The heat is removed by the heavy water coolant completely separated from stationary moderator. Due to the good neutron economy of the CANDU reactor, natural uranium fuel is used without enrichment. Because of the unique core configuration characteristic, there is less resonance absorption of neutron in fuel which leads to a relatively small fuel temperature coefficient (FTC). The value of FTC can even be positive due to the 239Pu buildup during the fuel depletion and also the neutron up-scattering by the oxygen atoms in the fuel. Unlike the pressurized light water reactor, it is well known that CANDU-6 has a positive coolant void reactivity (CVR) and coolant temperature coefficient (CTC). In a traditional reactor analysis, the asymptotic scattering kernel has been used and neglects the thermal motion of nuclides such as U-238. However, it is well accepted that in a scattering reaction, the thermal movement of the target can affect the scattering reaction in the vicinity of scattering resonance and enhance neutron capture by the capture resonance. Some recent works have revealed that the thermal motion of U-238 affects the scattering reaction and that the resulting Doppler broadening of the scattering resonance enhances the FTC of the thermal reactor including PWRs by 10- 15%. In order to observe the impacts of the Doppler broadening of the scattering resonances on the criticality and FTC, a recent investigation was done for a clean and fresh CANDU fuel lattice using Monte Carlo code MCNPX for analysis.. In ref. 3 the so-called DBRC (Doppler Broadened Rejection Correction) method was adopted to consider the thermal movement of U-238. In this study, the safety parameter of CANDU-6 is re-evaluated by using the continuous energy Monte Carlo code SERPENT 2 which uses the DBRC method to simulate the thermal motion of U-238. The analysis is performed for a full 3-D CANDU-6 core and the PCR is evaluated near equilibrium burnup. For a high-fidelity Monte Carlo calculation
Combination of Monte Carlo and transfer matrix methods to study 2D and 3D percolation
Saleur, H.; Derrida, B.
1985-07-01
In this paper we develop a method which combines the transfer matrix and the Monte Carlo methods to study the problem of site percolation in 2 and 3 dimensions. We use this method to calculate the properties of strips (2D) and bars (3D). Using a finite size scaling analysis, we obtain estimates of the threshold and of the exponents wich confirm values already known. We discuss the advantages and the limitations of our method by comparing it with usual Monte Carlo calculations.
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)
This work introduces a new approach for calculating the sensitivity of generalized neutronic responses to nuclear data uncertainties using continuous-energy Monte Carlo methods. The GEneralized Adjoint Responses in Monte Carlo (GEAR-MC) method has enabled the calculation of high resolution sensitivity coefficients for multiple, generalized neutronic responses in a single Monte Carlo calculation with no nuclear data perturbations or knowledge of nuclear covariance data. The theory behind the GEAR-MC method is presented here and proof of principle is demonstrated by calculating sensitivity coefficients for responses in several 3D, continuous-energy Monte Carlo applications. (author)
3D Monte Carlo radiation transfer modelling of photodynamic therapy
Campbell, C. Louise; Christison, Craig; Brown, C. Tom A.; Wood, Kenneth; Valentine, Ronan M.; Moseley, Harry
2015-06-01
The effects of ageing and skin type on Photodynamic Therapy (PDT) for different treatment methods have been theoretically investigated. A multilayered Monte Carlo Radiation Transfer model is presented where both daylight activated PDT and conventional PDT are compared. It was found that light penetrates deeper through older skin with a lighter complexion, which translates into a deeper effective treatment depth. The effect of ageing was found to be larger for darker skin types. The investigation further strengthens the usage of daylight as a potential light source for PDT where effective treatment depths of about 2 mm can be achieved.
Perfetti, Christopher M [ORNL; Rearden, Bradley T [ORNL
2014-01-01
This work introduces a new approach for calculating sensitivity coefficients for generalized neutronic responses to nuclear data uncertainties using continuous-energy Monte Carlo methods. The approach presented in this paper, known as the GEAR-MC method, allows for the calculation of generalized sensitivity coefficients for multiple responses in a single Monte Carlo calculation with no nuclear data perturbations or knowledge of nuclear covariance data. The theory behind the GEAR-MC method is presented here, and proof of principle is demonstrated by using the GEAR-MC method to calculate sensitivity coefficients for responses in several 3D, continuous-energy Monte Carlo applications.
A combination of Monte Carlo and transfer matrix methods to study 2D and 3D percolation
Saleur, H.; Derrida, B.
1985-01-01
In this paper we develop a method which combines the transfer matrix and the Monte Carlo methods to study the problem of site percolation in 2 and 3 dimensions. We use this method to calculate the properties of strips (2D) and bars (3D). Using a finite size scaling analysis, we obtain estimates of the threshold and of the exponents which confirm values already known. We discuss the advantages and the limitations of our method by comparing it with usual Monte Carlo calculations.
A combination of Monte Carlo and transfer matrix methods to study 2D and 3D percolation
In this paper we develop a method which combines the transfer matrix and the Monte Carlo methods to study the problem of site percolation in 2 and 3 dimensions. We use this method to calculate the properties of strips (2D) and bars (3D). Using a finite size scaling analysis, we obtain estimates of the threshold and of the exponents wich confirm values already known. We discuss the advantages and the limitations of our method by comparing it with usual Monte Carlo calculations
A highly heterogeneous 3D PWR core benchmark: deterministic and Monte Carlo method comparison
Physical analyses of the LWR potential performances with regards to the fuel utilization require an important part of the work dedicated to the validation of the deterministic models used for theses analyses. Advances in both codes and computer technology give the opportunity to perform the validation of these models on complex 3D core configurations closed to the physical situations encountered (both steady-state and transient configurations). In this paper, we used the Monte Carlo Transport code TRIPOLI-4 to describe a whole 3D large-scale and highly-heterogeneous LWR core. The aim of this study is to validate the deterministic CRONOS2 code to Monte Carlo code TRIPOLI-4 in a relevant PWR core configuration. As a consequence, a 3D pin by pin model with a consistent number of volumes (4.3 millions) and media (around 23.000) is established to precisely characterize the core at equilibrium cycle, namely using a refined burn-up and moderator density maps. The configuration selected for this analysis is a very heterogeneous PWR high conversion core with fissile (MOX fuel) and fertile zones (depleted uranium). Furthermore, a tight pitch lattice is selected (to increase conversion of 238U in 239Pu) that leads to harder neutron spectrum compared to standard PWR assembly. This benchmark shows 2 main points. First, independent replicas are an appropriate method to achieve a fare variance estimation when dominance ratio is near 1. Secondly, the diffusion operator with 2 energy groups gives satisfactory results compared to TRIPOLI-4 even with a highly heterogeneous neutron flux map and an harder spectrum
The accuracy of Single Photon Emission Computed Tomography (SPECT) images is degraded by physical effects, namely photon attenuation, Compton scatter and spatially varying collimator response. The 3D nature of these effects is usually neglected by the methods used to correct for these effects. To deal with the 3D nature of the problem, a 3D projector modeling the spread of photons in 3D can be used in iterative tomographic reconstruction. The 3D projector can be estimated analytically with some approximations, or using precise Monte Carlo simulations. This latter approach has not been applied to fully 3D reconstruction yet due to impractical storage and computation time. The goal of this paper was to determine the gain to be expected from fully 3D Monte Carlo (F3DMC) modeling of the projector in iterative reconstruction, compared to conventional 2D and 3D reconstruction methods. As a proof-of-concept, two small datasets were considered. The projections of the two phantoms were simulated using the Monte Carlo simulation code GATE, as well as the corresponding projector, by taking into account all physical effects (attenuation, scatter, camera point spread function) affecting the imaging process. F3DMC was implemented by using this 3D projector in a maximum likelihood expectation maximization (MLEM) iterative reconstruction. To assess the value of F3DMC, data were reconstructed using 4 methods: filtered backprojection (FBP), MLEM without attenuation correction (MLEM), MLEM with attenuation correction, Jaszczak scatter correction and 3D correction for depth-dependent spatial resolution using an analytical model (MLEMC) and F3DMC. Our results suggest that F3DMC improves mainly imaging sensitivity and signal-to-noise ratio (SNR): sensitivity is multiplied by about 103 and SNR is increased by 20 to 70% compared to MLEMC. Computation of a more robust projector and application of the method on more realistic datasets are currently under investigation. (authors)
Variance reduction in Monte Carlo analysis of rarefied gas diffusion.
Perlmutter, M.
1972-01-01
The problem of rarefied diffusion between parallel walls is solved using the Monte Carlo method. The diffusing molecules are evaporated or emitted from one of the two parallel walls and diffuse through another molecular species. The Monte Carlo analysis treats the diffusing molecule as undergoing a Markov random walk, and the local macroscopic properties are found as the expected value of the random variable, the random walk payoff. By biasing the transition probabilities and changing the collision payoffs, the expected Markov walk payoff is retained but its variance is reduced so that the Monte Carlo result has a much smaller error.
Bayesian phylogeny analysis via stochastic approximation Monte Carlo
Cheon, Sooyoung
2009-11-01
Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.
MCMG: a 3-D multigroup P3 Monte Carlo code and its benchmarks
In this paper a 3-D Monte Carlo multigroup neutron transport code MCMG has been developed from a coupled neutron and photon transport Monte Carlo code MCNP. The continuous-energy cross section library of the MCNP code is replaced by the multigroup cross section data generated by the transport lattice code, such as the WIMS code. It maintains the strong abilities of MCNP for geometry treatment, counting, variance reduction techniques and plotting. The multigroup neutron scattering cross sections adopt the Pn (n ≤ 3) approximation. The test results are in good agreement with the results of other methods and experiments. The number of energy groups can be varied from few groups to multigroup, and either macroscopic or microscopic cross section can be used. (author)
Implementation of 3D Lattice Monte Carlo Simulation on a Cluster of Symmetric Multiprocessors
雷咏梅; 蒋英; 等
2002-01-01
This paper presents a new approach to parallelize 3D lattice Monte Carlo algorithms used in the numerical simulation of polymer on ZiQiang 2000-a cluster of symmetric multiprocessors(SMPs).The combined load for cell and energy calculations over the time step is balanced together to form a single spatial decomposition.Basic aspects and strategies of running Monte Carlo calculations on parallel computers are studied.Different steps involved in porting the software on a parallel architecture based on ZiQiang 2000 running under Linux and MPI are described briefly.It is found that parallelization becomes more advantageous when either the lattice is very large or the model contains many cells and chains.
Adaptive Multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model
Navarro, C A; Deng, Youjin
2015-01-01
The study of disordered spin systems through Monte Carlo simulations has proven to be a hard task due to the adverse energy landscape present at the low temperature regime, making it difficult for the simulation to escape from a local minimum. Replica based algorithms such as the Exchange Monte Carlo (also known as parallel tempering) are effective at overcoming this problem, reaching equilibrium on disordered spin systems such as the Spin Glass or Random Field models, by exchanging information between replicas of neighbor temperatures. In this work we present a multi-GPU Exchange Monte Carlo method designed for the simulation of the 3D Random Field Model. The implementation is based on a two-level parallelization scheme that allows the method to scale its performance in the presence of faster and GPUs as well as multiple GPUs. In addition, we modified the original algorithm by adapting the set of temperatures according to the exchange rate observed from short trial runs, leading to an increased exchange rate...
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.
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)
Monte Carlo methods for the reliability analysis of Markov systems
This paper presents Monte Carlo methods for the reliability analysis of Markov systems. Markov models are useful in treating dependencies between components. The present paper shows how the adjoint Monte Carlo method for the continuous time Markov process can be derived from the method for the discrete-time Markov process by a limiting process. The straightforward extensions to the treatment of mean unavailability (over a time interval) are given. System unavailabilities can also be estimated; this is done by making the system failed states absorbing, and not permitting repair from them. A forward Monte Carlo method is presented in which the weighting functions are related to the adjoint function. In particular, if the exact adjoint function is known then weighting factors can be constructed such that the exact answer can be obtained with a single Monte Carlo trial. Of course, if the exact adjoint function is known, there is no need to perform the Monte Carlo calculation. However, the formulation is useful since it gives insight into choices of the weight factors which will reduce the variance of the estimator
Even with state of the art treatment planning systems the photon dose calculation can be erroneous under certain circumstances. In these cases Monte Carlo methods promise a higher accuracy. We have used the photon transport code CHILD of the GSF-Forschungszentrum, which was developed to calculate dose in diagnostic radiation protection matters. The code was refined for application in radiotherapy for high energy photon irradiation and should serve for dose verification in individual cases. The irradiation phantom can be entered as any desired 3D matrix or be generated automatically from an individual CT database. The particle transport takes into account pair production, photo, and Compton effect with certain approximations. Efficiency is increased by the method of 'fractional photons'. The generated secondary electrons are followed by the unscattered continuous-slowing-down-approximation (CSDA). The developed Monte Carlo code Monaco Matrix was tested with simple homogeneous and heterogeneous phantoms through comparisons with simulations of the well known but slower EGS4 code. The use of a point source with a direction independent energy spectrum as simplest model of the radiation field from the accelerator head is shown to be sufficient for simulation of actual accelerator depth dose curves. Good agreement (<2%) was found for depth dose curves in water and in bone. With complex test phantoms and comparisons with EGS4 calculated dose profiles some drawbacks in the code were found. Thus, the implementation of the electron multiple-scattering should lead us to step by step improvement of the algorithm. (orig.)
Monte Carlo Radiation Analysis of a Spacecraft Radioisotope Power System
Wallace, M.
1994-01-01
A Monte Carlo statistical computer analysis was used to create neutron and photon radiation predictions for the General Purpose Heat Source Radioisotope Thermoelectric Generator (GPHS RTG). The GPHS RTG is being used on several NASA planetary missions. Analytical results were validated using measured health physics data.
Hybrid methods of neutron transport have increased greatly in use, for example, in applications of using both Monte Carlo and deterministic transport methods to calculate quantities of interest, such as the flux and eigenvalue in a nuclear reactor. Many 3d parallel Sn codes apply a Cartesian mesh, and thus for nuclear reactors the representation of curved fuels (cylinder, sphere, etc.) are impacted in the representation of proper fuel inventory, resulting in both a deviation of mass and exact geometry in the computer model representation. In addition, we discuss auto-conversion techniques with our 3d Cartesian mesh generation tools to allow for full generation of MCNP5 inputs (Cartesian mesh and Multigroup XS) from a basis PENTRAN Sn model. For a PWR assembly eigenvalue problem, we explore the errors associated with this Cartesian discrete mesh representation, and perform an analysis to calculate a slope parameter that relates the pcm to the percent areal/volumetric deviation (areal → 2d problems, volumetric → 3d problems). This paper analysis demonstrates a linear relationship between pcm change and areal/volumetric deviation using Multigroup MCNP on a PWR assembly compared to a reference exact combinatorial MCNP geometry calculation. For the same MCNP multigroup problems, we also characterize this linear relationship in discrete ordinates (3d PENTRAN). Finally, for 3D Sn models, we show an application of corner fractioning, a volume-weighted recovery of underrepresented target fuel mass that reduced pcm error to < 100, compared to reference Monte Carlo, in the application to a PWR assembly. (author)
Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...
OptogenSIM: a 3D Monte Carlo simulation platform for light delivery design in optogenetics.
Liu, Yuming; Jacques, Steven L; Azimipour, Mehdi; Rogers, Jeremy D; Pashaie, Ramin; Eliceiri, Kevin W
2015-12-01
Optimizing light delivery for optogenetics is critical in order to accurately stimulate the neurons of interest while reducing nonspecific effects such as tissue heating or photodamage. Light distribution is typically predicted using the assumption of tissue homogeneity, which oversimplifies light transport in heterogeneous brain. Here, we present an open-source 3D simulation platform, OptogenSIM, which eliminates this assumption. This platform integrates a voxel-based 3D Monte Carlo model, generic optical property models of brain tissues, and a well-defined 3D mouse brain tissue atlas. The application of this platform in brain data models demonstrates that brain heterogeneity has moderate to significant impact depending on application conditions. Estimated light density contours can show the region of any specified power density in the 3D brain space and thus can help optimize the light delivery settings, such as the optical fiber position, fiber diameter, fiber numerical aperture, light wavelength and power. OptogenSIM is freely available and can be easily adapted to incorporate additional brain atlases. PMID:26713200
The impact of Monte Carlo simulation. A scientometric analysis of scholarly literature
A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications. (author)
Benchmark for a 3D Monte Carlo boiling water reactor fluence computational package - MF3D
A detailed three dimensional model of a quadrant of an operating BWR has been developed using MCNP to calculate flux spectrum and fluence levels at various locations in the reactor system. The calculational package, MF3D, was benchmarked against test data obtained over a complete fuel cycle of the host BWR. The test package included activation wires sensitive in both the fast and thermal ranges. Comparisons between the calculational results and test data are good to within ten percent, making the MF3D package an accurate tool for neutron and gamma fluence computation in BWR pressure vessel internals. (orig.)
Monte carlo analysis of multicolour LED light engine
Chakrabarti, Maumita; Thorseth, Anders; Jepsen, Jørgen;
2015-01-01
A new Monte Carlo simulation as a tool for analysing colour feedback systems is presented here to analyse the colour uncertainties and achievable stability in a multicolour dynamic LED system. The Monte Carlo analysis presented here is based on an experimental investigation of a multicolour LED...... light engine designed for white tuneable studio lighting. The measured sensitivities to the various factors influencing the colour uncertainty for similar system are incorporated. The method aims to provide uncertainties in the achievable chromaticity coordinates as output over the tuneable range, e.......g. expressed in correlated colour temperature (CCT) and chromaticity distance from Planckian locus (Duv), and colour rendering indices (CRIs) for that dynamic system. Data for the uncertainty in chromaticity is analysed in the u', v' (Uniform Chromaticity Scale Diagram) for light output by comparing the...
IMPROVEMENT OF 3D MONTE CARLO LOCALIZATION USING A DEPTH CAMERA AND TERRESTRIAL LASER SCANNER
S. Kanai
2015-05-01
Full Text Available Effective and accurate localization method in three-dimensional indoor environments is a key requirement for indoor navigation and lifelong robotic assistance. So far, Monte Carlo Localization (MCL has given one of the promising solutions for the indoor localization methods. Previous work of MCL has been mostly limited to 2D motion estimation in a planar map, and a few 3D MCL approaches have been recently proposed. However, their localization accuracy and efficiency still remain at an unsatisfactory level (a few hundreds millimetre error at up to a few FPS or is not fully verified with the precise ground truth. Therefore, the purpose of this study is to improve an accuracy and efficiency of 6DOF motion estimation in 3D MCL for indoor localization. Firstly, a terrestrial laser scanner is used for creating a precise 3D mesh model as an environment map, and a professional-level depth camera is installed as an outer sensor. GPU scene simulation is also introduced to upgrade the speed of prediction phase in MCL. Moreover, for further improvement, GPGPU programming is implemented to realize further speed up of the likelihood estimation phase, and anisotropic particle propagation is introduced into MCL based on the observations from an inertia sensor. Improvements in the localization accuracy and efficiency are verified by the comparison with a previous MCL method. As a result, it was confirmed that GPGPU-based algorithm was effective in increasing the computational efficiency to 10-50 FPS when the number of particles remain below a few hundreds. On the other hand, inertia sensor-based algorithm reduced the localization error to a median of 47mm even with less number of particles. The results showed that our proposed 3D MCL method outperforms the previous one in accuracy and efficiency.
Highlights: • Pu-239 based spectral history method was tested on 3D BWR single assembly case. • Burnup of a BWR fuel assembly was performed with the nodal code DYN3D. • Reference solution was obtained by coupled Monte-Carlo thermal-hydraulic code BGCore. • The proposed method accurately reproduces moderator density history effect for BWR test case. - Abstract: This research focuses on the verification of a recently developed methodology accounting for spectral history effects in 3D full core nodal simulations. The traditional deterministic core simulation procedure includes two stages: (1) generation of homogenized macroscopic cross section sets and (2) application of these sets to obtain a full 3D core solution with nodal codes. The standard approach adopts the branch methodology in which the branches represent all expected combinations of operational conditions as a function of burnup (main branch). The main branch is produced for constant, usually averaged, operating conditions (e.g. coolant density). As a result, the spectral history effects that associated with coolant density variation are not taken into account properly. Number of methods to solve this problem (such as micro-depletion and spectral indexes) were developed and implemented in modern nodal codes. Recently, we proposed a new and robust method to account for history effects. The methodology was implemented in DYN3D and involves modification of the few-group cross section sets. The method utilizes the local Pu-239 concentration as an indicator of spectral history. The method was verified for PWR and VVER applications. However, the spectrum variation in BWR core is more pronounced due to the stronger coolant density change. The purpose of the current work is investigating the applicability of the method to BWR analysis. The proposed methodology was verified against recently developed BGCore system, which couples Monte Carlo neutron transport with depletion and thermal-hydraulic solvers and
Current work presents a new methodology which uses Serpent Monte-Carlo (MC) code for generating multi-group beginning-of-life (BOL) cross section (XS) database file that is compatible with PARCS 3D reactor core simulator and allows simulation of transients with the FAST code system. The applicability of the methodology was tested on European Sodium-cooled Fast Reactor (ESFR) design with an oxide fuel proposed by CEA (France). The k-effective, power peaking factors and safety parameters (such as Doppler constant, coolant density coefficient, fuel axial expansion coefficient, diagrid expansion coefficients and control rod worth) calculated by PARCS/TRACE were compared with the results of the Serpent MC code. The comparison indicates overall reasonable agreement between conceptually different (deterministic and stochastic) codes. The new development makes it in principle possible to use the Serpent MC code for cross section generation for the PARCS code to perform transient analyses for fast reactors. The advantages and limitations of this methodology are discussed in the paper. (author)
Asymptotic analysis of spatial discretizations in implicit Monte Carlo
Densmore, Jeffery D [Los Alamos National Laboratory
2009-01-01
We perform an asymptotic analysis of spatial discretizations in Implicit Monte Carlo (IMC). We consider two asymptotic scalings: one that represents a time step that resolves the mean-free time, and one that corresponds to a fixed, optically large time step. We show that only the latter scaling results in a valid spatial discretization of the proper diffusion equation, and thus we conclude that IMC only yields accurate solutions when using optically large spatial cells if time steps are also optically large. We demonstrate the validity of our analysis with a set of numerical examples.
Asymptotic analysis of spatial discretizations in implicit Monte Carlo
Densmore, Jeffery D [Los Alamos National Laboratory
2008-01-01
We perform an asymptotic analysis of spatial discretizations in Implicit Monte Carlo (IMC). We consider two asymptotic scalings: one that represents a time step that resolves the mean-free time, and one that corresponds to a fixed, optically large time step. We show that only the latter scaling results in a valid spatial discretization of the proper diffusion equation, and thus we conclude that IMC only yields accurate solutions when using optically large spatial cells if time steps are also optically large, We demonstrate the validity of our analysis with a set of numerical examples.
Ziegle, Jens; Müller, Bernhard H.; Neumann, Bernd; Hoeschen, Christoph
2016-03-01
A new 3D breast computed tomography (CT) system is under development enabling imaging of microcalcifications in a fully uncompressed breast including posterior chest wall tissue. The system setup uses a steered electron beam impinging on small tungsten targets surrounding the breast to emit X-rays. A realization of the corresponding detector concept is presented in this work and it is modeled through Monte Carlo simulations in order to quantify first characteristics of transmission and secondary photons. The modeled system comprises a vertical alignment of linear detectors hold by a case that also hosts the breast. Detectors are separated by gaps to allow the passage of X-rays towards the breast volume. The detectors located directly on the opposite side of the gaps detect incident X-rays. Mechanically moving parts in an imaging system increase the duration of image acquisition and thus can cause motion artifacts. So, a major advantage of the presented system design is the combination of the fixed detectors and the fast steering electron beam which enable a greatly reduced scan time. Thereby potential motion artifacts are reduced so that the visualization of small structures such as microcalcifications is improved. The result of the simulation of a single projection shows high attenuation by parts of the detector electronics causing low count levels at the opposing detectors which would require a flat field correction, but it also shows a secondary to transmission ratio of all counted X-rays of less than 1 percent. Additionally, a single slice with details of various sizes was reconstructed using filtered backprojection. The smallest detail which was still visible in the reconstructed image has a size of 0.2mm.
The accuracy of Single-Photon Emission Computed Tomography images is degraded by physical effects, namely photon attenuation, Compton scatter and spatially varying collimator response. The 3D nature of these effects is usually neglected by the methods used to correct for these effects. To deal with the 3D nature of the problem, a 3D projector modeling the spread of photons in 3D can be used in iterative tomographic reconstruction. The 3D projector can be estimated analytically with some approximations, or using precise Monte Carlo simulations. This latter approach has not been applied to fully 3D reconstruction yet due to impractical storage and computation time. The goal of this paper was to determine the gain to be expected from fully 3D Monte Carlo (F3DMC) modeling of the projector in iterative reconstruction, compared to conventional 2D and 3D reconstruction methods. As a proof-of-concept, two small datasets were considered. The projections of the two phantoms were simulated using the Monte Carlo simulation code GATE, as well as the corresponding projector, by taking into account all physical effects (attenuation, scatter, camera point spread function) affecting the imaging process. F3DMC was implemented by using this 3D projector in a maximum likelihood expectation maximization (MLEM) iterative reconstruction. To assess the value of F3DMC, data were reconstructed using four methods: filtered backprojection, MLEM without attenuation correction (MLEM), MLEM with attenuation correction, Jaszczak scatter correction and 3D correction for depth-dependent spatial resolution using an analytical model (MLEMC) and F3DMC. Our results suggest that F3DMC improves mainly imaging sensitivity and signal-to-noise ratio (SNR): sensitivity is multiplied by about 103 and SNR is increased by 20-70% compared to MLEMC. Computation of a more robust projector and application of the method on more realistic datasets are currently under investigation
Review of neutron noise analysis theory by Monte Carlo simulation
Some debates on the theory of neutron noise analysis for reactor kinetic parameter measurement were found before 1970 but a report firmly clearing these debates has not been found, and a question was raised when neutron noise experiments for the TRIGA and HANARO reactors in Korea were performed. In order to clarify this question, the neutron noise experiment is simulated by the Monte Carlo method. This simulation confirms that the widely used equation is approximately valid and that the confusion was caused from the explanation on the derivation of the equation. Rossi-α technique is one of the representative methods of noise analyses for the reactor kinetic parameter measurement, but different opinions were raised for the chain reaction related term in the equation. The equation originally derived at the Los Alamos National Laboratory (LANL) has been widely accepted. However, the others were supported by strict mathematics and experiments as well, and the reason of discrepancy has not been clarified. Since it is the problem of basic concept before the effect of neutron energy or geometry is included, the Monte Carlo simulation for the simplest reactor model could clarify it. For this purpose, the experiment measuring the neutron noise is simulated, and it results that the original equation is approximately valid. However, it is judged that the explanation on the equation by the authors derived it for the first time is not so correct, but Orndoff who made the first experiment by the Ross-α technique explained it rather correctly
Monte Carlo analysis of Musashi TRIGA mark II reactor core
Matsumoto, Tetsuo [Atomic Energy Research Laboratory, Musashi Institute of Technology, Kawasaki, Kanagawa (Japan)
1999-08-01
The analysis of the TRIGA-II core at the Musashi Institute of Technology Research Reactor (Musashi reactor, 100 kW) was performed by the three-dimensional continuous-energy Monte Carlo code (MCNP4A). Effective multiplication factors (k{sub eff}) for the several fuel-loading patterns including the initial core criticality experiment, the fuel element and control rod reactivity worth as well as the neutron flux measurements were used in the validation process of the physical model and neutron cross section data from the ENDF/B-V evaluation. The calculated k{sub eff} overestimated the experimental data by about 1.0%{delta}k/k for both the initial core and the several fuel-loading arrangements. The calculated reactivity worths of control rod and fuel element agree well the measured ones within the uncertainties. The comparison of neutron flux distribution was consistent with the experimental ones which were measured by activation methods at the sample irradiation tubes. All in all, the agreement between the MCNP predictions and the experimentally determined values is good, which indicated that the Monte Carlo model is enough to simulate the Musashi TRIGA-II reactor core. (author)
Stratified source-sampling techniques for Monte Carlo eigenvalue analysis
In 1995, at a conference on criticality safety, a special session was devoted to the Monte Carlo ''Eigenvalue of the World'' problem. Argonne presented a paper, at that session, in which the anomalies originally observed in that problem were reproduced in a much simplified model-problem configuration, and removed by a version of stratified source-sampling. In this paper, stratified source-sampling techniques are generalized and applied to three different Eigenvalue of the World configurations which take into account real-world statistical noise sources not included in the model problem, but which differ in the amount of neutronic coupling among the constituents of each configuration. It is concluded that, in Monte Carlo eigenvalue analysis of loosely-coupled arrays, the use of stratified source-sampling reduces the probability of encountering an anomalous result over that if conventional source-sampling methods are used. However, this gain in reliability is substantially less than that observed in the model-problem results
Simulations with the Hybrid Monte Carlo algorithm: implementation and data analysis
Schaefer, Stefan
2011-01-01
This tutorial gives a practical introduction to the Hybrid Monte Carlo algorithm and the analysis of Monte Carlo data. The method is exemplified at the ϕ 4 theory, for which all steps from the derivation of the relevant formulae to the actual implementation in a computer program are discussed in detail. It concludes with the analysis of Monte Carlo data, in particular their auto-correlations.
