NASA Astrophysics Data System (ADS)
Neicu, Toni; Aljarrah, Khaled M.; Jiang, Steve B.
2005-10-01
A computer program has been developed for novel 2D/3D visualization and analysis of the phase-space parameters of Monte Carlo simulations of medical accelerator radiation beams. The software is written in the IDL language and reads the phase-space data generated in the BEAMnrc/BEAM Monte Carlo code format. Contour and colour-wash plots of the fluence, mean energy, energy fluence, mean angle, spectra distribution, energy fluence distribution, angular distribution, and slices and projections of the 3D ZLAST distribution can be calculated and displayed. Based on our experience of using it at Massachusetts General Hospital, the software has proven to be a useful tool for analysis and verification of the Monte Carlo generated phase-space files. The software is in the public domain.
Miao, Han; Li, Jianfeng; Chen, Daoyong
2016-05-18
Nanofibers are well-known nanomaterials that are promising for many important applications. Since sample preparation for the applications usually starts from a nanofiber solution, characterization of the original conformation of nanofibers in the solution is significant because the conformation affects remarkably the behavior of nanofibers in the samples. However, the characterization is very difficult by existing methods: light scattering can only roughly evaluate the conformation in solution; cryo-TEM is laborious, time-consuming, and challenging technically, and thus difficult to study a system statistically. Herein we report a novel and reliable method to recover the 3D original image of nanofibers in solution through theoretical analysis and Monte-Carlo simulations of TEM images of the nanofibers. Firstly, six kinds of monodisperse nanofibers with the same composition and inner structure but different contour lengths were prepared by the method developed in our laboratory. Then, each kind of nanofiber deposited on the substrate of the TEM sample was measured by TEM and meanwhile simulated by the Monte Carlo method. By matching the simulation results with the TEM results, we determined information about the nanofibers including their rigidity and the interaction between the nanofibers and the substrate. Furthermore, for each kind of nanofiber, based on the information, 3D images of the nanofibers in solution can be re-constructed, and then the average gyration radius and hydrodynamic radius can be calculated, which were compared with the corresponding values measured experimentally to demonstrate the reliability of this method. PMID:27101798
Monte Carlo Ion Transport Analysis Code.
Energy Science and Technology Software Center (ESTSC)
2009-04-15
Version: 00 TRIPOS is a versatile Monte Carlo ion transport analysis code. It has been applied to the treatment of both surface and bulk radiation effects. The media considered is composed of multilayer polyatomic materials.
A highly heterogeneous 3D PWR core benchmark: deterministic and Monte Carlo method comparison
NASA Astrophysics Data System (ADS)
Jaboulay, J.-C.; Damian, F.; Douce, S.; Lopez, F.; Guenaut, C.; Aggery, A.; Poinot-Salanon, C.
2014-06-01
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 selcted (to increase conversion of 238U in 239Pu) that leads to harder neutron spectrum compared to standard PWR assembly. In these conditions two main subjects will be discussed: the Monte Carlo variance calculation and the assessment of the diffusion operator with two energy groups for the core calculation.
MCMAC: Monte Carlo Merger Analysis Code
NASA Astrophysics Data System (ADS)
Dawson, William A.
2014-07-01
Monte Carlo Merger Analysis Code (MCMAC) aids in the study of merging clusters. It takes observed priors on each subcluster's mass, radial velocity, and projected separation, draws randomly from those priors, and uses them in a analytic model to get posterior PDF's for merger dynamic properties of interest (e.g. collision velocity, time since collision).
Monte Carlo methods in genetic analysis
Lin, Shili
1996-12-31
Many genetic analyses require computation of probabilities and likelihoods of pedigree data. With more and more genetic marker data deriving from new DNA technologies becoming available to researchers, exact computations are often formidable with standard statistical methods and computational algorithms. The desire to utilize as much available data as possible, coupled with complexities of realistic genetic models, push traditional approaches to their limits. These methods encounter severe methodological and computational challenges, even with the aid of advanced computing technology. Monte Carlo methods are therefore increasingly being explored as practical techniques for estimating these probabilities and likelihoods. This paper reviews the basic elements of the Markov chain Monte Carlo method and the method of sequential imputation, with an emphasis upon their applicability to genetic analysis. Three areas of applications are presented to demonstrate the versatility of Markov chain Monte Carlo for different types of genetic problems. A multilocus linkage analysis example is also presented to illustrate the sequential imputation method. Finally, important statistical issues of Markov chain Monte Carlo and sequential imputation, some of which are unique to genetic data, are discussed, and current solutions are outlined. 72 refs.
3D Monte Carlo radiation transfer modelling of photodynamic therapy
NASA Astrophysics Data System (ADS)
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; Rearden, Bradley T
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.
Improving light propagation Monte Carlo simulations with accurate 3D modeling of skin tissue
Paquit, Vincent C; Price, Jeffery R; Meriaudeau, Fabrice; Tobin Jr, Kenneth William
2008-01-01
In this paper, we present a 3D light propagation model to simulate multispectral reflectance images of large skin surface areas. In particular, we aim to simulate more accurately the effects of various physiological properties of the skin in the case of subcutaneous vein imaging compared to existing models. Our method combines a Monte Carlo light propagation model, a realistic three-dimensional model of the skin using parametric surfaces and a vision system for data acquisition. We describe our model in detail, present results from the Monte Carlo modeling and compare our results with those obtained with a well established Monte Carlo model and with real skin reflectance images.
Monte Carlo generators for studies of the 3D structure of the nucleon
Avakian, Harut; D'Alesio, U.; Murgia, F.
2015-01-23
In this study, extraction of transverse momentum and space distributions of partons from measurements of spin and azimuthal asymmetries requires development of a self consistent analysis framework, accounting for evolution effects, and allowing control of systematic uncertainties due to variations of input parameters and models. Development of realistic Monte-Carlo generators, accounting for TMD evolution effects, spin-orbit and quark-gluon correlations will be crucial for future studies of quark-gluon dynamics in general and 3D structure of the nucleon in particular.
CT based 3D Monte Carlo radiation therapy treatment planning.
Wallace, S; Allen, B J
1998-06-01
This paper outlines the "voxel reconstruction" technique used to model the macroscopic human anatomy of the cranial, abdominal and cervical regions directly from CT scans. Tissue composition, density, and radiation transport characteristics were assigned to each individual volume element (voxel) automatically depending on its greyscale number and physical location. Both external beam and brachytherapy treatment techniques were simulated using the Monte Carlo radiation transport code MCNP (Monte Carlo N-Particle) version 3A. To obtain a high resolution dose calculation, yet not overly extend computational times, variable voxel sizes have been introduced. In regions of interest where high attention to anatomical detail and dose calculation was required, the voxel dimensions were reduced to a few millimetres. In less important regions that only influence the region of interest via scattered radiation, the voxel dimensions were increased to the scale of centimetres. With the use of relatively old (1991) supercomputing hardware, dose calculations were performed in under 10 hours to a standard deviation of 5% in each voxel with a resolution of a few millimetres--current hardware should substantially improve these figures. It is envisaged that with coupled photon/electron transport incorporated into MCNP version 4A and 4B, conventional photon and electron treatment planning will be undertaken using this technique, in addition to neutron and associated photon dosimetry presented here. PMID:9745789
A Monte Carlo method for 3D thermal infrared radiative transfer
NASA Astrophysics Data System (ADS)
Chen, Y.; Liou, K. N.
2006-09-01
A 3D Monte Carlo model for specific application to the broadband thermal radiative transfer has been developed in which the emissivities for gases and cloud particles are parameterized by using a single cubic element as the building block in 3D space. For spectral integration in the thermal infrared, the correlated k-distribution method has been used for the sorting of gaseous absorption lines in multiple-scattering atmospheres involving 3D clouds. To check the Monte-Carlo simulation, we compare a variety of 1D broadband atmospheric fluxes and heating rates to those computed from the conventional plane-parallel (PP) model and demonstrate excellent agreement between the two. Comparisons of the Monte Carlo results for broadband thermal cooling rates in 3D clouds to those computed from the delta-diffusion approximation for 3D radiative transfer and the independent pixel-by-pixel approximation are subsequently carried out to understand the relative merits of these approaches.
Geometrically-compatible 3-D Monte Carlo and discrete-ordinates methods
Morel, J.E.; Wareing, T.A.; McGhee, J.M.; Evans, T.M.
1998-12-31
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The purpose of this project was two-fold. The first purpose was to develop a deterministic discrete-ordinates neutral-particle transport scheme for unstructured tetrahedral spatial meshes, and implement it in a computer code. The second purpose was to modify the MCNP Monte Carlo radiation transport code to use adjoint solutions from the tetrahedral-mesh discrete-ordinates code to reduce the statistical variance of Monte Carlo solutions via a weight-window approach. The first task has resulted in a deterministic transport code that is much more efficient for modeling complex 3-D geometries than any previously existing deterministic code. The second task has resulted in a powerful new capability for dramatically reducing the cost of difficult 3-D Monte Carlo calculations.
3D Direct Simulation Monte Carlo Code Which Solves for Geometrics
Energy Science and Technology Software Center (ESTSC)
1998-01-13
Pegasus is a 3D Direct Simulation Monte Carlo Code which solves for geometries which can be represented by bodies of revolution. Included are all the surface chemistry enhancements in the 2D code Icarus as well as a real vacuum pump model. The code includes multiple species transport.
PEGASUS. 3D Direct Simulation Monte Carlo Code Which Solves for Geometrics
Bartel, T.J.
1998-12-01
Pegasus is a 3D Direct Simulation Monte Carlo Code which solves for geometries which can be represented by bodies of revolution. Included are all the surface chemistry enhancements in the 2D code Icarus as well as a real vacuum pump model. The code includes multiple species transport.
Economic Risk Analysis: Using Analytical and Monte Carlo Techniques.
ERIC Educational Resources Information Center
O'Donnell, Brendan R.; Hickner, Michael A.; Barna, Bruce A.
2002-01-01
Describes the development and instructional use of a Microsoft Excel spreadsheet template that facilitates analytical and Monte Carlo risk analysis of investment decisions. Discusses a variety of risk assessment methods followed by applications of the analytical and Monte Carlo methods. Uses a case study to illustrate use of the spreadsheet tool…
Vectorized Monte Carlo methods for reactor lattice analysis
NASA Technical Reports Server (NTRS)
Brown, F. B.
1984-01-01
Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.
Full 3D visualization tool-kit for Monte Carlo and deterministic transport codes
Frambati, S.; Frignani, M.
2012-07-01
We propose a package of tools capable of translating the geometric inputs and outputs of many Monte Carlo and deterministic radiation transport codes into open source file formats. These tools are aimed at bridging the gap between trusted, widely-used radiation analysis codes and very powerful, more recent and commonly used visualization software, thus supporting the design process and helping with shielding optimization. Three main lines of development were followed: mesh-based analysis of Monte Carlo codes, mesh-based analysis of deterministic codes and Monte Carlo surface meshing. The developed kit is considered a powerful and cost-effective tool in the computer-aided design for radiation transport code users of the nuclear world, and in particular in the fields of core design and radiation analysis. (authors)
Variance reduction in Monte Carlo analysis of rarefied gas diffusion.
NASA Technical Reports Server (NTRS)
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.
Chadha, N; Jasuja, H; Kaur, M; Singh Bahia, M; Silakari, O
2014-01-01
Phosphoinositide 3-kinase alpha (PI3Kα) is a lipid kinase involved in several cellular functions such as cell growth, proliferation, differentiation and survival, and its anomalous regulation leads to cancerous conditions. PI3Kα inhibition completely blocks the cancer signalling pathway, hence it can be explored as an important therapeutic target for cancer treatment. In the present study, docking analysis of 49 selective imidazo[1,2-a]pyrazine inhibitors of PI3Kα was carried out using the QM-Polarized ligand docking (QPLD) program of the Schrödinger software, followed by the refinement of receptor-ligand conformations using the Hybrid Monte Carlo algorithm in the Liaison program, and alignment of refined conformations of inhibitors was utilized for the development of an atom-based 3D-QSAR model in the PHASE program. Among the five generated models, the best model was selected corresponding to PLS factor 2, displaying the highest value of Q(2)test (0.650). The selected model also displayed high values of r(2)train (0.917), F-value (166.5) and Pearson-r (0.877) and a low value of SD (0.265). The contour plots generated for the selected 3D-QSAR model were correlated with the results of docking simulations. Finally, this combined information generated from 3D-QSAR and docking analysis was used to design new congeners. PMID:24601789
3D dose distribution calculation in a voxelized human phantom by means of Monte Carlo method.
Abella, V; Miró, R; Juste, B; Verdú, G
2010-01-01
The aim of this work is to provide the reconstruction of a real human voxelized phantom by means of a MatLab program and the simulation of the irradiation of such phantom with the photon beam generated in a Theratron 780 (MDS Nordion) (60)Co radiotherapy unit, by using the Monte Carlo transport code MCNP (Monte Carlo N-Particle), version 5. The project results in 3D dose mapping calculations inside the voxelized antropomorphic head phantom. The program provides the voxelization by first processing the CT slices; the process follows a two-dimensional pixel and material identification algorithm on each slice and three-dimensional interpolation in order to describe the phantom geometry via small cubic cells, resulting in an MCNP input deck format output. Dose rates are calculated by using the MCNP5 tool FMESH, superimposed mesh tally, which gives the track length estimation of the particle flux in units of particles/cm(2). Furthermore, the particle flux is converted into dose by using the conversion coefficients extracted from the NIST Physical Reference Data. The voxelization using a three-dimensional interpolation technique in combination with the use of the FMESH tool of the MCNP Monte Carlo code offers an optimal simulation which results in 3D dose mapping calculations inside anthropomorphic phantoms. This tool is very useful in radiation treatment assessments, in which voxelized phantoms are widely utilized. PMID:19892556
3-D Monte Carlo-Based Scatter Compensation in Quantitative I-131 SPECT Reconstruction
Dewaraja, Yuni K.; Ljungberg, Michael; Fessler, Jeffrey A.
2010-01-01
We have implemented highly accurate Monte Carlo based scatter modeling (MCS) with 3-D ordered subsets expectation maximization (OSEM) reconstruction for I-131 single photon emission computed tomography (SPECT). The scatter is included in the statistical model as an additive term and attenuation and detector response are included in the forward/backprojector. In the present implementation of MCS, a simple multiple window-based estimate is used for the initial iterations and in the later iterations the Monte Carlo estimate is used for several iterations before it is updated. For I-131, MCS was evaluated and compared with triple energy window (TEW) scatter compensation using simulation studies of a mathematical phantom and a clinically realistic voxel-phantom. Even after just two Monte Carlo updates, excellent agreement was found between the MCS estimate and the true scatter distribution. Accuracy and noise of the reconstructed images were superior with MCS compared to TEW. However, the improvement was not large, and in some cases may not justify the large computational requirements of MCS. Furthermore, it was shown that the TEW correction could be improved for most of the targets investigated here by applying a suitably chosen scaling factor to the scatter estimate. Finally clinical application of MCS was demonstrated by applying the method to an I-131 radioimmunotherapy (RIT) patient study. PMID:20104252
Monte Carlo analysis of magnetic aftereffect phenomena
NASA Astrophysics Data System (ADS)
Andrei, Petru; Stancu, Alexandru
2006-04-01
Magnetic aftereffect phenomena are analyzed by using the Monte Carlo technique. This technique has the advantage that it can be applied to any model of hysteresis. It is shown that a log t-type dependence of the magnetization can be qualitatively predicted even in the framework of hysteresis models with local history, such as the Jiles-Atherton model. These models are computationally much more efficient than the models with global history such as the Preisach model. Numerical results related to the decay of the magnetization as of function of time, as well as to the viscosity coefficient, are presented.
3D Direct Simulation Monte Carlo Modeling of the Spacecraft Environment of Rosetta
NASA Astrophysics Data System (ADS)
Bieler, A. M.; Tenishev, V.; Fougere, N.; Gombosi, T. I.; Hansen, K. C.; Combi, M. R.; Huang, Z.; Jia, X.; Toth, G.; Altwegg, K.; Wurz, P.; Jäckel, A.; Le Roy, L.; Gasc, S.; Calmonte, U.; Rubin, M.; Tzou, C. Y.; Hässig, M.; Fuselier, S.; De Keyser, J.; Berthelier, J. J.; Mall, U. A.; Rème, H.; Fiethe, B.; Balsiger, H.
2014-12-01
The European Space Agency's Rosetta mission is the first to escort a comet over an extended time as the comet makes its way through the inner solar system. The ROSINA instrument suite consisting of a double focusing mass spectrometer, a time of flight mass spectrometer and a pressure sensor, will provide temporally and spatially resolved data on the comet's volatile inventory. The effect of spacecraft outgassing is well known and has been measured with the ROSINA instruments onboard Rosetta throughout the cruise phase. The flux of released neutral gas originating from the spacecraft cannot be distinguished from the cometary signal by the mass spectrometers and varies significantly with solar illumination conditions. For accurate interpretation of the instrument data, a good understanding of spacecraft outgassing is necessary. In this talk we present results simulating the spacecraft environment with the Adaptive Mesh Particle Simulator (AMPS) code. AMPS is a direct simulation monte carlo code that includes multiple species in a 3D adaptive mesh to describe a full scale model of the spacecraft environment. We use the triangulated surface model of the spacecraft to implement realistic outgassing rates for different areas on the surface and take shadowing effects in consideration. The resulting particle fluxes are compared to the measurements of the ROSINA experiment and implications for ROSINA measurements and data analysis are discussed. Spacecraft outgassing has implications for future space missions to rarefied atmospheres as it imposes a limit on the detection of various species.
ORPHEE research reactor: 3D core depletion calculation using Monte-Carlo code TRIPOLI-4®
NASA Astrophysics Data System (ADS)
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.
Supernova Spectrum Synthesis for 3D Composition Models with the Monte Carlo Method
NASA Astrophysics Data System (ADS)
Thomas, Rollin
2002-07-01
newcommandBruteextttBrute Relying on spherical symmetry when modelling supernova spectra is clearly at best a good approximation. Recent polarization measurements, interesting features in flux spectra, and the clumpy textures of supernova remnants suggest that supernova envelopes are rife with fine structure. To account for this fine structure and create a complete picture of supernovae, new 3D explosion models will be forthcoming. To reconcile these models with observed spectra, 3D radiative transfer will be necessary. We propose a 3D Monte Carlo radiative transfer code, Brute, and improvements that will move it toward a fully self-consistent 3D transfer code. Spectroscopic HST observations of supernovae past, present and future will definitely benefit. Other 3D transfer problems of interest to HST users like AGNs will benefit from the techniques developed.
