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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

MontePy: a Python library for reading, editing, and writing MCNP input files.

The Monte Carlo N-Particle (MCNP) radiation transport code is a highly capable and accurate code with a long legacy. MCNP uses the Monte Carlo simulation process to simulate the path of particles (e.g., neutrons, photons, charged particles, etc.), and their interaction with materials. It is widely used in nuclear engineering, high-energy physics, and other fields. Its origins in the mid-twentieth century predate many modern software conventions. MCNP users provide an input file to MCNP, which it then uses to create an internal representation of the simulation problem. These input files originally had to be stored as punchcard decks, and the user manual still uses the terminology of cards and decks, despite moving beyond punchcards. MCNP predates nearly all modern human readable markup or data serialization languages, such as the extensible Markup Language (XML), the Standard Generalized Markup Language (SGML), YAML (YAML Ain’t Markup Language), and Javascript Object Notation (JSON). Due to this, MCNP uses an entirely custom defined syntax language for its input, making off-the-shelf libraries for XML, YAML, and JSON impossible to use for scripting various operations on MCNP input files (Kulesza et al., 2022).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Practical guide to Parsing MCNP Inputs: Lessons Learned from Implementing Context-Free Parsing in MontePy

Monte Carlo N-Particle (MCNP) is a widely used Monte Carlo transport solver that began development in the 1960’s. Due to this MCNP input files uses a custom input syntax, for which there are no off-the-shelf parsing libraries available. For MontePy to create an effective Object-Oriented interface for MCNP input files, an context-free parser was implemented to be able to fully parse the files. MontePy uses a number of shortcuts and optimizations to avoid creating a single universal input file parser. . These lessons can be applied to working with the many other custom input syntax languages persistent throughout the nuclear industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Parallel Programming in MCNP6

Monte Carlo N-Particle (MCNP)1 is a general-purpose Monte Carlo particle transport code developed by Los Alamos National Laboratory (LANL). To efficiently handle long simulations, MCNP version 6 (MCNP6) supports parallel execution using two primary programming models: • Shared-memory task-based threading using OpenMP (Open Multi-Processing), and • Distributed-memory calculations using MPI (Message Passing Interface). The OpenMP and MPI programming models enable MCNP6 to scale from desktop systems to high-performance computing (HPC) clusters, allowing users to run MCNP in one of three parallel modes: • OpenMP-only, • MPI-only, and • Hybrid (MPI + OpenMP). The choice of parallelization mode depends on the underlying computer architecture and the characteristics of the simulation problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

MCNP® Code Version 6.3.1 Release Notes

The Monte Carlo N-Particle® (MCNP® ) code is a general-purpose, continuous-energy, generalized-geometry, time-dependent, radiation transport code developed by the MCNP development team. MCNP calculations provide predictive capabilities that can replace expensive or impossible-to-perform experiments. Specific application problems include simulations of experimental diagnostics, intrinsic radiation, radiation detection and measurement, criticality safety, nuclear threat reduction and response, radiation health protection, nuclear weapons effects, and nuclear forensics. This MCNP code, version 6.3.1, follows the MCNP6.3.0 version. Since the release of MCNP6.3.0, a variety of bug fixes and code enhancements have been completed for MCNP6.3.1. A few new features have also been added to this release to support both ongoing research and the release of the latest ENDF/B-VIII.1 nuclear data library. The MCNP code, version 6.3.1, theory and user input information is documented in MCNP® Code Version 6.3.1 Theory & User Manual, the build guidance for various platforms is documented in MCNP® Code Version 6.3.1 Build Guide, and the verification and validation testing for various application benchmark test suites is documented in MCNP® Code Version 6.3.1 Verification & Validation Testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Godiva IV Thermal Neutron Dosimetry Modeling and Variance Reduction

