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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Assessing Several Modeling Approaches in Depletion Studies of a TRISO-Fueled Microreactor

The impact of MCNP6 depletion resolution on core lifetime is examined in the context of the Snowflake microreactor with explicit TRISO fuel. The change in core lifetime and isotope mass as a result of different tracked isotopes, timesteps, and spatial regions is discussed. Calculation speed of a prototype MCNP delta tracking module is compared to a reactivity equivalent physical transformation (RPT). Using a single depletion material underpredicts core lifetime by 15%, and the resolution necessary to converge isotope mass greatly depends on the specific isotope, in addition to the size (and location) of the depletion region. The prototype delta tracking module decreases the CPU time of explicit TRISO criticality calculations by 30%, but does not always result in a speedup when used with depletion. Significant depletion speedup is obtained using RPT (50% faster), and all isotope masses agreed within three percent.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

MTA Secondary Beamline Production and Optics Optimization

A new secondary beamline was recently installed in the MeV Test Area (MTA) with the objective of enhancing mu+/mu- production by factors of 3/8 by using a tungsten target versus the conventional graphite production target using the 400 MeV Fermilab proton Linac beam. Ultra-low energy muon beams can support world-class physics experiments for fundamental muon measurements, sensitive searches for symmetry violation, and precision tests of theory. Extensive production studies have confirmed higher muon yield from heavy targets (tungsten vs carbon), but also, surprisingly, showed significant differences in production fluence and energy spectrum between modern hadronic models (GENIEhad) and between GEANT and MCNP. Studies are also underway towards a high-efficiency source of muonium by stopping the mu+ beam in superfluid helium. Muon fluxes can be measured at MTA including using higher-Z and novel target geometries to test hadronic and production models which are critical to understanding ongoing experiments (Mu2e) and will significantly impact the planning of future HEP experiments and planning PIP II facilities. The MTA beamline will additionally support a broad user muon test beam for future experiments and R&D.

Ahmed, Shiza↗
DOE OSTI2023

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Secondary Pion Production using the LINAC Beam on Graphite and Tungsten Targets

The Fermilab 400-MeV Linac primary proton beam can produce precision, single-species secondary beams using a production target in the MeV Test Area experimental hall; specifically, pions from 4 up to 120 MeV kinetic energy. (These low energy pions rapidly decay into a muon beam in a secondary collection and transport beamline.) Although graphite is a standard production target material given its ultra-high temperature tolerance and low impact on the post-target primary beam, secondary pion/muon total production cross sections increase approximately as Z1/3 for positive muons and N2/3 for negative muons. Higher mass targets such as tungsten can potentially increase low-energy m+ and m- rates by factors of 3 and 8, respectively. Initial production studies have confirmed higher muon yield from heavy targets (tungsten vs carbon), but also, surprisingly, show significant differences in pion production between modern hadronic models (GENIEhad) and between GEANT and MCNP, state of the art production modeling codes. This project will further investigate the production discrepancies between these two target materials and between different physics models with high-statistics runs using the GEANT-based code, G4Beamline to better quantify the results and compare with production data which will be obtained using the MTA secondary beamline.