Energy Science and Technology Software Center (ESTSC)
2013-06-24
Version 07 TART2012 is a coupled neutron-photon Monte Carlo transport code designed to use three-dimensional (3-D) combinatorial geometry. Neutron and/or photon sources as well as neutron induced photon production can be tracked. It is a complete system to assist you with input preparation, running Monte Carlo calculations, and analysis of output results. TART2012 is also incredibly FAST; if you have used similar codes, you will be amazed at how fast this code is compared tomore » other similar codes. Use of the entire system can save you a great deal of time and energy. TART2012 extends the general utility of the code to even more areas of application than available in previous releases by concentrating on improving the physics, particularly with regard to improved treatment of neutron fission, resonance self-shielding, molecular binding, and extending input options used by the code. Several utilities are included for creating input files and displaying TART results and data. TART2012 uses the latest ENDF/B-VI, Release 8, data. New for TART2012 is the use of continuous energy neutron cross sections, in addition to its traditional multigroup cross sections. For neutron interaction, the data are derived using ENDF-ENDL2005 and include both continuous energy cross sections and 700 group neutron data derived using a combination of ENDF/B-VI, Release 8, and ENDL data. The 700 group structure extends from 10-5 eV up to 1 GeV. Presently nuclear data are only available up to 20 MeV, so that only 616 of the groups are currently used. For photon interaction, 701 point photon data were derived using the Livermore EPDL97 file. The new 701 point structure extends from 100 eV up to 1 GeV, and is currently used over this entire energy range. TART2012 completely supersedes all older versions of TART, and it is strongly recommended that one use only the most recent version of TART2012 and its data files. Check authors homepage for related information: http
3-D Direct Simulation Monte Carlo modeling of comet 67P/Churyumov-Gerasimenko
NASA Astrophysics Data System (ADS)
Liao, Y.; Su, C.; Finklenburg, S.; Rubin, M.; Ip, W.; Keller, H.; Knollenberg, J.; Kührt, E.; Lai, I.; Skorov, Y.; Thomas, N.; Wu, J.; Chen, Y.
2014-07-01
After deep-space hibernation, ESA's Rosetta spacecraft has been successfully woken up and obtained the first images of comet 67P /Churyumov-Gerasimenko (C-G) in March 2014. It is expected that Rosetta will rendezvous with comet 67P and start to observe the nucleus and coma of the comet in the middle of 2014. As the comet approaches the Sun, a significant increase in activity is expected. Our aim is to understand the physical processes in the coma with the help of modeling in order to interpret the resulting measurements and establish observational and data analysis strategies. DSMC (Direct Simulation Monte Carlo) [1] is a very 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 [2,3]. Comparisons between DSMC and fluid techniques have also been performed to establish the limits of these techniques [2,4]. The drawback with 3D DSMC is that it is computationally highly intensive and thus time consuming. However, the performance can be dramatically increased with parallel computing on Graphic Processor Units (GPUs) [5]. We have already studied a case with comet 9P/Tempel 1 where the Deep Impact observations were used to define the shape of the nucleus and the outflow was simulated with the DSMC approach [6,7]. For comet 67P, we intend to determine the gas flow field in the innermost coma and the surface outgassing properties from analyses of the flow field, to investigate dust acceleration by gas drag, and to compare with observations (including time variability). The boundary conditions are implemented with a nucleus shape model [8] and thermal models which are based on the surface heat-balance equation. Several different parameter sets have been investigated. The calculations have been performed using the PDSC^{++} (Parallel Direct Simulation Monte Carlo) code [9] developed by Wu and his coworkers [10-12]. Simulation tasks can be accomplished within 24
A Monte Carlo correction for the effect of Compton scattering in 3-D PET brain imaging
Levin, C.S.; Dahlbom, M.; Hoffman, E.J.
1995-08-01
A Monte Carlo simulation has been developed to simulate and correct for the effect of Compton scatter in 3-D acquired PET brain scans. The method utilizes the 3-D reconstructed image volume as the source intensity distribution for a photon-tracking Monte Carlo simulation. It is assumed that the number of events in each pixel of the image represents the isotope concentration at that location in the brain. The history of each annihilation photon`s interactions in the scattering medium is followed, and the sinograms for the scattered and unscattered photon pairs are generated in a simulated 3-D PET acquisition. The calculated scatter contribution is used to correct the original data set. The method is general and can be applied to any scanner configuration or geometry. In its current form the simulation requires 25 hours on a single Sparc 10 CPU when every pixel in a 15-plane, 128 x 128 pixel image volume is sampled, and less than 2 hours when 16 pixels (4 x 4) are grouped as a single pixel. Results of the correction applied to 3-D human and phantom studies are presented.
A graphical user interface for calculation of 3D dose distribution using Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Chow, J. C. L.; Leung, M. K. K.
2008-02-01
A software graphical user interface (GUI) for calculation of 3D dose distribution using Monte Carlo (MC) simulation is developed using MATLAB. This GUI (DOSCTP) provides a user-friendly platform for DICOM CT-based dose calculation using EGSnrcMP-based DOSXYZnrc code. It offers numerous features not found in DOSXYZnrc, such as the ability to use multiple beams from different phase-space files, and has built-in dose analysis and visualization tools. DOSCTP is written completely in MATLAB, with integrated access to DOSXYZnrc and CTCREATE. The program function may be divided into four subgroups, namely, beam placement, MC simulation with DOSXYZnrc, dose visualization, and export. Each is controlled by separate routines. The verification of DOSCTP was carried out by comparing plans with different beam arrangements (multi-beam/photon arc) on an inhomogeneous phantom as well as patient CT between the GUI and Pinnacle3. DOSCTP was developed and verified with the following features: (1) a built-in voxel editor to modify CT-based DOSXYZnrc phantoms for research purposes; (2) multi-beam placement is possible, which cannot be achieved using the current DOSXYZnrc code; (3) the treatment plan, including the dose distributions, contours and image set can be exported to a commercial treatment planning system such as Pinnacle3 or to CERR using RTOG format for plan evaluation and comparison; (4) a built-in RTOG-compatible dose reviewer for dose visualization and analysis such as finding the volume of hot/cold spots in the 3D dose distributions based on a user threshold. DOSCTP greatly simplifies the use of DOSXYZnrc and CTCREATE, and offers numerous features that not found in the original user-code. Moreover, since phase-space beams can be defined and generated by the user, it is a particularly useful tool to carry out plans using specifically designed irradiators/accelerators that cannot be found in the Linac library of commercial treatment planning systems.
Ultrafast vectorized multispin coding algorithm for the Monte Carlo simulation of the 3D Ising model
NASA Astrophysics Data System (ADS)
Wansleben, Stephan
1987-02-01
A new Monte Carlo algorithm for the 3D Ising model and its implementation on a CDC CYBER 205 is presented. This approach is applicable to lattices with sizes between 3·3·3 and 192·192·192 with periodic boundary conditions, and is adjustable to various kinetic models. It simulates a canonical ensemble at given temperature generating a new random number for each spin flip. For the Metropolis transition probability the speed is 27 ns per updates on a two-pipe CDC Cyber 205 with 2 million words physical memory, i.e. 1.35 times the cycle time per update or 38 million updates per second.
Tool for Rapid Analysis of Monte Carlo Simulations
NASA Technical Reports Server (NTRS)
Restrepo, Carolina; McCall, Kurt E.; Hurtado, John E.
2011-01-01
Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very di cult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The Tool for Rapid Analysis of Monte Carlo simulations (TRAM) has been used in recent design and analysis work for the Orion vehicle, greatly decreasing the time it takes to evaluate performance requirements. A previous version of this tool was developed to automatically identify driving design variables in Monte Carlo data sets. This paper describes a new, parallel version, of TRAM implemented on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.
TART97 a coupled neutron-photon 3-D, combinatorial geometry Monte Carlo transport code
Cullen, D.E.
1997-11-22
TART97 is a coupled neutron-photon, 3 Dimensional, combinatorial geometry, time dependent Monte Carlo transport code. This code can on any modern computer. It is a complete system to assist you with input preparation, running Monte Carlo calculations, and analysis of output results. TART97 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. TART97 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. TART97 completely supersedes all older versions of TART, and it is strongly recommended that users only use the most recent version of TART97 and its data riles.
A Monte Carlo method for combined segregation and linkage analysis.
Guo, S W; Thompson, E A
1992-01-01
We introduce a Monte Carlo approach to combined segregation and linkage analysis of a quantitative trait observed in an extended pedigree. In conjunction with the Monte Carlo method of likelihood-ratio evaluation proposed by Thompson and Guo, the method provides for estimation and hypothesis testing. The greatest attraction of this approach is its ability to handle complex genetic models and large pedigrees. Two examples illustrate the practicality of the method. One is of simulated data on a large pedigree; the other is a reanalysis of published data previously analyzed by other methods. PMID:1415253
NASA Astrophysics Data System (ADS)
Besemer, Abigail E.
Targeted radionuclide therapy is emerging as an attractive treatment option for a broad spectrum of tumor types because it has the potential to simultaneously eradicate both the primary tumor site as well as the metastatic disease throughout the body. Patient-specific absorbed dose calculations for radionuclide therapies are important for reducing the risk of normal tissue complications and optimizing tumor response. However, the only FDA approved software for internal dosimetry calculates doses based on the MIRD methodology which estimates mean organ doses using activity-to-dose scaling factors tabulated from standard phantom geometries. Despite the improved dosimetric accuracy afforded by direct Monte Carlo dosimetry methods these methods are not widely used in routine clinical practice because of the complexity of implementation, lack of relevant standard protocols, and longer dose calculation times. The main goal of this work was to develop a Monte Carlo internal dosimetry platform in order to (1) calculate patient-specific voxelized dose distributions in a clinically feasible time frame, (2) examine and quantify the dosimetric impact of various parameters and methodologies used in 3D internal dosimetry methods, and (3) develop a multi-criteria treatment planning optimization framework for multi-radiopharmaceutical combination therapies. This platform utilizes serial PET/CT or SPECT/CT images to calculate voxelized 3D internal dose distributions with the Monte Carlo code Geant4. Dosimetry can be computed for any diagnostic or therapeutic radiopharmaceutical and for both pre-clinical and clinical applications. In this work, the platform's dosimetry calculations were successfully validated against previously published reference doses values calculated in standard phantoms for a variety of radionuclides, over a wide range of photon and electron energies, and for many different organs and tumor sizes. Retrospective dosimetry was also calculated for various pre
Billion-atom synchronous parallel kinetic Monte Carlo simulations of critical 3D Ising systems
Martinez, E.; Monasterio, P.R.; Marian, J.
2011-02-20
An extension of the synchronous parallel kinetic Monte Carlo (spkMC) algorithm developed by Martinez et al. [J. Comp. Phys. 227 (2008) 3804] to discrete lattices is presented. The method solves the master equation synchronously by recourse to null events that keep all processors' time clocks current in a global sense. Boundary conflicts are resolved by adopting a chessboard decomposition into non-interacting sublattices. We find that the bias introduced by the spatial correlations attendant to the sublattice decomposition is within the standard deviation of serial calculations, which confirms the statistical validity of our algorithm. We have analyzed the parallel efficiency of spkMC and find that it scales consistently with problem size and sublattice partition. We apply the method to the calculation of scale-dependent critical exponents in billion-atom 3D Ising systems, with very good agreement with state-of-the-art multispin simulations.
Billion-atom synchronous parallel kinetic Monte Carlo simulations of critical 3D Ising systems
NASA Astrophysics Data System (ADS)
Martínez, E.; Monasterio, P. R.; Marian, J.
2011-02-01
An extension of the synchronous parallel kinetic Monte Carlo (spkMC) algorithm developed by Martinez et al. [J. Comp. Phys. 227 (2008) 3804] to discrete lattices is presented. The method solves the master equation synchronously by recourse to null events that keep all processors' time clocks current in a global sense. Boundary conflicts are resolved by adopting a chessboard decomposition into non-interacting sublattices. We find that the bias introduced by the spatial correlations attendant to the sublattice decomposition is within the standard deviation of serial calculations, which confirms the statistical validity of our algorithm. We have analyzed the parallel efficiency of spkMC and find that it scales consistently with problem size and sublattice partition. We apply the method to the calculation of scale-dependent critical exponents in billion-atom 3D Ising systems, with very good agreement with state-of-the-art multispin simulations.
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.
2015-01-01
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
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
3D electro-thermal Monte Carlo study of transport in confined silicon devices
NASA Astrophysics Data System (ADS)
Mohamed, Mohamed Y.
The simultaneous explosion of portable microelectronics devices and the rapid shrinking of microprocessor size have provided a tremendous motivation to scientists and engineers to continue the down-scaling of these devices. For several decades, innovations have allowed components such as transistors to be physically reduced in size, allowing the famous Moore's law to hold true. As these transistors approach the atomic scale, however, further reduction becomes less probable and practical. As new technologies overcome these limitations, they face new, unexpected problems, including the ability to accurately simulate and predict the behavior of these devices, and to manage the heat they generate. This work uses a 3D Monte Carlo (MC) simulator to investigate the electro-thermal behavior of quasi-one-dimensional electron gas (1DEG) multigate MOSFETs. In order to study these highly confined architectures, the inclusion of quantum correction becomes essential. To better capture the influence of carrier confinement, the electrostatically quantum-corrected full-band MC model has the added feature of being able to incorporate subband scattering. The scattering rate selection introduces quantum correction into carrier movement. In addition to the quantum effects, scaling introduces thermal management issues due to the surge in power dissipation. Solving these problems will continue to bring improvements in battery life, performance, and size constraints of future devices. We have coupled our electron transport Monte Carlo simulation to Aksamija's phonon transport so that we may accurately and efficiently study carrier transport, heat generation, and other effects at the transistor level. This coupling utilizes anharmonic phonon decay and temperature dependent scattering rates. One immediate advantage of our coupled electro-thermal Monte Carlo simulator is its ability to provide an accurate description of the spatial variation of self-heating and its effect on non
Error propagation in the computation of volumes in 3D city models with the Monte Carlo method
NASA Astrophysics Data System (ADS)
Biljecki, F.; Ledoux, H.; Stoter, J.
2014-11-01
This paper describes the analysis of the propagation of positional uncertainty in 3D city models to the uncertainty in the computation of their volumes. Current work related to error propagation in GIS is limited to 2D data and 2D GIS operations, especially of rasters. In this research we have (1) developed two engines, one that generates random 3D buildings in CityGML in multiple LODs, and one that simulates acquisition errors to the geometry; (2) performed an error propagation analysis on volume computation based on the Monte Carlo method; and (3) worked towards establishing a framework for investigating error propagation in 3D GIS. The results of the experiments show that a comparatively small error in the geometry of a 3D city model may cause significant discrepancies in the computation of its volume. This has consequences for several applications, such as in estimation of energy demand and property taxes. The contribution of this work is twofold: this is the first error propagation analysis in 3D city modelling, and the novel approach and the engines that we have created can be used for analysing most of 3D GIS operations, supporting related research efforts in the future.
A Coupled Neutron-Photon 3-D Combinatorial Geometry Monte Carlo Transport Code
Energy Science and Technology Software Center (ESTSC)
1998-06-12
TART97 is a coupled neutron-photon, 3 dimensional, combinatorial geometry, time dependent Monte Carlo 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. TART97 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 canmore » save you a great deal of time and energy. TART 97 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. TART97 completely supersedes all older versions of TART, and it is strongly recommended that users only use the most recent version of TART97 and ist data files.« less
Self-assembly of ABC triblock copolymers under 3D soft confinement: a Monte Carlo study.
Yan, Nan; Zhu, Yutian; Jiang, Wei
2016-01-21
Under three-dimensional (3D) soft confinement, block copolymers can self-assemble into unique nanostructures that cannot be fabricated in an un-confined space. Linear ABC triblock copolymers containing three chemically distinct polymer blocks possess relatively complex chain architecture, which can be a promising candidate for the 3D confined self-assembly. In the current study, the Monte Carlo technique was applied in a lattice model to study the self-assembly of ABC triblock copolymers under 3D soft confinement, which corresponds to the self-assembly of block copolymers confined in emulsion droplets. We demonstrated how to create various nanostructures by tuning the symmetry of ABC triblock copolymers, the incompatibilities between different block types, and solvent properties. Besides common pupa-like and bud-like nanostructures, our simulations predicted various unique self-assembled nanostructures, including a striped-pattern nanoparticle with intertwined A-cages and C-cages, a pyramid-like nanoparticle with four Janus B-C lamellae adhered onto its four surfaces, an ellipsoidal nanoparticle with a dumbbell-like A-core and two Janus B-C lamellae and a Janus B-C ring surrounding the A-core, a spherical nanoparticle with a A-core and a helical Janus B-C stripe around the A-core, a cubic nanoparticle with a cube-shape A-core and six Janus B-C lamellae adhered onto the surfaces of the A-cube, and a spherical nanoparticle with helical A, B and C structures, from the 3D confined self-assembly of ABC triblock copolymers. Moreover, the formation mechanisms of some typical nanostructures were also examined by the variations of the contact numbers with time and a series of snapshots at different Monte Carlo times. It is found that ABC triblock copolymers usually aggregate into a loose aggregate at first, and then the microphase separation between A, B and C blocks occurs, resulting in the formation of various nanostructures. PMID:26571300
Improvement of 3d Monte Carlo Localization Using a Depth Camera and Terrestrial Laser Scanner
NASA Astrophysics Data System (ADS)
Kanai, S.; Hatakeyama, R.; Date, H.
2015-05-01
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.
3D Visualization of Monte-Carlo Simulation's of HZE Track Structure and Initial Chemical Species
NASA Technical Reports Server (NTRS)
Plante, Ianik; Cucinotta, Francis A.
2009-01-01
Heavy ions biophysics is important for space radiation risk assessment [1] and hadron-therapy [2]. The characteristic of heavy ions tracks include a very high energy deposition region close to the track (<20 nm) denoted as the track core, and an outer penumbra region consisting of individual secondary electrons (6-rays). A still open question is the radiobiological effects of 6- rays relative to the track core. Of importance is the induction of double-strand breaks (DSB) [3] and oxidative damage to the biomolecules and the tissue matrix, considered the most important lesions for acute and long term effects of radiation. In this work, we have simulated a 56Fe26+ ion track of 1 GeV/amu with our Monte-Carlo code RITRACKS [4]. The simulation results have been used to calculate the energy depiction and initial chemical species in a "voxelized" space, which is then visualized in 3D. Several voxels with dose >1000 Gy are found in the penumbra, some located 0.1 mm from the track core. In computational models, the DSB induction probability is calculated with radial dose [6], which may not take into account the higher RBE of electron track ends for DSB induction. Therefore, these simulations should help improve models of DSB induction and our understanding of heavy ions biophysics.
A Post-Monte-Carlo Sensitivity Analysis Code
Energy Science and Technology Software Center (ESTSC)
2000-04-04
SATOOL (Sensitivity Analysis TOOL) is a code for sensitivity analysis, following an uncertainity analysis with Monte Carlo simulations. Sensitivity analysis identifies those input variables, whose variance contributes dominatly to the variance in the output. This analysis can be used to reduce the variance in the output variables by redefining the "sensitive" variables with greater precision, i.e. with lower variance. The code identifies a group of sensitive variables, ranks them in the order of importance andmore » also quantifies the relative importance among the sensitive variables.« less
Adaptive multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model
NASA Astrophysics Data System (ADS)
Navarro, Cristóbal A.; Huang, Wei; Deng, Youjin
2016-08-01
This work presents an adaptive multi-GPU Exchange Monte Carlo approach for the simulation of the 3D Random Field Ising Model (RFIM). The design is based on a two-level parallelization. The first level, spin-level parallelism, maps the parallel computation as optimal 3D thread-blocks that simulate blocks of spins in shared memory with minimal halo surface, assuming a constant block volume. The second level, replica-level parallelism, uses multi-GPU computation to handle the simulation of an ensemble of replicas. CUDA's concurrent kernel execution feature is used in order to fill the occupancy of each GPU with many replicas, providing a performance boost that is more notorious at the smallest values of L. In addition to the two-level parallel design, the work proposes an adaptive multi-GPU approach that dynamically builds a proper temperature set free of exchange bottlenecks. The strategy is based on mid-point insertions at the temperature gaps where the exchange rate is most compromised. The extra work generated by the insertions is balanced across the GPUs independently of where the mid-point insertions were performed. Performance results show that spin-level performance is approximately two orders of magnitude faster than a single-core CPU version and one order of magnitude faster than a parallel multi-core CPU version running on 16-cores. Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99 % efficiency as long as the number of GPUs and L increase together. The combination of the adaptive approach with the parallel multi-GPU design has extended our possibilities of simulation to sizes of L = 32 , 64 for a workstation with two GPUs. Sizes beyond L = 64 can eventually be studied using larger multi-GPU systems.
