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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

ADVANTG An Automated Variance Reduction Parameter Generator

The AutomateD VAriaNce reducTion Generator (ADVANTG) software automates the generation of variance reduction (VR) parameters for continuous-energy Monte Carlo simulations of fixed-source neutron, photon, and coupled neutron-photon transport problems using MCNP5 (X-5 Monte Carlo Team 2003). ADVANTG generates space- and energy dependent mesh-based weight-window bounds and biased source distributions from three dimensional (3-D) discrete ordinates (SN) calculations that are performed by the Denovo package (Evans et al. 2010). The deterministic calculations can be performed using multiple cores and/or processors (e.g., on multi-core desktop systems and clusters). The final variance reduction parameters are output in a format that can be used with unmodified versions of MCNP. The primary objective of the development of ADVANTG has been to reduce both the user effort and the computational time required to obtain accurate and precise tally estimates across a broad range of challenging transport application areas.

ADVANTG↗
DOE OSTI2018

Dose Rate Evaluation for the ES-3100 Package with HEU Content Using MCNP, ADVANTG, Monaco, and MAVRIC

Here, this paper presents a comparative study of dose rate calculations for the ES-3100 package with highly enriched uranium (HEU) content for different source configurations using computer codes: (1) MCNP; (2) Automated Variance Reduction Generator (ADVANTG)/MCNP; (3) Monaco; and (4) Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). The Model ES-3100 package was developed at the Y-12 National Security Complex for domestic and international transportation of Type B fissile radioactive material. In this study, six different source configurations (i.e., solid cylinder, cylindrical hemi-shell, cylindrical shell, rectangular plate, cylindrical rod, or cylindrical segment form) having 36 kg of HEU metal inside the package containment vessel (based on configurations in the ES-3100/HEU safety analysis report for packaging) are evaluated. Dose rates at the package surfaces and 1 m from the package surfaces are calculated for these different source configurations. MCNP and Monaco cases are run without any biasing options to accelerate the convergence. Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods developed at the Oak Ridge National Laboratory are implemented in ADVANTG/MCNP and MAVRIC codes to accelerate the convergence. ADVANTG generates variance reduction parameters using Denovo code, and MCNP is used with the variance reduction parameters to accelerate the convergence. MAVRIC uses Denovo code to construct an importance map and a biased source distribution that are supplied to Monaco to accelerate the Monte Carlo simulation. The FW-CADIS option in ADVANTG and MAVRIC is used to accelerate the convergence in this study. The accelerated convergence cases (ADVANTG/MCNP and MAVRIC) are about 100 times faster with 100 times less particle simulation than those cases run without biasing options (analog MCNP and analog Monaco). Lastly, the MCNP, ADVANTG/MCNP, Monaco, and MAVRIC calculated dose rates at the package surfaces and at 1 m from the package surfaces for the different source configurations are compared and are found to be in general agreement.

42 ENGINEERING↗
DOE OSTI2018

Dose Rate Evaluation for the ES-3100 Package with HEU Content Using MCNP, ADVANTG, Monaco, and MAVRIC

This paper presents a comparative study of dose rate calculations for the ES-3100 package with highly enriched uranium (HEU) content for different source configurations using computer codes: (1) MCNP; (2) Automated Variance Reduction Generator (ADVANTG)/MCNP; (3) Monaco; and (4) Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). The Model ES-3100 package was developed at the Y-12 National Security Complex for domestic and international transportation of Type B fissile radioactive material. In this study, six different source configurations (i.e., solid cylinder, cylindrical hemi-shell, cylindrical shell, rectangular plate, cylindrical rod, or cylindrical segment form) having 36 kg of HEU metal inside the package containment vessel (based on configurations in the ES-3100/HEU safety analysis report for packaging) are evaluated. Dose rates at the package surfaces and 1 m from the package surfaces are calculated for these different source configurations. MCNP and Monaco cases are run without any biasing options to accelerate the convergence. Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods developed at the Oak Ridge National Laboratory are implemented in ADVANTG/MCNP and MAVRIC codes to accelerate the convergence. ADVANTG generates variance reduction parameters using Denovo code, and MCNP is used with the variance reduction parameters to accelerate the convergence. MAVRIC uses Denovo code to construct an importance map and a biased source distribution that are supplied to Monaco to accelerate the Monte Carlo simulation. The FW-CADIS option in ADVANTG and MAVRIC is used to accelerate the convergence in this study. The accelerated convergence cases (ADVANTG/MCNP and MAVRIC) are about 100 times faster with 100 times less particle simulation than those cases run without biasing options (analog MCNP and analog Monaco). The MCNP, ADVANTG/MCNP, Monaco, and MAVRIC calculated dose rates at the package surfaces and at 1 m from the package surfaces for the different source configurations are compared and are found to be in general agreement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Shielding Benchmark Comparison - MCNP6.2

