Radiation Transport Model Research Articles

DG-IMEX method for a two-moment model for radiation transport in the [formula omitted] limit

We consider neutral particle systems described by moments of a phase-space density and propose a realizability-preserving numerical method to evolve a spectral two-moment model for particles interacting with a background fluid moving with nonrelativistic velocities. The system of nonlinear moment equations, with special relativistic corrections to O(v/c), expresses a balance between phase-space advection and collisions and includes velocity-dependent terms that account for spatial advection, Doppler shift, and angular aberration. The model is conservative for the correct O(v/c) Eulerian-frame number density and is consistent, to O(v/c), with Eulerian-frame energy and momentum conservation. This model is closely related to the one promoted by Lowrie et al. [1] and similar to models currently used to study transport phenomena in large-scale simulations of astrophysical environments. The proposed numerical method is designed to preserve moment realizability, which guarantees that the moments correspond to a nonnegative phase-space density. The realizability-preserving scheme consists of the following key components: (i) a strong stability-preserving implicit-explicit (IMEX) time-integration method; (ii) a discontinuous Galerkin (DG) phase-space discretization with carefully constructed numerical fluxes; (iii) a realizability-preserving implicit collision update; and (iv) a realizability-enforcing limiter. In time integration, nonlinearity of the moment model necessitates solution of nonlinear equations, which we formulate as fixed-point problems and solve with tailored iterative solvers that preserve moment realizability with guaranteed global convergence. We also analyze the simultaneous Eulerian-frame number and energy conservation properties of the semi-discrete DG scheme and propose a “spectral redistribution” scheme that promotes Eulerian-frame energy conservation. Through numerical experiments, we demonstrate the accuracy and robustness of this DG-IMEX method and investigate its Eulerian-frame energy conservation properties.

Observed Correlation Between Local Topography and Passive Neutron Measurements From the Dynamic Albedo of Neutrons (DAN) Instrument on the Mars Science Laboratory (MSL) Rover

AbstractThe Dynamic Albedo of Neutrons (DAN) instrument on the Mars Science Laboratory Curiosity rover primarily measures neutrons that have undergone interactions with rocks and materials in the rover's local environment. As the rover ascends Aeolis Mons, it may encounter more extreme local topography (e.g., cliffs, gullies, canyons). We present three parts of the rover's traverse in which local topography, expressed as the average local relief relative to the rover, is moderately to strongly correlated with an increase in passive thermal neutron count rates. These increases in count rates are consistent with results from radiation transport models of the instrument's performance near simulated topographic features. Additional DAN measurements in areas of high average local relief (>0.25 m) within 5 m of the instrument could bolster this correlation. DAN's sensitivity to topography in its passive mode could be utilized as a new measurement capability and has implications for the operation of future landed missions carrying neutron spectrometers (e.g., VIPER, MoonRanger, Lunar‐VISE).

Simulation and experimental benchmarking of a proton pencil beam scanning nozzle model for development of MR-integrated proton therapy.

MR-integrated proton therapy is under development. It consists of the unique challenge of integrating a proton pencil beam scanning (PBS) beam line nozzle with an magnetic resonance imaging (MRI) scanner. The magnetic interaction between these two components is deemed high risk as the MR images can be degraded if there is cross-talk during beam delivery and imageacquisition. To create and benchmark a self-consistent proton PBS nozzle model for empowering the next stages of MR-integrated proton therapy development, namely exploring and de-risking complete integrated prototype system designs including magnetic shielding of the PBS nozzle. Magnetic field (COMSOL ) and radiation transport (Geant4) models of a proton PBS nozzle located at OncoRay (Dresden, Germany) were developed according to the manufacturers specifications. Geant4 simulations of the PBS process were performed by using magnetic field data generated by the COMSOL simulations. In total 315 spots were simulated which consisted of a scan pattern with 5cm spot spacings and for proton energies of 70, 100, 150, 200, and 220MeV. Analysis of the simulated deflection at the beam isocenter plane was performed to determine the self-consistency of the model. The magnetic fringe field from a sub selection of 24 of the 315 spot simulations were directly compared with high precision magnetometer measurements. These focused on the maximum scanning setting of 20cm beam deflection as generated from the second scanning magnet in the PBS for a proton beam energy of 220MeV. Locations along the beam line central axis (CAX) were measured at beam isocenter and downstream of 22, 47, 72, 97, and 122cm. Horizontal off-axis positions were measured at 22cm downstream of isocenter ( 50, 100, and 150cm from CAX). The proton PBS simulations had good spatial agreement to the theoretical values in all 315 spots examined at the beam line isocenter plane (0-2.9mm differences or within 1.5% of the local spot deflection amount). Careful analysis of the experimental measurements were able to isolate the changes in magnetic fields due solely to the scanning magnet contribution, and showed 1.9 1.2 -9.4 1.2 changes over the range of measurement locations. Direct comparison with the equivalent simulations matched within the measurement apparatus and setup uncertainty in all but one measurementpoint. For the first time a robust, accurate and self-consistent model of a proton PBS nozzle assembly has been created and successfully benchmarked for the purposes of advancing MR-integrated proton therapy research. The model will enable confidence in further simulation based work on fully integrated designs including MRI scanners and PBS nozzle magnetic shielding in order to de-risk and realize the full potential of MR-integrated proton therapy.