Asymptotic analysis of spatial discretizations in implicit Monte Carlo
Densmore, Jeffery D
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.
Asymptotic analysis of spatial discretizations in implicit Monte Carlo
Densmore, Jeffery D
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.
Variance reduction in Monte Carlo analysis of rarefied gas diffusion
NASA Technical Reports Server (NTRS)
Perlmutter, M.
1972-01-01
The present analysis uses the Monte Carlo method to solve the problem of rarefied diffusion between parallel walls. The diffusing molecules are evaporated or emitted from one of two parallel walls and diffused through another molecular species. The 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 M. C. result has a much smaller error.
Assessment of a fully 3D Monte Carlo reconstruction method for preclinical PET with iodine-124
NASA Astrophysics Data System (ADS)
Moreau, M.; Buvat, I.; Ammour, L.; Chouin, N.; Kraeber-Bodéré, F.; Chérel, M.; Carlier, T.
2015-03-01
Iodine-124 is a radionuclide well suited to the labeling of intact monoclonal antibodies. Yet, accurate quantification in preclinical imaging with I-124 is challenging due to the large positron range and a complex decay scheme including high-energy gammas. The aim of this work was to assess the quantitative performance of a fully 3D Monte Carlo (MC) reconstruction for preclinical I-124 PET. The high-resolution small animal PET Inveon (Siemens) was simulated using GATE 6.1. Three system matrices (SM) of different complexity were calculated in addition to a Siddon-based ray tracing approach for comparison purpose. Each system matrix accounted for a more or less complete description of the physics processes both in the scanned object and in the PET scanner. One homogeneous water phantom and three heterogeneous phantoms including water, lungs and bones were simulated, where hot and cold regions were used to assess activity recovery as well as the trade-off between contrast recovery and noise in different regions. The benefit of accounting for scatter, attenuation, positron range and spurious coincidences occurring in the object when calculating the system matrix used to reconstruct I-124 PET images was highlighted. We found that the use of an MC SM including a thorough modelling of the detector response and physical effects in a uniform water-equivalent phantom was efficient to get reasonable quantitative accuracy in homogeneous and heterogeneous phantoms. Modelling the phantom heterogeneities in the SM did not necessarily yield the most accurate estimate of the activity distribution, due to the high variance affecting many SM elements in the most sophisticated SM.
NASA Astrophysics Data System (ADS)
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.
Doblhoff-Dier, Katharina; Meyer, Jörg; Hoggan, Philip E; Kroes, Geert-Jan; Wagner, Lucas K
2016-06-14
Transition metals and transition metal compounds are important to catalysis, photochemistry, and many superconducting systems. We study the performance of diffusion Monte Carlo (DMC) applied to transition metal containing dimers (TMCDs) using single-determinant Slater-Jastrow trial wavefunctions and investigate the possible influence of the locality and pseudopotential errors. We find that the locality approximation can introduce nonsystematic errors of up to several tens of kilocalories per mole in the absolute energy of Cu and CuH if Ar or Mg core pseudopotentials (PPs) are used for the 3d transition metal atoms. Even for energy differences such as binding energies, errors due to the locality approximation can be problematic if chemical accuracy is sought. The use of the Ne core PPs developed by Burkatzki et al. (J. Chem. Phys. 2008, 129, 164115), the use of linear energy minimization rather than unreweighted variance minimization for the optimization of the Jastrow function, and the use of large Jastrow parametrizations reduce the locality errors. In the second section of this article, we study the general performance of DMC for 3d TMCDs using a database of binding energies of 20 TMCDs, for which comparatively accurate experimental data is available. Comparing our DMC results to these data for our results that compare best with experiment, we find a mean unsigned error (MUE) of 4.5 kcal/mol. This compares well with the achievable accuracy in CCSDT(2)Q (MUE = 4.6 kcal/mol) and the best all-electron DFT results (MUE = 4.5 kcal/mol) for the same set of systems (Truhlar et al. J. Chem. Theory Comput. 2015, 11, 2036-2052). The mean errors in DMC depend less on the exchange-correlation functionals used to generate the trial wavefunction than the corresponding mean errors in the underlying DFT calculations. Furthermore, the QMC results obtained for each molecule individually vary less with the functionals used. These observations are relevant for systems such as
Tool for Rapid Analysis of Monte Carlo Simulations
NASA Technical Reports Server (NTRS)
Restrepo, Carolina; McCall, Kurt E.; Hurtado, John E.
2013-01-01
Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very difficult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The first version of this tool was a serial code and the current version is a parallel code, which has greatly increased the analysis capabilities. This paper describes the new implementation of this analysis tool on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.
Monte Carlo Test Assembly for Item Pool Analysis and Extension
ERIC Educational Resources Information Center
Belov, Dmitry I.; Armstrong, Ronald D.
2005-01-01
A new test assembly algorithm based on a Monte Carlo random search is presented in this article. A major advantage of the Monte Carlo test assembly over other approaches (integer programming or enumerative heuristics) is that it performs a uniform sampling from the item pool, which provides every feasible item combination (test) with an equal…
NASA Astrophysics Data System (ADS)
Zhang, M. Q.
1989-09-01
A new Monte Carlo algorithm for 3D Kawasaki spin-exchange simulations and its implementation on a CDC CYBER 205 is presented. This approach is applicable to lattices with sizes between 4×4×4 and 256×L2×L3 ((L2+2)(L3+4)/4⩽65535) and periodic boundary conditions. It is adjustable to various kinetic models in which the total magnetization is conserved. Maximum speed on 10 million steps per second can be reached for 3-D Ising model with Metropolis rate.
RMC - A Monte Carlo code for reactor physics analysis
Wang, K.; Li, Z.; She, D.; Liang, J.; Xu, Q.; Qiu, A.; Yu, J.; Sun, J.; Fan, X.; Yu, G.
2013-07-01
A new Monte Carlo neutron transport code RMC has been being developed by Department of Engineering Physics, Tsinghua University, Beijing as a tool for reactor physics analysis on high-performance computing platforms. To meet the requirements of reactor analysis, RMC now has such functions as criticality calculation, fixed-source calculation, burnup calculation and kinetics simulations. Some techniques for geometry treatment, new burnup algorithm, source convergence acceleration, massive tally and parallel calculation, and temperature dependent cross sections processing are researched and implemented in RMC to improve the efficiency. Validation results of criticality calculation, burnup calculation, source convergence acceleration, tallies performance and parallel performance shown in this paper prove the capabilities of RMC in dealing with reactor analysis problems with good performances. (authors)
Iterative Monte Carlo analysis of spin-dependent parton distributions
NASA Astrophysics Data System (ADS)
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.
Applicability of 3D Monte Carlo simulations for local values calculations in a PWR core
NASA Astrophysics Data System (ADS)
Bernard, Franck; Cochet, Bertrand; Jinaphanh, Alexis; Jacquet, Olivier
2014-06-01
As technical support of the French Nuclear Safety Authority, IRSN has been developing the MORET Monte Carlo code for many years in the framework of criticality safety assessment and is now working to extend its application to reactor physics. For that purpose, beside the validation for criticality safety (more than 2000 benchmarks from the ICSBEP Handbook have been modeled and analyzed), a complementary validation phase for reactor physics has been started, with benchmarks from IRPHEP Handbook and others. In particular, to evaluate the applicability of MORET and other Monte Carlo codes for local flux or power density calculations in large power reactors, it has been decided to contribute to the "Monte Carlo Performance Benchmark" (hosted by OECD/NEA). The aim of this benchmark is to monitor, in forthcoming decades, the performance progress of detailed Monte Carlo full core calculations. More precisely, it measures their advancement towards achieving high statistical accuracy in reasonable computation time for local power at fuel pellet level. A full PWR reactor core is modeled to compute local power densities for more than 6 million fuel regions. This paper presents results obtained at IRSN for this benchmark with MORET and comparisons with MCNP. The number of fuel elements is so large that source convergence as well as statistical convergence issues could cause large errors in local tallies, especially in peripheral zones. Various sampling or tracking methods have been implemented in MORET, and their operational effects on such a complex case have been studied. Beyond convergence issues, to compute local values in so many fuel regions could cause prohibitive slowing down of neutron tracking. To avoid this, energy grid unification and tallies preparation before tracking have been implemented, tested and proved to be successful. In this particular case, IRSN obtained promising results with MORET compared to MCNP, in terms of local power densities, standard
NASA Astrophysics Data System (ADS)
Wang, Brian; Goldstein, Moshe; Xu, X. George; Sahoo, Narayan
2005-03-01
Recently, the theoretical framework of the adjoint Monte Carlo (AMC) method has been developed using a simplified patient geometry. In this study, we extended our previous work by applying the AMC framework to a 3D anatomical model called VIP-Man constructed from the Visible Human images. First, the adjoint fluxes for the prostate (PTV) and rectum and bladder (organs at risk (OARs)) were calculated on a spherical surface of 1 m radius, centred at the centre of gravity of PTV. An importance ratio, defined as the PTV dose divided by the weighted OAR doses, was calculated for each of the available beamlets to select the beam angles. Finally, the detailed doses in PTV and OAR were calculated using a forward Monte Carlo simulation to include the electron transport. The dose information was then used to generate dose volume histograms (DVHs). The Pinnacle treatment planning system was also used to generate DVHs for the 3D plans with beam angles obtained from the AMC (3D-AMC) and a standard six-field conformal radiation therapy plan (3D-CRT). Results show that the DVHs for prostate from 3D-AMC and the standard 3D-CRT are very similar, showing that both methods can deliver prescribed dose to the PTV. A substantial improvement in the DVHs for bladder and rectum was found for the 3D-AMC method in comparison to those obtained from 3D-CRT. However, the 3D-AMC plan is less conformal than the 3D-CRT plan because only bladder, rectum and PTV are considered for calculating the importance ratios. Nevertheless, this study clearly demonstrated the feasibility of the AMC in selecting the beam directions as a part of a treatment planning based on the anatomical information in a 3D and realistic patient anatomy.
The X-43A Six Degree of Freedom Monte Carlo Analysis
NASA Technical Reports Server (NTRS)
Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger
2008-01-01
This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A inflight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.
The X-43A Six Degree of Freedom Monte Carlo Analysis
NASA Technical Reports Server (NTRS)
Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger; Richard, Michael
2007-01-01
This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A in-flight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.
Photons, Electrons and Positrons Transport in 3D by Monte Carlo Techniques
Energy Science and Technology Software Center (ESTSC)
2014-12-01
Version 04 FOTELP-2014 is a new compact general purpose version of the previous FOTELP-2K6 code designed to simulate the transport of photons, electrons and positrons through three-dimensional material and sources geometry by Monte Carlo techniques, using subroutine package PENGEOM from the PENELOPE code under Linux-based and Windows OS. This new version includes routine ELMAG for electron and positron transport simulation in electric and magnetic fields, RESUME option and routine TIMER for obtaining starting random numbermore » and for measuring the time of simulation.« less
Photons, Electrons and Positrons Transport in 3D by Monte Carlo Techniques
2014-12-01
Version 04 FOTELP-2014 is a new compact general purpose version of the previous FOTELP-2K6 code designed to simulate the transport of photons, electrons and positrons through three-dimensional material and sources geometry by Monte Carlo techniques, using subroutine package PENGEOM from the PENELOPE code under Linux-based and Windows OS. This new version includes routine ELMAG for electron and positron transport simulation in electric and magnetic fields, RESUME option and routine TIMER for obtaining starting random number and for measuring the time of simulation.
Interpretation of 3D void measurements with Tripoli4.6/JEFF3.1.1 Monte Carlo code
Blaise, P.; Colomba, A.
2012-07-01
The present work details the first analysis of the 3D void phase conducted during the EPICURE/UM17x17/7% mixed UOX/MOX configuration. This configuration is composed of a homogeneous central 17x17 MOX-7% assembly, surrounded by portions of 17x17 1102 assemblies with guide-tubes. The void bubble is modelled by a small waterproof 5x5 fuel pin parallelepiped box of 11 cm height, placed in the centre of the MOX assembly. This bubble, initially placed at the core mid-plane, is then moved in different axial positions to study the evolution in the core of the axial perturbation. Then, to simulate the growing of this bubble in order to understand the effects of increased void fraction along the fuel pin, 3 and 5 bubbles have been stacked axially, from the core mid-plane. The C/E comparison obtained with the Monte Carlo code Tripoli4 for both radial and axial fission rate distributions, and in particular the reproduction of the very important flux gradients at the void/water interfaces, changing as the bubble is displaced along the z-axis are very satisfactory. It demonstrates both the capability of the code and its library to reproduce this kind of situation, as the very good quality of the experimental results, confirming the UM-17x17 as an excellent experimental benchmark for 3D code validation. This work has been performed within the frame of the V and V program for the future APOLL03 deterministic code of CEA starting in 2012, and its V and V benchmarking database. (authors)
Adamson, Justus; Newton, Joseph; Yang, Yun; Steffey, Beverly; Cai, Jing; Adamovics, John; Oldham, Mark; Chino, Junzo; Craciunescu, Oana
2012-01-01
Purpose: To determine the geometric and dose attenuation characteristics of a new commercially available CT-compatible LDR tandem and ovoid (T&O) applicator using Monte Carlo calculation and 3D dosimetry. Methods: For geometric characterization, we quantified physical dimensions and investigated a systematic difference found to exist between nominal ovoid angle and the angle at which the afterloading buckets fall within the ovoid. For dosimetric characterization, we determined source attenuation through asymmetric gold shielding in the buckets using Monte Carlo simulations and 3D dosimetry. Monte Carlo code MCNP5 was used to simulate 1.5 × 109 photon histories from a 137Cs source placed in the bucket to achieve statistical uncertainty of 1% at a 6 cm distance. For 3D dosimetry, the distribution about an unshielded source was first measured to evaluate the system for 137Cs, after which the distribution was measured about sources placed in each bucket. Cylindrical PRESAGE® dosimeters (9.5 cm diameter, 9.2 cm height) with a central channel bored for source placement were supplied by Heuris Inc. The dosimeters were scanned with the Duke Large field of view Optical CT-Scanner before and after delivering a nominal dose at 1 cm of 5–8 Gy. During irradiation the dosimeter was placed in a water phantom to provide backscatter. Optical CT scan time lasted 15 min during which 720 projections were acquired at 0.5° increments, and a 3D distribution was reconstructed with a (0.05 cm)3 isotropic voxel size. The distributions about the buckets were used to calculate a 3D distribution of transmission rate through the bucket, which was applied to a clinical CT-based T&O implant plan. Results: The systematic difference in bucket angle relative to the nominal ovoid angle (105°) was 3.1°–4.7°. A systematic difference in bucket angle of 1°, 5°, and 10° caused a 1% ± 0.1%, 1.7% ± 0.4%, and 2.6% ± 0.7% increase in rectal dose, respectively, with smaller effect to dose to
Adamson, Justus; Newton, Joseph; Yang Yun; Steffey, Beverly; Cai, Jing; Adamovics, John; Oldham, Mark; Chino, Junzo; Craciunescu, Oana
2012-07-15
Purpose: To determine the geometric and dose attenuation characteristics of a new commercially available CT-compatible LDR tandem and ovoid (T and O) applicator using Monte Carlo calculation and 3D dosimetry. Methods: For geometric characterization, we quantified physical dimensions and investigated a systematic difference found to exist between nominal ovoid angle and the angle at which the afterloading buckets fall within the ovoid. For dosimetric characterization, we determined source attenuation through asymmetric gold shielding in the buckets using Monte Carlo simulations and 3D dosimetry. Monte Carlo code MCNP5 was used to simulate 1.5 Multiplication-Sign 10{sup 9} photon histories from a {sup 137}Cs source placed in the bucket to achieve statistical uncertainty of 1% at a 6 cm distance. For 3D dosimetry, the distribution about an unshielded source was first measured to evaluate the system for {sup 137}Cs, after which the distribution was measured about sources placed in each bucket. Cylindrical PRESAGE{sup Registered-Sign} dosimeters (9.5 cm diameter, 9.2 cm height) with a central channel bored for source placement were supplied by Heuris Inc. The dosimeters were scanned with the Duke Large field of view Optical CT-Scanner before and after delivering a nominal dose at 1 cm of 5-8 Gy. During irradiation the dosimeter was placed in a water phantom to provide backscatter. Optical CT scan time lasted 15 min during which 720 projections were acquired at 0.5 Degree-Sign increments, and a 3D distribution was reconstructed with a (0.05 cm){sup 3} isotropic voxel size. The distributions about the buckets were used to calculate a 3D distribution of transmission rate through the bucket, which was applied to a clinical CT-based T and O implant plan. Results: The systematic difference in bucket angle relative to the nominal ovoid angle (105 Degree-Sign ) was 3.1 Degree-Sign -4.7 Degree-Sign . A systematic difference in bucket angle of 1 Degree-Sign , 5 Degree-Sign , and
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
NASA Astrophysics Data System (ADS)
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.
Ilić, Radovan D; Spasić-Jokić, Vesna; Belicev, Petar; Dragović, 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. PMID:15798273
NASA Technical Reports Server (NTRS)
Langmore, Ian; Davis, Anthony B.; Bal, Guillaume; Marzouk, Youssef M.
2012-01-01
We describe a method for accelerating a 3D Monte Carlo forward radiative transfer model to the point where it can be used in a new kind of Bayesian retrieval framework. The remote sensing challenge is to detect and quantify a chemical effluent of a known absorbing gas produced by an industrial facility in a deep valley. The available data is a single low resolution noisy image of the scene in the near IR at an absorbing wavelength for the gas of interest. The detected sunlight has been multiply reflected by the variable terrain and/or scattered by an aerosol that is assumed partially known and partially unknown. We thus introduce a new class of remote sensing algorithms best described as "multi-pixel" techniques that call necessarily for a 3D radaitive transfer model (but demonstrated here in 2D); they can be added to conventional ones that exploit typically multi- or hyper-spectral data, sometimes with multi-angle capability, with or without information about polarization. The novel Bayesian inference methodology uses adaptively, with efficiency in mind, the fact that a Monte Carlo forward model has a known and controllable uncertainty depending on the number of sun-to-detector paths used.
NASA Astrophysics Data System (ADS)
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
Uncertainty analysis of penicillin V production using Monte Carlo simulation.