This report documents the calculations performed for a shielding code comparison between various Department of Energy (DOE) sites. These shielding calculations were performed using an experiment drawn from the International Handbook of Evaluated Criticality Safety Benchmark Experiments, published by the Organisation for Economic Cooperation and Development/Nuclear Energy Agency (OECD/NEA). The benchmark selected for comparison is ALARM-CF-AIR-LAB-001 (“Neutron Fields in the Three-Section Concrete Labyrinth from Cf-252 Source, Benchmark ALARM CF AIR LAB-001”). The Y-12 submission for this code comparison was performed with Monte Carlo N Particle (MCNP) Transport Code System, Version 6.2 and Automated Variance Reduction Generator (ADVANTG).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

ADVANTG—An Automated Variance Reduction Parameter Generator (Rev. 1)

The primary objective of ADVANTG is to reduce both the user effort and the computational time required to obtain accurate and precise tally estimates across a broad range of challenging transport applications. ADVANTG has been applied to simulations of real-world radiation shielding, detection, and neutron activation problems. Examples of shielding applications include material damage and dose rate analyses of the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source and High Flux Isotope Reactor (Risner and Blakeman 2013) and the ITER Tokamak (Ibrahim et al. 2011). ADVANTG has been applied to a suite of radiation detection, safeguards, and special nuclear material movement detection test problems (Shaver et al. 2011). ADVANTG has also been used in the prediction of activation rates within light water reactor facilities (Pantelias and Mosher 2013). In these projects, ADVANTG was demonstrated to significantly increase the tally figure of merit (FOM) relative to an analog MCNP simulation. The ADVANTG-generated parameters were also shown to be more effective than manually generated geometry splitting parameters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Oak Ridge National Laboratory Shutdown Dose Rate Code Suite

The Oak Ridge National Laboratory (ORNL) shutdown dose rate (SDDR) code suite calculates gamma dose rates at a location of interest due to activation of materials. The code suite is based on the rigorous two-step (R2S) method that involves two radiation transport calculations: (1) neutron radiation transport to determine neutron fluxes in the material for which activation calculations will be performed and (2) gamma radiation transport to determine dose rates at a location of interest, due to material activation. The ORNL SDDR code suite is used to determine an importance function that characterizes the neutron’s importance to the final SDDR when the Monte Carlo radiation transport method is used. This report demonstrates how the ORNL SDDR code suite is implemented through the following codes: Monte Carlo N-Particle (MCNP) code Version 5-1.60, Oak Ridge Isotope Generator (ORIGEN), MSX suite of utilities, Neutron Activation Gamma Source Sampler (NAGSS), and Automated Variance Reduction Generator (ADVANTG). For this demonstration, the International Thermonuclear Experimental Reactor (ITER) SDDR benchmark problem is used and the dose rate result is compared to previously published work.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Comparison of ADVANTG Simulations to Simple Shielding Measurements - Paper 36