Iterative Monte Carlo analysis of spin-dependent parton distributions
Sato, Nobuo; Melnitchouk, W.; Kuhn, S. E.; Ethier, J. J.; Accardi, A.; Jefferson Lab Angular Momentum Collaboration
2016-04-01
We present a comprehensive new global QCD analysis of polarized inclusive deep-inelastic scattering, including the latest high-precision data on longitudinal and transverse polarization asymmetries from Jefferson Lab and elsewhere. The analysis is performed using a new iterative Monte Carlo fitting technique which generates stable fits to polarized parton distribution functions (PDFs) with statistically rigorous uncertainties. Inclusion of the Jefferson Lab data leads to a reduction in the PDF errors for the valence and sea quarks, as well as in the gluon polarization uncertainty at x ≳0.1 . The study also provides the first determination of the flavor-separated twist-3 PDFs and the d2 moment of the nucleon within a global PDF analysis.
Iterative Monte Carlo analysis of spin-dependent parton distributions
Sato, Nobuo; Kuhn, S E; Ethier, J J; Accardi, A
2016-01-01
We present a comprehensive new global QCD analysis of polarized inclusive deep-inelastic scattering, including the latest high-precision data on longitudinal and transverse polarization asymmetries from Jefferson Lab and elsewhere. The analysis is performed using a new iterative Monte Carlo fitting technique which generates stable fits to polarized parton distribution functions (PDFs) with statistically rigorous uncertainties. Inclusion of the Jefferson Lab data leads to a reduction in the PDF errors for the valence and sea quarks, as well as in the gluon polarization uncertainty at $x \\gtrsim 0.1$. The study also provides the first determination of the flavor-separated twist-3 PDFs and the $d_2$ moment of the nucleon within a global PDF analysis.
Monte Carlo uncertainty analysis for an iron shielding benchmark experiment
Fischer, U.; Tsige-Tamirat, H. [Association Euratom-FZK Forschungszentrum Karlsruhe (Germany); Perel, R.L. [Hebrew Univ., Jerusalem (Israel); Wu, Y. [Institute of Plasma Physics, Heifi (China)
1998-07-01
This work is devoted to the computational uncertainty analysis of an iron benchmark experiment having been performed previously at the Technical University of Dresden (TUD). The analysis is based on the use of a novel Monte Carlo approach for calculating sensitivities of point detectors and focuses on the new {sup 56}Fe evaluation of the European Fusion File EFF-3. The calculated uncertainties of the neutron leakage fluxes are shown to be significantly smaller than with previous data. Above 5 MeV the calculated uncertainties are larger than the experimental ones. As the measured neutron leakage fluxes are underestimated by about 10 - 20 % in that energy range, it is concluded that the {sup 56}Fe cross-section data have to be further improved. (authors)
A model of a gamma sterilizer was built using the ITS/ACCEPT Monte Carlo code and verified through dosimetry. Individual dosimetry measurements in homogeneous material were pooled to represent larger bodies that could be simulated in a reasonable time. With the assumptions and simplifications described, dose predictions were within 2-5% of dosimetry. The model was used to simulate product movement through the sterilizer and to predict information useful for process optimization and facility design
On Monte Carlo Simulation and Analysis of Electricity Markets
This dissertation is about how Monte Carlo simulation can be used to analyse electricity markets. There are a wide range of applications for simulation; for example, players in the electricity market can use simulation to decide whether or not an investment can be expected to be profitable, and authorities can by means of simulation find out which consequences a certain market design can be expected to have on electricity prices, environmental impact, etc. In the first part of the dissertation, the focus is which electricity market models are suitable for Monte Carlo simulation. The starting point is a definition of an ideal electricity market. Such an electricity market is partly practical from a mathematical point of view (it is simple to formulate and does not require too complex calculations) and partly it is a representation of the best possible resource utilisation. The definition of the ideal electricity market is followed by analysis how the reality differs from the ideal model, what consequences the differences have on the rules of the electricity market and the strategies of the players, as well as how non-ideal properties can be included in a mathematical model. Particularly, questions about environmental impact, forecast uncertainty and grid costs are studied. The second part of the dissertation treats the Monte Carlo technique itself. To reduce the number of samples necessary to obtain accurate results, variance reduction techniques can be used. Here, six different variance reduction techniques are studied and possible applications are pointed out. The conclusions of these studies are turned into a method for efficient simulation of basic electricity markets. The method is applied to some test systems and the results show that the chosen variance reduction techniques can produce equal or better results using 99% fewer samples compared to when the same system is simulated without any variance reduction technique. More complex electricity market models
Neutronic analysis of the PULSTAR reactor using Monte Carlo simulations
Neutronic analysis of the PULSTAR nuclear reactor was performed in support of its utilization and power upgrade from 1-MWth to 2-MWth. The PULSTAR is an open pool research reactor that is currently fueled with UO2 enriched to 4% in U-235. Detailed models were constructed of its core using the MCNP6 Monte Carlo code and its standard nuclear data libraries. The models covered all eight variations of the core starting with the first critical core in 1972 to the current core that was configured in 2011. Three dimensional heterogeneous models were constructed that faithfully reflected the geometry of the core and its surroundings using the original as-built engineering drawings. The Monte Carlo simulations benefited extensively from measurements that were performed upon the loading of each core and its subsequent operation. This includes power distribution and peaking measurements, depletion measurements (reflecting a core's excess reactivity), and measurements of reactivity feedback coefficients. Furthermore, to support the PULSTAR's fuel needs, the simulations explored the utilization of locally existing inventory of fresh UO2 fuel that is enriched to 6% in U-235. The analysis shows reasonable agreement between the results of the MCNP6 simulations and the available measured data. In general, most discrepancies between simulations and measurements may be attributed to the limited knowledge of the exact conditions of the historical measurements and the procedures used to analyze the measured data. Nonetheless, the results indicate the ability of the constructed models to support safety analysis and licensing action in relation to the on-going upgrades of the PULSTAR reactor. (author)
Implementation and analysis of an adaptive multilevel Monte Carlo algorithm
Hoel, Hakon
2014-01-01
We present an adaptive multilevel Monte Carlo (MLMC) method for weak approximations of solutions to Itô stochastic dierential equations (SDE). The work [11] proposed and analyzed an MLMC method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a single level Euler-Maruyama Monte Carlo method from O(TOL-3) to O(TOL-2 log(TOL-1)2) for a mean square error of O(TOL2). Later, the work [17] presented an MLMC method using a hierarchy of adaptively re ned, non-uniform time discretizations, and, as such, it may be considered a generalization of the uniform time discretizationMLMC method. This work improves the adaptiveMLMC algorithms presented in [17] and it also provides mathematical analysis of the improved algorithms. In particular, we show that under some assumptions our adaptive MLMC algorithms are asymptotically accurate and essentially have the correct complexity but with improved control of the complexity constant factor in the asymptotic analysis. Numerical tests include one case with singular drift and one with stopped diusion, where the complexity of a uniform single level method is O(TOL-4). For both these cases the results con rm the theory, exhibiting savings in the computational cost for achieving the accuracy O(TOL) from O(TOL-3) for the adaptive single level algorithm to essentially O(TOL-2 log(TOL-1)2) for the adaptive MLMC algorithm. © 2014 by Walter de Gruyter Berlin/Boston 2014.
Status of vectorized Monte Carlo for particle transport analysis
The conventional particle transport Monte Carlo algorithm is ill suited for modern vector supercomputers because the random nature of the particle transport process in the history based algorithm inhibits construction of vectors. An alternative, event-based algorithm is suitable for vectorization and has been used recently to achieve impressive gains in performance on vector supercomputers. This review describes the event-based algorithm and several variations of it. Implementations of this algorithm for applications in particle transport are described, and their relative merits are discussed. The implementation of Monte Carlo methods on multiple vector parallel processors is considered, as is the potential of massively parallel processors for Monte Carlo particle transport simulations
To model key aspects of surface morphology evolution and to overcome one of the main barriers to the implementation of extreme ultraviolet lithography in semiconductor processing, the 3D Monte Carlo simulation of ion-beam deposition on pit-type defects was performed. Typical pit defects have depths in the 5–20 nm range and are about 10 times that wide. The aspect ratio of a defect cross section defined as depth divided by the full width at half maximum was used to measure the defect profile (decoration) as a function of film thickness. Previous attempts to model this system used 2D level set methods; 3D calculations using these methods were found to be too computationally intensive. In an effort to model the system in 3D the simulation of this study used the Solid-on-Solid aggregation model to deposit particles onto initial substrate defects. Surface diffusion was then simulated to relax the defect. Aspect ratio decay data was collected from the simulated defects and analyzed. The model was validated for defect evolution by comparing simulations to the experimental scanning transmission electron microscopy data. The statistics of effective activation energy were considered to show that observed defects have important geometric differences which define a unique aspect ratio decay path. Close fitting to the observed case was utilized to validate Monte Carlo physical models of thin film growth for use in predicting the multilayer profile of pit-type defects. - Highlights: • Model pit-type defects in multilayers using Monte Carlo methods. • Simulation substrates derived from Atomic Force Microscopy (AFM) scan defects • AFM scanned defect simulations return close fitting to the physical observations • Activation energy statistics on the surface show unique aspect ratio decay paths. • A test using of the fitting case applied to a different situation works accurately
3-D Monte Carlo neutron-photon transport code JMCT and its algorithms
JMCT Monte Carlo neutron and photon transport code has been developed which is based on the JCOGIN toolbox. JCOGIN includes the geometry operation, tally, the domain decomposition and the parallel computation about particle (MPI) and spatial domain (OpenMP) etc. The viewdata of CAD is equipped in JMCT preprocessor. The full-core pin-mode, which is from Chinese Qinshan-II nuclear power station, is design and simulated by JMCT. The detail pin-power distribution and keff results are shown in this paper. (author)
TART2000 is a coupled neutron-photon, 3 Dimensional, combinatorial geometry, time dependent Monte Carlo radiation transport code. This code can run on any modern computer. It is a complete system to assist you with input Preparation, running Monte Carlo calculations, and analysis of output results. TART2000 is also incredibly FAST; if you have used similar codes, you will be amazed at how fast this code is compared to other similar codes. Use of the entire system can save you a great deal of time and energy. TART2000 is distributed on CD. This CD contains on-line documentation for all codes included in the system, the codes configured to run on a variety of computers, and many example problems that you can use to familiarize yourself with the system. TART2000 completely supersedes all older versions of TART, and it is strongly recommended that users only use the most recent version of TART2000 and its data files
Cullen, D E
1998-11-22
TART98 is a coupled neutron-photon, 3 Dimensional, combinatorial geometry, time dependent Monte Carlo radiation transport code. This code can run on any modern computer. It is a complete system to assist you with input preparation, running Monte Carlo calculations, and analysis of output results. TART98 is also incredibly FAST; if you have used similar codes, you will be amazed at how fast this code is compared to other similar codes. Use of the entire system can save you a great deal of time and energy. TART98 is distributed on CD. This CD contains on-line documentation for all codes included in the system, the codes configured to run on a variety of computers, and many example problems that you can use to familiarize yourself with the system. TART98 completely supersedes all older versions of TART, and it is strongly recommended that users only use the most recent version of TART98 and its data files.
The Monte Carlo SRNA-VOX code for 3D proton dose distribution in voxelized geometry using CT data
Ilic, Radovan D [Laboratory of Physics (010), Vinca Institute of Nuclear Sciences, PO Box 522, 11001 Belgrade (Serbia and Montenegro); Spasic-Jokic, Vesna [Laboratory of Physics (010), Vinca Institute of Nuclear Sciences, PO Box 522, 11001 Belgrade (Serbia and Montenegro); Belicev, Petar [Laboratory of Physics (010), Vinca Institute of Nuclear Sciences, PO Box 522, 11001 Belgrade (Serbia and Montenegro); Dragovic, Milos [Center for Nuclear Medicine MEDICA NUCLEARE, Bulevar Despota Stefana 69, 11000 Belgrade (Serbia and Montenegro)
2005-03-07
This paper describes the application of the SRNA Monte Carlo package for proton transport simulations in complex geometry and different material compositions. The SRNA package was developed for 3D dose distribution calculation in proton therapy and dosimetry and it was based on the theory of multiple scattering. The decay of proton induced compound nuclei was simulated by the Russian MSDM model and our own using ICRU 63 data. The developed package consists of two codes: the SRNA-2KG, which simulates proton transport in combinatorial geometry and the SRNA-VOX, which uses the voxelized geometry using the CT data and conversion of the Hounsfield's data to tissue elemental composition. Transition probabilities for both codes are prepared by the SRNADAT code. The simulation of the proton beam characterization by multi-layer Faraday cup, spatial distribution of positron emitters obtained by the SRNA-2KG code and intercomparison of computational codes in radiation dosimetry, indicate immediate application of the Monte Carlo techniques in clinical practice. In this paper, we briefly present the physical model implemented in the SRNA package, the ISTAR proton dose planning software, as well as the results of the numerical experiments with proton beams to obtain 3D dose distribution in the eye and breast tumour.
The Monte Carlo SRNA-VOX code for 3D proton dose distribution in voxelized geometry using CT data
Ilic, Radovan D.; Spasic-Jokic, Vesna; Belicev, Petar; Dragovic, Milos
2005-03-01
This paper describes the application of the SRNA Monte Carlo package for proton transport simulations in complex geometry and different material compositions. The SRNA package was developed for 3D dose distribution calculation in proton therapy and dosimetry and it was based on the theory of multiple scattering. The decay of proton induced compound nuclei was simulated by the Russian MSDM model and our own using ICRU 63 data. The developed package consists of two codes: the SRNA-2KG, which simulates proton transport in combinatorial geometry and the SRNA-VOX, which uses the voxelized geometry using the CT data and conversion of the Hounsfield's data to tissue elemental composition. Transition probabilities for both codes are prepared by the SRNADAT code. The simulation of the proton beam characterization by multi-layer Faraday cup, spatial distribution of positron emitters obtained by the SRNA-2KG code and intercomparison of computational codes in radiation dosimetry, indicate immediate application of the Monte Carlo techniques in clinical practice. In this paper, we briefly present the physical model implemented in the SRNA package, the ISTAR proton dose planning software, as well as the results of the numerical experiments with proton beams to obtain 3D dose distribution in the eye and breast tumour.
The Monte Carlo SRNA-VOX code for 3D proton dose distribution in voxelized geometry using CT data
This paper describes the application of the SRNA Monte Carlo package for proton transport simulations in complex geometry and different material compositions. The SRNA package was developed for 3D dose distribution calculation in proton therapy and dosimetry and it was based on the theory of multiple scattering. The decay of proton induced compound nuclei was simulated by the Russian MSDM model and our own using ICRU 63 data. The developed package consists of two codes: the SRNA-2KG, which simulates proton transport in combinatorial geometry and the SRNA-VOX, which uses the voxelized geometry using the CT data and conversion of the Hounsfield's data to tissue elemental composition. Transition probabilities for both codes are prepared by the SRNADAT code. The simulation of the proton beam characterization by multi-layer Faraday cup, spatial distribution of positron emitters obtained by the SRNA-2KG code and intercomparison of computational codes in radiation dosimetry, indicate immediate application of the Monte Carlo techniques in clinical practice. In this paper, we briefly present the physical model implemented in the SRNA package, the ISTAR proton dose planning software, as well as the results of the numerical experiments with proton beams to obtain 3D dose distribution in the eye and breast tumour
LISA data analysis using Markov chain Monte Carlo methods
The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low-frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50 000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analysis, and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we supercool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions
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)
Bergmann, Ryan
Graphics processing units, or GPUs, have gradually increased in computational power from the small, job-specific boards of the early 1990s to the programmable powerhouses of today. Compared to more common central processing units, or CPUs, GPUs have a higher aggregate memory bandwidth, much higher floating-point operations per second (FLOPS), and lower energy consumption per FLOP. Because one of the main obstacles in exascale computing is power consumption, many new supercomputing platforms are gaining much of their computational capacity by incorporating GPUs into their compute nodes. Since CPU-optimized parallel algorithms are not directly portable to GPU architectures (or at least not without losing substantial performance), transport codes need to be rewritten to execute efficiently on GPUs. Unless this is done, reactor simulations cannot take full advantage of these new supercomputers. WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed in this work as to efficiently implement a continuous energy Monte Carlo neutron transport algorithm on a GPU. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo Method, namely, very few physical and geometrical simplifications. WARP is able to calculate multiplication factors, flux tallies, and fission source distributions for time-independent problems, and can run in both criticality or fixed source modes. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. WARP uses an event-based algorithm, but with some important differences. Moving data is expensive, so WARP uses a remapping vector of pointer/index pairs to direct GPU threads to the data they need to access. The remapping vector is sorted by reaction type after every transport iteration using a high-efficiency parallel radix sort, which serves to keep the
COLLI-PTB, Neutron Fluence Spectra for 3-D Collimator System by Monte-Carlo
1 - Description of program or function: For optimizing collimator systems (shieldings) for fast neutrons with energies between 10 KeV and 20 MeV. Only elastic and inelastic neutron scattering processes are involved. Isotropic angular distribution for inelastic scattering in the center of mass system is assumed. 2 - Method of solution: The Monte Carlo method with importance sampling technique, splitting and Russian Roulette is used. The neutron attenuation and scattering kinematics is taken into account. 3 - Restrictions on the complexity of the problem: Energy range from 10 KeV to 20 MeV. For the output spectra any bin width is possible. The output spectra are confined to 40 equidistant channels
A Multivariate Time Series Method for Monte Carlo Reactor Analysis
A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor
Analysis of error in Monte Carlo transport calculations
The Monte Carlo method for neutron transport calculations suffers, in part, because of the inherent statistical errors associated with the method. Without an estimate of these errors in advance of the calculation, it is difficult to decide what estimator and biasing scheme to use. Recently, integral equations have been derived that, when solved, predicted errors in Monte Carlo calculations in nonmultiplying media. The present work allows error prediction in nonanalog Monte Carlo calculations of multiplying systems, even when supercritical. Nonanalog techniques such as biased kernels, particle splitting, and Russian Roulette are incorporated. Equations derived here allow prediction of how much a specific variance reduction technique reduces the number of histories required, to be weighed against the change in time required for calculation of each history. 1 figure, 1 table
Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis
Hyung Jin Shim
2015-01-01
Full Text Available The α-k iteration method which searches the fundamental mode alpha-eigenvalue via iterative updates of the fission source distribution has been successfully used for the Monte Carlo (MC alpha-static calculations of supercritical systems. However, the α-k iteration method for the deep subcritical system analysis suffers from a gigantic number of neutron generations or a huge neutron weight, which leads to an abnormal termination of the MC calculations. In order to stably estimate the prompt neutron decay constant (α of prompt subcritical systems regardless of subcriticality, we propose a new MC alpha-static calculation method named as the α iteration algorithm. The new method is derived by directly applying the power method for the α-mode eigenvalue equation and its calculation stability is achieved by controlling the number of time source neutrons which are generated in proportion to α divided by neutron speed in MC neutron transport simulations. The effectiveness of the α iteration algorithm is demonstrated for two-group homogeneous problems with varying the subcriticality by comparisons with analytic solutions. The applicability of the proposed method is evaluated for an experimental benchmark of the thorium-loaded accelerator-driven system.
Monte Carlo simulation for moment-independent sensitivity analysis
The moment-independent sensitivity analysis (SA) is one of the most popular SA techniques. It aims at measuring the contribution of input variable(s) to the probability density function (PDF) of model output. However, compared with the variance-based one, robust and efficient methods are less available for computing the moment-independent SA indices (also called delta indices). In this paper, the Monte Carlo simulation (MCS) methods for moment-independent SA are investigated. A double-loop MCS method, which has the advantages of high accuracy and easy programming, is firstly developed. Then, to reduce the computational cost, a single-loop MCS method is proposed. The later method has several advantages. First, only a set of samples is needed for computing all the indices, thus it can overcome the problem of “curse of dimensionality”. Second, it is suitable for problems with dependent inputs. Third, it is purely based on model output evaluation and density estimation, thus can be used for model with high order (>2) interactions. At last, several numerical examples are introduced to demonstrate the advantages of the proposed methods.
Further experience in Bayesian analysis using Monte Carlo Integration
Dijk, Herman; Kloek, Teun
1980-01-01
textabstractAn earlier paper [Kloek and Van Dijk (1978)] is extended in three ways. First, Monte Carlo integration is performed in a nine-dimensional parameter space of Klein's model I [Klein (1950)]. Second, Monte Carlo is used as a tool for the elicitation of a uniform prior on a finite region by making use of several types of prior information. Third, special attention is given to procedures for the construction of importance functions which make use of nonlinear optimization methods. *1 T...
Monte Carlo analysis of radiative transport in oceanographic lidar measurements
Cupini, E.; Ferro, G. [ENEA, Divisione Fisica Applicata, Centro Ricerche Ezio Clementel, Bologna (Italy); Ferrari, N. [Bologna Univ., Bologna (Italy). Dipt. Ingegneria Energetica, Nucleare e del Controllo Ambientale
2001-07-01
The analysis of oceanographic lidar systems measurements is often carried out with semi-empirical methods, since there is only a rough understanding of the effects of many environmental variables. The development of techniques for interpreting the accuracy of lidar measurements is needed to evaluate the effects of various environmental situations, as well as of different experimental geometric configurations and boundary conditions. A Monte Carlo simulation model represents a tool that is particularly well suited for answering these important questions. The PREMAR-2F Monte Carlo code has been developed taking into account the main molecular and non-molecular components of the marine environment. The laser radiation interaction processes of diffusion, re-emission, refraction and absorption are treated. In particular are considered: the Rayleigh elastic scattering, produced by atoms and molecules with small dimensions with respect to the laser emission wavelength (i.e. water molecules), the Mie elastic scattering, arising from atoms or molecules with dimensions comparable to the laser wavelength (hydrosols), the Raman inelastic scattering, typical of water, the absorption of water, inorganic (sediments) and organic (phytoplankton and CDOM) hydrosols, the fluorescence re-emission of chlorophyll and yellow substances. PREMAR-2F is an extension of a code for the simulation of the radiative transport in atmospheric environments (PREMAR-2). The approach followed in PREMAR-2 was to combine conventional Monte Carlo techniques with analytical estimates of the probability of the receiver to have a contribution from photons coming back after an interaction in the field of view of the lidar fluorosensor collecting apparatus. This offers an effective mean for modelling a lidar system with realistic geometric constraints. The retrieved semianalytic Monte Carlo radiative transfer model has been developed in the frame of the Italian Research Program for Antarctica (PNRA) and it is
Ulmer, W.; Pyyry, J.; Kaissl, W.
2005-04-01
Based on previous publications on a triple Gaussian analytical pencil beam model and on Monte Carlo calculations using Monte Carlo codes GEANT-Fluka, versions 95, 98, 2002, and BEAMnrc/EGSnrc, a three-dimensional (3D) superposition/convolution algorithm for photon beams (6 MV, 18 MV) is presented. Tissue heterogeneity is taken into account by electron density information of CT images. A clinical beam consists of a superposition of divergent pencil beams. A slab-geometry was used as a phantom model to test computed results by measurements. An essential result is the existence of further dose build-up and build-down effects in the domain of density discontinuities. These effects have increasing magnitude for field sizes densities <=0.25 g cm-3, in particular with regard to field sizes considered in stereotaxy. They could be confirmed by measurements (mean standard deviation 2%). A practical impact is the dose distribution at transitions from bone to soft tissue, lung or cavities. This work has partially been presented at WC 2003, Sydney.
Immuno-PET imaging can be used to assess the pharmacokinetic in radioimmunotherapy. When using iodine-124, PET quantitative imaging is limited by physics-based degrading factors within the detection system and the object, such as the long positron range in water and the complex spectrum of gamma photons. The objective of this thesis was to develop a fully 3D tomographic reconstruction method (S(MC)2PET) using Monte Carlo simulations for estimating the system matrix, in the context of preclinical imaging with iodine-124. The Monte Carlo simulation platform GATE was used for that respect. Several complexities of system matrices were calculated, with at least a model of the PET system response function. Physics processes in the object was either neglected or taken into account using a precise or a simplified object description. The impact of modelling refinement and statistical variance related to the system matrix elements was evaluated on final reconstructed images. These studies showed that a high level of complexity did not always improve qualitative and quantitative results, owing to the high-variance of the associated system matrices. (author)
OMEGA, Subcritical and Critical Neutron Transport in General 3-D Geometry by Monte-Carlo
1 - Description of problem or function: OMEGA is a Monte Carlo code for the solution of the stationary neutron transport equation with k-eff as the Eigenvalue. A three-dimensional geometry is permitted consisting of a very general arrangement of three basic shapes (columns with circular, rectangular, or hexagonal cross section with a finite height and different material layers along their axes). The main restriction is that all the basic shapes must have parallel axes. Most real arrangements of fissile material inside and outside a reactor (e.g., in a fuel storage or transport container) can be described without approximation. The main field of application is the estimation of criticality safety. Many years of experience and comparison with reference cases have shown that the code together with the built-in cross section libraries gives reliable results. The following results can be calculated: - the effective multiplication factor k-eff; - the flux distribution; - reaction rates; - spatially and energetically condensed cross sections for later use in a subsequent OMEGA run. A running job may be interrupted and continued later, possibly with an increased number of batches for an improved statistical accuracy. The geometry as well as the k-eff results may be visualized. The use of the code is demonstrated by many illustrating examples. 2 - Method of solution: The Monte Carlo method is used with neutrons starting from an initial source distribution. The histories of a generation (or batch) of neutrons are followed from collision to collision until the histories are terminated by capture, fission, or leakage. For the solution of the Eigenvalue problem, the starting positions of the neutrons for a given generation are determined by the fission points of the preceding generation. The summation of the results starts only after some initial generations when the spatial part of the fission source has converged. At present the code uses the BNAB-78 subgroup library of the
Monte-Carlo Application for Nondestructive Nuclear Waste Analysis
Carasco, C.; Engels, R.; Frank, M.; Furletov, S.; Furletova, J.; Genreith, C.; Havenith, A.; Kemmerling, G.; Kettler, J.; Krings, T.; Ma, J.-L.; Mauerhofer, E.; Neike, D.; Payan, E.; Perot, B.; Rossbach, M.; Schitthelm, O.; Schumann, M.; Vasquez, R.
