Validation of a Monte Carlo Based Depletion Methodology Using HFIR Post-Irradiation Measurements
Chandler, David [ORNL; Maldonado, G Ivan [ORNL; Primm, Trent [ORNL
2009-11-01
Post-irradiation uranium isotopic atomic densities within the core of the High Flux Isotope Reactor (HFIR) were calculated and compared to uranium mass spectrographic data measured in the late 1960s and early 70s [1]. This study was performed in order to validate a Monte Carlo based depletion methodology for calculating the burn-up dependent nuclide inventory, specifically the post-irradiation uranium
Tippayakul, Chanatip
The main objective of this research is to develop a practical fuel management system for the Pennsylvania State University Breazeale research reactor (PSBR) based on several advanced Monte Carlo coupled depletion methodologies. Primarily, this research involved two major activities: model and method developments and analyses and validations of the developed models and methods. The starting point of this research was the utilization of the earlier developed fuel management tool, TRIGSIM, to create the Monte Carlo model of core loading 51 (end of the core loading). It was found when comparing the normalized power results of the Monte Carlo model to those of the current fuel management system (using HELIOS/ADMARC-H) that they agreed reasonably well (within 2%--3% differences on average). Moreover, the reactivity of some fuel elements was calculated by the Monte Carlo model and it was compared with measured data. It was also found that the fuel element reactivity results of the Monte Carlo model were in good agreement with the measured data. However, the subsequent task of analyzing the conversion from the core loading 51 to the core loading 52 using TRIGSIM showed quite significant difference of each control rod worth between the Monte Carlo model and the current methodology model. The differences were mainly caused by inconsistent absorber atomic number densities between the two models. Hence, the model of the first operating core (core loading 2) was revised in light of new information about the absorber atomic densities to validate the Monte Carlo model with the measured data. With the revised Monte Carlo model, the results agreed better to the measured data. Although TRIGSIM showed good modeling and capabilities, the accuracy of TRIGSIM could be further improved by adopting more advanced algorithms. Therefore, TRIGSIM was planned to be upgraded. The first task of upgrading TRIGSIM involved the improvement of the temperature modeling capability. The new TRIGSIM was
The purpose of this study is to validate a Monte Carlo based depletion methodology by comparing calculated post-irradiation uranium isotopic compositions in the fuel elements of the High Flux Isotope Reactor (HFIR) core to values measured using uranium mass-spectrographic analysis. Three fuel plates were analyzed: two from the outer fuel element (OFE) and one from the inner fuel element (IFE). Fuel plates O-111-8, O-350-I, and I-417-24 from outer fuel elements 5-O and 21-O and inner fuel element 49-I, respectively, were selected for examination. Fuel elements 5-O, 21-O, and 49-I were loaded into HFIR during cycles 4, 16, and 35, respectively (mid to late 1960s). Approximately one year after each of these elements were irradiated, they were transferred to the High Radiation Level Examination Laboratory (HRLEL) where samples from these fuel plates were sectioned and examined via uranium mass-spectrographic analysis. The isotopic composition of each of the samples was used to determine the atomic percent of the uranium isotopes. A Monte Carlo based depletion computer program, ALEPH, which couples the MCNP and ORIGEN codes, was utilized to calculate the nuclide inventory at the end-of-cycle (EOC). A current ALEPH/MCNP input for HFIR fuel cycle 400 was modified to replicate cycles 4, 16, and 35. The control element withdrawal curves and flux trap loadings were revised, as well as the radial zone boundaries and nuclide concentrations in the MCNP model. The calculated EOC uranium isotopic compositions for the analyzed plates were found to be in good agreement with measurements, which reveals that ALEPH/MCNP can accurately calculate burn-up dependent uranium isotopic concentrations for the HFIR core. The spatial power distribution in HFIR changes significantly as irradiation time increases due to control element movement. Accurate calculation of the end-of-life uranium isotopic inventory is a good indicator that the power distribution variation as a function of space and
MCOR - Monte Carlo depletion code for reference LWR calculations
Research highlights: → Introduction of a reference Monte Carlo based depletion code with extended capabilities. → Verification and validation results for MCOR. → Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations
MCOR - Monte Carlo depletion code for reference LWR calculations
Puente Espel, Federico, E-mail: fup104@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Tippayakul, Chanatip, E-mail: cut110@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Ivanov, Kostadin, E-mail: kni1@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Misu, Stefan, E-mail: Stefan.Misu@areva.com [AREVA, AREVA NP GmbH, Erlangen (Germany)
2011-04-15
Research highlights: > Introduction of a reference Monte Carlo based depletion code with extended capabilities. > Verification and validation results for MCOR. > Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations. Additionally
Monte Carlo simulation in UWB1 depletion code
UWB1 depletion code is being developed as a fast computational tool for the study of burnable absorbers in the University of West Bohemia in Pilsen, Czech Republic. In order to achieve higher precision, the newly developed code was extended by adding a Monte Carlo solver. Research of fuel depletion aims at development and introduction of advanced types of burnable absorbers in nuclear fuel. Burnable absorbers (BA) allow the compensation of the initial reactivity excess of nuclear fuel and result in an increase of fuel cycles lengths with higher enriched fuels. The paper describes the depletion calculations of VVER nuclear fuel doped with rare earth oxides as burnable absorber based on performed depletion calculations, rare earth oxides are divided into two equally numerous groups, suitable burnable absorbers and poisoning absorbers. According to residual poisoning and BA reactivity worth, rare earth oxides marked as suitable burnable absorbers are Nd, Sm, Eu, Gd, Dy, Ho and Er, while poisoning absorbers include Sc, La, Lu, Y, Ce, Pr and Tb. The presentation slides have been added to the article
Monte Carlo solver for UWB1 nuclear fuel depletion code
Highlights: • A new Monte Carlo solver was developed in order to speed-up depletion calculations. • For LWR model, UWB1 Monte Carlo solver is on average 10 times faster than MCNP6. • The UWB1 code will allow faster calculation analysis of BA parameters in fuel design. - Abstract: Recent nuclear reactor burnable absorber research tries to introduce new materials in the nuclear fuel. As a part of this effort, a fast computational tool is being developed for the advanced nuclear fuel. The first version of the newly developed UWB1 fast nuclear fuel depletion code significantly reduced calculation time by omitting the solution step for the Boltzmann transport equation. However, estimation of neutron multiplication factor during depletion was not sufficiently calculated. Therefore, at least one transport calculation for fuel depletion is necessary. This paper presents a new Monte Carlo solver that is implemented into the UWB1 code. The UWB1 Monte Carlo solver calculates neutron multiplication factor and neutron flux in the fuel for collapsed cross sections. Accuracy of the solver is supported by using current nuclear data stored in the ENDF/B-VII.1 library. Speed of the solver is the product of development focusing on minimization of CPU utilization at the expense of RAM demands. The UWB1 Monte Carlo solver is approximately 14 times faster than the MCNP6 reference code when one transport equation solution within fuel depletion is compared. Another speed-up can be achieved by employing advanced depletion scheme in the coupled transport and burnup equations. The resulting faster code will be used in optimization studies for ideal burnable absorber material selection where many various materials and concentrations will be evaluated
Monte Carlo depletion analysis of a PWR integral fuel burnable absorber by MCNAP
The MCNAP is a personal computer-based continuous energy Monte Carlo (MC) neutronics analysis program written on C++ language. For the purpose of examining its qualification, a comparison of the depletion analysis of three integral burnable fuel assemblies of the pressurized water reactor(PWR) by the MCNAP and deterministic fuel assembly(FA) design vendor codes is presented. It is demonstrated that the continuous energy MC calculation by the MCNAP can provide a very accurate neutronics analysis method for the burnable absorber FA's. It is also demonstrated that the parallel MC computation by adoption of multiple PC's enables one to complete the lifetime depletion analysis of the FA's within the order of hours instead of order of days otherwise. (orig.)
XIAO Chang-Ming; GUO Ji-Yuan; HU Ping
2006-01-01
@@ According to the acceptance ratio method, the influences on the depletion interactions between a large sphere and a plate from another closely placed large sphere are studied by Monte Carlo simulation. The numerical results show that both the depletion potential and depletion force are affected by the presence of the closely placed large sphere; the closer the large sphere are placed to them, the larger the influence will be. Furthermore, the influences on the depletion interactions from another large sphere are more sensitive to the angle than to the distance.
Progress on burnup calculation methods coupling Monte Carlo and depletion codes
Leszczynski, Francisco [Comision Nacional de Energia Atomica, San Carlos de Bariloche, RN (Argentina). Centro Atomico Bariloche]. E-mail: lesinki@cab.cnea.gob.ar
2005-07-01
Several methods of burnup calculations coupling Monte Carlo and depletion codes that were investigated and applied for the author last years are described. here. Some benchmark results and future possibilities are analyzed also. The methods are: depletion calculations at cell level with WIMS or other cell codes, and use of the resulting concentrations of fission products, poisons and actinides on Monte Carlo calculation for fixed burnup distributions obtained from diffusion codes; same as the first but using a method o coupling Monte Carlo (MCNP) and a depletion code (ORIGEN) at a cell level for obtaining the concentrations of nuclides, to be used on full reactor calculation with Monte Carlo code; and full calculation of the system with Monte Carlo and depletion codes, on several steps. All these methods were used for different problems for research reactors and some comparisons with experimental results of regular lattices were performed. On this work, a resume of all these works is presented and discussion of advantages and problems found are included. Also, a brief description of the methods adopted and MCQ system for coupling MCNP and ORIGEN codes is included. (author)
Monte Carlo depletion calculations for nuclear reactors are affected by the presence of stochastic noise in the local flux estimates produced during the calculation. The effects of this random noise and its propagation between timesteps during long depletion simulations are not well understood. To improve this understanding, a series of Monte Carlo depletion simulations have been conducted for a 3-D, eighth-core model of the H.B. Robinson PWR. The studies were performed by using the in-line depletion capability of the MC21 Monte Carlo code to produce multiple independent depletion simulations. Global and local results from each simulation are compared in order to determine the variance among the different depletion realizations. These comparisons indicate that global quantities, such as eigenvalue (keff), do not tend to diverge among the independent depletion calculations. However, local quantities, such as fuel concentration, can deviate wildly between independent depletion realizations, especially at high burnup levels. Analysis and discussion of the results from the study are provided, along with several new observations regarding the propagation of random noise during Monte Carlo depletion calculations. (author)
Depletion of a BWR lattice using the racer continuous energy Monte Carlo code
In the past several years there has been a renewed interest in the accuracy of a new generation of lattice physics codes. Most of the time these codes are benchmarked against Monte Carlo codes only at beginning of cycle. In this paper a highly heterogeneous BWR lattice depletion benchmark problem is presented. Results of a 40% void depletion using the RACER continuous energy Monte Carlo code are also presented. Complete problem specifications are given so that comparisons with lattice physics codes or other Monte Carlo codes is possible. The RACER calculations were performed with the ENDF/B-V cross section set. Each flux calculation utilized 2.7 million histories resulting in 95% confidence intervals of ∼1 milli-k on the eigenvalue and ∼1% uncertainties on pin-wise power fractions. Timing statistics for the calculation using the vectorized RACER code averaged ∼ 24,000 neutrons/minute on a single processor of a CRAY-C90 computer
The development of depletion program coupled with Monte Carlo computer code
The paper presents the development of depletion code for light water reactor coupled with MCNP5 code called the MCDL code (Monte Carlo Depletion for Light Water Reactor). The first order differential depletion system equations of 21 actinide isotopes and 50 fission product isotopes are solved by the Radau IIA Implicit Runge Kutta (IRK) method after receiving neutron flux, reaction rates in one group energy and multiplication factors for fuel pin, fuel assembly or whole reactor core from the calculation results of the MCNP5 code. The calculation for beryllium poisoning and cooling time is also integrated in the code. To verify and validate the MCDL code, high enriched uranium (HEU) and low enriched uranium (LEU) fuel assemblies VVR-M2 types and 89 fresh HEU fuel assemblies, 92 LEU fresh fuel assemblies cores of the Dalat Nuclear Research Reactor (DNRR) have been investigated and compared with the results calculated by the SRAC code and the MCNPREBUS linkage system code. The results show good agreement between calculated data of the MCDL code and reference codes. (author)
ORPHEE research reactor: 3D core depletion calculation using Monte-Carlo code TRIPOLI-4®
Damian, F.; Brun, E.
2014-06-01
ORPHEE is a research reactor located at CEA Saclay. It aims at producing neutron beams for experiments. This is a pool-type reactor (heavy water), and the core is cooled by light water. Its thermal power is 14 MW. ORPHEE core is 90 cm height and has a cross section of 27x27 cm2. It is loaded with eight fuel assemblies characterized by a various number of fuel plates. The fuel plate is composed of aluminium and High Enriched Uranium (HEU). It is a once through core with a fuel cycle length of approximately 100 Equivalent Full Power Days (EFPD) and with a maximum burnup of 40%. Various analyses under progress at CEA concern the determination of the core neutronic parameters during irradiation. Taking into consideration the geometrical complexity of the core and the quasi absence of thermal feedback for nominal operation, the 3D core depletion calculations are performed using the Monte-Carlo code TRIPOLI-4® [1,2,3]. A preliminary validation of the depletion calculation was performed on a 2D core configuration by comparison with the deterministic transport code APOLLO2 [4]. The analysis showed the reliability of TRIPOLI-4® to calculate a complex core configuration using a large number of depleting regions with a high level of confidence.
Monte Carlo Depletion Analysis of a TRU-Cermet Fuel. Design for a Sodium Cooled Fast Reactor
Monte Carlo depletion has generally not been considered practical for designing the equilibrium cycle of a reactor. One objective of the work here was to demonstrate that recent advances in high performance computing clusters is making Monte Carlo core depletion competitive with traditional deterministic depletion methods for some applications. The application here was to a sodium fast reactor core with an innovative TRU cermet fuel type. An equilibrium cycle search was performed for a multi-batch core loading using the Monte Carlo depletion code Monteburn. A final fuel design of 38% w/o TRU with a pin radius of 0.32 cm was found to display similar operating characteristics to its metal fueled counterparts. The TRU-cermet fueled core has a smaller sodium void worth, and a less negative axial expansion coefficient. These effects result in a core with safety characteristics similar to the metal fuel design, however, the TRU consumption rate of the cermet fueled core is found to be higher than that of the metal fueled core. (authors)
Qin, Jianguo; Lai, Caifeng; Liu, Rong; Zhu, Tonghua; Zhang, Xinwei; Ye, Bangjiao
2015-01-01
To overcome the problem of inefficient computing time and unreliable results in MCNP5 calculation, a two-step method is adopted to calculate the energy deposition of prompt gamma-rays in detectors for depleted uranium spherical shells under D-T neutrons irradiation. In the first step, the gamma-ray spectrum for energy below 7 MeV is calculated by MCNP5 code; secondly, the electron recoil spectrum in a BC501A liquid scintillator detector is simulated based on EGSnrc Monte Carlo Code with the g...
Coevolution Based Adaptive Monte Carlo Localization (CEAMCL
Luo Ronghua
2008-11-01
Full Text Available An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot's pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robot's pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL. Experiments have been carried out to prove the efficiency of the new localization algorithm.
Coevolution Based Adaptive Monte Carlo Localization (CEAMCL)
Luo Ronghua; Hong Bingrong
2004-01-01
An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot's pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the unce...
Qin, Jianguo; Liu, Rong; Zhu, Tonghua; Zhang, Xinwei; Ye, Bangjiao
2015-01-01
To overcome the problem of inefficient computing time and unreliable results in MCNP5 calculation, a two-step method is adopted to calculate the energy deposition of prompt gamma-rays in detectors for depleted uranium spherical shells under D-T neutrons irradiation. In the first step, the gamma-ray spectrum for energy below 7 MeV is calculated by MCNP5 code; secondly, the electron recoil spectrum in a BC501A liquid scintillator detector is simulated based on EGSnrc Monte Carlo Code with the gamma-ray spectrum from the first step as input. The comparison of calculated results with experimental ones shows that the simulations agree well with experiment in the energy region 0.4-3 MeV for the prompt gamma-ray spectrum and below 4 MeVee for the electron recoil spectrum. The reliability of the two-step method in this work is validated.
Accelerated GPU based SPECT Monte Carlo simulations.
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational
Accelerated GPU based SPECT Monte Carlo simulations
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency
CERN Summer Student Report 2016 Monte Carlo Data Base Improvement
Caciulescu, Alexandru Razvan
2016-01-01
During my Summer Student project I worked on improving the Monte Carlo Data Base and MonALISA services for the ALICE Collaboration. The project included learning the infrastructure for tracking and monitoring of the Monte Carlo productions as well as developing a new RESTful API for seamless integration with the JIRA issue tracking framework.
Full text of publication follows. We propose a novel approach for simulating, with atomistic kinetic Monte Carlo (KMC), the segregation or depletion of solute atoms at interfaces, via transport by vacancies. Differently from classical lattice KMC, no assumption is made regarding the crystallographic structure. The model can thus potentially be applied to any type of interfaces, e.g. grain boundaries. Fully off-lattice KMC models were already proposed in the literature, but are rather demanding in CPU time, mainly because of the necessity to perform static relaxation several times at every step of the simulation, and to calculate migration energies between different metastable states. In our LA-KMC model, we aim at performing static relaxation only once per step at the most, and define possible transitions to other metastable states following a generic predefined procedure. The corresponding migration energies can then be calculated using artificial neural networks, trained to predict them as a function of a full description of the local atomic environment, in term of both the exact location in space of atoms and in term of their chemical nature. Our model is thus a compromise between fully off-lattice and fully on-lattice models: (a) The description of the system is not bound to strict assumptions, but is readapted automatically performing the minimum required amount of static relaxation; (b) The procedure to define transition events is not guaranteed to find all important transitions, and is thereby potentially disregarding some mechanisms of system evolution. This shortcoming is in fact classical to non-fully off-lattice models, but is in our case limited thanks to the application of relaxation at every step; (c) Computing time is largely reduced thanks to the use of neural network to calculate the migration energies. In this presentation, we show the premises of this novel approach, in the case of grain-boundaries for bcc Fe-Cr alloys. (authors)
Jian-Guo, Qin; Cai-Feng, Lai; Rong, Liu; Tong-Hua, Zhu; Xin-Wei, Zhang; Bang-Jiao, Ye
2016-03-01
To overcome the problem of inefficient computing time and unreliable results in MCNP5 calculation, a two-step method is adopted to calculate the energy deposition of prompt γ-rays in detectors for depleted uranium spherical shells under D-T neutron irradiation. In the first step, the γ-ray spectrum for energy below 7 MeV is calculated by MCNP5 code; secondly, the electron recoil spectrum in a BC501A liquid scintillator detector is simulated based on EGSnrc Monte Carlo Code with the γ-ray spectrum from the first step as input. The comparison of calculated results with experimental ones shows that the simulations agree well with experiment in the energy region 0.4-3 MeV for the prompt γ-ray spectrum and below 4 MeVee for the electron recoil spectrum. The reliability of the two-step method in this work is validated. Supported by the National Natural Science Foundation of China (91226104) and National Special Magnetic Confinement Fusion Energy Research, China (2015GB108001)
Investigations on Monte Carlo based coupled core calculations
The present trend in advanced and next generation nuclear reactor core designs is towards increased material heterogeneity and geometry complexity. The continuous energy Monte Carlo method has the capability of modeling such core environments with high accuracy. This paper presents results from feasibility studies being performed at the Pennsylvania State University (PSU) on both accelerating Monte Carlo criticality calculations by using hybrid nodal diffusion Monte Carlo schemes and thermal-hydraulic feedback modeling in Monte Carlo core calculations. The computation process is greatly accelerated by calculating the three-dimensional (3D) distributions of fission source and thermal-hydraulics parameters with the coupled NEM/COBRA-TF code and then using coupled MCNP5/COBRA-TF code to fine tune the results to obtain an increased accuracy. The PSU NEM code employs cross-sections generated by MCNP5 for pin-cell based nodal compositions. The implementation of different code modifications facilitating coupled calculations are presented first. Then the coupled hybrid Monte Carlo based code system is applied to a 3D 2*2 pin array extracted from a Boiling Water Reactor (BWR) assembly with reflective radial boundary conditions. The obtained results are discussed and it is showed that performing Monte-Carlo based coupled core steady state calculations are feasible. (authors)
Rundel, R. D.; Butler, D. M.; Stolarski, R. S.
1978-01-01
The paper discusses the development of a concise stratospheric model which uses iteration to obtain coupling between interacting species. The one-dimensional, steady-state, diurnally-averaged model generates diffusion equations with appropriate sources and sinks for species odd oxygen, H2O, H2, CO, N2O, odd nitrogen, CH4, CH3Cl, CCl4, CF2Cl2, CFCl3, and odd chlorine. The model evaluates steady-state perturbations caused by injections of chlorine and NO(x) and may be used to predict ozone depletion. The model is used in a Monte Carlo study of the propagation of reaction-rate imprecisions by calculating an ozone perturbation caused by the addition of chlorine. Since the model is sensitive to only 10 of the more than 50 reaction rates considered, only about 1000 Monte Carlo cases are required to span the space of possible results.
The double-heterogeneity characterising pebble-bed high temperature reactors (HTRs) makes Monte Carlo based calculation tools the most suitable for detailed core analyses. These codes can be successfully used to predict the isotopic evolution during irradiation of the fuel of this kind of cores. At the moment, there are many computational systems based on MCNP that are available for performing depletion calculation. All these systems use MCNP to supply problem dependent fluxes and/or microscopic cross sections to the depletion module. This latter then calculates the isotopic evolution of the fuel resolving Bateman's equations. In this paper, a comparative analysis of three different MCNP-based depletion codes is performed: Montburns2.0, MCNPX2.6.0 and BGCore. Monteburns code can be considered as the reference code for HTR calculations, since it has been already verified during HTR-N and HTR-N1 EU project. All calculations have been performed on a reference model representing an infinite lattice of thorium-plutonium fuelled pebbles. The evolution of k-inf as a function of burnup has been compared, as well as the inventory of the important actinides. The k-inf comparison among the codes shows a good agreement during the entire burnup history with the maximum difference lower than 1%. The actinide inventory prediction agrees well. However significant discrepancy in Am and Cm concentrations calculated by MCNPX as compared to those of Monteburns and BGCore has been observed. This is mainly due to different Am-241 (n,γ) branching ratio utilized by the codes. The important advantage of BGCore is its significantly lower execution time required to perform considered depletion calculations. While providing reasonably accurate results BGCore runs depletion problem about two times faster than Monteburns and two to five times faster than MCNPX.
Depleting methyl bromide residues in soil by reaction with bases
Despite generally being considered the most effective soil fumigant, methyl bromide (MeBr) use is being phased out because its emissions from soil can lead to stratospheric ozone depletion. However, a large amount is still currently used due to Critical Use Exemptions. As strategies for reducing the...
This paper summarizes studies performed on the Deep-Burner Modular Helium Reactor (DB-MHR) concept-design. Feasibility and sensitivity studies as well as fuel-cycle studies with probabilistic methodology are presented. Current investigations on design strategies in one and two pass scenarios, and the computational tools are also presented. Computations on the prismatic concept-design were performed on a full-core 3D model basis. The probabilistic MCNP-MONTEBURNS-ORIGEN chain, with either JEF2.2 or BVI libraries, was used. One or two independently depleting media per assembly were accounted. Due to the calculation time necessary to perform MCNP5 calculations with sufficient accuracy, the different parameters of the depletion calculations have to be optimized according to the desired accuracy of the results. Three strategies were compared: the two pass with driver and transmuter fuel loading in three rings, the one pass with driver fuel only in three rings geometry and finally the one pass in four rings. The 'two pass' scenario is the best deep burner with about 70% mass reduction of actinides for the PWR discharged fuel. However the small difference obtained for incineration (∼5%) raises the question of the interest of this scenario given the difficulty of the process for TF fuel. Finally the advantage of the 'two pass' scenario is mainly the reduction of actinide activity. (author)
Stenbæk, D S; Einarsdottir, H S; Goregliad-Fjaellingsdal, T;
2016-01-01
Acute Tryptophan Depletion (ATD) is a dietary method used to modulate central 5-HT to study the effects of temporarily reduced 5-HT synthesis. The aim of this study is to evaluate a novel method of ATD using a gelatin-based collagen peptide (CP) mixture. We administered CP-Trp or CP+Trp mixtures ...... effects of CP-Trp compared to CP+Trp were observed. The transient increase in plasma Trp after CP+Trp may impair comparison to the CP-Trp and we therefore recommend in future studies to use a smaller dose of Trp supplement to the CP mixture....
Satellite-based estimates of groundwater depletion in India
Rodell, M.; Velicogna, I; Famiglietti, JS
2009-01-01
Groundwater is a primary source of fresh water in many parts of the world. Some regions are becoming overly dependent on it, consuming groundwater faster than it is naturally replenished and causing water tables to decline unremittingly. Indirect evidence suggests that this is the case in northwest India, but there has been no regional assessment of the rate of groundwater depletion. Here we use terrestrial water storage-change observations from the NASA Gravity Recovery and Climate Experimen...
GPU based Monte Carlo for PET image reconstruction: detector modeling
Monte Carlo (MC) calculations and Graphical Processing Units (GPUs) are almost like the dedicated hardware designed for the specific task given the similarities between visible light transport and neutral particle trajectories. A GPU based MC gamma transport code has been developed for Positron Emission Tomography iterative image reconstruction calculating the projection from unknowns to data at each iteration step taking into account the full physics of the system. This paper describes the simplified scintillation detector modeling and its effect on convergence. (author)
Monte Carlo based weighting functions in neutron capture measurements
To determine neutron capture cross sections using C6D6 detectors, the Pulse Height Weighting Technique (PHWT) is mostly applied. The weighting function depends from the response function of the detection system in use. Therefore, the quality of the data depends on the detector response used for the calculation of the weighting function. An experimental determination of the response of C6D6 detectors is not always straightforward. We determined the detector response and, hence, the weighting function from Monte Carlo simulations, using the MCNP 4C2 code. To obtain reliable results a big effort was made in preparing geometry input file describing the experimental conditions. To validate the results of the Monte Carlo simulations we performed several experiments at GELINA. First, we measured the C6D6 detector response for standard -sources and for selected resonances in the 206Pb(n,). These responses were compared with the one based on Monte Carlo simulations. The good agreement between experimental and simulated data confirms the reliability of the Monte Carlo simulations. As a second validation exercise, we also determined the normalization factor in Ag and Au sample of different composition and thickness and the neutron width of the 1.15 keV resonance in 5 Fe using samples of different compositions. The result of this validation exercise was that the photon transport and the coupling of the photon and neutron transport must be accounted for in the determination of the weighting function. Accurate weighting functions are required for capture reactions in nuclei where the gamma cascade differs strongly from resonance to resonance, and are extremely important for neutron data related to reactor technologies where Pb-isotopes play an important role. The Monte Carlo based weighting function have been used to deduce the capture yield of 206Pb between 3 and 620 keV and of 232Th between 5 and 150 keV. This method will also be used for the analysis of other neutron capture
A practical fuel management system for the he Pennsylvania State University Breazeale Research Reactor (PSBR) based on the advanced Monte Carlo methodology was developed from the existing fuel management tool in this research. Several modeling improvements were implemented to the old system. The improved fuel management system can now utilize the burnup dependent cross section libraries generated specifically for PSBR fuel and it is also able to update the cross sections of these libraries by the Monte Carlo calculation automatically. Considerations were given to balance the computation time and the accuracy of the cross section update. Thus, certain types of a limited number of isotopes, which are considered 'important', are calculated and updated by the scheme. Moreover, the depletion algorithm of the existing fuel management tool was replaced from the predictor only to the predictor-corrector depletion scheme to account for burnup spectrum changes during the burnup step more accurately. An intermediate verification of the fuel management system was performed to assess the correctness of the newly implemented schemes against HELIOS. It was found that the agreement of both codes is good when the same energy released per fission (Q values) is used. Furthermore, to be able to model the reactor at various temperatures, the fuel management tool is able to utilize automatically the continuous cross sections generated at different temperatures. Other additional useful capabilities were also added to the fuel management tool to make it easy to use and be practical. As part of the development, a hybrid nodal diffusion/Monte Carlo calculation was devised to speed up the Monte Carlo calculation by providing more converged initial source distribution for the Monte Carlo calculation from the nodal diffusion calculation. Finally, the fuel management system was validated against the measured data using several actual PSBR core loadings. The agreement of the predicted core
Quantitative Monte Carlo-based holmium-166 SPECT reconstruction
Purpose: Quantitative imaging of the radionuclide distribution is of increasing interest for microsphere radioembolization (RE) of liver malignancies, to aid treatment planning and dosimetry. For this purpose, holmium-166 (166Ho) microspheres have been developed, which can be visualized with a gamma camera. The objective of this work is to develop and evaluate a new reconstruction method for quantitative 166Ho SPECT, including Monte Carlo-based modeling of photon contributions from the full energy spectrum.Methods: A fast Monte Carlo (MC) simulator was developed for simulation of 166Ho projection images and incorporated in a statistical reconstruction algorithm (SPECT-fMC). Photon scatter and attenuation for all photons sampled from the full 166Ho energy spectrum were modeled during reconstruction by Monte Carlo simulations. The energy- and distance-dependent collimator-detector response was modeled using precalculated convolution kernels. Phantom experiments were performed to quantitatively evaluate image contrast, image noise, count errors, and activity recovery coefficients (ARCs) of SPECT-fMC in comparison with those of an energy window-based method for correction of down-scattered high-energy photons (SPECT-DSW) and a previously presented hybrid method that combines MC simulation of photopeak scatter with energy window-based estimation of down-scattered high-energy contributions (SPECT-ppMC+DSW). Additionally, the impact of SPECT-fMC on whole-body recovered activities (Aest) and estimated radiation absorbed doses was evaluated using clinical SPECT data of six 166Ho RE patients.Results: At the same noise level, SPECT-fMC images showed substantially higher contrast than SPECT-DSW and SPECT-ppMC+DSW in spheres ≥17 mm in diameter. The count error was reduced from 29% (SPECT-DSW) and 25% (SPECT-ppMC+DSW) to 12% (SPECT-fMC). ARCs in five spherical volumes of 1.96–106.21 ml were improved from 32%–63% (SPECT-DSW) and 50%–80% (SPECT-ppMC+DSW) to 76%–103
Clinical dosimetry in photon radiotherapy. A Monte Carlo based investigation
Practical clinical dosimetry is a fundamental step within the radiation therapy process and aims at quantifying the absorbed radiation dose within a 1-2% uncertainty. To achieve this level of accuracy, corrections are needed for calibrated and air-filled ionization chambers, which are used for dose measurement. The procedures of correction are based on cavity theory of Spencer-Attix and are defined in current dosimetry protocols. Energy dependent corrections for deviations from calibration beams account for changed ionization chamber response in the treatment beam. The corrections applied are usually based on semi-analytical models or measurements and are generally hard to determine due to their magnitude of only a few percents or even less. Furthermore the corrections are defined for fixed geometrical reference-conditions and do not apply to non-reference conditions in modern radiotherapy applications. The stochastic Monte Carlo method for the simulation of radiation transport is becoming a valuable tool in the field of Medical Physics. As a suitable tool for calculation of these corrections with high accuracy the simulations enable the investigation of ionization chambers under various conditions. The aim of this work is the consistent investigation of ionization chamber dosimetry in photon radiation therapy with the use of Monte Carlo methods. Nowadays Monte Carlo systems exist, which enable the accurate calculation of ionization chamber response in principle. Still, their bare use for studies of this type is limited due to the long calculation times needed for a meaningful result with a small statistical uncertainty, inherent to every result of a Monte Carlo simulation. Besides heavy use of computer hardware, techniques methods of variance reduction to reduce the needed calculation time can be applied. Methods for increasing the efficiency in the results of simulation were developed and incorporated in a modern and established Monte Carlo simulation environment
Too exhausted to remember: ego depletion undermines subsequent event-based prospective memory.
