Search NASA⌕ Search

SEARCH · Search NASA

Results for “N-Particles”

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 55 records · Page 3

Impact of Time Dependent Reactor and Sensor Physics on Core Power Synthesis

Online synthesis of the power distribution is critical in the operation and control of nuclear power reactors to ensure that the core is operating within safety margins, and to provide essential knowledge associated with the burnup of the fuel. In light water reactors (LWRs), power synthesis is achieved by using some a priori knowledge of the state of the reactor core and updating based on the signals coming from in-core sensors—namely, self-powered neutron detectors (SPNDs). This report aims to study the effects of fuel burnup and sensor degradation on the ability to accurately synthesize the power distribution in a LWR. Several modeling tools were used to simulate power synthesis based on the responses of SPNDs, with emitters made out of Rh or V. A representative pressurized water reactor low-enriched uranium (LEU) core was modeled using the Polaris/Purdue Advanced Reactor Core Simulator (PARCS) approach. The Monte Carlo N-Particle Transport 6 (MCNP6) code was used, as well, to calculate response functions between different segments of fuel to individual SPNDs; this is a crucial parameter for power synthesis. The Oak Ridge Isotope GENeration (ORIGEN) package in the Standardized Computer Analyses for Licensing Evaluation (SCALE) code was used to model the time-dependent isotopic transmutation in the SPND emitters. All these data were fed into a custom code that enacted the point-based iterative (PBI) method to simulate power synthesis. Developmental work was also performed on high-fidelity SPND models in the GEometry ANd Tracking 4 (Geant4) code, which enables higher-accuracy modeling of the current responses from SPNDs. In this work, five sets of time-dependent power synthesis test cases were conducted. In these test cases, systematic changes in the input conditions enabled an analysis of the effect of (1) slightly inaccurate a priori power distribution assumptions with respect to fuel burnup, (2) highly inaccurate a priori assumptions with respect to fuel burnup (such that burnup is not included in the a priori assumed distribution), and (3) differences between Rh and V SPNDs in terms of downstream consequences of the transmutation in the emitters. The authors discovered that one may permissibly have slightly inaccurate a priori assumptions of the fuel burnup (such that the level of burnup may be slightly under- or over-approximated by the accumulated burnup in approximately 9.3 full power days), but to not account for burnup at all in the a priori assumption leads to severe levels of error, approaching 25% at maximum. The authors also discovered that V SPNDs are extraordinarily robust in the low-enriched uranium fuel cycle considered in this modeling work, whereas Rh SPNDs undergo significant transmutation that can result in large errors in the synthesized power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Burnup Monitoring for Pebble Bed Reactor Systems

A pebble burnup monitoring system is a required component for domestic reactor safety and safeguards applications associated with pebble bed reactors (PBRs). One of the main requirements of a PBR burnup monitoring system is that it needs to be capable of rapid measurements to assess the burnup of each individual pebble to determine whether to recirculate it in the reactor or discard it as spent fuel. This report considers three different approaches for a burnup monitoring system for pebbles discharged from the reactor core in a pebble bed modular reactor-400: • passive gamma spectrometry measurement, • passive neutron coincidence measurement, and • active neutron counter based on the differential die-away technique. Conceptual designs have been created for each of these detectors, and preliminary analysis has been performed using Monte Carlo N-Particle and Oak Ridge Isotope Generation code simulations. The advantages and practical limitations (e.g., high radiation background) of each system were identified. Simulations suggest that each of the three measurement techniques can be successfully employed to distinguish between pebbles based on their number of passes through the core and to quantify the burnup of pebbles.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FINESSE As-Run Neutronics Analysis for Cycle 171A

This Engineering Calculations and Analysis Report (ECAR) is a summary of the detailed Monte Carlo N-Particle (MCNP) physics analysis performed for the Purdue JW 16297/Fracture of Irradiated Neutron Embrittled Structural Steel and Examination (FINESSE) experiment irradiated in the B-10 position in Advanced Test Reactor (ATR), Cycle 171A.