2014-06-01
Radioactive waste has to undergo a process of quality checking in order to check its conformance with national regulations prior to its transport, intermediate storage and final disposal. Within the quality checking of radioactive waste packages non-destructive assays are required to characterize their radio-toxic and chemo-toxic contents. The Institute of Energy and Climate Research - Nuclear Waste Management and Reactor Safety of the Forschungszentrum Jülich develops in the framework of cooperation nondestructive analytical techniques for the routine characterization of radioactive waste packages at industrial-scale. During the phase of research and development Monte Carlo techniques are used to simulate the transport of particle, especially photons, electrons and neutrons, through matter and to obtain the response of detection systems. The radiological characterization of low and intermediate level radioactive waste drums is performed by segmented γ-scanning (SGS). To precisely and accurately reconstruct the isotope specific activity content in waste drums by SGS measurement, an innovative method called SGSreco was developed. The Geant4 code was used to simulate the response of the collimated detection system for waste drums with different activity and matrix configurations. These simulations allow a far more detailed optimization, validation and benchmark of SGSreco, since the construction of test drums covering a broad range of activity and matrix properties is time consuming and cost intensive. The MEDINA (Multi Element Detection based on Instrumental Neutron Activation) test facility was developed to identify and quantify non-radioactive elements and substances in radioactive waste drums. MEDINA is based on prompt and delayed gamma neutron activation analysis (P&DGNAA) using a 14 MeV neutron generator. MCNP simulations were carried out to study the response of the MEDINA facility in terms of gamma spectra, time dependence of the neutron energy spectrum
A Markov chain Monte Carlo analysis of the CMSSM
We perform a comprehensive exploration of the Constrained MSSM parameter space employing a Markov Chain Monte Carlo technique and a Bayesian analysis. We compute superpartner masses and other collider observables, as well as a cold dark matter abundance, and compare them with experimental data. We include uncertainties arising from theoretical approximations as well as from residual experimental errors of relevant Standard Model parameters. We delineate probability distributions of the CMSSM parameters, the collider and cosmological observables as well as a dark matter direct detection cross section. The 68% probability intervals of the CMSSM parameters are: 0.52TeV 1/2 0 0 g-tilde q-tildeR χ1± -9 s→μ+μ-) -8, 1.9 x 10-10 μSUSY -10 and 1 x 10-10 pb SIp -8 pb for direct WIMP detection. We highlight a complementarity between LHC and WIMP dark matter searches in exploring the CMSSM parameter space. We further expose a number of correlations among the observables, in particular between BR(Bs→μ+μ-) and BR(B-bar →Xsγ) or σSIp. Once SUSY is discovered, this and other correlations may prove helpful in distinguishing the CMSSM from other supersymmetric models. We investigate the robustness of our results in terms of the assumed ranges of CMSSM parameters and the effect of the (g-2)μ anomaly which shows some tension with the other observables. We find that the results for m0, and the observables which strongly depend on it, are sensitive to our assumptions, while our conclusions for the other variables are robust
Benchmark analysis of the TRIGA MARK II research reactor using Monte Carlo techniques
This study deals with the neutronic analysis of the current core configuration of a 3-MW TRIGA MARK II research reactor at Atomic Energy Research Establishment (AERE), Savar, Dhaka, Bangladesh and validation of the results by benchmarking with the experimental, operational and available Final Safety Analysis Report (FSAR) values. The 3-D continuous-energy Monte Carlo code MCNP4C was used to develop a versatile and accurate full-core model of the TRIGA core. The model represents in detail all components of the core with literally no physical approximation. All fresh fuel and control elements as well as the vicinity of the core were precisely described. Continuous energy cross-section data from ENDF/B-VI and ENDF/B-V and S(α,β) scattering functions from the ENDF/B-VI library were used. The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics was established by benchmarking the TRIGA experiments. The effective multiplication factor, power distribution and peaking factors, neutron flux distribution, and reactivity experiments comprising control rod worths, critical rod height, excess reactivity and shutdown margin were used in the validation process. The MCNP predictions and the experimentally determined values are found to be in very good agreement, which indicates that the simulation of TRIGA reactor is treated adequately
Benchmark of Atucha-2 PHWR RELAP5-3D control rod model by Monte Carlo MCNP5 core calculation
Pecchia, M.; D' Auria, F. [San Piero A Grado Nuclear Research Group GRNSPG, Univ. of Pisa, via Diotisalvi, 2, 56122 - Pisa (Italy); Mazzantini, O. [Nucleo-electrica Argentina Societad Anonima NA-SA, Buenos Aires (Argentina)
2012-07-01
Atucha-2 is a Siemens-designed PHWR reactor under construction in the Republic of Argentina. Its geometrical complexity and peculiarities require the adoption of advanced Monte Carlo codes for performing realistic neutronic simulations. Therefore core models of Atucha-2 PHWR were developed using MCNP5. In this work a methodology was set up to collect the flux in the hexagonal mesh by which the Atucha-2 core is represented. The scope of this activity is to evaluate the effect of obliquely inserted control rod on neutron flux in order to validate the RELAP5-3D{sup C}/NESTLE three dimensional neutron kinetic coupled thermal-hydraulic model, applied by GRNSPG/UNIPI for performing selected transients of Chapter 15 FSAR of Atucha-2. (authors)
The percolation threshold problem in insulating polymers filled with exfoliated conductive graphite nanoplatelets (GNPs) is re-examined in this 3D Monte Carlo simulation study. GNPs are modelled as solid discs wrapped by electrically conductive layers of certain thickness which represent half of the electron tunnelling distance. Two scenarios of 'impenetrable' and 'penetrable' GNPs are implemented in the simulations. The percolation thresholds for both scenarios are plotted versus the electron tunnelling distance for various GNP thicknesses. The assumption of successful dispersion and exfoliation, and the incorporation of the electron tunnelling phenomenon in the impenetrable simulations suggest that the simulated percolation thresholds are lower bounds for any experimental study. Finally, the simulation results are discussed and compared with other experimental studies.
TIMOC-72, 3-D Time-Dependent Homogeneous or Inhomogeneous Neutron Transport by Monte-Carlo
1 - Nature of physical problem solved: TIMOC solves the energy and time dependent (or stationary) homogeneous or inhomogeneous neutron transport equation in three-dimensional geometries. The program can treat all commonly used scattering kernels, such as absorption, fission, isotropic and anisotropic elastic scattering, level excitation, the evaporation model, and the energy transfer matrix model, which includes (n,2n) reactions. The exchangeable geometry routines consist at present of (a) periodical multilayer slab, spherical and cylindrical lattices, (b) an elaborate three-dimensional cylindrical geometry which allows all kinds of subdivisions, (c) the very flexible O5R geometry routine which is able to describe any body combinations with surfaces of second order. The program samples the stationary or time-energy-region dependent fluxes as well as the transmission ratios between geometrical regions and the following integral quantities or eigenvalues, the leakage rate, the slowing down density, the production to source ratio, the multiplication factor based on flux and collision estimator, the mean production time, the mean destruction time, time distribution of production and destruction, the fission rates, the energy dependent absorption rates, the energy deposition due to elastic scattering for the different geometrical regions. 2 - Method of solution: TIMOC is a Monte Carlo program and uses several, partially optional variance reducing techniques, such as the method of expected values (weight factor), Russian roulette, the method of fractional generated neutrons, double sampling, semi-systematic sampling and the method of expected leakage probability. Within the neutron lifetime a discrete energy value is given after each collision process. The nuclear data input is however done by group averaged cross sections. The program can generate the neutron fluxes either resulting from an external source or in the form of fundamental mode distributions by a special
MONTE CARLO SIMULATION APPLIED TO ECONOMIC AND FINANCIAL ANALYSIS OF AN AGRIBUSINESS PROJECT
Danilo Simões; Lucas Raul Scherrer
2014-01-01
In practice, all management decisions involving an organization, regardless of size, have uncertainties which lead to different levels of risk. Monte Carlo simulation allows risk analysis by designing probabilistic models. From a deterministic model of economic viability indicators, commonly used for decision investment projects, it was developed a probabilistic model with Monte Carlo method simulations in order to carry out economic and financial analysis of an agroindustrial ...
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)
Highlights: • Code works based on Monte Carlo and escape probability methods. • Sensitivity of Dancoff factor to number of energy groups and type and arrangement of neighbor’s fuels is considered. • Sensitivity of Dancoff factor to control rod’s height is considered. • Dancoff factor high efficiency is achieved versus method sampling neutron flight direction from the fuel surface. • Sensitivity of K to Dancoff factor is considered. - Abstract: Evaluation of multigroup constants in reactor calculations depends on several parameters, the Dancoff factor amid them is used for calculation of the resonance integral as well as flux depression in the resonance region in the heterogeneous systems. This paper focuses on the computer program (MCDAN-3D) developed for calculation of the multigroup black and gray Dancoff factor in three dimensional geometry based on Monte Carlo and escape probability methods. The developed program is capable to calculate the Dancoff factor for an arbitrary arrangement of fuel rods with different cylindrical fuel dimensions and control rods with various lengths inserted in the reactor core. The initiative calculates the black and gray Dancoff factor versus generated neutron flux in cosine and constant shapes in axial fuel direction. The effects of clad and moderator are followed by studying of Dancoff factor’s sensitivity with variation of fuel arrangements and neutron’s energy group for CANDU37 and VVER1000 fuel assemblies. MCDAN-3D outcomes poses excellent agreement with the MCNPX code. The calculated Dancoff factors are then used for cell criticality calculations by the WIMS code
Analytical band Monte Carlo analysis of electron transport in silicene
Yeoh, K. H.; Ong, D. S.; Ooi, C. H. Raymond; Yong, T. K.; Lim, S. K.
2016-06-01
An analytical band Monte Carlo (AMC) with linear energy band dispersion has been developed to study the electron transport in suspended silicene and silicene on aluminium oxide (Al2O3) substrate. We have calibrated our model against the full band Monte Carlo (FMC) results by matching the velocity-field curve. Using this model, we discover that the collective effects of charge impurity scattering and surface optical phonon scattering can degrade the electron mobility down to about 400 cm2 V‑1 s‑1 and thereafter it is less sensitive to the changes of charge impurity in the substrate and surface optical phonon. We also found that further reduction of mobility to ∼100 cm2 V‑1 s‑1 as experimentally demonstrated by Tao et al (2015 Nat. Nanotechnol. 10 227) can only be explained by the renormalization of Fermi velocity due to interaction with Al2O3 substrate.
Monte-Carlo application for nondestructive nuclear waste analysis
The Institute of Energy and Climate Research - Nuclear Waste Management and Reactor Safety of the Forschungszentrum Juelich develops in the framework of cooperation nondestructive analytical techniques for the routine characterization of radioactive waste packages at industrial-scale. During the phase of research and development Monte Carlo techniques are used to simulate the transport of particle, especially photons, electrons and neutrons, through matter in order to obtain the response of detection systems
Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept
Thipphavong, David
2010-01-01
Safe separation of aircraft is a primary objective of any air traffic control system. An accelerated Monte Carlo approach was developed to assess the level of safety provided by a proposed next-generation air traffic control system. It combines features of fault tree and standard Monte Carlo methods. It runs more than one order of magnitude faster than the standard Monte Carlo method while providing risk estimates that only differ by about 10%. It also preserves component-level model fidelity that is difficult to maintain using the standard fault tree method. This balance of speed and fidelity allows sensitivity analysis to be completed in days instead of weeks or months with the standard Monte Carlo method. Results indicate that risk estimates are sensitive to transponder, pilot visual avoidance, and conflict detection failure probabilities.
Bergmann, Ryan
Graphics processing units, or GPUs, have gradually increased in computational power from the small, job-specific boards of the early 1990s to the programmable powerhouses of today. Compared to more common central processing units, or CPUs, GPUs have a higher aggregate memory bandwidth, much higher floating-point operations per second (FLOPS), and lower energy consumption per FLOP. Because one of the main obstacles in exascale computing is power consumption, many new supercomputing platforms are gaining much of their computational capacity by incorporating GPUs into their compute nodes. Since CPU-optimized parallel algorithms are not directly portable to GPU architectures (or at least not without losing substantial performance), transport codes need to be rewritten to execute efficiently on GPUs. Unless this is done, reactor simulations cannot take full advantage of these new supercomputers. WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed in this work as to efficiently implement a continuous energy Monte Carlo neutron transport algorithm on a GPU. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo Method, namely, very few physical and geometrical simplifications. WARP is able to calculate multiplication factors, flux tallies, and fission source distributions for time-independent problems, and can run in both criticality or fixed source modes. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. WARP uses an event-based algorithm, but with some important differences. Moving data is expensive, so WARP uses a remapping vector of pointer/index pairs to direct GPU threads to the data they need to access. The remapping vector is sorted by reaction type after every transport iteration using a high-efficiency parallel radix sort, which serves to keep the
Currently, many proton therapy facilities are used for radiotherapy for treating cancer. The main advantage of proton therapy is the absence of exit dose, which offers a highly conformal dose to treatment target as well as better normal organ sparing. The most of treatment planning system (TPS) in proton therapy calculates dose distribution using a pencil beam algorithm (PBA). PBA is suitable for clinical proton therapy because of the fast computation time. However PBA shows accuracy limitations mainly because of the one-dimensional density scaling of proton pencil beams in water. Recently, we developed Monte Carlo simulation tools for the design of proton therapy facility at National Cancer Center (NCC) using GEANT4 toolkit (version GEANT4.9.2p02). Monte Carlo simulation is expected to reproduce precise influences of complex geometry and material varieties which are difficult to introduce to the PBA. The data format of Monte Carlo simulation result has different from DICOM-RT. Consequently we need we analysis software for comparing between TPS and Monte Carlo simulation. The main objective of this research is to develop an analysis toolkit for verifying precision and accuracy of the proton treatment planning system and to analyze dose calculating algorithm of the proton therapy using Monte Carlo simulation. In this work, we conclude that we developed an analysis software for GEANT4-based medical application. This toolkit is capable of evaluating the accuracy of calculated dose by TPS with Monte Carlo simulation.
Kim, Dae Hyun; Suh, Tae Suk [Dept. of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul (Korea, Republic of); Park, Sey Joon; Yoo, Seung Hoon; Lee, Se Byeong [Proton Therapy Center, National Cancer Center, Goyang (Korea, Republic of); Shin, Jung Wook [Dept. of Radiation Oncology, University of California, SanFrancisco (United States)
2011-11-15
Currently, many proton therapy facilities are used for radiotherapy for treating cancer. The main advantage of proton therapy is the absence of exit dose, which offers a highly conformal dose to treatment target as well as better normal organ sparing. The most of treatment planning system (TPS) in proton therapy calculates dose distribution using a pencil beam algorithm (PBA). PBA is suitable for clinical proton therapy because of the fast computation time. However PBA shows accuracy limitations mainly because of the one-dimensional density scaling of proton pencil beams in water. Recently, we developed Monte Carlo simulation tools for the design of proton therapy facility at National Cancer Center (NCC) using GEANT4 toolkit (version GEANT4.9.2p02). Monte Carlo simulation is expected to reproduce precise influences of complex geometry and material varieties which are difficult to introduce to the PBA. The data format of Monte Carlo simulation result has different from DICOM-RT. Consequently we need we analysis software for comparing between TPS and Monte Carlo simulation. The main objective of this research is to develop an analysis toolkit for verifying precision and accuracy of the proton treatment planning system and to analyze dose calculating algorithm of the proton therapy using Monte Carlo simulation. In this work, we conclude that we developed an analysis software for GEANT4-based medical application. This toolkit is capable of evaluating the accuracy of calculated dose by TPS with Monte Carlo simulation.
Optimization of scintillation-detector timing systems using Monte Carlo analysis
Monte Carlo analysis is used to model statistical noise associated with scintillation-detector photoelectron emissions and photomultiplier tube operation. Additionally, the impulse response of a photomultiplier tube, front-end amplifier, and constant-fraction discriminator (CFD) is modeled so the effects of front-end bandwidth and constant-fraction delay and fraction can be evaluated for timing-system optimizations. Such timing-system analysis is useful for detectors having low photo-electron-emission rates, including Bismuth Germanate (BGO) scintillation detectors used in Positron Emission Tomography (PET) systems. Monte Carlo timing resolution for a BGO / photomultiplier scintillation detector, CFD timing system is presented as a function of constant-fraction delay for 511-keV coincident gamma rays in the presence of Compton scatter. Monte Carlo results are in good agreement with measured results when a tri-exponential BGO scintillation model is used. Monte Carlo simulation is extended to include CFD energy-discrimination performance. Monte Carlo energy-discrimination performance is experimentally verified along with timing performance (Monte Carlo timing resolution of 3.22 ns FWHM versus measured resolution of 3.30 ns FWHM) for a front-end rise time of 10 ns (10--90%), CFD delay of 8 ns, and CFD fraction of 20%
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.
pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis
White, J.; Brakefield, L. K.
2015-12-01
The null-space monte carlo technique is a non-linear uncertainty analyses technique that is well-suited to high-dimensional inverse problems. While the technique is powerful, the existing workflow for completing null-space monte carlo is cumbersome, requiring the use of multiple commandline utilities, several sets of intermediate files and even a text editor. pyNSMC is an open-source python module that automates the workflow of null-space monte carlo uncertainty analyses. The module is fully compatible with the PEST and PEST++ software suites and leverages existing functionality of pyEMU, a python framework for linear-based uncertainty analyses. pyNSMC greatly simplifies the existing workflow for null-space monte carlo by taking advantage of object oriented design facilities in python. The core of pyNSMC is the ensemble class, which draws and stores realized random vectors and also provides functionality for exporting and visualizing results. By relieving users of the tedium associated with file handling and command line utility execution, pyNSMC instead focuses the user on the important steps and assumptions of null-space monte carlo analysis. Furthermore, pyNSMC facilitates learning through flow charts and results visualization, which are available at many points in the algorithm. The ease-of-use of the pyNSMC workflow is compared to the existing workflow for null-space monte carlo for a synthetic groundwater model with hundreds of estimable parameters.
Finite-Time Analysis of Stratified Sampling for Monte Carlo
Carpentier, Alexandra; Munos, Rémi
2011-01-01
International audience We consider the problem of stratified sampling for Monte-Carlo integration. We model this problem in a multi-armed bandit setting, where the arms represent the strata, and the goal is to estimate a weighted average of the mean values of the arms. We propose a strategy that samples the arms according to an upper bound on their standard deviations and compare its estimation quality to an ideal allocation that would know the standard deviations of the strata. We provide...
Li, Yong Gang; Yang, Yang; Short, Michael P.; Ding, Ze Jun; Zeng, Zhi; Li, Ju
2015-12-01
SRIM-like codes have limitations in describing general 3D geometries, for modeling radiation displacements and damage in nanostructured materials. A universal, computationally efficient and massively parallel 3D Monte Carlo code, IM3D, has been developed with excellent parallel scaling performance. IM3D is based on fast indexing of scattering integrals and the SRIM stopping power database, and allows the user a choice of Constructive Solid Geometry (CSG) or Finite Element Triangle Mesh (FETM) method for constructing 3D shapes and microstructures. For 2D films and multilayers, IM3D perfectly reproduces SRIM results, and can be ∼102 times faster in serial execution and > 104 times faster using parallel computation. For 3D problems, it provides a fast approach for analyzing the spatial distributions of primary displacements and defect generation under ion irradiation. Herein we also provide a detailed discussion of our open-source collision cascade physics engine, revealing the true meaning and limitations of the “Quick Kinchin-Pease” and “Full Cascades” options. The issues of femtosecond to picosecond timescales in defining displacement versus damage, the limitation of the displacements per atom (DPA) unit in quantifying radiation damage (such as inadequacy in quantifying degree of chemical mixing), are discussed.
Pukite, Janis [Max- Planck-Institut fuer Chemie, Mainz (Germany); Institute of Atomic Physics and Spectroscopy, University of Latvia (Latvia); Kuehl, Sven; Wagner, Thomas [Max- Planck-Institut fuer Chemie, Mainz (Germany); Deutschmann, Tim; Platt, Ulrich [Institut fuer Umweltphysik, University of Heidelberg (Germany)
2007-07-01
A two step method for the retrieval of stratospheric trace gases (NO{sub 2}, BrO, OClO) from SCIAMACHY limb observations in the UV/VIS spectral region is presented: First, DOAS is applied on the spectra, yielding slant column densities (SCDs) of the respective trace gases. Second, the SCDs are converted into vertical concentration profiles applying radiative transfer modeling. The Monte Carlo method benefits from conceptual simplicity and allows realizing the concept of full spherical geometry of the atmosphere and also its 3D properties, which are important for a realistic description of the limb geometry. The implementation of a 3D box air mass factor concept allows accounting for horizontal gradients of trace gases. An important point is the effect of horizontal gradients on the profile inversion. This is of special interest in Polar Regions, where the Sun elevation is typically low and photochemistry can highly vary along the long absorption paths. We investigate the influence of horizontal gradients by applying 3-dimensional radiative transfer modelling.
An Advanced Neutronic Analysis Toolkit with Inline Monte Carlo capability for VHTR Analysis
Monte Carlo capability has been combined with a production LWR lattice physics code to allow analysis of high temperature gas reactor configurations, accounting for the double heterogeneity due to the TRISO fuel. The Monte Carlo code MCNP5 has been used in conjunction with CPM3, which was the testbench lattice physics code for this project. MCNP5 is used to perform two calculations for the geometry of interest, one with homogenized fuel compacts and the other with heterogeneous fuel compacts, where the TRISO fuel kernels are resolved by MCNP5.
Shape analysis of blocking dips: Monte Carlo vs. analytical results
Angular blocking dips around the axis in Al single crystal of α-particles of about 2 MeV produced at a depth of 0.2 μm are calculated for several values of the mean transverse displacement v perpendicular to tau of the decaying nucleus within the range 0 <= v perpendicular to tau <= 260 pm. Calculations have been made both by an extensive multistring Monte Carlo simulation and by a continuum model with diffusion. As far as the Monte Carlo method is concerned, the influence of the (small) solid angle of particles emission and of the 'single interaction' approximation has been investigated. The analytical calculations performed on the basis of a Moliere (thermally averaged) multistring potential show, for large v perpendicular to tau, a clear dependence of the blocking dips on the recoil direction and a sharp peak at very small angles. The shapes of the dips obtained by the two methods are in overall good agreement while a very satisfactory comparison has been found for the dip widths and the relative parameters used in many lifetime measurements. (author)
Highlights: • A Monte Carlo simulation of a SOFC stack model is conducted for sensitivity analysis. • The non-isothermal stack model allows fast computation for statistical modeling. • Modeling parameters are ranked in view of their correlations with stack performance. • Rankings are different when varying the parameters simultaneously and individually. • Rankings change with the variability of the parameters and positions in the stack. - Abstract: The development of fuel cells has progressed to portable applications recently. This paper conducts a Monte Carlo simulation (MCS) of a spatially-smoothed non-isothermal model to correlate the performance of a 3D 5-cell planar solid oxide fuel cell (P-SOFC) stack with the variability of modeling parameters regarding material and geometrical properties and operating conditions. The computationally cost-efficient P-SOFC model for the MCS captures the leading-order transport phenomena and electrochemical mechanics of the 3D stack. Sensitivity analysis is carried out in two scenarios: first, by varying modeling parameters individually, and second by varying them simultaneously. The stochastic parameters are ranked according to the strength of their correlations with global and local stack performances. As a result, different rankings are obtained for the two scenarios. Moreover, in the second scenario, the rankings change with the nominal values and variability of the stochastic parameters as well as local positions within the stack, because of compensating or reinforcing effects between the varying parameters. Apart from the P-SOFCs, the present MCS can be extended to other types of fuel cells equipped with parallel flow channels. The fast stack model allows statistical modeling of a large stack of hundreds of cells for high-power applications without a prohibitive computational cost
3D imaging using combined neutron-photon fan-beam tomography: A Monte Carlo study.
Hartman, J; Yazdanpanah, A Pour; Barzilov, A; Regentova, E
2016-05-01
The application of combined neutron-photon tomography for 3D imaging is examined using MCNP5 simulations for objects of simple shapes and different materials. Two-dimensional transmission projections were simulated for fan-beam scans using 2.5MeV deuterium-deuterium and 14MeV deuterium-tritium neutron sources, and high-energy X-ray sources, such as 1MeV, 6MeV and 9MeV. Photons enable assessment of electron density and related mass density, neutrons aid in estimating the product of density and material-specific microscopic cross section- the ratio between the two provides the composition, while CT allows shape evaluation. Using a developed imaging technique, objects and their material compositions have been visualized. PMID:26953978
Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-network (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials
Li, Ming; Huang, Xiaobo; Kang, Zhan
2015-08-01
Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-network (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials.
Li, Ming; Kang, Zhan, E-mail: zhankang@dlut.edu.cn [State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024 (China); Huang, Xiaobo [Suzhou Nuclear Power Research Institute, Suzhou 215000 (China)
2015-08-28
Hydrogen is clean, sustainable, and renewable, thus is viewed as promising energy carrier. However, its industrial utilization is greatly hampered by the lack of effective hydrogen storage and release method. Carbon nanotubes (CNTs) were viewed as one of the potential hydrogen containers, but it has been proved that pure CNTs cannot attain the desired target capacity of hydrogen storage. In this paper, we present a numerical study on the material-driven and structure-driven hydrogen adsorption of 3D silicon networks and propose a deformation-driven hydrogen desorption approach based on molecular simulations. Two types of 3D nanostructures, silicon nanotube-network (Si-NN) and silicon film-network (Si-FN), are first investigated in terms of hydrogen adsorption and desorption capacity with grand canonical Monte Carlo simulations. It is revealed that the hydrogen storage capacity is determined by the lithium doping ratio and geometrical parameters, and the maximum hydrogen uptake can be achieved by a 3D nanostructure with optimal configuration and doping ratio obtained through design optimization technique. For hydrogen desorption, a mechanical-deformation-driven-hydrogen-release approach is proposed. Compared with temperature/pressure change-induced hydrogen desorption method, the proposed approach is so effective that nearly complete hydrogen desorption can be achieved by Si-FN nanostructures under sufficient compression but without structural failure observed. The approach is also reversible since the mechanical deformation in Si-FN nanostructures can be elastically recovered, which suggests a good reusability. This study may shed light on the mechanism of hydrogen adsorption and desorption and thus provide useful guidance toward engineering design of microstructural hydrogen (or other gas) adsorption materials.
General purpose dynamic Monte Carlo with continuous energy for transient analysis
Sjenitzer, B. L.; Hoogenboom, J. E. [Delft Univ. of Technology, Dept. of Radiation, Radionuclide and Reactors, Mekelweg 15, 2629JB Delft (Netherlands)
2012-07-01
For safety assessments transient analysis is an important tool. It can predict maximum temperatures during regular reactor operation or during an accident scenario. Despite the fact that this kind of analysis is very important, the state of the art still uses rather crude methods, like diffusion theory and point-kinetics. For reference calculations it is preferable to use the Monte Carlo method. In this paper the dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli4. Also, the method is extended for use with continuous energy. The first results of Dynamic Tripoli demonstrate that this kind of calculation is indeed accurate and the results are achieved in a reasonable amount of time. With the method implemented in Tripoli it is now possible to do an exact transient calculation in arbitrary geometry. (authors)
Image quality assessment of LaBr3-based whole-body 3D PET scanners: a Monte Carlo evaluation
The main thrust for this work is the investigation and design of a whole-body PET scanner based on new lanthanum bromide scintillators. We use Monte Carlo simulations to generate data for a 3D PET scanner based on LaBr3 detectors, and to assess the count-rate capability and the reconstructed image quality of phantoms with hot and cold spheres using contrast and noise parameters. Previously we have shown that LaBr3 has very high light output, excellent energy resolution and fast timing properties which can lead to the design of a time-of-flight (TOF) whole-body PET camera. The data presented here illustrate the performance of LaBr3 without the additional benefit of TOF information, although our intention is to develop a scanner with TOF measurement capability. The only drawbacks of LaBr3 are the lower stopping power and photo-fraction which affect both sensitivity and spatial resolution. However, in 3D PET imaging where energy resolution is very important for reducing scattered coincidences in the reconstructed image, the image quality attained in a non-TOF LaBr3 scanner can potentially equal or surpass that achieved with other high sensitivity scanners. Our results show that there is a gain in NEC arising from the reduced scatter and random fractions in a LaBr3 scanner. The reconstructed image resolution is slightly worse than a high-Z scintillator, but at increased count-rates, reduced pulse pileup leads to an image resolution similar to that of LSO. Image quality simulations predict reduced contrast for small hot spheres compared to an LSO scanner, but improved noise characteristics at similar clinical activity levels
Advanced Mesh-Enabled Monte carlo capability for Multi-Physics Reactor Analysis
Wilson, Paul; Evans, Thomas; Tautges, Tim
2012-12-24
This project will accumulate high-precision fluxes throughout reactor geometry on a non- orthogonal grid of cells to support multi-physics coupling, in order to more accurately calculate parameters such as reactivity coefficients and to generate multi-group cross sections. This work will be based upon recent developments to incorporate advanced geometry and mesh capability in a modular Monte Carlo toolkit with computational science technology that is in use in related reactor simulation software development. Coupling this capability with production-scale Monte Carlo radiation transport codes can provide advanced and extensible test-beds for these developments. Continuous energy Monte Carlo methods are generally considered to be the most accurate computational tool for simulating radiation transport in complex geometries, particularly neutron transport in reactors. Nevertheless, there are several limitations for their use in reactor analysis. Most significantly, there is a trade-off between the fidelity of results in phase space, statistical accuracy, and the amount of computer time required for simulation. Consequently, to achieve an acceptable level of statistical convergence in high-fidelity results required for modern coupled multi-physics analysis, the required computer time makes Monte Carlo methods prohibitive for design iterations and detailed whole-core analysis. More subtly, the statistical uncertainty is typically not uniform throughout the domain, and the simulation quality is limited by the regions with the largest statistical uncertainty. In addition, the formulation of neutron scattering laws in continuous energy Monte Carlo methods makes it difficult to calculate adjoint neutron fluxes required to properly determine important reactivity parameters. Finally, most Monte Carlo codes available for reactor analysis have relied on orthogonal hexahedral grids for tallies that do not conform to the geometric boundaries and are thus generally not well
The present of shielding analysis with nuclear data for continuous energy Monte Carlo code MCNP
Following three problems are analyzed by continuous energy Monte Carlo code MCNP with JENDL-3.2, 3.3, and ENDF/B-VI. 1. Shielding analysis of WINFRITH-Aspins iron deep penetration experiment. 2. Shielding analysis of TN-12A spent fuel transport cask experiment. 3. Shielding analysis of modular shielding house keeping spent fuel transportable casks. (author)
Reliability analysis of tunnel surrounding rock stability by Monte-Carlo method
XI Jia-mi; YANG Geng-she
2008-01-01
Discussed advantages of improved Monte-Carlo method and feasibility aboutproposed approach applying in reliability analysis for tunnel surrounding rock stability. Onthe basis of deterministic parsing for tunnel surrounding rock, reliability computing methodof surrounding rock stability was derived from improved Monte-Carlo method. The com-puting method considered random of related parameters, and therefore satisfies relativityamong parameters. The proposed method can reasonably determine reliability of sur-rounding rock stability. Calculation results show that this method is a scientific method indiscriminating and checking surrounding rock stability.
