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This repository contains the laboratory data, Monte Carlo simulation data and computer codes associated with the analysis and results presented in the paper "Role of Intersections in Fracture Connectivity",Journal of Geophysical Research: Solid Earth, 130, e2025JB033007, https://doi.org/10.1029/2025JB033007.
Abstract not provided
Monte Carlo (MC) radiation transport simulations, like those performed using Monte Carlo N-Particle (MCNP), can be highly accurate but require time to reduce the statistical uncertainties in the calculated detector response(s). Many different 'variance reduction' techniques devised over the years increase the efficiency of MC calculations, but these methods can be more art than science. Many of these methods are problem specific or require careful tuning of parameters for good performance. One of the best variance reduction methods, in terms of both reliable performance increases and ease of use, is the use of weight windows. Weight windows are derived from an importance map in space and energy that allows the transport code to focus more simulation time on particles that have a higher likelihood of being important to the final detector response. Less time is spent simulating particles that have little chance of making a contribution to the detector response. MCNP already includes the abilities to generate and use weight windows. Unfortunately, generating weight windows can take a very long time, perhaps longer than the original problem. Oak Ridge National Laboratory has led the development of hybrid methods using a discrete ordinates adjoint calculation to quickly develop an importance map (weight windows) for use in a Monte Carlo code. The Consistent Adjoint Driven Importance Sampling (CADIS) method uses an adjoint calculation to develop both an importance map and a biased source distribution that work together. This method is reasonably automatic, is easy to use, and has been implemented in the Automated Variance reduction Generator (ADVANTG) package that works with MCNP5. ADVANTG reads an MCNP input file and a small amount of extra user information and then runs an adjoint deterministic calculation using Denovo. The importance map and biased source distribution derived from the CADIS method can then be incorporated back into the original MCNP input file to enhance the figure-of-merit (FOM) of the calculation. The FOM is a measure of the efficiency of the calculation using the amount of run time and corresponding level of statistical uncertainty in the detector result. ADVANTG-enhanced MCNP input files have been shown to increase the FOM of many types of problems, obtaining the same level of statistical uncertainty in a shorter time compared to standard MCNP. ADVANTG can also generate variance reduction parameters (importance map and biased source) using the Forward-Weighted CADIS (FW-CADIS) method for optimizing mesh tallies. The CADIS method creates variance reduction parameters that optimize a tally's total quantity (flux, dose rate, interaction rate, etc.) and will not generally increase performance for all parts of a segmented tally. To optimize a segmented tally, the FW-CADIS method uses two discrete ordinates calculations to make variance reduction parameters that help compute a segmented tally with uniform relative uncertainties in each bin. This report will demonstrate that using ADVANTG for neutron and photon radiation shielding problems will (1) preserve the standard MCNP results and (2) obtain those results either with less statistical uncertainty or in shorter times than the standard MCNP calculation. The four demonstration problems in this report are based on simple neutron or photon transmission measurements through different materials. All of the problems here used the CADIS method and still saw improvement across the flux tallies segmented by particle energy. (authors)
A computational model has been developed to simulate the performance of the Los Alamos Isotope Production Facility's (IPF) routine production target configuration, which consists of two Inconel-encapsulated RbCl salt targets and one niobium-encapsulated gallium target separated by water cooling channels. The methodology involves iteratively coupling particle transport and thermal hydraulic codes to determine the time dependent behavior of the target. Phase and density changes seen in targets are known to impact beam penetration and distribution. In addition, evidence of energy distributions seen in experimental radionuclide yield measurements at IPF do not match those seen in previous MCNP predictions. Density reduction as a result of heat deposition affects proton energy loss along the particle's track, impacting both radionuclide yields and target design. Accurate modeling of the thermal behavior of these multi-phase targets and the corresponding impact on beam behavior will significantly improve our understanding of incident and exit proton energy distributions and resulting radionuclide yields in downstream targets. Thermal hydraulic modeling, including computational fluid dynamics (CFD) and heat transfer, was performed with ANSYS CFX while particle transport was performed with the Monte Carlo N-Particle code (MCNP). (authors)
The P2 experiment at the MESA facility in Mainz aims to make a high precision measurement of the weak charge of the proton, and a suitable experimental setup is currently being designed [1]. As high precision measurements of the weak charges of different particles and nuclei are differently sensitive to physics beyond the Standard Model in the form of new quantum loop correction parameters, experiments with a range of different target materials are complementary. We introduce first feasibility considerations for the determination of the Weak Mixing Angle via the scattering of electrons from carbon nuclei in a graphite target with the P2 detector setup. In order to make an estimate of the achievable precision we present analytic calculations as well as Monte-Carlo simulations. The results of Geant4 simulations of proposed experimental setups are included.
