Monte Carlo N-Particle Research Articles

A pilot study of diabetes effects on radiation attenuation characteristics of tibia and femur of rats

This study aimed to investigate the effect of diabetes on radiation attenuation parameters of the femur and tibia of rats using Monte Carlo Simulations. First, control and diabetic rats were identified and tibias and femurs were removed. Then, the elemental ratios of the bones obtained were calculated using EDS (Energy Dissipative X-ray Spectroscopy). Therefore, radiation permeability properties of control and diabetic bones were simulated by using the content ratios in the bones in MCNP6 (Monte Carlo N-Particle) and PHITS (Particle and Heavy Ion Transport code System) 3.22 and Stopping and Range of Ions in Matter (SRIM) simulation codes. Attenuation coefficient results were compared with the NIST database via XCOM. Although differences in absorption coefficients are observed at low energies, these differences disappear as the energy increases.

Evaluation of Gamma-Ray Dose Distribution in the Toroidal Direction of LHD Vacuum Vessel from Radionuclides Generated in Deuterium Plasma Experiments

The evaluation of activities from radionuclides inside a vacuum vessel is required for the safe maintenance and estimation of the activation level of fusion devices. The Large Helical Device (LHD), Toki, Japan, has been performing deuterium plasma experiments since 2017, and radionuclides have accumulated in components such as vacuum vessels. In this work, the gamma-ray spectrum and activity of each detected radionuclide in an LHD vacuum vessel were evaluated using portable high-purity germanium (P-HPGe) and numerical calculations of photon transport for comparison with the removed armor tiles to evaluate the occupational exposure in the maintenance of LHD experiments. Measurements using the P-HPGe detector were performed at 20 positions along the toroidal direction of the LHD, at each O port, and between each pair of adjacent O ports. Using the estimated efficiency of the photoelectronic effects inside the P-HPGe detector calculated by Monte Carlo N-particle code version 6.1, the activities of the radionuclides in the armor tiles attached to the vacuum vessel were evaluated. The estimated activity concentrations were compared with the measured activities of the armor tiles removed from the vacuum vessel. Gamma rays from 58Co, 54Mn, and 60Co were detected, and the measured activities of 58Co and 54Mn generated by fast neutrons in the armor tile were almost consistent with those obtained from the removed armor tiles. The radioactivity of 60Co in the armor tile was underestimated compared with the activity obtained from the removed armor tiles. The measurement of activation by fast neutrons is feasible, whereas activation by thermal neutrons requires more accurate calculations and surveys to be measured using this method.

Design of an optimized nuclear fuel pellet

Background The design of an improved nuclear fuel pellet for use in the Westinghouse AP1000 reactor that is more powerful than existing pellets, is less expensive to manufacture, and meets Nuclear Regulatory Commission requirements for certification was undertaken to complete a senior design course in the ABET-certified nuclear engineering curriculum of Rensselaer Polytechnic Institute, Troy, NY. Methods The modeling team selected the Monte Carlo N-Particle (MCNP) program for assessing how well the pellet design achieves a k-effective value of 1, designed the base model consisting of a fuel pin inside a boron-water moderator with reflector, and ran MCNP tests on the base pellet. The design team modified the base pellet and tested it at different uranium-235 enrichments, with void spheres of varying volume and silicon carbide inclusions in the void volume. The simulation team selected K-code for testing the fuel pellets. The economics team analyzed the cost of manufacturing the improved pellet from cost of raw material through its tail assay in the form of Separative Work Unit (SWUs). The impacts team researched environmental, societal, governmental, political, and public affairs aspects of nuclear fuel production. Results Multiple configurations of uranium enrichment and silicon carbide volume inclusions in the nuclear fuel pellet achieved a k eff of 1, and the price per pellet, assuming fabrication costs comparable to existing manufacturing processes, was reduced by as much as about 50% when the volume of uranium oxide replaced by silicon carbide is 0.27 cm3. At smaller replacement volumes, the price per pellet is reduced by as little as 5%. Conclusions The goal of designing an optimized fuel pellet was met. Replacing a 0.27 cm3-volume sphere of uranium oxide with silicon carbide from the center of a pellet of 4%, 5%, or 6% uranium-235 enrichment reduced the cost of the pellet by approximately 50%.