Towards integration of compositional risk analysis using Monte Carlo simulation and security testing
Viehmann, Johannes
2014-01-01
This short paper describes ongoing efforts to combine concepts of security risk analysis with security testing into a single process. Using risk analysis artefact composition and Monte Carlo simulation to calculate likelihood values, the method described here is intended to become applicable for complex large scale systems with dynamically changing probability values.
A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis
Edwards, Michael C.
2010-01-01
Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…
Lautenschlager, Gary J.
The parallel analysis method for determining the number of components to retain in a principal components analysis has received a recent resurgence of support and interest. However, researchers and practitioners desiring to use this criterion have been hampered by the required Monte Carlo analyses needed to develop the criteria. Two recent…
Construction of the quantitative analysis environment using Monte Carlo simulation
The thoracic phantom image was acquisitioned of the axial section to construct maps of the source and density with Monte Carlo (MC) simulation. The phantom was Heart/Liver Type HL (Kyoto Kagaku Co., Ltd.) single photon emission CT (SPECT)/CT machine was Symbia T6 (Siemence) with the collimator LMEGP (low-medium energy general purpose). Maps were constructed from CT images with an in-house software using Visual studio C Sharp (Microsoft). The code simulation of imaging nuclear detectors (SIMIND) was used for MC simulation, Prominence processor (Nihon Medi-Physics) for filter processing and image reconstruction, and the environment DELL Precision T7400 for all image processes. For the actual experiment, the phantom was given 15 MBq of 99mTc assuming the uptake 2% at the dose of 740 MBq in its myocardial portion and SPECT image was acquisitioned and reconstructed with Butter-worth filter and filter back projection method. CT images were similarly obtained in 0.3 mm thick slices, which were filed in one formatted with digital imaging and communication in medicine (DICOM), and then processed for application to SIMIND for mapping the source and density. Physical and mensuration factors were examined in ideal images by sequential exclusion and simulation of those factors as attenuation, scattering, spatial resolution deterioration and statistical fluctuation. Gamma energy spectrum, SPECT projection and reconstructed images given by the simulation were found to well agree with the actual data, and the precision of MC simulation was confirmed. Physical and mensuration factors were found to be evaluable individually, suggesting the usefulness of the simulation for assessing the precision of their correction. (T.T.)
The seasonal KPSS test when neglecting seasonal dummies: a Monte Carlo analysis
El Montasser, Ghassen; Boufateh, Talel; Issaoui, Fakhri
2013-01-01
This paper shows through a Monte Carlo analysis the effect of neglecting seasonal deterministics on the seasonal KPSS test. We found that the test is most of the time heavily oversized and not convergent in this case. In addition, Bartlett-type non-parametric correction of error variances did not signally change the test's rejection frequencies.
Taxometrics, Polytomous Constructs, and the Comparison Curve Fit Index: A Monte Carlo Analysis
Walters, Glenn D.; McGrath, Robert E.; Knight, Raymond A.
2010-01-01
The taxometric method effectively distinguishes between dimensional (1-class) and taxonic (2-class) latent structure, but there is virtually no information on how it responds to polytomous (3-class) latent structure. A Monte Carlo analysis showed that the mean comparison curve fit index (CCFI; Ruscio, Haslam, & Ruscio, 2006) obtained with 3…
The Lagrangian approach to Markov Monte Carlo methods for systems reliability analysis is generalized to include non-Markovian phenomena in which system components are replaced. The method is then employed to analyze the unreliability and unavailability of a number of redundant systems in which maintenance is carried out by batch or time replacement of aging components. (orig.)
Highlights: • Performance estimation of nuclear-data benchmark was investigated. • Point detector contribution played a benchmark role not only to the neutron producing the detector contribution but also equally to all the upstream transport neutrons. • New functions were defined to give how well the contribution could be interpreted for benchmarking. • Benchmark performance could be evaluated only by a forward Monte Carlo calculation. -- Abstract: The author's group has been investigating how the performance estimation of nuclear-data benchmark using experiment and its analysis by Monte Carlo code should be carried out especially at 14 MeV. We have recently found that a detector contribution played a benchmark role not only to the neutron producing the detector contribution but also equally to all the upstream neutrons during the neutron history. This result would propose that the benchmark performance could be evaluated only by a forward Monte Carlo calculation. In this study, we thus defined new functions to give how well the contribution could be utilized for benchmarking using the point detector, and described that it was deeply related to the newly introduced “partial adjoint contribution”. By preparing these functions before benchmark experiments, one could know beforehand how well and for which nuclear data the experiment results could do benchmarking in forward Monte Carlo calculations
Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Analysis
Hanson, J. M.; Beard, B. B.
2010-01-01
This Technical Publication (TP) is meant to address a number of topics related to the application of Monte Carlo simulation to launch vehicle design and requirements analysis. Although the focus is on a launch vehicle application, the methods may be applied to other complex systems as well. The TP is organized so that all the important topics are covered in the main text, and detailed derivations are in the appendices. The TP first introduces Monte Carlo simulation and the major topics to be discussed, including discussion of the input distributions for Monte Carlo runs, testing the simulation, how many runs are necessary for verification of requirements, what to do if results are desired for events that happen only rarely, and postprocessing, including analyzing any failed runs, examples of useful output products, and statistical information for generating desired results from the output data. Topics in the appendices include some tables for requirements verification, derivation of the number of runs required and generation of output probabilistic data with consumer risk included, derivation of launch vehicle models to include possible variations of assembled vehicles, minimization of a consumable to achieve a two-dimensional statistical result, recontact probability during staging, ensuring duplicated Monte Carlo random variations, and importance sampling.
Marcus, Ryan C. [Los Alamos National Laboratory
2012-07-25
MCMini is a proof of concept that demonstrates the possibility for Monte Carlo neutron transport using OpenCL with a focus on performance. This implementation, written in C, shows that tracing particles and calculating reactions on a 3D mesh can be done in a highly scalable fashion. These results demonstrate a potential path forward for MCNP or other Monte Carlo codes.
New strategies of sensitivity analysis capabilities in continuous-energy Monte Carlo code RMC
Highlights: • Data decomposition techniques are proposed for memory reduction. • New strategies are put forward and implemented in RMC code to improve efficiency and accuracy for sensitivity calculations. • A capability to compute region-specific sensitivity coefficients is developed in RMC code. - Abstract: The iterated fission probability (IFP) method has been demonstrated to be an accurate alternative for estimating the adjoint-weighted parameters in continuous-energy Monte Carlo forward calculations. However, the memory requirements of this method are huge especially when a large number of sensitivity coefficients are desired. Therefore, data decomposition techniques are proposed in this work. Two parallel strategies based on the neutron production rate (NPR) estimator and the fission neutron population (FNP) estimator for adjoint fluxes, as well as a more efficient algorithm which has multiple overlapping blocks (MOB) in a cycle, are investigated and implemented in the continuous-energy Reactor Monte Carlo code RMC for sensitivity analysis. Furthermore, a region-specific sensitivity analysis capability is developed in RMC. These new strategies, algorithms and capabilities are verified against analytic solutions of a multi-group infinite-medium problem and against results from other software packages including MCNP6, TSUANAMI-1D and multi-group TSUNAMI-3D. While the results generated by the NPR and FNP strategies agree within 0.1% of the analytic sensitivity coefficients, the MOB strategy surprisingly produces sensitivity coefficients exactly equal to the analytic ones. Meanwhile, the results generated by the three strategies in RMC are in agreement with those produced by other codes within a few percent. Moreover, the MOB strategy performs the most efficient sensitivity coefficient calculations (offering as much as an order of magnitude gain in FoMs over MCNP6), followed by the NPR and FNP strategies, and then MCNP6. The results also reveal that these
Palau, J.M. [CEA Cadarache, Service de Physique des Reacteurs et du Cycle, Lab. de Projets Nucleaires, 13 - Saint-Paul-lez-Durance (France)
2005-07-01
This paper presents how Monte-Carlo calculations (French TRIPOLI4 poly-kinetic code with an appropriate pre-processing and post-processing software called OVNI) are used in the case of 3-dimensional heterogeneous benchmarks (slab reactor cores) to reduce model biases and enable a thorough and detailed analysis of the performances of deterministic methods and their associated data libraries with respect to key neutron parameters (reactivity, local power). Outstanding examples of application of these tools are presented regarding the new numerical methods implemented in the French lattice code APOLLO2 (advanced self-shielding models, new IDT characteristics method implemented within the discrete-ordinates flux solver model) and the JEFF3.1 nuclear data library (checked against JEF2.2 previous file). In particular we have pointed out, by performing multigroup/point-wise TRIPOLI4 (assembly and core) calculations, the efficiency (in terms of accuracy and computation time) of the new IDT method developed in APOLLO2. In addition, by performing 3-dimensional TRIPOLI4 calculations of the whole slab core (few millions of elementary volumes), the high quality of the new JEFF3.1 nuclear data files and revised evaluations (U{sup 235}, U{sup 238}, Hf) for reactivity prediction of slab cores critical experiments has been stressed. As a feedback of the whole validation process, improvements in terms of nuclear data (mainly Hf capture cross-sections) and numerical methods (advanced quadrature formulas accounting validation results, validation of new self-shielding models, parallelization) are suggested to improve even more the APOLLO2-CRONOS2 standard calculation route. (author)
This paper presents how Monte-Carlo calculations (French TRIPOLI4 poly-kinetic code with an appropriate pre-processing and post-processing software called OVNI) are used in the case of 3-dimensional heterogeneous benchmarks (slab reactor cores) to reduce model biases and enable a thorough and detailed analysis of the performances of deterministic methods and their associated data libraries with respect to key neutron parameters (reactivity, local power). Outstanding examples of application of these tools are presented regarding the new numerical methods implemented in the French lattice code APOLLO2 (advanced self-shielding models, new IDT characteristics method implemented within the discrete-ordinates flux solver model) and the JEFF3.1 nuclear data library (checked against JEF2.2 previous file). In particular we have pointed out, by performing multigroup/point-wise TRIPOLI4 (assembly and core) calculations, the efficiency (in terms of accuracy and computation time) of the new IDT method developed in APOLLO2. In addition, by performing 3-dimensional TRIPOLI4 calculations of the whole slab core (few millions of elementary volumes), the high quality of the new JEFF3.1 nuclear data files and revised evaluations (U235, U238, Hf) for reactivity prediction of slab cores critical experiments has been stressed. As a feedback of the whole validation process, improvements in terms of nuclear data (mainly Hf capture cross-sections) and numerical methods (advanced quadrature formulas accounting validation results, validation of new self-shielding models, parallelization) are suggested to improve even more the APOLLO2-CRONOS2 standard calculation route. (author)
The Null Space Monte Carlo Uncertainty Analysis of Heterogeneity for Preferential Flow Simulation
Ghasemizade, M.; Radny, D.; Schirmer, M.
2014-12-01
Preferential flow paths can have a huge impact on the amount and time of runoff generation, particularly in areas where subsurface flow dominates this process. In order to simulate preferential flow mechanisms, many different approaches have been suggested. However, the efficiency of such approaches are rarely investigated in a predictive sense. The main reason is that the models which are used to simulate preferential flows require many parameters. This can lead to a dramatic increase of model run times, especially in the context of highly nonlinear models which themselves are demanding. We attempted in this research to simulate the daily recharge values of a weighing lysimeter, including preferential flows, with the 3-D physically based model HydroGeoSphere. To accomplish that, we used the matrix pore concept with varying hydraulic conductivities within the lysimeter to represent heterogeneity. It was assumed that spatially correlated heterogeneity is the main driver of triggering preferential flow paths. In order to capture the spatial distribution of hydraulic conductivity values we used pilot points and geostatistical model structures. Since hydraulic conductivity values at each pilot point are functioning as parameters, the model is a highly parameterized one. Due to this fact, we used the robust and newly developed method of null space Monte Carlo for analyzing the uncertainty of the model outputs. Results of the uncertainty analysis show that the method of pilot points is reliable in order to represent preferential flow paths.
Chan, Mark K.H. [Tuen Mun Hospital, Department of Clinical Oncology, Hong Kong (S.A.R) (China); Werner, Rene [The University Medical Center Hamburg-Eppendorf, Department of Computational Neuroscience, Hamburg (Germany); Ayadi, Miriam [Leon Berard Cancer Center, Department of Radiation Oncology, Lyon (France); Blanck, Oliver [University Clinic of Schleswig-Holstein, Department of Radiation Oncology, Luebeck (Germany); CyberKnife Center Northern Germany, Guestrow (Germany)
2014-09-20
To investigate the adequacy of three-dimensional (3D) Monte Carlo (MC) optimization (3DMCO) and the potential of four-dimensional (4D) dose renormalization (4DMC{sub renorm}) and optimization (4DMCO) for CyberKnife (Accuray Inc., Sunnyvale, CA) radiotherapy planning in lung cancer. For 20 lung tumors, 3DMCO and 4DMCO plans were generated with planning target volume (PTV{sub 5} {sub mm}) = gross tumor volume (GTV) plus 5 mm, assuming 3 mm for tracking errors (PTV{sub 3} {sub mm}) and 2 mm for residual organ deformations. Three fractions of 60 Gy were prescribed to ≥ 95 % of the PTV{sub 5} {sub mm}. Each 3DMCO plan was recalculated by 4D MC dose calculation (4DMC{sub recal}) to assess the dosimetric impact of organ deformations. The 4DMC{sub recal} plans were renormalized (4DMC{sub renorm}) to 95 % dose coverage of the PTV{sub 5} {sub mm} for comparisons with the 4DMCO plans. A 3DMCO plan was considered adequate if the 4DMC{sub recal} plan showed ≥ 95 % of the PTV{sub 3} {sub mm} receiving 60 Gy and doses to other organs at risk (OARs) were below the limits. In seven lesions, 3DMCO was inadequate, providing < 95 % dose coverage to the PTV{sub 3} {sub mm}. Comparison of 4DMC{sub recal} and 3DMCO plans showed that organ deformations resulted in lower OAR doses. Renormalizing the 4DMC{sub recal} plans could produce OAR doses higher than the tolerances in some 4DMC{sub renorm} plans. Dose conformity of the 4DMC{sub renorm} plans was inferior to that of the 3DMCO and 4DMCO plans. The 4DMCO plans did not always achieve OAR dose reductions compared to 3DMCO and 4DMC{sub renorm} plans. This study indicates that 3DMCO with 2 mm margins for organ deformations may be inadequate for Cyberknife-based lung stereotactic body radiotherapy (SBRT). Renormalizing the 4DMC{sub recal} plans could produce degraded dose conformity and increased OAR doses; 4DMCO can resolve this problem. (orig.) [German] Untersucht wurde die Angemessenheit einer dreidimensionalen (3-D) Monte-Carlo
A new Monte Carlo atmospheric radiative transfer model is presented which is designed to support the interpretation of UV/vis/near-IR spectroscopic measurements of scattered Sun light in the atmosphere. The integro differential equation describing the underlying transport process and its formal solution are discussed. A stochastic approach to solve the differential equation, the Monte Carlo method, is deduced and its application to the formal solution is demonstrated. It is shown how model photon trajectories of the resulting ray tracing algorithm are used to estimate functionals of the radiation field such as radiances, actinic fluxes and light path integrals. In addition, Jacobians of the former quantities with respect to optical parameters of the atmosphere are analyzed. Model output quantities are validated against measurements, by self-consistency tests and through inter comparisons with other radiative transfer models.
Statistical analysis and Monte Carlo simulation of growing self-avoiding walks on percolation
The two-dimensional growing self-avoiding walk on percolation was investigated by statistical analysis and Monte Carlo simulation. We obtained the expression of the mean square displacement and effective exponent as functions of time and percolation probability by statistical analysis and made a comparison with simulations. We got a reduced time to scale the motion of walkers in growing self-avoiding walks on regular and percolation lattices
The energy analysis for the monte carlo simulations of a diffusive shock
Wang, Xin; Yan, Yihua
2011-01-01
According to the shock jump conditions, the total fluid's mass, momentum, and energy should be conserved in the entire simulation box. We perform the dynamical Monte Carlo simulations with the multiple scattering law for energy analysis. The various energy functions of time are obtained by monitoring the total particles' mass, momentum, and energy in the simulation box. In conclusion, the energy analysis indicates that the smaller energy losses in the prescribed scattering law are, the harder...
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.
Risk Analysis of Tilapia Recirculating Aquaculture Systems: A Monte Carlo Simulation Approach
Kodra, Bledar
2007-01-01
Risk Analysis of Tilapia Recirculating Aquaculture Systems: A Monte Carlo Simulation Approach Bledar Kodra (ABSTRACT) The purpose of this study is to modify an existing static analytical model developed for a Re-circulating Aquaculture Systems through incorporation of risk considerations to evaluate the economic viability of the system. In addition the objective of this analysis is to provide a well documented risk based analytical system so that individuals (investors/lenders) c...
Genius, Margarita; Strazzera, Elisabetta
2005-01-01
A Monte Carlo analysis is conducted to assess the validity of the bivariate modeling approach for detection and correction of different forms of elicitation effects in Double Bound Contingent Valuation data. Alternative univariate and bivariate models are applied to several simulated data sets, each one characterized by a specific elicitation effect, and their performance is assessed using standard selection criteria. The bivariate models include the standard Bivariate Probit model, and an al...
Risk analysis and Monte Carlo simulation applied to the generation of drilling AFE estimates
This paper presents a method for developing an authorization-for-expenditure (AFE)-generating model and illustrates the technique with a specific offshore field development case study. The model combines Monte Carlo simulation and statistical analysis of historical drilling data to generate more accurate, risked, AFE estimates. In addition to the general method, two examples of making AFE time estimates for North Sea wells with the presented techniques are given
Timing resolution of scintillation-detector systems: a Monte Carlo analysis
Choong, Woon-Seng
2009-01-01
Recent advancements in fast scintillating materials and fast photomultiplier tubes (PMTs) have stimulated renewed interest in time-of-flight (TOF) positron emission tomography (PET). It is well known that the improvement in the timing resolution in PET can significantly reduce the noise variance in the reconstructed image resulting in improved image quality. In order to evaluate the timing performance of scintillation detectors used in TOF PET, we use a Monte Carlo analysis to model the physi...
A Monte Carlo computer program originally developed for analysis of molecular gas flow in axi-symmetric vacuum systems has been extended to include modelling of high energy backscattering and sputtering processes. This report describes the input data required by the computer program together with the results produced. A general description is given of the program operation and the backscattering and sputtering modelling used. An example calculation is included to illustrate practical application of the program. (author)
Present status of Monte Carlo seminar for sub-criticality safety analysis in Japan
This paper provides overview of the methods and results of a series of sub-criticality safety analysis seminars for nuclear fuel cycle facility with the Monte Carlo method held in Japan from July 2000 to July 2003. In these seminars, MCNP-4C2 system (MS-DOS version) was installed in note-type personal computers for participants. Fundamental theory of reactor physics and Monte Carlo simulation as well as the contents of the MCNP manual were lectured. Effective neutron multiplication factors and neutron spectra were calculated for some examples such as JCO deposit tank, JNC uranium solution storage tank, JNC plutonium solution storage tank and JAERI TCA core. Management for safety of nuclear fuel cycle facilities was discussed in order to prevent criticality accidents in some of the seminars. (author)
A study on the radioactivity analysis of decommissioning concrete using Monte Carlo simulation
In order to decommission the shielding concrete of KRR(Korea Research Reactor)-1 and 2, it must be exactly determined activated level and range by neutron irradiation during operation. To determine the activated level and range, it must be sampled and analyzed the core sample. But, there are difficulties in sample preparation and determination of the measurement efficiency by self-absorption. In the study, the full energy efficiency of the HPGe detector was compared with the measured value using standard source and the calculated one using Monte Carlo simulation. Also, self-absorption effects due to the density and component change of the concrete were calculated using the Monte Carlo method. Its results will be used radioactivity analysis of the real concrete core sample in the future
A study on the radioactivity analysis of decommissioning concrete using Monte Carlo simulation
Seo, Bum Kyoung; Kim, Gye Hong; Chung, Un Soo; Lee, Keun Woo; Oh, Won Zin; Park, Jin Ho [KAERI, Taejon (Korea, Republic of)
2004-07-01
In order to decommission the shielding concrete of KRR(Korea Research Reactor)-1 and 2, it must be exactly determined activated level and range by neutron irradiation during operation. To determine the activated level and range, it must be sampled and analyzed the core sample. But, there are difficulties in sample preparation and determination of the measurement efficiency by self-absorption. In the study, the full energy efficiency of the HPGe detector was compared with the measured value using standard source and the calculated one using Monte Carlo simulation. Also, self-absorption effects due to the density and component change of the concrete were calculated using the Monte Carlo method. Its results will be used radioactivity analysis of the real concrete core sample in the future.
Monte Carlo Calculation for Landmine Detection using Prompt Gamma Neutron Activation Analysis
Park, Seungil; Kim, Seong Bong; Yoo, Suk Jae [Plasma Technology Research Center, Gunsan (Korea, Republic of); Shin, Sung Gyun; Cho, Moohyun [POSTECH, Pohang (Korea, Republic of); Han, Seunghoon; Lim, Byeongok [Samsung Thales, Yongin (Korea, Republic of)
2014-05-15
Identification and demining of landmines are a very important issue for the safety of the people and the economic development. To solve the issue, several methods have been proposed in the past. In Korea, National Fusion Research Institute (NFRI) is developing a landmine detector using prompt gamma neutron activation analysis (PGNAA) as a part of the complex sensor-based landmine detection system. In this paper, the Monte Carlo calculation results for this system are presented. Monte Carlo calculation was carried out for the design of the landmine detector using PGNAA. To consider the soil effect, average soil composition is analyzed and applied to the calculation. This results has been used to determine the specification of the landmine detector.
Validation of the problem definition and analysis of the results (tallies) produced during a Monte Carlo particle transport calculation can be a complicated, time-intensive processes. The time required for a person to create an accurate, validated combinatorial geometry (CG) or mesh-based representation of a complex problem, free of common errors such as gaps and overlapping cells, can range from days to weeks. The ability to interrogate the internal structure of a complex, three-dimensional (3-D) geometry, prior to running the transport calculation, can improve the user's confidence in the validity of the problem definition. With regard to the analysis of results, the process of extracting tally data from printed tables within a file is laborious and not an intuitive approach to understanding the results. The ability to display tally information overlaid on top of the problem geometry can decrease the time required for analysis and increase the user's understanding of the results. To this end, our team has integrated VisIt, a parallel, production-quality visualization and data analysis tool into Mercury, a massively-parallel Monte Carlo particle transport code. VisIt provides an API for real time visualization of a simulation as it is running. The user may select which plots to display from the VisIt GUI, or by sending VisIt a Python script from Mercury. The frequency at which plots are updated can be set and the user can visualize the simulation results as it is running
Number of iterations needed in Monte Carlo Simulation using reliability analysis for tunnel supports
E. Bukaçi
2016-06-01
Full Text Available There are many methods in geotechnical engineering which could take advantage of Monte Carlo Simulation to establish probability of failure, since closed form solutions are almost impossible to use in most cases. The problem that arises with using Monte Carlo Simulation is the number of iterations needed for a particular simulation.This article will show why it’s important to calculate number of iterations needed for Monte Carlo Simulation used in reliability analysis for tunnel supports using convergence – confinement method. Number if iterations needed will be calculated with two methods. In the first method, the analyst has to accept a distribution function for the performance function. The other method suggested by this article is to calculate number of iterations based on the convergence of the factor the analyst is interested in the calculation. Reliability analysis will be performed for the diversion tunnel in Rrëshen, Albania, by using both methods mentioned and results will be confronted
Time Series Analysis of Monte Carlo Fission Sources - I: Dominance Ratio Computation
In the nuclear engineering community, the error propagation of the Monte Carlo fission source distribution through cycles is known to be a linear Markov process when the number of histories per cycle is sufficiently large. In the statistics community, linear Markov processes with linear observation functions are known to have an autoregressive moving average (ARMA) representation of orders p and p - 1. Therefore, one can perform ARMA fitting of the binned Monte Carlo fission source in order to compute physical and statistical quantities relevant to nuclear criticality analysis. In this work, the ARMA fitting of a binary Monte Carlo fission source has been successfully developed as a method to compute the dominance ratio, i.e., the ratio of the second-largest to the largest eigenvalues. The method is free of binning mesh refinement and does not require the alteration of the basic source iteration cycle algorithm. Numerical results are presented for problems with one-group isotropic, two-group linearly anisotropic, and continuous-energy cross sections. Also, a strategy for the analysis of eigenmodes higher than the second-largest eigenvalue is demonstrated numerically
Ueki, Kohtaro; Ohashi, Atsuto (Ship Research Inst., Mitaka, Tokyo (Japan)); Kawai, Masayoshi
1993-04-01
The iron, carbon and beryllium cross sections in JENDL-3 have been tested by the continuous energy Monte Carlo analysis of the neutron shielding benchmark experiments. The iron cross sections have been tested with analysis of the ORNL and the Winfrith experiments using the fission neutron sources, and also the LLNL iron experiment using the D-T neutron source. The carbon and beryllium cross sections have been tested with the JAERI-FNS TOF experiments using the D-T neutron source. Revision of the subroutine TALLYD and an appropriate weight-window-parameter assignment have been accomplished in the MCNP code. In consequence, the FSD for each energy bin is reduced so small that the Monte Carlo results for neutron energy spectra could be recognized to be reliable. The Monte Carlo calculations with JENDL-3 indicate a good agreement with the benchmark experiments in a wide energy range, as a whole. Particularly, for the Winfrith iron experiment, the results with JENDL-3 give better agreement, just below the iron 24keV window, than that with ENDF/B-IV. For the JAERI-FNS TOF graphite experiment, the calculated angular fluxes with JENDL-3 give closer agreement than that with ENDF/B-IV at several peaks and dips caused by the inelastic scattering. However, distinct underestimation is observed in the calculated energy spectrum with JENDL-3 between 0.8 and 3.0 MeV for the two iron experiments using fission neutron sources. (author).
Perturbation analysis for Monte Carlo continuous cross section models
Sensitivity analysis, including both its forward and adjoint applications, collectively referred to hereinafter as Perturbation Analysis (PA), is an essential tool to complete Uncertainty Quantification (UQ) and Data Assimilation (DA). PA-assisted UQ and DA have traditionally been carried out for reactor analysis problems using deterministic as opposed to stochastic models for radiation transport. This is because PA requires many model executions to quantify how variations in input data, primarily cross sections, affect variations in model's responses, e.g. detectors readings, flux distribution, multiplication factor, etc. Although stochastic models are often sought for their higher accuracy, their repeated execution is at best computationally expensive and in reality intractable for typical reactor analysis problems involving many input data and output responses. Deterministic methods however achieve computational efficiency needed to carry out the PA analysis by reducing problem dimensionality via various spatial and energy homogenization assumptions. This however introduces modeling error components into the PA results which propagate to the following UQ and DA analyses. The introduced errors are problem specific and therefore are expected to limit the applicability of UQ and DA analyses to reactor systems that satisfy the introduced assumptions. This manuscript introduces a new method to complete PA employing a continuous cross section stochastic model and performed in a computationally efficient manner. If successful, the modeling error components introduced by deterministic methods could be eliminated, thereby allowing for wider applicability of DA and UQ results. Two MCNP models demonstrate the application of the new method - a Critical Pu Sphere (Jezebel), a Pu Fast Metal Array (Russian BR-1). The PA is completed for reaction rate densities, reaction rate ratios, and the multiplication factor. (author)
Fallahpoor, M; Abbasi, M [Tehran University of Medical Sciences, Vali-Asr Hospital, Tehran, Tehran (Iran, Islamic Republic of); Sen, A [University of Houston, Houston, TX (United States); Parach, A [Shahid Sadoughi University of Medical Sciences, Yazd, Yazd (Iran, Islamic Republic of); Kalantari, F [UT Southwestern Medical Center, Dallas, TX (United States)
2015-06-15
Purpose: Patient-specific 3-dimensional (3D) internal dosimetry in targeted radionuclide therapy is essential for efficient treatment. Two major steps to achieve reliable results are: 1) generating quantitative 3D images of radionuclide distribution and attenuation coefficients and 2) using a reliable method for dose calculation based on activity and attenuation map. In this research, internal dosimetry for 153-Samarium (153-Sm) was done by SPECT-CT images coupled GATE Monte Carlo package for internal dosimetry. Methods: A 50 years old woman with bone metastases from breast cancer was prescribed 153-Sm treatment (Gamma: 103keV and beta: 0.81MeV). A SPECT/CT scan was performed with the Siemens Simbia-T scanner. SPECT and CT images were registered using default registration software. SPECT quantification was achieved by compensating for all image degrading factors including body attenuation, Compton scattering and collimator-detector response (CDR). Triple energy window method was used to estimate and eliminate the scattered photons. Iterative ordered-subsets expectation maximization (OSEM) with correction for attenuation and distance-dependent CDR was used for image reconstruction. Bilinear energy mapping is used to convert Hounsfield units in CT image to attenuation map. Organ borders were defined by the itk-SNAP toolkit segmentation on CT image. GATE was then used for internal dose calculation. The Specific Absorbed Fractions (SAFs) and S-values were reported as MIRD schema. Results: The results showed that the largest SAFs and S-values are in osseous organs as expected. S-value for lung is the highest after spine that can be important in 153-Sm therapy. Conclusion: We presented the utility of SPECT-CT images and Monte Carlo for patient-specific dosimetry as a reliable and accurate method. It has several advantages over template-based methods or simplified dose estimation methods. With advent of high speed computers, Monte Carlo can be used for treatment planning
Purpose: Patient-specific 3-dimensional (3D) internal dosimetry in targeted radionuclide therapy is essential for efficient treatment. Two major steps to achieve reliable results are: 1) generating quantitative 3D images of radionuclide distribution and attenuation coefficients and 2) using a reliable method for dose calculation based on activity and attenuation map. In this research, internal dosimetry for 153-Samarium (153-Sm) was done by SPECT-CT images coupled GATE Monte Carlo package for internal dosimetry. Methods: A 50 years old woman with bone metastases from breast cancer was prescribed 153-Sm treatment (Gamma: 103keV and beta: 0.81MeV). A SPECT/CT scan was performed with the Siemens Simbia-T scanner. SPECT and CT images were registered using default registration software. SPECT quantification was achieved by compensating for all image degrading factors including body attenuation, Compton scattering and collimator-detector response (CDR). Triple energy window method was used to estimate and eliminate the scattered photons. Iterative ordered-subsets expectation maximization (OSEM) with correction for attenuation and distance-dependent CDR was used for image reconstruction. Bilinear energy mapping is used to convert Hounsfield units in CT image to attenuation map. Organ borders were defined by the itk-SNAP toolkit segmentation on CT image. GATE was then used for internal dose calculation. The Specific Absorbed Fractions (SAFs) and S-values were reported as MIRD schema. Results: The results showed that the largest SAFs and S-values are in osseous organs as expected. S-value for lung is the highest after spine that can be important in 153-Sm therapy. Conclusion: We presented the utility of SPECT-CT images and Monte Carlo for patient-specific dosimetry as a reliable and accurate method. It has several advantages over template-based methods or simplified dose estimation methods. With advent of high speed computers, Monte Carlo can be used for treatment planning
Successful vectorization - reactor physics Monte Carlo code
Most particle transport Monte Carlo codes in use today are based on the ''history-based'' algorithm, wherein one particle history at a time is simulated. Unfortunately, the ''history-based'' approach (present in all Monte Carlo codes until recent years) is inherently scalar and cannot be vectorized. In particular, the history-based algorithm cannot take advantage of vector architectures, which characterize the largest and fastest computers at the current time, vector supercomputers such as the Cray X/MP or IBM 3090/600. However, substantial progress has been made in recent years in developing and implementing a vectorized Monte Carlo algorithm. This algorithm follows portions of many particle histories at the same time and forms the basis for all successful vectorized Monte Carlo codes that are in use today. This paper describes the basic vectorized algorithm along with descriptions of several variations that have been developed by different researchers for specific applications. These applications have been mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas. The relative merits of the various approach schemes will be discussed and the present status of known vectorization efforts will be summarized along with available timing results, including results from the successful vectorization of 3-D general geometry, continuous energy Monte Carlo. (orig.)
