Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “mcnp”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

Neutronics Calculation Advances at Los Alamos: Manhattan Project to Monte Carlo

The history and advances of neutronics calculations at Los Alamos during the Manhattan Project through the present are reviewed. Substantial improvements to neutron diffusion methods and the invention of both the Monte Carlo neutron transport methods in 1947 and deterministic discrete ordinates Sn in 1953 were all made at Los Alamos just after the Manhattan Project. We briefly summarize early simpler and more approximate neutronics methods and then describe the need to better predict neutronics behavior through consideration of theoretical equations, models and algorithms, experimental measurements, and available computing capabilities and their limitations. This paper briefly covers key advances in deterministic methods during the Manhattan Project. These capabilities, coupled with increasing postwar defense needs and the invention of electronic computing with the Electronic Numeric Integrator and Computer, known as ENIAC, and the Mathematical Analyzer Numerical Integrator and Automatic Computer Model, known as MANIAC, led to the creation of Monte Carlo and deterministic discrete ordinates neutronics transport methods. We note the important role that the scientific comradery between the Los Alamos scientists played in the process. This paper briefly covers the early methods, algorithms, computers, and electronic and women pioneers that enabled Monte Carlo to spread to all areas of science. We focus heavily on these early developments and the subsequent creation of the MCNP® code, advances in its associated nuclear data, and its applications to problems of national defense at Los Alamos.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Activation Analysis in Preparation for a Tungsten Irradiation Experiment at LANSCE

To organize the safe handling of activated material, knowing the residual dose rates is crucial. Here, in this work, we present the pre-experiment activation analysis for an experiment in which tungsten blocks are irradiated by 800-MeV protons. In this analysis, we use the Monte Carlo N-Particle (MCNP) code for radiation transport, Attila4MC for unstructured mesh generation, and Activation in Accelerator Radiation Environments (AARE), including CINDER2008, for activation analysis. If the tungsten blocks must be removed within a day after the experiment, then exposure to personnel entering the room must be reduced. One exposure-reduction strategy is to add carbon steel shielding around the tungsten blocks, efficiently reducing the dose from the activated tungsten. However, the shielding becomes activated itself during irradiation: 56Mn is the dominant contributor for short decay times. The actual schedule at the time of the experiment allowed sufficient cool-off time for the tungsten in the room so that additional shielding was not necessary. A less rigorous comparison of the calculated values with the post-experiment measurements showed reasonable agreement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advancing the STS Neutron Moderator Design with an Automated Optimization Workflow and Unstructured Mesh Modeling

With the Second Target Station approaching its final design phase, a detailed neutronics evaluation of its critical components is necessary. Optimizing the dimensions of the two cold-source moderators that are at the heart of this facility presents a multi-objective optimization problem for which an accurate geometric description is crucial. We have applied a fully automated optimization workflow in which a detailed unstructured mesh geometry is automatically generated with Attila4MC, starting from a parametrized CREO geometry followed by preprocessing with SpaceClaim. With this geometry, a MCNP run is performed to calculate the brightness metrics, which are subsequently provided to the optimization algorithm in DAKOTA that provides new parameters and drives the optimization loop until convergence. In this paper, we show the results of the analysis that are used for the final design of the cylindrical and tube moderator. The optimization simulations provide a refinement to and confirmation of the conclusions of the previous design iteration. Additional to the optimization, a sensitivity study is performed to study the effect of minor geometry changes, which is important for the final engineering design. In conclusion, with these studies, we demonstrate that the automated workflow and high-fidelity unstructured mesh modeling are efficient tools for a thorough design evaluation.

DAKOTA↗

Conceptual Spacer Design for the ATR GEN I Target for Pu-238 Production in the Advanced Test Reactor at Idaho National Laboratory

The initial target design used for Pu-238 production at Idaho National Laboratory was designed by Oak Ridge National Laboratory to optimize the production of Pu-238 in the High Flux Isotope Reactor (HFIR) and are referred to as HFIR GEN II targets. To take advantage of the Advanced Test Reactor’s (ATR) taller active core region a redesign of the HFIR GEN II targets was needed. It was proposed to stack two HFIR GEN II targets nose to nose about the core center line; however, this resulted in excessive neutron and photon heating in the pellets located in the center. This peak heating was not desirable so three alternative designs were investigated for the ATR GEN I targets. The python-based code, MCNP to ORIGEN2 in Python (MOPY), was used to calculate the heating rates after 40 days of irradiation to capture the effects of each configuration. The purpose of this paper is to document the details of these conceptual design calculations and comparisons for the ATR GEN I targets.