Optimization of the Second Target Station cold source moderators using an automated workflow

The Second Target Station (STS) at the US Department of Energy’s Oak Ridge National Laboratory is designed to become the world’s highest peak-brightness spallation source of cold neutrons. Successful completion of the STS, which is currently in the preliminary design phase, will provide transformative new capabilities to examine novel materials for future technologies. At STS, neutrons will be generated by spallation reactions in a solid tungsten target. They will be moderated and thermalized in two cold (20 K) para-hydrogen moderators. Careful optimization of these moderators is essential to the project’s success. To find optimal moderator designs, an advanced optimization workflow integrates high-fidelity neutronics calculations using the Monte Carlo N-Particle (MCNP) transport code MCNP6.2 with state-of-the-art optimization algorithms in the Dakota optimization toolkit. For each design iteration, a parametrized solid CAD geometry is generated in Creo and automatically converted into an unstructured mesh geometry by Attila 4MC for the neutronics calculation with MCNP. Iterations repeat until optimal designs are found. This paper presents the results of a sensitivity and optimization study for the cylindrical and tube moderators. Both moderators can be optimized for maximum peak brightness, maximum time-integrated brightness, or any combination between these extremes. Maximum peak brightness is achieved by using smaller optimal dimensions of the moderators, whereas maximum time-integrated brightness is achieved by using larger dimensions. A Pareto front details the designs that optimally balance both brightness metrics. The Pareto front can be found in only 40–110 iterations with 4–5 design parameters when using the efficient global and Pareto-set optimization algorithms in Dakota. Additionally, important engineering constraints can be taken into account, such as the coupling between the cylindrical moderator radius and aluminum vessel wall thicknesses required to ensure structural integrity of the vessels. This interaction has a significant impact on the resulting optimal designs. Our new, highly efficient, fully automated optimization workflow will be used to optimize additional STS components in the future and can be adopted for design and optimization studies at other experimental neutron and accelerator facilities.

Experimental validation of Monte Carlo simulation model for X-ray security scanner

Transmission X-ray security scanners are deployed to detect smuggling of contraband articles, including weapons, narcotics, and explosives, for the purposes of homeland security. Current X-ray scanners use a fixed tube voltage (i.e., 160 kV); hence, they have a limitation in detecting thinly coated and/or low-density objects. To overcome this limitation, we are developing an X-ray scanner that applies variable tube voltage according to the physical/chemical properties of the object being inspected. To this end, in our previous study, Monte Carlo simulations with Geant4 (GEometry ANd Tracking4) and MCNP (Monte Carlo N Particle) were performed to optimize the design of the X-ray scanner for variable tube voltages. The MCNP was used to simulate the radiation generator for the X-ray source term, and the Geant4 was used to optimize the design of the dual-energy detector and to obtain the detector counts. In the present study, we experimentally validated the reliability of the Monte Carlo simulation model for the X-ray scanner. An 241Am source and a radiation generator were employed in this validation. For the 241Am source, the dual-energy detector signal was measured at a distance of 1 cm from the detector. In the case of the radiation generator, the source-to-object distance and the source-to-detector distance were 70 cm and 120 cm, respectively, as used in a typical X-ray security scanner. The tube voltage and the current were 140 kV and 10 mA, respectively. To obtain the X-ray images, the object was scanned while moving at a speed of 0.2 m/s on a conveyor system. The X-ray source term used in the simulation was obtained by monoenergetic-electron-beam bombardment onto the target. 4-D simulations were performed for the moving object. To validate the simulation model, we compared the simulated and measured image profiles, as well as the pixel counts of the dual-energy detector. The percent differences between the simulated and measured pixel counts and the image profiles were all within 5%. Thus, we concluded that our simulation model for the X-ray scanner can be considered to be reliable.