A Monte Carlo based spent fuel analysis safeguards strategy assessment
Fensin, Michael L [Los Alamos National Laboratory; Tobin, Stephen J [Los Alamos National Laboratory; Swinhoe, Martyn T [Los Alamos National Laboratory; Menlove, Howard O [Los Alamos National Laboratory; Sandoval, Nathan P [Los Alamos National Laboratory
2009-01-01
assessment process, the techniques employed to automate the coupled facets of the assessment process, and the standard burnup/enrichment/cooling time dependent spent fuel assembly library. We also clearly define the diversion scenarios that will be analyzed during the standardized assessments. Though this study is currently limited to generic PWR assemblies, it is expected that the results of the assessment will yield an adequate spent fuel analysis strategy knowledge that will help the down-select process for other reactor types.
Monte Carlo Neutronics and Thermal Hydraulics Analysis of Reactor Cores with Multilevel Grids
Bernnat, W.; Mattes, M.; Guilliard, N.; Lapins, J.; Zwermann, W.; Pasichnyk, I.; Velkov, K.
2014-06-01
Power reactors are composed of assemblies with fuel pin lattices or other repeated structures with several grid levels, which can be modeled in detail by Monte Carlo neutronics codes such as MCNP6 using corresponding lattice options, even for large cores. Except for fresh cores at beginning of life, there is a varying material distribution due to burnup in the different fuel pins. Additionally, for power states the fuel and moderator temperatures and moderator densities vary according to the power distribution and cooling conditions. Therefore, a coupling of the neutronics code with a thermal hydraulics code is necessary. Depending on the level of detail of the analysis, a very large number of cells with different materials and temperatures must be regarded. The assignment of different material properties to all elements of a multilevel grid is very elaborate and may exceed program limits if the standard input procedure is used. Therefore, an internal assignment is used which overrides uniform input parameters. The temperature dependency of continuous energy cross sections, probability tables for the unresolved resonance region and thermal neutron scattering laws is taken into account by interpolation, requiring only a limited number of data sets generated for different temperatures. The method is applied with MCNP6 and proven for several full core reactor models. For the coupling of MCNP6 with thermal hydraulics appropriate interfaces were developed for the GRS system code ATHLET for liquid coolant and the IKE thermal hydraulics code ATTICA-3D for gaseous coolant. Examples will be shown for different applications for PWRs with square and hexagonal lattices, fast reactors (SFR) with hexagonal lattices and HTRs with pebble bed and prismatic lattices.
Benchmark of Atucha-2 PHWR RELAP5-3D control rod model by Monte Carlo MCNP5 core calculation
Atucha-2 is a Siemens-designed PHWR reactor under construction in the Republic of Argentina. Its geometrical complexity and peculiarities require the adoption of advanced Monte Carlo codes for performing realistic neutronic simulations. Therefore core models of Atucha-2 PHWR were developed using MCNP5. In this work a methodology was set up to collect the flux in the hexagonal mesh by which the Atucha-2 core is represented. The scope of this activity is to evaluate the effect of obliquely inserted control rod on neutron flux in order to validate the RELAP5-3DC/NESTLE three dimensional neutron kinetic coupled thermal-hydraulic model, applied by GRNSPG/UNIPI for performing selected transients of Chapter 15 FSAR of Atucha-2. (authors)
Analysis of the tritium breeding ratio benchmark experiments using the Monte Carlo code TRIPOLI-4
Tritium breeding is an essential element of fusion nuclear technology. A tritium breeding ratio greater than unity is necessary for self-sufficient fueling. To simulate the 14 MeV neutron transport in tritium breeding systems from the D-T fusion reaction, the 3D realistic modeling with Monte Carlo code and the point-wise nuclear data are recommended. Continuous-energy TRIPOLI-4 Monte Carlo transport code has been widely used on the radiation shielding, criticality safety, and fission reactor physics. For supporting the ITER TBM (test blanket module) neutronics study with TRIPOLI-4 code, this paper presents the TRIPOLI-4 simulation of TBR (tritium breeding ratio) for six OKTAVIAN spherical assemblies of Osaka University: Li, Li-C, Pb-Li, Pb-Li-C, Be-Li, and Be-Li-C. It also investigates the impact of nuclear data libraries on TBR calculations from ENDF/B-VI.4, ENDF/B-VII.0, JEFF-3.1, JENDL-3.3, and FENDL-2.1. In general, TRIPOLI-4 produced satisfactory C/E values. Only beryllium of JEFF-3.1 library introduces higher uncertainties.
A vectorized Monte Carlo method with pseudo-scattering for neutron transport analysis
A vectorized Monte Carlo method has been developed for the neutron transport analysis on the vector supercomputer HITAC S810. In this method, a multi-particle tracking algorithm is adopted and fundamental processing such as pseudo-random number generation is modified to use the vector processor effectively. The flight analysis of this method is characterized by the new algorithm with pseudo-scattering. This algorithm was verified by comparing its results with those of the conventional one. The method realized a speed-up of factor 10; about 7 times by vectorization and 1.5 times by the new algorithm for flight analysis
Liao, Y.; Su, C. C.; Marschall, R.; Wu, J. S.; Rubin, M.; Lai, I. L.; Ip, W. H.; Keller, H. U.; Knollenberg, J.; Kührt, E.; Skorov, Y. V.; Thomas, N.
2016-03-01
Direct Simulation Monte Carlo (DSMC) is a powerful numerical method to study rarefied gas flows such as cometary comae and has been used by several authors over the past decade to study cometary outflow. However, the investigation of the parameter space in simulations can be time consuming since 3D DSMC is computationally highly intensive. For the target of ESA's Rosetta mission, comet 67P/Churyumov-Gerasimenko, we have identified to what extent modification of several parameters influence the 3D flow and gas temperature fields and have attempted to establish the reliability of inferences about the initial conditions from in situ and remote sensing measurements. A large number of DSMC runs have been completed with varying input parameters. In this work, we present the simulation results and conclude on the sensitivity of solutions to certain inputs. It is found that among cases of water outgassing, the surface production rate distribution is the most influential variable to the flow field.
Monte-Carlo Analysis of the Flavour Changing Neutral Current B \\to Gamma at Babar
Smith, D. [Imperial College, London (United Kingdom)
2001-09-01
The main theme of this thesis is a Monte-Carlo analysis of the rare Flavour Changing Neutral Current (FCNC) decay b→sγ. The analysis develops techniques that could be applied to real data, to discriminate between signal and background events in order to make a measurement of the branching ratio of this rare decay using the BaBar detector. Also included in this thesis is a description of the BaBar detector and the work I have undertaken in the development of the electronic data acquisition system for the Electromagnetic calorimeter (EMC), a subsystem of the BaBar detector.
First Monte Carlo analysis of fragmentation functions from single-inclusive $e^+ e^-$ annihilation
Sato, N; Melnitchouk, W; Hirai, M; Kumano, S; Accardi, A
2016-01-01
We perform the first iterative Monte Carlo (IMC) analysis of fragmentation functions constrained by all available data from single-inclusive $e^+ e^-$ annihilation into pions and kaons. The IMC method eliminates potential bias in traditional analyses based on single fits introduced by fixing parameters not well contrained by the data and provides a statistically rigorous determination of uncertainties. Our analysis reveals specific features of fragmentation functions using the new IMC methodology and those obtained from previous analyses, especially for light quarks and for strange quark fragmentation to kaons.
A domain decomposed Monte Carlo communication kernel is used to carry out performance tests to establish the feasibility of using Monte Carlo techniques for practical Light Water Reactor (LWR) core analyses. The results of the prototype code are interpreted in the context of simplified performance models which elucidate key scaling regimes of the parallel algorithm.
MKENO-DAR: a direct angular representation Monte Carlo code for criticality safety analysis
Improving the Monte Carlo code MULTI-KENO, the MKENO-DAR (Direct Angular Representation) code has been developed for criticality safety analysis in detail. A function was added to MULTI-KENO for representing anisotropic scattering strictly. With this function, the scattering angle of neutron is determined not by the average scattering angle μ-bar of the Pl Legendre polynomial but by the random work operation using probability distribution function produced with the higher order Legendre polynomials. This code is avilable for the FACOM-M380 computer. This report is a computer code manual for MKENO-DAR. (author)
FTREE. Single-history Monte Carlo analysis for radiation detection and measurement
This work introduces FTREE, which describes radiation cascades following impingement of a source particle on matter. The ensuing radiation field is characterised interaction by interaction, accounting for each generation of secondaries recursively. Each progeny is uniquely differentiated and catalogued into a family tree; the kinship is identified without ambiguity. This mode of observation, analysis and presentation goes beyond present-day detector technologies, beyond conventional Monte Carlo simulations and beyond standard pedagogy. It is able to observe rare events far out in the Gaussian tail which would have been lost in averaging-events less probable, but no less correct in physics. (author)
Microlens assembly error analysis for light field camera based on Monte Carlo method
Li, Sai; Yuan, Yuan; Zhang, Hao-Wei; Liu, Bin; Tan, He-Ping
2016-08-01
This paper describes numerical analysis of microlens assembly errors in light field cameras using the Monte Carlo method. Assuming that there were no manufacturing errors, home-built program was used to simulate images of coupling distance error, movement error and rotation error that could appear during microlens installation. By researching these images, sub-aperture images and refocus images, we found that the images present different degrees of fuzziness and deformation for different microlens assembly errors, while the subaperture image presents aliasing, obscured images and other distortions that result in unclear refocus images.
Markov chain Monte Carlo linkage analysis of a complex qualitative phenotype.
Hinrichs, A; Lin, J H; Reich, T; Bierut, L; Suarez, B K
1999-01-01
We tested a new computer program, LOKI, that implements a reversible jump Markov chain Monte Carlo (MCMC) technique for segregation and linkage analysis. Our objective was to determine whether this software, designed for use with continuously distributed phenotypes, has any efficacy when applied to the discrete disease states of the simulated data from the Mordor data from GAW Problem 1. Although we were able to identify the genomic location for two of the three quantitative trait loci by repeated application of the software, the MCMC sampler experienced significant mixing problems indicating that the method, as currently formulated in LOKI, was not suitable for the discrete phenotypes in this data set. PMID:10597502
In this research, we used a 135 MeV/nucleon carbon-ion beam to irradiate a biological sample composed of fresh chicken meat and bones, which was placed in front of a PAGAT gel dosimeter, and compared the measured and simulated transverse-relaxation-rate (R2) distributions in the gel dosimeter. We experimentally measured the three-dimensional R2 distribution, which records the dose induced by particles penetrating the sample, by using magnetic resonance imaging. The obtained R2 distribution reflected the heterogeneity of the biological sample. We also conducted Monte Carlo simulations using the PHITS code by reconstructing the elemental composition of the biological sample from its computed tomography images while taking into account the dependence of the gel response on the linear energy transfer. The simulation reproduced the experimental distal edge structure of the R2 distribution with an accuracy under about 2 mm, which is approximately the same as the voxel size currently used in treatment planning. (paper)
Hao Wang; Guo-quan Liu; Xiang-ge Qin
2009-01-01
Three-dimensional normal grain growth was appropriately simulated using a Potts model Monte Carlo algorithm.The quasi-stationary grain size distribution obtained from simulation agreed well with the experimental result of pure iron.The Weibull function with a parameter β=2.77 and the Yu-Liu function with a parameter v =2.71 fit the quasi-stationary grain size distribution well.The grain volume distribution is a function that decreased exponentially with increasing grain volume.The distribution of boundary area of grains has a peak at S/=0.5,where S is the boundary area of a grain and is the mean boundary area of all grains in the system.The lognormal function fits the face number distribution well and the peak of the face number distribution is f=10.The mean radius of f=faced grains is not proportional to the face number,but appears to be related by a curve convex upward.In the 2D cross-section,both the perimeter law and the Aboav-Weaire law are observed to hold.
Furuta, T.; Maeyama, T.; Ishikawa, K. L.; Fukunishi, N.; Fukasaku, K.; Takagi, S.; Noda, S.; Himeno, R.; Hayashi, S.
2015-08-01
In this research, we used a 135 MeV/nucleon carbon-ion beam to irradiate a biological sample composed of fresh chicken meat and bones, which was placed in front of a PAGAT gel dosimeter, and compared the measured and simulated transverse-relaxation-rate (R2) distributions in the gel dosimeter. We experimentally measured the three-dimensional R2 distribution, which records the dose induced by particles penetrating the sample, by using magnetic resonance imaging. The obtained R2 distribution reflected the heterogeneity of the biological sample. We also conducted Monte Carlo simulations using the PHITS code by reconstructing the elemental composition of the biological sample from its computed tomography images while taking into account the dependence of the gel response on the linear energy transfer. The simulation reproduced the experimental distal edge structure of the R2 distribution with an accuracy under about 2 mm, which is approximately the same as the voxel size currently used in treatment planning.
Proper interpretation of space based critical velocity ionization experiments depends upon understanding the expected results from in-situ or remote sensors. A three-dimensional electromagnetic Particle-in-Cell code with Monte Carlo charged particle-neutral collisions has been developed to model CIV interactions in typical neutral gas release experiments. In the model, the released neutral gas is taken to be a spherical cloud traveling with a constant density and velocity rvec υn across the geomagnetic field rvec B0. Then dynamics of the plasma ionized from the neutral cloud are studied, and the induced instabilities are discussed. The simulations show that the newly ionized plasma evolves to form an ''asymmetric sphere-sheet tail'' structure: the ions mainly drift with the neutral cloud and expand in the rvec υ x rvec B0 direction; the electrons are trapped by the magnetic field and form a curved ''sheet-like'' tail which spreads along the rvec B0 direction. The ionization rate determines the structure shape. Significant ion density enhancement occurs only in the core region of the neutral gas cloud. It is shown that the detection of CIV in an ionospheric gas release experiment critically depends on the sensor location
Uncertainty Assessment of the Core Thermal-Hydraulic Analysis Using the Monte Carlo Method
Choi, Sun Rock; Yoo, Jae Woon; Hwang, Dae Hyun; Kim, Sang Ji [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2010-10-15
In the core thermal-hydraulic design of a sodium cooled fast reactor, the uncertainty factor analysis is a critical issue in order to assure safe and reliable operation. The deviations from the nominal values need to be quantitatively considered by statistical thermal design methods. The hot channel factors (HCF) were employed to evaluate the uncertainty in the early design such as the CRBRP. The improved thermal design procedure (ISTP) calculates the overall uncertainty based on the Root Sum Square technique and sensitivity analyses of each design parameters. Another way to consider the uncertainties is to use the Monte Carlo method (MCM). In this method, all the input uncertainties are randomly sampled according to their probability density functions and the resulting distribution for the output quantity is analyzed. It is able to directly estimate the uncertainty effects and propagation characteristics for the present thermalhydraulic model. However, it requires a huge computation time to get a reliable result because the accuracy is dependent on the sampling size. In this paper, the analysis of uncertainty factors using the Monte Carlo method is described. As a benchmark model, the ORNL 19 pin test is employed to validate the current uncertainty analysis method. The thermal-hydraulic calculation is conducted using the MATRA-LMR program which was developed at KAERI based on the subchannel approach. The results are compared with those of the hot channel factors and the improved thermal design procedure
Monte Carlo analysis of Very High Temperature gas-cooled Reactor for hydrogen production
This work has been pursued during 2 years. In the first year, the development of Monte Carlo analysis method for pebble-type VHTR core was focused with zero-power reactor. The pebble-bed cores of HTR-PROTEUS critical facility in Switzerland were selected for the benchmark model and detailed full-scope MCNP modeling was carried out. Especially, accurate and effective modeling of UO2 particles and their distributions in fuel pebble was pursed as well as the pebbles distribution within core region. After the detailed MCNP modeling of the whole facility, analyses of nuclear characteristics were carried out, and the results were compared with experiments and those of other research groups. The effective multiplication factors (keff) were calculated for the two HTR-PROTEUS cores, and then homogenization effect of TRISO fuel on criticality investigated. Control rod and shutdown rod worths were also calculated, and the criticality calculations with different cross-section library and various reflector thickness were carried out. In the 2nd year of the research period, the Monte Carol analysis method developed in the 1st year was applied to the core with thermal power. The pebble-bed cores of HTR-10 test reactor in China were selected for the benchmark model. After the detailed full-scope MCNP modeling the Monte Carlo analysis results calculated in this work were verified with the benchmark results which have been done for first criticality state and initial core
Full text of publication follows. Purpose: a 3D-Personalized Monte Carlo Dosimetry (PMCD) was developed for treatment planning in nuclear medicine. The method was applied to Selective Internal Radiation Therapy (SIRT) using 90Y-microspheres for unresectable hepatic cancers. Methods: The PMCD method was evaluated for 20 patients treated for hepatic metastases or hepatocellular carcinoma at the European Hospital Georges Pompidou (Paris). First, regions of interest were outlined on the patient CT images. Using the OEDIPE software, patient-specific voxel phantoms were created. 99mTc-MAA SPECT data were then used to generate 3D-matrices of cumulated activity. Absorbed doses and Biologically Effective Dose (BED) were calculated at the voxel scale using the MCNPX Monte Carlo transport code. Finally, OEDIPE was used to determine the maximum injectable activity (MIA) for tolerance criteria on organs at risk (OARs), i.e. the lungs and non tumoral liver (NTL). Tolerance criteria based on mean absorbed doses, mean BED, Dose-Volume Histograms (DVHs) or BED-Volume Histograms (BVHs) were considered. Those MIAs were compared to the Partition Model with tolerance criteria on mean absorbed doses, which is a conventional method applied in clinical practice. Results: compared to Partition Model recommendations, performing dosimetry using the PMCD method enables to increase the activity prescription while ensuring OARs' radiation protection. Moreover, tolerance criteria based on DVHs allow us to enhance treatment planning efficiency by taking advantage of the parallel characteristic of the liver and the lungs, whose functions are not impaired if the level of irradiation to a fraction of the organ is kept sufficiently low. Finally, multi-cycle treatments based on tolerance criteria on mean BED and BVHs, were considered to go further in the dose optimization, taking into account biological considerations such as cell repair or radiosensitivity. Conclusion: besides its feasibility
Use of Monte Carlo simulations for cultural heritage X-ray fluorescence analysis
Brunetti, Antonio, E-mail: brunetti@uniss.it [Polcoming Department, University of Sassari (Italy); Golosio, Bruno [Polcoming Department, University of Sassari (Italy); Schoonjans, Tom; Oliva, Piernicola [Chemical and Pharmaceutical Department, University of Sassari (Italy)
2015-06-01
The analytical study of Cultural Heritage objects often requires merely a qualitative determination of composition and manufacturing technology. However, sometimes a qualitative estimate is not sufficient, for example when dealing with multilayered metallic objects. Under such circumstances a quantitative estimate of the chemical contents of each layer is sometimes required in order to determine the technology that was used to produce the object. A quantitative analysis is often complicated by the surface state: roughness, corrosion, incrustations that remain even after restoration, due to efforts to preserve the patina. Furthermore, restorers will often add a protective layer on the surface. In all these cases standard quantitative methods such as the fundamental parameter based approaches are generally not applicable. An alternative approach is presented based on the use of Monte Carlo simulations for quantitative estimation. - Highlights: • We present an application of fast Monte Carlo codes for Cultural Heritage artifact analysis. • We show applications to complex multilayer structures. • The methods allow estimating both the composition and the thickness of multilayer, such as bronze with patina. • The performance in terms of accuracy and uncertainty is described for the bronze samples.
Standard modeling approaches can produce the most likely values of the formation constants of metal-ligand complexes if a particular set of species containing the metal ion is known or assumed to exist in solution equilibrium with complexing ligands. Identifying the most likely set of species when more than one set is plausible is a more difficult problem to address quantitatively. A Monte Carlo method of data analysis is described that measures the relative abilities of different speciation models to fit optical spectra of open-shell actinide ions. The best model(s) can be identified from among a larger group of models initially judged to be plausible. The method is demonstrated by analyzing the absorption spectra of aqueous Pu(IV) titrated with nitrate ion at constant 2 molal ionic strength in aqueous perchloric acid. The best speciation model supported by the data is shown to include three Pu(IV) species with nitrate coordination numbers 0, 1, and 2. Formation constants are β1=3.2±0.5 and β2=11.2±1.2, where the uncertainties are 95% confidence limits estimated by propagating raw data uncertainties using Monte Carlo methods. Principal component analysis independently indicates three Pu(IV) complexes in equilibrium. (c) 2000 Society for Applied Spectroscopy
Use of Monte Carlo simulations for cultural heritage X-ray fluorescence analysis
The analytical study of Cultural Heritage objects often requires merely a qualitative determination of composition and manufacturing technology. However, sometimes a qualitative estimate is not sufficient, for example when dealing with multilayered metallic objects. Under such circumstances a quantitative estimate of the chemical contents of each layer is sometimes required in order to determine the technology that was used to produce the object. A quantitative analysis is often complicated by the surface state: roughness, corrosion, incrustations that remain even after restoration, due to efforts to preserve the patina. Furthermore, restorers will often add a protective layer on the surface. In all these cases standard quantitative methods such as the fundamental parameter based approaches are generally not applicable. An alternative approach is presented based on the use of Monte Carlo simulations for quantitative estimation. - Highlights: • We present an application of fast Monte Carlo codes for Cultural Heritage artifact analysis. • We show applications to complex multilayer structures. • The methods allow estimating both the composition and the thickness of multilayer, such as bronze with patina. • The performance in terms of accuracy and uncertainty is described for the bronze samples
Neutronic Analysis of the 3 MW TRIGA MARK II Research Reactor, Part I: Monte Carlo Simulation
This study deals with the neutronic analysis of the current core configuration of a 3 MW TRIGA MARK II research reactor at Atomic Energy Research Establishment (AERE), Savar, Dhaka, Bangladesh and validation of the results by benchmarking with the experimental, operational and available Final Safety Analysis Report (FSAR) values. The three-dimensional continuous-energy Monte Carlo code MCNP4C was used to develop a versatile and accurate full-core model of the TRIGA core. The model represents in detail all components of the core with literally no physical approximation. All fresh fuel and control elements as well as the vicinity of the core were precisely described. Continuous energy cross-section data from ENDF/B-VI and S(α, β) scattering functions from the ENDF/B-V library were used. The validation of the model against benchmark experimental results is presented. The MCNP predictions and the experimentally determined values are found to be in very good agreement, which indicates that the Monte Carlo model is correctly simulating the TRIGA reactor. (author)
Monte Carlo simulation for slip rate sensitivity analysis in Cimandiri fault area
Pratama, Cecep, E-mail: great.pratama@gmail.com [Graduate Program of Earth Science, Faculty of Earth Science and Technology, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia); Meilano, Irwan [Geodesy Research Division, Faculty of Earth Science and Technology, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia); Nugraha, Andri Dian [Global Geophysical Group, Faculty of Mining and Petroleum Engineering, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia)
2015-04-24
Slip rate is used to estimate earthquake recurrence relationship which is the most influence for hazard level. We examine slip rate contribution of Peak Ground Acceleration (PGA), in probabilistic seismic hazard maps (10% probability of exceedance in 50 years or 500 years return period). Hazard curve of PGA have been investigated for Sukabumi using a PSHA (Probabilistic Seismic Hazard Analysis). We observe that the most influence in the hazard estimate is crustal fault. Monte Carlo approach has been developed to assess the sensitivity. Then, Monte Carlo simulations properties have been assessed. Uncertainty and coefficient of variation from slip rate for Cimandiri Fault area has been calculated. We observe that seismic hazard estimates is sensitive to fault slip rate with seismic hazard uncertainty result about 0.25 g. For specific site, we found seismic hazard estimate for Sukabumi is between 0.4904 – 0.8465 g with uncertainty between 0.0847 – 0.2389 g and COV between 17.7% – 29.8%.