Li, Jian-Bin; Nie, Yan-Gang; Zeng, Min-Xia; Huntoon, Meghan; Smith, Jessi L
2013-01-01
Past research has consistently found that people are likely to do worse on high-level cognitive tasks after exerting self-control on previous actions. However, little has been unraveled about to what extent ego depletion affects subsequent prospective memory. Drawing upon the self-control strength model and the relationship between self-control resources and executive control, this study proposes that the initial actions of self-control may undermine subsequent event-based prospective memory (EBPM). Ego depletion was manipulated through watching a video requiring visual attention (Experiment 1) or completing an incongruent Stroop task (Experiment 2). Participants were then tested on EBPM embedded in an ongoing task. As predicted, the results showed that after ruling out possible intervening variables (e.g. mood, focal and nonfocal cues, and characteristics of ongoing task and ego depletion task), participants in the high-depletion condition performed significantly worse on EBPM than those in the low-depletion condition. The results suggested that the effect of ego depletion on EBPM was mainly due to an impaired prospective component rather than to a retrospective component. PMID:23432682
Quantitative Monte Carlo-based holmium-166 SPECT reconstruction
Elschot, Mattijs; Smits, Maarten L. J.; Nijsen, Johannes F. W.; Lam, Marnix G. E. H.; Zonnenberg, Bernard A.; Bosch, Maurice A. A. J. van den; Jong, Hugo W. A. M. de [Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht (Netherlands); Viergever, Max A. [Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht (Netherlands)
2013-11-15
Purpose: Quantitative imaging of the radionuclide distribution is of increasing interest for microsphere radioembolization (RE) of liver malignancies, to aid treatment planning and dosimetry. For this purpose, holmium-166 ({sup 166}Ho) microspheres have been developed, which can be visualized with a gamma camera. The objective of this work is to develop and evaluate a new reconstruction method for quantitative {sup 166}Ho SPECT, including Monte Carlo-based modeling of photon contributions from the full energy spectrum.Methods: A fast Monte Carlo (MC) simulator was developed for simulation of {sup 166}Ho projection images and incorporated in a statistical reconstruction algorithm (SPECT-fMC). Photon scatter and attenuation for all photons sampled from the full {sup 166}Ho energy spectrum were modeled during reconstruction by Monte Carlo simulations. The energy- and distance-dependent collimator-detector response was modeled using precalculated convolution kernels. Phantom experiments were performed to quantitatively evaluate image contrast, image noise, count errors, and activity recovery coefficients (ARCs) of SPECT-fMC in comparison with those of an energy window-based method for correction of down-scattered high-energy photons (SPECT-DSW) and a previously presented hybrid method that combines MC simulation of photopeak scatter with energy window-based estimation of down-scattered high-energy contributions (SPECT-ppMC+DSW). Additionally, the impact of SPECT-fMC on whole-body recovered activities (A{sup est}) and estimated radiation absorbed doses was evaluated using clinical SPECT data of six {sup 166}Ho RE patients.Results: At the same noise level, SPECT-fMC images showed substantially higher contrast than SPECT-DSW and SPECT-ppMC+DSW in spheres ≥17 mm in diameter. The count error was reduced from 29% (SPECT-DSW) and 25% (SPECT-ppMC+DSW) to 12% (SPECT-fMC). ARCs in five spherical volumes of 1.96–106.21 ml were improved from 32%–63% (SPECT-DSW) and 50%–80
GPU-Monte Carlo based fast IMRT plan optimization
Yongbao Li
2014-03-01
Full Text Available Purpose: Intensity-modulated radiation treatment (IMRT plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow.Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, a rough dose calculation is conducted with only a few number of particle per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final result.Results: For a lung case with 5317 beamlets, 105 particles per beamlet in the first round, and 108 particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec.Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.--------------------------------Cite this article as: Li Y, Tian Z
A CNS calculation line based on a Monte Carlo method
Full text: The design of the moderator cell of a Cold Neutron Source (CNS) involves many different considerations regarding geometry, location, and materials. Decisions taken in this sense affect not only the neutron flux in the source neighborhood, which can be evaluated by a standard empirical method, but also the neutron flux values in experimental positions far away of the neutron source. At long distances from the neutron source, very time consuming 3D deterministic methods or Monte Carlo transport methods are necessary in order to get accurate figures. Standard and typical terminology such as average neutron flux, neutron current, angular flux, luminosity, are magnitudes very difficult to evaluate in positions located several meters away from the neutron source. The Monte Carlo method is a unique and powerful tool to transport neutrons. Its use in a bootstrap scheme appears to be an appropriate solution for this type of systems. The proper use of MCNP as the main tool leads to a fast and reliable method to perform calculations in a relatively short time with low statistical errors. The design goal is to evaluate the performance of the neutron sources, their beam tubes and neutron guides at specific experimental locations in the reactor hall as well as in the neutron or experimental hall. In this work, the calculation methodology used to design Cold, Thermal and Hot Neutron Sources and their associated Neutron Beam Transport Systems, based on the use of the MCNP code, is presented. This work also presents some changes made to the cross section libraries in order to cope with cryogenic moderators such as liquid hydrogen and liquid deuterium. (author)
The New MCNP6 Depletion Capability
Fensin, Michael Lorne [Los Alamos National Laboratory; James, Michael R. [Los Alamos National Laboratory; Hendricks, John S. [Los Alamos National Laboratory; Goorley, John T. [Los Alamos National Laboratory
2012-06-19
The first MCNP based inline Monte Carlo depletion capability was officially released from the Radiation Safety Information and Computational Center as MCNPX 2.6.0. Both the MCNP5 and MCNPX codes have historically provided a successful combinatorial geometry based, continuous energy, Monte Carlo radiation transport solution for advanced reactor modeling and simulation. However, due to separate development pathways, useful simulation capabilities were dispersed between both codes and not unified in a single technology. MCNP6, the next evolution in the MCNP suite of codes, now combines the capability of both simulation tools, as well as providing new advanced technology, in a single radiation transport code. We describe here the new capabilities of the MCNP6 depletion code dating from the official RSICC release MCNPX 2.6.0, reported previously, to the now current state of MCNP6. NEA/OECD benchmark results are also reported. The MCNP6 depletion capability enhancements beyond MCNPX 2.6.0 reported here include: (1) new performance enhancing parallel architecture that implements both shared and distributed memory constructs; (2) enhanced memory management that maximizes calculation fidelity; and (3) improved burnup physics for better nuclide prediction. MCNP6 depletion enables complete, relatively easy-to-use depletion calculations in a single Monte Carlo code. The enhancements described here help provide a powerful capability as well as dictate a path forward for future development to improve the usefulness of the technology.
GPU based Monte Carlo for PET image reconstruction: parameter optimization
This paper presents the optimization of a fully Monte Carlo (MC) based iterative image reconstruction of Positron Emission Tomography (PET) measurements. With our MC re- construction method all the physical effects in a PET system are taken into account thus superior image quality is achieved in exchange for increased computational effort. The method is feasible because we utilize the enormous processing power of Graphical Processing Units (GPUs) to solve the inherently parallel problem of photon transport. The MC approach regards the simulated positron decays as samples in mathematical sums required in the iterative reconstruction algorithm, so to complement the fast architecture, our work of optimization focuses on the number of simulated positron decays required to obtain sufficient image quality. We have achieved significant results in determining the optimal number of samples for arbitrary measurement data, this allows to achieve the best image quality with the least possible computational effort. Based on this research recommendations can be given for effective partitioning of computational effort into the iterations in limited time reconstructions. (author)
A spreading resistance based method of mapping the resistivity and potential of a depleted diode
The characterization of the depletion states of reverse operated p-n junctions is an important task within the scope of high energy physics detector development. The configuration of the sensitive volume inside these structures determines the particle detection process. Therefore a spreading resistance profiling based method has been developed to map the local resistivity and potential along the prepared edge of a depleted diode. This ''edge-SRP' method is capable of detecting the boarder of the space charge region and its transition to the electrical neutral bulk. In order to characterize the depleted space charge region, the surface potential along the edge could be measured by slightly modifying the setup. These surface potential results complement the spreading resistance one. In this paper the functionality of the developed method is verified by performing measurements on a prepared diode, which has been biased with different voltages
EXPERIMENTAL ACIDIFICATION CAUSES SOIL BASE-CATION DEPLETION AT THE BEAR BROOK WATERSHED IN MAINE
There is concern that changes in atmospheric deposition, climate, or land use have altered the biogeochemistry of forests causing soil base-cation depletion, particularly Ca. The Bear Brook Watershed in Maine (BBWM) is a paired watershed experiment with one watershed subjected to...
Application of equivalence methods on Monte Carlo method based homogenization multi-group constants
The multi-group constants generated via continuous energy Monte Carlo method do not satisfy the equivalence between reference calculation and diffusion calculation applied in reactor core analysis. To the satisfaction of the equivalence theory, general equivalence theory (GET) and super homogenization method (SPH) were applied to the Monte Carlo method based group constants, and a simplified reactor core and C5G7 benchmark were examined with the Monte Carlo constants. The results show that the calculating precision of group constants is improved, and GET and SPH are good candidates for the equivalence treatment of Monte Carlo homogenization. (authors)
Dieudonne, Cyril; Dumonteil, Eric; Malvagi, Fausto; M'Backé Diop, Cheikh
2014-06-01
For several years, Monte Carlo burnup/depletion codes have appeared, which couple Monte Carlo codes to simulate the neutron transport to deterministic methods, which handle the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3-dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the Monte Carlo solver called at each time step. In this paper we present a methodology to avoid the repetitive and time-expensive Monte Carlo simulations, and to replace them by perturbation calculations: indeed the different burnup steps may be seen as perturbations of the isotopic concentration of an initial Monte Carlo simulation. In a first time we will present this method, and provide details on the perturbative technique used, namely the correlated sampling. In a second time the implementation of this method in the TRIPOLI-4® code will be discussed, as well as the precise calculation scheme a meme to bring important speed-up of the depletion calculation. Finally, this technique will be used to calculate the depletion of a REP-like assembly, studied at beginning of its cycle. After having validated the method with a reference calculation we will show that it can speed-up by nearly an order of magnitude standard Monte-Carlo depletion codes.
Refined Stratified Sampling for efficient Monte Carlo based uncertainty quantification
A general adaptive approach rooted in stratified sampling (SS) is proposed for sample-based uncertainty quantification (UQ). To motivate its use in this context the space-filling, orthogonality, and projective properties of SS are compared with simple random sampling and Latin hypercube sampling (LHS). SS is demonstrated to provide attractive properties for certain classes of problems. The proposed approach, Refined Stratified Sampling (RSS), capitalizes on these properties through an adaptive process that adds samples sequentially by dividing the existing subspaces of a stratified design. RSS is proven to reduce variance compared to traditional stratified sample extension methods while providing comparable or enhanced variance reduction when compared to sample size extension methods for LHS – which do not afford the same degree of flexibility to facilitate a truly adaptive UQ process. An initial investigation of optimal stratification is presented and motivates the potential for major advances in variance reduction through optimally designed RSS. Potential paths for extension of the method to high dimension are discussed. Two examples are provided. The first involves UQ for a low dimensional function where convergence is evaluated analytically. The second presents a study to asses the response variability of a floating structure to an underwater shock. - Highlights: • An adaptive process, rooted in stratified sampling, is proposed for Monte Carlo-based uncertainty quantification. • Space-filling, orthogonality, and projective properties of stratified sampling are investigated • Stratified sampling is shown to possess attractive properties for certain classes of problems. • Refined Stratified Sampling, a new sampling method is proposed that enables the adaptive UQ process. • Optimality of RSS stratum division is explored
Monte Carlo-based simulation of dynamic jaws tomotherapy
Purpose: Original TomoTherapy systems may involve a trade-off between conformity and treatment speed, the user being limited to three slice widths (1.0, 2.5, and 5.0 cm). This could be overcome by allowing the jaws to define arbitrary fields, including very small slice widths (<1 cm), which are challenging for a beam model. The aim of this work was to incorporate the dynamic jaws feature into a Monte Carlo (MC) model called TomoPen, based on the MC code PENELOPE, previously validated for the original TomoTherapy system. Methods: To keep the general structure of TomoPen and its efficiency, the simulation strategy introduces several techniques: (1) weight modifiers to account for any jaw settings using only the 5 cm phase-space file; (2) a simplified MC based model called FastStatic to compute the modifiers faster than pure MC; (3) actual simulation of dynamic jaws. Weight modifiers computed with both FastStatic and pure MC were compared. Dynamic jaws simulations were compared with the convolution/superposition (C/S) of TomoTherapy in the ''cheese'' phantom for a plan with two targets longitudinally separated by a gap of 3 cm. Optimization was performed in two modes: asymmetric jaws-constant couch speed (''running start stop,'' RSS) and symmetric jaws-variable couch speed (''symmetric running start stop,'' SRSS). Measurements with EDR2 films were also performed for RSS for the formal validation of TomoPen with dynamic jaws. Results: Weight modifiers computed with FastStatic were equivalent to pure MC within statistical uncertainties (0.5% for three standard deviations). Excellent agreement was achieved between TomoPen and C/S for both asymmetric jaw opening/constant couch speed and symmetric jaw opening/variable couch speed, with deviations well within 2%/2 mm. For RSS procedure, agreement between C/S and measurements was within 2%/2 mm for 95% of the points and 3%/3 mm for 98% of the points, where dose is greater than 30% of the prescription dose (gamma analysis
MCHITS: Monte Carlo based Method for Hyperlink Induced Topic Search on Networks
Zhaoyan Jin
2013-10-01
Full Text Available Hyperlink Induced Topic Search (HITS is the most authoritative and most widely used personalized ranking algorithm on networks. The HITS algorithm ranks nodes on networks according to power iteration, and has high complexity of computation. This paper models the HITS algorithm with the Monte Carlo method, and proposes Monte Carlo based algorithms for the HITS computation. Theoretical analysis and experiments show that the Monte Carlo based approximate computing of the HITS ranking reduces computing resources a lot while keeping higher accuracy, and is significantly better than related works
An empirical formula based on Monte Carlo simulation for diffuse reflectance from turbid media
Gnanatheepam, Einstein; Aruna, Prakasa Rao; Ganesan, Singaravelu
2016-03-01
Diffuse reflectance spectroscopy has been widely used in diagnostic oncology and characterization of laser irradiated tissue. However, still accurate and simple analytical equation does not exist for estimation of diffuse reflectance from turbid media. In this work, a diffuse reflectance lookup table for a range of tissue optical properties was generated using Monte Carlo simulation. Based on the generated Monte Carlo lookup table, an empirical formula for diffuse reflectance was developed using surface fitting method. The variance between the Monte Carlo lookup table surface and the surface obtained from the proposed empirical formula is less than 1%. The proposed empirical formula may be used for modeling of diffuse reflectance from tissue.
CAD-based Monte Carlo program for integrated simulation of nuclear system SuperMC
Highlights: • The new developed CAD-based Monte Carlo program named SuperMC for integrated simulation of nuclear system makes use of hybrid MC-deterministic method and advanced computer technologies. SuperMC is designed to perform transport calculation of various types of particles, depletion and activation calculation including isotope burn-up, material activation and shutdown dose, and multi-physics coupling calculation including thermo-hydraulics, fuel performance and structural mechanics. The bi-directional automatic conversion between general CAD models and physical settings and calculation models can be well performed. Results and process of simulation can be visualized with dynamical 3D dataset and geometry model. Continuous-energy cross section, burnup, activation, irradiation damage and material data etc. are used to support the multi-process simulation. Advanced cloud computing framework makes the computation and storage extremely intensive simulation more attractive just as a network service to support design optimization and assessment. The modular design and generic interface promotes its flexible manipulation and coupling of external solvers. • The new developed and incorporated advanced methods in SuperMC was introduced including hybrid MC-deterministic transport method, particle physical interaction treatment method, multi-physics coupling calculation method, geometry automatic modeling and processing method, intelligent data analysis and visualization method, elastic cloud computing technology and parallel calculation method. • The functions of SuperMC2.1 integrating automatic modeling, neutron and photon transport calculation, results and process visualization was introduced. It has been validated by using a series of benchmarking cases such as the fusion reactor ITER model and the fast reactor BN-600 model. - Abstract: Monte Carlo (MC) method has distinct advantages to simulate complicated nuclear systems and is envisioned as a routine
Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence
Monte Carlo analysis has become nearly ubiquitous since its introduction, now over 65 years ago. It is an important tool in many assessments of the reliability and robustness of systems, structures or solutions. As the deterministic core simulation can be lengthy, the computational costs of Monte Carlo can be a limiting factor. To reduce that computational expense as much as possible, sampling efficiency and convergence for Monte Carlo are investigated in this paper. The first section shows that non-collapsing space-filling sampling strategies, illustrated here with the maximin and uniform Latin hypercube designs, highly enhance the sampling efficiency, and render a desired level of accuracy of the outcomes attainable with far lesser runs. In the second section it is demonstrated that standard sampling statistics are inapplicable for Latin hypercube strategies. A sample-splitting approach is put forward, which in combination with a replicated Latin hypercube sampling allows assessing the accuracy of Monte Carlo outcomes. The assessment in turn permits halting the Monte Carlo simulation when the desired levels of accuracy are reached. Both measures form fairly noncomplex upgrades of the current state-of-the-art in Monte-Carlo based uncertainty analysis but give a substantial further progress with respect to its applicability.
Implementation of a Monte Carlo based inverse planning model for clinical IMRT with MCNP code
He, Tongming Tony
In IMRT inverse planning, inaccurate dose calculations and limitations in optimization algorithms introduce both systematic and convergence errors to treatment plans. The goal of this work is to practically implement a Monte Carlo based inverse planning model for clinical IMRT. The intention is to minimize both types of error in inverse planning and obtain treatment plans with better clinical accuracy than non-Monte Carlo based systems. The strategy is to calculate the dose matrices of small beamlets by using a Monte Carlo based method. Optimization of beamlet intensities is followed based on the calculated dose data using an optimization algorithm that is capable of escape from local minima and prevents possible pre-mature convergence. The MCNP 4B Monte Carlo code is improved to perform fast particle transport and dose tallying in lattice cells by adopting a selective transport and tallying algorithm. Efficient dose matrix calculation for small beamlets is made possible by adopting a scheme that allows concurrent calculation of multiple beamlets of single port. A finite-sized point source (FSPS) beam model is introduced for easy and accurate beam modeling. A DVH based objective function and a parallel platform based algorithm are developed for the optimization of intensities. The calculation accuracy of improved MCNP code and FSPS beam model is validated by dose measurements in phantoms. Agreements better than 1.5% or 0.2 cm have been achieved. Applications of the implemented model to clinical cases of brain, head/neck, lung, spine, pancreas and prostate have demonstrated the feasibility and capability of Monte Carlo based inverse planning for clinical IMRT. Dose distributions of selected treatment plans from a commercial non-Monte Carlo based system are evaluated in comparison with Monte Carlo based calculations. Systematic errors of up to 12% in tumor doses and up to 17% in critical structure doses have been observed. The clinical importance of Monte Carlo based
Reactor physics analysis method based on Monte Carlo homogenization
Background: Many new concepts of nuclear energy systems with complicated geometric structures and diverse energy spectra have been put forward to meet the future demand of nuclear energy market. The traditional deterministic neutronics analysis method has been challenged in two aspects: one is the ability of generic geometry processing; the other is the multi-spectrum applicability of the multi-group cross section libraries. The Monte Carlo (MC) method predominates the suitability of geometry and spectrum, but faces the problems of long computation time and slow convergence. Purpose: This work aims to find a novel scheme to take the advantages of both methods drawn from the deterministic core analysis method and MC method. Methods: A new two-step core analysis scheme is proposed to combine the geometry modeling capability and continuous energy cross section libraries of MC method, as well as the higher computational efficiency of deterministic method. First of all, the MC simulations are performed for assembly, and the assembly homogenized multi-group cross sections are tallied at the same time. Then, the core diffusion calculations can be done with these multi-group cross sections. Results: The new scheme can achieve high efficiency while maintain acceptable precision. Conclusion: The new scheme can be used as an effective tool for the design and analysis of innovative nuclear energy systems, which has been verified by numeric tests. (authors)
Application of Photon Transport Monte Carlo Module with GPU-based Parallel System
Park, Chang Je [Sejong University, Seoul (Korea, Republic of); Shon, Heejeong [Golden Eng. Co. LTD, Seoul (Korea, Republic of); Lee, Donghak [CoCo Link Inc., Seoul (Korea, Republic of)
2015-05-15
In general, it takes lots of computing time to get reliable results in Monte Carlo simulations especially in deep penetration problems with a thick shielding medium. To mitigate such a weakness of Monte Carlo methods, lots of variance reduction algorithms are proposed including geometry splitting and Russian roulette, weight windows, exponential transform, and forced collision, etc. Simultaneously, advanced computing hardware systems such as GPU(Graphics Processing Units)-based parallel machines are used to get a better performance of the Monte Carlo simulation. The GPU is much easier to access and to manage when comparing a CPU cluster system. It also becomes less expensive these days due to enhanced computer technology. There, lots of engineering areas adapt GPU-bases massive parallel computation technique. based photon transport Monte Carlo method. It provides almost 30 times speedup without any optimization and it is expected almost 200 times with fully supported GPU system. It is expected that GPU system with advanced parallelization algorithm will contribute successfully for development of the Monte Carlo module which requires quick and accurate simulations.
Application of Photon Transport Monte Carlo Module with GPU-based Parallel System
In general, it takes lots of computing time to get reliable results in Monte Carlo simulations especially in deep penetration problems with a thick shielding medium. To mitigate such a weakness of Monte Carlo methods, lots of variance reduction algorithms are proposed including geometry splitting and Russian roulette, weight windows, exponential transform, and forced collision, etc. Simultaneously, advanced computing hardware systems such as GPU(Graphics Processing Units)-based parallel machines are used to get a better performance of the Monte Carlo simulation. The GPU is much easier to access and to manage when comparing a CPU cluster system. It also becomes less expensive these days due to enhanced computer technology. There, lots of engineering areas adapt GPU-bases massive parallel computation technique. based photon transport Monte Carlo method. It provides almost 30 times speedup without any optimization and it is expected almost 200 times with fully supported GPU system. It is expected that GPU system with advanced parallelization algorithm will contribute successfully for development of the Monte Carlo module which requires quick and accurate simulations
Coupled neutronic thermo-hydraulic analysis of full PWR core with Monte-Carlo based BGCore system
Highlights: → New thermal-hydraulic (TH) feedback module was integrated into the MCNP based depletion system BGCore. → A coupled neutronic-TH analysis of a full PWR core was performed with the upgraded BGCore system. → The BGCore results were verified against those of 3D nodal diffusion code DYN3D. → Very good agreement in major core operational parameters between the BGCore and DYN3D results was observed. - Abstract: BGCore reactor analysis system was recently developed at Ben-Gurion University for calculating in-core fuel composition and spent fuel emissions following discharge. It couples the Monte Carlo transport code MCNP with an independently developed burnup and decay module SARAF. Most of the existing MCNP based depletion codes (e.g. MOCUP, Monteburns, MCODE) tally directly the one-group fluxes and reaction rates in order to prepare one-group cross sections necessary for the fuel depletion analysis. BGCore, on the other hand, uses a multi-group (MG) approach for generation of one group cross-sections. This coupling approach significantly reduces the code execution time without compromising the accuracy of the results. Substantial reduction in the BGCore code execution time allows consideration of problems with much higher degree of complexity, such as introduction of thermal hydraulic (TH) feedback into the calculation scheme. Recently, a simplified TH feedback module, THERMO, was developed and integrated into the BGCore system. To demonstrate the capabilities of the upgraded BGCore system, a coupled neutronic TH analysis of a full PWR core was performed. The BGCore results were compared with those of the state of the art 3D deterministic nodal diffusion code DYN3D. Very good agreement in major core operational parameters including k-eff eigenvalue, axial and radial power profiles, and temperature distributions between the BGCore and DYN3D results was observed. This agreement confirms the consistency of the implementation of the TH feedback module
Acceptance and implementation of a system of planning computerized based on Monte Carlo
It has been done the acceptance for use clinical Monaco computerized planning system, based on an on a virtual model of the energy yield of the head of the linear electron Accelerator and that performs the calculation of the dose with an algorithm of x-rays (XVMC) based on Monte Carlo algorithm. (Author)
A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography
Zhun Xu; Xiaolei Song; Xiaomeng Zhang; Jing Bai
2007-01-01
We present an approach based on the improved Levenberg Marquardt (LM) algorithm of backpropagation (BP) neural network to estimate the light source position in bioluminescent imaging. For solving the forward problem, the table-based random sampling algorithm (TBRS), a fast Monte Carlo simulation method ...
Ondis, L.A., II; Tyburski, L.J.; Moskowitz, B.S.
2000-03-01
The RCP01 Monte Carlo program is used to analyze many geometries of interest in nuclear design and analysis of light water moderated reactors such as the core in its pressure vessel with complex piping arrangement, fuel storage arrays, shipping and container arrangements, and neutron detector configurations. Written in FORTRAN and in use on a variety of computers, it is capable of estimating steady state neutron or photon reaction rates and neutron multiplication factors. The energy range covered in neutron calculations is that relevant to the fission process and subsequent slowing-down and thermalization, i.e., 20 MeV to 0 eV. The same energy range is covered for photon calculations.
The RCP01 Monte Carlo program is used to analyze many geometries of interest in nuclear design and analysis of light water moderated reactors such as the core in its pressure vessel with complex piping arrangement, fuel storage arrays, shipping and container arrangements, and neutron detector configurations. Written in FORTRAN and in use on a variety of computers, it is capable of estimating steady state neutron or photon reaction rates and neutron multiplication factors. The energy range covered in neutron calculations is that relevant to the fission process and subsequent slowing-down and thermalization, i.e., 20 MeV to 0 eV. The same energy range is covered for photon calculations
Lopez-Tarjuelo, J.; Garcia-Molla, R.; Suan-Senabre, X. J.; Quiros-Higueras, J. Q.; Santos-Serra, A.; Marco-Blancas, N.; Calzada-Feliu, S.
2013-07-01
It has been done the acceptance for use clinical Monaco computerized planning system, based on an on a virtual model of the energy yield of the head of the linear electron Accelerator and that performs the calculation of the dose with an algorithm of x-rays (XVMC) based on Monte Carlo algorithm. (Author)
Makovicka, L.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J. [Universite de Franche-Comte, Equipe IRMA/ENISYS/FEMTO-ST, UMR6174 CNRS, 25 - Montbeliard (France); Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Salomon, M. [Universite de Franche-Comte, Equipe AND/LIFC, 90 - Belfort (France)
2009-01-15
Monte Carlo codes, precise but slow, are very important tools in the vast majority of specialities connected to Radiation Physics, Radiation Protection and Dosimetry. A discussion about some other computing solutions is carried out; solutions not only based on the enhancement of computer power, or on the 'biasing'used for relative acceleration of these codes (in the case of photons), but on more efficient methods (A.N.N. - artificial neural network, C.B.R. - case-based reasoning - or other computer science techniques) already and successfully used for a long time in other scientific or industrial applications and not only Radiation Protection or Medical Dosimetry. (authors)
Response matrix Monte Carlo based on a general geometry local calculation for electron transport
A Response Matrix Monte Carlo (RMMC) method has been developed for solving electron transport problems. This method was born of the need to have a reliable, computationally efficient transport method for low energy electrons (below a few hundred keV) in all materials. Today, condensed history methods are used which reduce the computation time by modeling the combined effect of many collisions but fail at low energy because of the assumptions required to characterize the electron scattering. Analog Monte Carlo simulations are prohibitively expensive since electrons undergo coulombic scattering with little state change after a collision. The RMMC method attempts to combine the accuracy of an analog Monte Carlo simulation with the speed of the condensed history methods. Like condensed history, the RMMC method uses probability distributions functions (PDFs) to describe the energy and direction of the electron after several collisions. However, unlike the condensed history method the PDFs are based on an analog Monte Carlo simulation over a small region. Condensed history theories require assumptions about the electron scattering to derive the PDFs for direction and energy. Thus the RMMC method samples from PDFs which more accurately represent the electron random walk. Results show good agreement between the RMMC method and analog Monte Carlo. 13 refs., 8 figs
Convex-based void filling method for CAD-based Monte Carlo geometry modeling
Highlights: • We present a new void filling method named CVF for CAD based MC geometry modeling. • We describe convex based void description based and quality-based space subdivision. • The results showed improvements provided by CVF for both modeling and MC calculation efficiency. - Abstract: CAD based automatic geometry modeling tools have been widely applied to generate Monte Carlo (MC) calculation geometry for complex systems according to CAD models. Automatic void filling is one of the main functions in the CAD based MC geometry modeling tools, because the void space between parts in CAD models is traditionally not modeled while MC codes such as MCNP need all the problem space to be described. A dedicated void filling method, named Convex-based Void Filling (CVF), is proposed in this study for efficient void filling and concise void descriptions. The method subdivides all the problem space into disjointed regions using Quality based Subdivision (QS) and describes the void space in each region with complementary descriptions of the convex volumes intersecting with that region. It has been implemented in SuperMC/MCAM, the Multiple-Physics Coupling Analysis Modeling Program, and tested on International Thermonuclear Experimental Reactor (ITER) Alite model. The results showed that the new method reduced both automatic modeling time and MC calculation time
Yu Hyeong; Kim Byungwook; Kim Hyunsoo; Min Hophil; Yu Jiyoung; Kim Kyunggon; Kim Youngsoo
2010-01-01
Abstract Background The removal of high-abundance proteins from plasma is an efficient approach to investigating flow-through proteins for biomarker discovery studies. Most depletion methods are based on multiple immunoaffinity methods available commercially including LC columns and spin columns. Despite its usefulness, high-abundance depletion has an intrinsic problem, the sponge effect, which should be assessed during depletion experiments. Concurrently, the yield of depletion of high-abund...