Ahmed, Shiza↗
DOE OSTI2020

Neural MUSE Analysis

Researchers at Oak Ridge National Laboratory (ORNL) created data as part of the MUSE (Multi-Agency Urban Search Experiment Detector and Algorithm Test Bed) project simulating illicit nuclear materials located in various buildings along a road. In the simulation, a truck containing a radiation detector drives down the road gathering listmode data (counting the and energy of incident gamma radiation). Building materials, source shielding, driving speed, truck direction, truck location on the road, source type, and source placement are all varied between runs of the data set. This data was created using deterministic neutron transport and Monte Carlo methods through a combination of SCALE, MAVRIC, MCNP, and GADRAS. As part of a follow-on NA-22 project, two Kaggle competitions were created to determine the best algorithms for finding and identifying gamma sources in this simulated urban environment. The winning algorithm was neural network-based and had a test accuracy of 76.4% accuracy for source identification. This work seeks to build upon this work and improve the results through the application of novel machine learning techniques. As a first step, the data was classified by a simple Convolutional Neural Network (CNN) To accomplish this, the data was first preprocessed into “waterfall plots.” These plots are composed of energy vs count plots that are stacked vertically to show progression in time. The horizontal axis indicating the particle energy incorporated user defined bin spacing with options for in linear-, logarithmic-, square root-, and user-spaced bins. The z or color dimension showed the number of counts corresponding the energy-time combination. This data was then used to generate more data, by generating a local estimate of the mean of the distribution for a bin and then randomly re-sampling that bin from a Poisson distribution. Once all of this data was generated, it was fed into a well-known CNN architecture, ResNet50. The output layer of this model was removed and replaced with layers corresponding to the shape desired isotope outputs. The provided training data was used to train the classifier and the remaining testing data was used to evaluate the model. Results are soon to be forthcoming.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

A Primer on Nuclear "Recoil" Data

For many years the ENDF-6 format has existed to contain evaluated nuclear data. One primary driver for the format and the data is neutron transport calculations. Evaluated data can be processed by a code like NJOY into either continuous energy form (ACE format) for Monte Carlo codes like MCNP or into multi-group form (NDI tables) for deterministic codes like Partisn. The reaction cross sections are found in the MF 3 section of the ENDF-6 format. If the reaction produces one or more neutrons as outputs, then secondary neutron data must also be given in MF 4,5 or 6 sections of the format. Energy and angular distributions for the output neutrons must be given in one of several available formats. The most general formats are found in MF 6. MF 4 is for angular distributions, MF 5 is for Energy distributions, and MF 6 contains both. In recent years, more interest has developed in the other output particles (i.e., the “recoil” particles) from neutron induced reactions. This has been driven by interest in charged particle transport and in more specialized partial kermas. ( A separate total neutron kerma has been available for a long time.) Partial kermas are a breakdown of the Kinetic Energy Released into the MAterial by output particle or by neutron reaction. The sum of the partial kermas should be equal to the total kerma on a group-wise basis. The ENDF-6 format is general enough for these new data requirements. Ideally, evaluated data would exist for every output particle (including the secondary neutrons) from every neutron-induced reaction. In the MF 6 format section, data for multi-particle outputs may be entered using the LAW =1 option. This option explicitly allows energy and angular output distributions for each particle produced in the reaction. Such information should preserve the balance between partial kermas and the total kerma at the groupwise level as well as the individual particle averaged energies. For simpler 2-body reactions, LAW = 2 is available. This allows the evaluation to specify only enough data to specify the 2-body reaction fully. Such a simplification does not exist for 3 (or more) body breakups. A simplified form of LAW 2, i.e., LAW 3, also exists to generate approximate recoil output distributions in the absence of full data. However, evaluated data does not generally exist at this fine granularity for reactions involving more than 2 output particles ( e.g., the 3-body break-up reaction). When the multi-body detailed output distribution data is not available, LAW=6 may be employed in NJOY. LAW 6 produces approximate output distributions for all the particles produced in the reaction. Just like in the 2-body case, the smaller particles will generally carry off more energy. At any particular energy, the balance between the sum of the partial kermas and the total kerma will not necessarily be preserved. However, the average energy of each output particle from a reaction is preserved.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Conjugate Heat Transfer Analysis in Pressurized Helium Gas Cooling Channels