In consideration of application for reprocessing facility, where a variety of causal events such as equipment failure and human error might occur, and the event progression would take place with relatively substantial time delay before getting to the accident stage, a component Monte Carlo program for accident sequence analysis has been developed to pursue chronologically the probabilistic behavior of each component failure and repair in an exact manner. In comparison with analytical formulation and its calculated results, this Monte Carlo technique is shown to predict a reasonable result. Then, taking an example for a sample problem from a German reprocessing facility model, an accident sequence of red-oil explosion in a plutonium evaporator is analyzed to give a comprehensive interpretation about statistic variation range and computer time elapsed for random walk history calculations. Furthermore, to discuss about its applicability for the practical case of plant system with complex component constitution, a possibility of drastic speed-up of computation is shown by parallelization of the computer program. (author)
Monte Carlo simulation for slip rate sensitivity analysis in Cimandiri fault area
Slip rate is used to estimate earthquake recurrence relationship which is the most influence for hazard level. We examine slip rate contribution of Peak Ground Acceleration (PGA), in probabilistic seismic hazard maps (10% probability of exceedance in 50 years or 500 years return period). Hazard curve of PGA have been investigated for Sukabumi using a PSHA (Probabilistic Seismic Hazard Analysis). We observe that the most influence in the hazard estimate is crustal fault. Monte Carlo approach has been developed to assess the sensitivity. Then, Monte Carlo simulations properties have been assessed. Uncertainty and coefficient of variation from slip rate for Cimandiri Fault area has been calculated. We observe that seismic hazard estimates is sensitive to fault slip rate with seismic hazard uncertainty result about 0.25 g. For specific site, we found seismic hazard estimate for Sukabumi is between 0.4904 – 0.8465 g with uncertainty between 0.0847 – 0.2389 g and COV between 17.7% – 29.8%
Monte Carlo analysis of the measurements of Smith et al. of the number of fission neutrons produced per neutron absorbed, eta, for 2200 m/sec neutrons absorbed by 233U and 235U yields: eta2200233 = 2.2993 +- 0.0082 and eta2200235 = 2.0777 +- 0.0064. The standard deviations include Monte Carlo, cross section, and experimental uncertainties. The Monte Carlo analysis was confirmed by calculating measured quantities used by the experimentalists in determining eta2200
1 - Nature of physical problem solved: The function of the AIRTRANS system is to calculate by Monte Carlo methods the radiation field produced by neutron and/or gamma-ray sources which are located in the atmosphere. The radiation field is expressed as the time - and energy-dependent flux at a maximum of 50 point detectors in the atmosphere. The system calculates un-collided fluxes analytically and collided fluxes by the 'once-more collided' flux-at-a-point technique. Energy-dependent response functions can be applied to the fluxes to obtain desired flux functionals, such as doses, at the detector point. AIRTRANS also can be employed to generate sources of secondary gamma radiation. 2 - Method of solution - Neutron interactions treated in the calculational scheme include elastic (isotropic and anisotropic) scattering, inelastic (discrete level and continuum) scattering, and absorption. Charged particle reactions, e.g, (n,p) are treated as absorptions. A built-in kernel option can be employed to take neutrons from the 150 keV to thermal energy, thus eliminating the need for particle tracking in this energy range. Another option used in conjunction with the neutron transport problem creates an 'interaction tape' which describes all the collision events that can lead to the production of secondary gamma-rays. This interaction tape subsequently can be used to generate a source of secondary gamma rays. The gamma-ray interactions considered include Compton scattering, pair production, and the photoelectric effect; the latter two processes are treated as absorption events. Incorporated in the system is an option to use a simple importance sampling technique for detectors that are many mean free paths from the source. In essence, particles which fly far from the source are split into fragments, the degree of fragmentation being proportional to the penetration distance from the source. Each fragment is tracked separately, thus increasing the percentage of computer time spent
BOT3P consists of a set of standard Fortran 77 language programs that gives the users of the deterministic transport codes DORT, TORT, TWODANT, THREEDANT, PARTISN and the sensitivity code SUSD3D some useful diagnostic tools to prepare and check the geometry of their input data files for both Cartesian and cylindrical geometries, including graphical display modules. Users can produce the geometrical and material distribution data for all the cited codes for both two-dimensional and three-dimensional applications and, only in 3-dimensional Cartesian geometry, for the Monte Carlo Transport Code MCNP, starting from the same BOT3P input. Moreover, BOT3P stores the fine mesh arrays and the material zone map in a binary file, the content of which can be easily interfaced to any deterministic and Monte Carlo transport code. This makes it possible to compare directly for the same geometry the effects stemming from the use of different data libraries and solution approaches on transport analysis results. BOT3P Version 5.0 lets users optionally and with the desired precision compute the area/volume error of material zones with respect to the theoretical values, if any, because of the stair-cased representation of the geometry, and automatically update material densities on the whole zone domains to conserve masses. A local (per mesh) density correction approach is also available. BOT3P is designed to run on Linux/UNIX platforms and is publicly available from the Organization for Economic Cooperation and Development (OECD/NEA)/Nuclear Energy Agency Data Bank. Through the use of BOT3P, radiation transport problems with complex 3-dimensional geometrical structures can be modelled easily, as a relatively small amount of engineer-time is required and refinement is achieved by changing few parameters. This tool is useful for solving very large challenging problems, as successfully demonstrated not only in some complex neutron shielding and criticality benchmarks but also in a power
Shutdown dose rate (SDDR) inside and around the diagnostics ports of ITER is performed at PPPL/UCLA using the 3-D, FEM, Discrete Ordinates code, ATTILA, along with its updated FORNAX transmutation/decay gamma library. Other ITER partners assess SDDR using codes based on the Monte Carlo (MC) approach (e.g. MCNP code) for transport calculation and the radioactivity inventory code FISPACT or other equivalent decay data libraries for dose rate assessment. To reveal the range of discrepancies in the results obtained by various analysts, an extensive experimental and calculation benchmarking effort has been undertaken to validate the capability of ATTILA for dose rate assessment. On the experimental validation front, the comparison was performed using the measured data from two SDDR experiments performed at the FNG facility, Italy. Comparison was made to the experimental data and to MC results obtained by other analysts. On the calculation validation front, the ATTILA's predictions were compared to other results at key locations inside a calculation benchmark whose configuration duplicates an upper diagnostics port plug (UPP) in ITER. Both serial and parallel version of ATTILA-7.1.0 are used in the PPPL/UCLA analysis performed with FENDL-2.1/FORNAX databases. In the FNG 1st experimental, it was shown that ATTILA's dose rates are largely over estimated (by ∼30–60%) with the ANSI/ANS-6.1.1 flux-to-dose factors whereas the ICRP-74 factors give better agreement (10–20%) with the experimental data and with the MC results at all cooling times. In the 2nd experiment, there is an under estimation in SDDR calculated by both MCNP and ATTILA based on ANSI/ANS-6.1.1 for cooling times up to ∼4 days after irradiation. Thereafter, an over estimation is observed (∼5–10% with MCNP and ∼10–15% with ATTILA). As for the calculation benchmark, the agreement is much better based on ICRP-74 1996 data. The divergence among all dose rate results at ∼11 days cooling time is no
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.)
Data uncertainty analysis for safety assessment of HLW disposal by the Monte Carlo simulation
Based on the conceptual model of the Reference Case, which is defined as the baseline for various cases in the safety assessment of the H12 report, a new probabilistic simulation code that allowed rapid evaluation of the effect of data uncertainty has been developed. Using this code, probabilistic simulation was performed by the Monte Carlo method and conservativeness and sufficiency of the safety assessment in the H12 report was confirmed, which was performed deterministically. In order to examine the important parameter, this study includes the analysis of sensitivity structure among the input and the output. Cluster analysis and multiple regression analysis for each cluster were applied in this analysis. As a result, the transmissivity had a strong influence on the uncertainty of the system performance. Furthermore, this approach was confirmed to evaluate the global sensitive parameters and local sensitive parameters that strongly influence the space of the partial simulation results. (author)
The timing resolution of scintillation-detector systems: Monte Carlo analysis
Recent advancements in fast scintillating materials and fast photomultiplier tubes (PMTs) have stimulated renewed interest in time-of-flight (TOF) positron emission tomography (PET). It is well known that the improvement in the timing resolution in PET can significantly reduce the noise variance in the reconstructed image resulting in improved image quality. In order to evaluate the timing performance of scintillation detectors used in TOF PET, we use Monte Carlo analysis to model the physical processes (crystal geometry, crystal surface finish, scintillator rise time, scintillator decay time, photoelectron yield, PMT transit time spread, PMT single-electron response, amplifier response and time pick-off method) that can contribute to the timing resolution of scintillation-detector systems. In the Monte Carlo analysis, the photoelectron emissions are modeled by a rate function, which is used to generate the photoelectron time points. The rate function, which is simulated using Geant4, represents the combined intrinsic light emissions of the scintillator and the subsequent light transport through the crystal. The PMT output signal is determined by the superposition of the PMT single-electron response resulting from the photoelectron emissions. The transit time spread and the single-electron gain variation of the PMT are modeled in the analysis. Three practical time pick-off methods are considered in the analysis. Statistically, the best timing resolution is achieved with the first photoelectron timing. The calculated timing resolution suggests that a leading edge discriminator gives better timing performance than a constant fraction discriminator and produces comparable results when a two-threshold or three-threshold discriminator is used. For a typical PMT, the effect of detector noise on the timing resolution is negligible. The calculated timing resolution is found to improve with increasing mean photoelectron yield, decreasing scintillator decay time and
The timing resolution of scintillation-detector systems: Monte Carlo analysis.
Choong, Woon-Seng
2009-11-01
Recent advancements in fast scintillating materials and fast photomultiplier tubes (PMTs) have stimulated renewed interest in time-of-flight (TOF) positron emission tomography (PET). It is well known that the improvement in the timing resolution in PET can significantly reduce the noise variance in the reconstructed image resulting in improved image quality. In order to evaluate the timing performance of scintillation detectors used in TOF PET, we use Monte Carlo analysis to model the physical processes (crystal geometry, crystal surface finish, scintillator rise time, scintillator decay time, photoelectron yield, PMT transit time spread, PMT single-electron response, amplifier response and time pick-off method) that can contribute to the timing resolution of scintillation-detector systems. In the Monte Carlo analysis, the photoelectron emissions are modeled by a rate function, which is used to generate the photoelectron time points. The rate function, which is simulated using Geant4, represents the combined intrinsic light emissions of the scintillator and the subsequent light transport through the crystal. The PMT output signal is determined by the superposition of the PMT single-electron response resulting from the photoelectron emissions. The transit time spread and the single-electron gain variation of the PMT are modeled in the analysis. Three practical time pick-off methods are considered in the analysis. Statistically, the best timing resolution is achieved with the first photoelectron timing. The calculated timing resolution suggests that a leading edge discriminator gives better timing performance than a constant fraction discriminator and produces comparable results when a two-threshold or three-threshold discriminator is used. For a typical PMT, the effect of detector noise on the timing resolution is negligible. The calculated timing resolution is found to improve with increasing mean photoelectron yield, decreasing scintillator decay time and
Within the framework of the Second Agreement 'Nucleoelectrica Argentina-SA - University of Pisa', a complex three dimensional (3D) neutron kinetics (NK) coupled thermal-hydraulic (TH) RELAP5-3D model of the Atucha 2 PHWR has been developed and validated. Homogenized cross section database was produced by the lattice physics code HELIOS. In order to increase the level of confidence on the results of such sophisticated models, an independent Monte Carlo code model, based on the MONTEBURNS package (MCNP5 + ORIGEN), has been set up. The scope of this activity is to obtain a systematic check of the deterministic codes results. This necessity is particularly felt in the case of Atucha-2 reactor modeling, since its own peculiarities (e.g., oblique Control Rods, Positive Void Coefficient) and since, if approved by the Argentinean Safety Authority, the RELAP53D 3D NK TH model will constitute the first application of a neutronic thermal-hydraulics coupled code techniques to a reactor licensing project. (authors)
Current status of safety analysis code MARS and uncertainty quantification by Monte-Carlo method
MARS (Multi-dimensional Analysis of Reactor Safety) code has been developed since 1997 for a realistic multi-dimensional thermal-hydraulic system analysis of light water reactor transients. The backbones of MARS are the RELAP5/MOD3.2.1.2 and COBRA-TF codes of USNRC. These two codes were consolidated into a single code by integrating the hydrodynamic solution schemes. New multidimensional TH model has been developed and extended to enable integrated coupled TH analysis through code coupling technique, DLL. The motivation for uncertainty quantification of MARS is considered twofold, 1) to provide “best estimate plus uncertainty” analysis for licensing of commercial power reactor with realistic margins, and 2) to provide support to design and/or validation related analysis for research and production reactors. An assessment of the current LBLOCA uncertainty analysis methodology has been done using data from an integral thermal-hydraulic experiment LOFT L2-5. Monte Carlo calculation has been performed and compared with the tolerance level determined by Wilks formula. The calculation has been done within reasonable CPU time on PC cluster system. Monte-Carlo exercise shows that the 95% upper limit value can be obtained well with 95% confidence level by Wilks formula, although we have to endure 5% risk of PCT under-prediction. The result also shows the statistical fluctuation of limit value using Wilks 1st order is as large as PCT uncertainty itself. The main conclusion is that it is desirable to increase the order of Wilks formula to be higher than the second order to get the reliable safety margin of current design feature. (author)
Refined Monte Carlo analysis of the H.B. Robinson-2 reactor pressure vessel dosimetry benchmark
Highlights: → Activation of in- and ex-vessel radiometric dosimeters is studied with MCNPX. → Influences of neutron source definition and cross-section libraries are examined. → 237Np(n,f) energy cut-off is set at 10 eV to cover the reaction completely. → Different methods for deriving activities from reaction rates are compared. → Uncertainties are evaluated and are below 10%, final C/E ratios being within 15%. - Abstract: Refined analysis, based on use of the Monte Carlo code MCNPX-2.4.0, is presented for the 'H.B. Robinson-2 pressure vessel dosimetry benchmark', which is a part of the Radiation Shielding and Dosimetry Experiments Database (SINBAD). First, the performance of the Monte Carlo methodology is reassessed relative to the reported deterministic results obtained with DORT. Thereby, the analysis is accompanied by a quantitative evaluation of the optimal energy cut-off value for each of the in- and ex-vessel dosimeters that were employed. Second, a more realistic definition of the neutron source is implemented than proposed in the benchmark. Thus, the current procedure for power-to-neutron-source-strength conversion, as also for explicitly considering the burnup-dependent fuel assembly-wise average fission neutron spectrum, is found to affect the calculated values significantly. In addition to the modelling refinements made, different approaches are tested for deriving the dosimeter activities, such that the neutron source time-evolution and the activity decay can be taken into account more accurately. Finally, in order to achieve a certain assessment of uncertainties, several sensitivity studies are carried out, e.g. with respect to the nuclear data used for the dosimeters, as also to the assumed physical location of the dosimeters. In spite of some apparent degradation in the prediction of experimental results when refining the Monte Carlo modelling, the final calculation/experiment (C/E) ratios for the measured dosimeter activities remain
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.
A bottom collider vertex detector design, Monte-Carlo simulation and analysis package
A detailed simulation of the BCD vertex detector is underway. Specifications and global design issues are briefly reviewed. The BCD design based on double sided strip detector is described in more detail. The GEANT3-based Monte-Carlo program and the analysis package used to estimate detector performance are discussed in detail. The current status of the expected resolution and signal to noise ratio for the ''golden'' CP violating mode Bd → π+π- is presented. These calculations have been done at FNAL energy (√s = 2.0 TeV). Emphasis is placed on design issues, analysis techniques and related software rather than physics potentials. 20 refs., 46 figs
Core-scale solute transport model selection using Monte Carlo analysis
Malama, Bwalya; James, Scott C
2013-01-01
Model applicability to core-scale solute transport is evaluated using breakthrough data from column experiments conducted with conservative tracers tritium (H-3) and sodium-22, and the retarding solute uranium-232. The three models considered are single-porosity, double-porosity with single-rate mobile-immobile mass-exchange, and the multirate model, which is a deterministic model that admits the statistics of a random mobile-immobile mass-exchange rate coefficient. The experiments were conducted on intact Culebra Dolomite core samples. Previously, data were analyzed using single- and double-porosity models although the Culebra Dolomite is known to possess multiple types and scales of porosity, and to exhibit multirate mobile-immobile-domain mass transfer characteristics at field scale. The data are reanalyzed here and null-space Monte Carlo analysis is used to facilitate objective model selection. Prediction (or residual) bias is adopted as a measure of the model structural error. The analysis clearly shows ...
Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations
In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-“coupled”- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz–Kalos–Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary
Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations
Arampatzis, Georgios; Katsoulakis, Markos A.
2014-03-01
In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-"coupled"- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz-Kalos-Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary MATLAB
Dubecký, Matúš; Jurečka, Petr; Mitas, Lubos; Hobza, Pavel; Otyepka, Michal
2014-01-01
Reliable theoretical predictions of noncovalent interaction energies, which are important e.g. in drug-design and hydrogen-storage applications, belong to longstanding challenges of contemporary quantum chemistry. In this respect, the fixed-node diffusion Monte Carlo (FN-DMC) is a promising alternative to the commonly used ``gold standard'' coupled-cluster CCSD(T)/CBS method for its benchmark accuracy and favourable scaling, in contrast to other correlated wave function approaches. This work is focused on the analysis of protocols and possible tradeoffs for FN-DMC estimations of noncovalent interaction energies and proposes a significantly more efficient yet accurate computational protocol using simplified explicit correlation terms. Its performance is illustrated on a number of weakly bound complexes, including water dimer, benzene/hydrogen, T-shape benzene dimer and stacked adenine-thymine DNA base pair complex. The proposed protocol achieves excellent agreement ($\\sim$0.2 kcal/mol) with respect to the reli...
2D Monte Carlo analysis of radiological risk assessment for the food intake in Korea
Most public health risk assessments assume and combine a series of average, conservative and worst-case values to derive an acceptable point estimate of risk. To improve quality of risk information, insight of uncertainty in the assessments is needed and more emphasis is put on the probabilistic risk assessment. Probabilistic risk assessment studies use probability distributions for one or more variables of the risk equation in order to quantitatively characterize variability and uncertainty. In this study, an advanced technique called the two-dimensional Monte Carlo analysis (2D MCA) is applied to estimation of internal doses from intake of radionuclides in foodstuffs and drinking water in Korea. The variables of the risk model along with the parameters of these variables are described in terms of probability density functions (PDFs). In addition, sensitivity analyses were performed to identify important factors to the radiation doses. (author)
Predictive uncertainty analysis of a saltwater intrusion model using null-space Monte Carlo
Herckenrath, Daan; Langevin, Christian D.; Doherty, John
2011-01-01
. Random noise was added to the observations to approximate realistic field conditions. The NSMC method was used to calculate 1000 calibration-constrained parameter fields. If the dimensionality of the solution space was set appropriately, the estimated uncertainty range from the NSMC analysis encompassed......Because of the extensive computational burden and perhaps a lack of awareness of existing methods, rigorous uncertainty analyses are rarely conducted for variable-density flow and transport models. For this reason, a recently developed null-space Monte Carlo (NSMC) method for quantifying prediction...... the truth. Several variants of the method were implemented to investigate their effect on the efficiency of the NSMC method. Reducing the dimensionality of the null-space for the processing of the random parameter sets did not result in any significant gains in efficiency and compromised the ability...
Ligand-receptor binding kinetics in surface plasmon resonance cells: A Monte Carlo analysis
Carroll, Jacob; Forsten-Williams, Kimberly; Täuber, Uwe C
2016-01-01
Surface plasmon resonance (SPR) chips are widely used to measure association and dissociation rates for the binding kinetics between two species of chemicals, e.g., cell receptors and ligands. It is commonly assumed that ligands are spatially well mixed in the SPR region, and hence a mean-field rate equation description is appropriate. This approximation however ignores the spatial fluctuations as well as temporal correlations induced by multiple local rebinding events, which become prominent for slow diffusion rates and high binding affinities. We report detailed Monte Carlo simulations of ligand binding kinetics in an SPR cell subject to laminar flow. We extract the binding and dissociation rates by means of the techniques frequently employed in experimental analysis that are motivated by the mean-field approximation. We find major discrepancies in a wide parameter regime between the thus extracted rates and the known input simulation values. These results underscore the crucial quantitative importance of s...
Outlier detection in near-infrared spectroscopic analysis by using Monte Carlo cross-validation
2008-01-01
An outlier detection method is proposed for near-infrared spectral analysis. The underlying philosophy of the method is that,in random test(Monte Carlo) cross-validation,the probability of outliers presenting in good models with smaller prediction residual error sum of squares(PRESS) or in bad models with larger PRESS should be obviously different from normal samples. The method builds a large number of PLS models by using random test cross-validation at first,then the models are sorted by the PRESS,and at last the outliers are recognized according to the accumulative probability of each sample in the sorted models. For validation of the proposed method,four data sets,including three published data sets and a large data set of tobacco lamina,were investigated. The proposed method was proved to be highly efficient and veracious compared with the conventional leave-one-out(LOO) cross validation method.
Marathon: An Open Source Software Library for the Analysis of Markov-Chain Monte Carlo Algorithms.
Rechner, Steffen; Berger, Annabell
2016-01-01
We present the software library marathon, which is designed to support the analysis of sampling algorithms that are based on the Markov-Chain Monte Carlo principle. The main application of this library is the computation of properties of so-called state graphs, which represent the structure of Markov chains. We demonstrate applications and the usefulness of marathon by investigating the quality of several bounding methods on four well-known Markov chains for sampling perfect matchings and bipartite graphs. In a set of experiments, we compute the total mixing time and several of its bounds for a large number of input instances. We find that the upper bound gained by the famous canonical path method is often several magnitudes larger than the total mixing time and deteriorates with growing input size. In contrast, the spectral bound is found to be a precise approximation of the total mixing time. PMID:26824442
Monte Carlo analysis of doppler reactivity coefficient for UO2 pin cell geometry
Monte Carlo analysis has been performed to investigate the impact of the exact resonance elastic scattering model on the Doppler reactivity coefficient for the UO2 pin cell geometry with the parabolic temperature profile. As a result, the exact scattering model affects the coefficient similarly for both the flat and parabolic temperature profiles; it increases the contribution of uranium-238 resonance capture in the energy region from ∼16 eV to ∼150 eV and does uniformly in the radial direction. Then the following conclusions hold for both the exact and asymptotic resonance scattering models. The Doppler reactivity coefficient is well reproduced with the definition of the effective fuel temperature (equivalent flat temperature) proposed by Grandi et al. In addition, the effective fuel temperature volume-averaged over the entire fuel region negatively overestimates the reference Doppler reactivity coefficient but the calculated one can be significantly improved by dividing the fuel region into a few equi-volumes. (author)
New approach to spectrum analysis. Iterative Monte Carlo simulations and fitting
A novel spectrum analysis code which combines the Monte Carlo simulations with spectrum fitting is introduced. The shapes used in the fitting are obtained from the simulations. The code is developed especially to analyze complex alpha particle energy spectra - such as those obtained from non-processed air filters, swipe samples or isolated particles emitting alpha radiation. In addition to activities of the nuclides present in the sample, the code can provide source characterization. In particular, the code can be used to characterize samples of nuclear material, i.e. those containing fissionable isotopes such as 235U or 239Pu. In the present paper we illustrate the use of the code to identify and quantify alpha-particle emitting isotopes in a depleted U projectile found in Kosovo. (author)
Contrast to Noise Ratio and Contrast Detail Analysis in Mammography:A Monte Carlo Study
Metaxas, V.; Delis, H.; Kalogeropoulou, C.; Zampakis, P.; Panayiotakis, G.
2015-09-01
The mammographic spectrum is one of the major factors affecting image quality in mammography. In this study, a Monte Carlo (MC) simulation model was used to evaluate image quality characteristics of various mammographic spectra. The anode/filter combinations evaluated, were those traditionally used in mammography, for tube voltages between 26 and 30 kVp. The imaging performance was investigated in terms of Contrast to Noise Ratio (CNR) and Contrast Detail (CD) analysis, by involving human observers, utilizing a mathematical CD phantom. Soft spectra provided the best characteristics in terms of both CNR and CD scores, while tube voltage had a limited effect. W-anode spectra filtered with k-edge filters demonstrated an improved performance, that sometimes was better compared to softer x-ray spectra, produced by Mo or Rh anode. Regarding the filter material, k-edge filters showed superior performance compared to Al filters.
Marathon: An Open Source Software Library for the Analysis of Markov-Chain Monte Carlo Algorithms
Rechner, Steffen; Berger, Annabell
2016-01-01
We present the software library marathon, which is designed to support the analysis of sampling algorithms that are based on the Markov-Chain Monte Carlo principle. The main application of this library is the computation of properties of so-called state graphs, which represent the structure of Markov chains. We demonstrate applications and the usefulness of marathon by investigating the quality of several bounding methods on four well-known Markov chains for sampling perfect matchings and bipartite graphs. In a set of experiments, we compute the total mixing time and several of its bounds for a large number of input instances. We find that the upper bound gained by the famous canonical path method is often several magnitudes larger than the total mixing time and deteriorates with growing input size. In contrast, the spectral bound is found to be a precise approximation of the total mixing time. PMID:26824442
Heat-Flux Analysis of Solar Furnace Using the Monte Carlo Ray-Tracing Method
An understanding of the concentrated solar flux is critical for the analysis and design of solar-energy-utilization systems. The current work focuses on the development of an algorithm that uses the Monte Carlo ray-tracing method with excellent flexibility and expandability; this method considers both solar limb darkening and the surface slope error of reflectors, thereby analyzing the solar flux. A comparison of the modeling results with measurements at the solar furnace in Korea Institute of Energy Research (KIER) show good agreement within a measurement uncertainty of 10%. The model evaluates the concentration performance of the KIER solar furnace with a tracking accuracy of 2 mrad and a maximum attainable concentration ratio of 4400 sun. Flux variations according to measurement position and flux distributions depending on acceptance angles provide detailed information for the design of chemical reactors or secondary concentrators
Enrichment effects on CANDU-SEU spent fuel Monte Carlo shielding analysis
Shielding analyses are an essential component of the nuclear safety, the estimations of radiation doses in order to reduce them under specified limitation values being the main task here. According to IAEA data, more than 10 millions packages containing radioactive materials are annually transported world wide. All the problems arisen from the safe radioactive materials transport assurance must be carefully settled. Last decade, both for operating reactors and future reactor projects, a general trend to raise the discharge fuel burnup has been recorded world wide. For CANDU type reactors, the most attractive solution seems to be SEU and RU fuels utilization. The basic tasks accomplished by the shielding calculations in a nuclear safety analysis consist in dose rates calculation, to prevent any risks both for personnel protection and impact on the environment during the spent fuel manipulation, transport and storage. The paper aims to study the effects induced by fuel enrichment variation on CANDU-SEU spent fuel photon dose rates for a Monte Carlo shielding analysis applied to spent fuel transport after a defined cooling period in the NPP pools. The fuel bundles projects considered here have 43 Zircaloy rods, filled with SEU fuel pellets, the fuel having different enrichment in U-235. All the geometrical and material data related on the cask were considered according to the shipping cask type B model. After a photon source profile calculation by using ORIGEN-S code, in order to perform the shielding calculations, Monte Carlo MORSE-SGC code has been used, both codes being included in the ORNL's SCALE 5 system. The photon dose rates to the shipping cask wall and in air, at different distances from the cask, have been estimated. Finally, a photon dose rates comparison for different fuel enrichments has been performed. (author)
On the feasibility of a homogenised multi-group Monte Carlo method in reactor analysis
The use of homogenised multi-group cross sections to speed up Monte Carlo calculation has been studied to some extent, but the method is not widely implemented in modern calculation codes. This paper presents a calculation scheme in which homogenised material parameters are generated using the PSG continuous-energy Monte Carlo reactor physics code and used by MORA, a new full-core Monte Carlo code entirely based on homogenisation. The theory of homogenisation and its implementation in the Monte Carlo method are briefly introduced. The PSG-MORA calculation scheme is put to practice in two fundamentally different test cases: a small sodium-cooled fast reactor (JOYO) and a large PWR core. It is shown that the homogenisation results in a dramatic increase in efficiency. The results are in a reasonably good agreement with reference PSG and MCNP5 calculations, although fission source convergence becomes a problem in the PWR test case. (authors)
Experience with Monte Carlo variance reduction using adjoint solutions in HYPER neutronics analysis
The variance reduction techniques using adjoint solutions are applied to the Monte Carlo calculation of the HYPER(HYbrid Power Extraction Reactor) core neutronics. The applied variance reduction techniques are the geometry splitting and the weight windows. The weight bounds and the cell importance needed for these techniques are generated from an adjoint discrete ordinate calculation by the two-dimensional TWODANT code. The flux distribution variances of the Monte Carlo calculations by these variance reduction techniques are compared with the results of the standard Monte Carlo calculations. It is shown that the variance reduction techniques using adjoint solutions to the HYPER core neutronics result in a decrease in the efficiency of the Monte Carlo calculation
Analysis of some splitting and roulette algorithms in shield calculations by the Monte Carlo method
Different schemes of using the splitting and roulette methods in calculation of radiation transport in nuclear facility shields by the Monte Carlo method are considered. Efficiency of the considered schemes is estimated on the example of test calculations
The effect of load imbalances on the performance of Monte Carlo algorithms in LWR analysis
A model is developed to predict the impact of particle load imbalances on the performance of domain-decomposed Monte Carlo neutron transport algorithms. Expressions for upper bound performance “penalties” are derived in terms of simple machine characteristics, material characterizations and initial particle distributions. The hope is that these relations can be used to evaluate tradeoffs among different memory decomposition strategies in next generation Monte Carlo codes, and perhaps as a metric for triggering particle redistribution in production codes
Study of the quantitative analysis approach of maintenance by the Monte Carlo simulation method
This study is examination of the quantitative valuation by Monte Carlo simulation method of maintenance activities of a nuclear power plant. Therefore, the concept of the quantitative valuation of maintenance that examination was advanced in the Japan Society of Maintenology and International Institute of Universality (IUU) was arranged. Basis examination for quantitative valuation of maintenance was carried out at simple feed water system, by Monte Carlo simulation method. (author)
This analysis is part of the report on ' Implementation of geometry module of 05R code in another Monte Carlo code', chapter 6.0: establishment of future activity related to geometry in Monte Carlo method. The introduction points out some problems in solving complex three-dimensional models which induce the need for developing more efficient geometry modules in Monte Carlo calculations. Second part include formulation of the problem and geometry module. Two fundamental questions to be solved are defined: (1) for a given point, it is necessary to determine material region or boundary where it belongs, and (2) for a given direction, all cross section points with material regions should be determined. Third part deals with possible connection with Monte Carlo calculations for computer simulation of geometry objects. R-function theory enables creation of geometry module base on the same logic (complex regions are constructed by elementary regions sets operations) as well as construction geometry codes. R-functions can efficiently replace functions of three-value logic in all significant models. They are even more appropriate for application since three-value logic is not typical for digital computers which operate in two-value logic. This shows that there is a need for work in this field. It is shown that there is a possibility to develop interactive code for computer modeling of geometry objects in parallel with development of geometry module
A polarized atmospheric radiative transfer model for the computation of radiative transfer inside three-dimensional inhomogeneous mediums is described. This code is based on Monte Carlo methods and takes into account the polarization state of the light. Specificities introduced by such consideration are presented. After validation of the model by comparisons with adding-doubling computations, examples of reflectances simulated from a synthetic inhomogeneous cirrus cloud are analyzed and compared with reflectances obtained with the classical assumption of a plane parallel homogeneous cloud (1D approximation). As polarized reflectance is known to saturate for optical thickness of about 3, one could think that they should be less sensitive to 3D effects than total reflectances. However, at high spatial resolution (80 m), values of polarized reflectances much higher than the ones predicted by the 1D theory can be reached. The study of the reflectances of a step cloud shows that these large values are the results of illumination and shadowing effects similar to those often observed on total reflectances. In addition, we show that for larger spatial resolution (10 km), the so-called plane-parallel bias leads to a non-negligible overestimation of the polarized reflectances of about 7-8%.