Biwer, Arno; Griffith, Steve; Cooney, Charles
2005-04-20
Uncertainty and variability affect economic and environmental performance in the production of biotechnology and pharmaceutical products. However, commercial process simulation software typically provides analysis that assumes deterministic rather than stochastic process parameters and thus is not capable of dealing with the complexities created by variance that arise in the decision-making process. Using the production of penicillin V as a case study, this article shows how uncertainty can be quantified and evaluated. The first step is construction of a process model, as well as analysis of its cost structure and environmental impact. The second step is identification of uncertain variables and determination of their probability distributions based on available process and literature data. Finally, Monte Carlo simulations are run to see how these uncertainties propagate through the model and affect key economic and environmental outcomes. Thus, the overall variation of these objective functions are quantified, the technical, supply chain, and market parameters that contribute most to the existing variance are identified and the differences between economic and ecological evaluation are analyzed. In our case study analysis, we show that final penicillin and biomass concentrations in the fermenter have the highest contribution to variance for both unit production cost and environmental impact. The penicillin selling price dominates return on investment variance as well as the variance for other revenue-dependent parameters. PMID:15742389
Development of a randomized 3D cell model for Monte Carlo microdosimetry simulations
Douglass, Michael; Bezak, Eva; Penfold, Scott
2012-06-15
Purpose: The objective of the current work was to develop an algorithm for growing a macroscopic tumor volume from individual randomized quasi-realistic cells. The major physical and chemical components of the cell need to be modeled. It is intended to import the tumor volume into GEANT4 (and potentially other Monte Carlo packages) to simulate ionization events within the cell regions. Methods: A MATLAB Copyright-Sign code was developed to produce a tumor coordinate system consisting of individual ellipsoidal cells randomized in their spatial coordinates, sizes, and rotations. An eigenvalue method using a mathematical equation to represent individual cells was used to detect overlapping cells. GEANT4 code was then developed to import the coordinate system into GEANT4 and populate it with individual cells of varying sizes and composed of the membrane, cytoplasm, reticulum, nucleus, and nucleolus. Each region is composed of chemically realistic materials. Results: The in-house developed MATLAB Copyright-Sign code was able to grow semi-realistic cell distributions ({approx}2 Multiplication-Sign 10{sup 8} cells in 1 cm{sup 3}) in under 36 h. The cell distribution can be used in any number of Monte Carlo particle tracking toolkits including GEANT4, which has been demonstrated in this work. Conclusions: Using the cell distribution and GEANT4, the authors were able to simulate ionization events in the individual cell components resulting from 80 keV gamma radiation (the code is applicable to other particles and a wide range of energies). This virtual microdosimetry tool will allow for a more complete picture of cell damage to be developed.
NASA Astrophysics Data System (ADS)
Schiettekatte, François; Chicoine, Martin
2016-03-01
Corteo is a program that implements Monte Carlo (MC) method to simulate ion beam analysis (IBA) spectra of several techniques by following the ions trajectory until a sufficiently large fraction of them reach the detector to generate a spectrum. Hence, it fully accounts for effects such as multiple scattering (MS). Here, a version of Corteo is presented where the target can be a 2D or 3D image. This image can be derived from micrographs where the different compounds are identified, therefore bringing extra information into the solution of an IBA spectrum, and potentially significantly constraining the solution. The image intrinsically includes many details such as the actual surface or interfacial roughness, or actual nanostructures shape and distribution. This can for example lead to the unambiguous identification of structures stoichiometry in a layer, or at least to better constraints on their composition. Because MC computes in details the trajectory of the ions, it simulates accurately many of its aspects such as ions coming back into the target after leaving it (re-entry), as well as going through a variety of nanostructures shapes and orientations. We show how, for example, as the ions angle of incidence becomes shallower than the inclination distribution of a rough surface, this process tends to make the effective roughness smaller in a comparable 1D simulation (i.e. narrower thickness distribution in a comparable slab simulation). Also, in ordered nanostructures, target re-entry can lead to replications of a peak in a spectrum. In addition, bitmap description of the target can be used to simulate depth profiles such as those resulting from ion implantation, diffusion, and intermixing. Other improvements to Corteo include the possibility to interpolate the cross-section in angle-energy tables, and the generation of energy-depth maps.
Time series analysis of Monte Carlo neutron transport calculations
NASA Astrophysics Data System (ADS)
Nease, Brian Robert
A time series based approach is applied to the Monte Carlo (MC) fission source distribution to calculate the non-fundamental mode eigenvalues of the system. The approach applies Principal Oscillation Patterns (POPs) to the fission source distribution, transforming the problem into a simple autoregressive order one (AR(1)) process. Proof is provided that the stationary MC process is linear to first order approximation, which is a requirement for the application of POPs. The autocorrelation coefficient of the resulting AR(1) process corresponds to the ratio of the desired mode eigenvalue to the fundamental mode eigenvalue. All modern k-eigenvalue MC codes calculate the fundamental mode eigenvalue, so the desired mode eigenvalue can be easily determined. The strength of this approach is contrasted against the Fission Matrix method (FMM) in terms of accuracy versus computer memory constraints. Multi-dimensional problems are considered since the approach has strong potential for use in reactor analysis, and the implementation of the method into production codes is discussed. Lastly, the appearance of complex eigenvalues is investigated and solutions are provided.
Fast Monte Carlo for ion beam analysis simulations
NASA Astrophysics Data System (ADS)
Schiettekatte, François
2008-04-01
A Monte Carlo program for the simulation of ion beam analysis data is presented. It combines mainly four features: (i) ion slowdown is computed separately from the main scattering/recoil event, which is directed towards the detector. (ii) A virtual detector, that is, a detector larger than the actual one can be used, followed by trajectory correction. (iii) For each collision during ion slowdown, scattering angle components are extracted form tables. (iv) Tables of scattering angle components, stopping power and energy straggling are indexed using the binary representation of floating point numbers, which allows logarithmic distribution of these tables without the computation of logarithms to access them. Tables are sufficiently fine-grained that interpolation is not necessary. Ion slowdown computation thus avoids trigonometric, inverse and transcendental function calls and, as much as possible, divisions. All these improvements make possible the computation of 107 collisions/s on current PCs. Results for transmitted ions of several masses in various substrates are well comparable to those obtained using SRIM-2006 in terms of both angular and energy distributions, as long as a sufficiently large number of collisions is considered for each ion. Examples of simulated spectrum show good agreement with experimental data, although a large detector rather than the virtual detector has to be used to properly simulate background signals that are due to plural collisions. The program, written in standard C, is open-source and distributed under the terms of the GNU General Public License.
Monte Carlo analysis of localization errors in magnetoencephalography
Medvick, P.A.; Lewis, P.S.; Aine, C.; Flynn, E.R.
1989-01-01
In magnetoencephalography (MEG), the magnetic fields created by electrical activity in the brain are measured on the surface of the skull. To determine the location of the activity, the measured field is fit to an assumed source generator model, such as a current dipole, by minimizing chi-square. For current dipoles and other nonlinear source models, the fit is performed by an iterative least squares procedure such as the Levenberg-Marquardt algorithm. Once the fit has been computed, analysis of the resulting value of chi-square can determine whether the assumed source model is adequate to account for the measurements. If the source model is adequate, then the effect of measurement error on the fitted model parameters must be analyzed. Although these kinds of simulation studies can provide a rough idea of the effect that measurement error can be expected to have on source localization, they cannot provide detailed enough information to determine the effects that the errors in a particular measurement situation will produce. In this work, we introduce and describe the use of Monte Carlo-based techniques to analyze model fitting errors for real data. Given the details of the measurement setup and a statistical description of the measurement errors, these techniques determine the effects the errors have on the fitted model parameters. The effects can then be summarized in various ways such as parameter variances/covariances or multidimensional confidence regions. 8 refs., 3 figs.
Ahmad, Rizwan; Deng, Yuanmu; Vikram, Deepti S.; Clymer, Bradley; Srinivasan, Parthasarathy; Zweier, Jay L.; Kuppusamy, Periannan
2007-01-01
In continuous wave (CW) electron paramagnetic resonance imaging (EPRI), high quality of reconstructed image along with fast and reliable data acquisition is highly desirable for many biological applications. An accurate representation of uniform distribution of projection data is necessary to ensure high reconstruction quality. The current techniques for data acquisition suffer from nonuniformities or local anisotropies in the distribution of projection data and present a poor approximation of a true uniform and isotropic distribution. In this work, we have implemented a technique based on Quasi-Monte Carlo method to acquire projections with more uniform and isotropic distribution of data over a 3D acquisition space. The proposed technique exhibits improvements in the reconstruction quality in terms of both mean-square-error and visual judgment. The effectiveness of the suggested technique is demonstrated using computer simulations and 3D EPRI experiments. The technique is robust and exhibits consistent performance for different object configurations and orientations. PMID:17095271
NASA Astrophysics Data System (ADS)
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 <=5.5 cm2 and 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.
Monte-Carlo Application for Nondestructive Nuclear Waste Analysis
NASA Astrophysics Data System (ADS)
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
Algebraic Monte Carlo precedure reduces statistical analysis time and cost factors
NASA Technical Reports Server (NTRS)
Africano, R. C.; Logsdon, T. S.
1967-01-01
Algebraic Monte Carlo procedure statistically analyzes performance parameters in large, complex systems. The individual effects of input variables can be isolated and individual input statistics can be changed without having to repeat the entire analysis.
Hydrogen analysis depth calibration by CORTEO Monte-Carlo simulation
NASA Astrophysics Data System (ADS)
Moser, M.; Reichart, P.; Bergmaier, A.; Greubel, C.; Schiettekatte, F.; Dollinger, G.
2016-03-01
Hydrogen imaging with sub-μm lateral resolution and sub-ppm sensitivity has become possible with coincident proton-proton (pp) scattering analysis (Reichart et al., 2004). Depth information is evaluated from the energy sum signal with respect to energy loss of both protons on their path through the sample. In first order, there is no angular dependence due to elastic scattering. In second order, a path length effect due to different energy loss on the paths of the protons causes an angular dependence of the energy sum. Therefore, the energy sum signal has to be de-convoluted depending on the matrix composition, i.e. mainly the atomic number Z, in order to get a depth calibrated hydrogen profile. Although the path effect can be calculated analytically in first order, multiple scattering effects lead to significant deviations in the depth profile. Hence, in our new approach, we use the CORTEO Monte-Carlo code (Schiettekatte, 2008) in order to calculate the depth of a coincidence event depending on the scattering angle. The code takes individual detector geometry into account. In this paper we show, that the code correctly reproduces measured pp-scattering energy spectra with roughness effects considered. With more than 100 μm thick Mylar-sandwich targets (Si, Fe, Ge) we demonstrate the deconvolution of the energy spectra on our current multistrip detector at the microprobe SNAKE at the Munich tandem accelerator lab. As a result, hydrogen profiles can be evaluated with an accuracy in depth of about 1% of the sample thickness.
Brown, F.B.; Sutton, T.M.
1996-02-01
This report is composed of the lecture notes from the first half of a 32-hour graduate-level course on Monte Carlo methods offered at KAPL. These notes, prepared by two of the principle developers of KAPL`s RACER Monte Carlo code, cover the fundamental theory, concepts, and practices for Monte Carlo analysis. In particular, a thorough grounding in the basic fundamentals of Monte Carlo methods is presented, including random number generation, random sampling, the Monte Carlo approach to solving transport problems, computational geometry, collision physics, tallies, and eigenvalue calculations. Furthermore, modern computational algorithms for vector and parallel approaches to Monte Carlo calculations are covered in detail, including fundamental parallel and vector concepts, the event-based algorithm, master/slave schemes, parallel scaling laws, and portability issues.
Benchmark of Atucha-2 PHWR RELAP5-3D control rod model by Monte Carlo MCNP5 core calculation
Pecchia, M.; D'Auria, F.; Mazzantini, O.
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)
Analytical band Monte Carlo analysis of electron transport in silicene
NASA Astrophysics Data System (ADS)
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.
Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept
NASA Technical Reports Server (NTRS)
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.
Comparison of basis functions for 3D PET reconstruction using a Monte Carlo system matrix
NASA Astrophysics Data System (ADS)
Cabello, Jorge; Rafecas, Magdalena
2012-04-01
In emission tomography, iterative statistical methods are accepted as the reconstruction algorithms that achieve the best image quality. The accuracy of these methods relies partly on the quality of the system response matrix (SRM) that characterizes the scanner. The more physical phenomena included in the SRM, the higher the SRM quality, and therefore higher image quality is obtained from the reconstruction process. High-resolution small animal scanners contain as many as 103-104 small crystal pairs, while the field of view (FOV) is divided into hundreds of thousands of small voxels. These two characteristics have a significant impact on the number of elements to be calculated in the SRM. Monte Carlo (MC) methods have gained popularity as a way of calculating the SRM, due to the increased accuracy achievable, at the cost of introducing some statistical noise and long simulation times. In the work presented here the SRM is calculated using MC methods exploiting the cylindrical symmetries of the scanner, significantly reducing the simulation time necessary to calculate a high statistical quality SRM and the storage space necessary. The use of cylindrical symmetries makes polar voxels a convenient basis function. Alternatively, spherically symmetric basis functions result in improved noise properties compared to cubic and polar basis functions. The quality of reconstructed images using polar voxels, spherically symmetric basis functions on a polar grid, cubic voxels and post-reconstruction filtered polar and cubic voxels is compared from a noise and spatial resolution perspective. This study demonstrates that polar voxels perform as well as cubic voxels, reducing the simulation time necessary to calculate the SRM and the disk space necessary to store it. Results showed that spherically symmetric functions outperform polar and cubic basis functions in terms of noise properties, at the cost of slightly degraded spatial resolution, larger SRM file size and longer
NASA Astrophysics Data System (ADS)
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
Feasibility of a Monte Carlo-deterministic hybrid method for fast reactor analysis
Heo, W.; Kim, W.; Kim, Y.; Yun, S.
2013-07-01
A Monte Carlo and deterministic hybrid method is investigated for the analysis of fast reactors in this paper. Effective multi-group cross sections data are generated using a collision estimator in the MCNP5. A high order Legendre scattering cross section data generation module was added into the MCNP5 code. Both cross section data generated from MCNP5 and TRANSX/TWODANT using the homogeneous core model were compared, and were applied to DIF3D code for fast reactor core analysis of a 300 MWe SFR TRU burner core. For this analysis, 9 groups macroscopic-wise data was used. In this paper, a hybrid calculation MCNP5/DIF3D was used to analyze the core model. The cross section data was generated using MCNP5. The k{sub eff} and core power distribution were calculated using the 54 triangle FDM code DIF3D. A whole core calculation of the heterogeneous core model using the MCNP5 was selected as a reference. In terms of the k{sub eff}, 9-group MCNP5/DIF3D has a discrepancy of -154 pcm from the reference solution, 9-group TRANSX/TWODANT/DIF3D analysis gives -1070 pcm discrepancy. (authors)
pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis
NASA Astrophysics Data System (ADS)
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.
Nakaguchi, Yuji; Ono, Takeshi; Maruyama, Masato; Nagasue, Nozomu; Shimohigashi, Yoshinobu; Kai, Yudai
2015-01-01
In this study, we evaluated the performance of a three-dimensional (3D) dose verification system, COMPASS version 3, which has a dedicated beam models and dose calculation engine. It was possible to reconstruct the 3D dose distributions in patient anatomy based on the measured fluence using the MatriXX 2D array. The COMPASS system was compared with Monte Carlo simulation (MC), glass rod dosimeter (GRD), and 3DVH, using an anthropomorphic phantom for intensity-modulated radiation therapy (IMRT) dose verification in clinical neck cases. The GRD measurements agreed with the MC within 5% at most measurement points. In addition, most points for COMPASS and 3DVH also agreed with the MC within 5%. The COMPASS system showed better results than 3DVH for dose profiles due to individual adjustments, such as beam modeling for each linac. Regarding the dose-volume histograms, there were no large differences between MC, analytical anisotropic algorithm (AAA) in Eclipse treatment planning system (TPS), 3DVH, and the COMPASS system. However, AAA underestimated the dose to the clinical target volume and Rt-Parotid slightly. This is because AAA has some problems with dose calculation accuracy. Our results indicated that the COMPASS system offers highly accurate 3D dose calculation for clinical IMRT quality assurance. Also, the COMPASS system will be useful as a commissioning tool in routine clinical practice for TPS. PMID:25679177
Active neutron multiplicity analysis and Monte Carlo calculations
NASA Astrophysics Data System (ADS)
Krick, M. S.; Ensslin, N.; Langner, D. G.; Miller, M. C.; Siebelist, R.; Stewart, J. E.; Ceo, R. N.; May, P. K.; Collins, L. L., Jr.
Active neutron multiplicity measurements of high-enrichment uranium metal and oxide samples have been made at Los Alamos and Y-12. The data from the measurements of standards at Los Alamos were analyzed to obtain values for neutron multiplication and source-sample coupling. These results are compared to equivalent results obtained from Monte Carlo calculations. An approximate relationship between coupling and multiplication is derived and used to correct doubles rates for multiplication and coupling. The utility of singles counting for uranium samples is also examined.
Analysis of real-time networks with monte carlo methods
NASA Astrophysics Data System (ADS)
Mauclair, C.; Durrieu, G.
2013-12-01
Communication networks in embedded systems are ever more large and complex. A better understanding of the dynamics of these networks is necessary to use them at best and lower costs. Todays tools are able to compute upper bounds of end-to-end delays that a packet being sent through the network could suffer. However, in the case of asynchronous networks, those worst end-to-end delay (WEED) cases are rarely observed in practice or through simulations due to the scarce situations that lead to worst case scenarios. A novel approach based on Monte Carlo methods is suggested to study the effects of the asynchrony on the performances.
Li, Yong Gang; Yang, Yang; Short, Michael P.; Ding, Ze Jun; Zeng, Zhi; Li, Ju
2015-01-01
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. PMID:26658477
NASA Astrophysics Data System (ADS)
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.
An Advanced Neutronic Analysis Toolkit with Inline Monte Carlo capability for BHTR Analysis
William R. Martin; John C. Lee
2009-12-30
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.
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
POWER ANALYSIS FOR COMPLEX MEDIATIONAL DESIGNS USING MONTE CARLO METHODS
Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.
2013-01-01
Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex mediational models. The approach is based on the well known technique of generating a large number of samples in a Monte Carlo study, and estimating power as the percentage of cases in which an estimate of interest is significantly different from zero. Examples of power calculation for commonly used mediational models are provided. Power analyses for the single mediator, multiple mediators, three-path mediation, mediation with latent variables, moderated mediation, and mediation in longitudinal designs are described. Annotated sample syntax for Mplus is appended and tabled values of required sample sizes are shown for some models. PMID:23935262
Li, Ming; Kang, Zhan; Huang, Xiaobo
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.
NASA Astrophysics Data System (ADS)
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.
3D polymer gel dosimetry and Geant4 Monte Carlo characterization of novel needle based X-ray source
NASA Astrophysics Data System (ADS)
Liu, Y.; Sozontov, E.; Safronov, V.; Gutman, G.; Strumban, E.; Jiang, Q.; Li, S.
2010-11-01
In the recent years, there have been a few attempts to develop a low energy x-ray radiation sources alternative to conventional radioisotopes used in brachytherapy. So far, all efforts have been centered around the intent to design an interstitial miniaturized x-ray tube. Though direct irradiation of tumors looks very promising, the known insertable miniature x-ray tubes have many limitations: (a) difficulties with focusing and steering the electron beam to the target; (b)necessity to cool the target to increase x-ray production efficiency; (c)impracticability to reduce the diameter of the miniaturized x-ray tube below 4mm (the requirement to decrease the diameter of the x-ray tube and the need to have a cooling system for the target have are mutually exclusive); (c) significant limitations in changing shape and energy of the emitted radiation. The specific aim of this study is to demonstrate the feasibility of a new concept for an insertable low-energy needle x-ray device based on simulation with Geant4 Monte Carlo code and to measure the dose rate distribution for low energy (17.5 keV) x-ray radiation with the 3D polymer gel dosimetry.
A study of the earth radiation budget using a 3D Monte-Carlo radiative transer code
NASA Astrophysics Data System (ADS)
Okata, M.; Nakajima, T.; Sato, Y.; Inoue, T.; Donovan, D. P.