The transfer of the Godiva IV experiment from the Los Alamos Critical Experiments Facility (LACEF) to the National Critical Experiments Research Center (NCERC) introduced a vastly different experiment room return to the neutron flux. The contribution of the background to the burst neutron energy spectrum is significant in the thermal and epithermal neutron energies. Target materials may be placed in various locations in the Godiva room, or outside of the room, for thermal neutron activation. Modeling of this dosimetry problem in Monte Carlo N-Particle (MCNP) presented a novel challenge compared to previous Godiva IV glory hole irradiation simulations. An advanced dosimetry modeling framework for high efficiency calculations in locations far from the Godiva IV fission source was desired. The mesh-based weight windows and point detector advanced variance reduction techniques in MCNP were implemented and tested using adaptations of the critical experiment benchmark model of the Godiva IV problem. The models were validated against measured activations of Nickel, Indium, Scandium, and Cobalt foils at locations 2 meters from the Godiva IV core. Dosimetry measurements were performed in collaboration with Sandia National Laboratory. The weight windows and point detector variance reduction coupled method resulted in the highest problem efficiency.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

MCNP® Code Version 6.3.2 Theory & User Manual (Rev. 1)

This document acts as a repository of knowledge for the Monte Carlo N-Particle (MCNP) transport computer code. It is maintained alongside the source code and attempts to introduce new users and re-familiarize experienced users with the theory and practices of using the MCNP code for the wide range of particle transport analyses that it is appropriate for. The latest version of the MCNP code, version 6.3.2, provides the Monte Carlo particle transport community with the latest feature developments and bug fixes in the MCNP code. The MCNP code version 6.0 and later is also known as the MCNP6 code.

42 ENGINEERING↗
DOE OSTI2026

ACRRF High-Bay Dose Calculations using MCNP (Part A)

Analytical tools and models have been developed as a starting point for directly assessing dose in the Annular Core Research Reactor Facility (ACRRF) due to reactor operation. Key results include peak dose along the Central Cavity (CC) centerline (beamline) at the cavity level, dose throughout the High-Bay (HB), and dose on the facility roof for partially-shielded reactor operation where the 4” insert is removed from the CC Shield Plug (SP). Model results in the beamline are benchmarked against measured doses from passive dosimetry evaluations. Personnel total (neutron and gamma) dose in the ACRRF HB is calculated using Monte Carlo N-Particle (MCNP). Various CC and SP configurations are analyzed, including unshielded (no SP) and partially shielded (SP installed but 4” insert removed). Novel application of Variance Reduction (VR) techniques, namely the Surface Source Write (SSW) and Surface Source Read (SSR) capabilities in MCNP, enable impressive resolution (in a Monte Carlo modeling sense) of dose throughout much the facility. The VR techniques reduce stochastic error for challenging tallies, with more advanced techniques explored in the companion to this report (Part B) [1]. Supplementary studies (including a verification analysis) and pedagogic evaluations in Part B involve neutron spectra, angular distributions, and the dose impact of facility characteristics. With the SP 4” insert removed and the Lead-Boron (44”) Bucket (LB–44) in the reactor cavity, Total Effective Dose (TED) within the CC beamline is ≈140 rem per 300 MJ of reactor yield (or 3900 rem per hour at 100% Steady-State (SS) power). With no SP (unshielded) and a Free-Field (FF) cavity, TED within the beamline is ≈610 rem per 300 MJ (or 17000 rem per hour at 100% SS power). Due to the predicted collimation of radiation by the reactor pool (and partial SP, if present), beamline dose is much greater than the scattered radiation field surrounding the cavity and reactor tank. Comparisons are made to beamline dosimetry measurements to validate the model. Model predictions agree reasonably well (⪅10%) with measured quantities of neutron fluence, gamma fluence, and spectral metrics. Away from the beamline, comparisons made to previous dose measurements in the HB agreement within an order of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Integrating HPC simulations and physical experiments to characterize the effects of gamma radiation on seismic protective devices