07 ISOTOPE AND RADIATION SOURCES↗

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks

Confidently designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear applications. This type of analysis relies on matching new nuclear applications with existing benchmark experiments. The Whisper-1.1 software package included in MCNP6.2 ®1 contains more than 1,100 International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks. These benchmarks however rarely match new nuclear applications. The number of benchmarks available to match a given set of materials or geometric configurations varies significantly. Furthermore, recently performed benchmark experiments may not have had enough time to be properly documented and published. Benchmarks are vital for determining the accuracy of nuclear data and can assist nuclear physics and evaluators in improving nuclear data libraries. Exhaustively exploring the parameter space using simulations with software such as MCNP is too computationally expensive. In this work, Gaussian process optimization was implemented to reduce the number of simulations needed for optimization over multiple parameters. This optimization scheme was designed to selectively generate new benchmarks with high sensitivity-based similarity metrics to user-defined nuclear applications. Two benchmark models of spherically nested shells containing plutonium, uranium, tantalum, and water were used in the optimization to match an application containing plutonium plates, stacked in a tantalum reflector, surrounded by water.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Discovery of AMPX Thermal Scattering Law Processing Issue for Solid Moderators

The 2020 edition of The International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook includes a newly produced plastic-moderated evaluation, identified as PU-MET-MIXED-002 and referred to as PMM002. The 2021 edition should include another new plastic-moderated experiment, HEU-MET-THERM-004, referred to as HMT-004. These evaluations are of particular interest, as PMM-002 is moderated with polyethylene, and HMT-004 is moderated with polymethyl methacrylate (Lucite), allowing for investigation of the differences in the thermal scattering laws (TSLs) available for these materials. ENDF/B-VIII.0 includes newly produced data for 1 H-based scattering materials, including Lucite and yttrium hydride. Other available 1 H TSLs include polyethylene, light water, zirconium hydride. The unbound 1 H (free-gas) cross sections were also used. ENDF/B-VIII.0 also includes revisions made to the ENDF/B-VII.1 light water and polyethylene evaluations. Zirconium hydride was unchanged from ENDF/B-VII.1. As of this writing, there are no benchmarks included in the Verified, Archived Library of Inputs and Data (VALID) that are primarily moderated with any solid moderator, so validation that includes the PMM-002 and HMT-004 evaluations would expand the coverage to two new moderators. A study was undertaken at Oak Ridge National Laboratory with two purposes: to provide validation data based on systems that are primarily moderated with polyethylene and Lucite, and to demonstrate the reactivity changes that can result from use of different 1 H TSLs in these plastic-moderated systems. The first objective was mainly to test data and code for SCALE and AMPX, whereas the second objective was to provide useful data for practitioners on the potential variability of predicted $k_{eff}$ based on TSL changes. The use of an exactly correct TSL is often not possible given the materials involved (e.g., lubricants), but this study was intended to provide some indication of the magnitude of the changes among similar materials that can manifest through application of different TSLs in hydrogenous systems over a range of different neutron energy spectra. Unfortunately, the nominal $k_{eff}$ results exposed deviations between SCALE and Monte Carlo N-Particle (MCNP). Some of the results using different TSLs were also unexpected and difficult to explain. An investigation revealed a processing issue in AMPX that was caused by an ambiguous description of the data for incoherent elastic scattering in the ENDF manual. This issue is discussed in detail in a SCALE User Notification, and it affects some solid moderators, but it does not apply to 1 H bound in water. This issue highlights the importance of validating all TSLs used in safety analysis calculations. The remainder of this paper provides a more detailed examination of the results that triggered the investigation and a summary of the findings of that investigation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensitivity-based Similarity Metrics for New Experiment Design Optimization

The nuclear data used in advanced reactor simulations requires validation. Data from nuclear criticality experiments can provide this validation. New nuclear criticality experiment design requires extensive knowledge and expert judgement such that the experimental design parameters are selected in such a way to keep the experiment subcritical. To aide in this experimental design process, professionals can utilize sensitivity and uncertainty analysis. Sensitivity and uncertainty analysis relies on matching new application experiments with currently existing benchmark experiments. Currently, there is functionality in the Whisper 1.1 software package to calculate a similarity metric based on neutron multiplication factor sensitivity coefficients between a new application designed by the user and existing International Criticality Safety Benchmark Experiment Project (ICSBEP) benchmarks. The Whisper 1.1 software package is included in Monte Carlo N-Particle ® Code Version 6.21 (MCNP ® 6.2). This work is geared toward expanding this capability to new similarity metrics based on beta-effective sensitivity coefficients and reactivity coefficient sensitivity coefficients. While the investigation of these sensitivity coefficients is presented in detail in separate works at this same conference, this work will be primarily focused on studying the similarity metrics in more detail. These similarity metrics will then be incorporated into the optimization algorithms used for experiment design in EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data), which is a Los Alamos National Laboratory (LANL) project designed to constrain nuclear data of interest, such that adjustments can be made to possible inaccuracies. A more detailed optimization can be subsequently performed by breaking down these similarity metrics by isotope, reaction, and energy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Designing Critical Experiments Using Gaussian Process Optimization