The spectrum of gamma energy absorption in the NaI crystal (scintillation detector) is the interaction result of gamma photon with NaI crystal, and it’s associated with the photon gamma energy incoming to the detector. Through a simulation approach, we can perform an early observation of gamma energy absorption spectrum in a scintillator crystal detector (NaI) before the experiment conducted. In this paper, we present a simulation model result of gamma energy absorption spectrum for energy 100-700 keV (i.e. 297 keV, 400 keV and 662 keV). This simulation developed based on the concept of photon beam point source distribution and photon cross section interaction with the Monte Carlo method. Our computational code has been successfully predicting the multiple energy peaks absorption spectrum, which derived from multiple photon energy sources.
We have performed absolute calibrations of a fusion-neutron-yield copper-activation diagnostic in environments that significantly attenuate and scatter neutrons. We have measured attenuation and scattering effects and have compared the measurements to Monte Carlo simulations using the Monte Carlo N-Particle code. We find that measurements and simulations are consistent within 10%.
A theoretical model was developed to investigate the mechanism of the formation of nanoclusters via ion beam implantation. The evolution of nanoclusters, including the nucleation and growth process known as Ostwald ripening, was rebuilt using numerical simulations. The effects of implantation parameters such as the ion energy, ion fluence, and temperature on the morphology of implanted microstructures were also studied through integration with the Monte Carlo Transport of Ions in Matter code calculation for the distribution profiles of implanted ions. With an appropriate ion fluence, a labyrinth-like nanostructure with broad size distributions of nanoclusters formed along the ion implantation range. In a latter stage, a buried layer of implanted impurity developed. With decreasing ion energy, the model predicted the formation of precipitates on the surface. These simulation results were fully consistent with many experimental observations. With increased temperature, the characteristic length and size of nanostructures would increase due to the high mobility. This theoretical model provides an efficient numerical approach for fully understanding the mechanism of the formation of nanoclusters, allowing for the design of ion beam experiments to form specific nanostructures through ion-implantation technology.
A novel approach to facility radiometric characterization for non-uniformly distributed radiation sources has been developed by ANTECH and is currently being employed at the Argonne National Laboratory. It is being applied to the measurement of a wide range of objects and the interiors and contents of laboratories and buildings. The integrated non destructive assay measurement process involves the use of a scanning spectroscopic gamma ray camera as well as high purity Germanium detectors with different collimators and hence differing detector fields of view to measure and quantify non-uniformly distributed sources of radioactivity in laboratory equipment, glove boxes, storage tanks, pipework and general laboratory objects and process components. The purpose of the radiometric characterization is to quantify radiation sources and radioactive contamination levels in facilities containing nuclear material and to ensure compliance with facility characterization requirements and for decontamination and decommissioning planning and execution. The integrated measurement process also involves automated data capture and processing software and a database with which both measurement instrument operators and subject matter expert analysts can interact. An appropriate measuring instrument (gamma camera, scintillation detector, high purity Germanium detector system, neutron detector or alpha-beta counter) records the measurement data and the measurement site is recorded in a photograph. All of the data relevant to the measurement (or set of measurements for a particular object) are recorded in the database including measured gamma ray spectra, equipment description and relevant calibration, measurement site photograph and measurement descriptive data. Once data analysis protocols are established for specific geometries and measurement situations they can be applied to the measured data in a partially automated manner, reducing analysis and transcription errors. In addition to measurements and data analysis the process also utilises radiometric modelling computer codes including MicroShield and Monte Carlo Neutrons Photons in order to perform model calculations where appropriate. In a typical measurement, the ANTECH RadSearch spectroscopic gamma camera is utilized to find areas of concentrated activity so that these areas can be measured and calculated separately from areas with diffuse contamination. The use of the gamma camera in scanning mode helps to ensure that the assay does not overestimate the detected radiation source, which is a frequent consequence of using standard far field geometry and attenuation analysis codes that assume uniformity of both density and radioactive source distribution. Once the hot spots are identified, high purity Germanium detector measurements are made using various collimators with wide or narrow fields of view as required. These