Monte Carlo (MC) radiation transport simulations, like those performed using Monte Carlo N-Particle (MCNP), can be highly accurate but require time to reduce the statistical uncertainties in the calculated detector response(s). Many different 'variance reduction' techniques devised over the years increase the efficiency of MC calculations, but these methods can be more art than science. Many of these methods are problem specific or require careful tuning of parameters for good performance. One of the best variance reduction methods, in terms of both reliable performance increases and ease of use, is the use of weight windows. Weight windows are derived from an importance map in space and energy that allows the transport code to focus more simulation time on particles that have a higher likelihood of being important to the final detector response. Less time is spent simulating particles that have little chance of making a contribution to the detector response. MCNP already includes the abilities to generate and use weight windows. Unfortunately, generating weight windows can take a very long time, perhaps longer than the original problem. Oak Ridge National Laboratory has led the development of hybrid methods using a discrete ordinates adjoint calculation to quickly develop an importance map (weight windows) for use in a Monte Carlo code. The Consistent Adjoint Driven Importance Sampling (CADIS) method uses an adjoint calculation to develop both an importance map and a biased source distribution that work together. This method is reasonably automatic, is easy to use, and has been implemented in the Automated Variance reduction Generator (ADVANTG) package that works with MCNP5. ADVANTG reads an MCNP input file and a small amount of extra user information and then runs an adjoint deterministic calculation using Denovo. The importance map and biased source distribution derived from the CADIS method can then be incorporated back into the original MCNP input file to enhance the figure-of-merit (FOM) of the calculation. The FOM is a measure of the efficiency of the calculation using the amount of run time and corresponding level of statistical uncertainty in the detector result. ADVANTG-enhanced MCNP input files have been shown to increase the FOM of many types of problems, obtaining the same level of statistical uncertainty in a shorter time compared to standard MCNP. ADVANTG can also generate variance reduction parameters (importance map and biased source) using the Forward-Weighted CADIS (FW-CADIS) method for optimizing mesh tallies. The CADIS method creates variance reduction parameters that optimize a tally's total quantity (flux, dose rate, interaction rate, etc.) and will not generally increase performance for all parts of a segmented tally. To optimize a segmented tally, the FW-CADIS method uses two discrete ordinates calculations to make variance reduction parameters that help compute a segmented tally with uniform relative uncertainties in each bin. This report will demonstrate that using ADVANTG for neutron and photon radiation shielding problems will (1) preserve the standard MCNP results and (2) obtain those results either with less statistical uncertainty or in shorter times than the standard MCNP calculation. The four demonstration problems in this report are based on simple neutron or photon transmission measurements through different materials. All of the problems here used the CADIS method and still saw improvement across the flux tallies segmented by particle energy. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Analysis of Radiation Transport Due to Activated Coolant in the ITER Neutral Beam Injection Cell

Detailed spatial distributions of the biological dose rate due to a variety of sources are required for the design of the ITER tokamak facility to ensure that all radiological zoning limits are met. During operation, water in the Integrated loop of Blanket, Edge-localized mode and vertical stabilization coils, and Divertor (IBED) cooling system will be activated by plasma neutrons and will flow out of the bioshield through a complex system of pipes and heat exchangers. This paper discusses the methods used to characterize the biological dose rate outside the tokamak complex due to 16 N gamma radiation emitted by the activated coolant in the Neutral Beam Injection (NBI) cell of the tokamak building. Activated coolant will enter the NBI cell through the IBED Primary Heat Transfer System (PHTS), and the NBI PHTS will also become activated due to radiation streaming through the NBI system. To properly characterize these gamma sources, the production of 16 N, the decay of 16 N, and the flow of activated water through the coolant loops were modeled. The impact of conservative approximations on the solution was also examined. Once the source due to activated coolant was calculated, the resulting biological dose rate outside the north wall of the NBI cell was determined through the use of sophisticated variance reduction techniques. The AutomateD VAriaNce reducTion Generator (ADVANTG) software implements methods developed specifically to provide highly effective variance reduction for complex radiation transport simulations such as those encountered with ITER. Using ADVANTG with the Monte Carlo N-particle (MCNP) radiation transport code, radiation responses were calculated on a fine spatial mesh with a high degree of statistical accuracy. In conclusion, advanced visualization tools were also developed and used to determine pipe cell connectivity, to facilitate model checking, and to post-process the transport simulation results.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Preliminary Assessment of the Impact on Reactor Vessel dpa Rates Due to Installation of a Proposed Low Enriched Uranium (LEU) Core in the High Flux Isotope Reactor (HFIR)