Monte-Carlo based prediction of radiochromic film response for hadrontherapy dosimetry
A model has been developed to calculate MD-55-V2 radiochromic film response to ion irradiation. This model is based on photon film response and film saturation by high local energy deposition computed by Monte-Carlo simulation. We have studied the response of the film to photon irradiation and we proposed a calculation method for hadron beams.
A lattice-based Monte Carlo evaluation of Canada Deuterium Uranium-6 safety parameters
Kim, Yong Hee; Hartanto, Donny; Kim, Woo Song [Dept. of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon (Korea, Republic of)
2016-06-15
Important safety parameters such as the fuel temperature coefficient (FTC) and the power coefficient of reactivity (PCR) of the CANada Deuterium Uranium (CANDU-6) reactor have been evaluated using the Monte Carlo method. For accurate analysis of the parameters, the Doppler broadening rejection correction scheme was implemented in the MCNPX code to account for the thermal motion of the heavy uranium-238 nucleus in the neutron-U scattering reactions. In this work, a standard fuel lattice has been modeled and the fuel is depleted using MCNPX. The FTC value is evaluated for several burnup points including the mid-burnup representing a near-equilibrium core. The Doppler effect has been evaluated using several cross-section libraries such as ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1.1, and JENDL-4.0. The PCR value is also evaluated at mid-burnup conditions to characterize the safety features of an equilibrium CANDU-6 reactor. To improve the reliability of the Monte Carlo calculations, we considered a huge number of neutron histories in this work and the standard deviation of the k-infinity values is only 0.5-1 pcm.
MOx benchmark calculations by deterministic and Monte Carlo codes
Highlights: ► MOx based depletion calculation. ► Methodology to create continuous energy pseudo cross section for lump of minor fission products. ► Mass inventory comparison between deterministic and Monte Carlo codes. ► Higher deviation was found for several isotopes. - Abstract: A depletion calculation benchmark devoted to MOx fuel is an ongoing objective of the OECD/NEA WPRS following the study of depletion calculation concerning UOx fuels. The objective of the proposed benchmark is to compare existing depletion calculations obtained with various codes and data libraries applied to fuel and back-end cycle configurations. In the present work the deterministic code NEWT/ORIGEN-S of the SCALE6 codes package and the Monte Carlo based code MONTEBURNS2.0 were used to calculate the masses of inventory isotopes. The methodology to apply the MONTEBURNS2.0 to this benchmark is also presented. Then the results from both code were compared.
Valence-dependent influence of serotonin depletion on model-based choice strategy.
Worbe, Y; Palminteri, S; Savulich, G; Daw, N D; Fernandez-Egea, E; Robbins, T W; Voon, V
2016-05-01
Human decision-making arises from both reflective and reflexive mechanisms, which underpin goal-directed and habitual behavioural control. Computationally, these two systems of behavioural control have been described by different learning algorithms, model-based and model-free learning, respectively. Here, we investigated the effect of diminished serotonin (5-hydroxytryptamine) neurotransmission using dietary tryptophan depletion (TD) in healthy volunteers on the performance of a two-stage decision-making task, which allows discrimination between model-free and model-based behavioural strategies. A novel version of the task was used, which not only examined choice balance for monetary reward but also for punishment (monetary loss). TD impaired goal-directed (model-based) behaviour in the reward condition, but promoted it under punishment. This effect on appetitive and aversive goal-directed behaviour is likely mediated by alteration of the average reward representation produced by TD, which is consistent with previous studies. Overall, the major implication of this study is that serotonin differentially affects goal-directed learning as a function of affective valence. These findings are relevant for a further understanding of psychiatric disorders associated with breakdown of goal-directed behavioural control such as obsessive-compulsive disorders or addictions. PMID:25869808
Development of the point-depletion code DEPTH
Highlights: ► The DEPTH code has been developed for the large-scale depletion system. ► DEPTH uses the data library which is convenient to couple with MC codes. ► TTA and matrix exponential methods are implemented and compared. ► DEPTH is able to calculate integral quantities based on the matrix inverse. ► Code-to-code comparisons prove the accuracy and efficiency of DEPTH. -- Abstract: The burnup analysis is an important aspect in reactor physics, which is generally done by coupling of transport calculations and point-depletion calculations. DEPTH is a newly-developed point-depletion code of handling large burnup depletion systems and detailed depletion chains. For better coupling with Monte Carlo transport codes, DEPTH uses data libraries based on the combination of ORIGEN-2 and ORIGEN-S and allows users to assign problem-dependent libraries for each depletion step. DEPTH implements various algorithms of treating the stiff depletion systems, including the Transmutation trajectory analysis (TTA), the Chebyshev Rational Approximation Method (CRAM), the Quadrature-based Rational Approximation Method (QRAM) and the Laguerre Polynomial Approximation Method (LPAM). Three different modes are supported by DEPTH to execute the decay, constant flux and constant power calculations. In addition to obtaining the instantaneous quantities of the radioactivity, decay heats and reaction rates, DEPTH is able to calculate the integral quantities by a time-integrated solver. Through calculations compared with ORIGEN-2, the validity of DEPTH in point-depletion calculations is proved. The accuracy and efficiency of depletion algorithms are also discussed. In addition, an actual pin-cell burnup case is calculated to illustrate the DEPTH code performance in coupling with the RMC Monte Carlo code
Development of Monte Carlo-based pebble bed reactor fuel management code
Highlights: • A new Monte Carlo-based fuel management code for OTTO cycle pebble bed reactor was developed. • The double-heterogeneity was modeled using statistical method in MVP-BURN code. • The code can perform analysis of equilibrium and non-equilibrium phase. • Code-to-code comparisons for Once-Through-Then-Out case were investigated. • Ability of the code to accommodate the void cavity was confirmed. - Abstract: A fuel management code for pebble bed reactors (PBRs) based on the Monte Carlo method has been developed in this study. The code, named Monte Carlo burnup analysis code for PBR (MCPBR), enables a simulation of the Once-Through-Then-Out (OTTO) cycle of a PBR from the running-in phase to the equilibrium condition. In MCPBR, a burnup calculation based on a continuous-energy Monte Carlo code, MVP-BURN, is coupled with an additional utility code to be able to simulate the OTTO cycle of PBR. MCPBR has several advantages in modeling PBRs, namely its Monte Carlo neutron transport modeling, its capability of explicitly modeling the double heterogeneity of the PBR core, and its ability to model different axial fuel speeds in the PBR core. Analysis at the equilibrium condition of the simplified PBR was used as the validation test of MCPBR. The calculation results of the code were compared with the results of diffusion-based fuel management PBR codes, namely the VSOP and PEBBED codes. Using JENDL-4.0 nuclide library, MCPBR gave a 4.15% and 3.32% lower keff value compared to VSOP and PEBBED, respectively. While using JENDL-3.3, MCPBR gave a 2.22% and 3.11% higher keff value compared to VSOP and PEBBED, respectively. The ability of MCPBR to analyze neutron transport in the top void of the PBR core and its effects was also confirmed
Jeraj, Robert; Keall, Paul
2000-12-01
The effect of the statistical uncertainty, or noise, in inverse treatment planning for intensity modulated radiotherapy (IMRT) based on Monte Carlo dose calculation was studied. Sets of Monte Carlo beamlets were calculated to give uncertainties at Dmax ranging from 0.2% to 4% for a lung tumour plan. The weights of these beamlets were optimized using a previously described procedure based on a simulated annealing optimization algorithm. Several different objective functions were used. It was determined that the use of Monte Carlo dose calculation in inverse treatment planning introduces two errors in the calculated plan. In addition to the statistical error due to the statistical uncertainty of the Monte Carlo calculation, a noise convergence error also appears. For the statistical error it was determined that apparently successfully optimized plans with a noisy dose calculation (3% 1σ at Dmax ), which satisfied the required uniformity of the dose within the tumour, showed as much as 7% underdose when recalculated with a noise-free dose calculation. The statistical error is larger towards the tumour and is only weakly dependent on the choice of objective function. The noise convergence error appears because the optimum weights are determined using a noisy calculation, which is different from the optimum weights determined for a noise-free calculation. Unlike the statistical error, the noise convergence error is generally larger outside the tumour, is case dependent and strongly depends on the required objectives.
A Markov Chain Monte Carlo Based Method for System Identification
Glaser, R E; Lee, C L; Nitao, J J; Hanley, W G
2002-10-22
This paper describes a novel methodology for the identification of mechanical systems and structures from vibration response measurements. It combines prior information, observational data and predictive finite element models to produce configurations and system parameter values that are most consistent with the available data and model. Bayesian inference and a Metropolis simulation algorithm form the basis for this approach. The resulting process enables the estimation of distributions of both individual parameters and system-wide states. Attractive features of this approach include its ability to: (1) provide quantitative measures of the uncertainty of a generated estimate; (2) function effectively when exposed to degraded conditions including: noisy data, incomplete data sets and model misspecification; (3) allow alternative estimates to be produced and compared, and (4) incrementally update initial estimates and analysis as more data becomes available. A series of test cases based on a simple fixed-free cantilever beam is presented. These results demonstrate that the algorithm is able to identify the system, based on the stiffness matrix, given applied force and resultant nodal displacements. Moreover, it effectively identifies locations on the beam where damage (represented by a change in elastic modulus) was specified.
Monte Carlo vs. Pencil Beam based optimization of stereotactic lung IMRT
Weinmann Martin; Söhn Matthias; Muzik Jan; Sikora Marcin; Alber Markus
2009-01-01
Abstract Background The purpose of the present study is to compare finite size pencil beam (fsPB) and Monte Carlo (MC) based optimization of lung intensity-modulated stereotactic radiotherapy (lung IMSRT). Materials and methods A fsPB and a MC algorithm as implemented in a biological IMRT planning system were validated by film measurements in a static lung phantom. Then, they were applied for static lung IMSRT planning based on three different geometrical patient models (one phase static CT, ...
Monte Carlo vs. Pencil Beam based optimization of stereotactic lung IMRT
Sikora, Marcin; Muzik, Jan; Söhn, Matthias; Weinmann, Martin; Alber, Markus
2009-01-01
Background The purpose of the present study is to compare finite size pencil beam (fsPB) and Monte Carlo (MC) based optimization of lung intensity-modulated stereotactic radiotherapy (lung IMSRT). Materials and methods A fsPB and a MC algorithm as implemented in a biological IMRT planning system were validated by film measurements in a static lung phantom. Then, they were applied for static lung IMSRT planning based on three different geometrical patient models (one phase static CT, density o...
Monte Carlo vs. Pencil Beam based optimization of stereotactic lung IMRT
Sikora, Marcin Pawel; Muzik, Jan; Söhn, Matthias; Weinmann, Martin; Alber, Markus
2009-01-01
Background: The purpose of the present study is to compare finite size pencil beam (fsPB) and Monte Carlo (MC) based optimization of lung intensity-modulated stereotactic radiotherapy (lung IMSRT). Materials and methods: A fsPB and a MC algorithm as implemented in a biological IMRT planning system were validated by film measurements in a static lung phantom. Then, they were applied for static lung IMSRT planning based on three different geometrical patient models (one phase ...
Effects of CT based Voxel Phantoms on Dose Distribution Calculated with Monte Carlo Method
Chen Chaobin; Huang Qunying; Wu Yican
2005-01-01
A few CT-based voxel phantoms were produced to investigate the sensitivity of Monte Carlo simulations of X-ray beam and electron beam to the proportions of elements and the mass densities of the materials used to express the patient's anatomical structure. The human body can be well outlined by air, lung, adipose, muscle, soft bone and hard bone to calculate the dose distribution with Monte Carlo method. The effects of the calibration curves established by using various CT scanners are not clinically significant based on our investigation. The deviation from the values of cumulative dose volume histogram derived from CT-based voxel phantoms is less than 1% for the given target.
Effects of CT based Voxel Phantoms on Dose Distribution Calculated with Monte Carlo Method
Chen, Chaobin; Huang, Qunying; Wu, Yican
2005-04-01
A few CT-based voxel phantoms were produced to investigate the sensitivity of Monte Carlo simulations of x-ray beam and electron beam to the proportions of elements and the mass densities of the materials used to express the patient's anatomical structure. The human body can be well outlined by air, lung, adipose, muscle, soft bone and hard bone to calculate the dose distribution with Monte Carlo method. The effects of the calibration curves established by using various CT scanners are not clinically significant based on our investigation. The deviation from the values of cumulative dose volume histogram derived from CT-based voxel phantoms is less than 1% for the given target.
DNA vector-based RNAi approach for stable depletion of poly(ADP-ribose) polymerase-1
RNA-mediated interference (RNAi) is a powerful technique that is now being used in mammalian cells to specifically silence a gene. Some recent studies have used this technique to achieve variable extent of depletion of a nuclear enzyme poly(ADP-ribose) polymerase-1 (PARP-1). These studies reported either transient silencing of PARP-1 using double-stranded RNA or stable silencing of PARP-1 with a DNA vector which was introduced by a viral delivery system. In contrast, here we report that a simple RNAi approach which utilizes a pBS-U6-based DNA vector containing strategically selected PARP-1 targeting sequence, introduced in the cells by conventional CaPO4 protocol, can be used to achieve stable and specific silencing of PARP-1 in different types of cells. We also provide a detailed strategy for selection and cloning of PARP-1-targeting sequences for the DNA vector, and demonstrate that this technique does not affect expression of its closest functional homolog PARP-2
Development of 3d reactor burnup code based on Monte Carlo method and exponential Euler method
Burnup analysis plays a key role in fuel breeding, transmutation and post-processing in nuclear reactor. Burnup codes based on one-dimensional and two-dimensional transport method have difficulties in meeting the accuracy requirements. A three-dimensional burnup analysis code based on Monte Carlo method and Exponential Euler method has been developed. The coupling code combines advantage of Monte Carlo method in complex geometry neutron transport calculation and FISPACT in fast and precise inventory calculation, meanwhile resonance Self-shielding effect in inventory calculation can also be considered. The IAEA benchmark text problem has been adopted for code validation. Good agreements were shown in the comparison with other participants' results. (authors)
Ray-Based Calculations with DEPLETE of Laser Backscatter in ICF Targets
Strozzi, D J; Williams, E; Hinkel, D; Froula, D; London, R; Callahan, D
2008-05-19
A steady-state model for Brillouin and Raman backscatter along a laser ray path is presented. The daughter plasma waves are treated in the strong damping limit, and have amplitudes given by the (linear) kinetic response to the ponderomotive drive. Pump depletion, inverse-bremsstrahlung damping, bremsstrahlung emission, Thomson scattering off density fluctuations, and whole-beam focusing are included. The numerical code Deplete, which implements this model, is described. The model is compared with traditional linear gain calculations, as well as 'plane-wave' simulations with the paraxial propagation code pF3D. Comparisons with Brillouin-scattering experiments at the Omega Laser Facility show that laser speckles greatly enhance the reflectivity over the Deplete results. An approximate upper bound on this enhancement is given by doubling the Deplete coupling coefficient. Analysis with Deplete of an ignition design for the National Ignition Facility (NIF), with a peak radiation temperature of 285 eV, shows encouragingly low reflectivity. Doubling the coupling to bracket speckle effects suggests a less optimistic picture. Re-absorption of Raman light is seen to be significant in this design.
We briefly present our atomistic kinetic Monte Carlo approach to model the diffusion of point-defects in Fe-based alloys, and therefore to simulate diffusion induced mass transport and subsequent nano-structural and microchemical changes. This methodology has been hitherto successfully applied to the simulation of thermal annealing experiments. We here present our achievements in the generalization of this method to the simulation of neutron irradiation damage. (authors)
Laser-based detection and tracking moving objects using data-driven Markov chain Monte Carlo
Vu, Trung-Dung; Aycard, Olivier
2009-01-01
We present a method of simultaneous detection and tracking moving objects from a moving vehicle equipped with a single layer laser scanner. A model-based approach is introduced to interpret the laser measurement sequence by hypotheses of moving object trajectories over a sliding window of time. Knowledge of various aspects including object model, measurement model, motion model are integrated in one theoretically sound Bayesian framework. The data-driven Markov chain Monte Carlo (DDMCMC) tech...
Development of a space radiation Monte Carlo computer simulation based on the FLUKA and ROOT codes
Pinsky, L; Ferrari, A; Sala, P; Carminati, F; Brun, R
2001-01-01
This NASA funded project is proceeding to develop a Monte Carlo-based computer simulation of the radiation environment in space. With actual funding only initially in place at the end of May 2000, the study is still in the early stage of development. The general tasks have been identified and personnel have been selected. The code to be assembled will be based upon two major existing software packages. The radiation transport simulation will be accomplished by updating the FLUKA Monte Carlo program, and the user interface will employ the ROOT software being developed at CERN. The end-product will be a Monte Carlo-based code which will complement the existing analytic codes such as BRYNTRN/HZETRN presently used by NASA to evaluate the effects of radiation shielding in space. The planned code will possess the ability to evaluate the radiation environment for spacecraft and habitats in Earth orbit, in interplanetary space, on the lunar surface, or on a planetary surface such as Mars. Furthermore, it will be usef...
The influence of air cavities within the PTV on Monte Carlo-based IMRT optimization
Smedt, Bart de [Department of Medical Physics, Ghent University, Gent (Belgium); Vanderstraeten, Barbara [Department of Medical Physics, Ghent University, Gent (Belgium); Reynaert, Nick [Department of Medical Physics, Ghent University, Gent (Belgium); Gersem, Werner de [Department of Radiotherapy, Ghent University Hospital, Gent (Belgium); Neve, Wilfried de [Department of Radiotherapy, Ghent University Hospital, Gent (Belgium); Thierens, Hubert [Department of Medical Physics, Ghent University, Gent (Belgium)
2007-06-15
Integrating Monte Carlo calculated dose distributions into an iterative aperture-based IMRT optimization process can improve the final treatment plan. However, the influence of large air cavities in the planning target volume (PTV) on the outcome of the optimization process should not be underestimated. To study this influence, the treatment plan of an ethmoid sinus cancer patient, which has large air cavities included in the PTV, is iteratively optimized in two different situations, namely when the large air cavities are included in the PTV and when these air cavities are excluded from the PTV. Two optimization methods were applied to integrate the Monte Carlo calculated dose distributions into the optimization process, namely the 'Correction-method' and the 'Per Segment-method'. The 'Correction-method' takes the Monte Carlo calculated global dose distribution into account in the optimization process by means of a correction matrix, which is in fact a dose distribution that is equal to the difference between the Monte Carlo calculated global dose distribution and the global dose distribution calculated by a conventional dose calculation algorithm. The 'Per Segment-method' uses directly the Monte Carlo calculated dose distributions of the individual segments in the optimization process. Both methods tend to converge whether or not large air cavities are excluded from the PTV during the optimization process. However, the 'Per Segment-method' performs better than the 'Correction-method' in both situations and the 'Per Segment-method' in the case where the large air cavities are excluded from the PTV leads to a better treatment plan then when these air cavities are included. Therefore we advise to exclude large air cavities and to apply the 'Per Segment-method' to integrate the Monte Carlo dose calculations into an iterative aperture-based optimization process. Nevertheless, the &apos
Fluctuations in the EAS radio signal derived with improved Monte Carlo simulations based on CORSIKA
Huege, T; Badea, F; Bähren, L; Bekk, K; Bercuci, A; Bertaina, M; Biermann, P L; Blumer, J; Bozdog, H; Brancus, I M; Buitink, S; Bruggemann, M; Buchholz, P; Butcher, H; Chiavassa, A; Daumiller, K; De Bruyn, A G; De Vos, C M; Di Pierro, F; Doll, P; Engel, R; Falcke, H; Gemmeke, H; Ghia, P L; Glasstetter, R; Grupen, C; Haungs, A; Heck, D; Hörandel, J R; Horneffer, A; Kampert, K H; Kant, G W; Klein, U; Kolotaev, Yu; Koopman, Y; Krömer, O; Kuijpers, J; Lafebre, S; Maier, G; Mathes, H J; Mayer, H J; Milke, J; Mitrica, B; Morello, C; Navarra, G; Nehls, S; Nigl, A; Obenland, R; Oehlschläger, J; Ostapchenko, S; Over, S; Pepping, H J; Petcu, M; Petrovic, J; Pierog, T; Plewnia, S; Rebel, H; Risse, A; Roth, M; Schieler, H; Schoonderbeek, G; Sima, O; Stumpert, M; Toma, G; Trinchero, G C; Ulrich, H; Valchierotti, S; Van Buren, J; Van Capellen, W; Walkowiak, W; Weindl, A; Wijnholds, S J; Wochele, J; Zabierowski, J; Zensus, J A; Zimmermann, D; Bowman, J D; Huege, Tim
2005-01-01
Cosmic ray air showers are known to emit pulsed radio emission which can be understood as coherent geosynchrotron radiation arising from the deflection of electron-positron pairs in the earth's magnetic field. Here, we present simulations carried out with an improved version of our Monte Carlo code for the calculation of geosynchrotron radiation. Replacing the formerly analytically parametrised longitudinal air shower development with CORSIKA-generated longitudinal profiles, we study the radio flux variations arising from inherent fluctuations between individual air showers. Additionally, we quantify the dependence of the radio emission on the nature of the primary particle by comparing the emission generated by proton- and iron-induced showers. This is only the first step in the incorporation of a more realistic air shower model into our Monte Carlo code. The inclusion of highly realistic CORSIKA-based particle energy, momentum and spatial distributions together with an analytical treatment of ionisation los...
ERSN-OpenMC, a Java-based GUI for OpenMC Monte Carlo code
Jaafar EL Bakkali
2016-07-01
Full Text Available OpenMC is a new Monte Carlo transport particle simulation code focused on solving two types of neutronic problems mainly the k-eigenvalue criticality fission source problems and external fixed fission source problems. OpenMC does not have any Graphical User Interface and the creation of one is provided by our java-based application named ERSN-OpenMC. The main feature of this application is to provide to the users an easy-to-use and flexible graphical interface to build better and faster simulations, with less effort and great reliability. Additionally, this graphical tool was developed with several features, as the ability to automate the building process of OpenMC code and related libraries as well as the users are given the freedom to customize their installation of this Monte Carlo code. A full description of the ERSN-OpenMC application is presented in this paper.
Polarization imaging of multiply-scattered radiation based on integral-vector Monte Carlo method
A new integral-vector Monte Carlo method (IVMCM) is developed to analyze the transfer of polarized radiation in 3D multiple scattering particle-laden media. The method is based on a 'successive order of scattering series' expression of the integral formulation of the vector radiative transfer equation (VRTE) for application of efficient statistical tools to improve convergence of Monte Carlo calculations of integrals. After validation against reference results in plane-parallel layer backscattering configurations, the model is applied to a cubic container filled with uniformly distributed monodispersed particles and irradiated by a monochromatic narrow collimated beam. 2D lateral images of effective Mueller matrix elements are calculated in the case of spherical and fractal aggregate particles. Detailed analysis of multiple scattering regimes, which are very similar for unpolarized radiation transfer, allows identifying the sensitivity of polarization imaging to size and morphology.
Monte Carlo Methods in Materials Science Based on FLUKA and ROOT
Pinsky, Lawrence; Wilson, Thomas; Empl, Anton; Andersen, Victor
2003-01-01
A comprehensive understanding of mitigation measures for space radiation protection necessarily involves the relevant fields of nuclear physics and particle transport modeling. One method of modeling the interaction of radiation traversing matter is Monte Carlo analysis, a subject that has been evolving since the very advent of nuclear reactors and particle accelerators in experimental physics. Countermeasures for radiation protection from neutrons near nuclear reactors, for example, were an early application and Monte Carlo methods were quickly adapted to this general field of investigation. The project discussed here is concerned with taking the latest tools and technology in Monte Carlo analysis and adapting them to space applications such as radiation shielding design for spacecraft, as well as investigating how next-generation Monte Carlos can complement the existing analytical methods currently used by NASA. We have chosen to employ the Monte Carlo program known as FLUKA (A legacy acronym based on the German for FLUctuating KAscade) used to simulate all of the particle transport, and the CERN developed graphical-interface object-oriented analysis software called ROOT. One aspect of space radiation analysis for which the Monte Carlo s are particularly suited is the study of secondary radiation produced as albedoes in the vicinity of the structural geometry involved. This broad goal of simulating space radiation transport through the relevant materials employing the FLUKA code necessarily requires the addition of the capability to simulate all heavy-ion interactions from 10 MeV/A up to the highest conceivable energies. For all energies above 3 GeV/A the Dual Parton Model (DPM) is currently used, although the possible improvement of the DPMJET event generator for energies 3-30 GeV/A is being considered. One of the major tasks still facing us is the provision for heavy ion interactions below 3 GeV/A. The ROOT interface is being developed in conjunction with the
Espel, Federico Puente
The main objective of this PhD research is to develop a high accuracy modeling tool using a Monte Carlo based coupled system. The presented research comprises the development of models to include the thermal-hydraulic feedback to the Monte Carlo method and speed-up mechanisms to accelerate the Monte Carlo criticality calculation. Presently, deterministic codes based on the diffusion approximation of the Boltzmann transport equation, coupled with channel-based (or sub-channel based) thermal-hydraulic codes, carry out the three-dimensional (3-D) reactor core calculations of the Light Water Reactors (LWRs). These deterministic codes utilize nuclear homogenized data (normally over large spatial zones, consisting of fuel assembly or parts of fuel assembly, and in the best case, over small spatial zones, consisting of pin cell), which is functionalized in terms of thermal-hydraulic feedback parameters (in the form of off-line pre-generated cross-section libraries). High accuracy modeling is required for advanced nuclear reactor core designs that present increased geometry complexity and material heterogeneity. Such high-fidelity methods take advantage of the recent progress in computation technology and coupled neutron transport solutions with thermal-hydraulic feedback models on pin or even on sub-pin level (in terms of spatial scale). The continuous energy Monte Carlo method is well suited for solving such core environments with the detailed representation of the complicated 3-D problem. The major advantages of the Monte Carlo method over the deterministic methods are the continuous energy treatment and the exact 3-D geometry modeling. However, the Monte Carlo method involves vast computational time. The interest in Monte Carlo methods has increased thanks to the improvements of the capabilities of high performance computers. Coupled Monte-Carlo calculations can serve as reference solutions for verifying high-fidelity coupled deterministic neutron transport methods
Comparing analytical and Monte Carlo optical diffusion models in phosphor-based X-ray detectors
Kalyvas, N.; Liaparinos, P.
2014-03-01
Luminescent materials are employed as radiation to light converters in detectors of medical imaging systems, often referred to as phosphor screens. Several processes affect the light transfer properties of phosphors. Amongst the most important is the interaction of light. Light attenuation (absorption and scattering) can be described either through "diffusion" theory in theoretical models or "quantum" theory in Monte Carlo methods. Although analytical methods, based on photon diffusion equations, have been preferentially employed to investigate optical diffusion in the past, Monte Carlo simulation models can overcome several of the analytical modelling assumptions. The present study aimed to compare both methodologies and investigate the dependence of the analytical model optical parameters as a function of particle size. It was found that the optical photon attenuation coefficients calculated by analytical modeling are decreased with respect to the particle size (in the region 1- 12 μm). In addition, for particles sizes smaller than 6μm there is no simultaneous agreement between the theoretical modulation transfer function and light escape values with respect to the Monte Carlo data.
Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy
Bonenfant, Éric; Magnoux, Vincent; Hissoiny, Sami; Ozell, Benoît; Beaulieu, Luc; Després, Philippe
2015-07-01
The aim of this study was to evaluate the potential of bGPUMCD, a Monte Carlo algorithm executed on Graphics Processing Units (GPUs), for fast dose calculations in permanent prostate implant dosimetry. It also aimed to validate a low dose rate brachytherapy source in terms of TG-43 metrics and to use this source to compute dose distributions for permanent prostate implant in very short times. The physics of bGPUMCD was reviewed and extended to include Rayleigh scattering and fluorescence from photoelectric interactions for all materials involved. The radial and anisotropy functions were obtained for the Nucletron SelectSeed in TG-43 conditions. These functions were compared to those found in the MD Anderson Imaging and Radiation Oncology Core brachytherapy source registry which are considered the TG-43 reference values. After appropriate calibration of the source, permanent prostate implant dose distributions were calculated for four patients and compared to an already validated Geant4 algorithm. The radial function calculated from bGPUMCD showed excellent agreement (differences within 1.3%) with TG-43 accepted values. The anisotropy functions at r = 1 cm and r = 4 cm were within 2% of TG-43 values for angles over 17.5°. For permanent prostate implants, Monte Carlo-based dose distributions with a statistical uncertainty of 1% or less for the target volume were obtained in 30 s or less for 1 × 1 × 1 mm3 calculation grids. Dosimetric indices were very similar (within 2.7%) to those obtained with a validated, independent Monte Carlo code (Geant4) performing the calculations for the same cases in a much longer time (tens of minutes to more than a hour). bGPUMCD is a promising code that lets envision the use of Monte Carlo techniques in a clinical environment, with sub-minute execution times on a standard workstation. Future work will explore the use of this code with an inverse planning method to provide a complete Monte Carlo-based planning solution.
Lin, N.-H.; Saxena, V. K.
1992-01-01
The physical characteristics of the Antarctic stratospheric aerosol are investigated via a comprehensive analysis of the SAGE II data during the most severe ozone depletion episode of October 1987. The aerosol size distribution is found to be bimodal in several instances using the randomized minimization search technique, which suggests that the distribution of a single mode may be used to fit the data in the retrieved size range only at the expense of resolution for the larger particles. On average, in the region below 18 km, a wavelike perturbation with the upstream tilting for the parameters of mass loading, total number, and surface area concentration is found to be located just above the region of the most severe ozone depletion.
