift effects

The drift surfaces of minority heated ions differ from flux surfaces due to finite poloidal gyroradius effects. As the minority poloidal gyroradius approaches radial scale lengths in the plasma the difference between drift and flux surfaces can modify the heating and lead to a symmetric spectrum minority counter-current being driven. In response, a corresponding overall net co-current of comparable size is driven. This beneficial symmetric spectrum current drive in a tokamak is due to the parallel velocity asymmetry in the drift departure from a flux surface. As this new source of driven current is a side effect of minority heating it comes without any additional economic cost to reactor power balance. The symmetric spectrum current driven for near Maxwellian minorities is evaluated by an adjoint method and found to be modest. However, minority heating typically results in strong non-Maxwellian features on minority distributions so it may be possible to drive significantly larger co-current. A related evaluation is performed for alpha particles in a deuterium minority heated plasma with a tritium majority. The low density of the alphas tends to keep this driven symmetric spectrum current small, but at very high heating levels a significant co-current might be driven. Other mechanisms to drive co-current with a symmetric spectrum are discussed and estimated, including asymmetric electron drag and focusing of the applied minority heating radio frequency fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Symmetric spectrum current drive due to finite radial drift effects

We report the drift surfaces of minority heated ions differ from flux surfaces due to finite poloidal gyroradius effects. As the minority poloidal gyroradius approaches radial scale lengths in the plasma, the difference between drift and flux surfaces can modify the heating and lead to a symmetric spectrum minority counter-current being driven. In response, a corresponding overall net co-current of comparable size is driven. This beneficial symmetric spectrum current drive in a tokamak is due to the parallel velocity asymmetry in the drift departure from a flux surface. As this new source of driven current is a side effect of minority heating it comes without any additional economic cost to reactor power balance. The symmetric spectrum current driven for near Maxwellian minorities is evaluated by an adjoint method and found to be modest. However, minority heating typically results in strong non-Maxwellian features on minority distributions so it may be possible to drive a significantly larger co-current. A related evaluation is performed for alpha particles in a deuterium minority heated plasma with a tritium majority. The low density of the alphas tends to keep this driven symmetric spectrum current small, but at very high heating levels a significant co-current might be driven. Other mechanisms to drive co-current with a symmetric spectrum are discussed and estimated, including asymmetric electron drag and focusing of the applied minority heating radio frequency fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Historical Examination of the ASTM Standard E722 1-MeV Silicon Equivalent Fluence Metric

ASTM Committee E10 on Nuclear Technology and Applications develops and maintains many standards that are relevant to the radiation metrology activities in Sandia National Laboratories' Radiation and Electrical Sciences Center. This is particularly true for the reactor facilities and Subcommittee E10.07 on Radiation Dosimetry for Radiation Effects on Materials and Devices. In the past decade, Subcommittee E10.07 has been making substantive changes to the standard widely used to assess radiation hardness to neutron effects in electronics, E722 – Standard Practice for Characterking Neutron Fluence Spectra in Terms of an Equivalent Monoenergetic Neutron Fluence for Radiation-Hardness Testing of Electronics . ASTM Standard E722 describes the method that defines the 1-MeV silicon and the 1-MeV gallium arsenide equivalent fluence radiation damage metrics. An evaluation of the impact of changes to the shape of the 1-MeV silicon equivalent fluence radiation damage metric from the 1985 version (E722-85) to the most recent version (E722-19) is performed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Identifying Challenges in Safeguards for Metallic Fuel Fabrication Facilities