An assessment of the impact on the High Flux Isotope Reactor (HFIR) reactor vessel (RV) displacements-per-atom (dpa) rates due to operations with the proposed low enriched uranium (LEU) core described by Ilas and Primm has been performed and is presented herein. The analyses documented herein support the conclusion that conversion of HFIR to low-enriched uranium (LEU) core operations using the LEU core design of Ilas and Primm will have no negative impact on HFIR RV dpa rates. Since its inception, HFIR has been operated with highly enriched uranium (HEU) cores. As part of an effort sponsored by the National Nuclear Security Administration (NNSA), conversion to LEU cores is being considered for future HFIR operations. The HFIR LEU configurations analyzed are consistent with the LEU core models used by Ilas and Primm and the HEU balance-of-plant models used by Risner and Blakeman in the latest analyses performed to support the HFIR materials surveillance program. The Risner and Blakeman analyses, as well as the studies documented herein, are the first to apply the hybrid transport methods available in the Automated Variance reduction Generator (ADVANTG) code to HFIR RV dpa rate calculations. These calculations have been performed on the Oak Ridge National Laboratory (ORNL) Institutional Cluster (OIC) with version 1.60 of the Monte Carlo N-Particle 5 (MCNP5) computer code.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

ACCELERATING FUSION REACTOR NEUTRONICS MODELING BY AUTOMATIC COUPLING OF HYBRID MONTE CARLO/DETERMINISTIC TRANSPORT ON CAD GEOMETRY

Detailed radiation transport calculations are necessary for many aspects of the design of fusion energy systems (FES) such as ensuring occupational safety, assessing the activation of system components for waste disposal, and maintaining cryogenic temperatures within superconducting magnets. Hybrid Monte Carlo (MC)/deterministic techniques are necessary for this analysis because FES are large, heavily shielded, and contain streaming paths that can only be resolved with MC. The tremendous complexity of FES necessitates the use of CAD geometry for design and analysis. Previous ITER analysis has required the translation of CAD geometry to MCNP5 form in order to use the AutomateD VAriaNce reducTion Generator (ADVANTG) for hybrid MC/deterministic transport. In this work, ADVANTG was modified to support CAD geometry, allowing hybrid (MC)/deterministic transport to be done automatically and eliminating the need for this translation step. This was done by adding a new ray tracing routine to ADVANTG for CAD geometries using the Direct Accelerated Geometry Monte Carlo (DAGMC) software library. This new capability is demonstrated with a prompt dose rate calculation for an ITER computational benchmark problem using both the Consistent Adjoint Driven Importance Sampling (CADIS) method an the Forward Weighted (FW)-CADIS method. The variance reduction parameters produced by ADVANTG are shown to be the same using CAD geometry and standard MCNP5 geometry. Significant speedups were observed for both neutrons (as high as a factor of 7.1) and photons (as high as a factor of 59.6).

Biondo, Elliott D↗
DOE OSTI2016

Acceleration Techniques using ADVANTG for the MDF Design and Optimization

The Spallation Neutron Source (SNS) facility at Oak Ridge National Laboratory (ORNL) is implementing a Moderator Demonstration Facility (MDF) to demonstrate the performance characteristics of advanced moderators central to the Second Target Station (STS) for SNS. The MDF will provide a small, short-pulsed neutron source for slow neutron production in which we intend to easily and quickly change from one moderator concept to another, characterizing the performance of each moderator in a reproducible and consistent fashion. The MDF will be unique and innovative amongst the world's moderator test facilities in that it will be intended to be very prototypic in terms of 'moderator illumination' - the spatial variation of the neutron flux entering the moderator itself - as well as capable of testing so-called high-brightness moderators in a wing configuration. During the design phase of the MDF, the Monte Carlo N-Particle transport code MCNPX v.2.7.0 is being used as the primary tool for the neutronic analysis of the facility and characterization of the moderator performance. The Automated Variance Reduction Generator (ADVANTG) code is being utilized to accelerate the MCNPX calculations. The ADVANTG code generates space- and energy-dependent weight window parameters for a successive MCNP run by calculating the adjoint flux with the Denovo discrete ordinates code based on the user defined MCNP tally. We have tested various strategies using ADVANTG to generate weight window parameters to efficiently calculate detailed moderator performance. Using point detector response functions for weight window parameter optimization with ADVANTG did not work well for improving the efficiency of Monte Carlo calculations of neutron emission into beam lines. However, using cell fluxes of the area of highest contributions to the point detector for the variance reduction parameter analysis worked very well and improved the FOM of the calculation of neutron emission into a beamline by a factor of 50 over the unbiased case. (authors)