Adjoint-based uncertainty quantification and sensitivity analysis for reactor depletion calculations
Stripling, Hayes Franklin
Depletion calculations for nuclear reactors model the dynamic coupling between the material composition and neutron flux and help predict reactor performance and safety characteristics. In order to be trusted as reliable predictive tools and inputs to licensing and operational decisions, the simulations must include an accurate and holistic quantification of errors and uncertainties in its outputs. Uncertainty quantification is a formidable challenge in large, realistic reactor models because of the large number of unknowns and myriad sources of uncertainty and error. We present a framework for performing efficient uncertainty quantification in depletion problems using an adjoint approach, with emphasis on high-fidelity calculations using advanced massively parallel computing architectures. This approach calls for a solution to two systems of equations: (a) the forward, engineering system that models the reactor, and (b) the adjoint system, which is mathematically related to but different from the forward system. We use the solutions of these systems to produce sensitivity and error estimates at a cost that does not grow rapidly with the number of uncertain inputs. We present the framework in a general fashion and apply it to both the source-driven and k-eigenvalue forms of the depletion equations. We describe the implementation and verification of solvers for the forward and ad- joint equations in the PDT code, and we test the algorithms on realistic reactor analysis problems. We demonstrate a new approach for reducing the memory and I/O demands on the host machine, which can be overwhelming for typical adjoint algorithms. Our conclusion is that adjoint depletion calculations using full transport solutions are not only computationally tractable, they are the most attractive option for performing uncertainty quantification on high-fidelity reactor analysis problems.
State-of-the-art in Comprehensive Cascade Control Approach through Monte-Carlo Based Representation
A.H. Mazinan
2015-10-01
Full Text Available The research relies on the comprehensive cascade control approach to be developed in the area of spacecraft, as long as Monte-Carlo based representation is taken into real consideration with respect to state-of-the-art. It is obvious that the conventional methods do not have sufficient merit to be able to deal with such a process under control, constantly, provided that a number of system parameters variations are to be used in providing real situations. It is to note that the new insights in the area of the research’s topic are valuable to outperform a class of spacecrafts performance as the realizations of the acquired results are to be addressed in both real and academic environments. In a word, there are a combination of double closed loop based upon quaternion based control approach in connection with Euler based control approach to handle the three-axis rotational angles and its rates, synchronously, in association with pulse modulation analysis and control allocation, where the dynamics and kinematics of the present system under control are analyzed. A series of experiments are carried out to consider the approach performance in which the aforementioned Monte-Carlo based representation is to be realized in verifying the investigated outcomes.
Experimental method for scanning the surface depletion region in nitride based heterostructures
The group-III-nitride semiconductors feature strong spontaneous polarization in the[0001] direction and charges on the respective polar surfaces. Within the resulting surface depletion region the surface field causes band banding and affects the optical transitions in quantum wells. We studied the changes of the emission characteristics of a single GaInN quantum well when its distance to the surface and the influence of the surface field varies. We observe a strong increase of the quantum well emission energy and a decrease of the line width when the surface field partially compensates the piezoelectric field of the quantum well. A scan of the total surface depletion region with a single quantum well as probe was performed. The obtained emission data allow for the direct determination of the width of the depletion region. The experimental method is promising for studies of the surface field and the surface potential of III-nitride surfaces and interfaces. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Zhu Feng [State Key Laboratory for Physical Chemistry of Solid Surfaces and Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005 (China); Yan Jiawei, E-mail: jwyan@xmu.edu.cn [State Key Laboratory for Physical Chemistry of Solid Surfaces and Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005 (China); Lu Miao [Pen-Tung Sah Micro-Nano Technology Research Center, Xiamen University, Xiamen, Fujian 361005 (China); Zhou Yongliang; Yang Yang; Mao Bingwei [State Key Laboratory for Physical Chemistry of Solid Surfaces and Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005 (China)
2011-10-01
Highlights: > A novel strategy based on a combination of interferent depleting and redox cycling is proposed for the plane-recessed microdisk array electrodes. > The strategy break up the restriction of selectively detecting a species that exhibits reversible reaction in a mixture with one that exhibits an irreversible reaction. > The electrodes enhance the current signal by redox cycling. > The electrodes can work regardless of the reversibility of interfering species. - Abstract: The fabrication, characterization and application of the plane-recessed microdisk array electrodes for selective detection are demonstrated. The electrodes, fabricated by lithographic microfabrication technology, are composed of a planar film electrode and a 32 x 32 recessed microdisk array electrode. Different from commonly used redox cycling operating mode for array configurations such as interdigitated array electrodes, a novel strategy based on a combination of interferent depleting and redox cycling is proposed for the electrodes with an appropriate configuration. The planar film electrode (the plane electrode) is used to deplete the interferent in the diffusion layer. The recessed microdisk array electrode (the microdisk array), locating within the diffusion layer of the plane electrode, works for detecting the target analyte in the interferent-depleted diffusion layer. In addition, the microdisk array overcomes the disadvantage of low current signal for a single microelectrode. Moreover, the current signal of the target analyte that undergoes reversible electron transfer can be enhanced due to the redox cycling between the plane electrode and the microdisk array. Based on the above working principle, the plane-recessed microdisk array electrodes break up the restriction of selectively detecting a species that exhibits reversible reaction in a mixture with one that exhibits an irreversible reaction, which is a limitation of single redox cycling operating mode. The advantages of the
Application of backtracking algorithm to depletion calculations
Based on the theory of linear chain method for analytical depletion calculations, the burn-up matrix is decoupled by the divide and conquer strategy and the linear chain with Markov characteristic is formed. The density, activity and decay heat of every nuclide in the chain can be calculated by analytical solutions. Every possible reaction path of the nuclide must be considered during the linear chain establishment process. To confirm the calculation precision and efficiency, the algorithm which can cover all the reaction paths of the nuclide and search the paths automatically according to to problem description and precision restrictions should be sought. Through analysis and comparison of several kinds of searching algorithms, the backtracking algorithm was selected to search and calculate the linear chains using Depth First Search (DFS) method. The depletion program can solve the depletion problem adaptively and with high fidelity. The solution space and time complexity of the program were analyzed. The new developed depletion program was coupled with Monte Carlo program MCMG-II to calculate the benchmark burn-up problem of the first core of China Experimental Fast Reactor (CEFR). The initial verification and validation of the program was performed by the calculation. (author)
Application of backtracking algorithm to depletion calculations
Based on the theory of linear chain method for analytical depletion calculations, the burnup matrix is decoupled by the divide and conquer strategy and the linear chain with Markov characteristic is formed. The density, activity and decay heat of every nuclide in the chain then can be calculated by analytical solutions. Every possible reaction path of the nuclide must be considered during the linear chain establishment process. To confirm the calculation precision and efficiency, the algorithm which can cover all the reaction paths and search the paths automatically according to the problem description and precision restrictions should be found. Through analysis and comparison of several kinds of searching algorithms, the backtracking algorithm was selected to establish and calculate the linear chains in searching process using depth first search (DFS) method, forming an algorithm which can solve the depletion problem adaptively and with high fidelity. The complexity of the solution space and time was analyzed by taking into account depletion process and the characteristics of the backtracking algorithm. The newly developed depletion program was coupled with Monte Carlo program MCMG-Ⅱ to calculate the benchmark burnup problem of the first core of China Experimental Fast Reactor (CEFR) and the preliminary verification and validation of the program were performed. (authors)
Channel capacity of ocean water is limited by propagation distance and optical properties. Previous studies on this problem are based on water-tank experiments with different amounts of Maalox antacid. However, propagation distance is limited by the experimental set-up and the optical properties are different from ocean water. Therefore, the experiment result is not accurate for the physical design of underwater wireless communications links. This letter developed a Monte Carlo model to study channel capacity of underwater optical communications. Moreover, this model can flexibly configure various parameters of transmitter, receiver and channel, and is suitable for physical underwater optical communications links design. (paper)
A new Monte-Carlo based simulation for the CryoEDM experiment
Raso-Barnett, Matthew
2015-01-01
This thesis presents a new Monte-Carlo based simulation of the physics of ultra-cold neutrons (UCN) in complex geometries and its application to the CryoEDM experiment. It includes a detailed description of the design and performance of this simulation along with its use in a project to study the magnetic depolarisation time of UCN within the apparatus due to magnetic impurities in the measurement cell, which is a crucial parameter in the sensitivity of a neutron electricdipole-moment (nEDM) ...
CARMEN: a system Monte Carlo based on linear programming from direct openings
The use of Monte Carlo (MC) has shown an improvement in the accuracy of the calculation of the dose compared to other analytics algorithms installed on the systems of business planning, especially in the case of non-standard situations typical of complex techniques such as IMRT and VMAT. Our treatment planning system called CARMEN, is based on the complete simulation, both the beam transport in the head of the accelerator and the patient, and simulation designed for efficient operation in terms of the accuracy of the estimate and the required computation times. (Author)
Research on Reliability Modelling Method of Machining Center Based on Monte Carlo Simulation
Chuanhai Chen
2013-03-01
Full Text Available The aim of this study is to get the reliability of series system and analyze the reliability of machining center. So a modified method of reliability modelling based on Monte Carlo simulation for series system is proposed. The reliability function, which is built by the classical statistics method based on the assumption that machine tools were repaired as good as new, may be biased in the real case. The reliability functions of subsystems are established respectively and then the reliability model is built according to the reliability block diagram. Then the fitting reliability function of machine tools is established using the failure data of sample generated by Monte Carlo simulation, whose inverse reliability function is solved by the linearization technique based on radial basis function. Finally, an example of the machining center is presented using the proposed method to show its potential application. The analysis results show that the proposed method can provide an accurate reliability model compared with the conventional method.
GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources
Townson, Reid; Tian, Zhen; Graves, Yan Jiang; Zavgorodni, Sergei; Jiang, Steve B
2013-01-01
A novel phase-space source implementation has been designed for GPU-based Monte Carlo dose calculation engines. Due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a novel strategy to pre-process patient-independent phase-spaces and bin particles by type, energy and position. Position bins l...
PeneloPET, a Monte Carlo PET simulation tool based on PENELOPE: features and validation
Espana, S; Herraiz, J L; Vicente, E; Udias, J M [Grupo de Fisica Nuclear, Departmento de Fisica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid, Madrid (Spain); Vaquero, J J; Desco, M [Unidad de Medicina y CirugIa Experimental, Hospital General Universitario Gregorio Maranon, Madrid (Spain)], E-mail: jose@nuc2.fis.ucm.es
2009-03-21
Monte Carlo simulations play an important role in positron emission tomography (PET) imaging, as an essential tool for the research and development of new scanners and for advanced image reconstruction. PeneloPET, a PET-dedicated Monte Carlo tool, is presented and validated in this work. PeneloPET is based on PENELOPE, a Monte Carlo code for the simulation of the transport in matter of electrons, positrons and photons, with energies from a few hundred eV to 1 GeV. PENELOPE is robust, fast and very accurate, but it may be unfriendly to people not acquainted with the FORTRAN programming language. PeneloPET is an easy-to-use application which allows comprehensive simulations of PET systems within PENELOPE. Complex and realistic simulations can be set by modifying a few simple input text files. Different levels of output data are available for analysis, from sinogram and lines-of-response (LORs) histogramming to fully detailed list mode. These data can be further exploited with the preferred programming language, including ROOT. PeneloPET simulates PET systems based on crystal array blocks coupled to photodetectors and allows the user to define radioactive sources, detectors, shielding and other parts of the scanner. The acquisition chain is simulated in high level detail; for instance, the electronic processing can include pile-up rejection mechanisms and time stamping of events, if desired. This paper describes PeneloPET and shows the results of extensive validations and comparisons of simulations against real measurements from commercial acquisition systems. PeneloPET is being extensively employed to improve the image quality of commercial PET systems and for the development of new ones.
Purpose: Microbeam radiation therapy (MRT) is an experimental radiotherapy technique that has shown potent antitumor effects with minimal damage to normal tissue in animal studies. This unique form of radiation is currently only produced in a few large synchrotron accelerator research facilities in the world. To promote widespread translational research on this promising treatment technology we have proposed and are in the initial development stages of a compact MRT system that is based on carbon nanotube field emission x-ray technology. We report on a Monte Carlo based feasibility study of the compact MRT system design. Methods: Monte Carlo calculations were performed using EGSnrc-based codes. The proposed small animal research MRT device design includes carbon nanotube cathodes shaped to match the corresponding MRT collimator apertures, a common reflection anode with filter, and a MRT collimator. Each collimator aperture is sized to deliver a beam width ranging from 30 to 200 μm at 18.6 cm source-to-axis distance. Design parameters studied with Monte Carlo include electron energy, cathode design, anode angle, filtration, and collimator design. Calculations were performed for single and multibeam configurations. Results: Increasing the energy from 100 kVp to 160 kVp increased the photon fluence through the collimator by a factor of 1.7. Both energies produced a largely uniform fluence along the long dimension of the microbeam, with 5% decreases in intensity near the edges. The isocentric dose rate for 160 kVp was calculated to be 700 Gy/min/A in the center of a 3 cm diameter target. Scatter contributions resulting from collimator size were found to produce only small (<7%) changes in the dose rate for field widths greater than 50 μm. Dose vs depth was weakly dependent on filtration material. The peak-to-valley ratio varied from 10 to 100 as the separation between adjacent microbeams varies from 150 to 1000 μm. Conclusions: Monte Carlo simulations demonstrate
Monte Carlo capabilities of the SCALE code system
Highlights: • Foundational Monte Carlo capabilities of SCALE are described. • Improvements in continuous-energy treatments are detailed. • New methods for problem-dependent temperature corrections are described. • New methods for sensitivity analysis and depletion are described. • Nuclear data, users interfaces, and quality assurance activities are summarized. - Abstract: SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a “plug-and-play” framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE’s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. An overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2
A four-dimensional (x, y, z, t) composite superquadric-based object model of the human heart for Monte Carlo simulation of radiological imaging systems has been developed. The phantom models the real temporal geometric conditions of a beating heart for frame rates up to 32 per cardiac cycle. Phantom objects are described by boolean combinations of superquadric ellipsoid sections.Moving spherical coordinate systems are chosen to model wall movement whereby points of the ventricle and atria walls are assumed to move towards a moving center-of-gravity point. Due to the non-static coordinate systems, the atrial/ventricular valve plane of the mathematical heart phantom moves up and down along the left ventricular long axis resulting in reciprocal emptying and filling of atria and ventricles. Compared to the base movement, the epicardial apex as well as the superior atria area are almost fixed in space. Since geometric parameters of the objects are directly applied on intersection calculations of the photon ray with object boundaries during Monte Carlo simulation, no phantom discretization artifacts are involved
Inverse treatment planning for radiation therapy based on fast Monte Carlo dose calculation
An inverse treatment planning system based on fast Monte Carlo (MC) dose calculation is presented. It allows optimisation of intensity modulated dose distributions in 15 to 60 minutes on present day personal computers. If a multi-processor machine is available, parallel simulation of particle histories is also possible, leading to further calculation time reductions. The optimisation process is divided into two stages. The first stage results influence profiles based on pencil beam (PB) dose calculation. The second stage starts with MC verification and post-optimisation of the PB dose and fluence distributions. Because of the potential to accurately model beam modifiers, MC based inverse planning systems are able to optimise compensator thicknesses and leaf trajectories instead of intensity profiles only. The corresponding techniques, whose implementation is the subject for future work, are also presented here. (orig.)
GPU-based high performance Monte Carlo simulation in neutron transport
Heimlich, Adino; Mol, Antonio C.A.; Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Lab. de Inteligencia Artificial Aplicada], e-mail: cmnap@ien.gov.br
2009-07-01
Graphics Processing Units (GPU) are high performance co-processors intended, originally, to improve the use and quality of computer graphics applications. Since researchers and practitioners realized the potential of using GPU for general purpose, their application has been extended to other fields out of computer graphics scope. The main objective of this work is to evaluate the impact of using GPU in neutron transport simulation by Monte Carlo method. To accomplish that, GPU- and CPU-based (single and multicore) approaches were developed and applied to a simple, but time-consuming problem. Comparisons demonstrated that the GPU-based approach is about 15 times faster than a parallel 8-core CPU-based approach also developed in this work. (author)
IMPROVED ALGORITHM FOR ROAD REGION SEGMENTATION BASED ON SEQUENTIAL MONTE-CARLO ESTIMATION
Zdenek Prochazka
2014-12-01
Full Text Available In recent years, many researchers and car makers put a lot of intensive effort into development of autonomous driving systems. Since visual information is the main modality used by human driver, a camera mounted on moving platform is very important kind of sensor, and various computer vision algorithms to handle vehicle surrounding situation are under intensive research. Our final goal is to develop a vision based lane detection system with ability to handle various types of road shapes, working on both structured and unstructured roads, ideally under presence of shadows. This paper presents a modified road region segmentation algorithm based on sequential Monte-Carlo estimation. Detailed description of the algorithm is given, and evaluation results show that the proposed algorithm outperforms the segmentation algorithm developed as a part of our previous work, as well as an conventional algorithm based on colour histogram.
Pattern-oriented Agent-based Monte Carlo simulation of Cellular Redox Environment
Tang, Jiaowei; Holcombe, Mike; Boonen, Harrie C.M.
. Because complex networks and dynamics of redox still is not completely understood , results of existing experiments will be used to validate the modeling according to ideas in pattern-oriented agent-based modeling[8]. The simulation of this model is computational intensive, thus an application 'FLAME......] could be very important factors. In our project, an agent-based Monte Carlo modeling [6] is offered to study the dynamic relationship between extracellular and intracellular redox and complex networks of redox reactions. In the model, pivotal redox-related reactions will be included, and the reactants...... cells. Biochimica Et Biophysica Acta-General Subjects, 2008. 1780(11): p. 1271-1290. 5. Jones, D.P., Redox sensing: orthogonal control in cell cycle and apoptosis signalling. J Intern Med, 2010. 268(5): p. 432-48. 6. Pogson, M., et al., Formal agent-based modelling of intracellular chemical interactions...
GPU-based high performance Monte Carlo simulation in neutron transport
Graphics Processing Units (GPU) are high performance co-processors intended, originally, to improve the use and quality of computer graphics applications. Since researchers and practitioners realized the potential of using GPU for general purpose, their application has been extended to other fields out of computer graphics scope. The main objective of this work is to evaluate the impact of using GPU in neutron transport simulation by Monte Carlo method. To accomplish that, GPU- and CPU-based (single and multicore) approaches were developed and applied to a simple, but time-consuming problem. Comparisons demonstrated that the GPU-based approach is about 15 times faster than a parallel 8-core CPU-based approach also developed in this work. (author)
Ureba, A.; Pereira-Barbeiro, A. R.; Jimenez-Ortega, E.; Baeza, J. A.; Salguero, F. J.; Leal, A.
2013-07-01
The use of Monte Carlo (MC) has shown an improvement in the accuracy of the calculation of the dose compared to other analytics algorithms installed on the systems of business planning, especially in the case of non-standard situations typical of complex techniques such as IMRT and VMAT. Our treatment planning system called CARMEN, is based on the complete simulation, both the beam transport in the head of the accelerator and the patient, and simulation designed for efficient operation in terms of the accuracy of the estimate and the required computation times. (Author)
Monte Carlo calculation based on hydrogen composition of the tissue for MV photon radiotherapy.
Demol, Benjamin; Viard, Romain; Reynaert, Nick
2015-01-01
The purpose of this study was to demonstrate that Monte Carlo treatment planning systems require tissue characterization (density and composition) as a function of CT number. A discrete set of tissue classes with a specific composition is introduced. In the current work we demonstrate that, for megavoltage photon radiotherapy, only the hydrogen content of the different tissues is of interest. This conclusion might have an impact on MRI-based dose calculations and on MVCT calibration using tissue substitutes. A stoichiometric calibration was performed, grouping tissues with similar atomic composition into 15 dosimetrically equivalent subsets. To demonstrate the importance of hydrogen, a new scheme was derived, with correct hydrogen content, complemented by oxygen (all elements differing from hydrogen are replaced by oxygen). Mass attenuation coefficients and mass stopping powers for this scheme were calculated and compared to the original scheme. Twenty-five CyberKnife treatment plans were recalculated by an in-house developed Monte Carlo system using tissue density and hydrogen content derived from the CT images. The results were compared to Monte Carlo simulations using the original stoichiometric calibration. Between 300 keV and 3 MeV, the relative difference of mass attenuation coefficients is under 1% within all subsets. Between 10 keV and 20 MeV, the relative difference of mass stopping powers goes up to 5% in hard bone and remains below 2% for all other tissue subsets. Dose-volume histograms (DVHs) of the treatment plans present no visual difference between the two schemes. Relative differences of dose indexes D98, D95, D50, D05, D02, and Dmean were analyzed and a distribution centered around zero and of standard deviation below 2% (3 σ) was established. On the other hand, once the hydrogen content is slightly modified, important dose differences are obtained. Monte Carlo dose planning in the field of megavoltage photon radiotherapy is fully achievable using
After an accidental release of radionuclides to the inhabited environment the external gamma irradiation from deposited radioactivity contributes significantly to the radiation exposure of the population for extended periods. For evaluating this exposure pathway, three main model requirements are needed: (i) to calculate the air kerma value per photon emitted per unit source area, based on Monte Carlo (MC) simulations; (ii) to describe the distribution and dynamics of radionuclides on the diverse urban surfaces; and (iii) to combine all these elements in a relevant urban model to calculate the resulting doses according to the actual scenario. This paper provides an overview about the different approaches to calculate photon transport in urban areas and about several dose calculation codes published. Two types of Monte Carlo simulations are presented using the global and the local approaches of photon transport. Moreover, two different philosophies of the dose calculation, the 'location factor method' and a combination of relative contamination of surfaces with air kerma values are described. The main features of six codes (ECOSYS, EDEM2M, EXPURT, PARATI, TEMAS, URGENT) are highlighted together with a short model-model features intercomparison
A CNS calculation line based on a Monte-Carlo method
The neutronic design of the moderator cell of a Cold Neutron Source (CNS) involves many different considerations regarding geometry, location, and materials. The decisions taken in this sense affect not only the neutron flux in the source neighbourhood, which can be evaluated by a standard deterministic method, but also the neutron flux values in experimental positions far away from the neutron source. At long distances from the CNS, very time consuming 3D deterministic methods or Monte Carlo transport methods are necessary in order to get accurate figures of standard and typical magnitudes such as average neutron flux, neutron current, angular flux, and luminosity. The Monte Carlo method is a unique and powerful tool to calculate the transport of neutrons and photons. Its use in a bootstrap scheme appears to be an appropriate solution for this type of systems. The use of MCNP as the main neutronic design tool leads to a fast and reliable method to perform calculations in a relatively short time with low statistical errors, if the proper scheme is applied. The design goal is to evaluate the performance of the CNS, its beam tubes and neutron guides, at specific experimental locations in the reactor hall and in the neutron or experimental hall. In this work, the calculation methodology used to design a CNS and its associated Neutron Beam Transport Systems (NBTS), based on the use of the MCNP code, is presented. (author)
Fission yield calculation using toy model based on Monte Carlo simulation
Jubaidah, E-mail: jubaidah@student.itb.ac.id [Nuclear Physics and Biophysics Division, Department of Physics, Bandung Institute of Technology. Jl. Ganesa No. 10 Bandung – West Java, Indonesia 40132 (Indonesia); Physics Department, Faculty of Mathematics and Natural Science – State University of Medan. Jl. Willem Iskandar Pasar V Medan Estate – North Sumatera, Indonesia 20221 (Indonesia); Kurniadi, Rizal, E-mail: rijalk@fi.itb.ac.id [Nuclear Physics and Biophysics Division, Department of Physics, Bandung Institute of Technology. Jl. Ganesa No. 10 Bandung – West Java, Indonesia 40132 (Indonesia)
2015-09-30
Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (R{sub c}), mean of left curve (μ{sub L}) and mean of right curve (μ{sub R}), deviation of left curve (σ{sub L}) and deviation of right curve (σ{sub R}). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90
Fission yield calculation using toy model based on Monte Carlo simulation
Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (Rc), mean of left curve (μL) and mean of right curve (μR), deviation of left curve (σL) and deviation of right curve (σR). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90
Adaptation of GEANT4 to Monte Carlo dose calculations based on CT data
The GEANT4 Monte Carlo code provides many powerful functions for conducting particle transport simulations with great reliability and flexibility. However, as a general purpose Monte Carlo code, not all the functions were specifically designed and fully optimized for applications in radiation therapy. One of the primary issues is the computational efficiency, which is especially critical when patient CT data have to be imported into the simulation model. In this paper we summarize the relevant aspects of the GEANT4 tracking and geometry algorithms and introduce our work on using the code to conduct dose calculations based on CT data. The emphasis is focused on modifications of the GEANT4 source code to meet the requirements for fast dose calculations. The major features include a quick voxel search algorithm, fast volume optimization, and the dynamic assignment of material density. These features are ready to be used for tracking the primary types of particles employed in radiation therapy such as photons, electrons, and heavy charged particles. Re-calculation of a proton therapy treatment plan generated by a commercial treatment planning program for a paranasal sinus case is presented as an example
Yu Hyeong
2010-12-01
Full Text Available Abstract Background The removal of high-abundance proteins from plasma is an efficient approach to investigating flow-through proteins for biomarker discovery studies. Most depletion methods are based on multiple immunoaffinity methods available commercially including LC columns and spin columns. Despite its usefulness, high-abundance depletion has an intrinsic problem, the sponge effect, which should be assessed during depletion experiments. Concurrently, the yield of depletion of high-abundance proteins must be monitored during the use of the depletion column. To date, there is no reasonable technique for measuring the recovery of flow-through proteins after depletion and assessing the capacity for capture of high-abundance proteins. Results In this study, we developed a method of measuring recovery yields of a multiple affinity removal system column easily and rapidly using enhanced green fluorescence protein as an indicator of flow-through proteins. Also, we monitored the capture efficiency through depletion of a high-abundance protein, albumin labeled with fluorescein isothiocyanate. Conclusion This simple method can be applied easily to common high-abundance protein depletion methods, effectively reducing experimental variations in biomarker discovery studies.
Sign learning kink-based (SiLK) quantum Monte Carlo for molecular systems
Ma, Xiaoyao; Loffler, Frank; Kowalski, Karol; Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana
2015-01-01
The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H$_{2}$O, N$_2$, and F$_2$ molecules. The method is based on Feynman's path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.
Study of CANDU thorium-based fuel cycles by deterministic and Monte Carlo methods
In the framework of the Generation IV forum, there is a renewal of interest in self-sustainable thorium fuel cycles applied to various concepts such as Molten Salt Reactors [1, 2] or High Temperature Reactors [3, 4]. Precise evaluations of the U-233 production potential relying on existing reactors such as PWRs [5] or CANDUs [6] are hence necessary. As a consequence of its design (online refueling and D2O moderator in a thermal spectrum), the CANDU reactor has moreover an excellent neutron economy and consequently a high fissile conversion ratio [7]. For these reasons, we try here, with a shorter term view, to re-evaluate the economic competitiveness of once-through thorium-based fuel cycles in CANDU [8]. Two simulation tools are used: the deterministic Canadian cell code DRAGON [9] and MURE [10], a C++ tool for reactor evolution calculations based on the Monte Carlo code MCNP [11]. (authors)
Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems.
Ma, Xiaoyao; Hall, Randall W; Löffler, Frank; Kowalski, Karol; Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana
2016-01-01
The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H2O, N2, and F2 molecules. The method is based on Feynman's path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem. PMID:26747795
Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems
Ma, Xiaoyao; Hall, Randall W.; Löffler, Frank; Kowalski, Karol; Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana
2016-01-01
The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H2O, N2, and F2 molecules. The method is based on Feynman's path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.
Sign learning kink-based (SiLK) quantum Monte Carlo for molecular systems
Ma, Xiaoyao; Hall, Randall W.; Loffler, Frank; Kowalski, Karol; Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana
2016-01-07
The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H2O, N2, and F2 molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.
Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems
Ma, Xiaoyao [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Hall, Randall W. [Department of Natural Sciences and Mathematics, Dominican University of California, San Rafael, California 94901 (United States); Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Löffler, Frank [Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Kowalski, Karol [William R. Wiley Environmental Molecular Sciences Laboratory, Battelle, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States); Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803 (United States)
2016-01-07
The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H{sub 2}O, N{sub 2}, and F{sub 2} molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.
Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems
The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H2O, N2, and F2 molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem
Simulation of Cone Beam CT System Based on Monte Carlo Method
Wang, Yu; Cao, Ruifen; Hu, Liqin; Li, Bingbing
2014-01-01
Adaptive Radiation Therapy (ART) was developed based on Image-guided Radiation Therapy (IGRT) and it is the trend of photon radiation therapy. To get a better use of Cone Beam CT (CBCT) images for ART, the CBCT system model was established based on Monte Carlo program and validated against the measurement. The BEAMnrc program was adopted to the KV x-ray tube. Both IOURCE-13 and ISOURCE-24 were chosen to simulate the path of beam particles. The measured Percentage Depth Dose (PDD) and lateral dose profiles under 1cm water were compared with the dose calculated by DOSXYZnrc program. The calculated PDD was better than 1% within the depth of 10cm. More than 85% points of calculated lateral dose profiles was within 2%. The correct CBCT system model helps to improve CBCT image quality for dose verification in ART and assess the CBCT image concomitant dose risk.
Monte Carlo dose calculation using a cell processor based PlayStation 3 system
This study investigates the performance of the EGSnrc computer code coupled with a Cell-based hardware in Monte Carlo simulation of radiation dose in radiotherapy. Performance evaluations of two processor-intensive functions namely, HOWNEAR and RANMARGET in the EGSnrc code were carried out basing on the 20-80 rule (Pareto principle). The execution speeds of the two functions were measured by the profiler gprof specifying the number of executions and total time spent on the functions. A testing architecture designed for Cell processor was implemented in the evaluation using a PlayStation3 (PS3) system. The evaluation results show that the algorithms examined are readily parallelizable on the Cell platform, provided that an architectural change of the EGSnrc was made. However, as the EGSnrc performance was limited by the PowerPC Processing Element in the PS3, PC coupled with graphics processing units or GPCPU may provide a more viable avenue for acceleration.
GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources
A novel phase-space source implementation has been designed for graphics processing unit (GPU)-based Monte Carlo dose calculation engines. Short of full simulation of the linac head, using a phase-space source is the most accurate method to model a clinical radiation beam in dose calculations. However, in GPU-based Monte Carlo dose calculations where the computation efficiency is very high, the time required to read and process a large phase-space file becomes comparable to the particle transport time. Moreover, due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a novel source implementation utilizing pre-processed patient-independent phase-spaces that are sorted by particle type, energy and position. Position bins located outside a rectangular region of interest enclosing the treatment field are ignored, substantially decreasing simulation time with little effect on the final dose distribution. The three methods were validated in absolute dose against BEAMnrc/DOSXYZnrc and compared using gamma-index tests (2%/2 mm above the 10% isodose). It was found that the PSL method has the optimal balance between accuracy and efficiency and thus is used as the default method in gDPM v3.0. Using the PSL method, open fields of 4 × 4, 10 × 10 and 30 × 30 cm
GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources.