As new advanced reactors gain popularity, there is an increasing interest in metallic fuel fabrication for fast reactors. While metallic fuels themselves are not a new idea, as many of the first reactors employed metallic fuels, new designs, compositions, and fabrication methods are appearing throughout the nuclear community. As the interest grows and facilities are constructed, both domestic and international safeguards will need to be heavily involved to support safeguards-by-design (SBD) measures from the start. This work compiles a review of historical and modern fuel types and fabrication methods, fabrication processes, safeguards gaps, and potential safeguards solutions. Metallic nuclear fuel types have been around for many decades and were included in some of the first reactors including the Experimental Breeder Reactor (EBR)-I and -II, the Fermi 1 reactor, the Integral Fast Reactor (IFR), and the Dounreay Fast Reactor (DFR). These reactors used various compositions including pure uranium (U) metal, U-zirconium (Zr) alloys, plutonium (Pu)-aluminum (Al) alloys, U-fissium (Fs) alloys, U-Pu-Zr alloys, and U-molybdenum (Mo) alloys [1, 2, 3, 4, 5]. These small alloying additions are included to improve the material properties of the pure U metal. The alpha-phase U (stable below 661C) suffers elongation in one direction causing grain boundary cracking and increasing creep rate due to irradiation growth, thermal cycling, and preferential crystal orientation. It is ideal to utilize the gamma-phase U (typically stable above 769C) by adding small amounts of alloying elements such as Zr or Mo to stabilize this phase down to room temperature [3]. Additionally, some research has been focused on U with transuranic (TRU) elements present, typically coming from the used fuel recycling process. Including these elements in fast reactor fuel can aid in the reduction of nuclear waste by burning minor long-lived actinides. However, the additions of TRU elements can cause concerns to arise when trying to fabrication or safeguard metallic fuels. A typical metallic fuel element is shown in Figure 1. Sodium is added into the cladding to create a thermal bond between the fuel slug and cladding wall. The fuel slug is then inserted and the end plug is welded on to the top of the fuel element. A gas plenum is left to create a headspace for gaseous fission products to escape rather than continue to build in the fuel itself [1, 5]. Other fuel element geometries exist as well, such as the Lightbridge twisted cruciform geometry shown in Figure 2 [6]. This design allows for better cooling performance and provides room for fuel rod swelling without impacting the fuel rod diameter. There are many different fabrication methods for metallic fuels, which is one of the many benefits of these fuel types. Many of these fabrication methods are relatively easy and cost-efficient. The most popular fabrication method is injection casting, sometimes called vacuum induction melting (VIM), shown in Figure 3 [4, 8, 9, 7, 10]. This method was largely used for EBR-II fuel fabrication. The injection casting system is contained inside of a vessel consisting of a Y2O3-coated graphite crucible surrounded by an induction coil with ZrO2-coated quartz molds suspended above the crucible. The fuel feedstock is placed inside of the graphite crucible and melted using the induction furnace. The induction furnace utilizes a dual frequency with the high frequency melting the feedstock and the low frequency causing stirring of the melted feedstock to form a homogeneous mixture. The mixture is heated to approximately 1600C in an argon environment. The vessel is evacuated and then the quartz molds are lowered into the graphite crucible containing the molten metal and the vessel is repressurized to inject the metal fuel upwards into the molds. The molds are removed and then shattered to release the fuel slugs. This fabrication method was used to fabricate 39,000 metallic fuel pins for EBR-II. While injection casting has been the most common metallic fuel fabrication method throughout the decades, many other methods have been explored including low-pressure gravity casting, microwave casting, continuous casting, centrifugal casting, coextrusion, and many others [11, 12, 8, 13, 14, 15]. Some of these methods aim to mitigate challenges that arise with americium (Am) volatilization during the casting process for TRU-containing fuel feedstocks, an issue with injection casting. Coextrusion is one of the methods explored at the Idaho National Laboratory (INL) and has been utilized for the initial fabrication tests of Lightbridge's unique fuels, as well as other metallic fuels with cladding coextruded. In this process, large billets are formed and machined and then inserted into a molten salt bath for approximately 30 minutes. The billets are then loaded into the extrusion press and extruded. This process can be seen in Figure 4 [15].

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

AREVA NP's industrial CFD single-phase methodology and applications for nuclear fuel

During the course of the last decade, AREVA NP has developed Computational Fluid Dynamics (CFD) methods capable of accurately predicting flow fields and thermal mixing within fuel bundles, as well as pressure losses and hydrodynamic forces on fuel assembly components such as spacer grids, lower and upper nozzles. The present work summarizes the evolution of AREVA NP's single-phase CFD methodology and the extensive validation efforts, with focus on improving confidence level in CFD results. Currently, it is possible to produce models for large sections of a fuel assembly and produce CFD simulation results with an uncertainty proven to be similar to the corresponding measurement uncertainty. Extensive validation has been conducted against in-house data obtained for a wide range of geometries representative of actual hardware, in multiple test facilities, with various measurement techniques. In addition to in-house validation data, AREVA NP has also exercised its best-practices against international benchmarks; blind test results were in very good agreement with the data. The current high level of confidence in single-phase CFD predictions allows investigating a wide variety of physics in Pressurized Water Reactor (PWR) as well as Boiling Water Reactor (BWR) fuel assemblies. CFD is used as a design and optimization tool as well as a supplement to regular testing to improve the quality of tests and optimize hardware design features for specific targets. CFD played a major role in the design of AREVA NP's latest fuel assembly designs (ATRIUM{sup TM1} 11 and GAIA). In this paper we first illustrate AREVA NP's comprehensive validation database for single-phase CFD (pressure drop, flow field), then provide several examples of applications: virtual testing for parts optimization and support of core operation. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Bulk production and evaluation of high specific activity 186g Re for cancer therapy using enriched 186 WO 3 targets in a proton beam

Rhenium-186 g (t 1/2 = 3.72 d) is a β– emitting isotope suitable for theranostic applications. Current production methods rely on reactor production by way of the reaction 185 Re(n,γ) 186g Re, which results in low specific activities limiting its use for cancer therapy. Production via charged particle activation of enriched 186 W results in a 186g Re product with a much specific activity, allowing it to be used more broadly for targeted radiotherapy applications. Furthermore, this targets the unmet clinical need for more efficient radiotherapeutics.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Development of a continuous synthesis process for carbamazepine using validated in-line Raman spectroscopy and kinetic modelling for disturbance simulation