2013-12-01
The purpose of this study is to evaluate the earth's radiation budget when data are available from satellite-borne active sensors, i.e. cloud profiling radar (CPR) and lidar, and a multi-spectral imager (MSI) in the project of the Earth Explorer/EarthCARE mission. For this purpose, we first developed forward and backward 3D Monte Carlo radiative transfer codes that can treat a broadband solar flux calculation including thermal infrared emission calculation by k-distribution parameters of Sekiguchi and Nakajima (2008). In order to construct the 3D cloud field, we tried the following three methods: 1) stochastic cloud generated by randomized optical thickness each layer distribution and regularly-distributed tilted clouds, 2) numerical simulations by a non-hydrostatic model with bin cloud microphysics model and 3) Minimum cloud Information Deviation Profiling Method (MIDPM) as explained later. As for the method-2 (numerical modeling method), we employed numerical simulation results of Californian summer stratus clouds simulated by a non-hydrostatic atmospheric model with a bin-type cloud microphysics model based on the JMA NHM model (Iguchi et al., 2008; Sato et al., 2009, 2012) with horizontal (vertical) grid spacing of 100m (20m) and 300m (20m) in a domain of 30km (x), 30km (y), 1.5km (z) and with a horizontally periodic lateral boundary condition. Two different cell systems were simulated depending on the cloud condensation nuclei (CCN) concentration. In the case of horizontal resolution of 100m, regionally averaged cloud optical thickness,
Discrete ordinates-Monte Carlo coupling: A comparison of techniques in NERVA radiation analysis
NASA Technical Reports Server (NTRS)
Lindstrom, D. G.; Normand, E.; Wilcox, A. D.
1972-01-01
In the radiation analysis of the NERVA nuclear rocket system, two-dimensional discrete ordinates calculations are sufficient to provide detail in the pressure vessel and reactor assembly. Other parts of the system, however, require three-dimensional Monte Carlo analyses. To use these two methods in a single analysis, a means of coupling was developed whereby the results of a discrete ordinates calculation can be used to produce source data for a Monte Carlo calculation. Several techniques for producing source detail were investigated. Results of calculations on the NERVA system are compared and limitations and advantages of the coupling techniques discussed.
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
A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
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…
A Monte Carlo Study of Recovery of Weak Factor Loadings in Confirmatory Factor Analysis
ERIC Educational Resources Information Center
Ximenez, Carmen
2006-01-01
The recovery of weak factors has been extensively studied in the context of exploratory factor analysis. This article presents the results of a Monte Carlo simulation study of recovery of weak factor loadings in confirmatory factor analysis under conditions of estimation method (maximum likelihood vs. unweighted least squares), sample size,…
Taxometrics, Polytomous Constructs, and the Comparison Curve Fit Index: A Monte Carlo Analysis
ERIC Educational Resources Information Center
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…
Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Analysis
NASA Technical Reports Server (NTRS)
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.
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.
The Null Space Monte Carlo Uncertainty Analysis of Heterogeneity for Preferential Flow Simulation
NASA Astrophysics Data System (ADS)
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.
Uncertainty Analysis of Power Grid Investment Capacity Based on Monte Carlo
NASA Astrophysics Data System (ADS)
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.
Monte Carlo verification of point kinetics for safety analysis of nuclear reactors
Valentine, T.E.; Mihalczo, J.T.
1995-06-01
Monte Carlo neutron transport methods can be used to verify the applicability of point kinetics for safety analysis of nuclear reactors. KENO-NR was used to obtain the transfer function of the Advanced Neutron Source reactor and the time delay between the core power production and the external detectors, a parameter of interest to the safety systems design. The good agreement between the Monte Carlo generated transfer function and the point kinetics transfer function validates that the uncommon ANS geometry does not preclude the use of point kinetics in the frequency range that was investigated. Various features of the power spectral densities also demonstrated the applicability of point kinetics. The time delay was obtained from the cross-power spectral density (CPSD) and is {approximately}15 ms. These analyses show that frequency analysis can be used experimentally to investigate the validity of the use of point kinetics models in critical experiments or zero power testing of reactors.
Stability analysis and time-step limits for a Monte Carlo Compton-scattering method
Densmore, Jeffery D. Warsa, James S. Lowrie, Robert B.
2010-05-20
A Monte Carlo method for simulating Compton scattering in high energy density applications has been presented that models the photon-electron collision kinematics exactly [E. Canfield, W.M. Howard, E.P. Liang, Inverse Comptonization by one-dimensional relativistic electrons, Astrophys. J. 323 (1987) 565]. However, implementing this technique typically requires an explicit evaluation of the material temperature, which can lead to unstable and oscillatory solutions. In this paper, we perform a stability analysis of this Monte Carlo method and develop two time-step limits that avoid undesirable behavior. The first time-step limit prevents instabilities, while the second, more restrictive time-step limit avoids both instabilities and nonphysical oscillations. With a set of numerical examples, we demonstrate the efficacy of these time-step limits.
Monte Carlo analysis of voxel resolution of off-axially distributed image sensing system
NASA Astrophysics Data System (ADS)
Zhang, Miao; Piao, Yongri; Cho, Myungjin
2016-03-01
In this paper, we present a generalization framework to analyze the effect of voxel resolution on Monte Carlo simulation for off-axially distributed image sensing (ODIS) system under fixed resource constraints. Our framework can evaluate the performance of ODIS systems based on various sensing parameters such as the slanted angle between the optical axis and the moving direction, the number of cameras, the pixel size, the distance between the optical axis and the point source plane and so on. We carry out Monte Carlo simulations based on this framework to evaluate ODIS system performance as a function of sensing parameters. To the best of our knowledge, this is the first report on quantitative analysis of ODIS systems under fixed resource constraints.
Monte Carlo Analysis as a Trajectory Design Driver for the TESS Mission
NASA Technical Reports Server (NTRS)
Nickel, Craig; Lebois, Ryan; Lutz, Stephen; Dichmann, Donald; Parker, Joel
2016-01-01
The Transiting Exoplanet Survey Satellite (TESS) will be injected into a highly eccentric Earth orbit and fly 3.5 phasing loops followed by a lunar flyby to enter a mission orbit with lunar 2:1 resonance. Through the phasing loops and mission orbit, the trajectory is significantly affected by lunar and solar gravity. We have developed a trajectory design to achieve the mission orbit and meet mission constraints, including eclipse avoidance and a 30-year geostationary orbit avoidance requirement. A parallelized Monte Carlo simulation was performed to validate the trajectory after injecting common perturbations, including launch dispersions, orbit determination errors, and maneuver execution errors. The Monte Carlo analysis helped identify mission risks and is used in the trajectory selection process.
O'Brien, M J; Procassini, R J; Joy, K I
2009-03-09
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.
Time Series Analysis of Monte Carlo Fission Sources - I: Dominance Ratio Computation
Ueki, Taro; Brown, Forrest B.; Parsons, D. Kent; Warsa, James S.
2004-11-15
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.
NASA Astrophysics Data System (ADS)
Hara, Shotaro; Ohi, Akihiro; Shikazono, Naoki
2015-02-01
Since sintering of sub-micron-sized particles is a critical phenomenon affecting the electrochemical performance and reliability of solid oxide fuel cell systems, a better understanding of this microstructure-related process is of great importance. In this study, we show that kinetic Potts Monte Carlo modeling is capable of quantitatively predicting the three-dimensional (3D) microstructure evolution over an entire stage of nickel sintering at the sub-micron scale. This is achieved through direct comparison of simulation results and 3D microstructural analysis using focused ion beam-scanning electron microscopy. We show that grain boundary diffusion is the dominant mechanism on densification, while surface diffusion has an impact on the coarsening during sub-micron scale sintering, only acting as one of the multiple mechanisms of sintering.
Use of the FLUKA Monte Carlo code for 3D patient-specific dosimetry on PET-CT and SPECT-CT images
NASA Astrophysics Data System (ADS)
Botta, F.; Mairani, A.; Hobbs, R. F.; Vergara Gil, A.; Pacilio, M.; Parodi, K.; Cremonesi, M.; Coca Pérez, M. A.; Di Dia, A.; Ferrari, M.; Guerriero, F.; Battistoni, G.; Pedroli, G.; Paganelli, G.; Torres Aroche, L. A.; Sgouros, G.
2013-11-01
Patient-specific absorbed dose calculation for nuclear medicine therapy is a topic of increasing interest. 3D dosimetry at the voxel level is one of the major improvements for the development of more accurate calculation techniques, as compared to the standard dosimetry at the organ level. This study aims to use the FLUKA Monte Carlo code to perform patient-specific 3D dosimetry through direct Monte Carlo simulation on PET-CT and SPECT-CT images. To this aim, dedicated routines were developed in the FLUKA environment. Two sets of simulations were performed on model and phantom images. Firstly, the correct handling of PET and SPECT images was tested under the assumption of homogeneous water medium by comparing FLUKA results with those obtained with the voxel kernel convolution method and with other Monte Carlo-based tools developed to the same purpose (the EGS-based 3D-RD software and the MCNP5-based MCID). Afterwards, the correct integration of the PET/SPECT and CT information was tested, performing direct simulations on PET/CT images for both homogeneous (water) and non-homogeneous (water with air, lung and bone inserts) phantoms. Comparison was performed with the other Monte Carlo tools performing direct simulation as well. The absorbed dose maps were compared at the voxel level. In the case of homogeneous water, by simulating 108 primary particles a 2% average difference with respect to the kernel convolution method was achieved; such difference was lower than the statistical uncertainty affecting the FLUKA results. The agreement with the other tools was within 3-4%, partially ascribable to the differences among the simulation algorithms. Including the CT-based density map, the average difference was always within 4% irrespective of the medium (water, air, bone), except for a maximum 6% value when comparing FLUKA and 3D-RD in air. The results confirmed that the routines were properly developed, opening the way for the use of FLUKA for patient-specific, image
Use of the FLUKA Monte Carlo code for 3D patient-specific dosimetry on PET-CT and SPECT-CT images*
Botta, F; Mairani, A; Hobbs, R F; Vergara Gil, A; Pacilio, M; Parodi, K; Cremonesi, M; Coca Pérez, M A; Di Dia, A; Ferrari, M; Guerriero, F; Battistoni, G; Pedroli, G; Paganelli, G; Torres Aroche, L A; Sgouros, G
2014-01-01
Patient-specific absorbed dose calculation for nuclear medicine therapy is a topic of increasing interest. 3D dosimetry at the voxel level is one of the major improvements for the development of more accurate calculation techniques, as compared to the standard dosimetry at the organ level. This study aims to use the FLUKA Monte Carlo code to perform patient-specific 3D dosimetry through direct Monte Carlo simulation on PET-CT and SPECT-CT images. To this aim, dedicated routines were developed in the FLUKA environment. Two sets of simulations were performed on model and phantom images. Firstly, the correct handling of PET and SPECT images was tested under the assumption of homogeneous water medium by comparing FLUKA results with those obtained with the voxel kernel convolution method and with other Monte Carlo-based tools developed to the same purpose (the EGS-based 3D-RD software and the MCNP5-based MCID). Afterwards, the correct integration of the PET/SPECT and CT information was tested, performing direct simulations on PET/CT images for both homogeneous (water) and non-homogeneous (water with air, lung and bone inserts) phantoms. Comparison was performed with the other Monte Carlo tools performing direct simulation as well. The absorbed dose maps were compared at the voxel level. In the case of homogeneous water, by simulating 108 primary particles a 2% average difference with respect to the kernel convolution method was achieved; such difference was lower than the statistical uncertainty affecting the FLUKA results. The agreement with the other tools was within 3–4%, partially ascribable to the differences among the simulation algorithms. Including the CT-based density map, the average difference was always within 4% irrespective of the medium (water, air, bone), except for a maximum 6% value when comparing FLUKA and 3D-RD in air. The results confirmed that the routines were properly developed, opening the way for the use of FLUKA for patient-specific, image
MC21 analysis of the nuclear energy agency Monte Carlo performance benchmark problem
Kelly, D. J.; Sutton, T. M.; Wilson, S. C.
2012-07-01
Due to the steadily decreasing cost and wider availability of large scale computing platforms, there is growing interest in the prospects for the use of Monte Carlo for reactor design calculations that are currently performed using few-group diffusion theory or other low-order methods. To facilitate the monitoring of the progress being made toward the goal of practical full-core reactor design calculations using Monte Carlo, a performance benchmark has been developed and made available through the Nuclear Energy Agency. A first analysis of this benchmark using the MC21 Monte Carlo code was reported on in 2010, and several practical difficulties were highlighted. In this paper, a newer version of MC21 that addresses some of these difficulties has been applied to the benchmark. In particular, the confidence-interval-determination method has been improved to eliminate source correlation bias, and a fission-source-weighting method has been implemented to provide a more uniform distribution of statistical uncertainties. In addition, the Forward-Weighted, Consistent-Adjoint-Driven Importance Sampling methodology has been applied to the benchmark problem. Results of several analyses using these methods are presented, as well as results from a very large calculation with statistical uncertainties that approach what is needed for design applications. (authors)
Uncertainty Optimization Applied to the Monte Carlo Analysis of Planetary Entry Trajectories
NASA Technical Reports Server (NTRS)
Olds, John; Way, David
2001-01-01
Recently, strong evidence of liquid water under the surface of Mars and a meteorite that might contain ancient microbes have renewed interest in Mars exploration. With this renewed interest, NASA plans to send spacecraft to Mars approx. every 26 months. These future spacecraft will return higher-resolution images, make precision landings, engage in longer-ranging surface maneuvers, and even return Martian soil and rock samples to Earth. Future robotic missions and any human missions to Mars will require precise entries to ensure safe landings near science objective and pre-employed assets. Potential sources of water and other interesting geographic features are often located near hazards, such as within craters or along canyon walls. In order for more accurate landings to be made, spacecraft entering the Martian atmosphere need to use lift to actively control the entry. This active guidance results in much smaller landing footprints. Planning for these missions will depend heavily on Monte Carlo analysis. Monte Carlo trajectory simulations have been used with a high degree of success in recent planetary exploration missions. These analyses ascertain the impact of off-nominal conditions during a flight and account for uncertainty. Uncertainties generally stem from limitations in manufacturing tolerances, measurement capabilities, analysis accuracies, and environmental unknowns. Thousands of off-nominal trajectories are simulated by randomly dispersing uncertainty variables and collecting statistics on forecast variables. The dependability of Monte Carlo forecasts, however, is limited by the accuracy and completeness of the assumed uncertainties. This is because Monte Carlo analysis is a forward driven problem; beginning with the input uncertainties and proceeding to the forecasts outputs. It lacks a mechanism to affect or alter the uncertainties based on the forecast results. If the results are unacceptable, the current practice is to use an iterative, trial
Fallahpoor, M; Abbasi, M; Sen, A; Parach, A; Kalantari, F
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
A Monte Carlo based spent fuel analysis safeguards strategy assessment
Fensin, Michael L; Tobin, Stephen J; Swinhoe, Martyn T; Menlove, Howard O; Sandoval, Nathan P
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
NASA Astrophysics Data System (ADS)
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.
Momennezhad, Mehdi; Nasseri, Shahrokh; Zakavi, Seyed Rasoul; Parach, Ali Asghar; Ghorbani, Mahdi; Asl, Ruhollah Ghahraman
2016-01-01
Single-photon emission computed tomography (SPECT)-based tracers are easily available and more widely used than positron emission tomography (PET)-based tracers, and SPECT imaging still remains the most prevalent nuclear medicine imaging modality worldwide. The aim of this study is to implement an image-based Monte Carlo method for patient-specific three-dimensional (3D) absorbed dose calculation in patients after injection of (99m)Tc-hydrazinonicotinamide (hynic)-Tyr(3)-octreotide as a SPECT radiotracer. (99m)Tc patient-speciﬁc S values and the absorbed doses were calculated with GATE code for each source-target organ pair in four patients who were imaged for suspected neuroendocrine tumors. Each patient underwent multiple whole-body planar scans as well as SPECT imaging over a period of 1-24 h after intravenous injection of (99m)hynic-Tyr(3)-octreotide. The patient-specific S values calculated by GATE Monte Carlo code and the corresponding S values obtained by MIRDOSE program differed within 4.3% on an average for self-irradiation, and differed within 69.6% on an average for cross-irradiation. However, the agreement between total organ doses calculated by GATE code and MIRDOSE program for all patients was reasonably well (percentage difference was about 4.6% on an average). Normal and tumor absorbed doses calculated with GATE were slightly higher than those calculated with MIRDOSE program. The average ratio of GATE absorbed doses to MIRDOSE was 1.07 ± 0.11 (ranging from 0.94 to 1.36). According to the results, it is proposed that when cross-organ irradiation is dominant, a comprehensive approach such as GATE Monte Carlo dosimetry be used since it provides more reliable dosimetric results. PMID:27134562
Momennezhad, Mehdi; Nasseri, Shahrokh; Zakavi, Seyed Rasoul; Parach, Ali Asghar; Ghorbani, Mahdi; Asl, Ruhollah Ghahraman
2016-01-01
Single-photon emission computed tomography (SPECT)-based tracers are easily available and more widely used than positron emission tomography (PET)-based tracers, and SPECT imaging still remains the most prevalent nuclear medicine imaging modality worldwide. The aim of this study is to implement an image-based Monte Carlo method for patient-specific three-dimensional (3D) absorbed dose calculation in patients after injection of 99mTc-hydrazinonicotinamide (hynic)-Tyr3-octreotide as a SPECT radiotracer. 99mTc patient-speciﬁc S values and the absorbed doses were calculated with GATE code for each source-target organ pair in four patients who were imaged for suspected neuroendocrine tumors. Each patient underwent multiple whole-body planar scans as well as SPECT imaging over a period of 1-24 h after intravenous injection of 99mhynic-Tyr3-octreotide. The patient-specific S values calculated by GATE Monte Carlo code and the corresponding S values obtained by MIRDOSE program differed within 4.3% on an average for self-irradiation, and differed within 69.6% on an average for cross-irradiation. However, the agreement between total organ doses calculated by GATE code and MIRDOSE program for all patients was reasonably well (percentage difference was about 4.6% on an average). Normal and tumor absorbed doses calculated with GATE were slightly higher than those calculated with MIRDOSE program. The average ratio of GATE absorbed doses to MIRDOSE was 1.07 ± 0.11 (ranging from 0.94 to 1.36). According to the results, it is proposed that when cross-organ irradiation is dominant, a comprehensive approach such as GATE Monte Carlo dosimetry be used since it provides more reliable dosimetric results. PMID:27134562
NASA Astrophysics Data System (ADS)
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.
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.
Nuclear spectroscopy for in situ soil elemental analysis: Monte Carlo simulations
Wielopolski L.; Doron, O.
2012-07-01
We developed a model to simulate a novel inelastic neutron scattering (INS) system for in situ non-destructive analysis of soil using standard Monte Carlo Neutron Photon (MCNP5a) transport code. The volumes from which 90%, 95%, and 99% of the total signal are detected were estimated to be 0.23 m{sup 3}, 0.37 m{sup 3}, and 0.79 m{sup 3}, respectively. Similarly, we assessed the instrument's sampling footprint and depths. In addition we discuss the impact of the carbon's depth distribution on sampled depth.
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
Microlens assembly error analysis for light field camera based on Monte Carlo method
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Deguillaume, L.; Beekmann, M.; Menut, L.
2007-01-01
The purpose of this article is inverse modeling of emissions at regional scale for photochemical applications. The study is performed for the Ile-de-France region over a two summers (1998 and 1999) period. This area represents an ideal framework since concentrated anthropogenic emissions in the Paris region frequently lead to the formation of urban plumes. The inversion method is based on Bayesian Monte Carlo analysis applied to a regional-scale chemistry transport model, CHIMERE. This method consists in performing a large number of successive simulations with the same model but with a distinct set of model input parameters at each time. Then a posteriori weights are attributed to individual Monte Carlo simulations by comparing them with observations from the AIRPARIF network: urban NO and O3 concentrations and rural O3 concentrations around the Paris area. For both NO and O3 measurements, observations used for constraining Monte Carlo simulations are additionally averaged over the time period considered for analysis. The observational constraints strongly reduce the a priori uncertainties in anthropogenic NOx and volatile organic compounds (VOC) emissions: (1) The a posteriori probability density function (pdf) for NOx emissions is not modified in its average, but the standard deviation is decreased to around 20% (40% for the a priori one). (2) VOC emissions are enhanced (+16%) in the a posteriori pdf's with a standard deviation around 30% (40% for the a priori one). Uncertainties in the simulated urban NO, urban O3, and O3 production within the plume are reduced by a factor of 3.2, 2.4, and 1.7, respectively.