Townson, Reid W; Jia, Xun; Tian, Zhen; Graves, Yan Jiang; Zavgorodni, Sergei; Jiang, Steve B
2013-06-21
A novel phase-space source implementation has been designed for graphics processing unit (GPU)-based Monte Carlo dose calculation engines. Short of full simulation of the linac head, using a phase-space source is the most accurate method to model a clinical radiation beam in dose calculations. However, in GPU-based Monte Carlo dose calculations where the computation efficiency is very high, the time required to read and process a large phase-space file becomes comparable to the particle transport time. Moreover, due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a novel source implementation utilizing pre-processed patient-independent phase-spaces that are sorted by particle type, energy and position. Position bins located outside a rectangular region of interest enclosing the treatment field are ignored, substantially decreasing simulation time with little effect on the final dose distribution. The three methods were validated in absolute dose against BEAMnrc/DOSXYZnrc and compared using gamma-index tests (2%/2 mm above the 10% isodose). It was found that the PSL method has the optimal balance between accuracy and efficiency and thus is used as the default method in gDPM v3.0. Using the PSL method, open fields of 4 × 4, 10 × 10 and 30 × 30 cm
GGEMS-Brachy: GPU GEant4-based Monte Carlo simulation for brachytherapy applications
Lemaréchal, Yannick; Bert, Julien; Falconnet, Claire; Després, Philippe; Valeri, Antoine; Schick, Ulrike; Pradier, Olivier; Garcia, Marie-Paule; Boussion, Nicolas; Visvikis, Dimitris
2015-07-01
In brachytherapy, plans are routinely calculated using the AAPM TG43 formalism which considers the patient as a simple water object. An accurate modeling of the physical processes considering patient heterogeneity using Monte Carlo simulation (MCS) methods is currently too time-consuming and computationally demanding to be routinely used. In this work we implemented and evaluated an accurate and fast MCS on Graphics Processing Units (GPU) for brachytherapy low dose rate (LDR) applications. A previously proposed Geant4 based MCS framework implemented on GPU (GGEMS) was extended to include a hybrid GPU navigator, allowing navigation within voxelized patient specific images and analytically modeled 125I seeds used in LDR brachytherapy. In addition, dose scoring based on track length estimator including uncertainty calculations was incorporated. The implemented GGEMS-brachy platform was validated using a comparison with Geant4 simulations and reference datasets. Finally, a comparative dosimetry study based on the current clinical standard (TG43) and the proposed platform was performed on twelve prostate cancer patients undergoing LDR brachytherapy. Considering patient 3D CT volumes of 400 × 250 × 65 voxels and an average of 58 implanted seeds, the mean patient dosimetry study run time for a 2% dose uncertainty was 9.35 s (≈500 ms 10-6 simulated particles) and 2.5 s when using one and four GPUs, respectively. The performance of the proposed GGEMS-brachy platform allows envisaging the use of Monte Carlo simulation based dosimetry studies in brachytherapy compatible with clinical practice. Although the proposed platform was evaluated for prostate cancer, it is equally applicable to other LDR brachytherapy clinical applications. Future extensions will allow its application in high dose rate brachytherapy applications.
GGEMS-Brachy: GPU GEant4-based Monte Carlo simulation for brachytherapy applications
In brachytherapy, plans are routinely calculated using the AAPM TG43 formalism which considers the patient as a simple water object. An accurate modeling of the physical processes considering patient heterogeneity using Monte Carlo simulation (MCS) methods is currently too time-consuming and computationally demanding to be routinely used. In this work we implemented and evaluated an accurate and fast MCS on Graphics Processing Units (GPU) for brachytherapy low dose rate (LDR) applications. A previously proposed Geant4 based MCS framework implemented on GPU (GGEMS) was extended to include a hybrid GPU navigator, allowing navigation within voxelized patient specific images and analytically modeled 125I seeds used in LDR brachytherapy. In addition, dose scoring based on track length estimator including uncertainty calculations was incorporated. The implemented GGEMS-brachy platform was validated using a comparison with Geant4 simulations and reference datasets. Finally, a comparative dosimetry study based on the current clinical standard (TG43) and the proposed platform was performed on twelve prostate cancer patients undergoing LDR brachytherapy. Considering patient 3D CT volumes of 400 × 250 × 65 voxels and an average of 58 implanted seeds, the mean patient dosimetry study run time for a 2% dose uncertainty was 9.35 s (≈500 ms 10−6 simulated particles) and 2.5 s when using one and four GPUs, respectively. The performance of the proposed GGEMS-brachy platform allows envisaging the use of Monte Carlo simulation based dosimetry studies in brachytherapy compatible with clinical practice. Although the proposed platform was evaluated for prostate cancer, it is equally applicable to other LDR brachytherapy clinical applications. Future extensions will allow its application in high dose rate brachytherapy applications. (paper)
Pollutant nitrogen deposition effects on soil and foliar element concentrations were investigated in acidic and limestone grasslands, located in one of the most nitrogen and acid rain polluted regions of the UK, using plots treated for 8-10 years with 35-140 kg N ha-2 y-1 as NH4NO3. Historic data suggests both grasslands have acidified over the past 50 years. Nitrogen deposition treatments caused the grassland soils to lose 23-35% of their total available bases (Ca, Mg, K, and Na) and they became acidified by 0.2-0.4 pH units. Aluminium, iron and manganese were mobilised and taken up by limestone grassland forbs and were translocated down the acid grassland soil. Mineral nitrogen availability increased in both grasslands and many species showed foliar N enrichment. This study provides the first definitive evidence that nitrogen deposition depletes base cations from grassland soils. The resulting acidification, metal mobilisation and eutrophication are implicated in driving floristic changes. - Nitrogen deposition causes base cation depletion, acidification and eutrophication of semi-natural grassland soils
Development of a space radiation Monte Carlo computer simulation based on the FLUKA and ROOT codes.
Pinsky, L S; Wilson, T L; Ferrari, A; Sala, P; Carminati, F; Brun, R
2001-01-01
This NASA funded project is proceeding to develop a Monte Carlo-based computer simulation of the radiation environment in space. With actual funding only initially in place at the end of May 2000, the study is still in the early stage of development. The general tasks have been identified and personnel have been selected. The code to be assembled will be based upon two major existing software packages. The radiation transport simulation will be accomplished by updating the FLUKA Monte Carlo program, and the user interface will employ the ROOT software being developed at CERN. The end-product will be a Monte Carlo-based code which will complement the existing analytic codes such as BRYNTRN/HZETRN presently used by NASA to evaluate the effects of radiation shielding in space. The planned code will possess the ability to evaluate the radiation environment for spacecraft and habitats in Earth orbit, in interplanetary space, on the lunar surface, or on a planetary surface such as Mars. Furthermore, it will be useful in the design and analysis of experiments such as ACCESS (Advanced Cosmic-ray Composition Experiment for Space Station), which is an Office of Space Science payload currently under evaluation for deployment on the International Space Station (ISS). FLUKA will be significantly improved and tailored for use in simulating space radiation in four ways. First, the additional physics not presently within the code that is necessary to simulate the problems of interest, namely the heavy ion inelastic processes, will be incorporated. Second, the internal geometry package will be replaced with one that will substantially increase the calculation speed as well as simplify the data input task. Third, default incident flux packages that include all of the different space radiation sources of interest will be included. Finally, the user interface and internal data structure will be melded together with ROOT, the object-oriented data analysis infrastructure system. Beyond
Nanoscale Field Effect Optical Modulators Based on Depletion of Epsilon-Near-Zero Films
Lu, Zhaolin; Shi, Kaifeng
2015-01-01
The field effect in metal-oxide-semiconductor (MOS) capacitors plays a key role in field-effect transistors (FETs), which are the fundamental building blocks of modern digital integrated circuits. Recent works show that the field effect can also be used to make optical/plasmonic modulators. In this paper, we report field effect electro-absorption modulators (FEOMs) each made of an ultrathin epsilon-near-zero (ENZ) film, as the active material, sandwiched in a silicon or plasmonic waveguide. Without a bias, the ENZ film maximizes the attenuation of the waveguides and the modulators work at the OFF state; contrariwise, depletion of the carriers in the ENZ film greatly reduces the attenuation and the modulators work at the ON state. The double capacitor gating scheme is used to enhance the modulation by the field effect. According to our simulation, extinction ratio up to 3.44 dB can be achieved in a 500-nm long Si waveguide with insertion loss only 0.71 dB (85.0%); extinction ratio up to 7.86 dB can be achieved...
Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa
2011-08-01
In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.
MaGe - a Geant4-based Monte Carlo framework for low-background experiments
Chan, Yuen-Dat; Henning, Reyco; Gehman, Victor M; Johnson, Rob A; Jordan, David V; Kazkaz, Kareem; Knapp, Markus; Kroninger, Kevin; Lenz, Daniel; Liu, Jing; Liu, Xiang; Marino, Michael G; Mokhtarani, Akbar; Pandola, Luciano; Schubert, Alexis G; Tomei, Claudia
2008-01-01
A Monte Carlo framework, MaGe, has been developed based on the Geant4 simulation toolkit. Its purpose is to simulate physics processes in low-energy and low-background radiation detectors, specifically for the Majorana and Gerda $^{76}$Ge neutrinoless double-beta decay experiments. This jointly-developed tool is also used to verify the simulation of physics processes relevant to other low-background experiments in Geant4. The MaGe framework contains simulations of prototype experiments and test stands, and is easily extended to incorporate new geometries and configurations while still using the same verified physics processes, tunings, and code framework. This reduces duplication of efforts and improves the robustness of and confidence in the simulation output.
A Monte Carlo simulation based inverse propagation method for stochastic model updating
Bao, Nuo; Wang, Chunjie
2015-08-01
This paper presents an efficient stochastic model updating method based on statistical theory. Significant parameters have been selected implementing the F-test evaluation and design of experiments, and then the incomplete fourth-order polynomial response surface model (RSM) has been developed. Exploiting of the RSM combined with Monte Carlo simulation (MCS), reduces the calculation amount and the rapid random sampling becomes possible. The inverse uncertainty propagation is given by the equally weighted sum of mean and covariance matrix objective functions. The mean and covariance of parameters are estimated synchronously by minimizing the weighted objective function through hybrid of particle-swarm and Nelder-Mead simplex optimization method, thus the better correlation between simulation and test is achieved. Numerical examples of a three degree-of-freedom mass-spring system under different conditions and GARTEUR assembly structure validated the feasibility and effectiveness of the proposed method.
Electric conduction in semiconductors: a pedagogical model based on the Monte Carlo method
We present a pedagogic approach aimed at modelling electric conduction in semiconductors in order to describe and explain some macroscopic properties, such as the characteristic behaviour of resistance as a function of temperature. A simple model of the band structure is adopted for the generation of electron-hole pairs as well as for the carrier transport in moderate electric fields. The semiconductor behaviour is described by substituting the traditional statistical approach (requiring a deep mathematical background) with microscopic models, based on the Monte Carlo method, in which simple rules applied to microscopic particles and quasi-particles determine the macroscopic properties. We compare measurements of electric properties of matter with 'virtual experiments' built by using some models where the physical concepts can be presented at different formalization levels
CAD-based Monte Carlo program for integrated simulation of nuclear system SuperMC
SuperMC is a (Computer-Aided-Design) CAD-based Monte Carlo (MC) program for integrated simulation of nuclear systems developed by FDS Team (China), making use of hybrid MC-deterministic method and advanced computer technologies. The design aim, architecture and main methodology of SuperMC are presented in this paper. The taking into account of multi-physics processes and the use of advanced computer technologies such as automatic geometry modeling, intelligent data analysis and visualization, high performance parallel computing and cloud computing, contribute to the efficiency of the code. SuperMC2.1, the latest version of the code for neutron, photon and coupled neutron and photon transport calculation, has been developed and validated by using a series of benchmarking cases such as the fusion reactor ITER model and the fast reactor BN-600 model
Calculation and analysis of heat source of PWR assemblies based on Monte Carlo method
When fission occurs in nuclear fuel in reactor core, it releases numerous neutron and γ radiation, which takes energy deposition in fuel components and yields many factors such as thermal stressing and radiation damage influencing the safe operation of a reactor. Using the three-dimensional Monte Carlo transport calculation program MCNP and continuous cross-section database based on ENDF/B series to calculate the heat rate of the heat source on reference assemblies of a PWR when loading with 18-month short refueling cycle mode, and get the precise values of the control rod, thimble plug and new burnable poison rod within Gd, so as to provide basis for reactor design and safety verification. (authors)
Seabed radioactivity based on in situ measurements and Monte Carlo simulations
Activity concentration measurements were carried out on the seabed, by implementing the underwater detection system KATERINA. The efficiency calibration was performed in the energy range 350–2600 keV, using in situ and laboratory measurements. The efficiency results were reproduced and extended in a broadened range of energies from 150 to 2600 keV, by Monte Carlo simulations, using the MCNP5 code. The concentrations of 40K, 214Bi and 208Tl were determined utilizing the present approach. The results were validated by laboratory measurements. - Highlights: • The KATERINA system was applied for marine sediments. • MC simulations using MCNP5 reproduced experimental energy spectra and efficiency. • The in-situ method provided quantitative measurements. • The measurements were validated with lab-based methods
Monte Carlo-based Noise Compensation in Coil Intensity Corrected Endorectal MRI
Lui, Dorothy; Haider, Masoom; Wong, Alexander
2015-01-01
Background: Prostate cancer is one of the most common forms of cancer found in males making early diagnosis important. Magnetic resonance imaging (MRI) has been useful in visualizing and localizing tumor candidates and with the use of endorectal coils (ERC), the signal-to-noise ratio (SNR) can be improved. The coils introduce intensity inhomogeneities and the surface coil intensity correction built into MRI scanners is used to reduce these inhomogeneities. However, the correction typically performed at the MRI scanner level leads to noise amplification and noise level variations. Methods: In this study, we introduce a new Monte Carlo-based noise compensation approach for coil intensity corrected endorectal MRI which allows for effective noise compensation and preservation of details within the prostate. The approach accounts for the ERC SNR profile via a spatially-adaptive noise model for correcting non-stationary noise variations. Such a method is useful particularly for improving the image quality of coil i...
A Monte Carlo-based treatment-planning tool for ion beam therapy
Böhlen, T T; Dosanjh, M; Ferrari, A; Haberer, T; Parodi, K; Patera, V; Mairan, A
2013-01-01
Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), theMCTP tool is able to perform TP studies u...
Simulation of nuclear material identification system based on Monte Carlo sampling method
Background: Caused by the danger of radioactivity, nuclear material identification is sometimes a difficult problem. Purpose: In order to reflect the particle transport processes in nuclear fission and present the effectiveness of the signatures of Nuclear Materials Identification System (NMIS), based on physical principles and experimental statistical data. Methods: We established a Monte Carlo simulation model of nuclear material identification system and then acquired three channels of time domain pulse signal. Results: Auto-Correlation Functions (AC), Cross-Correlation Functions (CC), Auto Power Spectral Densities (APSD) and Cross Power Spectral Densities (CPSD) between channels can obtain several signatures, which can show some characters of nuclear material. Conclusions: The simulation results indicate that the way can help to further study the features of the system. (authors)
GPU-based fast Monte Carlo simulation for radiotherapy dose calculation
Jia, Xun; Graves, Yan Jiang; Folkerts, Michael; Jiang, Steve B
2011-01-01
Monte Carlo (MC) simulation is commonly considered to be the most accurate dose calculation method in radiotherapy. However, its efficiency still requires improvement for many routine clinical applications. In this paper, we present our recent progress towards the development a GPU-based MC dose calculation package, gDPM v2.0. It utilizes the parallel computation ability of a GPU to achieve high efficiency, while maintaining the same particle transport physics as in the original DPM code and hence the same level of simulation accuracy. In GPU computing, divergence of execution paths between threads can considerably reduce the efficiency. Since photons and electrons undergo different physics and hence attain different execution paths, we use a simulation scheme where photon transport and electron transport are separated to partially relieve the thread divergence issue. High performance random number generator and hardware linear interpolation are also utilized. We have also developed various components to hand...
Werner, M J; Sornette, D
2009-01-01
In meteorology, engineering and computer sciences, data assimilation is routinely employed as the optimal way to combine noisy observations with prior model information for obtaining better estimates of a state, and thus better forecasts, than can be achieved by ignoring data uncertainties. Earthquake forecasting, too, suffers from measurement errors and partial model information and may thus gain significantly from data assimilation. We present perhaps the first fully implementable data assimilation method for earthquake forecasts generated by a point-process model of seismicity. We test the method on a synthetic and pedagogical example of a renewal process observed in noise, which is relevant to the seismic gap hypothesis, models of characteristic earthquakes and to recurrence statistics of large quakes inferred from paleoseismic data records. To address the non-Gaussian statistics of earthquakes, we use sequential Monte Carlo methods, a set of flexible simulation-based methods for recursively estimating ar...
Monte Carlo simulation of grating-based neutron phase contrast imaging at CPHS
Since the launching of the Compact Pulsed Hadron Source (CPHS) project of Tsinghua University in 2009, works have begun on the design and engineering of an imaging/radiography instrument for the neutron source provided by CPHS. The instrument will perform basic tasks such as transmission imaging and computerized tomography. Additionally, we include in the design the utilization of coded-aperture and grating-based phase contrast methodology, as well as the options of prompt gamma-ray analysis and neutron-energy selective imaging. Previously, we had implemented the hardware and data-analysis software for grating-based X-ray phase contrast imaging. Here, we investigate Geant4-based Monte Carlo simulations of neutron refraction phenomena and then model the grating-based neutron phase contrast imaging system according to the classic-optics-based method. The simulated experimental results of the retrieving phase shift gradient information by five-step phase-stepping approach indicate the feasibility of grating-based neutron phase contrast imaging as an option for the cold neutron imaging instrument at the CPHS.
A CAD based automatic modeling method for primitive solid based Monte Carlo calculation geometry
The Multi-Physics Coupling Analysis Modeling Program (MCAM), developed by FDS Team, China, is an advanced modeling tool aiming to solve the modeling challenges for multi-physics coupling simulation. The automatic modeling method for SuperMC, the Super Monte Carlo Calculation Program for Nuclear and Radiation Process, was recently developed and integrated in MCAM5.2. This method could bi-convert between CAD model and SuperMC input file. While converting from CAD model to SuperMC model, the CAD model was decomposed into several convex solids set, and then corresponding SuperMC convex basic solids were generated and output. While inverting from SuperMC model to CAD model, the basic primitive solids was created and related operation was done to according the SuperMC model. This method was benchmarked with ITER Benchmark model. The results showed that the method was correct and effective. (author)
The internal radiation dose calculations based on Chinese models is important in nuclear medicine. Most of the existing models are based on the physical and anatomical data of Caucasian, whose anatomical structure and physiological parameters are quite different from the Chinese, may lead significant effect on internal radiation. Therefore, it is necessary to establish the model based on the Chinese ethnic characteristics, and applied to radiation dosimetry calculation. In this study, a voxel model was established based on the high resolution Visible Chinese Human (VCH). The transport procedure of photon and electron was simulated using the MCNPX Monte Carlo code. Absorbed fraction (AF) and specific absorbed fraction (SAF) were calculated and S-factors and mean absorbed doses for organs with 99mTc located in liver were also obtained. In comparison with those of VIP-Man and MIRD models, discrepancies were found to be correlated with the racial and anatomical differences in organ mass and inter-organ distance. The internal dosimetry data based on other models that were used to apply to Chinese adult population are replaced with Chinese specific data. The obtained results provide a reference for nuclear medicine, such as dose verification after surgery and potential radiation evaluation for radionuclides in preclinical research, etc. (authors)
Xu Xiao-Bo; Zhang He-Ming; Hu Hui-Yong; Ma Jian-Li; Xu Li-Jun
2011-01-01
The base-collector depletion capacitance for vertical SiGe npn heterojunction bipolar transistors (HBTs) on silicon on insulator (SOI) is split into vertical and lateral parts. This paper proposes a novel analytical depletion capacitance model of this structure for the first time. A large discrepancy is predicted when the present model is compared with the conventional depletion model, and it is shown that the capacitance decreases with the increase of the reverse collectorbase bias-and shows a kink as the reverse collector-base bias reaches the effective vertical punch-through voltage while the voltage differs with the collector doping concentrations, which is consistent with measurement results. The model can be employed for a fast evaluation of the depletion capacitance of an SOI SiGe HBT and has useful applications on the design and simulation of high performance SiGe circuits and devices.
Full modelling of the MOSAIC animal PET system based on the GATE Monte Carlo simulation code
within 9%. For a 410-665 keV energy window, the measured sensitivity for a centred point source was 1.53% and mouse and rat scatter fractions were respectively 12.0% and 18.3%. The scattered photons produced outside the rat and mouse phantoms contributed to 24% and 36% of total simulated scattered coincidences. Simulated and measured single and prompt count rates agreed well for activities up to the electronic saturation at 110 MBq for the mouse and rat phantoms. Volumetric spatial resolution was 17.6 μL at the centre of the FOV with differences less than 6% between experimental and simulated spatial resolution values. The comprehensive evaluation of the Monte Carlo modelling of the Mosaic(TM) system demonstrates that the GATE package is adequately versatile and appropriate to accurately describe the response of an Anger logic based animal PET system
Unfiltered Monte Carlo-based tungsten anode spectral model from 20 to 640 kV
Hernandez, A. M.; Boone, John M.
2014-03-01
A Monte Carlo-based tungsten anode spectral model, conceptually similar to the previously-developed TASMIP model, was developed. This new model provides essentially unfiltered x-ray spectra with better energy resolution and significantly extends the range of tube potentials for available spectra. MCNPX was used to simulate x-ray spectra as a function of tube potential for a conventional x-ray tube configuration with several anode compositions. Thirty five x-ray spectra were simulated and used as the basis of interpolating a complete set of tungsten x-ray spectra (at 1 kV intervals) from 20 to 640 kV. Additionally, Rh and Mo anode x-ray spectra were simulated from 20 to 60 kV. Cubic splines were used to construct piecewise polynomials that interpolate the photon fluence per energy bin as a function of tube potential for each anode material. The tungsten anode spectral model using interpolating cubic splines (TASMICS) generates minimally-filtered (0.8 mm Be) x-ray spectra from 20 to 640 kV with 1 keV energy bins. The rhodium and molybdenum anode spectral models (RASMICS and MASMICS, respectively) generate minimally-filtered x-ray spectra from 20 to 60 kV with 1 keV energy bins. TASMICS spectra showed no statistically significant differences when compared with the empirical TASMIP model, the semi-empirical Birch and Marshall model, and a Monte Carlo spectrum reported in AAPM TG 195. The RASMICS and MASMICS spectra showed no statistically significant differences when compared with their counterpart RASMIP and MASMIP models. Spectra from the TASMICS, MASMICS, and RASMICS models are available in spreadsheet format for interested users.
Highlights: • Monte-Carlo burnup simulations are often used as reference calculations. • Monte-Carlo burnup simulations suffers however of prohibitive calculation times. • This paper proposes a method to accelerate Monte-Carlo burnup codes. • This method factorizes the transport steps using the correlated sampling method. - Abstract: Monte-Carlo burnup calculations are nowadays the reference method to obtain fuel inventories in reactor configurations. Their main drawback is the very long computing time associated with the calculation. A method is presented here which attempts to speed up the calculation by replacing full simulations by perturbation calculations based on correlated sampling. The method is tested in a PWR assembly configuration and numerical results are given for the figure of merit. These results show that a speed-up of up to a factor of 5 can be achieved
Full text: The Director General of the International Atomic Energy Agency (IAEA), Mohamed ElBaradei, issued today the following statement: The IAEA has been involved in United Nations efforts relating to the impact of the use of depleted uranium (DU) ammunition in Kosovo. It has supported the United Nations Environment Programme (UNEP) in the assessment which it is making, at the request of the Secretary-General, of that impact. In this connection, in November 2000, Agency experts participated in a UNEP-led fact-finding mission in Kosovo. DU is only slightly radioactive, being about 40% as radioactive as natural uranium. Chemically and physically, DU behaves in the same way as natural uranium. The chemical toxicity is normally the dominant factor for human health. However, it is necessary to carefully assess the impact of DU in the special circumstances in which it was used, e.g. to determine whether it was inhaled or ingested or whether fragments came into close contact with individuals. It is therefore essential, before an authoritative conclusion can be reached, that a detailed survey of the territory in which DU was used and of the people who came in contact with the depleted uranium in any form be carried out. In the meantime it would be prudent, as recommended by the leader of the November UNEP mission, to adopt precautionary measures. Depending on the results of the survey further measures may be necessary. The Agency, within its statutory responsibilities and on the basis of internationally accepted radiation safety standards, will continue to co-operate with other organizations, in particular WHO and UNEP, with a view to carrying out a comprehensive assessment. Co-operation by and additional information from NATO will be prerequisites. The experience gained from such an assessment could be useful for similar studies that may be carried out elsewhere in the Balkans or in the Gulf. (author)
Highlights: • We present a new Monte Carlo method to perform sensitivity/perturbation calculations. • Sensitivity of keff, reaction rates, point kinetics parameters to nuclear data. • Fully continuous implicitly constrained Monte Carlo sensitivities to scattering distributions. • Implementation of the method in the continuous energy Monte Carlo code SERPENT. • Verification against ERANOS and TSUNAMI generalized perturbation theory results. - Abstract: In this work, the implementation of a collision history-based approach to sensitivity/perturbation calculations in the Monte Carlo code SERPENT is discussed. The proposed methods allow the calculation of the effects of nuclear data perturbation on several response functions: the effective multiplication factor, reaction rate ratios and bilinear ratios (e.g., effective kinetics parameters). SERPENT results are compared to ERANOS and TSUNAMI Generalized Perturbation Theory calculations for two fast metallic systems and for a PWR pin-cell benchmark. New methods for the calculation of sensitivities to angular scattering distributions are also presented, which adopts fully continuous (in energy and angle) Monte Carlo estimators
We present a new Monte Carlo method based upon the theoretical proposal of Claverie and Soto. By contrast with other Quantum Monte Carlo methods used so far, the present approach uses a pure diffusion process without any branching. The many-fermion problem (with the specific constraint due to the Pauli principle) receives a natural solution in the framework of this method: in particular, there is neither the fixed-node approximation not the nodal release problem which occur in other approaches (see, e.g., Ref. 8 for a recent account). We give some numerical results concerning simple systems in order to illustrate the numerical feasibility of the proposed algorithm
Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport
Jia, Xun; Sempau, Josep; Choi, Dongju; Majumdar, Amitava; Jiang, Steve B
2009-01-01
Monte Carlo simulation is the most accurate method for absorbed dose calculations in radiotherapy. Its efficiency still requires improvement for routine clinical applications, especially for online adaptive radiotherapy. In this paper, we report our recent development on a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport. We have implemented the Dose Planning Method (DPM) Monte Carlo dose calculation package (Sempau et al, Phys. Med. Biol., 45(2000)2263-2291) on GPU architecture under CUDA platform. The implementation has been tested with respect to the original sequential DPM code on CPU in two cases. Our results demonstrate the adequate accuracy of the GPU implementation for both electron and photon beams in radiotherapy energy range. A speed up factor of 4.5 and 5.5 times have been observed for electron and photon testing cases, respectively, using an NVIDIA Tesla C1060 GPU card against a 2.27GHz Intel Xeon CPU processor .
Monte Carlo vs. Pencil Beam based optimization of stereotactic lung IMRT
Weinmann Martin
2009-12-01
Full Text Available Abstract Background The purpose of the present study is to compare finite size pencil beam (fsPB and Monte Carlo (MC based optimization of lung intensity-modulated stereotactic radiotherapy (lung IMSRT. Materials and methods A fsPB and a MC algorithm as implemented in a biological IMRT planning system were validated by film measurements in a static lung phantom. Then, they were applied for static lung IMSRT planning based on three different geometrical patient models (one phase static CT, density overwrite one phase static CT, average CT of the same patient. Both 6 and 15 MV beam energies were used. The resulting treatment plans were compared by how well they fulfilled the prescribed optimization constraints both for the dose distributions calculated on the static patient models and for the accumulated dose, recalculated with MC on each of 8 CTs of a 4DCT set. Results In the phantom measurements, the MC dose engine showed discrepancies Conclusions It is feasible to employ the MC dose engine for optimization of lung IMSRT and the plans are superior to fsPB. Use of static patient models introduces a bias in the MC dose distribution compared to the 4D MC recalculated dose, but this bias is predictable and therefore MC based optimization on static patient models is considered safe.
A new method for RGB to CIELAB color space transformation based on Markov chain Monte Carlo
Chen, Yajun; Liu, Ding; Liang, Junli
2013-10-01
During printing quality inspection, the inspection of color error is an important content. However, the RGB color space is device-dependent, usually RGB color captured from CCD camera must be transformed into CIELAB color space, which is perceptually uniform and device-independent. To cope with the problem, a Markov chain Monte Carlo (MCMC) based algorithms for the RGB to the CIELAB color space transformation is proposed in this paper. Firstly, the modeling color targets and testing color targets is established, respectively used in modeling and performance testing process. Secondly, we derive a Bayesian model for estimation the coefficients of a polynomial, which can be used to describe the relation between RGB and CIELAB color space. Thirdly, a Markov chain is set up base on Gibbs sampling algorithm (one of the MCMC algorithm) to estimate the coefficients of polynomial. Finally, the color difference of testing color targets is computed for evaluating the performance of the proposed method. The experimental results showed that the nonlinear polynomial regression based on MCMC algorithm is effective, whose performance is similar to the least square approach and can accurately model the RGB to the CIELAB color space conversion and guarantee the color error evaluation for printing quality inspection system.
Fast CPU-based Monte Carlo simulation for radiotherapy dose calculation
Ziegenhein, Peter; Pirner, Sven; Kamerling, Cornelis Ph; Oelfke, Uwe
2015-08-01
Monte-Carlo (MC) simulations are considered to be the most accurate method for calculating dose distributions in radiotherapy. Its clinical application, however, still is limited by the long runtimes conventional implementations of MC algorithms require to deliver sufficiently accurate results on high resolution imaging data. In order to overcome this obstacle we developed the software-package PhiMC, which is capable of computing precise dose distributions in a sub-minute time-frame by leveraging the potential of modern many- and multi-core CPU-based computers. PhiMC is based on the well verified dose planning method (DPM). We could demonstrate that PhiMC delivers dose distributions which are in excellent agreement to DPM. The multi-core implementation of PhiMC scales well between different computer architectures and achieves a speed-up of up to 37× compared to the original DPM code executed on a modern system. Furthermore, we could show that our CPU-based implementation on a modern workstation is between 1.25× and 1.95× faster than a well-known GPU implementation of the same simulation method on a NVIDIA Tesla C2050. Since CPUs work on several hundreds of GB RAM the typical GPU memory limitation does not apply for our implementation and high resolution clinical plans can be calculated.