Gamma-ray measurement for classification of fuel debris and waste

The detection of prompt fission gamma-rays and Tl-208 decay gamma-rays, which are unique to nuclear materials, could be applied to sorting nuclear fuel debris and radioactive waste from the Fukushima Daiichi Nuclear Power Plant. To confirm its technical feasibility, particle transport calculations using the Monte Carlo N-Particle code were performed.

On β-titanium alloys: tailoring gamma-ray, and neutron transmission properties for nuclear and biomedical applications

This study explores the gamma-ray and neutron transmission properties of β-Titanium alloys pivotal for their performance in nuclear and biomedical applications. Utilizing the Monte Carlo N-Particle (MCNP 6.3) simulations, we analyzed a spectrum of Ti-based alloys modified with elements like molybdenum (Mo), zirconium (Zr), niobium (Nb), and hafnium (Hf) to determine their radiation attenuation properties. Key parameters such as mass and linear attenuation coefficients, half-value layers, exposure buildup factors, and fast neutron effective removal cross-section values were computed, revealing significant enhancements in attenuation with the addition of high-Z elements. Specifically, alloys like Ti50Hf50 and (TiZr)40Cu60 exhibited superior photon and fast neutron attenuation due to their high-Z constituents. For instance, Ti50Hf50 showed a mass attenuation coefficient of 0.217 cm2/g and a half-value layer of 2.97 cm at 0.1 MeV photon energy, while (TiZr)40Cu60 demonstrated similar performance with a mass attenuation coefficient of 0.198 cm2/g and a half-value layer of 3.26 cm. These alloys also exhibited effective neutron removal cross-section values of 0.115 cm−1 and 0.130 cm−1, respectively. Alloys with lower-Z elements showed less attenuation, which may be beneficial in scenarios requiring reduced radiographic contrast in biomedical applications. The MCNP outcomes were in strong agreement with standard data, affirming the accuracy of computational methods in predicting material behavior. In conclusion, tailored alloy development is crucial for improving radiation shielding and diagnostic visualization, with broader implications for patient safety and treatment efficacy.

A Preliminary Study on Evaluation of Time-Dependent Radionuclide Removal Performance Using Artificial Intelligence for Biological Adsorbents

Background: Recently, biological adsorbents have been developed for removing radionuclides from radioactive liquid waste due to their high selectivity, eco-friendliness, and renewability. However, since they can be damaged by radiation in radioactive waste, a method for estimating the bio-adsorbent performance as a time should consider the radiation damages in terms of their renewability. This paper aims to develop a simulation method that applies a deep learning technique to rapidly and accurately estimate the adsorption performance of bio-adsorbents when inserted into liquid radioactive waste.Materials and Methods: A model that describes various interactions between a bio-adsorbent and liquid has been constructed using numerical methods to estimate the adsorption capacity of the bio-adsorbent. To generate datasets for machine learning, Monte Carlo N-Particle (MCNP) simulations were conducted while considering radioactive concentrations in the adsorbent column.Results and Discussion: Compared with the result of the conventional method, the proposed method indicates that the accuracy is in good agreement, within 0.99% and 0.06% for the R<sup>2</sup> score and mean absolute percentage error, respectively. Furthermore, the estimation speed is improved by over 30 times.Conclusion: Note that an artificial neural network can rapidly and accurately estimate the survival rate of a bio-adsorbent from radiation ionization compared with the MCNP simulation and can determine if the bio-adsorbents are reusable.