A Monte Carlo Uncertainty Analysis of Ozone Trend Predictions in a Two Dimensional Model. Revision
NASA Technical Reports Server (NTRS)
Considine, D. B.; Stolarski, R. S.; Hollandsworth, S. M.; Jackman, C. H.; Fleming, E. L.
1998-01-01
We use Monte Carlo analysis to estimate the uncertainty in predictions of total O3 trends between 1979 and 1995 made by the Goddard Space Flight Center (GSFC) two-dimensional (2D) model of stratospheric photochemistry and dynamics. The uncertainty is caused by gas-phase chemical reaction rates, photolysis coefficients, and heterogeneous reaction parameters which are model inputs. The uncertainty represents a lower bound to the total model uncertainty assuming the input parameter uncertainties are characterized correctly. Each of the Monte Carlo runs was initialized in 1970 and integrated for 26 model years through the end of 1995. This was repeated 419 times using input parameter sets generated by Latin Hypercube Sampling. The standard deviation (a) of the Monte Carlo ensemble of total 03 trend predictions is used to quantify the model uncertainty. The 34% difference between the model trend in globally and annually averaged total O3 using nominal inputs and atmospheric trends calculated from Nimbus 7 and Meteor 3 total ozone mapping spectrometer (TOMS) version 7 data is less than the 46% calculated 1 (sigma), model uncertainty, so there is no significant difference between the modeled and observed trends. In the northern hemisphere midlatitude spring the modeled and observed total 03 trends differ by more than 1(sigma) but less than 2(sigma), which we refer to as marginal significance. We perform a multiple linear regression analysis of the runs which suggests that only a few of the model reactions contribute significantly to the variance in the model predictions. The lack of significance in these comparisons suggests that they are of questionable use as guides for continuing model development. Large model/measurement differences which are many multiples of the input parameter uncertainty are seen in the meridional gradients of the trend and the peak-to-peak variations in the trends over an annual cycle. These discrepancies unambiguously indicate model formulation
NASA Astrophysics Data System (ADS)
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.
Furuta, T; Maeyama, T; Ishikawa, K L; Fukunishi, N; Fukasaku, K; Takagi, S; Noda, S; Himeno, R; Hayashi, S
2015-08-21
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. PMID:26266894
Uncertainty analysis in environmental radioactivity measurements using the Monte Carlo code MCNP5
NASA Astrophysics Data System (ADS)
Gallardo, S.; Querol, A.; Ortiz, J.; Ródenas, J.; Verdú, G.; Villanueva, J. F.
2015-11-01
High Purity Germanium (HPGe) detectors are widely used for environmental radioactivity measurements due to their excellent energy resolution. Monte Carlo (MC) codes are a useful tool to complement experimental measurements in calibration procedures at the laboratory. However, the efficiency curve of the detector can vary due to uncertainties associated with measurements. These uncertainties can be classified into some categories: geometrical parameters of the measurement (distance source-detector, volume of the source), properties of the radiation source (radionuclide activity, branching ratio), and detector characteristics (Ge dead layer, active volume, end cap thickness). The Monte Carlo simulation can be also affected by other kind of uncertainties mainly related to cross sections and to the calculation itself. Normally, all these uncertainties are not well known and it required a deep analysis to determine their effect on the detector efficiency. In this work, the Noether-Wilks formula is used to carry out the uncertainty analysis. A Probability Density Function (PDF) is assigned to each variable involved in the sampling process. The size of the sampling is determined from the characteristics of the tolerance intervals by applying the Noether-Wilks formula. Results of the analysis transform the efficiency curve into a region of possible values into the tolerance intervals. Results show a good agreement between experimental measurements and simulations for two different matrices (water and sand).
NASA Astrophysics Data System (ADS)
Ramírez, Andrea; de Keizer, Corry; Van der Sluijs, Jeroen P.; Olivier, Jos; Brandes, Laurens
This paper presents an assessment of the value added of a Monte Carlo analysis of the uncertainties in the Netherlands inventory of greenhouse gases over a Tier 1 analysis. It also examines which parameters contributed the most to the total emission uncertainty and identified areas of high priority for the further improvement of the accuracy and quality of the inventory. The Monte Carlo analysis resulted in an uncertainty range in total GHG emissions of 4.1% in 2004 and 5.4% in 1990 (with LUCF) and 5.3% (in 1990) and 3.9% (in 2004) for GHG emissions without LUCF. Uncertainty in the trend was estimated at 4.5%. The values are in the same order of magnitude as those estimated in the Tier 1. The results show that accounting for correlation among parameters is important, and for the Netherlands inventory it has a larger impact on the uncertainty in the trend than on the uncertainty in the total GHG emissions. The main contributors to overall uncertainty are found to be related to N 2O emissions from agricultural soils, the N 2O implied emission factors of Nitric Acid Production, CH 4 from managed solid waste disposal on land, and the implied emission factor of CH 4 from manure management from cattle.
Nasif, Hesham; Neyama, Atsushi
2003-02-26
This paper presents results of an uncertainty and sensitivity analysis for performance of the different barriers of high level radioactive waste repositories. SUA is a tool to perform the uncertainty and sensitivity on the output of Wavelet Integrated Repository System model (WIRS), which is developed to solve a system of nonlinear partial differential equations arising from the model formulation of radionuclide transport through repository. SUA performs sensitivity analysis (SA) and uncertainty analysis (UA) on a sample output from Monte Carlo simulation. The sample is generated by WIRS and contains the values of the output values of the maximum release rate in the form of time series and values of the input variables for a set of different simulations (runs), which are realized by varying the model input parameters. The Monte Carlo sample is generated with SUA as a pure random sample or using Latin Hypercube sampling technique. Tchebycheff and Kolmogrov confidence bounds are compute d on the maximum release rate for UA and effective non-parametric statistics to rank the influence of the model input parameters SA. Based on the results, we point out parameters that have primary influences on the performance of the engineered barrier system of a repository. The parameters found to be key contributor to the release rate are selenium and Cesium distribution coefficients in both geosphere and major water conducting fault (MWCF), the diffusion depth and water flow rate in the excavation-disturbed zone (EDZ).
Monte Carlo Simulation for Perusal and Practice.
ERIC Educational Resources Information Center
Brooks, Gordon P.; Barcikowski, Robert S.; Robey, Randall R.
The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…
Energy Science and Technology Software Center (ESTSC)
2010-10-20
The "Monte Carlo Benchmark" (MCB) is intended to model the computatiional performance of Monte Carlo algorithms on parallel architectures. It models the solution of a simple heuristic transport equation using a Monte Carlo technique. The MCB employs typical features of Monte Carlo algorithms such as particle creation, particle tracking, tallying particle information, and particle destruction. Particles are also traded among processors using MPI calls.
An analysis method for evaluating gradient-index fibers based on Monte Carlo method
NASA Astrophysics Data System (ADS)
Yoshida, S.; Horiuchi, S.; Ushiyama, Z.; Yamamoto, M.
2011-05-01
We propose a numerical analysis method for evaluating gradient-index (GRIN) optical fiber using the Monte Carlo method. GRIN optical fibers are widely used in optical information processing and communication applications, such as an image scanner, fax machine, optical sensor, and so on. An important factor which decides the performance of GRIN optical fiber is modulation transfer function (MTF). The MTF of a fiber is swayed by condition of manufacturing process such as temperature. Actual measurements of the MTF of a GRIN optical fiber using this method closely match those made by conventional methods. Experimentally, the MTF is measured using a square wave chart, and is then calculated based on the distribution of output strength on the chart. In contrast, the general method using computers evaluates the MTF based on a spot diagram made by an incident point light source. But the results differ greatly from those by experiment. In this paper, we explain the manufacturing process which affects the performance of GRIN optical fibers and a new evaluation method similar to the experimental system based on the Monte Carlo method. We verified that it more closely matches the experimental results than the conventional method.
Monte Carlo simulation for slip rate sensitivity analysis in Cimandiri fault area
Pratama, Cecep; Meilano, Irwan; Nugraha, Andri Dian
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%.
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
Monte carlo uncertainty analysis for photothermal radiometry measurements using a curve fit process
NASA Astrophysics Data System (ADS)
Horne, Kyle; Fleming, Austin; Timmins, Ben; Ban, Heng
2015-12-01
Photothermal radiometry (PTR) has become a popular method to measure thermal properties of layered materials. Much research has been done to determine the capabilities of PTR, but with little uncertainty analysis. This study reports a Monte Carlo uncertainty analysis to quantify uncertainty of film diffusivity and effusivity measurements, presents a sensitivity study for each input parameter, compares linear and logarithmic spacing of data points on frequency scans, and investigates the validity of a one-dimensional heat transfer assumption. Logarithmic spacing of frequencies when taking data is found to be unequivocally superior to linear spacing, while the use of a higher-dimensional heat transfer model is only needed for certain measurement configurations. The sensitivity analysis supports the frequency spacing conclusion, as well as explains trends seen in the uncertainty data.
NASA Astrophysics Data System (ADS)
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.
Monte Carlo models and analysis of galactic disk gamma-ray burst distributions
NASA Technical Reports Server (NTRS)
Hakkila, Jon
1989-01-01
Gamma-ray bursts are transient astronomical phenomena which have no quiescent counterparts in any region of the electromagnetic spectrum. Although temporal and spectral properties indicate that these events are likely energetic, their unknown spatial distribution complicates astrophysical interpretation. Monte Carlo samples of gamma-ray burst sources are created which belong to Galactic disk populations. Spatial analysis techniques are used to compare these samples to the observed distribution. From this, both quantitative and qualitative conclusions are drawn concerning allowed luminosity and spatial distributions of the actual sample. Although the Burst and Transient Source Experiment (BATSE) experiment on Gamma Ray Observatory (GRO) will significantly improve knowledge of the gamma-ray burst source spatial characteristics within only a few months of launch, the analysis techniques described herein will not be superceded. Rather, they may be used with BATSE results to obtain detailed information about both the luminosity and spatial distributions of the sources.
A bottom collider vertex detector design, Monte-Carlo simulation and analysis package
Lebrun, P.
1990-10-01
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 B{sub d} {yields} {pi}{sup +}{pi}{sup {minus}} is presented. These calculations have been done at FNAL energy ({radical}s = 2.0 TeV). Emphasis is placed on design issues, analysis techniques and related software rather than physics potentials. 20 refs., 46 figs.
Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations.
Arampatzis, Georgios; Katsoulakis, Markos A
2014-03-28
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
Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations
NASA Astrophysics Data System (ADS)
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
Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations
Arampatzis, Georgios; Katsoulakis, Markos A.
2014-03-28
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
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
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
Use of Monte Carlo simulations for Cultural Heritage X-ray fluorescence analysis
NASA Astrophysics Data System (ADS)
Brunetti, Antonio; Golosio, Bruno; Schoonjans, Tom; Oliva, Piernicola
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.
Contrast to Noise Ratio and Contrast Detail Analysis in Mammography:A Monte Carlo Study
NASA Astrophysics Data System (ADS)
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.
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
Slattery, S. R.; Wilson, P. P. H.; Evans, T. M.
2013-07-01
The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)
Application analysis of Monte Carlo to estimate the capacity of geothermal resources in Lawu Mount
Supriyadi; Srigutomo, Wahyu; Munandar, Arif
2014-03-24
Monte Carlo analysis has been applied in calculation of geothermal resource capacity based on volumetric method issued by Standar Nasional Indonesia (SNI). A deterministic formula is converted into a stochastic formula to take into account the nature of uncertainties in input parameters. The method yields a range of potential power probability stored beneath Lawu Mount geothermal area. For 10,000 iterations, the capacity of geothermal resources is in the range of 139.30-218.24 MWe with the most likely value is 177.77 MWe. The risk of resource capacity above 196.19 MWe is less than 10%. The power density of the prospect area covering 17 km{sup 2} is 9.41 MWe/km{sup 2} with probability 80%.
Backward Monte Carlo analysis on stray radiation of an infrared optical system
NASA Astrophysics Data System (ADS)
Chen, Xue; Sun, Chuang; Xia, Xinlin
2013-09-01
In an infrared optical system, the thermal radiation of high temperature components is the major noise as stray radiation that degrades the system performance. Backward Monte Carlo method based on radiation distribution factor is proposed to perform the stray radiation calculation. Theoretical deduction and some techniques are presented, considering the semitransparent element like IR window as radiation emitter. The radiation distribution factors are calculated with ray tracing from the detector to radiation sources. Propagation of stray radiation and its distribution on the detector are obtained simultaneously. It is unnecessary to implement ray tracing again to study the effect of different temperatures for a given system, expect that the geometry or radiative property is changed. An infrared system is simulated using this method. Two different situations are discussed and the analysis shows that stray radiation is mainly created by IR window and lens tube.
NASA Technical Reports Server (NTRS)
1980-01-01
The results of three nonlinear the Monte Carlo dispersion analyses for the Space Transportation System 1 Flight (STS-1) Orbiter Descent Operational Flight Profile, Cycle 3 are presented. Fifty randomly selected simulation for the end of mission (EOM) descent, the abort once around (AOA) descent targeted line are steep target line, and the AOA descent targeted to the shallow target line are analyzed. These analyses compare the flight environment with system and operational constraints on the flight environment and in some cases use simplified system models as an aid in assessing the STS-1 descent flight profile. In addition, descent flight envelops are provided as a data base for use by system specialists to determine the flight readiness for STS-1. The results of these dispersion analyses supersede results of the dispersion analysis previously documented.
Jet-Track Correlation Analysis of Monte Carlo Simulated Data for the CMS Experiment
NASA Astrophysics Data System (ADS)
Tabb, William; Evdokimov, Olga
2015-10-01
Collisions of ultra-relativistic heavy ion beams delivered at the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) are used to study the properties of a special form of nuclear matter, termed Quark Gluon Plasma (QGP). Among the experimental tools actively employed to explore the QGP properties, are jets - collimated streams of particles produced from hard-scattered partons in the initial state of the collision. The hot and dense medium produced in heavy ion collisions interacts strongly with the partons traversing it, resulting in energy loss and modifications to the momentum distributions of the forming jets. A development of the jet-track correlation analysis was performed and tested with Monte Carlo (MC) data samples simulating jet data for the CMS experiment at LHC, allowing study of several jet-related properties in order to better understand the medium effects on penetrating probes.
NASA Technical Reports Server (NTRS)
Williams, Jessica L.; Bhat, Ramachandra S.; You, Tung-Han
2012-01-01
The Soil Moisture Active Passive (SMAP) mission will perform soil moisture content and freeze/thaw state observations from a low-Earth orbit. The observatory is scheduled to launch in October 2014 and will perform observations from a near-polar, frozen, and sun-synchronous Science Orbit for a 3-year data collection mission. At launch, the observatory is delivered to an Injection Orbit that is biased below the Science Orbit; the spacecraft will maneuver to the Science Orbit during the mission Commissioning Phase. The delta V needed to maneuver from the Injection Orbit to the Science Orbit is computed statistically via a Monte Carlo simulation; the 99th percentile delta V (delta V99) is carried as a line item in the mission delta V budget. This paper details the simulation and analysis performed to compute this figure and the delta V99 computed per current mission parameters.
Uncertainty analysis using Monte Carlo method in the measurement of phase by ESPI
Anguiano Morales, Marcelino; Martinez, Amalia; Rayas, J. A.; Cordero, Raul R.
2008-04-15
A method for simultaneously measuring whole field in-plane displacements by using optical fiber and based on the dual-beam illumination principle electronic speckle pattern interferometry (ESPI) is presented in this paper. A set of single mode optical fibers and beamsplitter are employed to split the laser beam into four beams of equal intensity.One pair of fibers is utilized to illuminate the sample in the horizontal plane so it is sensitive only to horizontal in-plane displacement. Another pair of optical fibers is set to be sensitive only to vertical in-plane displacement. Each pair of optical fibers differs in longitude to avoid unwanted interference. By means of a Fourier-transform method of fringe-pattern analysis (Takeda method), we can obtain the quantitative data of whole field displacements. We found the uncertainty associated with the phases by mean of Monte Carlo-based technique.
An analysis of the convergence of the direct simulation Monte Carlo method
NASA Astrophysics Data System (ADS)
Galitzine, Cyril; Boyd, Iain D.
2015-05-01
In this article, a rigorous framework for the analysis of the convergence of the direct simulation Monte Carlo (DSMC) method is presented. It is applied to the simulation of two test cases: an axisymmetric jet at a Knudsen number of 0.01 and Mach number of 1 and a two-dimensional cylinder flow at a Knudsen of 0.05 and Mach 10. The rate of convergence of sampled quantities is found to be well predicted by an extended form of the Central Limit Theorem that takes into account the correlation of samples but requires the calculation of correlation spectra. A simplified analytical model that does not require correlation spectra is then constructed to model the effect of sample correlation. It is then used to obtain an a priori estimate of the convergence error.
Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method
NASA Astrophysics Data System (ADS)
Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin
2015-12-01
The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problem are presented.
Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method
Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin
2015-12-31
The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problem are presented.
Energy Science and Technology Software Center (ESTSC)
2006-05-09
The Monte Carlo example programs VARHATOM and DMCATOM are two small, simple FORTRAN programs that illustrate the use of the Monte Carlo Mathematical technique for calculating the ground state energy of the hydrogen atom.
NASA Astrophysics Data System (ADS)
Rose, Martin
2014-12-01
A triple stage turbo molecular pump is simulated using the DSMC method in 3D. A 90° sector of the complete pump is simulated taking the symmetry of the pump into account. Simulations were performed for various fore line pressures in order to determine the compression ratio and the maximum pumping speed. Various features of the three dimensional flow field are discussed. Also the CPU time required to obtain the flow field is discussed. The simulations presented here are a powerful tool for the design and improvement of turbo molecular pumps.
Generation of SFR few-group constants using the Monte Carlo code Serpent
Fridman, E.; Rachamin, R.; Shwageraus, E.
2013-07-01
In this study, the Serpent Monte Carlo code was used as a tool for preparation of homogenized few-group cross sections for the nodal diffusion analysis of Sodium cooled Fast Reactor (SFR) cores. Few-group constants for two reference SFR cores were generated by Serpent and then employed by nodal diffusion code DYN3D in 2D full core calculations. The DYN3D results were verified against the references full core Serpent Monte Carlo solutions. A good agreement between the reference Monte Carlo and nodal diffusion results was observed demonstrating the feasibility of using Serpent for generation of few-group constants for the deterministic SFR analysis. (authors)
Boggula, Ramesh; Jahnke, Lennart; Wertz, Hansjoerg; Lohr, Frank; Wenz, Frederik
2011-11-15
Purpose: Fast and reliable comprehensive quality assurance tools are required to validate the safety and accuracy of complex intensity-modulated radiotherapy (IMRT) plans for prostate treatment. In this study, we evaluated the performance of the COMPASS system for both off-line and potential online procedures for the verification of IMRT treatment plans. Methods and Materials: COMPASS has a dedicated beam model and dose engine, it can reconstruct three-dimensional dose distributions on the patient anatomy based on measured fluences using either the MatriXX two-dimensional (2D) array (offline) or a 2D transmission detector (T2D) (online). For benchmarking the COMPASS dose calculation, various dose-volume indices were compared against Monte Carlo-calculated dose distributions for five prostate patient treatment plans. Gamma index evaluation and absolute point dose measurements were also performed in an inhomogeneous pelvis phantom using extended dose range films and ion chamber for five additional treatment plans. Results: MatriXX-based dose reconstruction showed excellent agreement with the ion chamber (<0.5%, except for one treatment plan, which showed 1.5%), film ({approx}100% pixels passing gamma criteria 3%/3 mm) and mean dose-volume indices (<2%). The T2D based dose reconstruction showed good agreement as well with ion chamber (<2%), film ({approx}99% pixels passing gamma criteria 3%/3 mm), and mean dose-volume indices (<5.5%). Conclusion: The COMPASS system qualifies for routine prostate IMRT pretreatment verification with the MatriXX detector and has the potential for on-line verification of treatment delivery using T2D.