Ultrafast cone-beam CT scatter correction with GPU-based Monte Carlo simulation
Yuan Xu
2014-03-01
Full Text Available Purpose: Scatter artifacts severely degrade image quality of cone-beam CT (CBCT. We present an ultrafast scatter correction framework by using GPU-based Monte Carlo (MC simulation and prior patient CT image, aiming at automatically finish the whole process including both scatter correction and reconstruction within 30 seconds.Methods: The method consists of six steps: 1 FDK reconstruction using raw projection data; 2 Rigid Registration of planning CT to the FDK results; 3 MC scatter calculation at sparse view angles using the planning CT; 4 Interpolation of the calculated scatter signals to other angles; 5 Removal of scatter from the raw projections; 6 FDK reconstruction using the scatter-corrected projections. In addition to using GPU to accelerate MC photon simulations, we also use a small number of photons and a down-sampled CT image in simulation to further reduce computation time. A novel denoising algorithm is used to eliminate MC noise from the simulated scatter images caused by low photon numbers. The method is validated on one simulated head-and-neck case with 364 projection angles.Results: We have examined variation of the scatter signal among projection angles using Fourier analysis. It is found that scatter images at 31 angles are sufficient to restore those at all angles with < 0.1% error. For the simulated patient case with a resolution of 512 × 512 × 100, we simulated 5 × 106 photons per angle. The total computation time is 20.52 seconds on a Nvidia GTX Titan GPU, and the time at each step is 2.53, 0.64, 14.78, 0.13, 0.19, and 2.25 seconds, respectively. The scatter-induced shading/cupping artifacts are substantially reduced, and the average HU error of a region-of-interest is reduced from 75.9 to 19.0 HU.Conclusion: A practical ultrafast MC-based CBCT scatter correction scheme is developed. It accomplished the whole procedure of scatter correction and reconstruction within 30 seconds.----------------------------Cite this
As The Monte Carlo (MC) particle transport analysis for a complex system such as research reactor, accelerator, and fusion facility may require accurate modeling of the complicated geometry. Its manual modeling by using the text interface of a MC code to define the geometrical objects is tedious, lengthy and error-prone. This problem can be overcome by taking advantage of modeling capability of the computer aided design (CAD) system. There have been two kinds of approaches to develop MC code systems utilizing the CAD data: the external format conversion and the CAD kernel imbedded MC simulation. The first approach includes several interfacing programs such as McCAD, MCAM, GEOMIT etc. which were developed to automatically convert the CAD data into the MCNP geometry input data. This approach makes the most of the existing MC codes without any modifications, but implies latent data inconsistency due to the difference of the geometry modeling system. In the second approach, a MC code utilizes the CAD data for the direct particle tracking or the conversion to an internal data structure of the constructive solid geometry (CSG) and/or boundary representation (B-rep) modeling with help of a CAD kernel. MCNP-BRL and OiNC have demonstrated their capabilities of the CAD-based MC simulations. Recently we have developed a CAD-based geometry processing module for the MC particle simulation by using the OpenCASCADE (OCC) library. In the developed module, CAD data can be used for the particle tracking through primitive CAD surfaces (hereafter the CAD-based tracking) or the internal conversion to the CSG data structure. In this paper, the performances of the text-based model, the CAD-based tracking, and the internal CSG conversion are compared by using an in-house MC code, McSIM, equipped with the developed CAD-based geometry processing module
Baba, Justin S [ORNL; John, Dwayne O [ORNL; Koju, Vijay [ORNL
2015-01-01
The propagation of light in turbid media is an active area of research with relevance to numerous investigational fields, e.g., biomedical diagnostics and therapeutics. The statistical random-walk nature of photon propagation through turbid media is ideal for computational based modeling and simulation. Ready access to super computing resources provide a means for attaining brute force solutions to stochastic light-matter interactions entailing scattering by facilitating timely propagation of sufficient (>10million) photons while tracking characteristic parameters based on the incorporated physics of the problem. One such model that works well for isotropic but fails for anisotropic scatter, which is the case for many biomedical sample scattering problems, is the diffusion approximation. In this report, we address this by utilizing Berry phase (BP) evolution as a means for capturing anisotropic scattering characteristics of samples in the preceding depth where the diffusion approximation fails. We extend the polarization sensitive Monte Carlo method of Ramella-Roman, et al.,1 to include the computationally intensive tracking of photon trajectory in addition to polarization state at every scattering event. To speed-up the computations, which entail the appropriate rotations of reference frames, the code was parallelized using OpenMP. The results presented reveal that BP is strongly correlated to the photon penetration depth, thus potentiating the possibility of polarimetric depth resolved characterization of highly scattering samples, e.g., biological tissues.
A new Monte Carlo mesh tally based on a Kernel Density Estimator (KDE) approach using integrated particle tracks is presented. We first derive the KDE integral-track estimator and present a brief overview of its implementation as an alternative to the MCNP fmesh tally. To facilitate a valid quantitative comparison between these two tallies for verification purposes, there are two key issues that must be addressed. The first of these issues involves selecting a good data transfer method to convert the nodal-based KDE results into their cell-averaged equivalents (or vice versa with the cell-averaged MCNP results). The second involves choosing an appropriate resolution of the mesh, since if it is too coarse this can introduce significant errors into the reference MCNP solution. After discussing both of these issues in some detail, we present the results of a convergence analysis that shows the KDE integral-track and MCNP fmesh tallies are indeed capable of producing equivalent results for some simple 3D transport problems. In all cases considered, there was clear convergence from the KDE results to the reference MCNP results as the number of particle histories was increased. (authors)
The development of GPU-based parallel PRNG for Monte Carlo applications in CUDA Fortran
Hamed Kargaran
2016-04-01
Full Text Available The implementation of Monte Carlo simulation on the CUDA Fortran requires a fast random number generation with good statistical properties on GPU. In this study, a GPU-based parallel pseudo random number generator (GPPRNG have been proposed to use in high performance computing systems. According to the type of GPU memory usage, GPU scheme is divided into two work modes including GLOBAL_MODE and SHARED_MODE. To generate parallel random numbers based on the independent sequence method, the combination of middle-square method and chaotic map along with the Xorshift PRNG have been employed. Implementation of our developed PPRNG on a single GPU showed a speedup of 150x and 470x (with respect to the speed of PRNG on a single CPU core for GLOBAL_MODE and SHARED_MODE, respectively. To evaluate the accuracy of our developed GPPRNG, its performance was compared to that of some other commercially available PPRNGs such as MATLAB, FORTRAN and Miller-Park algorithm through employing the specific standard tests. The results of this comparison showed that the developed GPPRNG in this study can be used as a fast and accurate tool for computational science applications.
The development of GPU-based parallel PRNG for Monte Carlo applications in CUDA Fortran
Kargaran, Hamed; Minuchehr, Abdolhamid; Zolfaghari, Ahmad
2016-04-01
The implementation of Monte Carlo simulation on the CUDA Fortran requires a fast random number generation with good statistical properties on GPU. In this study, a GPU-based parallel pseudo random number generator (GPPRNG) have been proposed to use in high performance computing systems. According to the type of GPU memory usage, GPU scheme is divided into two work modes including GLOBAL_MODE and SHARED_MODE. To generate parallel random numbers based on the independent sequence method, the combination of middle-square method and chaotic map along with the Xorshift PRNG have been employed. Implementation of our developed PPRNG on a single GPU showed a speedup of 150x and 470x (with respect to the speed of PRNG on a single CPU core) for GLOBAL_MODE and SHARED_MODE, respectively. To evaluate the accuracy of our developed GPPRNG, its performance was compared to that of some other commercially available PPRNGs such as MATLAB, FORTRAN and Miller-Park algorithm through employing the specific standard tests. The results of this comparison showed that the developed GPPRNG in this study can be used as a fast and accurate tool for computational science applications.
Development of an unstructured mesh based geometry model in the Serpent 2 Monte Carlo code
This paper presents a new unstructured mesh based geometry type, developed in the Serpent 2 Monte Carlo code as a by-product of another study related to multi-physics applications and coupling to CFD codes. The new geometry type is intended for the modeling of complicated and irregular objects, which are not easily constructed using the conventional CSG based approach. The capability is put to test by modeling the 'Stanford Critical Bunny' – a variation of a well-known 3D test case for methods used in the world of computer graphics. The results show that the geometry routine in Serpent 2 can handle the unstructured mesh, and that the use of delta-tracking results in a considerable reduction in the overall calculation time as the geometry is refined. The methodology is still very much under development, with the final goal of implementing a geometry routine capable of reading standardized geometry formats used by 3D design and imaging tools in industry and medical physics. (author)
TH-E-BRE-08: GPU-Monte Carlo Based Fast IMRT Plan Optimization
Li, Y; Tian, Z; Shi, F; Jiang, S; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)
2014-06-15
Purpose: Intensity-modulated radiation treatment (IMRT) plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC) methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow. Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, rough beamlet dose calculations is conducted with only a small number of particles per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final Result. Results: For a lung case with 5317 beamlets, 10{sup 5} particles per beamlet in the first round, and 10{sup 8} particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec. Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.
Monte-Carlo Simulation for PDC-Based Optical CDMA System
FAHIM AZIZ UMRANI; AHSAN AHMED URSANI; ABDUL WAHEED UMRANI
2010-01-01
This paper presents the Monte-Carlo simulation of Optical CDMA (Code Division Multiple Access) systems, and analyse its performance in terms of the BER (Bit Error Rate). The spreading sequence chosen for CDMA is Perfect Difference Codes. Furthermore, this paper derives the expressions of noise variances from first principles to calibrate the noise for both bipolar (electrical domain) and unipolar (optical domain) signalling required for Monte-Carlo simulation. The simulated res...
A GPU-based Monte Carlo dose calculation code for photon transport in a voxel phantom
Bellezzo, M.; Do Nascimento, E.; Yoriyaz, H., E-mail: mbellezzo@gmail.br [Instituto de Pesquisas Energeticas e Nucleares / CNEN, Av. Lineu Prestes 2242, Cidade Universitaria, 05508-000 Sao Paulo (Brazil)
2014-08-15
As the most accurate method to estimate absorbed dose in radiotherapy, Monte Carlo method has been widely used in radiotherapy treatment planning. Nevertheless, its efficiency can be improved for clinical routine applications. In this paper, we present the CUBMC code, a GPU-based Mc photon transport algorithm for dose calculation under the Compute Unified Device Architecture platform. The simulation of physical events is based on the algorithm used in Penelope, and the cross section table used is the one generated by the Material routine, als present in Penelope code. Photons are transported in voxel-based geometries with different compositions. To demonstrate the capabilities of the algorithm developed in the present work four 128 x 128 x 128 voxel phantoms have been considered. One of them is composed by a homogeneous water-based media, the second is composed by bone, the third is composed by lung and the fourth is composed by a heterogeneous bone and vacuum geometry. Simulations were done considering a 6 MeV monoenergetic photon point source. There are two distinct approaches that were used for transport simulation. The first of them forces the photon to stop at every voxel frontier, the second one is the Woodcock method, where the photon stop in the frontier will be considered depending on the material changing across the photon travel line. Dose calculations using these methods are compared for validation with Penelope and MCNP5 codes. Speed-up factors are compared using a NVidia GTX 560-Ti GPU card against a 2.27 GHz Intel Xeon CPU processor. (Author)
A GPU-based Monte Carlo dose calculation code for photon transport in a voxel phantom
As the most accurate method to estimate absorbed dose in radiotherapy, Monte Carlo method has been widely used in radiotherapy treatment planning. Nevertheless, its efficiency can be improved for clinical routine applications. In this paper, we present the CUBMC code, a GPU-based Mc photon transport algorithm for dose calculation under the Compute Unified Device Architecture platform. The simulation of physical events is based on the algorithm used in Penelope, and the cross section table used is the one generated by the Material routine, als present in Penelope code. Photons are transported in voxel-based geometries with different compositions. To demonstrate the capabilities of the algorithm developed in the present work four 128 x 128 x 128 voxel phantoms have been considered. One of them is composed by a homogeneous water-based media, the second is composed by bone, the third is composed by lung and the fourth is composed by a heterogeneous bone and vacuum geometry. Simulations were done considering a 6 MeV monoenergetic photon point source. There are two distinct approaches that were used for transport simulation. The first of them forces the photon to stop at every voxel frontier, the second one is the Woodcock method, where the photon stop in the frontier will be considered depending on the material changing across the photon travel line. Dose calculations using these methods are compared for validation with Penelope and MCNP5 codes. Speed-up factors are compared using a NVidia GTX 560-Ti GPU card against a 2.27 GHz Intel Xeon CPU processor. (Author)
Eutrophication of mangroves linked to depletion of foliar and soil base cations
Fauzi, A.; Skidmore, A.K.; Heitkonig, I.M.A.; Gils, van H.; Schlerf, M.
2014-01-01
There is growing concern that increasing eutrophication causes degradation of coastal ecosystems. Studies in terrestrial ecosystems have shown that increasing the concentration of nitrogen in soils contributes to the acidification process, which leads to leaching of base cations. To test the effects
This study aims to utilize a measurement-based Monte Carlo (MBMC) method to evaluate the accuracy of dose distributions calculated using the Eclipse radiotherapy treatment planning system (TPS) based on the anisotropic analytical algorithm. Dose distributions were calculated for the nasopharyngeal carcinoma (NPC) patients treated with the intensity modulated radiotherapy (IMRT). Ten NPC IMRT plans were evaluated by comparing their dose distributions with those obtained from the in-house MBMC programs for the same CT images and beam geometry. To reconstruct the fluence distribution of the IMRT field, an efficiency map was obtained by dividing the energy fluence of the intensity modulated field by that of the open field, both acquired from an aS1000 electronic portal imaging device. The integrated image of the non-gated mode was used to acquire the full dose distribution delivered during the IMRT treatment. This efficiency map redistributed the particle weightings of the open field phase-space file for IMRT applications. Dose differences were observed in the tumor and air cavity boundary. The mean difference between MBMC and TPS in terms of the planning target volume coverage was 0.6% (range: 0.0–2.3%). The mean difference for the conformity index was 0.01 (range: 0.0–0.01). In conclusion, the MBMC method serves as an independent IMRT dose verification tool in a clinical setting. - Highlights: ► The patient-based Monte Carlo method serves as a reference standard to verify IMRT doses. ► 3D Dose distributions for NPC patients have been verified by the Monte Carlo method. ► Doses predicted by the Monte Carlo method matched closely with those by the TPS. ► The Monte Carlo method predicted a higher mean dose to the middle ears than the TPS. ► Critical organ doses should be confirmed to avoid overdose to normal organs
A Monte Carlo-based knee phantom for in vivo measurements of 241Am in bone
Determination of internal contamination of 241Am can be done by direct counting of gamma emission using a Whole Body Counter. Due to the strong attenuation of the low-energy photons, it is advised to perform the measurement on bones surrounded by a thin layer of tissue. In vivo measurements are performed at CIEMAT using a system of four Low-Energy germanium (LE Ge) detectors calibrated with realistic anthropomorphic phantoms. As an alternative, Monte Carlo techniques are applied on voxel phantoms based on tomographic images to avoid the need of different physical phantoms for different radionuclides and organs. This technique is employed to study the convenience of americium measurements in the knee for the evaluation of the deposition in the whole skeleton. The spatial distribution of the photon fluence through a cylinder along the axis of the leg has been calculated to determine the best counting geometry. The detection efficiency is then calculated and the results are compared with those obtained using the physical phantom to validate the proposed method
Monte Carlo based time-domain Hspice noise simulation for CSA-CRRC circuit
We present a time-domain Monte Carlo based Hspice noise simulation for a charge-sensitive preamplifier-CRRC (CSA-CRRC) circuit with random amplitude piecewise noise waveform. The amplitude distribution of thermal noise is modeled with Gaussian random number. For 1/f noise, its amplitude distribution is modeled with several low-pass filters with thermal noise generators. These time-domain noise sources are connected in parallel with the drain and source nodes of the CMOS input transistor of CSA. The Hspice simulation of the CSA-CRRC circuit with these noise sources yielded ENC values at the output node of the shaper for thermal and 1/f noise of 47e- and 732e-, respectively. ENC values calculated from the frequency-domain transfer function and its integration are 44e- and 882e-, respectively. The values for Hspice simulation are similar to those for frequency-domain calculation. A test chip was designed and fabricated for this study. The measured ENC value was 904 e-. This study shows that the time-domain noise modeling is valid and the transient Hspice noise simulation can be an effective tool for low-noise circuit design
Monte Carlo simulation of novel breast imaging modalities based on coherent x-ray scattering
We present upgraded versions of MC-GPU and penEasyImaging, two open-source Monte Carlo codes for the simulation of radiographic projections and CT, that have been extended and validated to account for the effect of molecular interference in the coherent x-ray scatter. The codes were first validation by comparison between simulated and measured energy dispersive x-ray diffraction (EDXRD) spectra. A second validation was by evaluation of the rejection factor of a focused anti-scatter grid. To exemplify the capabilities of the new codes, the modified MC-GPU code was used to examine the possibility of characterizing breast tissue composition and microcalcifications in a volume of interest inside a whole breast phantom using EDXRD and to simulate a coherent scatter computed tomography (CSCT) system based on first generation CT acquisition geometry. It was confirmed that EDXRD and CSCT have the potential to characterize tissue composition inside a whole breast. The GPU-accelerated code was able to simulate, in just a few hours, a complete CSCT acquisition composed of 9758 independent pencil-beam projections. In summary, it has been shown that the presented software can be used for fast and accurate simulation of novel breast imaging modalities relying on scattering measurements and therefore can assist in the characterization and optimization of promising modalities currently under development. (paper)
Adjoint-based deviational Monte Carlo methods for phonon transport calculations
Péraud, Jean-Philippe M.; Hadjiconstantinou, Nicolas G.
2015-06-01
In the field of linear transport, adjoint formulations exploit linearity to derive powerful reciprocity relations between a variety of quantities of interest. In this paper, we develop an adjoint formulation of the linearized Boltzmann transport equation for phonon transport. We use this formulation for accelerating deviational Monte Carlo simulations of complex, multiscale problems. Benefits include significant computational savings via direct variance reduction, or by enabling formulations which allow more efficient use of computational resources, such as formulations which provide high resolution in a particular phase-space dimension (e.g., spectral). We show that the proposed adjoint-based methods are particularly well suited to problems involving a wide range of length scales (e.g., nanometers to hundreds of microns) and lead to computational methods that can calculate quantities of interest with a cost that is independent of the system characteristic length scale, thus removing the traditional stiffness of kinetic descriptions. Applications to problems of current interest, such as simulation of transient thermoreflectance experiments or spectrally resolved calculation of the effective thermal conductivity of nanostructured materials, are presented and discussed in detail.
IVF cycle cost estimation using Activity Based Costing and Monte Carlo simulation.
Cassettari, Lucia; Mosca, Marco; Mosca, Roberto; Rolando, Fabio; Costa, Mauro; Pisaturo, Valerio
2016-03-01
The Authors present a new methodological approach in stochastic regime to determine the actual costs of an healthcare process. The paper specifically shows the application of the methodology for the determination of the cost of an Assisted reproductive technology (ART) treatment in Italy. The reason of this research comes from the fact that deterministic regime is inadequate to implement an accurate estimate of the cost of this particular treatment. In fact the durations of the different activities involved are unfixed and described by means of frequency distributions. Hence the need to determine in addition to the mean value of the cost, the interval within which it is intended to vary with a known confidence level. Consequently the cost obtained for each type of cycle investigated (in vitro fertilization and embryo transfer with or without intracytoplasmic sperm injection), shows tolerance intervals around the mean value sufficiently restricted as to make the data obtained statistically robust and therefore usable also as reference for any benchmark with other Countries. It should be noted that under a methodological point of view the approach was rigorous. In fact it was used both the technique of Activity Based Costing for determining the cost of individual activities of the process both the Monte Carlo simulation, with control of experimental error, for the construction of the tolerance intervals on the final result. PMID:24752546
A global reaction route mapping-based kinetic Monte Carlo algorithm
Mitchell, Izaac; Irle, Stephan; Page, Alister J.
2016-07-01
We propose a new on-the-fly kinetic Monte Carlo (KMC) method that is based on exhaustive potential energy surface searching carried out with the global reaction route mapping (GRRM) algorithm. Starting from any given equilibrium state, this GRRM-KMC algorithm performs a one-step GRRM search to identify all surrounding transition states. Intrinsic reaction coordinate pathways are then calculated to identify potential subsequent equilibrium states. Harmonic transition state theory is used to calculate rate constants for all potential pathways, before a standard KMC accept/reject selection is performed. The selected pathway is then used to propagate the system forward in time, which is calculated on the basis of 1st order kinetics. The GRRM-KMC algorithm is validated here in two challenging contexts: intramolecular proton transfer in malonaldehyde and surface carbon diffusion on an iron nanoparticle. We demonstrate that in both cases the GRRM-KMC method is capable of reproducing the 1st order kinetics observed during independent quantum chemical molecular dynamics simulations using the density-functional tight-binding potential.
Monte Carlo efficiency calibration of a neutron generator-based total-body irradiator
Many body composition measurement systems are calibrated against a single-sized reference phantom. Prompt-gamma neutron activation (PGNA) provides the only direct measure of total body nitrogen (TBN), an index of the body's lean tissue mass. In PGNA systems, body size influences neutron flux attenuation, induced gamma signal distribution, and counting efficiency. Thus, calibration based on a single-sized phantom could result in inaccurate TBN values. We used Monte Carlo simulations (MCNP-5; Los Alamos National Laboratory) in order to map a system's response to the range of body weights (65-160 kg) and body fat distributions (25-60%) in obese humans. Calibration curves were constructed to derive body-size correction factors relative to a standard reference phantom, providing customized adjustments to account for differences in body habitus of obese adults. The use of MCNP-generated calibration curves should allow for a better estimate of the true changes in lean tissue mass that many occur during intervention programs focused only on weight loss. (author)
Monte Carlo vs. Pencil Beam based optimization of stereotactic lung IMRT
The purpose of the present study is to compare finite size pencil beam (fsPB) and Monte Carlo (MC) based optimization of lung intensity-modulated stereotactic radiotherapy (lung IMSRT). A fsPB and a MC algorithm as implemented in a biological IMRT planning system were validated by film measurements in a static lung phantom. Then, they were applied for static lung IMSRT planning based on three different geometrical patient models (one phase static CT, density overwrite one phase static CT, average CT) of the same patient. Both 6 and 15 MV beam energies were used. The resulting treatment plans were compared by how well they fulfilled the prescribed optimization constraints both for the dose distributions calculated on the static patient models and for the accumulated dose, recalculated with MC on each of 8 CTs of a 4DCT set. In the phantom measurements, the MC dose engine showed discrepancies < 2%, while the fsPB dose engine showed discrepancies of up to 8% in the presence of lateral electron disequilibrium in the target. In the patient plan optimization, this translates into violations of organ at risk constraints and unpredictable target doses for the fsPB optimized plans. For the 4D MC recalculated dose distribution, MC optimized plans always underestimate the target doses, but the organ at risk doses were comparable. The results depend on the static patient model, and the smallest discrepancy was found for the MC optimized plan on the density overwrite one phase static CT model. It is feasible to employ the MC dose engine for optimization of lung IMSRT and the plans are superior to fsPB. Use of static patient models introduces a bias in the MC dose distribution compared to the 4D MC recalculated dose, but this bias is predictable and therefore MC based optimization on static patient models is considered safe
Chi, Yujie; Tian, Zhen; Jia, Xun
2016-08-01
Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU's shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was ~3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75-2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0
Chi, Yujie; Tian, Zhen; Jia, Xun
2016-08-01
Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU’s shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was ~3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75–2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0
Unfolding an under-determined neutron spectrum using genetic algorithm based Monte Carlo
Spallation in addition to the other photon-neutron reactions in target materials and different components in accelerators may result in production of huge amount of energetic protons which further leads to the production of neutron and contributes to the main component of the total dose. For dosimetric purposes in accelerator facilities the detector measurements doesn't provide directly the actual neutron flux values but a cumulative picture. To obtain Neutron spectrum from the measured data, response functions of the measuring instrument together with the measurements are used into many unfolding techniques which are frequently used for unfolding the hidden spectral information. Here we discuss a genetic algorithm based unfolding technique which is in the process of development. Genetic Algorithm is a stochastic method based on natural selection, which mimics Darwinian theory of survival of the best. The above said method has been tested to unfold the neutron spectra obtained from a reaction carried out at an accelerator facility, with energetic carbon ions on thick silver target along with its respective neutron response of BC501A liquid scintillation detector. The problem dealt here is under-determined where the number of measurements is less than the required energy bin information. The results so obtained were compared with those obtained using the established unfolding code FERDOR, which unfolds data for completely determined problems. It is seen that the genetic algorithm based solution has a reasonable match with the results of FERDOR, when smoothening carried out by Monte Carlo is taken into consideration. This method appears to be a promising candidate for unfolding neutron spectrum in cases of under-determined and over-determined, where measurements are more. The method also has advantages of flexibility, computational simplicity and works well without need of any initial guess spectrum. (author)
Sihler, Holger [Institute of Environmental Physics, University of Heidelberg (Germany); Max-Planck-Institute for Chemistry, Mainz (Germany); Friess, Udo; Platt, Ulrich [Institute of Environmental Physics, University of Heidelberg (Germany); Wagner, Thomas [Max-Planck-Institute for Chemistry, Mainz (Germany)
2010-07-01
Bromine monoxide (BrO) radicals are known to play an important role in the chemistry of the springtime polar troposphere. Their release by halogen activation processes leads to the almost complete destruction of near-surface ozone during ozone depletion events ODEs. In order to improve our understanding of the halogen activation processes in three dimensions, we combine active and passive ground-based and satellite-borne measurements of BrO radicals. While satellites can not resolve the vertical distribution and have rather coarse horizontal resolution, they may provide information on the large-scale horizontal distribution. Information on the spatial variability within a satellite pixel may be derived from our combined ground-based instrumentation. Simultaneous passive multi-axis differential optical absorption spectroscopy (MAX-DOAS) and active long-path DOAS (LP-DOAS) measurements were conducted during the jointly organised OASIS campaign in Barrow, Alaska during Spring 2009 within the scope of the International Polar Year (IPY). Ground-based measurements are compared to BrO column densities measured by GOME-2 in order to find a conclusive picture of the spatial pattern of bromine activation.
Dosimetric studies are necessary for all patients treated with targeted radiotherapy. In order to attain the precision required, we have developed Oedipe, a dosimetric tool based on the MCNPX Monte Carlo code. The anatomy of each patient is considered in the form of a voxel-based geometry created using computed tomography (CT) images or magnetic resonance imaging (MRI). Oedipe enables dosimetry studies to be carried out at the voxel scale. Validation of the results obtained by comparison with existing methods is complex because there are multiple sources of variation: calculation methods (different Monte Carlo codes, point kernel), patient representations (model or specific) and geometry definitions (mathematical or voxel-based). In this paper, we validate Oedipe by taking each of these parameters into account independently. Monte Carlo methodology requires long calculation times, particularly in the case of voxel-based geometries, and this is one of the limits of personalized dosimetric methods. However, our results show that the use of voxel-based geometry as opposed to a mathematically defined geometry decreases the calculation time two-fold, due to an optimization of the MCNPX2.5e code. It is therefore possible to envisage the use of Oedipe for personalized dosimetry in the clinical context of targeted radiotherapy
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
A study of potential numerical pitfalls in GPU-based Monte Carlo dose calculation
Magnoux, Vincent; Ozell, Benoît; Bonenfant, Éric; Després, Philippe
2015-07-01
The purpose of this study was to evaluate the impact of numerical errors caused by the floating point representation of real numbers in a GPU-based Monte Carlo code used for dose calculation in radiation oncology, and to identify situations where this type of error arises. The program used as a benchmark was bGPUMCD. Three tests were performed on the code, which was divided into three functional components: energy accumulation, particle tracking and physical interactions. First, the impact of single-precision calculations was assessed for each functional component. Second, a GPU-specific compilation option that reduces execution time as well as precision was examined. Third, a specific function used for tracking and potentially more sensitive to precision errors was tested by comparing it to a very high-precision implementation. Numerical errors were found in two components of the program. Because of the energy accumulation process, a few voxels surrounding a radiation source end up with a lower computed dose than they should. The tracking system contained a series of operations that abnormally amplify rounding errors in some situations. This resulted in some rare instances (less than 0.1%) of computed distances that are exceedingly far from what they should have been. Most errors detected had no significant effects on the result of a simulation due to its random nature, either because they cancel each other out or because they only affect a small fraction of particles. The results of this work can be extended to other types of GPU-based programs and be used as guidelines to avoid numerical errors on the GPU computing platform.
A voxel-based mouse for internal dose calculations using Monte Carlo simulations (MCNP)
Murine models are useful for targeted radiotherapy pre-clinical experiments. These models can help to assess the potential interest of new radiopharmaceuticals. In this study, we developed a voxel-based mouse for dosimetric estimates. A female nude mouse (30 g) was frozen and cut into slices. High-resolution digital photographs were taken directly on the frozen block after each section. Images were segmented manually. Monoenergetic photon or electron sources were simulated using the MCNP4c2 Monte Carlo code for each source organ, in order to give tables of S-factors (in Gy Bq sup - sup 1 s sup - sup 1) for all target organs. Results obtained from monoenergetic particles were then used to generate S-factors for several radionuclides of potential interest in targeted radiotherapy. Thirteen source and 25 target regions were considered in this study. For each source region, 16 photon and 16 electron energies were simulated. Absorbed fractions, specific absorbed fractions and S-factors were calculated for 16 radionuclides of interest for targeted radiotherapy. The results obtained generally agree well with data published previously. For electron energies ranging from 0.1 to 2.5 MeV, the self-absorbed fraction varies from 0.98 to 0.376 for the liver, and from 0.89 to 0.04 for the thyroid. Electrons cannot be considered as 'non-penetrating' radiation for energies above 0.5 MeV for mouse organs. This observation can be generalized to radionuclides: for example, the beta self-absorbed fraction for the thyroid was 0.616 for I-131; absorbed fractions for Y-90 for left kidney-to-left kidney and for left kidney-to-spleen were 0.486 and 0.058, respectively. Our voxel-based mouse allowed us to generate a dosimetric database for use in preclinical targeted radiotherapy experiments. (author)
A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system
Purpose: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. Methods: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. Results: For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm3 and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. Conclusions: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45 000
Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun
2015-04-01
Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 106 particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 105 particles per beamlet. Correspondingly, the computation time
A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system
Ma, Jiasen, E-mail: ma.jiasen@mayo.edu; Beltran, Chris; Seum Wan Chan Tseung, Hok; Herman, Michael G. [Department of Radiation Oncology, Division of Medical Physics, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States)
2014-12-15
Purpose: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. Methods: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. Results: For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm{sup 3} and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. Conclusions: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45
Monte-Carlo Simulation for PDC-Based Optical CDMA System
FAHIM AZIZ UMRANI
2010-10-01
Full Text Available This paper presents the Monte-Carlo simulation of Optical CDMA (Code Division Multiple Access systems, and analyse its performance in terms of the BER (Bit Error Rate. The spreading sequence chosen for CDMA is Perfect Difference Codes. Furthermore, this paper derives the expressions of noise variances from first principles to calibrate the noise for both bipolar (electrical domain and unipolar (optical domain signalling required for Monte-Carlo simulation. The simulated results conform to the theory and show that the receiver gain mismatch and splitter loss at the transceiver degrades the system performance.