Seismic protective systems, composed of seismic isolators and dampers, can substantially reduce the effects of earthquake shaking on nuclear power plants and components therein. To enable the use of these devices to protect equipment inside a plant and close to a source of radiation, the U.S. Department of Energy (DOE) funded a project at the Idaho National Laboratory (INL) and the University at Buffalo to characterize the effects of absorbed gamma dose on their mechanical properties. An early task in the project was to determine the exposure time required in the INL Foss Therapy Services (FTS) 60 Co gamma irradiator to achieve a target absorbed dose in the materials used to construct isolators and dampers, including fluids, polymers, composites, and metals. This task required the novel integration of high-performance computing (HPC), Monte Carlo N-Particle (MCNP) simulations, and irradiation experiments using Fricke dosimetry. An MCNP model of the FTS irradiator at INL was developed and validated using Fricke dosimetry. Simulations of three experiments in the irradiator, two with Fricke vials only and one with Fricke vials and a large-size isolator, predicted the Fricke-measured absorbed dose rate to within 15% in all three cases, providing high confidence in the calculation of the gamma dose absorbed in the materials comprising the seismic protective devices. The simulations demonstrated that the effects of photon scattering on absorbed dose rate in the FTS irradiator are negligible for test articles installed close to the cobalt sources and near the rear of the irradiator. The validated MCNP model of the FTS irradiator is being used to support ongoing DOE-funded experiments on seismic protective devices and could be applied to future, non-seismic-related experiments. In conclusion, the novel validation process successfully deployed for the FTS irradiator at INL could be applied to other irradiators, requiring new MCNP models and simulations, and irradiation experiments using dosimeters.

42 - ENGINEERING↗
DOE OSTI2026

Investigation of irradiation damage and heat deposition: a comparative analysis for HEU-to-LEU conversion in HFIR

The planned conversion of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel requires detailed evaluation of experiment-relevant parameters to ensure continued performance for materials testing and isotope production. Here, this study presents the first comprehensive assessment of displacements per atom (dpa) and heat deposition rates in target materials within the HFIR flux trap with both HEU and candidate LEU core configurations. Seven analyses were conducted to evaluate key performance metrics, including fast neutron flux distribution, cross section response functions, cross section data, and local dpa and heat deposition rates using mesh- and cell-based tallies. Simulations employed Shift, Monte Carlo N-Particle (MCNP), and the HIFR Controller (HFIRCON) tool suite for high-fidelity transport and depletion modeling. The LEU designs—using U 3 Si 2 -Al dispersion fuel and operating at 95 MW—were compared to the current 85 MW HEU configuration. Results show that while the candidate LEU cores exhibit higher dpa rates due to a harder spectrum and extended cycle lengths, they also demonstrate reduced heat deposition rates in irradiation experiments, primarily due to increased gamma self-shielding from higher 238 U content in the core. These findings confirm that LEU conversion can maintain HFIR’s materials irradiation capabilities but may require redesigning existing experimental hardware.

HEU↗
DOE OSTI2026

CADIS and FW-CADIS Variance Reduction in Gamma Transport for Predicting Prompt Forensics Signatures

The goal of prompt nuclear forensics is to determine the characteristics of a nuclear detonation based on the signatures available almost immediately after the explosion. An important characteristic is the reaction time history (RTH), a measure of the device’s rate of neutron multiplication. The RTH can be estimated by observation of the gamma radiation emitted from the detonation, which can be detected directly or observed indirectly as Teller light. Gamma transport simulations used to predict these radiation fields are often modeled stochastically using the Monte Carlo N-Particle (MCNP) code, which can be a computationally demanding task due to the number of particle histories needed to achieve statistical convergence. In an attempt to improve the efficiency of these calculations, we evaluate two variance reduction techniques: Consistent Adjoint-Driven Importance Sampling (CADIS) and Forward-Weighted Consistent Adjoint-Driven Importance Sampling (FW-CADIS). These methods use a deterministically calculated adjoint flux to create weight windows and source biasing that guide MCNP sampling. We study the utility of CADIS and FW-CADIS for their use in MCNP gamma transport for nuclear forensics prediction simulations. Furthermore, the results demonstrate that both CADIS and FW-CADIS improve the accuracy for forensics-focused simulations, with CADIS being most beneficial in direct detection and FW-CADIS being ideal for computing a global Teller light source.