New nuclear applications may lack similarity between the application and existing ICSBEP benchmarks. Without accurate benchmark data, predictive simulations will have high uncertainty in the estimate of a parameter of interest (such as k eff ). The design of critical experiments tuned for specific applications of interest is one solution to reducing uncertainty in the necessarily nuclear data. We propose an optimization technique to design critical experiments that match the cross-section sensitivities of an application model while minimizing the number of simulation runs in the optimization. The optimization of a critical experiment is slow because the potential design space covers many qualitative variables (types of material and geometries) and corresponding quantitative variables (e.g., material dimensions) and the evaluation of any specific design requires running an expensive code like MCNP1 and Whisper. The optimization of expensive black-box computer codes with quantitative variables has been extensively explored in the literature of design of computer experiments. We propose a modified version of standard Gaussian process (GP) optimization that optimizes over multiple discrete configurations of qualitative variables in parallel which reduces the computational cost of the entire optimization. The goal of this work is to minimize the number of MCNP evaluations while still exploring many different design configurations in parallel.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

MCNP6 Class

This report provides a Monte Carlo method for simulating radiation transport and provides a common sense approach for MCNP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

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↗

Organic Scintillator Detector Response Simulations with DRiFT

Accurate detector modeling is a requirement to design systems in many non-proliferation scenarios; by determining a Detector’s Response Function (DRF) to incident radiation, it is possible characterize measurements of unknown sources. DRiFT is intended to post-process MCNP® output and create realistic detector spectra. Capabilities currently under development include the simulation of semiconductor, gas, and (as is discussed in this work) scintillator detector physics. Energy spectra and pulse shape discrimination (PSD) trends for incident photon and neutron radiation have been reproduced by DRiFT.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

User Manual for Whisper-1.1

Whisper is a statistical analysis package developed in 2014 to support nuclear criticality safety (NCS) validation [1-3]. It uses the sensitivity profile data for an application as computed by MCNP6 [4-6] along with covariance files [7,8] for the nuclear data to determine a baseline upper-subcritical-limit (USL) for the application. Whisper version 1.0 was first developed and used at LANL in 2014 [3]. During 2015- 2016, Whisper was updated to version 1.1 and is to be included with the upcoming release of MCNP6.2. This document describes the user input and options for running whisper-1.1, including 2 perl utility scripts that simplify ordinary NCS work, whisper_mcnp.pl and whisper_usl.pl. For many detailed references on the theory, applications, nuclear data & covariances, SQA, verification-validation, adjointbased methods for sensitivity-uncertainty analysis, and more – see the Whisper – NCS Validation section of the MCNP Reference Collection at mcnp.lanl.gov. There are currently over 50 Whisper reference documents available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

JM-1 SLOWPOKE-II Research Reactor Supporting Analysis Report for the Conversion from HEU to LEU

The JM-1 research reactor (SLOWPOKE-2 type) at the International Centre for Nuclear and Environmental Sciences (ICENS) of the University of West Indies, in Kingston (Jamaica), was successfully converted from HEU to LEU fuel on September 2015. As part of the work to produce the corresponding Safety Analysis Report (SAR), which was to be reviewed and approved by the Jamaican regulator in order to provide authorization for the reactor commissioning, a detailed safety analysis was carried out. This analysis, involving a variety of calculations, is summarized in the present report; describing the basic methodology and the obtained results. The report covers both the neutronic and thermal hydraulic aspects of the analysis, for which MCNP and PLTEMP/ANL codes, respectively, were used. On one hand, the HEU core was modeled and analyzed, subsequently comparing the obtained results with the available experimental data. On the other hand, the modifications involved with the change to an LEU core were introduced into the models and the results examined to ensure that the differences in the expected behavior did not negatively affect the reactor safety or performance. In fact, the LEU core was found to present significant advantages in different areas. Consequently, the present report provided a solid basis for the SAR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Big Ten MCNP6 Unstructured Mesh Benchmark

The purpose of this report is to document a benchmarking effort for the MCNP6 Unstructured Mesh (UM) geometry description method applied to a large and fairly complex critical assembly, Big Ten. A secondary goal of this effort is to provide a set of best practices for modeling a critical assembly with the MCNP UM method. Specification of geometry using UM requires creating a mesh from a solid geometry model and there are some important considerations when using this method for criticality problems. These considerations will be discussed along with suggested practices for correctly modeling these types of problems.