GPU-based fast Monte Carlo dose calculation for proton therapy
Jia, Xun; Schümann, Jan; Paganetti, Harald; Jiang, Steve B.
2012-12-01
Accurate radiation dose calculation is essential for successful proton radiotherapy. Monte Carlo (MC) simulation is considered to be the most accurate method. However, the long computation time limits it from routine clinical applications. Recently, graphics processing units (GPUs) have been widely used to accelerate computationally intensive tasks in radiotherapy. We have developed a fast MC dose calculation package, gPMC, for proton dose calculation on a GPU. In gPMC, proton transport is modeled by the class II condensed history simulation scheme with a continuous slowing down approximation. Ionization, elastic and inelastic proton nucleus interactions are considered. Energy straggling and multiple scattering are modeled. Secondary electrons are not transported and their energies are locally deposited. After an inelastic nuclear interaction event, a variety of products are generated using an empirical model. Among them, charged nuclear fragments are terminated with energy locally deposited. Secondary protons are stored in a stack and transported after finishing transport of the primary protons, while secondary neutral particles are neglected. gPMC is implemented on the GPU under the CUDA platform. We have validated gPMC using the TOPAS/Geant4 MC code as the gold standard. For various cases including homogeneous and inhomogeneous phantoms as well as a patient case, good agreements between gPMC and TOPAS/Geant4 are observed. The gamma passing rate for the 2%/2 mm criterion is over 98.7% in the region with dose greater than 10% maximum dose in all cases, excluding low-density air regions. With gPMC it takes only 6-22 s to simulate 10 million source protons to achieve ˜1% relative statistical uncertainty, depending on the phantoms and energy. This is an extremely high efficiency compared to the computational time of tens of CPU hours for TOPAS/Geant4. Our fast GPU-based code can thus facilitate the routine use of MC dose calculation in proton therapy.
Test Population Selection from Weibull-Based, Monte Carlo Simulations of Fatigue Life
Vlcek, Brian L.; Zaretsky, Erwin V.; Hendricks, Robert C.
2012-01-01
Fatigue life is probabilistic and not deterministic. Experimentally establishing the fatigue life of materials, components, and systems is both time consuming and costly. As a result, conclusions regarding fatigue life are often inferred from a statistically insufficient number of physical tests. A proposed methodology for comparing life results as a function of variability due to Weibull parameters, variability between successive trials, and variability due to size of the experimental population is presented. Using Monte Carlo simulation of randomly selected lives from a large Weibull distribution, the variation in the L10 fatigue life of aluminum alloy AL6061 rotating rod fatigue tests was determined as a function of population size. These results were compared to the L10 fatigue lives of small (10 each) populations from AL2024, AL7075 and AL6061. For aluminum alloy AL6061, a simple algebraic relationship was established for the upper and lower L10 fatigue life limits as a function of the number of specimens failed. For most engineering applications where less than 30 percent variability can be tolerated in the maximum and minimum values, at least 30 to 35 test samples are necessary. The variability of test results based on small sample sizes can be greater than actual differences, if any, that exists between materials and can result in erroneous conclusions. The fatigue life of AL2024 is statistically longer than AL6061 and AL7075. However, there is no statistical difference between the fatigue lives of AL6061 and AL7075 even though AL7075 had a fatigue life 30 percent greater than AL6061.
TH-C-17A-08: Monte Carlo Based Design of Efficient Scintillating Fiber Dosimeters
Purpose: To accurately predict Cherenkov radiation generation in scintillating fiber dosimeters. Quantifying Cherenkov radiation provides a method for optimizing fiber dimensions, orientation, optical filters, and photodiode spectral sensitivity to achieve efficient real time imaging dosimeter designs. Methods: We develop in-house Monte Carlo simulation software to model polymer scintillation fibers' fluorescence and Cherenkov emission in megavoltage clinical beams. The model computes emissions using generation probabilities, wavelength sampling, fiber photon capture, and fiber transport efficiency and incorporates the fiber's index of refraction, optical attenuation in the Cherenkov and visible spectrum and fiber dimensions. Detector component selection based on parameters such as silicon photomultiplier efficiency and optical coupling filters separates Cherenkov radiation from the dose-proportional scintillating emissions. The computation uses spectral and geometrical separation of Cherenkov radiation, however other filtering techniques can expand the model. Results: We compute Cherenkov generation per electron and fiber capture and transmission of those photons toward the detector with incident electron beam angle dependence. The model accounts for beam obliquity and nonperpendicular electron fiber impingement, which increases Cherenkov emission and trapping. The rotational angle around square fibers shows trapping efficiency variation from the normally incident minimum to a maximum at 45 degrees rotation. For rotation in the plane formed by the fiber axis and its surface normal, trapping efficiency increases with angle from the normal. The Cherenkov spectrum follows the theoretical curve from 300nm to 800nm, the wavelength range of interest defined by silicon photomultiplier and photodiode spectral efficiency. Conclusion: We are able to compute Cherenkov generation in realistic real time scintillating fiber dosimeter geometries. Design parameters
Cell death following BNCT: A theoretical approach based on Monte Carlo simulations
In parallel to boron measurements and animal studies, investigations on radiation-induced cell death are also in progress in Pavia, with the aim of better characterisation of the effects of a BNCT treatment down to the cellular level. Such studies are being carried out not only experimentally but also theoretically, based on a mechanistic model and a Monte Carlo code. Such model assumes that: (1) only clustered DNA strand breaks can lead to chromosome aberrations; (2) only chromosome fragments within a certain threshold distance can undergo misrejoining; (3) the so-called 'lethal aberrations' (dicentrics, rings and large deletions) lead to cell death. After applying the model to normal cells exposed to monochromatic fields of different radiation types, the irradiation section of the code was purposely extended to mimic the cell exposure to a mixed radiation field produced by the 10B(n,α) 7Li reaction, which gives rise to alpha particles and Li ions of short range and high biological effectiveness, and by the 14N(n,p)14C reaction, which produces 0.58 MeV protons. Very good agreement between model predictions and literature data was found for human and animal cells exposed to X- or gamma-rays, protons and alpha particles, thus allowing to validate the model for cell death induced by monochromatic radiation fields. The model predictions showed good agreement also with experimental data obtained by our group exposing DHD cells to thermal neutrons in the TRIGA Mark II reactor of University of Pavia; this allowed to validate the model also for a BNCT exposure scenario, providing a useful predictive tool to bridge the gap between irradiation and cell death.
Cell death following BNCT: A theoretical approach based on Monte Carlo simulations
Ballarini, F., E-mail: francesca.ballarini@pv.infn.it [University of Pavia, Department of Nuclear and Theoretical Physics, via Bassi 6, Pavia (Italy)] [INFN (National Institute of Nuclear Physics)-Sezione di Pavia, via Bassi 6, Pavia (Italy); Bakeine, J. [University of Pavia, Department of Nuclear and Theoretical Physics, via Bassi 6, Pavia (Italy); Bortolussi, S. [University of Pavia, Department of Nuclear and Theoretical Physics, via Bassi 6, Pavia (Italy)] [INFN (National Institute of Nuclear Physics)-Sezione di Pavia, via Bassi 6, Pavia (Italy); Bruschi, P. [University of Pavia, Department of Nuclear and Theoretical Physics, via Bassi 6, Pavia (Italy); Cansolino, L.; Clerici, A.M.; Ferrari, C. [University of Pavia, Department of Surgery, Experimental Surgery Laboratory, Pavia (Italy); Protti, N.; Stella, S. [University of Pavia, Department of Nuclear and Theoretical Physics, via Bassi 6, Pavia (Italy)] [INFN (National Institute of Nuclear Physics)-Sezione di Pavia, via Bassi 6, Pavia (Italy); Zonta, A.; Zonta, C. [University of Pavia, Department of Surgery, Experimental Surgery Laboratory, Pavia (Italy); Altieri, S. [University of Pavia, Department of Nuclear and Theoretical Physics, via Bassi 6, Pavia (Italy)] [INFN (National Institute of Nuclear Physics)-Sezione di Pavia, via Bassi 6, Pavia (Italy)
2011-12-15
In parallel to boron measurements and animal studies, investigations on radiation-induced cell death are also in progress in Pavia, with the aim of better characterisation of the effects of a BNCT treatment down to the cellular level. Such studies are being carried out not only experimentally but also theoretically, based on a mechanistic model and a Monte Carlo code. Such model assumes that: (1) only clustered DNA strand breaks can lead to chromosome aberrations; (2) only chromosome fragments within a certain threshold distance can undergo misrejoining; (3) the so-called 'lethal aberrations' (dicentrics, rings and large deletions) lead to cell death. After applying the model to normal cells exposed to monochromatic fields of different radiation types, the irradiation section of the code was purposely extended to mimic the cell exposure to a mixed radiation field produced by the {sup 10}B(n,{alpha}) {sup 7}Li reaction, which gives rise to alpha particles and Li ions of short range and high biological effectiveness, and by the {sup 14}N(n,p){sup 14}C reaction, which produces 0.58 MeV protons. Very good agreement between model predictions and literature data was found for human and animal cells exposed to X- or gamma-rays, protons and alpha particles, thus allowing to validate the model for cell death induced by monochromatic radiation fields. The model predictions showed good agreement also with experimental data obtained by our group exposing DHD cells to thermal neutrons in the TRIGA Mark II reactor of University of Pavia; this allowed to validate the model also for a BNCT exposure scenario, providing a useful predictive tool to bridge the gap between irradiation and cell death.
Cell death following BNCT: a theoretical approach based on Monte Carlo simulations.
Ballarini, F; Bakeine, J; Bortolussi, S; Bruschi, P; Cansolino, L; Clerici, A M; Ferrari, C; Protti, N; Stella, S; Zonta, A; Zonta, C; Altieri, S
2011-12-01
In parallel to boron measurements and animal studies, investigations on radiation-induced cell death are also in progress in Pavia, with the aim of better characterisation of the effects of a BNCT treatment down to the cellular level. Such studies are being carried out not only experimentally but also theoretically, based on a mechanistic model and a Monte Carlo code. Such model assumes that: (1) only clustered DNA strand breaks can lead to chromosome aberrations; (2) only chromosome fragments within a certain threshold distance can undergo misrejoining; (3) the so-called "lethal aberrations" (dicentrics, rings and large deletions) lead to cell death. After applying the model to normal cells exposed to monochromatic fields of different radiation types, the irradiation section of the code was purposely extended to mimic the cell exposure to a mixed radiation field produced by the (10)B(n,α) (7)Li reaction, which gives rise to alpha particles and Li ions of short range and high biological effectiveness, and by the (14)N(n,p)(14)C reaction, which produces 0.58 MeV protons. Very good agreement between model predictions and literature data was found for human and animal cells exposed to X- or gamma-rays, protons and alpha particles, thus allowing to validate the model for cell death induced by monochromatic radiation fields. The model predictions showed good agreement also with experimental data obtained by our group exposing DHD cells to thermal neutrons in the TRIGA Mark II reactor of the University of Pavia; this allowed to validate the model also for a BNCT exposure scenario, providing a useful predictive tool to bridge the gap between irradiation and cell death. PMID:21481595
Monte Carlo-based searching as a tool to study carbohydrate structure.
Dowd, Michael K; Kiely, Donald E; Zhang, Jinsong
2011-07-01
A torsion angle-based Monte Carlo searching routine was developed and applied to several carbohydrate modeling problems. The routine was developed as a Unix shell script that calls several programs, which allows it to be interfaced with multiple potential functions and various utilities for evaluating conformers. In its current form, the program operates with several versions of the MM3 and MM4 molecular mechanics programs and has a module to calculate hydrogen-hydrogen coupling constants. The routine was used to study the low-energy exo-cyclic substituents of β-D-glucopyranose and the conformers of D-glucaramide, both of which had been previously studied with MM3 by full conformational searches. For these molecules, the program found all previously reported low-energy structures. The routine was also used to find favorable conformers of 2,3,4,5-tetra-O-acetyl-N,N'-dimethyl-D-glucaramide and D-glucitol, the latter of which is believed to have many low-energy forms. Finally, the technique was used to study the inter-ring conformations of β-gentiobiose, a β-(1→6)-linked disaccharide of D-glucopyranose. The program easily found conformers in the 10 previously identified low-energy regions for this disaccharide. In 6 of the 10 local regions, the same previously identified low-energy structures were found. In the remaining four regions, the search identified structures with slightly lower energies than those previously reported. The approach should be useful for extending modeling studies on acyclic monosaccharides and possibly oligosaccharides. PMID:21536262
Monte-Carlo simulation of an ultra small-angle neutron scattering instrument based on Soller slits
Rieker, T. [Univ. of New Mexico, Albuquerque, NM (United States); Hubbard, P. [Sandia National Labs., Albuquerque, NM (United States)
1997-09-01
Monte Carlo simulations are used to investigate an ultra small-angle neutron scattering instrument for use at a pulsed source based on a Soller slit collimator and analyzer. The simulations show that for a q{sub min} of {approximately}le-4 {angstrom}{sup -1} (15 {angstrom} neutrons) a few tenths of a percent of the incident flux is transmitted through both collimators at q=0.
Tseung, H. Wan Chan; J. Ma; Beltran, C.
2014-01-01
Purpose: Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on GPUs. However, these usually use simplified models for non-elastic (NE) proton-nucleus interactions. Our primary goal is to build a GPU-based proton transport MC with detailed modeling of elastic and NE collisions. Methods: Using CUDA, we implemented GPU kernels for these tasks: (1) Simulation of spots from our scanning nozzle configurations, (2) Proton propagation through CT geometry, consid...
Mommen, G.P.M.; Waterbeemd, van de B.; Meiring, H.D.; Kersten, G.; Heck, A.J.R.; Jong, de A.P.J.M.
2012-01-01
A positional proteomics strategy for global N-proteome analysis is presented based on phospho tagging (PTAG) of internal peptides followed by depletion by titanium dioxide (TiO2) affinity chromatography. Therefore, N-terminal and lysine amino groups are initially completely dimethylated with formald
Monte Carlo-based multiphysics coupling analysis of x-ray pulsar telescope
Li, Liansheng; Deng, Loulou; Mei, Zhiwu; Zuo, Fuchang; Zhou, Hao
2015-10-01
X-ray pulsar telescope (XPT) is a complex optical payload, which involves optical, mechanical, electrical and thermal disciplines. The multiphysics coupling analysis (MCA) plays an important role in improving the in-orbit performance. However, the conventional MCA methods encounter two serious problems in dealing with the XTP. One is that both the energy and reflectivity information of X-ray can't be taken into consideration, which always misunderstands the essence of XPT. Another is that the coupling data can't be transferred automatically among different disciplines, leading to computational inefficiency and high design cost. Therefore, a new MCA method for XPT is proposed based on the Monte Carlo method and total reflective theory. The main idea, procedures and operational steps of the proposed method are addressed in detail. Firstly, it takes both the energy and reflectivity information of X-ray into consideration simultaneously. And formulate the thermal-structural coupling equation and multiphysics coupling analysis model based on the finite element method. Then, the thermalstructural coupling analysis under different working conditions has been implemented. Secondly, the mirror deformations are obtained using construction geometry function. Meanwhile, the polynomial function is adopted to fit the deformed mirror and meanwhile evaluate the fitting error. Thirdly, the focusing performance analysis of XPT can be evaluated by the RMS. Finally, a Wolter-I XPT is taken as an example to verify the proposed MCA method. The simulation results show that the thermal-structural coupling deformation is bigger than others, the vary law of deformation effect on the focusing performance has been obtained. The focusing performances of thermal-structural, thermal, structural deformations have degraded 30.01%, 14.35% and 7.85% respectively. The RMS of dispersion spot are 2.9143mm, 2.2038mm and 2.1311mm. As a result, the validity of the proposed method is verified through
Monte Carlo-based QA for IMRT of head and neck cancers
Tang, F.; Sham, J.; Ma, C.-M.; Li, J.-S.
2007-06-01
It is well-known that the presence of large air cavity in a dense medium (or patient) introduces significant electronic disequilibrium when irradiated with megavoltage X-ray field. This condition may worsen by the possible use of tiny beamlets in intensity-modulated radiation therapy (IMRT). Commercial treatment planning systems (TPSs), in particular those based on the pencil-beam method, do not provide accurate dose computation for the lungs and other cavity-laden body sites such as the head and neck. In this paper we present the use of Monte Carlo (MC) technique for dose re-calculation of IMRT of head and neck cancers. In our clinic, a turn-key software system is set up for MC calculation and comparison with TPS-calculated treatment plans as part of the quality assurance (QA) programme for IMRT delivery. A set of 10 off-the-self PCs is employed as the MC calculation engine with treatment plan parameters imported from the TPS via a graphical user interface (GUI) which also provides a platform for launching remote MC simulation and subsequent dose comparison with the TPS. The TPS-segmented intensity maps are used as input for the simulation hence skipping the time-consuming simulation of the multi-leaf collimator (MLC). The primary objective of this approach is to assess the accuracy of the TPS calculations in the presence of air cavities in the head and neck whereas the accuracy of leaf segmentation is verified by fluence measurement using a fluoroscopic camera-based imaging device. This measurement can also validate the correct transfer of intensity maps to the record and verify system. Comparisons between TPS and MC calculations of 6 MV IMRT for typical head and neck treatments review regional consistency in dose distribution except at and around the sinuses where our pencil-beam-based TPS sometimes over-predicts the dose by up to 10%, depending on the size of the cavities. In addition, dose re-buildup of up to 4% is observed at the posterior nasopharyngeal
Monte Carlo-based QA for IMRT of head and neck cancers
It is well-known that the presence of large air cavity in a dense medium (or patient) introduces significant electronic disequilibrium when irradiated with megavoltage X-ray field. This condition may worsen by the possible use of tiny beamlets in intensity-modulated radiation therapy (IMRT). Commercial treatment planning systems (TPSs), in particular those based on the pencil-beam method, do not provide accurate dose computation for the lungs and other cavity-laden body sites such as the head and neck. In this paper we present the use of Monte Carlo (MC) technique for dose re-calculation of IMRT of head and neck cancers. In our clinic, a turn-key software system is set up for MC calculation and comparison with TPS-calculated treatment plans as part of the quality assurance (QA) programme for IMRT delivery. A set of 10 off-the-self PCs is employed as the MC calculation engine with treatment plan parameters imported from the TPS via a graphical user interface (GUI) which also provides a platform for launching remote MC simulation and subsequent dose comparison with the TPS. The TPS-segmented intensity maps are used as input for the simulation hence skipping the time-consuming simulation of the multi-leaf collimator (MLC). The primary objective of this approach is to assess the accuracy of the TPS calculations in the presence of air cavities in the head and neck whereas the accuracy of leaf segmentation is verified by fluence measurement using a fluoroscopic camera-based imaging device. This measurement can also validate the correct transfer of intensity maps to the record and verify system. Comparisons between TPS and MC calculations of 6 MV IMRT for typical head and neck treatments review regional consistency in dose distribution except at and around the sinuses where our pencil-beam-based TPS sometimes over-predicts the dose by up to 10%, depending on the size of the cavities. In addition, dose re-buildup of up to 4% is observed at the posterior nasopharyngeal
Ding, George X.; Duggan, Dennis M.; Coffey, Charles W.; Shokrani, Parvaneh; Cygler, Joanna E.
2006-06-01
The purpose of this study is to present our experience of commissioning, testing and use of the first commercial macro Monte Carlo based dose calculation algorithm for electron beam treatment planning and to investigate new issues regarding dose reporting (dose-to-water versus dose-to-medium) as well as statistical uncertainties for the calculations arising when Monte Carlo based systems are used in patient dose calculations. All phantoms studied were obtained by CT scan. The calculated dose distributions and monitor units were validated against measurements with film and ionization chambers in phantoms containing two-dimensional (2D) and three-dimensional (3D) type low- and high-density inhomogeneities at different source-to-surface distances. Beam energies ranged from 6 to 18 MeV. New required experimental input data for commissioning are presented. The result of validation shows an excellent agreement between calculated and measured dose distributions. The calculated monitor units were within 2% of measured values except in the case of a 6 MeV beam and small cutout fields at extended SSDs (>110 cm). The investigation on the new issue of dose reporting demonstrates the differences up to 4% for lung and 12% for bone when 'dose-to-medium' is calculated and reported instead of 'dose-to-water' as done in a conventional system. The accuracy of the Monte Carlo calculation is shown to be clinically acceptable even for very complex 3D-type inhomogeneities. As Monte Carlo based treatment planning systems begin to enter clinical practice, new issues, such as dose reporting and statistical variations, may be clinically significant. Therefore it is imperative that a consistent approach to dose reporting is used.
The purpose of this study is to present our experience of commissioning, testing and use of the first commercial macro Monte Carlo based dose calculation algorithm for electron beam treatment planning and to investigate new issues regarding dose reporting (dose-to-water versus dose-to-medium) as well as statistical uncertainties for the calculations arising when Monte Carlo based systems are used in patient dose calculations. All phantoms studied were obtained by CT scan. The calculated dose distributions and monitor units were validated against measurements with film and ionization chambers in phantoms containing two-dimensional (2D) and three-dimensional (3D) type low- and high-density inhomogeneities at different source-to-surface distances. Beam energies ranged from 6 to 18 MeV. New required experimental input data for commissioning are presented. The result of validation shows an excellent agreement between calculated and measured dose distributions. The calculated monitor units were within 2% of measured values except in the case of a 6 MeV beam and small cutout fields at extended SSDs (>110 cm). The investigation on the new issue of dose reporting demonstrates the differences up to 4% for lung and 12% for bone when 'dose-to-medium' is calculated and reported instead of 'dose-to-water' as done in a conventional system. The accuracy of the Monte Carlo calculation is shown to be clinically acceptable even for very complex 3D-type inhomogeneities. As Monte Carlo based treatment planning systems begin to enter clinical practice, new issues, such as dose reporting and statistical variations, may be clinically significant. Therefore it is imperative that a consistent approach to dose reporting is used
van der Graaf, E. R.; Limburg, J.; Koomans, R. L.; Tijs, M.
2011-01-01
The calibration of scintillation detectors for gamma radiation in a well characterized setup can be transferred to other geometries using Monte Carlo simulations to account for the differences between the calibration and the other geometry. In this study a calibration facility was used that is const
Performance analysis based on a Monte Carlo simulation of a liquid xenon PET detector
Liquid xenon is a very attractive medium for position-sensitive gamma-ray detectors for a very wide range of applications, namely, in medical radionuclide imaging. Recently, the authors have proposed a liquid xenon detector for positron emission tomography (PET). In this paper, some aspects of the performance of a liquid xenon PET detector prototype were studied by means of Monte Carlo simulation
The information-based complexity of approximation problem by adaptive Monte Carlo methods
2008-01-01
In this paper, we study the complexity of information of approximation problem on the multivariate Sobolev space with bounded mixed derivative MWpr,α(Td), 1 < p < ∞, in the norm of Lq(Td), 1 < q < ∞, by adaptive Monte Carlo methods. Applying the discretization technique and some properties of pseudo-s-scale, we determine the exact asymptotic orders of this problem.
The Monte Carlo (MC) and discrete ordinates (SN) are the commonly used methods in the design of radiation shielding. Monte Carlo method is able to treat the geometry exactly, but time-consuming in dealing with the deep penetration problem. The discrete ordinate method has great computational efficiency, but it is quite costly in computer memory and it suffers from ray effect. Single discrete ordinates method or single Monte Carlo method has limitation in shielding calculation for large complex nuclear facilities. In order to solve the problem, the Monte Carlo and discrete ordinates bidirectional coupling method is developed. The bidirectional coupling method is implemented in the interface program to transfer the particle probability distribution of MC and angular flux of discrete ordinates. The coupling method combines the advantages of MC and SN. The test problems of cartesian and cylindrical coordinate have been calculated by the coupling methods. The calculation results are performed with comparison to MCNP and TORT and satisfactory agreements are obtained. The correctness of the program is proved. (authors)
Geometry navigation plays the most fundamental role in Monte Carlo particle transport simulation. It's mainly responsible for locating a particle inside which geometry volume it is and computing the distance to the volume boundary along the certain particle trajectory during each particle history. Geometry navigation directly affects the run-time performance of the Monte Carlo particle transport simulation, especially for large scale complicated systems. Two geometry acceleration algorithms, the automatic neighbor search algorithm and the oriented bounding box algorithm, are presented for improving geometry navigation performance. The algorithms have been implemented in the Super Monte Carlo Calculation Program for Nuclear and Radiation Process (SuperMC) version 2.0. The FDS-II and ITER benchmark models have been tested to highlight the efficiency gains that can be achieved by using the acceleration algorithms. The exact gains may be problem dependent, but testing results showed that runtime of Monte Carlo simulation can be considerably reduced 50%∼60% with the proposed acceleration algorithms. (author)
Miller, A C; Blakely, W F; Livengood, D; Whittaker, T; Xu, J.; Ejnik, J W; Hamilton, M. M.; Parlette, E; John, T S; Gerstenberg, H M; Hsu, H
1998-01-01
Depleted uranium (DU) is a dense heavy metal used primarily in military applications. Although the health effects of occupational uranium exposure are well known, limited data exist regarding the long-term health effects of internalized DU in humans. We established an in vitro cellular model to study DU exposure. Microdosimetric assessment, determined using a Monte Carlo computer simulation based on measured intracellular and extracellular uranium levels, showed that few (0.0014%) cell nuclei...
The probability distribution of the predicted CFM-induced ozone depletion. [Chlorofluoromethane
Ehhalt, D. H.; Chang, J. S.; Bulter, D. M.
1979-01-01
It is argued from the central limit theorem that the uncertainty in model predicted changes of the ozone column density is best represented by a normal probability density distribution. This conclusion is validated by comparison with a probability distribution generated by a Monte Carlo technique. In the case of the CFM-induced ozone depletion, and based on the estimated uncertainties in the reaction rate coefficients alone the relative mean standard deviation of this normal distribution is estimated to be 0.29.
Dual-energy CT-based material extraction for tissue segmentation in Monte Carlo dose calculations
Bazalova, Magdalena; Carrier, Jean-François; Beaulieu, Luc; Verhaegen, Frank
2008-05-01
Monte Carlo (MC) dose calculations are performed on patient geometries derived from computed tomography (CT) images. For most available MC codes, the Hounsfield units (HU) in each voxel of a CT image have to be converted into mass density (ρ) and material type. This is typically done with a (HU; ρ) calibration curve which may lead to mis-assignment of media. In this work, an improved material segmentation using dual-energy CT-based material extraction is presented. For this purpose, the differences in extracted effective atomic numbers Z and the relative electron densities ρe of each voxel are used. Dual-energy CT material extraction based on parametrization of the linear attenuation coefficient for 17 tissue-equivalent inserts inside a solid water phantom was done. Scans of the phantom were acquired at 100 kVp and 140 kVp from which Z and ρe values of each insert were derived. The mean errors on Z and ρe extraction were 2.8% and 1.8%, respectively. Phantom dose calculations were performed for 250 kVp and 18 MV photon beams and an 18 MeV electron beam in the EGSnrc/DOSXYZnrc code. Two material assignments were used: the conventional (HU; ρ) and the novel (HU; ρ, Z) dual-energy CT tissue segmentation. The dose calculation errors using the conventional tissue segmentation were as high as 17% in a mis-assigned soft bone tissue-equivalent material for the 250 kVp photon beam. Similarly, the errors for the 18 MeV electron beam and the 18 MV photon beam were up to 6% and 3% in some mis-assigned media. The assignment of all tissue-equivalent inserts was accurate using the novel dual-energy CT material assignment. As a result, the dose calculation errors were below 1% in all beam arrangements. Comparable improvement in dose calculation accuracy is expected for human tissues. The dual-energy tissue segmentation offers a significantly higher accuracy compared to the conventional single-energy segmentation.
Jimin Liang
2010-01-01
Full Text Available During the past decade, Monte Carlo method has obtained wide applications in optical imaging to simulate photon transport process inside tissues. However, this method has not been effectively extended to the simulation of free-space photon transport at present. In this paper, a uniform framework for noncontact optical imaging is proposed based on Monte Carlo method, which consists of the simulation of photon transport both in tissues and in free space. Specifically, the simplification theory of lens system is utilized to model the camera lens equipped in the optical imaging system, and Monte Carlo method is employed to describe the energy transformation from the tissue surface to the CCD camera. Also, the focusing effect of camera lens is considered to establish the relationship of corresponding points between tissue surface and CCD camera. Furthermore, a parallel version of the framework is realized, making the simulation much more convenient and effective. The feasibility of the uniform framework and the effectiveness of the parallel version are demonstrated with a cylindrical phantom based on real experimental results.
Parodi, K.; Ferrari, A.; Sommerer, F.; Paganetti, H.