Determination of Exposure during Handling of <sup>125</sup>I Seed Using Thermoluminescent Dosimeter and Monte Carlo Method Based on Computational Phantom

Background: The thermoluminescent dosimeter (TLD) and Monte Carlo (MC) dosimetry are carried out to determine the occupational dose for personnel in the handling of <sup>125</sup>I seed sources.Materials and Methods: TLDs were placed in different layers of the Alderson-Rando phantom in the thyroid, lung and also eyes and skin surface. An <sup>125</sup>I seed source was prepared and its activity was measured using a dose calibrator and was placed at two distances of 20 and 50 cm from the Alderson-Rando phantom. In addition, the Monte Carlo N-Particle Extended (MCNPX 2.6.0) code and a computational phantom with a lattice-based geometry were used for organ dose calculations.Results and Discussion: The comparison of TLD and MC results in the thyroid and lung is consistent. Although the relative difference of MC dosimetry to TLD for the eyes was between 4% and 13% and for the skin between 19% and 23%, because of the existence of a higher uncertainty regarding TLD positioning in the eye and skin, these inaccuracies can also be acceptable. The isodose distribution was calculated in the cross-section of the head phantom when the <sup>125</sup>I seed was at two distances of 20 and 50 cm and it showed that the greatest dose reduction was observed for the eyes, skin, thyroid, and lungs, respectively. The results of MC dosimetry indicated that for near the head positions (distance of 20 cm) the absorbed dose rates for the eye lens, eye and skin were 78.1±2.3, 59.0±1.8, and 10.7±0.7 µGy/mCi/hr, respectively. Furthermore, we found that a 30 cm displacement for the <sup>125</sup>I seed reduced the eye and skin doses by at least 3- and 2-fold, respectively.Conclusion: Using a computational phantom to monitor the dose to the sensitive organs (eye and skin) for personnel involved in the handling of <sup>125</sup>I seed sources can be an accurate and inexpensive method.

Enhancing Gamma-Neutron Shielding Effectiveness of Polyvinylidene Fluoride for Potent Applications in Nuclear Industries: A Study on the Impact of Tungsten Carbide, Trioxide, and Disulfide Using EpiXS, Phy-X/PSD, and MCNP5 Code

Background: Radiation protection is crucial in various fields due to the harmful effects of radiation. Shielding is used to reduce radiation exposure, but gamma radiation poses challenges due to its high energy and penetration capabilities.Materials and Methods: This work investigates the radiation shielding properties of polyvinylidene fluoride (PVDF) samples containing different weight fraction of tungsten carbide (WC), tungsten trioxide (WO<sub>3</sub>), and tungsten disulfide (WS<sub>2</sub>). Parameters such as the mass attenuation coefficient (MAC), half-value layer (HVL), mean free path (MFP), effective atomic number (Z<sub>eff</sub>), and macroscopic effective removal cross-section for fast neutrons (Σ<sub>R</sub>) were calculated using the Phy-X/PSD software. EpiXS simulations were conducted for MAC validation.Results and Discussion: Increasing the weight fraction of the additives resulted in higher MAC values, indicating improved radiation shielding. PVDF–xWC showed the highest percentage increase in MAC values. MFP results indicated that PVDF–0.20WC has the lowest values, suggesting superior shielding properties compared to PVDF–0.20WO<sub>3</sub> and PVDF–0.20WS<sub>2</sub>. PVDF–0.20WC also exhibited the highest Z<sub>eff</sub> values, while PVDF–0.20WS2 showed a slightly higher increase in Z<sub>eff</sub> at energies of 0.662 and 1.333 MeV. PVDF–0.20WC has demonstrated the highest Σ<sub>R</sub> value, indicating effective shielding against fast neutrons, while PVDF–0.20WS2 had the lowest Σ<sub>R</sub> value. The Monte Carlo N-Particle Transport version 5 (MCNP5) simulations showed that PVDF–xWC attenuates gamma radiation more than pure PVDF, significantly decreasing the dose equivalent rate.Conclusion: Overall, this research provides insights into the radiation shielding properties of PVDF mixtures, with PVDF–xWC showing the most promising results.