measurements are then processed through a semi-automatic calculation process assuming an appropriate source configuration as identified by RadSearch. These source configurations include point sources, line sources or surface sources. The Generalized Geometry Hold-up algorithms are employed to determine an estimate of the activity of the various sources that are identified in a measurement. The ANTECH integrated measurement process provides an automated calculation procedure where the analyst can select the source type, geometry and appropriate input data, and then the software calculates the activity by radionuclide for all sources identified in the measurement. The measurement and analysis process is controlled under the ANTECH ISO9001: 2008 Quality Assurance System and managed by a site specific Quality Assurance Plan. Both Argonne National Laboratory and Department of Energy technical reviewers have vetted the Integrated Measurement and Analysis Process. The application of the measurement and analysis process is described and measurement examples are provided. (authors)
The Griffin code is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. The code includes a variety of deterministic steady-state transport solvers for fixed source, k-eigenvalue, adjoint, and subcritical multiplication as well as transient solvers for spatial dynamics with the improved quasi-static method. Griffin uses cross section data in the ISOXML format generated from external deterministic or Monte Carlo cross section generation codes. In recent years, the MC 2 -3 modules have been added to Griffin for fast reactor cross section generation, and the self-shielding application programming interface (SSAPI) was implemented in the ISOXML module for thermal reactor cross section generation. The on-the-fly slowing down method and double-heterogeneity treatment have been implemented to SSAPI and verified against particulate fuel-bearing graphite-moderated thermal reactor problems with high accuracy. This year, work has been focused on improving the cross section generation capability of ISOXML and streamlining the cross section generation procedures. In addition, the form function data were added to ISOXML in order to support the pin power reconstruction capability that was newly implemented in Griffin in this fiscal year. To facilitate the cross section generation using MC 2 -3 and SSAPI in Griffin, the cross section generation workflows have been set up for both fast and thermal spectrum reactors. The MOOSE action system tool was devised for fast spectrum problems, and the MOOSE stochastic tool was adopted to the branch calculation procedure for thermal spectrum problems. Meanwhile, to ensure the accuracy of group-constants, the thermal up-scattering kernel calculator accounting for resonance scattering was implemented in ISOXML, demonstrating the accurate computation of a Doppler-broadened scattering kernel of any Legendre order within a reasonable timescale. Other aspects of ISOXML, such as deletion solver and data, documentation, ISOXML file management, and the interface for Mixture, were improved as well.
The effective delayed neutron (β$_{eff}$) is a very important parameter for reactor and criticality applications. This parameter is equal to the difference in reactivity between delayed critical ($k_{eff}$ = 1, which requires both prompt and delayed neutrons to achieve criticality) and prompt critical ($k_p$ = 1, which requires only prompt neutrons to achieve criticality). This is often referred to as the delayed critical "window" (the region of criticality between delayed and prompt critical). β$_{eff}$ is a reactor kinetics parameters and depends on the nuclides in the system that undergo fission as well as the spectral characteristics of the system. Measurements of β$_{eff}$ have been performed for many criticality experiments. The EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) project at Los Alamos National Laboratory (LANL) aims to constrain nuclear data by using a suite of measurement types beyond $k_{eff}$. Our team has recently investigated the use of pulsed spheres for nuclear data validation. Several other measurement methods are also of interest, including β$_{eff}$ (investigated here) and reactivity coefficients (investigated in a separate work at this same meeting). One focus of our work is to determine if other methods are complimentary to the critical experiments already utilized for nuclear data validation. This is important because if a method has similar sensitivities then it will not be particularly useful for nuclear data validation as it will provide the same information as the critical experiments already being used. Here "similar" could refer to several characteristics, one being the shape of a sensitivity profile over energy. In the future, these methods will be utilized (with both existing and new experiments) in machine learning algorithms for nuclear validation, similar to what is currently done for criticality experiments. In order to use a measurement type for nuclear validation, it is necessary to obtain cross-section sensitivities for that parameter. This work looks at one approach to estimate β$_{eff}$ sensitivities by utilizing $k_{eff}$ sensitivities within Monte Carlo N-Particle ® Code Version 6.2. This is applied to several criticality benchmarks. Results are compared and the benefits and limitations of this approach are discussed.