CADIS↗
DOE OSTI2025

Sensor Placement Optimization Study for the Built Environment: Operational Use Cases

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear and radiological incidents. State, local, tribal, and territorial (SLTT) government agencies that implement systems of fixed-position sensors are faced with numerous decisions regarding sensor selection, quantity, and placement. To develop guidance on implementation of radiation detection systems, we simulated the release of radioactive material in an urban environment using a combination of three models: the Weather Research Forecasting (WRF), Quick Urban and Industrial Complex (QUIC), and Monte Carlo N-Particle (MCNP) models. We then evaluated the performance of several hypothetical sensor systems. The small number of simulations we conducted are not sufficient to generate definitive design guidance for radiation sensor systems, but we did identify trends that would be of interest to emergency planners. For a scenario that releases 1000 curies of Cs-137, radiation detectors were needed at 500-meter intervals to have a high likelihood of event detection and to estimate source location and plume detection. We also noted that optimal detector altitude varied with distance to the source. We recommend additional research in this area be conducted to support developing sensor placement guidelines that expand on a range of locations, isotopes, activity levels, and different weather conditions. Original simulation strategies included a range of environments, additional radioisotopes (Am241 and AmBe), and a larger selection of sensor types. These types of expansions would support SLTT guidance on sensor system recommendations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Rapid Gamma Simulations of TRISO Fuel Elements

As energy demand rises, nuclear energy, particularly from reactors that use tristructural isotropic (TRISO) fuels, has gained attention due to the fuel’s enhanced resistance to radiation damage and high temperatures. This report investigates the modeling capabilities of the Gamma Detector Response and Analysis Software (GADRAS) for TRISO fuels, focusing on the gamma signatures of TRISO particles, which have not been extensively explored. Using the Monte Carlo N-Particle (MCNP) code as a benchmark, we developed both homogeneous and heterogeneous models of TRISO pebbles to analyze gamma spectra. Our findings reveal that the homogeneous and heterogeneous models produced different gamma signatures. Additionally, the GADRAS heterogeneous model significantly reduces computation times compared to MCNP, enabling effective modeling of gamma signatures for safeguards applications. This advancement is essential for the International Atomic Energy Agency (IAEA) in detecting anomalies and potential smuggling attempts in TRISO reactor fuel elements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies

Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

ORNLERASE - EPA COUNTS PER MINUTE CALCULATOR CONVERSION FACTORS

This database is used in the EPA's Superfund Counts Per Minute (CPM) Calculator (https://epa-cpm.ornl.gov/index.html). This database contains conversion factors used in the calculator that help users estimate the expected radiation detector reading, in counts per minute (CPM), corresponding to a measured radioactivity level reported in either pCi/cm² or pCi/g. Because surface contamination and volumetric contamination behave differently, the tool uses separate conversion processes, each based on Monte Carlo N-Particle (MCNP)–derived conversion factors. The CPM Calculator supports conversions for a range of common environmental media—including soil, steel, glass, drywall, concrete, and wood—to generate detector-ready CPM values. The primary goal of this tool is to enable more efficient, real-time field measurements, reducing reliance on laboratory analyses and ultimately saving both time and money during Superfund assessments.