42 ENGINEERING↗
DOE OSTI2014

FW-CADIS Method for Global and Regional Variance Reduction of Monte Carlo Radiation Transport Calculations

This paper presents a hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is an extension of the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for more than a decade to very effectively improve the efficiency of Monte Carlo calculations of localized quantities (e.g., flux, dose, or reaction rate at a specific location). The basis of this method is the development of an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space-and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain more uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented and demonstrated within the MAVRIC (Monaco with Automated Variance Reduction using Importance Calculations) sequence of SCALE and the ADVANTG (Automated Deterministic Variance Reduction Generator)/MCNP framework. Application of the method to representative real-world problems, including calculation of dose rate and energy-dependent flux throughout the problem space, dose rates in specific areas, and energy spectra at multiple detectors, is presented and discussed. Results of the FW-CADIS method and other recently developed global variance-reduction approaches are also compared, and the FW-CADIS method outperformed the other methods in all cases considered.

Wagner, John C↗
DOE OSTI2026

Analysis of Second Target Station Target Removal Dose Rates

The Second Target Station (STS) project at Oak Ridge National Laboratory’s spallation neutron source is a crucial initiative for maintaining U.S. leadership in neutron sciences. The STS aims to create the world’s brightest pulsed cold neutron source, enabling cutting-edge research across various scientific disciplines. To ensure safe and efficient maintenance operations, understanding the effects of shutdown dose rates from activated components within the STS target systems is essential. This study establishes a computational framework for calculating decay gamma sources and subsequent shutdown dose rates utilizing advanced methods to account for all activation channels, including high-energy interactions down to thermal neutron capture. This study describes a novel integration of multiple tools and provides an effective means of analyzing activation and shutdown dose rates at spallation neutron facilities. A custom-developed script automates the decay gamma source generation process, ensuring proper sampling during the variance reduction phase, which is critical for accurate predictions of shutdown dose rates.

Transmutation↗
DOE OSTI2020

HFIRCON Version 1.0.5 User Guide

The High Flux Isotope Reactor (HFIR) Controller (HFIRCON) code is a collection of python routines and C plugins that automate the workflow for fuel and single- or multicycle target depletion analyses for HFIR at Oak Ridge National Laboratory (ORNL). This code calls the LAVAMINT (LAVA Model Interrogator) parallel (MCNP) Monte Carlo N-Particle model interrogator to stochastically calculate cell volumes and bounding boxes, the ADVANTG (Automatic Variance Reduction Generation) code package for all variance reduction and source biasing calculations, the ORNL-Transformative Neutronics/MCNP5 transport solver for all transport solutions, and the MSX_DEPLETE module to perform all depletion calculations via the ORIGEN (Oak Ridge Isotope Generation) application programming interface. It also performs a robust set of postprocessing functions to automatically provide summaries of several key metrics that are common to a wide variety of typical HFIR design and safety-basis analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

SU-G-TeP1-05: Development and Clinical Introduction of Automated Radiotherapy Treatment Planning for Prostate Cancer

Purpose: To develop an automated radiotherapy treatment planning and optimization workflow for prostate cancer in order to generate clinical treatment plans. Methods: A fully automated radiotherapy treatment planning and optimization workflow was developed based on the treatment planning system Monaco (Elekta AB, Stockholm, Sweden). To evaluate our method, a retrospective planning study (n=100) was performed on patients treated for prostate cancer with 5 field intensity modulated radiotherapy, receiving a dose of 35×2Gy to the prostate and vesicles and a simultaneous integrated boost of 35×0.2Gy to the prostate only. A comparison was made between the dosimetric values of the automatically and manually generated plans. Operator time to generate a plan and plan efficiency was measured. Results: A comparison of the dosimetric values show that automatically generated plans yield more beneficial dosimetric values. In automatic plans reductions of 43% in the V72Gy of the rectum and 13% in the V72Gy of the bladder are observed when compared to the manually generated plans. Smaller variance in dosimetric values is seen, i.e. the intra- and interplanner variability is decreased. For 97% of the automatically generated plans and 86% of the clinical plans all criteria for target coverage and organs at risk constraints are met. The amount of plan segments and monitor units is reduced by 13% and 9% respectively. Automated planning requires less than one minute of operator time compared to over an hour for manual planning. Conclusion: The automatically generated plans are highly suitable for clinical use. The plans have less variance and a large gain in time efficiency has been achieved. Currently, a pilot study is performed, comparing the preference of the clinician and clinical physicist for the automatic versus manual plan. Future work will include expanding our automated treatment planning method to other tumor sites and develop other automated radiotherapy workflows.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Evaluation of PBR Spent Fuel Criticality and Dose Rate Compliance for Storage and Transportation