It is noted that the analog Monte Carlo method has low calculation efficiency at deep penetration problems such as radiation shielding analysis. In order to increase the calculation efficiency, variance reduction techniques have been introduced and applied for the shielding calculation. To optimize the variance reduction technique, the hybrid Monte Carlo method was introduced. For the determination of the parameters using the hybrid Monte Carlo method, the adjoint flux should be calculated by the deterministic methods. In this study, the collision probability method is applied to calculate adjoint flux. The solution of integration transport equation in the collision probability method is modified to calculate the adjoint flux approximately even for complex and arbitrary geometries. For the calculation, C++ program is developed. By using the calculated adjoint flux, importance parameters of each cell in shielding material are determined and used for variance reduction of transport calculation. In order to evaluate calculation efficiency with the proposed method, shielding calculations are performed with MCNPX 2.7. In this study, a method to calculate the adjoint flux in using the Monte Carlo variance reduction was proposed to improve Monte Carlo calculation efficiency of thick shielding problem. The importance parameter for each cell of shielding material is determined by calculating adjoint flux with the modified collision probability method. In order to calculate adjoint flux with the proposed method, C++ program is developed. The results show that the proposed method can efficiently increase the FOM of transport calculation. It is expected that the proposed method can be utilize for the calculation efficiency in thick shielding calculation
Guo, Hui-Jun; Huang, Wei; Liu, Xi; Gao, Pan; Zhuo, Shi-Yi; Xin, Jun; Yan, Cheng-Feng; Zheng, Yan-Qing; Yang, Jian-Hua; Shi, Er-Wei
2014-09-01
Polytype stability is very important for high quality SiC single crystal growth. However, the growth conditions for the 4H, 6H and 15R polytypes are similar, and the mechanism of polytype stability is not clear. The kinetics aspects, such as surface-step nucleation, are important. The kinetic Monte Carlo method is a common tool to study surface kinetics in crystal growth. However, the present lattice models for kinetic Monte Carlo simulations cannot solve the problem of the competitive growth of two or more lattice structures. In this study, a competitive lattice model was developed for kinetic Monte Carlo simulation of the competition growth of the 4H and 6H polytypes of SiC. The site positions are fixed at the perfect crystal lattice positions without any adjustment of the site positions. Surface steps on seeds and large ratios of diffusion/deposition have positive effects on the 4H polytype stability. The 3D polytype distribution in a physical vapor transport method grown SiC ingot showed that the facet preserved the 4H polytype even if the 6H polytype dominated the growth surface. The theoretical and experimental results of polytype growth in SiC suggest that retaining the step growth mode is an important factor to maintain a stable single 4H polytype during SiC growth.
Hui-Jun Guo
2014-09-01
Full Text Available Polytype stability is very important for high quality SiC single crystal growth. However, the growth conditions for the 4H, 6H and 15R polytypes are similar, and the mechanism of polytype stability is not clear. The kinetics aspects, such as surface-step nucleation, are important. The kinetic Monte Carlo method is a common tool to study surface kinetics in crystal growth. However, the present lattice models for kinetic Monte Carlo simulations cannot solve the problem of the competitive growth of two or more lattice structures. In this study, a competitive lattice model was developed for kinetic Monte Carlo simulation of the competition growth of the 4H and 6H polytypes of SiC. The site positions are fixed at the perfect crystal lattice positions without any adjustment of the site positions. Surface steps on seeds and large ratios of diffusion/deposition have positive effects on the 4H polytype stability. The 3D polytype distribution in a physical vapor transport method grown SiC ingot showed that the facet preserved the 4H polytype even if the 6H polytype dominated the growth surface. The theoretical and experimental results of polytype growth in SiC suggest that retaining the step growth mode is an important factor to maintain a stable single 4H polytype during SiC growth.
Derivation of landslide-triggering thresholds by Monte Carlo simulation and ROC analysis
Peres, David Johnny; Cancelliere, Antonino
2015-04-01
Rainfall thresholds of landslide-triggering are useful in early warning systems to be implemented in prone areas. Direct statistical analysis of historical records of rainfall and landslide data presents different shortcomings typically due to incompleteness of landslide historical archives, imprecise knowledge of the triggering instants, unavailability of a rain gauge located near the landslides, etc. In this work, a Monte Carlo approach to derive and evaluate landslide triggering thresholds is presented. Such an approach contributes to overcome some of the above mentioned shortcomings of direct empirical analysis of observed data. The proposed Monte Carlo framework consists in the combination of a rainfall stochastic model with hydrological and slope-stability model. Specifically, 1000-years long hourly synthetic rainfall and related slope stability factor of safety data are generated by coupling the Neyman-Scott rectangular pulses model with the TRIGRS unsaturated model (Baum et al., 2008) and a linear-reservoir water table recession model. Triggering and non-triggering rainfall events are then distinguished and analyzed to derive stochastic-input physically based thresholds that optimize the trade-off between correct and wrong predictions. For this purpose, receiver operating characteristic (ROC) indices are used. An application of the method to the highly landslide-prone area of the Peloritani mountains in north-eastern Sicily (Italy) is carried out. A threshold for the area is derived and successfully validated by comparison with thresholds proposed by other researchers. Moreover, the uncertainty in threshold derivation due to variability of rainfall intensity within events and to antecedent rainfall is investigated. Results indicate that variability of intensity during rainfall events influences significantly rainfall intensity and duration associated with landslide triggering. A representation of rainfall as constant-intensity hyetographs globally leads to
Improving Markov Chain Monte Carlo algorithms in LISA Pathfinder Data Analysis
The LISA Pathfinder mission (LPF) aims to test key technologies for the future LISA mission. The LISA Technology Package (LTP) on-board LPF will consist of an exhaustive suite of experiments and its outcome will be crucial for the future detection of gravitational waves. In order to achieve maximum sensitivity, we need to have an understanding of every instrument on-board and parametrize the properties of the underlying noise models. The Data Analysis team has developed algorithms for parameter estimation of the system. A very promising one implemented for LISA Pathfinder data analysis is the Markov Chain Monte Carlo. A series of experiments are going to take place during flight operations and each experiment is going to provide us with essential information for the next in the sequence. Therefore, it is a priority to optimize and improve our tools available for data analysis during the mission. Using a Bayesian framework analysis allows us to apply prior knowledge for each experiment, which means that we can efficiently use our prior estimates for the parameters, making the method more accurate and significantly faster. This, together with other algorithm improvements, will lead us to our main goal, which is no other than creating a robust and reliable tool for parameter estimation during the LPF mission.
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
Monte Carlo transport calculations and analysis for reactor pressure vessel neutron fluence
The application of Monte Carlo methods for reactor pressure vessel (RPV) neutron fluence calculations is examined. As many commercial nuclear light water reactors approach the end of their design lifetime, it is of great consequence that reactor operators and regulators be able to characterize the structural integrity of the RPV accurately for financial reasons, as well as safety reasons, due to the possibility of plant life extensions. The Monte Carlo method, which offers explicit three-dimensional geometric representation and continuous energy and angular simulation, is well suited for this task. A model of the Three Mile Island unit 1 reactor is presented for determination of RPV fluence; Monte Carlo (MCNP) and deterministic (DORT) results are compared for this application; and numerous issues related to performing these calculations are examined. Synthesized three-dimensional deterministic models are observed to produce results that are comparable to those of Monte Carlo methods, provided the two methods utilize the same cross-section libraries. Continuous energy Monte Carlo methods are shown to predict more (15 to 20%) high-energy neutrons in the RPV than deterministic methods
ZHANG Jun; GUO Fan
2015-01-01
Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system’s dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error(DTE) fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system’s dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.
In order to maintain the safety of the reactor core, the minimum DNBR (Departure from Nucleate Boiling Ratio) in the PWR (Pressurized-Water Reactor) core remains higher than the DNBR limit during Condition I and II events. Therefore, it is important to adequately evaluate the thermal performance of the PWR core. To realistically evaluate the relationship among the uncertainties and reduce the conservatism resulting from the unknown phenomena, the Monte Carlo method is being used in many areas requiring the statistical approach. Especially, the Monte Carlo method is drawing attention as the method for the evaluation of the thermal performance of the PWR core. For the best estimate evaluation of the uncertainties in the PWR core, KEPCO Nuclear Fuel (hereinafter KEPCO NF) has been developing the thermal design analysis based on the Monte Carlo method. For the Monte Carlo thermal design analysis, various studies are conducted as follows. To generate the Gaussian random numbers, Gaussian random number generators are investigated. In this paper, Box-Muller, Polar, GRAND, and Ziggurat method are briefly reviewed. The random numbers are generated on the basis of the nominal value and uncertainty of the parameter. If the normal distribution is acceptable at 5% significance level through the normality tests, the random numbers are used for the Monte Carlo thermal design analysis. Using the subchannel code THALES (Thermal Hydraulic AnaLyzer for Enhanced Simulation of core) developed by KEPCO NF, the subchannel analyses are carried out considering the core operating parameters randomized, and then DNBR distribution is derived. Finally, if the DNBR distribution is statistically combined with the uncertainties of the other parameters, the DNBRT distribution can be obtained. From the DNBRT distribution, the DNBR limit is determined to avoid DNB (Departure from Nucleate Boiling) at a 95% probability at a 95% confidence level. Through the example calculation, it is verified that
Monte Carlo (MC) power method based on the fixed number of fission sites at the beginning of each cycle is known to cause biases in the variances of the k-eigenvalue (keff) and the fission reaction rate estimates. Because of the biases, the apparent variances of keff and the fission reaction rate estimates from a single MC run tend to be smaller or larger than the real variances of the corresponding quantities, depending on the degree of the inter-generational correlation of the sample. We demonstrate this through a numerical experiment involving 100 independent MC runs for the neutronics analysis of a 17 x 17 fuel assembly of a pressurized water reactor (PWR). We also demonstrate through the numerical experiment that Gelbard and Prael's batch method and Ueki et al's covariance estimation method enable one to estimate the approximate real variances of keff and the fission reaction rate estimates from a single MC run. We then show that the use of the approximate real variances from the two-bias predicting methods instead of the apparent variances provides an efficient MC power iteration scheme that is required in the MC neutronics analysis of a real system to determine the pin power distribution consistent with the thermal hydraulic (TH) conditions of individual pins of the system. (authors)
Use of Monte Carlo Bootstrap Method in the Analysis of Sample Sufficiency for Radioecological Data
There are operational difficulties in obtaining samples for radioecological studies. Population data may no longer be available during the study and obtaining new samples may not be possible. These problems do the researcher sometimes work with a small number of data. Therefore, it is difficult to know whether the number of samples will be sufficient to estimate the desired parameter. Hence, it is critical do the analysis of sample sufficiency. It is not interesting uses the classical methods of statistic to analyze sample sufficiency in Radioecology, because naturally occurring radionuclides have a random distribution in soil, usually arise outliers and gaps with missing values. The present work was developed aiming to apply the Monte Carlo Bootstrap method in the analysis of sample sufficiency with quantitative estimation of a single variable such as specific activity of a natural radioisotope present in plants. The pseudo population was a small sample with 14 values of specific activity of 226Ra in forage palm (Opuntia spp.). Using the R software was performed a computational procedure to calculate the number of the sample values. The re sampling process with replacement took the 14 values of original sample and produced 10,000 bootstrap samples for each round. Then was calculated the estimated average θ for samples with 2, 5, 8, 11 and 14 values randomly selected. The results showed that if the researcher work with only 11 sample values, the average parameter will be within a confidence interval with 90% probability . (Author)
Criticality qualification of a new Monte Carlo code for reactor core analysis
In order to accurately simulate Accelerator Driven Systems (ADS), the utilization of at least two computational tools is necessary (the thermal-hydraulic problem is not considered in the frame of this work), namely: (a) A High Energy Physics (HEP) code system dealing with the 'Accelerator part' of the installation, i.e. the computation of the spectrum, intensity and spatial distribution of the neutrons source created by (p, n) reactions of a proton beam on a target and (b) a neutronics code system, handling the 'Reactor part' of the installation, i.e. criticality calculations, neutron transport, fuel burn-up and fission products evolution. In the present work, a single computational tool, aiming to analyze an ADS in its integrity and also able to perform core analysis for a conventional fission reactor, is proposed. The code is based on the well qualified HEP code GEANT (version 3), transformed to perform criticality calculations. The performance of the code is tested against two qualified neutronics code systems, the diffusion/transport SCALE-CITATION code system and the Monte Carlo TRIPOLI code, in the case of a research reactor core analysis. A satisfactory agreement was exhibited by the three codes.
Monte Carlo shielding comparative analysis applied to TRIGA HEU and LEU spent fuel transport
The paper is a comparative study of LEU (low uranium enrichment) and HEU (highly enriched uranium) fuel utilization effects for the shielding analysis during spent fuel transport. A comparison against the measured data for HEU spent fuel, available from the last stage of spent fuel repatriation fulfilled in the summer of 2008, is also presented. All geometrical and material data for the shipping cask were considered according to NAC-LWT Cask approved model. The shielding analysis estimates radiation doses to shipping cask wall surface, and in air at 1 m and 2 m, respectively, from the cask by means of 3-dimensional Monte Carlo MORSE-SGC code. Before loading into the shipping cask TRIGA spent fuel source terms and spent fuel parameters have been obtained by means of ORIGEN-S code. Both codes are included in ORNL's SCALE 5 programs package. 60Co radioactivity is important for HEU spent fuel; actinides contribution to total fuel radioactivity is low. For LEU spent fuel 60Co radioactivity is insignificant; actinides contribution to total fuel radioactivity is high. Dose rates for both HEU and LEU fuel contents are below regulatory limits, LEU spent fuel photon dose rates being greater than the HEU ones. The comparison between HEU spent fuel theoretical and measured dose rates in selected measuring points shows a good agreement, the calculated values being greater than the measured ones both to cask wall surface (about 34% relative difference) and in air at 1 m distance from the cask surface (about 15% relative difference). (authors)
Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics
Nuclear forensic science has become increasingly important for global nuclear security, and enhancing the timeliness of forensic analysis has been established as an important objective in the field. New, faster techniques must be developed to meet this objective. Current approaches for the analysis of minor actinides, fission products, and fuel-specific materials require time-consuming chemical separation coupled with measurement through either nuclear counting or mass spectrometry. These very sensitive measurement techniques can be hindered by impurities or incomplete separation in even the most painstaking chemical separations. High-temperature gas-phase separation or thermochromatography has been used in the past for the rapid separations in the study of newly created elements and as a basis for chemical classification of that element. This work examines the potential for rapid separation of gaseous species to be applied in nuclear forensic investigations. Monte Carlo modeling has been used to evaluate the potential utility of the thermochromatographic separation method, albeit this assessment is necessarily limited due to the lack of available experimental data for validation.
Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics
Nuclear forensic science has become increasingly important for global nuclear security, and enhancing the timeliness of forensic analysis has been established as an important objective in the field. New, faster techniques must be developed to meet this objective. Current approaches for the analysis of minor actinides, fission products, and fuel-specific materials require time-consuming chemical separation coupled with measurement through either nuclear counting or mass spectrometry. These very sensitive measurement techniques can be hindered by impurities or incomplete separation in even the most painstaking chemical separations. High-temperature gas-phase separation or thermochromatography has been used in the past for the rapid separations in the study of newly created elements and as a basis for chemical classification of that element. This work examines the potential for rapid separation of gaseous species to be applied in nuclear forensic investigations. Monte Carlo modeling has been used to evaluate the potential utility of the thermochromatographic separation method, albeit this assessment is necessarily limited due to the lack of available experimental data for validation. (author)
Criticality qualification of a new Monte Carlo code for reactor core analysis
Catsaros, N. [Institute of Nuclear Technology - Radiation Protection, NCSR ' DEMOKRITOS' , P.O. Box 60228, 15310 Aghia Paraskevi (Greece); Gaveau, B. [MAPS, Universite Paris VI, 4 Place Jussieu, 75005 Paris (France); Jaekel, M. [Laboratoire de Physique Theorique, Ecole Normale Superieure, 24 rue Lhomond, 75231 Paris (France); Maillard, J. [MAPS, Universite Paris VI, 4 Place Jussieu, 75005 Paris (France); CNRS-IDRIS, Bt 506, BP167, 91403 Orsay (France); CNRS-IN2P3, 3 rue Michel Ange, 75794 Paris (France); Maurel, G. [Faculte de Medecine, Universite Paris VI, 27 rue de Chaligny, 75012 Paris (France); MAPS, Universite Paris VI, 4 Place Jussieu, 75005 Paris (France); Savva, P., E-mail: savvapan@ipta.demokritos.g [Institute of Nuclear Technology - Radiation Protection, NCSR ' DEMOKRITOS' , P.O. Box 60228, 15310 Aghia Paraskevi (Greece); Silva, J. [MAPS, Universite Paris VI, 4 Place Jussieu, 75005 Paris (France); Varvayanni, M.; Zisis, Th. [Institute of Nuclear Technology - Radiation Protection, NCSR ' DEMOKRITOS' , P.O. Box 60228, 15310 Aghia Paraskevi (Greece)
2009-11-15
In order to accurately simulate Accelerator Driven Systems (ADS), the utilization of at least two computational tools is necessary (the thermal-hydraulic problem is not considered in the frame of this work), namely: (a) A High Energy Physics (HEP) code system dealing with the 'Accelerator part' of the installation, i.e. the computation of the spectrum, intensity and spatial distribution of the neutrons source created by (p, n) reactions of a proton beam on a target and (b) a neutronics code system, handling the 'Reactor part' of the installation, i.e. criticality calculations, neutron transport, fuel burn-up and fission products evolution. In the present work, a single computational tool, aiming to analyze an ADS in its integrity and also able to perform core analysis for a conventional fission reactor, is proposed. The code is based on the well qualified HEP code GEANT (version 3), transformed to perform criticality calculations. The performance of the code is tested against two qualified neutronics code systems, the diffusion/transport SCALE-CITATION code system and the Monte Carlo TRIPOLI code, in the case of a research reactor core analysis. A satisfactory agreement was exhibited by the three codes.
MULTI-KENO: a Monte Carlo code for criticality safety analysis
Modifying the Monte Carlo code KENO-IV, the MULTI-KENO code was developed for criticality safety analysis. The following functions were added to the code; (1) to divide a system into many sub-systems named super boxes where the size of box types in each super box can be selected independently, (2) to output graphical view of a system for examining geometrical input data, (3) to solve fixed source problems, (4) to permit intersection of core boundaries and inner geometries, (5) to output ANISN type neutron balance table. With the above function (1), many cases which had to be applied a general geometry option of KENO-IV, became to be treated as box type geometry. In such a case, input data became simpler and required computer time became shorter than those of KENO-IV. This code is now available for the FACOM-M200 computer and the CDC 6600 computer. This report is a computer code manual for MULTI-KENO. (author)
Markov chain Monte Carlo analysis to constrain dark matter properties with directional detection
Directional detection is a promising dark matter search strategy. Indeed, weakly interacting massive particle (WIMP)-induced recoils would present a direction dependence toward the Cygnus constellation, while background-induced recoils exhibit an isotropic distribution in the Galactic rest frame. Taking advantage of these characteristic features, and even in the presence of a sizeable background, it has recently been shown that data from forthcoming directional detectors could lead either to a competitive exclusion or to a conclusive discovery, depending on the value of the WIMP-nucleon cross section. However, it is possible to further exploit these upcoming data by using the strong dependence of the WIMP signal with: the WIMP mass and the local WIMP velocity distribution. Using a Markov chain Monte Carlo analysis of recoil events, we show for the first time the possibility to constrain the unknown WIMP parameters, both from particle physics (mass and cross section) and Galactic halo (velocity dispersion along the three axis), leading to an identification of non-baryonic dark matter.
In the design of the incore thermionic reactor system developed under the Advanced Thermionic Initiative (ATI), the fuel is highly enriched uranium dioxide and the moderating medium is zirconium hydride. The traditional burnup and fuel depletion analysis codes have been found to be inadequate for these calculations, largely because of the material and geometry modeled and because the neutron spectra assumed for the codes such as LEOPARD and ORIGEN do not even closely fit that for a small, thermal reactor using ZrH as moderator. More sophisticated codes such as the transport lattice type code WIMS often lack some materials, such as ZrH. Thus a new method which could accurately calculate the neutron spectrum and the appropriate reaction rates within the fuel element is needed. The method developed utilizes and interconnects the accuracy of the Monte Carlo Neutron/Photon (MCNP) method to calculate reaction rates for the important isotopes, and a time dependent depletion routine to calculate the temporal effects on isotope concentrations. This effort required the modification of MCNP itself to perform the additional task of accomplishing burnup calculations. The modified version called, MCNPBURN, evolved to be a general dual purpose code which can be used for standard calculations as well as for burn-up
Monte Carlo analysis of the MEGA microlensing events towards M31
Ingrosso, G; De Paolis, F; Jetzer, P; Nucita, A A; Strafella, F; Jetzer, Ph.
2005-01-01
We perform an analytical study and a Monte Carlo (MC) analysis of the main features for microlensing events in pixel lensing observations towards M31. Our main aim is to investigate the lens nature and location of the 14 candidate events found by the MEGA collaboration. Assuming a reference model for the mass distribution in M31 and the standard model for our galaxy, we estimate the MACHO-to-self lensing probability and the event time duration towards M31. Reproducing the MEGA observing conditions, as a result we get the MC event number density distribution as a function of the event full-width half-maximum duration $t_{1/2}$ and the magnitude at maximum $R_{\\mathrm {max}}$. For a MACHO mass of $0.5 M_{\\odot}$ we find typical values of $t_{1/2} \\simeq 20$ day and $R_{\\mathrm {max}} \\simeq 22$, for both MACHO-lensing and self-lensing events occurring beyond about 10 arcminutes from the M31 center. A comparison of the observed features ($t_{1/2}$ and $R_{\\mathrm {max}}$) with our MC results shows that for a MAC...
The benchmark analysis of reactivity experiments in the TRIGA-II core at the Musashi Institute of Technology Research Reactor (Musashi reactor; 100 kW) was performed by a three-dimensional continuous-energy Monte Carlo code MCNP4A. The reactivity worth and integral reactivity curves of the control rods as well as the reactivity worth distributions of fuel and graphite elements were used in the validation process of the physical model and neutron cross section data from the ENDF/B-V evaluation. The calculated values of integral reactivity curves of the control rods were in agreement with the experimental data obtained by the period method. The integral worth measured by the rod drop method was also consistent with the calculation. The calculated values of the fuel and the graphite element worth distributions were consistent with the measured ones within the statistical error estimates. These results showed that the exact core configuration including the control rod positions to reproduce the fission source distribution in the experiment must be introduced into the calculation core for obtaining the precise solution. It can be concluded that our simulation model of the TRIGA-II core is precise enough to reproduce the control rod worth, fuel and graphite elements reactivity worth distributions. (author)
The use of Monte Carlo analysis for exposure assessment of an estuarine food web
Iannuzzi, T.J.; Shear, N.M.; Harrington, N.W.; Henning, M.H. [McLaren/Hart Environmental Engineering Corp., Portland, ME (United States). ChemRisk Div.
1995-12-31
Despite apparent agreement within the scientific community that probabilistic methods of analysis offer substantially more informative exposure predictions than those offered by the traditional point estimate approach, few risk assessments conducted or approved by state and federal regulatory agencies have used probabilistic methods. Among the likely deterrents to application of probabilistic methods to ecological risk assessment is the absence of ``standard`` data distributions that are considered applicable to most conditions for a given ecological receptor. Indeed, point estimates of ecological exposure factor values for a limited number of wildlife receptors have only recently been published. The Monte Carlo method of probabilistic modeling has received increasing support as a promising technique for characterizing uncertainty and variation in estimates of exposure to environmental contaminants. An evaluation of literature on the behavior, physiology, and ecology of estuarine organisms was conducted in order to identify those variables that most strongly influence uptake of xenobiotic chemicals from sediments, water and food sources. The ranges, central tendencies, and distributions of several key parameter values for polychaetes (Nereis sp.), mummichog (Fundulus heteroclitus), blue crab (Callinectes sapidus), and striped bass (Morone saxatilis) in east coast estuaries were identified. Understanding the variation in such factors, which include feeding rate, growth rate, feeding range, excretion rate, respiration rate, body weight, lipid content, food assimilation efficiency, and chemical assimilation efficiency, is critical to the understanding the mechanisms that control the uptake of xenobiotic chemicals in aquatic organisms, and to the ability to estimate bioaccumulation from chemical exposures in the aquatic environment.
Lim, J. T.; Gold, H. J.; Wilkerson, G. G.; Raper, C. D. Jr; Raper CD, J. r. (Principal Investigator)
1989-01-01
We describe the application of a strategy for conducting a sensitivity analysis for a complex dynamic model. The procedure involves preliminary screening of parameter sensitivities by numerical estimation of linear sensitivity coefficients, followed by generation of a response surface based on Monte Carlo simulation. Application is to a physiological model of the vegetative growth of soybean plants. The analysis provides insights as to the relative importance of certain physiological processes in controlling plant growth. Advantages and disadvantages of the strategy are discussed.
Zakhnini, Abdelhamid; Kulenkampff, Johannes; Sauerzapf, Sophie; Pietrzyk, Uwe; Lippmann-Pipke, Johanna
2013-08-01
Understanding conservative fluid flow and reactive tracer transport in soils and rock formations requires quantitative transport visualization methods in 3D+t. After a decade of research and development we established the GeoPET as a non-destructive method with unrivalled sensitivity and selectivity, with due spatial and temporal resolution by applying Positron Emission Tomography (PET), a nuclear medicine imaging method, to dense rock material. Requirements for reaching the physical limit of image resolution of nearly 1 mm are (a) a high-resolution PET-camera, like our ClearPET scanner (Raytest), and (b) appropriate correction methods for scatter and attenuation of 511 keV—photons in the dense geological material. The latter are by far more significant in dense geological material than in human and small animal body tissue (water). Here we present data from Monte Carlo simulations (MCS) reflecting selected GeoPET experiments. The MCS consider all involved nuclear physical processes of the measurement with the ClearPET-system and allow us to quantify the sensitivity of the method and the scatter fractions in geological media as function of material (quartz, Opalinus clay and anhydrite compared to water), PET isotope (18F, 58Co and 124I), and geometric system parameters. The synthetic data sets obtained by MCS are the basis for detailed performance assessment studies allowing for image quality improvements. A scatter correction method is applied exemplarily by subtracting projections of simulated scattered coincidences from experimental data sets prior to image reconstruction with an iterative reconstruction process.
Hirano, Yoshiyuki; Koshino, Kazuhiro; Watabe, Hiroshi; Fukushima, Kazuhito; Iida, Hidehiro
2012-11-01
In clinical cardiac positron emission tomography using 15O-water, significant tracer accumulation is observed not only in the heart but also in the liver and lung, which are partially outside the field-of-view. In this work, we investigated the effects of scatter on quantitative myocardium blood flow (MBF) and perfusable tissue fraction (PTF) by a precise Monte Carlo simulation (Geant4) and a numerical human model. We assigned activities to the heart, liver, and lung of the human model with varying ratios of organ activities according to an experimental time activity curve and created dynamic sinograms. The sinogram data were reconstructed by filtered backprojection. By comparing a scatter-corrected image (SC) with a true image (TRUE), we evaluated the accuracy of the scatter correction. TRUE was reconstructed using a scatter-eliminated sinogram, which can be obtained only in simulations. A scatter-uncorrected image (W/O SC) and an attenuation-uncorrected image (W/O AC) were also constructed. Finally, we calculated MBF and PTF with a single tissue-compartment model for four types of images. As a result, scatter was corrected accurately, and MBFs derived from all types of images were consistent with the MBF obtained from TRUE. Meanwhile, the PTF of only the SC was in agreement with the PTF of TRUE. From the simulation results, we concluded that quantitative MBF is less affected by scatter and absorption in 3D-PET using 15O-water. However, scatter correction is essential for accurate PTF.