171A↗

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↗

Impact of Time-Dependent Reactor and Sensor Physics on Core Power Synthesis (Rev.1)

Online synthesis of power distribution is critical in the operation and control of nuclear power reactors to ensure that the core is operating within safety margins and to provide essential knowledge associated with the burnup of the fuel. In light-water reactors, power synthesis is achieved by using some a priori knowledge of the state of the reactor core and updating based on the signals coming from in-core sensors—namely, self-powered neutron detectors (SPNDs). This report examines the effects of fuel burnup and sensor degradation on the ability to accurately synthesize the power distribution in a pressurized water reactor (PWR), considering the typical low-enriched uranium (LEU, 3%-5% enrichment) fuel cycle as well as the higher enrichment LEU+ (5%-8% enrichment) fuel cycle. Several modeling tools were used to simulate power synthesis based on the responses of SPNDs, with emitters made out of Rh or V. A representative PWR LEU core was modeled using the Polaris/Purdue Advanced Reactor Core Simulator (PARCS) approach. The Monte Carlo N-Particle Transport 6 (MCNP6) code was used as well to calculate response functions between different segments of fuel to individual SPNDs; this is a crucial parameter for power synthesis. The Oak Ridge Isotope GENeration (ORIGEN) package in the Standardized Computer Analyses for Licensing Evaluation (SCALE) code was used to model the time-dependent isotopic transmutation in the SPND emitters. All these data were fed into a custom code that enacted the point-based iterative method to simulate power synthesis. Developmental work was also performed on high-fidelity SPND models in the GEometry ANd Tracking 4 (Geant4) code, which enables higher-accuracy modeling of the current responses from SPNDs. In this work, five sets of time-dependent power synthesis test cases were conducted. In these test cases, systematic changes in the input conditions enabled an analysis of the effect of (1) slightly inaccurate a priori power distribution assumptions with respect to fuel burnup, (2) highly inaccurate a priori power distribution assumptions with respect to fuel burnup (such that burnup is not included in the a priori assumed distribution), and (3) differences between Rh and V SPNDs in terms of downstream consequences of the transmutation in the emitters and the extended nature of the LEU+ fuel cycle in comparison with LEU. The authors discovered that one may permissibly have slightly inaccurate a priori assumptions of the fuel burnup (such that the level of burnup may be slightly underapproximated or overapproximated by the accumulated burnup in approximately 9.3 full power days), but to not account for burnup at all in the a priori assumptions leads to severe levels of error, approaching 25% at maximum (for LEU). The authors also discovered that V SPNDs are extraordinarily robust in both the LEU and LEU+ fuel cycles considered in this modeling work, whereas Rh SPNDs undergo significant transmutation that can result in large errors in the synthesized power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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↗

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↗

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↗

Myths of German Graphite in World War II, with Original Translations

We re-examine the common narrative that a 1941 experimental error by physicists Walther Bothe and Peter Jensen led Germany to abandon graphite as a reactor moderator during World War II. We first detail the history of both German and American graphite experiments, noting that the Americans faced similar setbacks but succeeded only at the end of a costly 18-month graphite purification program. We then use Monte Carlo N-Particle simulations to reconstruct Bothe's 1941 experiment. We find the thermal absorption cross section of Bothe's Siemens electrographite to be 12.2 mb, in contrast to his reported 7.9 mb. This discrepancy arises because the neutrons in Bothe's experiment did not reach thermal equilibrium, leading to an underestimation of neutron absorption. Additionally, despite misconceptions that the Germans were unaware of boron impurities, we share evidence that Wilhelm Hanle accurately measured boron and cadmium impurities in the electrographite. To support our findings, we provide 9 excerpted and 3 complete English translations of classified wartime reports by Heisenberg, Joos, Bothe, Jensen, Höcker, Hanle, and Kremer. Our work aims to illuminate the rational constraints behind Germany's decision to forgo graphite moderation.

Park, Patrick J.↗

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)↗

Photoneutron Production Using an Electron Linear Accelerator for Applications in Neutron Imaging

Photoneutron production is possible using an electron linear accelerator and a target capable of generating photonuclear reactions. A short pulse neutron source can be useful for neutron imaging dynamic experiments. This study is aimed at the feasibility of photoneutron production using a 20 MeV electron linear accelerator and tungsten and depleted uranium targets of various thicknesses. MCNP6 (Monte Carlo N-Particle) code will be used to develop a computational model to estimate total neutron yield, and this will be verified at the Idaho State University’s Accelerator Center. After verification of the neutron yield and energy spectra, an additional MCNP6 model will be developed to analyze the neutron imaging processes. This study will potentially prove it is possible to conduct multi-mode imaging experiments on the anticipated Scorpius electron linear accelerator at the Nevada National Security Sites.