Los Alamos National Laboratory (LANL) is working with NorthStar Medical Radioisotopes (NMR) on their efforts to produce Mo-99 from the irradiation of Mo-100 targets. The NMR target consists of an Inconel window that allows the electron beam to penetrate and irradiate a stack of Mo-100 disks. The irradiation process generates large amounts of heat and is cooled using pressurized helium gas flowing at 400 g/s. LANL provides both numerical analysis support and experimental support. Computational fluid dynamics (CFD) and conjugate heat transfer (CHT) analysis are performed on the NMR target to analyze the helium flow and volumetric heating through the NMR system. In this iteration of numerical analysis, we update the Mo-100 disk thickness to 0.74 mm and the gap between the Inconel window and the first disk to 0.69 mm. Estimates of the heat flux from the electron beams from Monte Carlo N-Particle code (MCNP) analysis were combined with CFD to perform the CHT analysis. The pressure drop through the targets, force applied on the first disk, beam window and target disk temperatures are some of the quantities estimated using the simulations. The pressure drop through the target was estimated as 0.198 MPa, while the force due to venturi effects across the first disk was estimated to be 100 N. The results show maximum window temperatures over 600 °C and peak disk temperatures over 1600 °C. Past work has shown that beyond 650-700 °C, the Inconel window becomes susceptible to yield and rupture. The increased temperature in these results reduces the margin of error possible on beam spot size. The disk temperatures showed a sinusoidal distribution with the 6 th – 8 th disk from each window exhibiting highest disk temperatures. The peak temperature of the stainless steel housing was close to 316 °C and that of the laminations and spacers was approximately 582 °C.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Niowave Neutron Source Converter: Lead-Bismuth-Eutectic (LBE) Windowless Target Design and Evaluation

Los Alamos National Laboratory (LANL) is working with Niowave on the design and evaluation of their lead-bismuth-eutectic (LBE) windowless target (i.e., neutron source converter). Niowave plans to use 200 kW electron beam at 40 MeV beam energy to produce neutrons by photonuclear reaction with LBE. Then, the neutrons undergo fission at the surrounding uranium target assembly (UTA) to produce Molybdenum 99 (Mo-99) as a fission product, which eventually decays to Technetium-99 (Tc-99m). Tc-99m is one of important radioisotopes that is used for medical diagnostics. LANL conducted 3D multiphysics analysis for the Niowave neutron converter design and provided design assessment in thermohydraulic aspects. LANL conducted radiation transport calculations using Monte-Carlo N-Particle (MCNP) code with unstructured meshing scheme. The 3D volumetric heating profiles in the LBE and Stainless-Steel (SS) housing were imported into multiphase computational fluid dynamics (CFD) to obtain 3D temperature profiles of LBE and SS through conjugate heat transfer (CHT) analysis. The key findings are: LBE film thickness at the center of the beam is approximately 1.6 cm with a maximum LBE velocity of approximately 1.8 m/s, which is below a 2 m/s limit to avoid erosion issues on supporting structures; Heat deposition in the LBE peaks at ~1 cm depth from the LBE free-surface because of the forward interactions of electron, photon, and neutron with LBE; LBE maximum temperature is ~360 °C, which is below LBE evaporation initiative temperature, ~450 °C; LBE-SS interface temperature is ~350 °C, which is below the safety thermal limit to prevent severe corrosion on SS. The results indicate that Niowave’s neutron converter design satisfies both hydraulic and thermal criteria for safe operation. By virtue of such computational analysis, Niowave can move toward establishing an experimental setup to experimentally test their LBE neutron converter. The following sections describe the detailed work done by LANL.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Effect of Lateral Conduction in a Rectangular Fuel Plate and Optimum Stripe Widths for the OPAL Reactor