Spent tri-structural isotropic (TRISO)–based fuels have a strong track record in storage and transportation without documented incidents. This work seeks to reduce uncertainty to aid in more informed spent fuel management of TRISO-based fuels by modeling both fresh and spent pebble bed reactor (PBR) fuel and comparing the results to the regulatory standards from 10 CFR 71. SCALE was used for all modeling due to it having fast and accurate methods for handling PBR fuel modeling, as well as having an efficient method for shielding calculations in monaco with automated variance reduction using importance calculations (MAVRIC), which utilizes the consistent adjoint-driven importance sampling (CADIS) and the forward-weighted consistent adjoint-driven importance sampling (FW-CADIS) methods. KENO-VI was used for all criticality calculations, TSUNAMI was used for uncertainty quantification on k-effective, TRITON and the Oak Ridge isotope generation code (ORIGEN) were both used for depletion of the fuel, and MAVRIC was used for shielding calculations. For criticality assessments, this study focused on the requirement that the value of the neutron multiplication factor, k-effective (k-eff), would not exceed a peak value of 0.95, including uncertainty, with 95% confidence. Criticality was initially examined by modeling fresh fuel from three different designs—HTR-10 fuel, PBMR-400 fuel, and demonstration fuel representative of a TRISO-fueled modern high-temperature gas reactor (HTGR) design, henceforth referred to as Demo HTGR—and placing them into various sized containers with conditions described in 10 CFR 71 to quantify the peak k-eff state. When the peak value of 0.95 k-eff was exceeded, mitigation methods were examined in those scenarios. Burnup credit, pebble displacement in areas of strong neutron multiplication, and random pebble replacement using pebbles of various compositions and replacement fractions were examined. In summary, the criticality of PBR fuels can be well accounted for by restricting container size, taking credit for burnup, or by displacing/replacing pebbles. Uncertainty of the k-eff due to nuclear data uncertainties was recorded at ~0.6644%Δk/k, or roughly 664% mil (pcm). The nuclear data–induced uncertainty was relatively small and should not require significant modification in the design to be accounted for. Revisions to the evaluated nuclear data file values have been shown to have a larger impact than nuclear data–induced uncertainty. For dose rate aspects, U.S. Nuclear Regulatory Commission regulations require a maximum dose rate of 10 millirem per hour (mrem/h) at 2 meters. In examining the dose rate behavior of spent PBR fuel, the representative Demo HTGR fuel was modeled exclusively due to it possessing the highest target burnup of the examined fuels. Equilibrium cycle modeling methods were used to produce a higher-fidelity discharge isotopic composition than simple assumptions, such as reflected pebbles. The discharge composition was used as a source term in the fixed-source transport shielding calculations, and dose rates were calculated at 2 m for the shortest possible cooling time. The low concentration of fuel material led to dose rates that were in line with regulatory limits, despite the high burnup when compared to traditional light water reactor fuels. In conclusion, the methods employed in this study would require more work to further verify and validate and are limited to the criticality and dose rate analyses performed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