Validation of the single-event method for low-energy electron transport via stopping power calculations with MCNP

Monte Carlo simulations of low-energy (<50 keV) electron transport in matter are essential for a broad range of application fields. Several Monte Carlo codes have developed specialized treatments for this case, but a comprehensive validation of low-energy electron transport for general-purpose simulations remains lacking in the literature. One approach to accomplish this validation is calculation of stopping power using low-energy electron transport physics, as stopping power is a fundamental radiation transport quantity which must be simulated accurately for nearly any application. In this work, we use the Monte Carlo N-Particle (MCNP) radiation transport code with the single-event method for electron transport to calculate stopping powers of low-energy electrons (50 eV to 30 keV) in 41 elemental solids, 14 compound solids, and five rare gas solids, comparing simulation results to published semi-empirical stopping power calculations from optical measurements. In general, the simulations give good agreement (typically within ±10%) with semi-empirical stopping power values at higher energies: 300 eV and above for most elemental solids, 1 keV and above for compound solids, and 400 eV and above for rare gas solids. Agreement between MCNP and semi-empirical values is worse below these energies. The most significant source of error is the EPRDATA14 cross section data, which does not account for changes in electronic structure due to solid-state bonding, particularly in compound materials. The simplistic model of atomic excitation used to generate the EPRDATA14 cross sections is another key source of error. Additionally, the breakdown of the continuous slowing-down approximation introduces significant uncertainty at low energies, although this is a limitation of the calculation method and not of the simulation procedure. Accounting for these and other uncertainty sources, the single event method in MCNP is robust and able to give good accuracy for a variety of low-energy electron transport problems through diverse kinds of materials.

Usage of radial basis function neural network for dual-energy radiative detection system for measuring the oil pipelines scale layer

Scaling oil pipelines over time leads to issues including diminished flow rates, wasted energy, and decreased efficiency. In order to take preventative measures in a timely manner and avoid the aforementioned issues, it is crucial to get a precise gauge of the scale within the pipe. Non-invasive gamma attenuation systems are one of the most accurate detection methods. In this investigation, he Monte Carlo N Particle (MCNP) technique was used to model a scale thickness measuring system including a test pipe, two sodium iodide detectors, and a dual-energy gamma source. The three-phase flow was created by simulating water, gas and oil in a homogenous flow regime in the test pipe. Additionally, a scale of varying thicknesses was installed inside the conduit. The photon intensity on the opposite side of the pipe was measured by detectors when gamma rays shone through it. Photopeaks of 241 Am and 133 Ba of the transmission detector and the total count of the scattering detector were derived from the signal received by the detectors. Since there are different variables such as scale layer and volume fractions in the present study, it is not possible to use regular known attenuation formulas for calculating the thickness. So, in this paper, RBF was implemented to solve this issue. By training and optimizing a RBF network, we were able to predict the thickness of a scale with an RMSE of 0.057. Having such a small margin for error confirms the validity of the suggested technology and its practical use in the petroleum and petrochemical industries.

Neutronic evaluation of a small lead-cooled nuclear reactor as an actinides burner

This study employs the Monte Carlo N-Particle code, version 6 (MCNP6), to simulate ELECTRA and investigate its neutronic parameters and the transmutation of spent fuel over a 15-year burnup period, as referenced. The primary objective is to evaluate actinide burning in a low-power fast reactor. The study consists of three phases: 1) validating Model 1 for MCNP6 code with results obtained by SERPENT code from previous studies, 2) conducting neutronic analysis of three ELECTRA models (1, 2, and 3) with varying levels of detail, and 3) assessing burnup using the most detailed ELECTRA MCNP6 model (Models 3). The neutronic calculations obtained from the MCNP6 code align with previous studies. Notably, including all core components in the simulation yields significant disparities in criticality and neutron flux compared to a simpler model. Despite its small size and low power, ELECTRA, as a research reactor, exhibits essential characteristics for effectively burning plutonium from Light Water Reactor (LWR) spent fuel. Therefore, ELECTRA contributes to developing LFRs and supports the GIF’s research goals for reactor development.