Extension of a radiation transport model for water-equivalent, portal imaging dose applications

Extension of a radiation transport model for water-equivalent, portal imaging dose applications

Calibration of buried NaI(Tl) scintillator detectors for natural radionuclide measurement based on Monte Carlo modelling

Measurements of naturally occurring concentrations of 40K, and of the decay series of 238U and 232Th, are of interest in the earth sciences in general, and in particular, scintillator-based gamma spectrometers can be used for the low cost determination of burial dose rates in natural geological samples. We are currently developing a robust, portable, wireless detector specifically intended for field measurement of natural radionuclide concentrations and hence, the calculation of dose rates. One of the challenges in developing and applying such an instrument is reliable calibration. Most calibrations of field instruments depend on access to non-finite matrices of known K, U, Th activity concentrations, in either a 4π or 2π geometry; these are only available at a few facilities around the world. Here we investigate an alternative approach, based on the measurement of small samples containing well-known activity concentrations of only K or U or Th, and Monte-Carlo radiation transport modelling to convert the observed spectra into those expected from specific activity concentrations in a non-finite 4π geometry. We first validate our modelling procedure by simulating these observed spectra. The non-finite matrix calibration spectra are then predicted, and least-squares fitted to the spectrum observed at the centre of a 1 m3 of granite chips; the resulting predicted U, Th and K activity concentrations are compared with independently known values.

Field-based soil-plant uptake measurements of natural radionuclides for key vegetables and ghaf leaves in Abu Dhabi

With the thriving fossil fuel and nuclear based industries in the nation, radioecology has become necessary for the radiation safety and emergency-preparedness for the United Arab Emirates (UAE). Environmental radiation transport modelling in the UAE and the Arabian Peninsula are severely limited, as we discuss in this paper, due to lack of experiments specific to arid desert climates. To fill the missing gaps in the baseline arid region radioecological database, especially for the soil-plant uptake studies, rigorous field works have been conducted for the first time on the soil and plant in the farms and open fields of the UAE. We present Abu Dhabi based measurements of activity concentrations of radionuclides of natural origins, in soils, key vegetables (cucumber, tomato, and bell pepper), and leaves of ghaf - a prominent native tree. The empirical data are utilized to get the first published estimates of UAE-specific plant-soil concentration ratios (CR), measuring root uptake of radionuclides in nonleafy vegetables and native trees. Such systematic studies are very rare for arid sandy soils. For the 27 samples analyzed, the activity concentrations' (unit Bq kg−1) ranges are: 169–1746 for 40K, 12–19.5 for 226Ra, and 2.7–23.1 for 228Ra. Likewise, wide variability is seen in the averages of concentration ratios also, ranging in 1.05–4.94 for 40K, 0.14–1.82 for 226Ra, and 0.53–2.78 for 228Ra. A net bioaccumulation (concentration ratio >1) of some of these natural radionuclides is found in many samples, but no significant doses or hazard indices are found due to these three radionuclides in the UAE's soils and vegetations. The paper discusses the careful work through tens of field sampling exercises, well controlled sample processing, high resolution gamma spectrometry, and treatment of data from gamma counting rates to accumulated dose rate estimations.