Mitigation of failure modes in the continuous synthesis (CS) of a drug substance (DS) has the potential to widen the adoption of continuous manufacturing (CM) technologies by the pharmaceutical industry. Here, this work demonstrates the development of a robust continuous process for the synthesis of carbamazepine (CBZ), an essential medicine as per the World Health Organization (WHO), facilitated by kinetic modelling and monitored by in-line Raman spectroscopy. Accurate kinetic modelling and the use of validated process analytical technology (PAT) models for quantitative measurement were found to play an important role in developing CS of drug substances. Kinetic data for the formation of CBZ from iminostilbene (ISB) were collected by batch reaction sampling and high-performance liquid chromatography (HPLC) analysis. A non-linear solver and iterative method was applied to determine two sets of Arrhenius parameters simultaneously for the reaction system by minimizing the standard error of the model fit. The start-up and dynamic equilibrium stages for the CS of CBZ using a continuous stirred tank reactor (CSTR) were modelled based on the batch kinetic data and employed to optimize conversion and simulate process disturbances. An in-line Raman spectroscopy method was successfully developed, validated, and integrated to determine the concentrations of CBZ and ISB within the operating range for the CS. The CS kinetic model was evaluated experimentally from startup to dynamic equilibrium over 10 residence times with monitoring by HPLC and in-line Raman spectroscopy. The developed kinetic model in tandem with in-line Raman spectroscopy successfully predicted disturbances due to changes in process variables and can serve as a useful tool in the future design of advanced process control strategies for the continuous synthesis of CBZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Investigations of Properties of {sup 89}Y Levels with Reactor Fast Neutrons

By employing a beam of reactor fast neutrons, the spectrum of gamma rays up to an energy of 4.6MeV and their angular distributions with respect to the neutron-beamaxis aremeasured in the reaction {sup 89}Y(n, n'γ). The multipolarities and multipole-mixture parameters for 34 gamma transitions and the spin–parities J{sup π} of states excited in this reaction are determined. The lifetimes of the lowest 32 levels of 89Y were measured by the Doppler shift attenuation method, and the reduced probabilities for the respective gamma transitions were calculated. Levels of the K{sup π} = +5/2{sup +} and K{sup π} = −7/2{sup +} bands associated with, respectively, prolate and oblate deformation shapes are found in {sup 89}Y at low excitation energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Determination of plasma density from data on the ion current to cylindrical and planar probes

To improve probe methods of plasma diagnostics, special probe measurements were performed and numerical models describing ion transport to a probe with allowance for collisions were developed. The current–voltage characteristics of cylindrical and planar probes were measured in an RF capacitive discharge in argon at a frequency of 81 MHz and plasma densities of 10{sup 10}–10{sup 11} cm{sup –3}, typical of modern RF reactors. 1D and 2D numerical models based on the particle-in-cell method with Monte Carlo collisions for simulating ion motion and the Boltzmann equilibrium for electrons are developed to describe current collection by a probe. The models were used to find the plasma density from the ion part of the current–voltage characteristic, study the effect of ion collisions, and verify simplified approaches to determining the plasma density. A 1D hydrodynamic model of the ion current to a cylindrical probe with allowance for ion collisions is proposed. For a planar probe, a method to determine the plasma density from the averaged numerical results is developed. A comparative analysis of different approaches to calculating the plasma density from the ion current to a probe is performed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Rancor-HUNTER: A Virtual Plant and Operator Environment for Predicting Human Performance

Advances in simulation capabilities to model physical systems have outpaced the development of simulations for humans using those physical systems. There is an argument that the infinite span of potential human behaviors inherently render human modeling more challenging than physical systems. Despite this challenge, the need for modeling humans interacting with these complex systems is paramount. As technologies have improved, many of the failure modes originating from the physical systems have been solved. This means the overall proportion of human errors has increased, such that it is not uncommon to be the primary driver of system failure in modern complex systems. Moreover, technologies such as automated systems may introduce emerging contexts that can cause new, unanticipated modes of human error. Therefore, it is now more important than ever to develop models of human behavior to realize overall system error reductions and achieve established safety margins. To support new and novel concepts of operations for the anticipated wave of advanced nuclear reactor deployments, human factors and human reliability analysis researchers need to develop advanced simulation-based approaches. This talk presents a simulation environment suitable to both collect data and then perform Monte Carlo simulations to evaluate human performance and develop better models of human behavior. Specifically, the Rancor Microworld Simulator models a complex energy production system in a simplified manner. Rancor includes computer-based procedures, which serve as a framework to automatically classify human behaviors without manual, subjective experimenter coding during scenarios. This method supports a detailed level of analysis at the task level. It is feasible for collecting large sample sizes required to develop quantitative modelling elements that have historically challenged traditional full-scope simulator study approaches. Additionally, the other portion of this experimental platform, the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), is presented to show how the collected data can be used to evaluate novel scenarios based on the contextual factors, or performance shaping factors, derived from Rancor simulations. Rancor-HUNTER is being used to predict operator performance with new procedures, such as results from control room modernization or new-build situations. Rancor-HUNTER is also proving a useful surrogate platform to model human performance for other complex systems.

99 GENERAL AND MISCELLANEOUS↗