The impetus for this work is the Proliferation Resistance Optimization (PRO-X) program, which was created by the National Nuclear Security Administration (NNSA) of the US Department of Energy (DOE) to provide a framework for developing reactor designs that minimize the production of special nuclear materials while maximizing performance for peaceful uses. The Argentine company INVAP and Argonne National Laboratory collaborated to share knowledge and expertise regarding the thermal analysis of research reactors. Working together, they designed a series of test problems based on the Open Pool Australian Light Water (OPAL) reactor, whose fuel is in the form of flat plates cooled by water flowing through narrow rectangular channels. ANL used their PLTEMP/ANL code. INVAP used their TERMIC code (and its new multi-plate version, TERMIC-MP). Then, INVAP and ANL compared the two sets of results. 1-D models were used during the collaboration since for research reactor analysis, largely 1-D thermal-hydraulics models are commonly used because they are simple to apply and technically defendable. The collaboration between the two organizations aims for improvements in thermal-hydraulic models. Improvements to methods and models can reduce modeling uncertainties and excessive conservatism, allowing greater reactor performance without reducing predicted safety margins. Therefore, these improvements potentially expand the design space, making additional designs feasible, which, in turn, may achieve better fuel utilization and proliferation resistance in the designs. This report provides justification for the lateral node size (stripe width) chosen for the 1-D computer models during the collaboration. The lateral heat conduction in OPAL fuel plates is evaluated using the two-dimensional conduction capability of PLTEMP/ANL to determine a representative hot-stripe width that can be conservatively used for one-dimensional steady-state thermal-hydraulic analysis. Basically, a representative hot-stripe width needs to be selected so that the actual heat flux averaged over this stripe width is greater than or equal to the maximum heat flux obtained by the two-dimensional analysis. Detailed results in this report show that a hot-stripe width of 8.125 mm can be conservatively used for the one-dimensional thermal-hydraulics analysis of all plates. Therefore, eight equal stripes (8.125 mm each) are recommended to be modeled in the MCNP and PLTEMP/ANL full core models of the OPAL reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Demonstrating Safeguards Applications of DRiFT Gas Detector Capabilities [Slides]

DRiFT, a Detector Response Function Toolkit, post-processes MCNP output to model detector response. Three primary components: scintillator (focus of FY 21 TED work), gas detectors (focus of this FY), and semiconductor detectors. Capability to model scintillator detectors has previously been demonstrated.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Alternative Source Verification for the NB5 Beamline

This report details the calculation and comparison of secondary neutron sources for the purpose of performing NB5 velocity selector shielding calculations without relying on the primary HB4 source and the use of a modified MCNP code to run the full model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Methodology to Generate Decay Gamma Sources for the Second Target Station Full Target Assembly

This report details the specifics of applying the Position-Averaged Method to the target wedges and staves. The methodology used to calculate the decay gamma sources for a single target wedge to the calculation of the Second Target Station (STS) target assembly activation and the resulting decay gamma source terms are detailed in this report. The methodology has been applied to the entire STS target assembly including all of the target wedges, staves, shaft, and drive. The target staves and shaft have been vertically segmented to ensure the decay gamma source gradient is sufficiently captured. MCNP ® Code Version 6.2.0 with the RNUCS patch coupled with CINDER2008 from the AARE V1.0 package are the main tools used to calculate the decay gamma source terms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Verification of RESRAD-BUILD Code Version 4

This report documents the verification of the RESRAD-BUILD code, Version 4.0, which was released on December 22, 2022. Two earlier reports verifying Versions 3.0 and 3.1, respectively, were published in 2001 (Kamboj, et al. 2001) and 2003 (Tetra Tech NUS 2003). Version 4.0 of the RESRAD-BUILD code has many new features and modeling enhancements over the earlier versions, including the previously released Version 3.5. Chapter 2 of this report focuses on verifying the external dose and risk modeling for point, line, area, and volume sources, as well as for floor deposition. Besides verification, the external radiation doses calculated by RESRAD-BUILD were also benchmarked with those calculated by the MCNP code (Briemeister 1993). Section J.3 of the RESRAD-BUILD User’s Manual Vol. 1 (Yu et al. 2022) documents the results of that benchmarking effort. Chapter 3 of this report focuses on verifying the ventilation modeling, from checking the remaining source inventory, releases of radionuclides to the air, air concentrations and deposited floor concentrations over time, to the radiation dose and risk associated with inhalation, ingestion, and air submersion, with and without vacuuming. The verification efforts involve designing spreadsheets to perform calculations the same as or like those performed by the RESRAD-BUILD code and then comparing the spreadsheet results with those produced by the code. When the results agree or the differences are within acceptable range, the accuracy of model implementation in the code is verified. In addition to model implementation, the implementation of key functions and features that facilitate the modeling or the use of the code were also verified during the release testing of the code. Appendix A presents the test cases developed for these verification testing, and Appendix B presents the testing results that verify proper implementation of key functions and features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Measured Thermal and Fast Neutrons Fluence Rates for ATF-1 Holders During ATR Cycle 166B