Dolislager, Fred [ORNL] (ORCID:0009000325477921)↗
NASA NTRS1994

Rates for neutron-capture reactions on tungsten isotopes in iron meteorites

High-precision W isotopic analyses by Harper and Jacobsen indicate the W-182/W-183 ratio in the Toluca iron meteorite is shifted by -(3.0 +/- 0.9) x 10(exp -4) relative to a terrestrial standard. Possible causes of this shift are neutron-capture reactions on W during Toluca's approximately 600-Ma exposure to cosmic ray particles or radiogenic growth of W-182 from 9-Ma Hf-182 in the silicate portion of the Earth after removal of W to the Earth's core. Calculations for the rates of neutron-capture reactions on W isotopes were done to study the first possibility. The LAHET Code System (LCS) which consists of the Los Alamos High Energy Transport (LAHET) code and the Monte Carlo N-Particle(MCNP) transport code was used to numerically simulate the irradiation of the Toluca iron meteorite by galactic-cosmic-ray (GCR) particles and to calculate the rates of W(n, gamma) reactions. Toluca was modeled as a 3.9-m-radius sphere with the composition of a typical IA iron meteorite. The incident GCR protons and their interactions were modeled with LAHET, which also handled the interactions of neutrons with energies above 20 MeV. The rates for the capture of neutrons by W-182, W-183, and W-186 were calculated using the detailed library of (n, gamma) cross sections in MCNP. For this study of the possible effect of W(n, gamma) reactions on W isotope systematics, we consider the peak rates. The calculated maximum change in the normalized W-182/W-183 ratio due to neutron-capture reactions cannot account for more than 25% of the mass 182 deficit observed in Toluca W.

Masarik, J.↗
NASA NTRS2000

Materials for Low-Energy Neutron Radiation Shielding

Various candidate aircraft and spacecraft materials were analyzed and compared in a low-energy neutron environment using the Monte Carlo N-Particle (MCNP) transport code with an energy range up to 20 MeV. Some candidate materials have been tested in particle beams, and others seemed reasonable to analyze in this manner before deciding to test them. The two metal alloys analyzed are actual materials being designed into or used in aircraft and spacecraft today. This analysis shows that hydrogen-bearing materials have the best shielding characteristics over the metal alloys. It also shows that neutrons above 1 MeV are reflected out of the face of the slab better by larger quantities of carbon in the material. If a low-energy absorber is added to the material, fewer neutrons are transmitted through the material. Future analyses should focus on combinations of scatterers and absorbers to optimize these reaction channels and on the higher energy neutron component (above 50 MeV).

Singleterry, Robert C., Jr.↗
DOE OSTI2024

ANS Winter 2024 Summary: MCCAFE: The Monte Carlo Constructor for ATR Fuel Elements

The Irradiation Experiment Neutronics Analysis Department at Idaho National Laboratory (INL) has implemented a new analysis workflow for experiments in the Advanced Test Reactor (ATR). One key piece of this workflow is the Monte Carlo Constructor for ATR Fuel Elements, or MCCAFE. For each ATR operating cycle, the Reactor and Nuclear Safety Engineering (RNSE) Department first solves the core in eigenvalue mode and depletes the driver fuel materials. In a separate calculation, neutronics analysts model and deplete the materials of one or more irradiation experiments, usually in a series of fixed-source Monte Carlo N-Particle (MCNP) models of the ATR for neutron transport calculations. It was desirable to use the results of the former calculations to inform the models of the latter. MCCAFE is a Python program developed using American Society of Mechanical Engineers Nuclear Quality Assurance-1 procedures at INL. Its purpose is to take the calculated results from the RNSE depletion solutions and the measured or projected operating parameters from the Nuclear Data Management and Analysis System (NDMAS) to generate fixed-source models of the ATR core at given points in time across one or more cycles.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Summary Report Of The FY25 Reactor Physics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Valdiation and verification of numerical tools is critical for ensuring reasonable predictions for design scoping, licensing, and safety analsyis. In this report, two reactor physics verification and validation exercises are presented. The first of these exercises focuses on burnup analysis with data from the Advanced Gas Reactor (AGR) program. Simulations are performed with Monte Carlo N-Particle (MCNP) and are compared with the experimental measurements for the AGR 1 and 2 experiments that utilize both UCO and UO2 fuel. The second exercises utilizes data from the HTR-Proteus experiments to perform reactor physics validation. Specifications of the experimental facility are provdied, along with a demonstration of initial modeling efforts in Serpent for one of the determistic packing experiments. Both cases are part of the Generation-IV international forum (GIF) Very High-Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) program, an international collaborative organization dedicated to the verification and validation of High-Temperature Gas-Cooled Reactor (HTGR) analysis. Participation in the CMVB allows the US Department of Energy (DOE) to leverage these existing validation activities to provide extra value through benchmarking activities with other CMVB members.

and Benchmarking (CMVB) program↗