43 PARTICLE ACCELERATORS↗

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↗

Development of Instrumented Advanced Test Reactor Irradiation Capsule Experiment for In-situ Thermal Conductivity Measurements of High-Density Fuels

Idaho National Laboratory (INL) is developing a first-of-a-kind leadout instrumented capsule experiment design to enable in-situ measurement capabilities in the Advanced Test Reactor (ATR) core. The Ceramic Advanced Thermal Evolution Research (CRATER) experiment supports the aLEU program objective to accelerate fuel performance irradiation testing for identifying alternative high-assay, low enriched uranium (HALEU) fuel systems. CRATER is a fueled, instrumented capsule experiment to measure in-situ temperature and thermal conductivity of ceramic fuels. Two ceramic fuel types will be used, uranium mono-nitride (UN) and uranium mono-carbide (UC), with a third metallic fuel used for comparison (UMo). The three fuel specimens will use a stainless-steel cladding. Programmatic objectives include linear heat generation rates (LHGR) of 210 ± 25 Watts per cm. and an inner clad temperature of 300-450 °C. The evolution of fuel thermal conductivity during irradiation has never been successfully measured in-situ for these systems and this experiment is designed to use advances in measurement sciences to characterize how thermal transport properties evolve while in reactor. Neutronic simulations of the experiment and its surrounding reactor environment were conducted using the Monte Carlo N-Particle Transport code (MCNP) and result in optimized fuel enrichment to meet target linear heat generation rates (LHGRs) influencing fuel temperatures, and fuel burnup requirements. Fabrication research and development (R&D) efforts are underway to produce annular right cylinder UC and UN pellets using carbothermic reduction and nitridation (or hydride-dehydride-nitride) synthesis methods, followed double-action die cold isostatic pressing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

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↗

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↗

Estimation of General Area Dose Rates During Closure Weld Operations on the DOE Standard Canister Pacific Basin Nuclear Conference 2024

The Department of Energy (DOE) Spent Nuclear Fuel (SNF) Road Ready Demonstration Project is an effort to package DOE-managed SNF for road-ready dry storage. A key operation in this demonstration is performing the closure weld on the DOE Standard Canister after it has been loaded with the SNF. Planning the closure weld operations is ongoing and must consider what parts of the operations (if any) can be done manually and what parts must be done remotely. A key parameter to inform the evolving planning of these operations is the dose rate in the vicinity of the canister and the dose hazard posed to the closure weld operators and collocated workers. This study developed a Monte Carlo N-Particle (MCNP) model of the closure weld operation, which was used to estimate general area dose rates as well as dose rates to the welding location, weld operators, and collocated workers. These estimates provide some insight into the potential radiation exposure hazard for workers during the operations and are a factor to be considered in the ongoing development of designs, technology, processes, and administrative controls for packaging DOE-managed SNF for road-ready dry storage.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparing Control Performance Between Simulation and Experiment using the Microreactor Automated Control System Testbed

In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Generative models on phase space

Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dimensional distributions. They are particularly useful when the training data appears to be concentrated on a submanifold of the data embedding space. For high-energy physics data, consisting of collections of relativistic energy-momentum 4-vectors, this submanifold can enforce extremely strong physically-motivated priors, such as energy and momentum conservation. If these constraints are learned only approximately, rather than exactly, this can inhibit the interpretability and reliability of such generative models. To remedy this deficiency, we introduce generative models which are, by construction, confined at every step of their sampling trajectory to the manifold of massless N-particle Lorentz-invariant phase space in the center-of-momentum frame. In the case of diffusion models, the "pure noise" forward process endpoint corresponds to the uniform distribution on phase space, which provides a clear starting point from which to identify how correlations among the particles emerge during the reverse (de-noising) process. We demonstrate that our models are able to learn both few-particle and many-particle distributions with various singularity structures, paving the way for future interpretability studies using generative models trained on simulated jet data.

Bogorad, Zachary [Fermilab]↗