Taheriyoun, Masoud; Moradinejad, Saber
2015-01-01
The reliability of a wastewater treatment plant is a critical issue when the effluent is reused or discharged to water resources. Main factors affecting the performance of the wastewater treatment plant are the variation of the influent, inherent variability in the treatment processes, deficiencies in design, mechanical equipment, and operational failures. Thus, meeting the established reuse/discharge criteria requires assessment of plant reliability. Among many techniques developed in system reliability analysis, fault tree analysis (FTA) is one of the popular and efficient methods. FTA is a top down, deductive failure analysis in which an undesired state of a system is analyzed. In this study, the problem of reliability was studied on Tehran West Town wastewater treatment plant. This plant is a conventional activated sludge process, and the effluent is reused in landscape irrigation. The fault tree diagram was established with the violation of allowable effluent BOD as the top event in the diagram, and the deficiencies of the system were identified based on the developed model. Some basic events are operator's mistake, physical damage, and design problems. The analytical method is minimal cut sets (based on numerical probability) and Monte Carlo simulation. Basic event probabilities were calculated according to available data and experts' opinions. The results showed that human factors, especially human error had a great effect on top event occurrence. The mechanical, climate, and sewer system factors were in subsequent tier. Literature shows applying FTA has been seldom used in the past wastewater treatment plant (WWTP) risk analysis studies. Thus, the developed FTA model in this study considerably improves the insight into causal failure analysis of a WWTP. It provides an efficient tool for WWTP operators and decision makers to achieve the standard limits in wastewater reuse and discharge to the environment. PMID:25487461
NASA Astrophysics Data System (ADS)
Weatherill, Graeme; Burton, Paul W.
2010-09-01
The Aegean is the most seismically active and tectonically complex region in Europe. Damaging earthquakes have occurred here throughout recorded history, often resulting in considerable loss of life. The Monte Carlo method of probabilistic seismic hazard analysis (PSHA) is used to determine the level of ground motion likely to be exceeded in a given time period. Multiple random simulations of seismicity are generated to calculate, directly, the ground motion for a given site. Within the seismic hazard analysis we explore the impact of different seismic source models, incorporating both uniform zones and distributed seismicity. A new, simplified, seismic source model, derived from seismotectonic interpretation, is presented for the Aegean region. This is combined into the epistemic uncertainty analysis alongside existing source models for the region, and models derived by a K-means cluster analysis approach. Seismic source models derived using the K-means approach offer a degree of objectivity and reproducibility into the otherwise subjective approach of delineating seismic sources using expert judgment. Similar review and analysis is undertaken for the selection of peak ground acceleration (PGA) attenuation models, incorporating into the epistemic analysis Greek-specific models, European models and a Next Generation Attenuation model. Hazard maps for PGA on a "rock" site with a 10% probability of being exceeded in 50 years are produced and different source and attenuation models are compared. These indicate that Greek-specific attenuation models, with their smaller aleatory variability terms, produce lower PGA hazard, whilst recent European models and Next Generation Attenuation (NGA) model produce similar results. The Monte Carlo method is extended further to assimilate epistemic uncertainty into the hazard calculation, thus integrating across several appropriate source and PGA attenuation models. Site condition and fault-type are also integrated into the hazard
NASA Astrophysics Data System (ADS)
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.
Derivation of landslide-triggering thresholds by Monte Carlo simulation and ROC analysis
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
Zhuravleva, Tatiana; Bedareva, Tatiana; Nasrtdinov, Ilmir
As is well known, the spectral measurements of direct and diffuse solar radiation can be used to retrieve the optical and microphysical characteristics of atmospheric aerosol and clouds. Most methods of radiation calculations, which are used to solve the inverse problems, are implemented under the assumption of horizontal homogeneity of the atmosphere (clear-sky and overcast conditions). However, it is recognized that the 3D effects of clouds have a significant impact on the transfer of solar radiation in the atmosphere which can be the cause of errors in retrieval of aerosol and cloud properties. In this work, we present the algorithms of the Monte Carlo method for calculating the angular structure of diffuse radiation in the molecular-aerosol atmosphere and the appearance of isolated cloud. The simulation of radiative characteristics with specified spectral resolution is performed in spherical model of the atmosphere for the conditions of observations at the Earth’s surface and at the top of the atmosphere. Cloud is approximated by inverted paraboloid. The molecular absorption is accounted for on the basis of approximation of transmission function by short exponential series (k-distribution method). The specific features of the radiative transfer, caused by the 3D effects of clouds, are considered depending on cloud location in space and its sizes, sensing scheme, and illumination conditions. The simulation results of the brightness fields in the clear sky and in the appearance of isolated cloud are compared. This work was supported in part by the Russian Fund for Basic Research (through the grant no. 12-05-00169).
Gifford, Kent A; Wareing, Todd A; Failla, Gregory; Horton, John L; Eifel, Patricia J; Mourtada, Firas
2010-01-01
A patient dose distribution was calculated by a 3D multi-group S N particle transport code for intracavitary brachytherapy of the cervix uteri and compared to previously published Monte Carlo results. A Cs-137 LDR intracavitary brachytherapy CT data set was chosen from our clinical database. MCNPX version 2.5.c, was used to calculate the dose distribution. A 3D multi-group S N particle transport code, Attila version 6.1.1 was used to simulate the same patient. Each patient applicator was built in SolidWorks, a mechanical design package, and then assembled with a coordinate transformation and rotation for the patient. The SolidWorks exported applicator geometry was imported into Attila for calculation. Dose matrices were overlaid on the patient CT data set. Dose volume histograms and point doses were compared. The MCNPX calculation required 14.8 hours, whereas the Attila calculation required 22.2 minutes on a 1.8 GHz AMD Opteron CPU. Agreement between Attila and MCNPX dose calculations at the ICRU 38 points was within +/- 3%. Calculated doses to the 2 cc and 5 cc volumes of highest dose differed by not more than +/- 1.1% between the two codes. Dose and DVH overlays agreed well qualitatively. Attila can calculate dose accurately and efficiently for this Cs-137 CT-based patient geometry. Our data showed that a three-group cross-section set is adequate for Cs-137 computations. Future work is aimed at implementing an optimized version of Attila for radiotherapy calculations. PMID:20160682
Risk analysis of gravity dam instability using credibility theory Monte Carlo simulation model.
Xin, Cao; Chongshi, Gu
2016-01-01
Risk analysis of gravity dam stability involves complicated uncertainty in many design parameters and measured data. Stability failure risk ratio described jointly by probability and possibility has deficiency in characterization of influence of fuzzy factors and representation of the likelihood of risk occurrence in practical engineering. In this article, credibility theory is applied into stability failure risk analysis of gravity dam. Stability of gravity dam is viewed as a hybrid event considering both fuzziness and randomness of failure criterion, design parameters and measured data. Credibility distribution function is conducted as a novel way to represent uncertainty of influence factors of gravity dam stability. And combining with Monte Carlo simulation, corresponding calculation method and procedure are proposed. Based on a dam section, a detailed application of the modeling approach on risk calculation of both dam foundation and double sliding surfaces is provided. The results show that, the present method is feasible to be applied on analysis of stability failure risk for gravity dams. The risk assessment obtained can reflect influence of both sorts of uncertainty, and is suitable as an index value. PMID:27386264
NASA Astrophysics Data System (ADS)
Zhang, Jun; Guo, Fan
2015-11-01
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.
Monte Carlo simulations of image analysis for flexible and high-resolution registration metrology
NASA Astrophysics Data System (ADS)
Arnz, M.; Klose, G.; Troll, G.; Beyer, D.; Mueller, A.
2009-01-01
The continuous progress of PROVE, the new photomask registration and overlay measurement tool currently under development at Carl Zeiss has been reported at mask related conferences since it's first publication at EMLC 2008. The project has moved in the past year from a final design on paper to functional hardware in the lab. Major tool components such as the climate control unit, the automated mask handling system and the metrology stage have been assembled and successfully tested. The scope of this paper is to report on the current status of PROVE and furthermore present results from simulations utilizing the image analysis routines of the tool. Monte-Carlo simulations were used to analyze the impact of several realistic tool limitations (camera noise, stage and focus noise and imaging telecentricity) on the image analysis process. The evaluation itself was based on a conventional threshold approach to perform both registration and CD measurement simultaneously. The results show, that the routines can deal with the tool imperfections and limit the contribution to the reproducibility error for standard registration markers to a negligible part. Even single contact holes suffer only from small errors, when camera noise is low and image averaging is increased. Employing a generally used test pattern the CD test results also confirm a sufficiently small error contribution to the CD non-uniformity reproducibility.
Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics
Hall, Howard L
2012-01-01
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.
A Monte Carlo error analysis program for near-Mars, finite-burn, orbital transfer maneuvers
NASA Technical Reports Server (NTRS)
Green, R. N.; Hoffman, L. H.; Young, G. R.
1972-01-01
A computer program was developed which performs an error analysis of a minimum-fuel, finite-thrust, transfer maneuver between two Keplerian orbits in the vicinity of Mars. The method of analysis is the Monte Carlo approach where each off-nominal initial orbit is targeted to the desired final orbit. The errors in the initial orbit are described by two covariance matrices of state deviations and tracking errors. The function of the program is to relate these errors to the resulting errors in the final orbit. The equations of motion for the transfer trajectory are those of a spacecraft maneuvering with constant thrust and mass-flow rate in the neighborhood of a single body. The thrust vector is allowed to rotate in a plane with a constant pitch rate. The transfer trajectory is characterized by six control parameters and the final orbit is defined, or partially defined, by the desired target parameters. The program is applicable to the deboost maneuver (hyperbola to ellipse), orbital trim maneuver (ellipse to ellipse), fly-by maneuver (hyperbola to hyperbola), escape maneuvers (ellipse to hyperbola), and deorbit maneuver.
Analysis of Monte Carlo methods applied to blackbody and lower emissivity cavities.
Pahl, Robert J; Shannon, Mark A
2002-02-01
Monte Carlo methods are often applied to the calculation of the apparent emissivities of blackbody cavities. However, for cavities with complex as well as some commonly encountered geometries, the emission Monte Carlo method experiences problems of convergence. The emission and absorption Monte Carlo methods are compared on the basis of ease of implementation and convergence speed when applied to blackbody sources. A new method to determine solution convergence compatible with both methods is developed, and the convergence speeds of the two methods are compared through the application of both methods to a right-circular cylinder cavity. It is shown that the absorption method converges faster and is easier to implement than the emission method when applied to most blackbody and lower emissivity cavities. PMID:11993915
A Monte Carlo Analysis of Gas Centrifuge Enrichment Plant Process Load Cell Data
Garner, James R; Whitaker, J Michael
2013-01-01
As uranium enrichment plants increase in number, capacity, and types of separative technology deployed (e.g., gas centrifuge, laser, etc.), more automated safeguards measures are needed to enable the IAEA to maintain safeguards effectiveness in a fiscally constrained environment. Monitoring load cell data can significantly increase the IAEA s ability to efficiently achieve the fundamental safeguards objective of confirming operations as declared (i.e., no undeclared activities), but care must be taken to fully protect the operator s proprietary and classified information related to operations. Staff at ORNL, LANL, JRC/ISPRA, and University of Glasgow are investigating monitoring the process load cells at feed and withdrawal (F/W) stations to improve international safeguards at enrichment plants. A key question that must be resolved is what is the necessary frequency of recording data from the process F/W stations? Several studies have analyzed data collected at a fixed frequency. This paper contributes to load cell process monitoring research by presenting an analysis of Monte Carlo simulations to determine the expected errors caused by low frequency sampling and its impact on material balance calculations.
Markov chain Monte Carlo analysis to constrain dark matter properties with directional detection
Billard, J.; Mayet, F.; Santos, D.
2011-04-01
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.
Monte Carlo analysis of dissociation and recombination behind strong shock waves in nitrogen
NASA Technical Reports Server (NTRS)
Boyd, I. D.
1991-01-01
Computations are presented for the relaxation zone behind strong, 1D shock waves in nitrogen. The analysis is performed with the direct simulation Monte Carlo method (DSMC). The DSMC code is vectorized for efficient use on a supercomputer. The code simulates translational, rotational and vibrational energy exchange and dissociative and recombinative chemical reactions. A model is proposed for the treatment of three body-recombination collisions in the DSMC technique which usually simulates binary collision events. The model improves previous models because it can be employed with a large range of chemical-rate data, does not introduce into the flow field troublesome pairs of atoms which may recombine upon further collision (pseudoparticles) and is compatible with the vectorized code. The computational results are compared with existing experimental data. It is shown that the derivation of chemical-rate coefficients must account for the degree of vibrational nonequilibrium in the flow. A nonequilibrium-chemistry model is employed together with equilibrium-rate data to compute the flow in several different nitrogen shock waves.
Improving Bayesian analysis for LISA Pathfinder using an efficient Markov Chain Monte Carlo method
NASA Astrophysics Data System (ADS)
Ferraioli, Luigi; Porter, Edward K.; Armano, Michele; Audley, Heather; Congedo, Giuseppe; Diepholz, Ingo; Gibert, Ferran; Hewitson, Martin; Hueller, Mauro; Karnesis, Nikolaos; Korsakova, Natalia; Nofrarias, Miquel; Plagnol, Eric; Vitale, Stefano
2014-02-01
We present a parameter estimation procedure based on a Bayesian framework by applying a Markov Chain Monte Carlo algorithm to the calibration of the dynamical parameters of the LISA Pathfinder satellite. The method is based on the Metropolis-Hastings algorithm and a two-stage annealing treatment in order to ensure an effective exploration of the parameter space at the beginning of the chain. We compare two versions of the algorithm with an application to a LISA Pathfinder data analysis problem. The two algorithms share the same heating strategy but with one moving in coordinate directions using proposals from a multivariate Gaussian distribution, while the other uses the natural logarithm of some parameters and proposes jumps in the eigen-space of the Fisher Information matrix. The algorithm proposing jumps in the eigen-space of the Fisher Information matrix demonstrates a higher acceptance rate and a slightly better convergence towards the equilibrium parameter distributions in the application to LISA Pathfinder data. For this experiment, we return parameter values that are all within ˜1 σ of the injected values. When we analyse the accuracy of our parameter estimation in terms of the effect they have on the force-per-unit of mass noise, we find that the induced errors are three orders of magnitude less than the expected experimental uncertainty in the power spectral density.
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
Slattery, Stuart R.; Evans, Thomas M.; Wilson, Paul P. H.
2015-09-08
The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear oper- ator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approxi- mation and the mean chord approximation are applied to estimate the leakage frac- tion of random walks from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem in numerical experiments to test the models for symmetric operators with spectral qualities similar to light water reactor problems. We find, in general, the derived approximations show good agreement with random walk lengths and leakage fractions computed by the numerical experiments.
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
Slattery, Stuart R.; Evans, Thomas M.; Wilson, Paul P. H.
2015-09-08
The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear oper- ator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approxi- mation and the mean chord approximation are applied to estimate the leakagemore » frac- tion of random walks from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem in numerical experiments to test the models for symmetric operators with spectral qualities similar to light water reactor problems. We find, in general, the derived approximations show good agreement with random walk lengths and leakage fractions computed by the numerical experiments.« less
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.
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.
NASA Technical Reports Server (NTRS)
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.
NASA Astrophysics Data System (ADS)
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.
Baillie, D; St Aubin, J; Fallone, B; Steciw, S
2014-06-15
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.
NASA Astrophysics Data System (ADS)
Sboev, A. G.; Ilyashenko, A. S.; Vetrova, O. A.
1997-02-01
The method of bucking evaluation, realized in the MOnte Carlo code MCS, is described. This method was applied for calculational analysis of well known light water experiments TRX-1 and TRX-2. The analysis of this comparison shows, that there is no coincidence between Monte Carlo calculations, obtained by different ways: the MCS calculations with given experimental bucklings; the MCS calculations with given bucklings evaluated on base of full core MCS direct simulations; the full core MCNP and MCS direct simulations; the MCNP and MCS calculations, where the results of cell calculations are corrected by the coefficients taking into the account the leakage from the core. Also the buckling values evaluated by full core MCS calculations have differed from experimental ones, especially in the case of TRX-1, when this difference has corresponded to 0.5 percent increase of Keff value.
Effect of lag time distribution on the lag phase of bacterial growth - a Monte Carlo analysis
Technology Transfer Automated Retrieval System (TEKTRAN)
The objective of this study is to use Monte Carlo simulation to evaluate the effect of lag time distribution of individual bacterial cells incubated under isothermal conditions on the development of lag phase. The growth of bacterial cells of the same initial concentration and mean lag phase durati...
NASA Astrophysics Data System (ADS)
Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.
2011-12-01
Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently
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
Shi, Wei; Wei, Si; Hu, Xin-xin; Hu, Guan-jiu; Chen, Cu-lan; Wang, Xin-ru; Giesy, John P.; Yu, Hong-xia
2013-01-01
Some synthetic chemicals, which have been shown to disrupt thyroid hormone (TH) function, have been detected in surface waters and people have the potential to be exposed through water-drinking. Here, the presence of thyroid-active chemicals and their toxic potential in drinking water sources in Yangtze River Delta were investigated by use of instrumental analysis combined with cell-based reporter gene assay. A novel approach was developed to use Monte Carlo simulation, for evaluation of the potential risks of measured concentrations of TH agonists and antagonists and to determine the major contributors to observed thyroid receptor (TR) antagonist potency. None of the extracts exhibited TR agonist potency, while 12 of 14 water samples exhibited TR antagonistic potency. The most probable observed antagonist equivalents ranged from 1.4 to 5.6 µg di-n-butyl phthalate (DNBP)/L, which posed potential risk in water sources. Based on Monte Carlo simulation related mass balance analysis, DNBP accounted for 64.4% for the entire observed antagonist toxic unit in water sources, while diisobutyl phthalate (DIBP), di-n-octyl phthalate (DNOP) and di-2-ethylhexyl phthalate (DEHP) also contributed. The most probable observed equivalent and most probable relative potency (REP) derived from Monte Carlo simulation is useful for potency comparison and responsible chemicals screening. PMID:24204563
NASA Astrophysics Data System (ADS)
Gratiy, Sergey L.; Walker, Andrew C.; Levin, Deborah A.; Goldstein, David B.; Varghese, Philip L.; Trafton, Laurence M.; Moore, Chris H.