This report contains the thermal (2200 m/s) and fast (E>lMeV) neutron fluence rate data for the ATF-1 holders located in core for ATR Cycle 166B which were measured by the Radiation Measurements Laboratory (RML) as requested by the Power Reactor Programs (ATR Experiments) Radiation Measurements Work Order. This report contains measurements of the fluence rates corresponding to the particular elevations relative to the 80-ft. core elevation. The data in this report consist of (1) a table of the ATR power history and distribution, (2) a hard copy listing of all thermal and fast neutron fluence rates, and (3) plots of both the thermal and fast neutron fluence rates. All "BR" holder monitor wires for this cycle are 56.375 inches long. This length allows measurements from 31.17 inches above core midplane to 19.81 inches below core midplane. The distance from the end of the wires to the first count position was 4.25 inches for all wires counted from this cycle. The monitors were located in an outward small I-holes,1-22 and 1-23. Thermal neutron fluence was determined based on the activation of the CoAl wires and resonance corrections determined in the irradiation of Cycle 152A when the RML measured cadmium-covered as well as bare neutron monitors in the Southwest, Southeast, and H positions at the Center lobe to determine the division in neutron energy between epithermal and thermal neutrons. For more information please refer to letter “Radiation Measurements Laboratory measurements of in core ATR physics testing during cycle 152A. The measured values documented in RML procedure, “ACMM-3600, Flux Monitoring,” will be used indefinitely until further measurements supersede the current values. Fast neutron fluence was determined using the activation of nickel wires. Typically, a fission spectrum averaged cross section (E>1 MeV) is used as determined in detailed measurements described in “ATR Neutron Spectral Characterization,” which gives an effective cross section of 97 mb for the small I-holes. However, those measurements were performed with unfueled experiments. The fast fluence values reported here use a perturbed 114 mb effective>1 MeV spectrum averaged cross section for the small I-holes based on MCNP simulations for a previous fueled experiment in the1-24 position. Refer to “LWR- ATR Irradiation Measured Thermal and Fast Neutron Fluence Rates ATR CYCLE 133A 04/19/04 thru 05/17/04” for more information.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

DRiFT Current Mode, Trigger Settings and Flexible Detector Specifications Applied to Scintillator Arrays

MCNP radiation transport output is post-processed by DRiFT, a Detector Response Function Toolkit to simulate detailed nuclear instrumentation response. DRiFT can be used to assess the performance and potential limitations of scintillator, gas, and semiconductor detectors under a variety of simulated conditions not easily achievable in a laboratory setting. This work describes new updates in DRiFT for scintillator simulations which focus on the capability to simulate scintillators in current mode, an expansion of trigger options, and the ability to customize individual detector properties in a simulation. These improvements are designed to facilitate the ability to model large arrays of scintillator detectors with higher fidelity than was previously possible and are demonstrated in three examples. The first shows the difference between operating DRiFT in current and pulse mode. In the second example, which is intended to demonstrate deviations in individual detector performance, each detector has properties (PMT gain, optical transport, scintillation yield, etc.) that vary between detectors and are specified in DRiFT. A final example examines how DRiFT could be used to optimize digitizer settings in high rate measurements with split signals using the new common trigger option.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Model Validation and Uncertainty Quantification on the KRUSTY Microreactor Design Using GRIFFIN Neutron Transport Code [Poster]