Purpose: To design a new compact S-band linac waveguide capable of producing a 10 MV x-ray beam, while maintaining the length (27.5 cm) of current 6 MV waveguides. This will allow higher x-ray energies to be used in our linac-MRI systems with the same footprint. Methods: Finite element software COMSOL Multiphysics was used to design an accelerator cavity matching one published in an experiment breakdown study, to ensure that our modeled cavities do not exceed the threshold electric fields published. This cavity was used as the basis for designing an accelerator waveguide, where each cavity of the full waveguide was tuned to resonate at 2.997 GHz by adjusting the cavity diameter. The RF field solution within the waveguide was calculated, and together with an electron-gun phase space generated using Opera3D/SCALA, were input into electron tracking software PARMELA to compute the electron phase space striking the x-ray target. This target phase space was then used in BEAM Monte Carlo simulations to generate percent depth doses curves for this new linac, which were then used to re-optimize the waveguide geometry. Results: The shunt impedance, Q-factor, and peak-to-mean electric field ratio were matched to those published for the breakdown study to within 0.1% error. After tuning the full waveguide, the peak surface fields are calculated to be 207 MV/m, 13% below the breakdown threshold, and a d-max depth of 2.42 cm, a D10/20 value of 1.59, compared to 2.45 cm and 1.59, respectively, for the simulated Varian 10 MV linac and brehmsstrahlung production efficiency 20% lower than a simulated Varian 10 MV linac. Conclusion: This work demonstrates the design of a functional 27.5 cm waveguide producing 10 MV photons with characteristics similar to a Varian 10 MV linac
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
Analysis of the distribution of X-ray characteristic production using the Monte Carlo methods
The Monte Carlo method has been applied for the simulation of electron trajectories in a bulk sample, and therefore for the distribution of signals produced in an electron microprobe. Results for the function φ(ρz) are compared with experimental data. Some conclusions are drawn with respect to the parameters involved in the gaussian model. (Author)
Dunn, William L
2012-01-01
Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble
Kim, Moo-Sub; Jung, Joo-Young; Suh, Tae Suk [College of Medicine, Catholic University of Korea, Seoul (Korea, Republic of)
2015-05-15
The purpose of this research was the statistical analysis for discrimination of the prompt gamma ray peak induced by the 14.1 MeV neutron particles from spectra using Monte Carlo simulation. For the simulation, the information of the eighteen detector materials was used to simulate spectra by the neutron capture reaction. To the best of our knowledge, the results in this study are the first reported data regarding the peak discrimination of high energy prompt gamma ray using the many cases (the eighteen detector materials and the nine prompt gamma ray peaks). The reliable data based on the Monte Carlo method and statistical method with the identical conditions was deducted. Our results are important data in the PGAA study for the peak detection within actual experiments.
The purpose of this research was the statistical analysis for discrimination of the prompt gamma ray peak induced by the 14.1 MeV neutron particles from spectra using Monte Carlo simulation. For the simulation, the information of the eighteen detector materials was used to simulate spectra by the neutron capture reaction. To the best of our knowledge, the results in this study are the first reported data regarding the peak discrimination of high energy prompt gamma ray using the many cases (the eighteen detector materials and the nine prompt gamma ray peaks). The reliable data based on the Monte Carlo method and statistical method with the identical conditions was deducted. Our results are important data in the PGAA study for the peak detection within actual experiments
The Center for Engineering Applications of Radioisotopes (CEAR) has been working for about ten years on the Monte Carlo - Library Least-Squares (MCLLS) approach for treating the nonlinear inverse analysis problem for PGNAA bulk analysis. This approach consists essentially of using Monte Carlo simulation to generate the libraries of all the elements to be analyzed plus any other required libraries. These libraries are then used in the linear Library Least-Squares (LLS) approach with unknown sample spectra to analyze for all elements in the sample. The other libraries include all sources of background which includes: (1) gamma-rays emitted by the neutron source, (2) prompt gamma-rays produced in the analyzer construction materials, (3) natural gamma-rays from K-40 and the uranium and thorium decay chains, and (4) prompt and decay gamma-rays produced in the NaI detector by neutron activation. A number of unforeseen problems have arisen in pursuing this approach including: (1) the neutron activation of the most common detector (NaI) used in bulk analysis PGNAA systems, (2) the nonlinearity of this detector, and (3) difficulties in obtaining detector response functions for this (and other) detectors. These problems have been addressed by CEAR recently and have either been solved or are almost solved at the present time. Development of Monte Carlo simulation for all of the libraries has been finished except the prompt gamma-ray library from the activation of the NaI detector. Treatment for the coincidence schemes for Na and particularly I must be first determined to complete the Monte Carlo simulation of this last library. (author)
The Albedo method applied to criticality calculations to nuclear reactors is characterized by following the neutron currents, allowing to make detailed analyses of the physics phenomena about interactions of the neutrons with the core-reflector set, by the determination of the probabilities of reflection, absorption, and transmission. Then, allowing to make detailed appreciations of the variation of the effective neutron multiplication factor, keff. In the present work, motivated for excellent results presented in dissertations applied to thermal reactors and shieldings, was described the methodology to Albedo method for the analysis criticality of thermal reactors by using two energy groups admitting variable core coefficients to each re-entrant current. By using the Monte Carlo KENO IV code was analyzed relation between the total fraction of neutrons absorbed in the core reactor and the fraction of neutrons that never have stayed into the reflector but were absorbed into the core. As parameters of comparison and analysis of the results obtained by the Albedo method were used one dimensional deterministic code ANISN (ANIsotropic SN transport code) and Diffusion method. The keff results determined by the Albedo method, to the type of analyzed reactor, showed excellent agreement. Thus were obtained relative errors of keff values smaller than 0,78% between the Albedo method and code ANISN. In relation to the Diffusion method were obtained errors smaller than 0,35%, showing the effectiveness of the Albedo method applied to criticality analysis. The easiness of application, simplicity and clarity of the Albedo method constitute a valuable instrument to neutronic calculations applied to nonmultiplying and multiplying media. (author)
Analysis of uncertainty quantification method by comparing Monte-Carlo method and Wilk's formula
An analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks' formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determined based on previous PIRT results and documentation during the BEMUSE project. Calulations were conducted on 3,500 cases within a 2-week CPU time on a 14-PC cluster system. The Monte-Carlo exercise shows that the 95% upper limit PCT value can be obtained well, with a 95% confidence level using the Wilks' formula, although we have to endure a 5% risk of PCT under-prediction. The results also show that the statistical fluctuation of the limit value using Wilks' first-order is as large as the uncertainty value itself. It is therefore desirable to increase the order of the Wilks' formula to be higher than the second-order to estimate the reliable safety margin of the design features. It is also shown that, with its ever increasing computational capability, the Monte-Carlo method is accessible for a nuclear power plant safety analysis within a realistic time frame.
Lai, Bo-Lun; Sheu, Rong-Jiun; Lin, Uei-Tyng
2015-05-01
Monte Carlo simulations are generally considered the most accurate method for complex accelerator shielding analysis. Simplified models based on point-source line-of-sight approximation are often preferable in practice because they are intuitive and easy to use. A set of shielding data, including source terms and attenuation lengths for several common targets (iron, graphite, tissue, and copper) and shielding materials (concrete, iron, and lead) were generated by performing Monte Carlo simulations for 100-300 MeV protons. Possible applications and a proper use of the data set were demonstrated through a practical case study, in which shielding analysis on a typical proton treatment room was conducted. A thorough and consistent comparison between the predictions of our point-source line-of-sight model and those obtained by Monte Carlo simulations for a 360° dose distribution around the room perimeter showed that the data set can yield fairly accurate or conservative estimates for the transmitted doses, except for those near the maze exit. In addition, this study demonstrated that appropriate coupling between the generated source term and empirical formulae for radiation streaming can be used to predict a reasonable dose distribution along the maze. This case study proved the effectiveness and advantage of applying the data set to a quick shielding design and dose evaluation for proton therapy accelerators. PMID:25811254
Performance Analysis of Korean Liquid metal type TBM based on Monte Carlo code
The objective of this project is to analyze a nuclear performance of the Korean HCML(Helium Cooled Molten Lithium) TBM(Test Blanket Module) which will be installed in ITER(International Thermonuclear Experimental Reactor). This project is intended to analyze a neutronic design and nuclear performances of the Korean HCML ITER TBM through the transport calculation of MCCARD. In detail, we will conduct numerical experiments for analyzing the neutronic design of the Korean HCML TBM and the DEMO fusion blanket, and improving the nuclear performances. The results of the numerical experiments performed in this project will be utilized further for a design optimization of the Korean HCML TBM. In this project, Monte Carlo transport calculations for evaluating TBR (Tritium Breeding Ratio) and EMF (Energy Multiplication factor) were conducted to analyze a nuclear performance of the Korean HCML TBM. The activation characteristics and shielding performances for the Korean HCML TBM were analyzed using ORIGEN and MCCARD. We proposed the neutronic methodologies for analyzing the nuclear characteristics of the fusion blanket, which was applied to the blanket analysis of a DEMO fusion reactor. In the results, the TBR of the Korean HCML ITER TBM is 0.1352 and the EMF is 1.362. Taking into account a limitation for the Li amount in ITER TBM, it is expected that tritium self-sufficiency condition can be satisfied through a change of the Li quantity and enrichment. In the results of activation and shielding analysis, the activity drops to 1.5% of the initial value and the decay heat drops to 0.02% of the initial amount after 10 years from plasma shutdown
Uncertainty analysis in the simulation of an HPGe detector using the Monte Carlo Code MCNP5
A gamma spectrometer including an HPGe detector is commonly used for environmental radioactivity measurements. Many works have been focused on the simulation of the HPGe detector using Monte Carlo codes such as MCNP5. However, the simulation of this kind of detectors presents important difficulties due to the lack of information from manufacturers and due to loss of intrinsic properties in aging detectors. Some parameters such as the active volume or the Ge dead layer thickness are many times unknown and are estimated during simulations. In this work, a detailed model of an HPGe detector and a petri dish containing a certified gamma source has been done. The certified gamma source contains nuclides to cover the energy range between 50 and 1800 keV. As a result of the simulation, the Pulse Height Distribution (PHD) is obtained and the efficiency curve can be calculated from net peak areas and taking into account the certified activity of the source. In order to avoid errors due to the net area calculation, the simulated PHD is treated using the GammaVision software. On the other hand, it is proposed to use the Noether-Wilks formula to do an uncertainty analysis of model with the main goal of determining the efficiency curve of this detector and its associated uncertainty. The uncertainty analysis has been focused on dead layer thickness at different positions of the crystal. Results confirm the important role of the dead layer thickness in the low energy range of the efficiency curve. In the high energy range (from 300 to 1800 keV) the main contribution to the absolute uncertainty is due to variations in the active volume. (author)
Monte Carlo shielding comparative analysis applied to TRIGA HEU and LEU spent fuel transport
Margeanu, C. A.; Iorgulis, C. [Reactor Physics, Nuclear Fuel Performances and Nuclear Safety Department, Institute for Nuclear Research Pitesti, P.O Box 78, Pitesti (Romania); Margeanu, S. [Radiation Protection Department, Institute for Nuclear Research Pitesti, Pitesti (Romania); Barbos, D. [TRIGA Research Reactor Department, Institute for Nuclear Research Pitesti, Pitesti (Romania)
2009-07-01
The paper is a comparative study of LEU (low uranium enrichment) and HEU (highly enriched uranium) fuel utilization effects for the shielding analysis during spent fuel transport. A comparison against the measured data for HEU spent fuel, available from the last stage of spent fuel repatriation fulfilled in the summer of 2008, is also presented. All geometrical and material data for the shipping cask were considered according to NAC-LWT Cask approved model. The shielding analysis estimates radiation doses to shipping cask wall surface, and in air at 1 m and 2 m, respectively, from the cask by means of 3-dimensional Monte Carlo MORSE-SGC code. Before loading into the shipping cask TRIGA spent fuel source terms and spent fuel parameters have been obtained by means of ORIGEN-S code. Both codes are included in ORNL's SCALE 5 programs package. {sup 60}Co radioactivity is important for HEU spent fuel; actinides contribution to total fuel radioactivity is low. For LEU spent fuel {sup 60}Co radioactivity is insignificant; actinides contribution to total fuel radioactivity is high. Dose rates for both HEU and LEU fuel contents are below regulatory limits, LEU spent fuel photon dose rates being greater than the HEU ones. The comparison between HEU spent fuel theoretical and measured dose rates in selected measuring points shows a good agreement, the calculated values being greater than the measured ones both to cask wall surface (about 34% relative difference) and in air at 1 m distance from the cask surface (about 15% relative difference). (authors)
In-silico analysis on biofabricating vascular networks using kinetic Monte Carlo simulations
We present a computational modeling approach to study the fusion of multicellular aggregate systems in a novel scaffold-less biofabrication process, known as ‘bioprinting’. In this novel technology, live multicellular aggregates are used as fundamental building blocks to make tissues or organs (collectively known as the bio-constructs,) via the layer-by-layer deposition technique or other methods; the printed bio-constructs embedded in maturogens, consisting of nutrient-rich bio-compatible hydrogels, are then placed in bioreactors to undergo the cellular aggregate fusion process to form the desired functional bio-structures. Our approach reported here is an agent-based modeling method, which uses the kinetic Monte Carlo (KMC) algorithm to evolve the cellular system on a lattice. In this method, the cells and the hydrogel media, in which cells are embedded, are coarse-grained to material’s points on a three-dimensional (3D) lattice, where the cell–cell and cell–medium interactions are quantified by adhesion and cohesion energies. In a multicellular aggregate system with a fixed number of cells and fixed amount of hydrogel media, where the effect of cell differentiation, proliferation and death are tactically neglected, the interaction energy is primarily dictated by the interfacial energy between cell and cell as well as between cell and medium particles on the lattice, respectively, based on the differential adhesion hypothesis. By using the transition state theory to track the time evolution of the multicellular system while minimizing the interfacial energy, KMC is shown to be an efficient time-dependent simulation tool to study the evolution of the multicellular aggregate system. In this study, numerical experiments are presented to simulate fusion and cell sorting during the biofabrication process of vascular networks, in which the bio-constructs are fabricated via engineering designs. The results predict the feasibility of fabricating the vascular
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
Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment
Durga Rao, K. [Bhabha Atomic Research Centre, Mumbai (India)], E-mail: durga_k_rao@yahoo.com; Gopika, V.; Sanyasi Rao, V.V.S.; Kushwaha, H.S. [Bhabha Atomic Research Centre, Mumbai (India); Verma, A.K.; Srividya, A. [Indian Institute of Technology Bombay, Mumbai (India)
2009-04-15
Traditional fault tree (FT) analysis is widely used for reliability and safety assessment of complex and critical engineering systems. The behavior of components of complex systems and their interactions such as sequence- and functional-dependent failures, spares and dynamic redundancy management, and priority of failure events cannot be adequately captured by traditional FTs. Dynamic fault tree (DFT) extend traditional FT by defining additional gates called dynamic gates to model these complex interactions. Markov models are used in solving dynamic gates. However, state space becomes too large for calculation with Markov models when the number of gate inputs increases. In addition, Markov model is applicable for only exponential failure and repair distributions. Modeling test and maintenance information on spare components is also very difficult. To address these difficulties, Monte Carlo simulation-based approach is used in this work to solve dynamic gates. The approach is first applied to a problem available in the literature which is having non-repairable components. The obtained results are in good agreement with those in literature. The approach is later applied to a simplified scheme of electrical power supply system of nuclear power plant (NPP), which is a complex repairable system having tested and maintained spares. The results obtained using this approach are in good agreement with those obtained using analytical approach. In addition to point estimates of reliability measures, failure time, and repair time distributions are also obtained from simulation. Finally a case study on reactor regulation system (RRS) of NPP is carried out to demonstrate the application of simulation-based DFT approach to large-scale problems.
Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment
Traditional fault tree (FT) analysis is widely used for reliability and safety assessment of complex and critical engineering systems. The behavior of components of complex systems and their interactions such as sequence- and functional-dependent failures, spares and dynamic redundancy management, and priority of failure events cannot be adequately captured by traditional FTs. Dynamic fault tree (DFT) extend traditional FT by defining additional gates called dynamic gates to model these complex interactions. Markov models are used in solving dynamic gates. However, state space becomes too large for calculation with Markov models when the number of gate inputs increases. In addition, Markov model is applicable for only exponential failure and repair distributions. Modeling test and maintenance information on spare components is also very difficult. To address these difficulties, Monte Carlo simulation-based approach is used in this work to solve dynamic gates. The approach is first applied to a problem available in the literature which is having non-repairable components. The obtained results are in good agreement with those in literature. The approach is later applied to a simplified scheme of electrical power supply system of nuclear power plant (NPP), which is a complex repairable system having tested and maintained spares. The results obtained using this approach are in good agreement with those obtained using analytical approach. In addition to point estimates of reliability measures, failure time, and repair time distributions are also obtained from simulation. Finally a case study on reactor regulation system (RRS) of NPP is carried out to demonstrate the application of simulation-based DFT approach to large-scale problems
Romania Monte Carlo Methods Application to CANDU Spent Fuel Comparative Analysis
Romania has a single NPP at Cernavoda with 5 PHWR reactors of CANDU6 type of 705 MW(e) each, with Cernavoda Unit1, operational starting from December 1996, Unit2 under construction while the remaining Unit3-5 is being conserved. The nuclear energy world wide development is accompanied by huge quantities of spent nuclear fuel accumulation. Having in view the possible impact upon population and environment, in all activities associated to nuclear fuel cycle, namely transportation, storage, reprocessing or disposal, the spent fuel characteristics must be well known. The paper aim is to apply Monte Carlo methods to CANDU spent fuel analysis, starting from the discharge moment, followed by spent fuel transport after a defined cooling period and finishing with the intermediate dry storage. As radiation source 3 CANDU fuels have been considered: standard 37 rods fuel bundle with natural UO2 and SEU fuels, and 43 rods fuel bundle with SEU fuel. After a criticality calculation using KENO-VI code, the criticality coefficient and the actinides and fission products concentrations are obtained. By using ORIGEN-S code, the photon source profiles are calculated and the spent fuel characteristics estimation is done. For the shielding calculations MORSE-SGC code has been used. Regarding to the spent fuel transport, the photon dose rates to the shipping cask wall and in air, at different distances from the cask, are estimated. The shielding calculation for the spent fuel intermediate dry storage is done and the photon dose rates at the storage basket wall (active element of the Cernavoda NPP intermediate dry storage) are obtained. A comparison between the 3 types of CANDU fuels is presented. (authors)
A Bayesian analysis of rare B decays with advanced Monte Carlo methods
Beaujean, Frederik
2012-11-12
Searching for new physics in rare B meson decays governed by b {yields} s transitions, we perform a model-independent global fit of the short-distance couplings C{sub 7}, C{sub 9}, and C{sub 10} of the {Delta}B=1 effective field theory. We assume the standard-model set of b {yields} s{gamma} and b {yields} sl{sup +}l{sup -} operators with real-valued C{sub i}. A total of 59 measurements by the experiments BaBar, Belle, CDF, CLEO, and LHCb of observables in B{yields}K{sup *}{gamma}, B{yields}K{sup (*)}l{sup +}l{sup -}, and B{sub s}{yields}{mu}{sup +}{mu}{sup -} decays are used in the fit. Our analysis is the first of its kind to harness the full power of the Bayesian approach to probability theory. All main sources of theory uncertainty explicitly enter the fit in the form of nuisance parameters. We make optimal use of the experimental information to simultaneously constrain theWilson coefficients as well as hadronic form factors - the dominant theory uncertainty. Generating samples from the posterior probability distribution to compute marginal distributions and predict observables by uncertainty propagation is a formidable numerical challenge for two reasons. First, the posterior has multiple well separated maxima and degeneracies. Second, the computation of the theory predictions is very time consuming. A single posterior evaluation requires O(1s), and a few million evaluations are needed. Population Monte Carlo (PMC) provides a solution to both issues; a mixture density is iteratively adapted to the posterior, and samples are drawn in a massively parallel way using importance sampling. The major shortcoming of PMC is the need for cogent knowledge of the posterior at the initial stage. In an effort towards a general black-box Monte Carlo sampling algorithm, we present a new method to extract the necessary information in a reliable and automatic manner from Markov chains with the help of hierarchical clustering. Exploiting the latest 2012 measurements, the fit
A Bayesian analysis of rare B decays with advanced Monte Carlo methods
Searching for new physics in rare B meson decays governed by b → s transitions, we perform a model-independent global fit of the short-distance couplings C7, C9, and C10 of the ΔB=1 effective field theory. We assume the standard-model set of b → sγ and b → sl+l- operators with real-valued Ci. A total of 59 measurements by the experiments BaBar, Belle, CDF, CLEO, and LHCb of observables in B→K*γ, B→K(*)l+l-, and Bs→μ+μ- decays are used in the fit. Our analysis is the first of its kind to harness the full power of the Bayesian approach to probability theory. All main sources of theory uncertainty explicitly enter the fit in the form of nuisance parameters. We make optimal use of the experimental information to simultaneously constrain theWilson coefficients as well as hadronic form factors - the dominant theory uncertainty. Generating samples from the posterior probability distribution to compute marginal distributions and predict observables by uncertainty propagation is a formidable numerical challenge for two reasons. First, the posterior has multiple well separated maxima and degeneracies. Second, the computation of the theory predictions is very time consuming. A single posterior evaluation requires O(1s), and a few million evaluations are needed. Population Monte Carlo (PMC) provides a solution to both issues; a mixture density is iteratively adapted to the posterior, and samples are drawn in a massively parallel way using importance sampling. The major shortcoming of PMC is the need for cogent knowledge of the posterior at the initial stage. In an effort towards a general black-box Monte Carlo sampling algorithm, we present a new method to extract the necessary information in a reliable and automatic manner from Markov chains with the help of hierarchical clustering. Exploiting the latest 2012 measurements, the fit reveals a flipped-sign solution in addition to a standard-model-like solution for the couplings Ci. The two solutions are related
雷咏梅; 蒋英; 冯捷
2002-01-01
This paper presents a new approach to parallelize 3D lattice Monte Carlo algorithms used in the numerical simulation of polymer on ZiQiang 2000-a cluster of symmetric multiprocessors (SMPs). The combined load for cell and energy calculations over the time step is balanced together to form a single spatial decomposition. Basic aspects and strategies of running Monte Carlo calculations on parallel computers are studied. Different steps involved in porting the software on a parallel architecture based on ZiQiang 2000 running under Linux and MPI are described briefly. It is found that parallelization becomes more advantageous when either the lattice is very large or the model contains many cells and chains.
Abraão Freires Saraiva Júnior
2011-03-01
Full Text Available The use of mathematical and statistical methods can help managers to deal with decision-making difficulties in the business environment. Some of these decisions are related to productive capacity optimization in order to obtain greater economic gains for the company. Within this perspective, this study aims to present the establishment of metrics to support economic decisions related to process or not orders in a company whose products have great variability in variable direct costs per unit that generates accounting uncertainties. To achieve this objective, is proposed a five-step method built from the integration of Management Accounting and Operations Research techniques, emphasizing the Monte Carlo simulation. The method is applied from a didactic example which uses real data achieved through a field research carried out in a plastic products industry that employ recycled material. Finally, it is concluded that the Monte Carlo simulation is effective for treating variable direct costs per unit variability and that the proposed method is useful to support decision-making related to order acceptance.A utilização de métodos matemáticos e estatísticos pode auxiliar gestores a lidar com dificuldades do processo de tomada de decisão no ambiente de negócios. Algumas dessas decisões estão relacionadas à otimização da utilização da capacidade produtiva visando a obtenção de melhores resultados econômicos para a empresa. Dentro dessa perspectiva, o presente trabalho objetiva apresentar o estabelecimento de métricas que deem suporte à decisão econômica de atender ou não a pedidos em uma empresa cujos produtos têm grande variabilidade de custos variáveis diretos unitários que gera incertezas contábeis. Para cumprir esse objetivo, é proposto um método em cinco etapas, construído a partir da integração de técnicas provindas da contabilidade gerencial e da pesquisa operacional, com destaque à simulação de Monte Carlo. O m
Evaluation of CASMO-3 and HELIOS for Fuel Assembly Analysis from Monte Carlo Code
Shim, Hyung Jin; Song, Jae Seung; Lee, Chung Chan
2007-05-15
This report presents a study comparing deterministic lattice physics calculations with Monte Carlo calculations for LWR fuel pin and assembly problems. The study has focused on comparing results from the lattice physics code CASMO-3 and HELIOS against those from the continuous-energy Monte Carlo code McCARD. The comparisons include k{sub inf}, isotopic number densities, and pin power distributions. The CASMO-3 and HELIOS calculations for the k{sub inf}'s of the LWR fuel pin problems show good agreement with McCARD within 956pcm and 658pcm, respectively. For the assembly problems with Gadolinia burnable poison rods, the largest difference between the k{sub inf}'s is 1463pcm with CASMO-3 and 1141pcm with HELIOS. RMS errors for the pin power distributions of CASMO-3 and HELIOS are within 1.3% and 1.5%, respectively.
A numerical study for effective implementation of the antithetic variates technique with geometric splitting/Russian roulette in Monte Carlo radiation transport calculations is presented. The study is based on the theory of Monte Carlo errors where a set of coupled integral equations are solved for the first and second moments of the score and for the expected number of flights per particle history. Numerical results are obtained for particle transmission through an infinite homogeneous slab shield composed of an isotropically scattering medium. Two types of antithetic transformations are considered. The results indicate that the antithetic transformations always lead to reduction in variance and increase in efficiency provided optimal antithetic parameters are chosen. A substantial gain in efficiency is obtained by incorporating antithetic transformations in rule of thumb splitting. The advantage gained for thick slabs (∼20 mfp) with low scattering probability (0.1-0.5) is attractively large . (author). 27 refs., 9 tabs
Regeneration and Fixed-Width Analysis of Markov Chain Monte Carlo Algorithms
Latuszynski, Krzysztof
2009-07-01
In the thesis we take the split chain approach to analyzing Markov chains and use it to establish fixed-width results for estimators obtained via Markov chain Monte Carlo procedures (MCMC). Theoretical results include necessary and sufficient conditions in terms of regeneration for central limit theorems for ergodic Markov chains and a regenerative proof of a CLT version for uniformly ergodic Markov chains with E_{π}f^2< infty. To obtain asymptotic confidence intervals for MCMC estimators, strongly consistent estimators of the asymptotic variance are essential. We relax assumptions required to obtain such estimators. Moreover, under a drift condition, nonasymptotic fixed-width results for MCMC estimators for a general state space setting (not necessarily compact) and not necessarily bounded target function f are obtained. The last chapter is devoted to the idea of adaptive Monte Carlo simulation and provides convergence results and law of large numbers for adaptive procedures under path-stability condition for transition kernels.
Monte Carlo Renormalization Group Analysis of Lattice $\\phi^4$ Model in $D=3,4$
Itakura, M
1999-01-01
We present a simple, sophisticated method to capture renormalization group flow in Monte Carlo simulation, which provides important information of critical phenomena. We applied the method to $D=3,4$ lattice $\\phi^4$ model and obtained renormalization flow diagram which well reproduces theoretically predicted behavior of continuum $\\phi^4$ model. We also show that the method can be easily applied to much more complicated models, such as frustrated spin models.
Jirauschek, Christian; Okeil, Hesham; Lugli, Paolo
2015-01-26
Based on self-consistent ensemble Monte Carlo simulations coupled to the optical field dynamics, we investigate the giant nonlinear susceptibility giving rise to terahertz difference frequency generation in quantum cascade laser structures. Specifically, the dependence on temperature, bias voltage and frequency is considered. It is shown that the optical nonlinearity is temperature insensitive and covers a broad spectral range, as required for widely tunable room temperature terahertz sources. The obtained results are consistent with available experimental data. PMID:25835923
Single pin BWR benchmark problem for coupled Monte Carlo - Thermal hydraulics analysis
As part of the European NURISP research project, a single pin BWR benchmark problem was defined. The aim of this initiative is to test the coupling strategies between Monte Carlo and subchannel codes developed by different project participants. In this paper the results obtained by the Delft Univ. of Technology and Karlsruhe Inst. of Technology will be presented. The benchmark problem was simulated with the following coupled codes: TRIPOLI-SUBCHANFLOW, MCNP-FLICA, MCNP-SUBCHANFLOW, and KENO-SUBCHANFLOW. (authors)
Single pin BWR benchmark problem for coupled Monte Carlo - Thermal hydraulics analysis
Ivanov, A.; Sanchez, V. [Karlsruhe Inst. of Technology, Inst. for Neutron Physics and Reactor Technology, Herman-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen (Germany); Hoogenboom, J. E. [Delft Univ. of Technology, Faculty of Applied Sciences, Mekelweg 15, 2629 JB Delft (Netherlands)
2012-07-01
As part of the European NURISP research project, a single pin BWR benchmark problem was defined. The aim of this initiative is to test the coupling strategies between Monte Carlo and subchannel codes developed by different project participants. In this paper the results obtained by the Delft Univ. of Technology and Karlsruhe Inst. of Technology will be presented. The benchmark problem was simulated with the following coupled codes: TRIPOLI-SUBCHANFLOW, MCNP-FLICA, MCNP-SUBCHANFLOW, and KENO-SUBCHANFLOW. (authors)