SCALE Enhancements for Detailed Cask Dose Rate Analysis - Paper 37

The Nuclear Fuels Storage and Transportation Planning Project and the Used Fuel Disposition Campaign, both under the US Department of Energy (DOE) Office of Nuclear Energy, require the ability to predict k{sub eff}, heat generation and temperature distributions, and external dose rates from any combination of commercial spent nuclear fuel assemblies loaded into any type of licensed cask. Work in the Reactor and Nuclear Systems Division at Oak Ridge National Laboratory has begun to develop the UNF-ST[and]DARDS system (Used Nuclear Fuel Storage, Transportation and Disposal Analysis Resource and Data System) that uses many of the nuclear analysis codes from the SCALE package, a comprehensive database of used nuclear fuel inventories from utilities, and a library of model template files to produce complete input files for the various types of UNF computational analyses. UNF-ST[and]DARDS uses the template files and input parameters that are applicable to a safety analysis to assemble and execute a complete input file, collect the output files and relevant information for subsequent calculations, and illustrate calculation results as a function of decay time and other relevant analysis parameters. This paper will focus on the shielding aspects and the ability to predict external dose rates from as-loaded casks. Realistic dose rate values based on actual canister fuel contents may be used in developing appropriate plans, procedures, and methods to keep personnel radiation exposures as low as reasonably achievable during cask repackaging and transportation operations, as well as in performing total system analyses and transportation risk evaluations. The MAVRIC shielding sequence of the SCALE package was created for the US Nuclear Regulatory Commission for analyzing dose rates outside of storage, transfer, or transportation casks loaded with spent nuclear fuel. MAVRIC contains automated variance reduction capabilities based on the CADIS and FW-CADIS methods that are effective for optimizing deep penetration Monte Carlo shielding problems for achieving low relative uncertainties in short computing times. MAVRIC uses the Denovo discrete ordinates code to compute importance maps and biased source terms for the Monaco fixed-source Monte Carlo code, which can use multi-group or continuous-energy cross section data. ORIGEN (Oak Ridge Isotope Generation and Depletion) is the SCALE computer code for calculating time-dependent isotopic concentrations during irradiation and decay for more than 2,200 nuclides that can be produced by nuclear fuel irradiation and activation. A series of SCALE enhancements was implemented to enable automatic decay heat and radiation source term generation and shielding safety analysis of as-loaded casks. The enhancements to SCALE made under this project will be a part of the SCALE 6.2 release expected in fall 2014. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

SU-C-207B-05: Tissue Segmentation of Computed Tomography Images Using a Random Forest Algorithm: A Feasibility Study

Purpose: Develop an automated Random Forest algorithm for tissue segmentation of CT examinations. Methods: Seven materials were classified for segmentation: background, lung/internal gas, fat, muscle, solid organ parenchyma, blood/contrast, and bone using Matlab and the Trainable Weka Segmentation (TWS) plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance each evaluated over a pixel radius of 2n, (n = 0–4). Also noise reduction and edge preserving filters, Gaussian, bilateral, Kuwahara, and anisotropic diffusion, were evaluated. The algorithm used 200 trees with 2 features per node. A training data set was established using an anonymized patient’s (male, 20 yr, 72 kg) chest-abdomen-pelvis CT examination. To establish segmentation ground truth, the training data were manually segmented using Eclipse planning software, and an intra-observer reproducibility test was conducted. Six additional patient data sets were segmented based on classifier data generated from the training data. Accuracy of segmentation was determined by calculating the Dice similarity coefficient (DSC) between manual and auto segmented images. Results: The optimized autosegmentation algorithm resulted in 16 features calculated using maximum, mean, variance, and Gaussian blur filters with kernel radii of 1, 2, and 4 pixels, in addition to the original CT number, and Kuwahara filter (linear kernel of 19 pixels). Ground truth had a DSC of 0.94 (range: 0.90–0.99) for adult and 0.92 (range: 0.85–0.99) for pediatric data sets across all seven segmentation classes. The automated algorithm produced segmentation with an average DSC of 0.85 ± 0.04 (range: 0.81–1.00) for the adult patients, and 0.86 ± 0.03 (range: 0.80–0.99) for the pediatric patients. Conclusion: The TWS Random Forest auto-segmentation algorithm was optimized for CT environment, and able to segment seven material classes over a range of body habitus and CT protocol parameters with an average DSC of 0.86 ± 0.04 (range: 0.80–0.99).

60 APPLIED LIFE SCIENCES↗