In detector systems, the minimum time separation between the events is called detector's deadtime. The The intrinsic properties of the detector and the pulse processing circuitry's characteristics are the sources of deadtime. Researchers have been working on improving a detector deadtime model that can implicitly characterize a detection system's behavior while reducing counting errors. There are two commonly known dead-time models: the 'Paralyzing' and the 'Non-paralyzing' models. In reality, detection systems fit neither of these idealized models perfectly, instead falling somewhere between the two models. The paralyzing model is mathematically expressed by eq. 1, where m is the measured count rate, n is the true count rate and t is dead-time. This model assumes that each event during the dead-time will reset it to a fixed duration, thus extending the deadtime. The dead-time extension depends on the count rate. According to the non-paralyzing model, deadtime is fixed after each detected event, and all events occurring during deadtime are lost. The fraction of time during which an apparatus is sensitive is 1-mt. Therefore, the fraction of the true number of events can be recorded. In this study, a Canberra {sup 3}He neutron detector (0.5NH1/1K) deadtime value was estimated using a combination of experimental subcritical assembly measurements and theoretical MCNP simulations. The deadtime of the Canberra 10 mm diameter {sup 3}He tube detector was calculated by comparing measured counts from different locations in the subcritical assembly at Missouri University of Science and Technology Reactor (MSTR) with MCNP (Monte Carlo N-Particle Code) simulations. The deadtime calculations are provided for both the paralyzing and non-paralyzing models for the Canberra 10 mm diameter {sup 3}He tube detector. (authors)
An advanced neutral particle analyzer (ANPA) capable of simultaneously measuring hydrogen and deuterium ions of energies up to 45 keV has recently been developed for use on the Madison Symmetric Torus. The charge-to-mass separation allows for separate analysis of bulk deuterium ions and hydrogen ions injected with a 1 MW, 25 keV neutral beam. Orientation of the ANPA allows sampling of different regions of ion velocity space; a radial viewport favors collection of ions with high v{sub Up-Tack }/ Double-Vertical-Line v Double-Vertical-Line while a recently installed tangential viewport favors ions with high v{sub Double-Vertical-Line Double-Vertical-Line }/ Double-Vertical-Line v Double-Vertical-Line , such as those from the core-localized fast ion population created by the neutral beam. Signals are observed in the ANPA's highest energy channels during periodic magnetic reconnection events, which are drivers of anisotropic, non-Maxwellian ion energization in the reversed-field pinch. ANPA signal strength is dependent on the background neutral density, which also increases during magnetic reconnection events, so careful analysis must be performed to identify the true change in the ion distribution. A Monte Carlo neutral particle tracing code (NENE) is used to reconstruct neutral density profiles based on D{sub {alpha}} line emission, which is measured using a 16-chord filtered photodiode array.
Twenty-eight slides give information about the work of the US DOE/NNSA Nuclear Criticality Safety Program on MCNP6 under the following headings: MCNP6.1.1 Release, with ENDF/B-VII.1; Verification/Validation; User Support & Training; Performance Improvements; and Work in Progress. Whisper methodology will be incorporated into the code, and run speed should be increased.