High-purity germanium semiconductor modeling in the detector response function toolkit

We have extended the detector response function toolkit (DRiFT) to provide modeling capabilities of semiconductor sensors. DRiFT provides realistic nuclear instrumentation response by post-processing Monte-Carlo N-particle (MCNP®) radiation transport outputs. MCNP® is capable of modeling radiation transport in complex environments, but has limited detector physics and readout electronics modeling capabilities. Semiconductor detector response can be calculated with a high-fidelity for a flexible range of environments by utilizing MCNP® to simulate radiation interactions inside of detector volumes, and then using DRiFT to model charge transport and signal formation in the semiconductor, as well as the readout electronics. DRiFT models charge transport in the semiconductor, the preamplifier, shaping amplifier, pulse pile-up, and electronic noise to generate detector response. The semiconductor application in DRiFT can model a range of semiconductor materials, shapes, and sizes; and is demonstrated here for a large volume coaxial high-purity germanium (HPGe) detector. Here, we compare detector response functions of a coaxial HPGe detector with measurement of 60Co, 133Ba, and 137Cs at varying count rates, and we conduct a parameter study to demonstrate the effect of changing parameters in the DRiFT simulation. The HPGe detector response function shows excellent agreement with measurements of difference sources with varying dead times and count rates.

Density scaling approximation for Monte-Carlo simulations of radioactive plumes

The release of radioactive gas into the atmosphere can diffuse into large volumes of air downwind from the point of release. The extent of radioactivity can cover thousands of cubic meters of air. For such large volumes, the weather models used to predict the down-wind distribution of the plume and the radiation transport models used to predict the radiation reaching ground-level from the plume can take tens of hours of computer time on multi-node institutional High-Performance Computing facilities.In this paper we focus on the radiation transport aspect of plume modeling. We describe a phenomenological method for approximating the amounts of radiation that reach ground level from large volumes of a static radioactive plume that can be calculated on a stand-alone personal computer in much shorter computation times than those usually needed for such large volume evaluations. We refer to this method as the Density Scaling Approximation (DSA). Its ability to approximate ground-level count rates of large plumes comes from using a small-plume volume with a scaled-up value of air density to simulate the same number of scatterings that occur during transport in larger plume volumes at normal air density.We demonstrate the DSA by using a 100 m-diameter air-filled hemispherical dome geometry with a uniform volumetric activity of 135Xe gas throughout the air-filled volume. The DSA for a larger dome diameter is obtained by evaluating the 100 m dome with an air density scaled up by the linear ratio of the larger diameter to the 100 m diameter. We find that this approximation works well for dome diameters up to 1200 m – the largest diameter studied and a size more than sufficient for accounting for all the radiation from 135Xe. Moreover, most of our DSA results can be calculated over 500 times faster than corresponding full-sized geometry with normal air density.To help evaluate the accuracy of the DSA and gain insight into how well it can reproduce different regions of the spectra, we use three, easily understood regions of interest to compare the DSA results to the full-sized geometry at normal air density results. These regions are the full-energy peak, the region of single-Compton scattering, and the region of multiple-Compton scattering. We show how the dominance of the Compton scattering mechanism determines this division and thus provides insight into how Compton scattering is manifested in spectra from photon scattering through air in general, and how well the DSA approximation works.

Model-based evaluation of cloud geometry and droplet size retrievals from two-dimensional polarized measurements of specMACS

Abstract. Cloud radiative properties play a significant role in radiation and energy budgets and are influenced by both the cloud top height and the particle size distribution. Both cloud top heights and particle size distributions can be derived from 2-D intensity and polarization measurements by the airborne spectrometer of the Munich Aerosol Cloud Scanner (specMACS). The cloud top heights are determined using a stereographic method (Kölling et al., 2019), and the particle size distributions are derived in terms of the cloud effective radius and the effective variance from multidirectional polarized measurements of the cloudbow (Pörtge et al., 2023). In this study, the accuracy of the two methods is evaluated using realistic 3-D radiative transfer simulations of specMACS measurements of a synthetic field of shallow cumulus clouds, and possible error sources are determined. The simulations are performed with the 3-D Monte Carlo radiative transport model MYSTIC (Mayer, 2009) using cloud data from highly resolved large-eddy simulations (LESs). Both retrieval methods are applied to the simulated data and compared to the respective properties of the underlying cloud field from the LESs. Moreover, the influence of the cloud development on both methods is evaluated by applying the algorithms to idealized simulated data where the clouds did not change during the simulated overflight of 1 min over the cloud field. For the cloud top height retrieval, an absolute mean difference of less than 70 m with a standard deviation of about 130 m compared to the expected heights from the model is found. The elimination of the cloud development as a possible error source results in mean differences of (46±140) m. For the effective radius, an absolute average difference of about (-0.2±1.30) µm from the expected effective radius from the LES model input is derived for the realistic simulation and (-0.03±1.28) µm for the simulation without cloud development. The difference between the effective variance derived from the cloudbow retrieval and the expected effective variance is (0.02±0.05) for both simulations. Additional studies concerning the correlations between larger errors in the effective radius or variance and the optical thickness of the observed clouds have revealed that low values in the optical thickness do not have an impact on the accuracy of the retrieval.