Accuracy improvement of a simulation model of a radiation portal monitor by correcting dead-time effect

Thousands of radiation portal monitors (RPMs) have been deployed around the world to detect radioactive materials that are outside of regulatory control. The detection capability of the RPMs can be evaluated by conducting a field test with various radioactive materials. However, field tests are limited because the RPMs are operated 24 h a day. The Monte Carlo N-Particle (MCNP) transport code provides an alternative. To evaluate the performance of the RPM with MCNP-based simulation model, the simulation results should be experimentally validated and the measurement result for the validation should be corrected for dead time effect. In this study, an MCNP-based RPM simulation model was developed and the accuracy of the RPM simulation model was improved by correcting dead-time effect. Static and dynamic measurements were conducted and the dead-time correction for the measurement data was factored in. With the static measurement data, the simulation model was developed and the comparing results with the static measurement data show that it satisfied an average relative difference of less than 10%. The simulation model was validated with 17 dynamic measurement datasets and the validation results show that the average relative differences are also within 10% even though the experimental conditions of the static and dynamic measurements were different.

Reexamination of a 40Ca(n,α)37Ar cross section measurement from existing literature

Background 37Ar, produced from the neutron activation of 40Ca in sub-surface rock and soil, is important for nuclear explosion monitoring. Most of the cross section measurements done for the 40Ca(n,α) 37 Ar reaction are in the fast neutron region. A thermal cross section measurement was attempted in 1989, with the assumption that the 4-8 MeV neutrons would be completely thermalized with 8-cm of water. Methods The experimental setup was modeled using Monte Carlo N-Particle code to see if the assumptions for the neutron distribution were accurate. A model of a 3.0 MeV deuteron source was used to recreate the neutron source from the experiment. Additional modeling was done using SCALE to compare the predictions of 37Ar yields when using the measured cross section from 1989 compared to current nuclear data models. Results Modeling showed the neutron distribution was closer to 10% thermal and 90% fast as opposed to entirely thermalized. The additional modeling showed how the overestimation of the thermal cross section would affect the predicted yield of 37Ar. Conclusions Based on the modeling results, the assumption that all the 4-8 MeV neutrons are thermalized with 8-cm of water is not accurate. The high fraction of fast neutrons interacting with the Ca will result in an overestimation of the thermal cross section.

Development of DynamicMC for PHITS Monte Carlo package.

Previously, we have developed DynamicMC for modeling relative movement of Oak Ridge National Laboratory phantom in a radiation field for the Monte Carlo N-Particle package (Health Physics. 2023,124(4):301-309). Using this software, three-dimensional dose distributions in a phantom irradiated by a certain mono-energetic (Mono E) source can be deduced through its graphical user interface. In this study, we extended DynamicMC to be used in combination with the Particle and Heavy Ion Transport code System (PHITS) by providing it with a higher flexibility for dynamic movement for an anthropomorphic phantom. For this purpose, we implemented four new functions into the software, which are (1) to generate not only Mono E sources but also those having an energy spectrum of an arbitrary radioisotope (2) to calculate the absorbed doses for several radiologically important organs (3) to automatically average the calculated absorbed doses along the path of the phantom and (4) to generate user-defined slab shielding materials. The first and third items utilize the PHITS-specific modalities named radioisotope-source and sumtally functions, respectively. The computational cost and complexity can be dramatically reduced with these features. We anticipate that the present work and the developed open-source tools will be in the interest of nuclear radiation physics community for research and teaching purposes.