Argonne National Laboratory (ANL) and INL have developed a GRIFFIN steady state neutronics model for the multiphysics simulations of the Kilopower Reactor Using Sterling TechnologY (KRUSTY) microreactor in the Multiphysics Object Oriented Simulation Environment (MOOSE). The reliability of such deterministic neutronics models can be validated by comparing with computations from Monte Carlo codes (e.g. MCNP, SERPENT, OpenMC, Shift, etc). Furthermore, potential modeling/design improvements can be identified by incorporating uncertainty quantification (UQ), which can be performed by MOOSE’s Stochastic Tools Module (STM). KRUSTY is a prototype for a 5-kW thermal nuclear-powered space reactor. Its primary components consist of nuclear fuel, heat pipes, a control rod, a reflector, and the shielding. The fuel consists of 3 stacked U-7.65Mo cylinders with a hole in the center for the control rod. 8 liquid sodium heat pipes transfer fission energy from the solid fuel block to the Sterling power conversion system where the energy is extracted, and the cooled sodium flows back to the core via capillary action . The movable Boron Carbide control rod regulates the neutron population during startup or when a reactor temperature boost is needed . The beryllium oxide reflector is in 3 places in the reactor; it surrounds the core axially, it lies beneath the core on a platen, and it is present in the shim. The axial and lower reflectors rest on an adjustable stainless-steel platen that moves upward to cover the fuel and help the reactor reach criticality. Lastly, radial stainless steel surrounds the core offering protection from radiation exposure .

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Modeling Tungsten Boride Neutronics in ORIGEN for Z-Facility

ORIGEN is one of the main transmutation software packages used in nuclear engineering Modeling Tungsten Boride Neutronics in ORIGEN for Z-Facilityproblems. For the case of this study, tungsten borides are studied using a coupled framework between MCNP and the ORIGEN package of scale. The input used four compositions of tungsten boride: WB with natural boron- 10 abundance, WB with 80wt% B-10 per isotope of boron, WB4 with natural boron-10 abundance, and WB4 with 80wt% B-10 per isotope of boron. Isotopic inventories were produced for WB which show the time dependent change up to 2 years after a 6-Month irradiation. This will allow for further studies of the materials to assess things material composition changes, dose contribution, and waste management requirements.

36 MATERIALS SCIENCE↗
DOE OSTI2024

SCALE 6.3 Validation: Radiation Shielding

Safe and reliable use of scientific and engineering computer codes requires validation for the types of applications in which they will be used. An example in the nuclear reactor engineering and licensing field is radiation transport employed in shielding analyses. The validity of computer codes for shielding applications is demonstrated in this report for SCALE version 6.3.0. Representative benchmarks corresponding to shielding analyses are selected for the validation study. Typical measurement results analyzed from these benchmarks include neutron fluxes, detector count rates, detector energy response functions, neutron and gamma dose rates, neutron activation rates and activities, neutron leakage fluxes, and skyshine dose rates. Thousands of points of comparison between measurement and calculation are presented in this work. Other than rare outliers typically explained by either a lack of information or large uncertainties in the experiment conditions, material, or dimensions, the Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC) radiation transport computer code with built-in variance reduction methods distributed with the SCALE computer code system agrees well with the measurement results. In selected benchmarks, MAVRIC is also compared to Monte Carlo N- Particle® (MCNP® ) 1 calculations. Both computer codes generally agree well within the estimated uncertainties. With the release of SCALE 6.3.0, Shift was integrated as an alternative transport solver in MAVRIC, denoted MAVRIC-Shift. Although the traditional MAVRIC using Monaco was used primarily in this validation study, many results have also been generated using MAVRIC-Shift. Agreement between MAVRIC-Monaco and MAVRIC-Shift is generally very good. The benchmarks presented in this report were obtained from reliable sources such as the International Criticality Safety Benchmark Evaluation Project Handbook, the Shielding Integral Benchmark Archive & Database, and other shielding validation work found in the literature. Additional datapoints and benchmarks will be added to future versions of this report to expand the shielding validation suite.

61 RADIATION PROTECTION AND DOSIMETRY↗