Radiation and heat transport in divergent shock–bubble interactions

Shock–bubble interactions (SBIs) are important across a wide range of physical systems. In inertial confinement fusion, interactions between laser-driven shocks and micro-voids in both ablators and foam targets generate instabilities that are a major obstacle in achieving ignition. Experiments imaging the collapse of such voids at high energy densities (HED) are constrained by spatial and temporal resolution, making simulations a vital tool in understanding these systems. In this study, we benchmark several radiation and thermal transport models in the xRAGE hydrodynamic code against experimental images of a collapsing mesoscale void during the passage of a 300 GPa shock. We also quantitatively examine the role of transport physics in the evolution of the SBI. This allows us to understand the dynamics of the interaction at timescales shorter than experimental imaging framerates. We find that all radiation models examined reproduce empirical shock velocities within experimental error. Radiation transport is found to reduce shock pressures by providing an additional energy pathway in the ablation region, but this effect is small (∼1% of total shock pressure). Employing a flux-limited Spitzer model for heat conduction, we find that flux limiters between 0.03 and 0.10 produce agreement with experimental velocities, suggesting that the system is well-within the Spitzer regime. Higher heat conduction is found to lower temperatures in the ablated plasma and to prevent secondary shocks at the ablation front, resulting in weaker primary shocks. Finally, we confirm that the SBI-driven instabilities observed in the HED regime are baroclinically driven, as in the low energy case.

Mechanistic model of radiotherapy-induced lung fibrosis using coupled 3D agent-based and Monte Carlo simulations

BackgroundMechanistic modelling of normal tissue toxicities is unfolding as an alternative to the phenomenological normal tissue complication probability models. The latter, currently used in the clinics, rely exclusively on limited patient data and neglect spatial dose distribution information. Among the various approaches, agent-based models are appealing as they provide the means to include patient-specific parameters and simulate long-term effects in complex systems. However, Monte Carlo tools remain the state-of-the-art for modelling radiation transport and provide measurements of the delivered dose with unmatched precision.MethodsIn this work, we develop and characterize a coupled 3D agent-based – Monte Carlo model that mechanistically simulates the onset of the radiation-induced lung fibrosis in an alveolar segment. To the best of our knowledge, this is the first such model.ResultsOur model replicates extracellular matrix patterns, radiation-induced lung fibrosis severity indexes and functional subunits survivals that show qualitative agreement with experimental studies and are consistent with our past results. Moreover, in accordance with experimental results, higher functional subunits survival and lower radiation-induced lung fibrosis severity indexes are achieved when a 5-fractions treatment is simulated. Finally, the model shows increased sensitivity to more uniform protons dose distributions with respect to more heterogeneous ones from photon irradiation.ConclusionsThis study lays thus the groundwork for further investigating the effects of different radiotherapeutic treatments on the onset of radiation-induced lung fibrosis via mechanistic modelling.

GEOUNED: A new conversion tool from CAD to Monte Carlo geometry

The GEOUNED code is specifically designed to convert CAD models, defined using the B-rep approach, into MC radiation transport models, defined using the CSG approach, and vice versa from MC to CAD. This code incorporates standard features commonly found in conversion tools, including decomposition, conversion, and automatic void generation. Additionally, it introduces innovative features, mainly in the automatic void generation part, which are described in this article.GEOUNED has demonstrated successful application in highly detailed 3D models used in fusion neutronics, which are known for their complex geometries, particularly those utilized in ITER. The article includes examples showcasing GEOUNED's performance in these challenging models, as well as custom applications that highlight its flexibility in addressing non-standard problems. The code is open-source and utilizes Open CASCADE as the geometry engine, with FreeCAD serving as the Python API.

Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model

Abstract. In September 2020, a global aerosol forecasting model was implemented as an ensemble member of the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Global Ensemble Forecasting System (GEFS) v12.0.1 (hereafter referred to as “GEFS-Aerosols”). In this study, GEFS-Aerosols simulation results from 1 September 2019 to 30 September 2020 were evaluated using an aerosol budget analysis. These results were compared with results from other global models as well as reanalysis data. From this analysis, the global average lifetimes of black carbon (BC), organic carbon (OC), dust, sea salt, and sulfate are 4.06, 4.29, 4.59, 0.34, and 3.3 d, respectively, with the annual average loads of 0.14, 1.29, 4.52, 6.80, and 0.51 Tg. Compared with the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System–Goddard Chemistry Aerosol and Radiation Transport (GEOS4-GOCART) model, the aerosols in GEFS-Aerosols have a relatively short lifetime because of the faster removal processes in GEFS-Aerosols. Meanwhile, in GEFS-Aerosols, aerosol emissions are the determining factor for the mass and composition of aerosols in the atmosphere. The size (bin) distribution of aerosol emissions is as important as its total emissions, especially in simulations of dust and sea salt. Moreover, most importantly, the strong monthly and interannual variations in natural sources of aerosols in GEFS-Aerosols suggest that improving the accuracy of the prognostic concentrations of aerosols is important for applying aerosol feedback to weather and climate predictions.

Effects on the accelerating electron bunches due to the presence of sulfur hexafluoride or air in the linac waveguide

Sulfur hexafluoride gas (SF6) is used as a dielectric insulator in the acceleration process of certain medical linear accelerator waveguides. Nevertheless, some innovative development and investigation cases require intervention in the linear accelerator or, specifically, on the waveguide, which could affect the sealing of the device. In this regard, vacuum sealing systems can be compromised, affecting the properties of the radiation beams produced. The presence of sulfur hexafluoride or air inside the VARIAN 6/100 waveguide was investigated under different pressure conditions and non-uniform electric fields, adapting Monte Carlo simulation techniques for modeling radiation transport coupled with electric fields. Obtained results indicated the suitability of the proposed approach, while comparisons with theoretical approaches and experimental evidence supported the model's consistency.

Вычислительный фантом для дозиметрии красного костного мозга пятилетнего ребенка от инкорпорированных бета-излучателей

The red bone marrow (RBM) exposure due to bone-seeking radionuclides can lead to grave medical consequences. In particular, the increased risk of leukemia in people exposed due to contamination of the Techa River in 1950s is associated with the RBM exposure due to 89,90Sr. Improvement of the internal RBM dosimetry methods includes the development of computational phantoms that represent 3D models of the skeletal sites. Modeling radiation transport within such phantoms enables estimation of conversion factors from the radionuclide activity in the bone to the RBM dose rate. This paper is an extension study focused on generating a set of computational phantoms representing skeletons of individuals of different ages. The aim was to develop a computational phantom representing a 5-yearold child for internal RBM dosimetry from incorporated beta emitters. The phantoms of the skeletal sites with active hematopoiesis were created using the original Stochastic Parametric Skeletal Dosimetry (SPSD) method. With this method, every such site represented a set of smaller phantoms of simple geometric shape. RBM distribution across the skeleton, bone size, characteristics of bone micro-architecture, as well as density and chemical composition of the simulated media (RBM, bone) were determined based on the published data. As a result, a computational phantom of the major skeletal sites with active hematopoiesis representing a 5-year-old child was generated that included 43 phantoms of bone fragments. Linear dimensions of phantoms were within 3–75 mm. Micro-architecture parameters varied greatly: BV/TV ratio —13–52%, Tb. Th. — 0.09–0.29 mm, Tb. Sp. —0.48–0.98 mm.