2007-07-01
Clinical investigations on post-irradiation PET/CT (positron emission tomography/computed tomography) imaging for in vivo verification of treatment delivery and, in particular, beam range in proton therapy are underway at Massachusetts General Hospital (MGH). Within this project, we have developed a Monte Carlo framework for CT-based calculation of dose and irradiation-induced positron emitter distributions. Initial proton beam information is provided by a separate Geant4 Monte Carlo simulation modelling the treatment head. Particle transport in the patient is performed in the CT voxel geometry using the FLUKA Monte Carlo code. The implementation uses a discrete number of different tissue types with composition and mean density deduced from the CT scan. Scaling factors are introduced to account for the continuous Hounsfield unit dependence of the mass density and of the relative stopping power ratio to water used by the treatment planning system (XiO (Computerized Medical Systems Inc.)). Resulting Monte Carlo dose distributions are generally found in good correspondence with calculations of the treatment planning program, except a few cases (e.g. in the presence of air/tissue interfaces). Whereas dose is computed using standard FLUKA utilities, positron emitter distributions are calculated by internally combining proton fluence with experimental and evaluated cross-sections yielding 11C, 15O, 14O, 13N, 38K and 30P. Simulated positron emitter distributions yield PET images in good agreement with measurements. In this paper, we describe in detail the specific implementation of the FLUKA calculation framework, which may be easily adapted to handle arbitrary phase spaces of proton beams delivered by other facilities or include more reaction channels based on additional cross-section data. Further, we demonstrate the effects of different acquisition time regimes (e.g., PET imaging during or after irradiation) on the intensity and spatial distribution of the irradiation
An accurate dose calculation in phantom and patient geometries requires an accurate description of the radiation source. Errors in the radiation source description are propagated through the dose calculation. With the emergence of linear accelerators whose dosimetric characteristics are similar to within measurement uncertainty, the same radiation source description can be used as the input to dose calculation for treatment planning at many institutions with the same linear accelerator model. Our goal in the current research was to determine the initial electron fluence above the linear accelerator target for such an accelerator to allow a dose calculation in water to within 1% or 1 mm of the measured data supplied by the manufacturer. The method used for both the radiation source description and the patient transport was Monte Carlo. The linac geometry was input into the Monte Carlo code using the accelerator's manufacturer's specifications. Assumptions about the initial electron source above the target were made based on previous studies. The free parameters derived for the calculations were the mean energy and radial Gaussian width of the initial electron fluence and the target density. A combination of the free parameters yielded an initial electron fluence that, when transported through the linear accelerator and into the phantom, allowed a dose-calculation agreement to the experimental ion chamber data to within the specified criteria at both 6 and 18 MV nominal beam energies, except near the surface, particularly for the 18 MV beam. To save time during Monte Carlo treatment planning, the initial electron fluence was transported through part of the treatment head to a plane between the monitor chambers and the jaws and saved as phase-space files. These files are used for clinical Monte Carlo-based treatment planning and are freely available from the authors
Ozone depletion by hydrofluorocarbons
Hurwitz, Margaret M.; Fleming, Eric L.; Newman, Paul A.; Li, Feng; Mlawer, Eli; Cady-Pereira, Karen; Bailey, Roshelle
2015-10-01
Atmospheric concentrations of hydrofluorocarbons (HFCs) are projected to increase considerably in the coming decades. Chemistry climate model simulations forced by current projections show that HFCs will impact the global atmosphere increasingly through 2050. As strong radiative forcers, HFCs increase tropospheric and stratospheric temperatures, thereby enhancing ozone-destroying catalytic cycles and modifying the atmospheric circulation. These changes lead to a weak depletion of stratospheric ozone. Simulations with the NASA Goddard Space Flight Center 2-D model show that HFC-125 is the most important contributor to HFC-related atmospheric change in 2050; its effects are comparable to the combined impacts of HFC-23, HFC-32, HFC-134a, and HFC-143a. Incorporating the interactions between chemistry, radiation, and dynamics, ozone depletion potentials (ODPs) for HFCs range from 0.39 × 10-3 to 30.0 × 10-3, approximately 100 times larger than previous ODP estimates which were based solely on chemical effects.
Charek, Daniel B; Meyer, Gregory J; Mihura, Joni L
2016-10-01
We investigated the impact of ego depletion on selected Rorschach cognitive processing variables and self-reported affect states. Research indicates acts of effortful self-regulation transiently deplete a finite pool of cognitive resources, impairing performance on subsequent tasks requiring self-regulation. We predicted that relative to controls, ego-depleted participants' Rorschach protocols would have more spontaneous reactivity to color, less cognitive sophistication, and more frequent logical lapses in visualization, whereas self-reports would reflect greater fatigue and less attentiveness. The hypotheses were partially supported; despite a surprising absence of self-reported differences, ego-depleted participants had Rorschach protocols with lower scores on two variables indicative of sophisticated combinatory thinking, as well as higher levels of color receptivity; they also had lower scores on a composite variable computed across all hypothesized markers of complexity. In addition, self-reported achievement striving moderated the effect of the experimental manipulation on color receptivity, and in the Depletion condition it was associated with greater attentiveness to the tasks, more color reactivity, and less global synthetic processing. Results are discussed with an emphasis on the response process, methodological limitations and strengths, implications for calculating refined Rorschach scores, and the value of using multiple methods in research and experimental paradigms to validate assessment measures. PMID:26002059
Uncertainties in Monte Carlo-based absorbed dose calculations for an experimental benchmark
There is a need to verify the accuracy of general purpose Monte Carlo codes like EGSnrc, which are commonly employed for investigations of dosimetric problems in radiation therapy. A number of experimental benchmarks have been published to compare calculated values of absorbed dose to experimentally determined values. However, there is a lack of absolute benchmarks, i.e. benchmarks without involved normalization which may cause some quantities to be cancelled. Therefore, at the Physikalisch-Technische Bundesanstalt a benchmark experiment was performed, which aimed at the absolute verification of radiation transport calculations for dosimetry in radiation therapy. A thimble-type ionization chamber in a solid phantom was irradiated by high-energy bremsstrahlung and the mean absorbed dose in the sensitive volume was measured per incident electron of the target. The characteristics of the accelerator and experimental setup were precisely determined and the results of a corresponding Monte Carlo simulation with EGSnrc are presented within this study. For a meaningful comparison, an analysis of the uncertainty of the Monte Carlo simulation is necessary. In this study uncertainties with regard to the simulation geometry, the radiation source, transport options of the Monte Carlo code and specific interaction cross sections are investigated, applying the general methodology of the Guide to the expression of uncertainty in measurement. Besides studying the general influence of changes in transport options of the EGSnrc code, uncertainties are analyzed by estimating the sensitivity coefficients of various input quantities in a first step. Secondly, standard uncertainties are assigned to each quantity which are known from the experiment, e.g. uncertainties for geometric dimensions. Data for more fundamental quantities such as photon cross sections and the I-value of electron stopping powers are taken from literature. The significant uncertainty contributions are identified as
Uncertainties in Monte Carlo-based absorbed dose calculations for an experimental benchmark
Renner, F.; Wulff, J.; Kapsch, R.-P.; Zink, K.
2015-10-01
There is a need to verify the accuracy of general purpose Monte Carlo codes like EGSnrc, which are commonly employed for investigations of dosimetric problems in radiation therapy. A number of experimental benchmarks have been published to compare calculated values of absorbed dose to experimentally determined values. However, there is a lack of absolute benchmarks, i.e. benchmarks without involved normalization which may cause some quantities to be cancelled. Therefore, at the Physikalisch-Technische Bundesanstalt a benchmark experiment was performed, which aimed at the absolute verification of radiation transport calculations for dosimetry in radiation therapy. A thimble-type ionization chamber in a solid phantom was irradiated by high-energy bremsstrahlung and the mean absorbed dose in the sensitive volume was measured per incident electron of the target. The characteristics of the accelerator and experimental setup were precisely determined and the results of a corresponding Monte Carlo simulation with EGSnrc are presented within this study. For a meaningful comparison, an analysis of the uncertainty of the Monte Carlo simulation is necessary. In this study uncertainties with regard to the simulation geometry, the radiation source, transport options of the Monte Carlo code and specific interaction cross sections are investigated, applying the general methodology of the Guide to the expression of uncertainty in measurement. Besides studying the general influence of changes in transport options of the EGSnrc code, uncertainties are analyzed by estimating the sensitivity coefficients of various input quantities in a first step. Secondly, standard uncertainties are assigned to each quantity which are known from the experiment, e.g. uncertainties for geometric dimensions. Data for more fundamental quantities such as photon cross sections and the I-value of electron stopping powers are taken from literature. The significant uncertainty contributions are identified as
Radiative characteristics of depleted uranium bomb and it is protection
Based on the developing process of depleted uranium bombs described in the first part, the radiative characteristics and mechanism of depleted uranium bombs are analyzed emphatically. The deeper discussion on protection of depleted uranium bombs is proceeded
Monte Carlo Capabilities of the SCALE Code System
Rearden, B. T.; Petrie, L. M.; Peplow, D. E.; Bekar, K. B.; Wiarda, D.; Celik, C.; Perfetti, C. M.; Ibrahim, A. M.; Hart, S. W. D.; Dunn, M. E.
2014-06-01
SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a "plug-and-play" framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE's graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2, to be released in 2014, will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. An overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2.
Development of a hybrid multi-scale phantom for Monte-Carlo based internal dosimetry
Full text of publication follows. Aim: in recent years several phantoms were developed for radiopharmaceutical dosimetry in clinical and preclinical settings. Voxel-based models (Zubal, Max/Fax, ICRP110) were developed to reach a level of realism that could not be achieved by mathematical models. In turn, 'hybrid' models (XCAT, MOBY/ROBY, Mash/Fash) allow a further degree of versatility by offering the possibility to finely tune each model according to various parameters. However, even 'hybrid' models require the generation of a voxel version for Monte-Carlo modeling of radiation transport. Since absorbed dose simulation time is strictly related to geometry spatial sampling, a compromise should be made between phantom realism and simulation speed. This trade-off leads on one side in an overestimation of the size of small radiosensitive structures such as the skin or hollow organs' walls, and on the other hand to unnecessarily detailed voxellization of large, homogeneous structures. The Aim of this work is to develop a hybrid multi-resolution phantom model for Geant4 and Gate, to better characterize energy deposition in small structures while preserving reasonable computation times. Materials and Methods: we have developed a pipeline for the conversion of preexisting phantoms into a multi-scale Geant4 model. Meshes of each organ are created from raw binary images of a phantom and then voxellized to the smallest spatial sampling required by the user. The user can then decide to re-sample the internal part of each organ, while leaving a layer of smallest voxels at the edge of the organ. In this way, the realistic shape of the organ is maintained while reducing the voxel number in the inner part. For hollow organs, the wall is always modeled using the smallest voxel sampling. This approach allows choosing different voxel resolutions for each organ according to a specific application. Results: preliminary results show that it is possible to
Tetrahedral-mesh-based computational human phantom for fast Monte Carlo dose calculations
Although polygonal-surface computational human phantoms can address several critical limitations of conventional voxel phantoms, their Monte Carlo simulation speeds are much slower than those of voxel phantoms. In this study, we sought to overcome this problem by developing a new type of computational human phantom, a tetrahedral mesh phantom, by converting a polygonal surface phantom to a tetrahedral mesh geometry. The constructed phantom was implemented in the Geant4 Monte Carlo code to calculate organ doses as well as to measure computation speed, the values were then compared with those for the original polygonal surface phantom. It was found that using the tetrahedral mesh phantom significantly improved the computation speed by factors of between 150 and 832 considering all of the particles and simulated energies other than the low-energy neutrons (0.01 and 1 MeV), for which the improvement was less significant (17.2 and 8.8 times, respectively). (paper)
A method for the calculation of the transit doses in HDR brachytherapy based on Monte Carlo simulations has been presented. The transit doses resulting from a linear implant with seven dwell positions is simulated by performing calculations at all positions in which, the moving 192Ir source, instantaneously, had its geometrical centre located exactly between two adjacent dwell positions. Discrete step sizes of 0.25 cm were used to calculate the dose rates and the total transit dose at any of the calculation points evaluated. By comparing this method to the results obtained from Sievert Integrals, we observed dose calculation errors ranging from 32 to 21% for the examples considered. The errors could be much higher for longer treatment lengths where contributions from points near the longitudinal axis of the source become more important. To date, the most accurate method of calculating doses in radiotherapy is by Monte Carlo Simulations but the long computational times associated with it renders its use in treatment planning impracticable. The Sievert Integral algorithms on the other hand are simple, versatile and very easy to use but its accuracy had been repeatedly put into question for low energy isotopes like iridium. We therefore advocate a modification of the Sievert Integral algorithms by superimposing the output from Monte Carlo Simulations on the Sievert Integrals when dealing with low energy isotopes. In this way, we would be combining accuracy, simplicity and reasonable computational times (author)
New approach based on tetrahedral-mesh geometry for accurate 4D Monte Carlo patient-dose calculation
In the present study, to achieve accurate 4D Monte Carlo dose calculation in radiation therapy, we devised a new approach that combines (1) modeling of the patient body using tetrahedral-mesh geometry based on the patient’s 4D CT data, (2) continuous movement/deformation of the tetrahedral patient model by interpolation of deformation vector fields acquired through deformable image registration, and (3) direct transportation of radiation particles during the movement and deformation of the tetrahedral patient model. The results of our feasibility study show that it is certainly possible to construct 4D patient models (= phantoms) with sufficient accuracy using the tetrahedral-mesh geometry and to directly transport radiation particles during continuous movement and deformation of the tetrahedral patient model. This new approach not only produces more accurate dose distribution in the patient but also replaces the current practice of using multiple 3D voxel phantoms and combining multiple dose distributions after Monte Carlo simulations. For routine clinical application of our new approach, the use of fast automatic segmentation algorithms is a must. In order to achieve, simultaneously, both dose accuracy and computation speed, the number of tetrahedrons for the lungs should be optimized. Although the current computation speed of our new 4D Monte Carlo simulation approach is slow (i.e. ∼40 times slower than that of the conventional dose accumulation approach), this problem is resolvable by developing, in Geant4, a dedicated navigation class optimized for particle transportation in tetrahedral-mesh geometry. (paper)
Doronin, Alexander; Rushmeier, Holly E.; Meglinski, Igor; Bykov, Alexander V.
2016-03-01
We present a new Monte Carlo based approach for the modelling of Bidirectional Scattering-Surface Reflectance Distribution Function (BSSRDF) for accurate rendering of human skin appearance. The variations of both skin tissues structure and the major chromophores are taken into account correspondingly to the different ethnic and age groups. The computational solution utilizes HTML5, accelerated by the graphics processing units (GPUs), and therefore is convenient for the practical use at the most of modern computer-based devices and operating systems. The results of imitation of human skin reflectance spectra, corresponding skin colours and examples of 3D faces rendering are presented and compared with the results of phantom studies.
Objective: With the Monte Carlo method to recalculate the IMRT dose distributions from four TPS to provide a platform for independent comparison and evaluation of the plan quality.These results will help make a clinical decision as which TPS will be used for prostate IMRT planning. Methods: Eleven prostate cancer cases were planned with the Corvus, Xio, Pinnacle and Eclipse TPS. The plans were recalculated by Monte Carlo using leaf sequences and MUs for individual plans. Dose-volume-histograms and isodose distributions were compared. Other quantities such as Dmin (the minimum dose received by 99% of CTV/PTV), Dmax (the maximum dose received by 1% of CTV/PTV), V110%, V105%, V95% (the volume of CTV/PTV receiving 110%, 105%, 95% of the prescription dose), the volume of rectum and bladder receiving >65 Gy and >40 Gy, and the volume of femur receiving >50 Gy were evaluated. Total segments and MUs were also compared. Results: The Monte Carlo results agreed with the dose distributions from the TPS to within 3%/3 mm. The Xio, Pinnacle and Eclipse plans show less target dose heterogeneity and lower V65 and V40 for the rectum and bladder compared to the Corvus plans. The PTV Dmin is about 2 Gy lower for Xio plans than others while the Corvus plans have slightly lower female head V50 (0.03% and 0.58%) than others. The Corvus plans require significantly most segments (187.8) and MUs (1264.7) to deliver and the Pinnacle plans require fewest segments (82.4) and MUs (703.6). Conclusions: We have tested an independent Monte Carlo dose calculation system for dose reconstruction and plan evaluation. This system provides a platform for the fair comparison and evaluation of treatment plans to facilitate clinical decision making in selecting a TPS and beam delivery system for particular treatment sites. (authors)
Monte Carlo tests of the Rasch model based on scalability coefficients
Christensen, Karl Bang; Kreiner, Svend
that summarizes the number of Guttman errors in the data matrix. These coefficients are shown to yield efficient tests of the Rasch model using p-values computed using Markov chain Monte Carlo methods. The power of the tests of unequal item discrimination, and their ability to distinguish between local...... dependence and unequal item discrimination, are discussed. The methods are illustrated and motivated using a simulation study and a real data example....
Uncertainty Analysis of Power Grid Investment Capacity Based on Monte Carlo
Qin, Junsong; Liu, Bingyi; Niu, Dongxiao
By analyzing the influence factors of the investment capacity of power grid, to depreciation cost, sales price and sales quantity, net profit, financing and GDP of the second industry as the dependent variable to build the investment capacity analysis model. After carrying out Kolmogorov-Smirnov test, get the probability distribution of each influence factor. Finally, obtained the grid investment capacity uncertainty of analysis results by Monte Carlo simulation.
A Monte Carlo method based on antithetic variates for network reliability computations
El Khadiri, Mohamed; Rubino, Gerardo
1992-01-01
The exact evaluation of usual reliability measures of communication networks is seriously limited because of the excessive computational time usually needed to obtain them. In the general case, the computation of almost all the interesting reliability metrics are NP-hard problems. An alternative approach is to estimate them by means of a Monte Carlo simulation. This allows to deal with larger models than those that can be evaluated exactly. In this paper, we propose an algorithm much more per...
Design and evaluation of a Monte Carlo based model of an orthovoltage treatment system
The aim of this study was to develop a flexible framework of an orthovoltage treatment system capable of calculating and visualizing dose distributions in different phantoms and CT datasets. The framework provides a complete set of various filters, applicators and X-ray energies and therefore can be adapted to varying studies or be used for educational purposes. A dedicated user friendly graphical interface was developed allowing for easy setup of the simulation parameters and visualization of the results. For the Monte Carlo simulations the EGSnrc Monte Carlo code package was used. Building the geometry was accomplished with the help of the EGSnrc C++ class library. The deposited dose was calculated according to the KERMA approximation using the track-length estimator. The validation against measurements showed a good agreement within 4-5% deviation, down to depths of 20% of the depth dose maximum. Furthermore, to show its capabilities, the validated model was used to calculate the dose distribution on two CT datasets. Typical Monte Carlo calculation time for these simulations was about 10 minutes achieving an average statistical uncertainty of 2% on a standard PC. However, this calculation time depends strongly on the used CT dataset, tube potential, filter material/thickness and applicator size.
Design and evaluation of a Monte Carlo based model of an orthovoltage treatment system
Penchev, Petar; Maeder, Ulf; Fiebich, Martin [IMPS University of Applied Sciences, Giessen (Germany). Inst. of Medical Physics and Radiation Protection; Zink, Klemens [IMPS University of Applied Sciences, Giessen (Germany). Inst. of Medical Physics and Radiation Protection; University Hospital Marburg (Germany). Dept. of Radiotherapy and Oncology
2015-07-01
The aim of this study was to develop a flexible framework of an orthovoltage treatment system capable of calculating and visualizing dose distributions in different phantoms and CT datasets. The framework provides a complete set of various filters, applicators and X-ray energies and therefore can be adapted to varying studies or be used for educational purposes. A dedicated user friendly graphical interface was developed allowing for easy setup of the simulation parameters and visualization of the results. For the Monte Carlo simulations the EGSnrc Monte Carlo code package was used. Building the geometry was accomplished with the help of the EGSnrc C++ class library. The deposited dose was calculated according to the KERMA approximation using the track-length estimator. The validation against measurements showed a good agreement within 4-5% deviation, down to depths of 20% of the depth dose maximum. Furthermore, to show its capabilities, the validated model was used to calculate the dose distribution on two CT datasets. Typical Monte Carlo calculation time for these simulations was about 10 minutes achieving an average statistical uncertainty of 2% on a standard PC. However, this calculation time depends strongly on the used CT dataset, tube potential, filter material/thickness and applicator size.
Development and validation of MCNPX-based Monte Carlo treatment plan verification system
Iraj Jabbari
2015-01-01
Full Text Available A Monte Carlo treatment plan verification (MCTPV system was developed for clinical treatment plan verification (TPV, especially for the conformal and intensity-modulated radiotherapy (IMRT plans. In the MCTPV, the MCNPX code was used for particle transport through the accelerator head and the patient body. MCTPV has an interface with TiGRT planning system and reads the information which is needed for Monte Carlo calculation transferred in digital image communications in medicine-radiation therapy (DICOM-RT format. In MCTPV several methods were applied in order to reduce the simulation time. The relative dose distribution of a clinical prostate conformal plan calculated by the MCTPV was compared with that of TiGRT planning system. The results showed well implementation of the beams configuration and patient information in this system. For quantitative evaluation of MCTPV a two-dimensional (2D diode array (MapCHECK2 and gamma index analysis were used. The gamma passing rate (3%/3 mm of an IMRT plan was found to be 98.5% for total beams. Also, comparison of the measured and Monte Carlo calculated doses at several points inside an inhomogeneous phantom for 6- and 18-MV photon beams showed a good agreement (within 1.5%. The accuracy and timing results of MCTPV showed that MCTPV could be used very efficiently for additional assessment of complicated plans such as IMRT plan.
Depleted uranium management alternatives
This report evaluates two management alternatives for Department of Energy depleted uranium: continued storage as uranium hexafluoride, and conversion to uranium metal and fabrication to shielding for spent nuclear fuel containers. The results will be used to compare the costs with other alternatives, such as disposal. Cost estimates for the continued storage alternative are based on a life-cycle of 27 years through the year 2020. Cost estimates for the recycle alternative are based on existing conversion process costs and Capital costs for fabricating the containers. Additionally, the recycle alternative accounts for costs associated with intermediate product resale and secondary waste disposal for materials generated during the conversion process
An analytic linear accelerator source model for GPU-based Monte Carlo dose calculations
Tian, Zhen; Li, Yongbao; Folkerts, Michael; Shi, Feng; Jiang, Steve B.; Jia, Xun
2015-10-01
Recently, there has been a lot of research interest in developing fast Monte Carlo (MC) dose calculation methods on graphics processing unit (GPU) platforms. A good linear accelerator (linac) source model is critical for both accuracy and efficiency considerations. In principle, an analytical source model should be more preferred for GPU-based MC dose engines than a phase-space file-based model, in that data loading and CPU-GPU data transfer can be avoided. In this paper, we presented an analytical field-independent source model specifically developed for GPU-based MC dose calculations, associated with a GPU-friendly sampling scheme. A key concept called phase-space-ring (PSR) was proposed. Each PSR contained a group of particles that were of the same type, close in energy and reside in a narrow ring on the phase-space plane located just above the upper jaws. The model parameterized the probability densities of particle location, direction and energy for each primary photon PSR, scattered photon PSR and electron PSR. Models of one 2D Gaussian distribution or multiple Gaussian components were employed to represent the particle direction distributions of these PSRs. A method was developed to analyze a reference phase-space file and derive corresponding model parameters. To efficiently use our model in MC dose calculations on GPU, we proposed a GPU-friendly sampling strategy, which ensured that the particles sampled and transported simultaneously are of the same type and close in energy to alleviate GPU thread divergences. To test the accuracy of our model, dose distributions of a set of open fields in a water phantom were calculated using our source model and compared to those calculated using the reference phase-space files. For the high dose gradient regions, the average distance-to-agreement (DTA) was within 1 mm and the maximum DTA within 2 mm. For relatively low dose gradient regions, the root-mean-square (RMS) dose difference was within 1.1% and the maximum
Houska, Tobias; Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz
2014-05-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the Van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 x 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape
Monte Carlo-based treatment planning system calculation engine for microbeam radiation therapy
Purpose: Microbeam radiation therapy (MRT) is a synchrotron radiotherapy technique that explores the limits of the dose-volume effect. Preclinical studies have shown that MRT irradiations (arrays of 25-75-μm-wide microbeams spaced by 200-400 μm) are able to eradicate highly aggressive animal tumor models while healthy tissue is preserved. These promising results have provided the basis for the forthcoming clinical trials at the ID17 Biomedical Beamline of the European Synchrotron Radiation Facility (ESRF). The first step includes irradiation of pets (cats and dogs) as a milestone before treatment of human patients. Within this context, accurate dose calculations are required. The distinct features of both beam generation and irradiation geometry in MRT with respect to conventional techniques require the development of a specific MRT treatment planning system (TPS). In particular, a Monte Carlo (MC)-based calculation engine for the MRT TPS has been developed in this work. Experimental verification in heterogeneous phantoms and optimization of the computation time have also been performed. Methods: The penelope/penEasy MC code was used to compute dose distributions from a realistic beam source model. Experimental verification was carried out by means of radiochromic films placed within heterogeneous slab-phantoms. Once validation was completed, dose computations in a virtual model of a patient, reconstructed from computed tomography (CT) images, were performed. To this end, decoupling of the CT image voxel grid (a few cubic millimeter volume) to the dose bin grid, which has micrometer dimensions in the transversal direction of the microbeams, was performed. Optimization of the simulation parameters, the use of variance-reduction (VR) techniques, and other methods, such as the parallelization of the simulations, were applied in order to speed up the dose computation. Results: Good agreement between MC simulations and experimental results was achieved, even at the
Monte Carlo-based treatment planning system calculation engine for microbeam radiation therapy
Martinez-Rovira, I.; Sempau, J.; Prezado, Y. [Institut de Tecniques Energetiques, Universitat Politecnica de Catalunya, Diagonal 647, Barcelona E-08028 (Spain) and ID17 Biomedical Beamline, European Synchrotron Radiation Facility (ESRF), 6 rue Jules Horowitz B.P. 220, F-38043 Grenoble Cedex (France); Institut de Tecniques Energetiques, Universitat Politecnica de Catalunya, Diagonal 647, Barcelona E-08028 (Spain); Laboratoire Imagerie et modelisation en neurobiologie et cancerologie, UMR8165, Centre National de la Recherche Scientifique (CNRS), Universites Paris 7 et Paris 11, Bat 440., 15 rue Georges Clemenceau, F-91406 Orsay Cedex (France)
2012-05-15
Purpose: Microbeam radiation therapy (MRT) is a synchrotron radiotherapy technique that explores the limits of the dose-volume effect. Preclinical studies have shown that MRT irradiations (arrays of 25-75-{mu}m-wide microbeams spaced by 200-400 {mu}m) are able to eradicate highly aggressive animal tumor models while healthy tissue is preserved. These promising results have provided the basis for the forthcoming clinical trials at the ID17 Biomedical Beamline of the European Synchrotron Radiation Facility (ESRF). The first step includes irradiation of pets (cats and dogs) as a milestone before treatment of human patients. Within this context, accurate dose calculations are required. The distinct features of both beam generation and irradiation geometry in MRT with respect to conventional techniques require the development of a specific MRT treatment planning system (TPS). In particular, a Monte Carlo (MC)-based calculation engine for the MRT TPS has been developed in this work. Experimental verification in heterogeneous phantoms and optimization of the computation time have also been performed. Methods: The penelope/penEasy MC code was used to compute dose distributions from a realistic beam source model. Experimental verification was carried out by means of radiochromic films placed within heterogeneous slab-phantoms. Once validation was completed, dose computations in a virtual model of a patient, reconstructed from computed tomography (CT) images, were performed. To this end, decoupling of the CT image voxel grid (a few cubic millimeter volume) to the dose bin grid, which has micrometer dimensions in the transversal direction of the microbeams, was performed. Optimization of the simulation parameters, the use of variance-reduction (VR) techniques, and other methods, such as the parallelization of the simulations, were applied in order to speed up the dose computation. Results: Good agreement between MC simulations and experimental results was achieved, even at
Generation of scintigraphic images in a virtual dosimetry trial based on Monte Carlo modelling
Full text of publication follows. Aim: the purpose of dosimetry calculations in therapeutic nuclear medicine is to maximize tumour absorbed dose while minimizing normal tissue toxicities. However a wide heterogeneity of dosimetric approaches is observed: there is no standardized dosimetric protocol to date. The DosiTest project (www.dositest.com) intends to identify critical steps in the dosimetry chain by implementing clinical dosimetry in different Nuclear Medicine departments, on scintigraphic images generated by Monte Carlo simulation from a same virtual patient. This study aims at presenting the different steps contributing to image generation, following the imaging protocol of a given participating centre, Milan's European Institute of Oncology (IEO). Materiel and methods: the chosen clinical application is that of 111In-pentetreotide (OctreoscanTM). Pharmacokinetic data from the literature are used to derive a compartmental model. The kinetic rates between 6 compartments (liver, spleen, kidneys, blood, urine, remainder body) were obtained from WinSaam [3]: the activity in each compartment is known at any time point. The TestDose [1] software (computing architecture of DosiTest) implements the NURBS-based phantom NCAT-WB [2] to generate anatomical data for the virtual patient. IEO gamma-camera was modelled with GATE [4] v6.2. Scintigraphic images were simulated for each compartment and the resulting projections were weighted by the respective pharmacokinetics for each compartment. The final step consisted in aggregating each compartment to generate the resulting image. Results: following IEO's imaging protocol, planar and tomographic image simulations were generated at various time points. Computation times (on a 480 virtual cores computing cluster) for 'step and shoot' whole body simulations (5 steps/time point) and acceptable statistics were: 10 days for extra-vascular fluid, 28 h for blood, 12 h for liver, 7 h for kidneys, and 1-2 h for
Optimization of Depletion Modeling and Simulation for the High Flux Isotope Reactor
Betzler, Benjamin R [ORNL; Ade, Brian J [ORNL; Chandler, David [ORNL; Ilas, Germina [ORNL; Sunny, Eva E [ORNL
2015-01-01
Monte Carlo based depletion tools used for the high-fidelity modeling and simulation of the High Flux Isotope Reactor (HFIR) come at a great computational cost; finding sufficient approximations is necessary to make the use of these tools feasible. The optimization of the neutronics and depletion model for the HFIR is based on two factors: (i) the explicit representation of the involute fuel plates with sets of polyhedra and (ii) the treatment of depletion mixtures and control element position during depletion calculations. A very fine representation (i.e., more polyhedra in the involute plate approximation) does not significantly improve simulation accuracy. The recommended representation closely represents the physical plates and ensures sufficient fidelity in regions with high flux gradients. Including the fissile targets in the central flux trap of the reactor as depletion mixtures has the greatest effect on the calculated cycle length, while localized effects (e.g., the burnup of specific isotopes or the power distribution evolution over the cycle) are more noticeable consequences of including a critical control element search or depleting burnable absorbers outside the fuel region.
This paper presents an unstructured mesh based multi-physics interface implemented in the Serpent 2 Monte Carlo code, for the purpose of coupling the neutronics solution to component-scale thermal hydraulics calculations, such as computational fluid dynamics (CFD). The work continues the development of a multi-physics coupling scheme, which relies on the separation of state-point information from the geometry input, and the capability to handle temperature and density distributions by a rejection sampling algorithm. The new interface type is demonstrated by a simplified molten-salt reactor test case, using a thermal hydraulics solution provided by the CFD solver in OpenFOAM. (author)
Sampling-Based Nuclear Data Uncertainty Quantification for Continuous Energy Monte Carlo Codes
Zhu, Ting
2015-01-01
The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of MCNPX makes it the choice of routine criticality safety calculations at PSI/LRS, but also raises challenges for NDUQ by conventional sensitivity/uncertainty (S/U) methods. The methodology developed during this PhD research is fundamentally ...