Comparison of x-ray spectra and mean glandular dose estimations in computed radiography systems for mammography: Simulations versus measurements

To determine the dose given to patients in mammography, it is necessary to evaluate the mean glandular dose (MGD) in the computed radiography (CR) system with a solid-state detector, utilizing polymethyl methacrylate (PMMA) phantoms and spacers to model breast thickness. In the present study, irradiations were performed in a mammograph with a solid-state detector, and simulations were carried out using the Monte Carlo N-Particle Extended (MCNPX) code to give the MGD and spectra for the same conditions. In the mammograph, the glandular dose values were calculated for three anode/filter combinations: molybdenum/molybdenum (Mo/Mo), molybdenum/rhodium (Mo/Rh), and rhodium/rhodium (Rh/Rh). Through acquisitions from kerma values, the spectra were plotted. The MGD results obtained from the mammograph for Mo/Mo, Mo/Rh, and Rh/Rh were below the reported acceptable levels, while the spectra were mostly in accordance with the literature.

Measurement on the neutron and gamma radiation shielding performance of boron-doped titanium alloy Ti50Cu30Zr15B5 via arc melting technique

The significance of radiation shielding is on the rise due to the expanding areas exposed to radiation emissions. Consequently, there is a critical need to develop metal alloys and composites that exhibit excellent capabilities in absorbing neutron and gamma rays for effective radiation shielding. Low-density Ti-based alloys with controlled structural properties can be used for radiation protection purposes. The present research investigates boron-doped Ti-based alloy, Ti50Cu30Zr15B5, which is synthesized by arc melting technique, and its structural, mechanical properties, neutron, and gamma-ray transmission rate were investigated. Monte Carlo N-Particle simulation (MCNP6.2) code is used for calculating the Thermal (2.53 × 10−8 MeV) and fast (2 MeV) neutron transmission ratio (I/I0) dependent on the sample thickness. The Phy-x program is employed for calculating the gamma-ray LAC, MAC, HVL, TVL, and MFP values. The calculated neutron shielding performance parameters of Ti50Cu30Zr15B5 alloy were compared with materials in the literature. It was found that Ti50Cu30Zr15B5 alloy demonstrated impressive physical characteristics, suggesting that it can serve as a promising alloy for neutron and gamma-ray shielding applications.

Model construction and software design of computed tomography radiation system based on visualization

The Monte Carlo N-Particle (MCNP) is often used to calculate the radiation dose during computed tomography (CT) scans. However, the physical calculation process of the model is complicated, the input file structure of the program is complex, and the three-dimensional (3D) display of the geometric model is not supported, so that the researchers cannot establish an accurate CT radiation system model, which affects the accuracy of the dose calculation results. Aiming at these two problems, this study designed a software that visualized CT modeling and automatically generated input files. In terms of model calculation, the theoretical basis was based on the integration of CT modeling improvement schemes of major researchers. For 3D model visualization, LabVIEW was used as the new development platform, constructive solid geometry (CSG) was used as the algorithm principle, and the introduction of editing of MCNP input files was used to visualize CT geometry modeling. Compared with a CT model established by a recent study, the root mean square error between the results simulated by this visual CT modeling software and the actual measurement was smaller. In conclusion, the proposed CT visualization modeling software can not only help researchers to obtain an accurate CT radiation system model, but also provide a new research idea for the geometric modeling visualization method of MCNP.

Subcritical neutron noise measurements for plutonium systems with varying geometry and mass

Recently, experiments were performed at the National Criticality Experiments Research Center (NCERC) with Zero Power Physics Reactor (ZPPR) plates in two very different geometries. The intent of this set of experiments was to provide the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project team measured data of multiple radiation detector responses to be used in an adjustment of plutonium nuclear data. The work shown in this paper will focus on multiplicity results measured for subcritical arrangements of ZPPR plates in the two geometries. The Hage–Cifarelli formalism of the Feynman variance-to-mean method, a moments-based time-correlated neutron noise approach, was used. A validation of the methodology used to estimate uncertainties in the moments was performed and is presented. The effective neutron multiplication factor (keff) value were inferred from this analysis. The keffvalues were compared to simulated values using the radiation transport code Monte Carlo N-Particle® (MCNP). The results shown in this work provide evidence of larger bias in keffvalues as the geometric buckling of the system increases. This effect will be important for nuclear data validation and future adjustments of plutonium nuclear data.