Nanocomposite physics and structure considerations in MCNP proton shielding models

Background Deep space crewed missions require unique radiation shielding considerations. Due to mission duration and the heavy, high-energy nature of deep space radiation, the aluminum alloys that have historically been used for spacecrafts do not provide sufficient protection for crew members. Polymer-based nanocomposites have been proposed as potential radiation shielding materials for deep space applications; however, the high tunability of nanocomposites and the limited number of facilities able to produce representative radiation energies presents barriers to nanocomposite testing. Computational approaches may allow for preliminary investigation and discrimination of nanocomposite parameters like polymer and filler composition, loading percentage, and filler size and structure. Methods This work aims to investigate several modeling methods to perform radiation transport simulations for a nanocomposite, particularly with regards to modeling the filler nanostructure and the involved physics. Published experiments of a polydimethylsiloxane-carbon nanotube nanocomposite in 63 MeV and 105 MeV proton beams were digitally recreated in MCNP6.2 with three different nanocomposite structures. Additionally, several simulations were performed under various physics assumptions. The computationally determined water equivalent thicknesses are compared between modeling methods, as well as between the computational and the published experimental work. Results Nanostructure model complexity had no impact on the computed water equivalent thickness, with <1% difference between the three modeling methods. The inclusion of delta ray production and tracking physics produced a slight decrease in the computed water equivalent thickness and significantly increased the computational time for a single simulation by a factor of 35.7. Computationally determined water equivalent thicknesses are within 5% of published experimentally determined values. Conclusions Shielding capabilities of a polymer/carbon nanotube nanocomposite estimated using Monte Carlo radiation transport models agree well with published experimental results, even with a simplistic representation of the nanocomposite material. Radiation transport settings influenced the resulting water equivalent thickness as well as computational resource needs.

Non-intrusive model order reduction for parametric radiation transport simulations

We present a parametric, non-intrusive reduced-order model (ROM) for multigroup radiation transport, addressing the high computational cost and resource requirements associated with transport simulations in scenarios involving multiple queries. To achieve this, we employ Proper Orthogonal Decomposition (POD) to learn a groupwise reduced basis representation of the observed data (obtained from full-order simulations). We utilize Gaussian Process Regression and Multivariate Adaptive Regression Splines to learn the parametric, low-dimensional latent code (the reduced coordinates in the subspace spanned by the observed data). The approach is non-invasive, making it applicable to any software without the need for accessing the source code. We provide numerical results for various parametric problems, including a 3D multigroup transport case. Comparing the ROM-based surrogate to the full-order radiation transport model, solved using discrete ordinates in angle and discontinuous finite elements in space, we achieve a scalar flux solution that is 20,000 times faster with less than 1% relative error in a 3D transport scenario. Moreover, by utilizing the ROM, we demonstrate how a simple uncertainty quantification study can be completed within minutes, which would otherwise require significantly larger computational resources.

Radiation-induced double-strand breaks by internal ex vivo irradiation of lymphocytes: Validation of a Monte Carlo simulation model using GATE and Geant4-DNA