97 MATHEMATICS AND COMPUTING↗

sUAS Support for Mars 2020

The release of airborne radioactive material presents a health risk hazard to many individuals, including emergency responders and the public. Characterizing the unknown radioactive dangers produced during such incidents is essential. An advantage to utilizing unmanned aerial systems in this effort is the reduction of risk to personnel otherwise tasked with characterization, as well as more quickly obtaining data points during cloud immersion. By pairing a continuous air monitor (CAM) and detector with a drone, quantification of unknown material in the plume can be determined, and thus the extent of dose to people in the area can be estimated. A small, low-flow air sampler with a Geiger-Mueller counter may be characterized using experimental measurements of point sources representing a cloud of material and modelled using the Monte Carlo N-Particle Transport Code (MCNP), a software package for simulating nuclear processes, to find the usefulness and advantages of the system for detection of nuclides of concern in various nuclear plume scenarios. The flying time of small-unmanned aircraft systems (sUASs) is limited; thus, the minimum detectable activity and concentration rates possible must be determined over the system’s window of operation. While the activity concentrations corresponding to external and internal doses of concern can be detected with certainty for 90 Sr and 137 Cs in a plume, those corresponding to 238 Pu are more difficult to detect. The central principle of employing the sUAS is that the cockpit does not have an operator onboard the aircraft; therefore, control of the aircraft must take place by other means. With a sUAS, command and control can be separated into three distinct methods: (1) ground control or remote piloting, (2) semi-autonomous control, and (3) autonomous control. The isotope 238 Pu is used in the space industry, providing long-lived heat generation for fuel in outer space (NASA 2014). Due to the inherent risks with rocket launches to get objects into space, monitoring for release of these hazardous substances is a major undertaking. The current means is through employment of environmental CAMs. It is conceivable, however, that drone monitoring for release of 238 Pu in the event of a space launch mishap would give a greater chance of detection of plutonium particulate, because the particulate’s diffusion in air upon settling to the ground would make the probability of collecting a particle on a filter in a CAM very low.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Re-Release of the ENDF/B VIII.0 S(α,β) Data Processed by NJOY2016

“ENDF/B-VIII.0 provides a major update to the ENDF thermal scattering library. Indeed, it is nearly a completely new sub-library. Only the legacy evaluations for Al, Fe, liquid and solid methane, ortho- and para- hydrogen and deuterium and benzene and the ENDF/B-VII.1 evaluations for SiO2 are unchanged.” Thirty-four (34) materials are provided in ENDF/B-VIII.0 with a total of two hundred and fifty-three (253) evaluations. LEAPR input files are also included for each of the materials as well as “readme” files for most of the materials. All of these 34 thermal scattering files have been re-processed with NJOY2016 (version 53) to produce 253 ACE files suitable for use in MCNP or other similar codes. Table 1 lists the 34 materials which are included in the ENDF/B-VIII.0 thermal scattering library and also notes where major changes have occurred in the re-release.

36 MATERIALS SCIENCE↗

Coincident Capture through Post-processing PTRAC [Slides]

This presentation discusses the new PTRAC capabilities and workflows. The PTRAC capability in MCNP6.3 has seen a massive overhaul since MCNP6.2. The new HDF5 file format allows for both MPI- and thread-based parallelism. MCNPTools has been updated to handle the new HDF5 PTRAC format and is now open sourced on GitHub. Built-in capabilities, such as the pulse-height tally coincident capture special treatment, can largely be replicated through separate postprocessing scripts that leverage both PTRAC and MCNPTools. This allows for greater flexibility in user-specified and controlled detector response functionality, ultimately using the MCNP code for what it is best at (i.e., particle transport).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Open-source release of CGMF 1.1 and Integration into the MCNP6.3 ® Code [Slides]

As a result of a multi-year NA-22 project, CGMF was integrated into MCNP6.2 and publicly released. CGMF was open-sourced and publicly released and MCNP6.3 was updated to include the latest version and is in the process of being publicly released. Current and future plans include global optimization and uncertainty quantification within CGMF, model parameter fitting such that CGMF may be used in ENDF/B evaluations, and improving both standalone and MCNP-integrated CGM (non-fission) simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