Purpose: A new design of a solid-state-microdetector based on silicon 3D microfabrication and its performance to characterise Lineal energy, Specific Energy, dose, LET and other microdosimetric variables required for modelling particle relative biological effectiveness (RBE) is presented. Methods: A microdosimeter formed by a matrix of independent sensors with well-defined micrometric cylindrical shape and with a volume similar to those of cellular dimensions is used to measure microdosimetric variables. Each sensor measures the radiation deposited energy which, divided by the mean cord length of the sensors, provides us with the Linear Energy (y) of the radiation as well as its energy distribution, and frequencymean. Starting from the these distributions in different points of a proton beam, we generate biophysical data (e.g. Linear Energy Transfer (LET), Specific Energy (z), etc…) needed for relative biological effectiveness (RBE) calculations radiation effect models used in particle radiotherapy treatment planning. In addition, a Tissue Equivalent Proportional Counter (TEPC) will be used as baseline to calibrate the “y” magnitude of the microdosimeter unit-cells. Results: The experimental measurements will soon be carried out at the Perelman Center for Advanced Medicine (University of Pennsylvania), which provides proton beam for clinical research proposals. The results of distributions measured of the microdosimetric variables from the first tests developed in the proton facility will be presented and compared with Monte Carlo simulations using the Geant4 code. Conclusion: The use of 3D microdosimeters such as the one presented here will enhance the accuracy of RBE calculations normally affected by the inherent uncertainty of monte carlo simulations due to the approximation of material composition and energy dependent physical laws involved in such calculations. The effect of such approximations will be quatified by comparison with absolute measurement of radiation quality parameters.
It is well-known that statistical estimates obtained from Monte Carlo criticality simulations can be adversely affected by cycle-to-cycle correlations in the fission source, which can lead to estimates of statistical uncertainties that are lower than the true uncertainty by a factor of 5 or more. However, several other more fundamental issues such as adequate source sampling over the fissionable regions and source convergence can have a significant impact on the uncertainties for the calculated eigenvalue and localized tally means, and these issues may be mistaken for effects resulting from cycle-to-cycle correlations. In worst-case scenarios, the uncertainty may be underpredicted by a factor of 40 or more. Since Monte Carlo methods are widely used in criticality safety applications and are increasingly being used for benchmarking reactor analyses, an in-depth understanding of the effects of these issues must be developed in order to support the practical use of Monte Carlo software packages. A rigorous statistical analysis of eigenvalue and localized tally results in Monte Carlo criticality calculations is presented using the SCALE/KENO-VI (continuous-energy version) and MCNP codes. The purpose of this analysis is to investigate the underprediction of uncertainty and its sensitivity to problem characteristics and calculational parameters using two of the most widely used Monte Carlo criticality codes. For the problems considered here, which are fuel rod and fuel assembly problems with reflecting boundary conditions on all four horizontal sides, we show that adequate source convergence along with proper specification of Monte Carlo parameters can reduce the magnitude of uncertainty underprediction to reasonable levels, below a factor of 2 in most cases.
When dealing with nuclear reactor calculation schemes, the need for three dimensional (3D) transport-based reference solutions is essential for both validation and optimization purposes. Considering a benchmark problem, this work investigates the potential of discrete ordinates (Sn) transport methods applied to 3D pressurized water reactor (PWR) full-core calculations. First, the benchmark problem is described. It involves a pin-by-pin description of a 3D PWR first core, and uses a 8-group cross-section library prepared with the DRAGON cell code. Then, a convergence analysis is performed using the PENTRAN parallel Sn Cartesian code. It discusses the spatial refinement and the associated angular quadrature required to properly describe the problem physics. It also shows that initializing the Sn solution with the EDF SPN solver COCAGNE reduces the number of iterations required to converge by nearly a factor of 6. Using a best estimate model, PENTRAN results are then compared to multigroup Monte Carlo results obtained with the MCNP5 code. Good consistency is observed between the two methods (Sn and Monte Carlo), with discrepancies that are less than 25 pcm for the k{sub eff}, and less than 2.1% and 1.6% for the flux at the pin-cell level and for the pin-power distribution, respectively. (authors)
The high-fluence neutron spectrum produced by the National Ignition Facility (NIF) provides an opportunity to measure the activation of materials by fast-spectrum neutrons. A new large-volume gas-cell diagnostic has been designed and qualified to measure the activation of gaseous substances at the NIF. This in-chamber diagnostic is recoverable, reusable and has been successfully fielded. Data from the qualification of the diagnostic have been used to benchmark an Monte Carlo N-Particle Transport Code simulation describing the downscattered neutron spectrum seen by the gas cell. We present early results from the use of this diagnostic to measure the activation of {sup nat}Xe and discuss future work to study the strength of interactions between plasma and nuclei.