This study describes a method to validate a radiation transport model that quantifies the number of DNA double-strand breaks (DSB) produced in the lymphocyte nucleus by internal ex vivo irradiation of whole blood with the radionuclides 90Y, 99mTc, 123I, 131I, 177Lu, 223Ra, and 225Ac in a test vial using the GATE/Geant4 code at the macroscopic level and the Geant4-DNA code at the microscopic level. MethodsThe simulation at the macroscopic level reproduces an 8 mL cylindrical water-equivalent medium contained in a vial that mimics the geometry for internal ex vivo blood irradiation. The lymphocytes were simulated as spheres of 3.75 µm radius randomly distributed, with a concentration of 125 spheres/mL. A phase-space actor was attached to each sphere to register all the entering particles. The simulation at the microscopic level for each radionuclide was performed using the Geant4-DNA tool kit, which includes the clustering example centered on a density-based spatial clustering of applications with noise (DBSCAN) algorithm. The irradiation source was constructed by generating a single phase space from the sum of all phase spaces. The lymphocyte nucleus was defined as a water sphere of a 3.1 µm radius. The absorbed dose coefficients for lymphocyte nuclei (dLymph) were calculated and compared with macroscopic whole blood absorbed dose coefficients (dBlood). The DBSCAN algorithm was used to calculate the number of DSBs. Lastly, the number of DSB∙cell−1∙mGy−1 (simulation) was compared with the number of radiation-induced foci per cell and absorbed dose (RIF∙cell−1∙mGy−1) provided by experimental data for gamma and beta emitting radionuclides. For alpha emitters, dLymph and the number of α-tracks∙100 cell−1∙mGy−1 and DBSs∙µm−1 were calculated using experiment-based thresholds for the α-track lengths and DBSs/track values. The results were compared with the results of an ex vivo study with 223Ra. ResultsThe dLymph values differed from the dBlood values by −1.0% (90Y), −5.2% (99mTc), −22.3% (123I), 0.35% (131I), 2.4% (177Lu), −5.6% (223Ra) and −6.1% (225Ac). The number of DSB∙cell−1∙mGy−1 for each radionuclide was 0.015 DSB∙cell−1∙mGy−1 (90Y), 0.012 DSB∙cell−1∙mGy−1 (99mTc), 0.014DSB∙cell−1∙mGy−1 (123I), 0.012 DSB∙cell−1∙mGy−1 (131I), and 0.016 DSB∙cell−1∙mGy−1 (177Lu). These values agree very well with experimental data. The number of α-tracks∙100 cells−1∙mGy−1 for 223Ra and 225Ac where 0.144 α-tracks∙100 cells−1∙mGy−1 and 0.151 α-tracks∙100 cells−1∙mGy−1, respectively. These values agree very well with experimental data. Moreover, the linear density of DSBs per micrometer α-track length were 11.13 ± 0.04 DSB/µm and 10.86 ± 0.06 DSB/µm for 223Ra and 225Ac, respectively. ConclusionThis study describes a model to simulate the DNA DSB damage in lymphocyte nuclei validated by experimental data obtained from internal ex vivo blood irradiation with radionuclides frequently used in diagnostic and therapeutic procedures in nuclear medicine.

The uncertainty of estimation of doses to the bone marrow from <sup>89,90</sup>Sr due to the variability of the chemical composition and bone density

Dosimetric modeling of radiation transport in skeletal bone tissues using computational phantoms provides the doses of internal exposure to active marrow. Computational phantoms of ICRP are created for reference people with anatomical and physiological characteristics typical of an average individual. The doses calculated with such phantoms will correspond to certain population-average values. Individual variability will introduce a stochastic component of uncertainty into the dose estimation. The objective of this study is to assess the influence of variability of chemical composition and bone density on the results of dosimetric modeling. The phantoms are represented by simple geometry figures filled with trabecular structures and bone marrow and covered with a cortical layer. Radiation transport was simulated using the Monte Carlo method. The dose factors to convert the radionuclide activity concentration to absorbed dose rates in active marrow were calculated assuming uniform radionuclide distribution in the volume of the trabecular and cortical bone. As a result of the numerical experiments, it has been shown that variations in chemical composition do not introduce an error of more than ± 4% into dosimetric modeling. The effect of bone density on active marrow dose formation depends on the size of a phantom. For computational phantoms with linear dimensions exceeding two electron free path lengths (~ 0.44 cm), variability of bone density within ± 3% leads to a similar relative uncertainty of the dose conversion factor. However, for smaller phantoms, bone density variability leads to uncertainties of 6% or 13% for a source deposited in the trabecular or cortical bone, respectively. The results obtained will be used to assess the uncertainty of bone marrow dosimetry, taking into account the uncertainty of all parameters including the variability of morphometric characteristics of bones, the variability of the active marrow distribution in skeletal sites, as well as the uncertainties introduced by model approximations.

A Novel Algorithm for CAD to CSG Conversion in McCAD

Modeling and simulation lie at the heart of the design process of any nuclear application. An accurate representation of the radiation environment ensures not only the feasibility of new technologies, but it also aids in operation, maintenance, and even decommissioning. With increasingly complex designs, high-fidelity models have become a necessity for design maturity. McCAD has been under development for many years at Karlsruhe Institute of Technology (KIT) to facilitate the process of generating suitable models for nuclear analyses. In this paper, an overview of the major advances in the new version of the code is presented. A novel conversion algorithm has proven to be robust in significantly reducing the processing time to generate radiation transport models, making it easier to iterate on design details. A first-of-a-kind capability to generate hierarchical void cells is also discussed with preliminary analysis showing performance gains for particle tracking.