2010-05-01
Conflicting observations regarding the dominance of either sublimation or volcanism as the source of the atmosphere on Io and disparate reports on the extent of its spatial distribution and the absolute column abundance invite the development of detailed computational models capable of improving our understanding of Io's unique atmospheric structure and origin. Improving upon previous models, Walker et al. (Walker, A.C., Gratiy, S.L., Levin, D.A., Goldstein, D.B., Varghese, P.L., Trafton, L.M., Moore, C.H., Stewart, B. [2009]. Icarus) developed a fully 3-D global rarefied gas dynamics model of Io's atmosphere including both sublimation and volcanic sources of SO 2 gas. The fidelity of the model is tested by simulating remote observations at selected wavelength bands and comparing them to the corresponding astronomical observations of Io's atmosphere. The simulations are performed with a new 3-D spherical-shell radiative transfer code utilizing a backward Monte Carlo method. We present: (1) simulations of the mid-infrared disk-integrated spectra of Io's sunlit hemisphere at 19 μm, obtained with TEXES during 2001-2004; (2) simulations of disk-resolved images at Lyman- α obtained with the Hubble Space Telescope (HST), Space Telescope Imaging Spectrograph (STIS) during 1997-2001; and (3) disk-integrated simulations of emission line profiles in the millimeter wavelength range obtained with the IRAM-30 m telescope in October-November 1999. We found that the atmospheric model generally reproduces the longitudinal variation in band depth from the mid-infrared data; however, the best match is obtained when our simulation results are shifted ˜30° toward lower orbital longitudes. The simulations of Lyman- α images do not reproduce the mid-to-high latitude bright patches seen in the observations, suggesting that the model atmosphere sustains columns that are too high at those latitudes. The simulations of emission line profiles in the millimeter spectral region support
Monte Carlo simulations for analysis and design of nuclear isomer experiments
NASA Astrophysics Data System (ADS)
Winick, Tristan; Goddard, Brian; Carroll, James
2014-09-01
The well-established GEANT4 Monte Carlo code was used to analyze the results from a test of bremsstrahlung-induced nuclear isomer switching and to guide development of an experiment to test nuclear excitation by electron capture (NEEC). Bremsstrahlung-induced experiments have historically been analyzed with the assumption that the photon flux of the bremsstrahlung spectrum at a given energy varies linearly with the spectrum's endpoint. The results obtained with GEANT4 suggest that this assumption is not justified; the revised function differs enough to warrant a re-analysis of the experimental data. This re-analysis has been applied to the switching of the unusually long-lived isomer of 180Ta (T1/2 > 1016 yr.), showing that the energies of its switching states differ by about 30 keV compared to those previously identified. GEANT4 was also employed in the design of a NEEC experiment to test the isomer switching of 93Mo via coupled atomic-nuclear processes. Initial work involved modeling a beam of 93Mo ions incident on a volume of 4He gas and observing the charge exchange process and associated emitted fluorescence. The beam and 4He volume, the ionization trails of the electrons liberated from the 4He atoms, and the subsequent fluorescence were successfully simulated; however, it was found that GEANT4 does not currently support ion charge exchange. Future work will entail either the development of the requisite code for GEANT4, or the use of a different model that can accurately simulate ion charge exchange.
LaFarge, R.A.
1992-01-01
Sandia National Laboratories (SNL) launched the Los Alamos National Laboratory (LANL) sponsored ZEST flight test program from the SNL Kauai Test Facility (KTF) in the summer of 1991. The ZEST program had about 255 pounds of high explosive (HE) aboard a Talos-Castor launch vehicle. Naturally, such undertakings raise questions about the safety of personnel and the environment in the event of a premature detonation of the HE. These questions pertain not only to KTF and the island of Kauai but to the neighboring islands as well. The ability to determine realistically P{sub I}, the probability of an explosively generated fragment impacting a given exclusion area, is an important factor in the safety analysis of any flight test involving explosive payloads. Once P{sub I} is known, the casualty expectations C{sub E} can be computed based on local demographics. A set of two computer codes was developed to determine P{sub I} based on computed fragment impacts. One of these codes, SAFETIE1 (Sandia Analysis of FragmEnt TrajectorIEs), computes files of trajectory initial conditions generated in a Monte Carlo sense for a set of n explosions each containing m fragments. These initial condition files are then used to compute trajectories in a parallel processing environment using a local area network (LAN) of 40 Sun workstations. This approach saves the equivalent of 40 hours of Cray YMP time. The other code, SAFETIE2, is a postprocessor that uses an AMEER output file generated by SAFETIE1, to determine how many explosions have at least one fragment in a user defined exclusion area. The average number of fragments per explosion in the exclusion area ({bar N}) is also computed (for C{sub E} considerations). 12 refs.
Investing in a robotic milking system: a Monte Carlo simulation analysis.
Hyde, J; Engel, P
2002-09-01
This paper uses Monte Carlo simulation methods to estimate the breakeven value for a robotic milking system (RMS) on a dairy farm in the United States. The breakeven value indicates the maximum amount that could be paid for the robots given the costs of alternative milking equipment and other important factors (e.g., milk yields, prices, length of useful life of technologies). The analysis simulates several scenarios under three herd sizes, 60, 120, and 180 cows. The base-case results indicate that the mean breakeven values are $192,056, $374,538, and $553,671 for each of the three progressively larger herd sizes. These must be compared to the per-unit RMS cost (about $125,000 to $150,000) and the cost of any construction or installation of other equipment that accompanies the RMS. Sensitivity analysis shows that each additional dollar spent on milking labor in the parlor increases the breakeven value by $4.10 to $4.30. Each dollar increase in parlor costs increases the breakeven value by $0.45 to $0.56. Also, each additional kilogram of initial milk production (under a 2x system in the parlor) decreases the breakeven by $9.91 to $10.64. Finally, each additional year of useful life for the RMS increases the per-unit breakeven by about $16,000 while increasing the life of the parlor by 1 yr decreases the breakeven value by between $5,000 and $6,000. PMID:12362453
Voit, E.O.; Balthis, W.L.; Holser, R.A.
1995-12-31
The quantitative assessment of environmental contaminants is a complex process. It involves nonlinear models and the characterization of variables, factors, and parameters that are distributed and dependent on each other. Assessments based on point estimates are easy to perform, but since they are unreliable, Monte Carlo simulations have become a standard procedure. Simulations pose two challenges: They require the numerical characterization of parameter distributions and they do not account for dependencies between parameters. This paper offers strategies for dealing with both challenges. The first part discusses the characterization of data with the S-distribution. This distribution offers several advantages, which include simplicity of numerical analysis, flexibility in shape, and easy computation of quantiles. The second part outlines how the S-distribution can be used for hierarchical Monte Carlo simulations. In these simulations the selection of parameter values occurs sequentially, and each choice depends on the parameter values selected before. The method is illustrated with preliminary simulation analyses that are concerned with mercury contamination in king mackerel (Scomberomorus cavalla). It is demonstrated that the results of such hierarchical simulations are generally different from those of traditional Monte Carlo simulations.
Regeneration and Fixed-Width Analysis of Markov Chain Monte Carlo Algorithms
NASA Astrophysics Data System (ADS)
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.
Analysis of single Monte Carlo methods for prediction of reflectance from turbid media
Martinelli, Michele; Gardner, Adam; Cuccia, David; Hayakawa, Carole; Spanier, Jerome; Venugopalan, Vasan
2011-01-01
Starting from the radiative transport equation we derive the scaling relationships that enable a single Monte Carlo (MC) simulation to predict the spatially- and temporally-resolved reflectance from homogeneous semi-infinite media with arbitrary scattering and absorption coefficients. This derivation shows that a rigorous application of this single Monte Carlo (sMC) approach requires the rescaling to be done individually for each photon biography. We examine the accuracy of the sMC method when processing simulations on an individual photon basis and also demonstrate the use of adaptive binning and interpolation using non-uniform rational B-splines (NURBS) to achieve order of magnitude reductions in the relative error as compared to the use of uniform binning and linear interpolation. This improved implementation for sMC simulation serves as a fast and accurate solver to address both forward and inverse problems and is available for use at http://www.virtualphotonics.org/. PMID:21996904
Analysis of single Monte Carlo methods for prediction of reflectance from turbid media.
Martinelli, Michele; Gardner, Adam; Cuccia, David; Hayakawa, Carole; Spanier, Jerome; Venugopalan, Vasan
2011-09-26
Starting from the radiative transport equation we derive the scaling relationships that enable a single Monte Carlo (MC) simulation to predict the spatially- and temporally-resolved reflectance from homogeneous semi-infinite media with arbitrary scattering and absorption coefficients. This derivation shows that a rigorous application of this single Monte Carlo (sMC) approach requires the rescaling to be done individually for each photon biography. We examine the accuracy of the sMC method when processing simulations on an individual photon basis and also demonstrate the use of adaptive binning and interpolation using non-uniform rational B-splines (NURBS) to achieve order of magnitude reductions in the relative error as compared to the use of uniform binning and linear interpolation. This improved implementation for sMC simulation serves as a fast and accurate solver to address both forward and inverse problems and is available for use at http://www.virtualphotonics.org/. PMID:21996904
Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm
NASA Astrophysics Data System (ADS)
Takaishi, Tetsuya
2013-04-01
The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is superior to other Markov Chain Monte Carlo methods in sampling volatility variables. We perform the HMC simulations of the SV model for two liquid stock returns traded on the Tokyo Stock Exchange and measure the volatilities of those stock returns. Then we calculate the accuracy of the volatility measurement using the realized volatility as a proxy of the true volatility and compare the SV model with the GARCH model which is one of other volatility models. Using the accuracy calculated with the realized volatility we find that empirically the SV model performs better than the GARCH model.
Single pin BWR benchmark problem for coupled Monte Carlo - Thermal hydraulics analysis
Ivanov, A.; Sanchez, V.; Hoogenboom, J. E.
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)
Douglass, Michael; Bezak, Eva; Penfold, Scott
2013-07-15
Purpose: Investigation of increased radiation dose deposition due to gold nanoparticles (GNPs) using a 3D computational cell model during x-ray radiotherapy.Methods: Two GNP simulation scenarios were set up in Geant4; a single 400 nm diameter gold cluster randomly positioned in the cytoplasm and a 300 nm gold layer around the nucleus of the cell. Using an 80 kVp photon beam, the effect of GNP on the dose deposition in five modeled regions of the cell including cytoplasm, membrane, and nucleus was simulated. Two Geant4 physics lists were tested: the default Livermore and custom built Livermore/DNA hybrid physics list. 10{sup 6} particles were simulated at 840 cells in the simulation. Each cell was randomly placed with random orientation and a diameter varying between 9 and 13 {mu}m. A mathematical algorithm was used to ensure that none of the 840 cells overlapped. The energy dependence of the GNP physical dose enhancement effect was calculated by simulating the dose deposition in the cells with two energy spectra of 80 kVp and 6 MV. The contribution from Auger electrons was investigated by comparing the two GNP simulation scenarios while activating and deactivating atomic de-excitation processes in Geant4.Results: The physical dose enhancement ratio (DER) of GNP was calculated using the Monte Carlo model. The model has demonstrated that the DER depends on the amount of gold and the position of the gold cluster within the cell. Individual cell regions experienced statistically significant (p < 0.05) change in absorbed dose (DER between 1 and 10) depending on the type of gold geometry used. The DER resulting from gold clusters attached to the cell nucleus had the more significant effect of the two cases (DER {approx} 55). The DER value calculated at 6 MV was shown to be at least an order of magnitude smaller than the DER values calculated for the 80 kVp spectrum. Based on simulations, when 80 kVp photons are used, Auger electrons have a statistically insignificant (p
Dupuis, Paul
2014-03-14
This proposal is concerned with applications of Monte Carlo to problems in physics and chemistry where rare events degrade the performance of standard Monte Carlo. One class of problems is concerned with computation of various aspects of the equilibrium behavior of some Markov process via time averages. The problem to be overcome is that rare events interfere with the efficient sampling of all relevant parts of phase space. A second class concerns sampling transitions between two or more stable attractors. Here, rare events do not interfere with the sampling of all relevant parts of phase space, but make Monte Carlo inefficient because of the very large number of samples required to obtain variance comparable to the quantity estimated. The project uses large deviation methods for the mathematical analyses of various Monte Carlo techniques, and in particular for algorithmic analysis and design. This is done in the context of relevant application areas, mainly from chemistry and biology.
Monte Carlo-based multiphysics coupling analysis of x-ray pulsar telescope
NASA Astrophysics Data System (ADS)
Li, Liansheng; Deng, Loulou; Mei, Zhiwu; Zuo, Fuchang; Zhou, Hao
2015-10-01
X-ray pulsar telescope (XPT) is a complex optical payload, which involves optical, mechanical, electrical and thermal disciplines. The multiphysics coupling analysis (MCA) plays an important role in improving the in-orbit performance. However, the conventional MCA methods encounter two serious problems in dealing with the XTP. One is that both the energy and reflectivity information of X-ray can't be taken into consideration, which always misunderstands the essence of XPT. Another is that the coupling data can't be transferred automatically among different disciplines, leading to computational inefficiency and high design cost. Therefore, a new MCA method for XPT is proposed based on the Monte Carlo method and total reflective theory. The main idea, procedures and operational steps of the proposed method are addressed in detail. Firstly, it takes both the energy and reflectivity information of X-ray into consideration simultaneously. And formulate the thermal-structural coupling equation and multiphysics coupling analysis model based on the finite element method. Then, the thermalstructural coupling analysis under different working conditions has been implemented. Secondly, the mirror deformations are obtained using construction geometry function. Meanwhile, the polynomial function is adopted to fit the deformed mirror and meanwhile evaluate the fitting error. Thirdly, the focusing performance analysis of XPT can be evaluated by the RMS. Finally, a Wolter-I XPT is taken as an example to verify the proposed MCA method. The simulation results show that the thermal-structural coupling deformation is bigger than others, the vary law of deformation effect on the focusing performance has been obtained. The focusing performances of thermal-structural, thermal, structural deformations have degraded 30.01%, 14.35% and 7.85% respectively. The RMS of dispersion spot are 2.9143mm, 2.2038mm and 2.1311mm. As a result, the validity of the proposed method is verified through
Monte Carlo homogenized limit analysis model for randomly assembled blocks in-plane loaded
NASA Astrophysics Data System (ADS)
Milani, Gabriele; Lourenço, Paulo B.
2010-11-01
A simple rigid-plastic homogenization model for the limit analysis of masonry walls in-plane loaded and constituted by the random assemblage of blocks with variable dimensions is proposed. In the model, blocks constituting a masonry wall are supposed infinitely resistant with a Gaussian distribution of height and length, whereas joints are reduced to interfaces with frictional behavior and limited tensile and compressive strength. Block by block, a representative element of volume (REV) is considered, constituted by a central block interconnected with its neighbors by means of rigid-plastic interfaces. The model is characterized by a few material parameters, is numerically inexpensive and very stable. A sub-class of elementary deformation modes is a-priori chosen in the REV, mimicking typical failures due to joints cracking and crushing. Masonry strength domains are obtained equating the power dissipated in the heterogeneous model with the power dissipated by a fictitious homogeneous macroscopic plate. Due to the inexpensiveness of the approach proposed, Monte Carlo simulations can be repeated on the REV in order to have a stochastic estimation of in-plane masonry strength at different orientations of the bed joints with respect to external loads accounting for the geometrical statistical variability of blocks dimensions. Two cases are discussed, the former consisting on full stochastic REV assemblages (obtained considering a random variability of both blocks height an length) and the latter assuming the presence of a horizontal alignment along bed joints, i.e. allowing blocks height variability only row by row. The case of deterministic blocks height (quasi-periodic texture) can be obtained as a subclass of this latter case. Masonry homogenized failure surfaces are finally implemented in an upper bound FE limit analysis code for the analysis at collapse of entire walls in-plane loaded. Two cases of engineering practice, consisting on the prediction of the failure
Predictive uncertainty analysis of a saltwater intrusion model using null-space Monte Carlo
Herckenrath, Daan; Langevin, Christian D.; Doherty, John
2011-01-01
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 uncertainty was tested for a synthetic saltwater intrusion model patterned after the Henry problem. Saltwater intrusion caused by a reduction in fresh groundwater discharge was simulated for 1000 randomly generated hydraulic conductivity distributions, representing a mildly heterogeneous aquifer. From these 1000 simulations, the hydraulic conductivity distribution giving rise to the most extreme case of saltwater intrusion was selected and was assumed to represent the "true" system. Head and salinity values from this true model were then extracted and used as observations for subsequent model calibration. 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 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 of the NSMC method to encompass the true prediction value. The addition of intrapilot point heterogeneity to the NSMC process was also tested. According to a variogram comparison, this provided the same scale of heterogeneity that was used to generate the truth. However, incorporation of intrapilot point variability did not make a noticeable difference to the uncertainty of the prediction. With this higher level of heterogeneity, however, the computational burden of
Dumonteil, E.; Le Peillet, A.; Lee, Y. K.; Petit, O.; Jouanne, C.; Mazzolo, A.
2006-07-01
The measurement of the stationarity of Monte Carlo fission source distributions in k{sub eff} calculations plays a central role in the ability to discriminate between fake and 'true' convergence (in the case of a high dominant ratio or in case of loosely coupled systems). Recent theoretical developments have been made in the study of source convergence diagnostics, using Shannon entropy. We will first recall those results, and we will then generalize them using the expression of Boltzmann entropy, highlighting the gain in terms of the various physical problems that we can treat. Finally we will present the results of several OECD/NEA benchmarks using the Tripoli-4 Monte Carlo code, enhanced with this new criterion. (authors)
NASA Astrophysics Data System (ADS)
Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.
2014-04-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures - for example, by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow for a more detailed analysis of the dynamic behaviour of the soil-plant interface. We coupled two of such high-process-oriented independent models and calibrated both models simultaneously. The catchment modelling framework (CMF) simulated soil hydrology based on the Richards equation and the van Genuchten-Mualem model of the soil hydraulic properties. CMF was coupled with the plant growth modelling framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo-based generalized likelihood uncertainty estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from a uniform distribution. The model was applied to three sites with different management in Müncheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matter of roots, storages, stems and leaves. The shape parameter of the retention curve n was highly constrained, whereas other parameters of the retention curve showed a large equifinality. We attribute this slightly poorer model performance to missing leaf senescence, which is currently not implemented in PMF. The most constrained parameters for the
Performance analysis of the Monte Carlo code MCNP4A for photon-based radiotherapy applications
DeMarco, J.J.; Solberg, T.D.; Wallace, R.E.; Smathers, J.B.
1995-12-31
The Los Alamos code MCNP4A (Monte Carlo M-Particle version 4A) is currently used to simulate a variety of problems ranging from nuclear reactor analysis to boron neutron capture therapy. This study is designed to evaluate MCNP4A as the dose calculation system for photon-based radiotherapy applications. A graphical user interface (MCNP Radiation Therapy) has been developed which automatically sets up the geometry and photon source requirements for three-dimensional simulations using Computed Tomography (CT) data. Preliminary results suggest the code is capable of calculating satisfactory dose distributions in a variety of simulated homogeneous and heterogeneous phantoms. The major drawback for this dosimetry system is the amount of time to obtain a statistically significant answer. MCNPRT allows the user to analyze the performance of MCNP4A as a function of material, geometry resolution and MCNP4A photon and electron physics parameters. A typical simulation geometry consists of a 10 MV photon point source incident on a 15 x 15 x 15 cm{sup 3} phantom composed of water voxels ranging in size from 10 x 10 x 10 mm{sup 3} to 2 x 2 x 2 mm{sup 3}. As the voxel size is decreased, a larger percentage of time is spent tracking photons through the voxelized geometry as opposed to the secondary electrons. A PRPR Patch file is under development that will optimize photon transport within the simulation phantom specifically for radiotherapy applications. MCNP4A also supports parallel processing capabilities via the Parallel Virtual Machine (PVM) message passing system. A dedicated network of five SUN SPARC2 processors produced a wall-clock speedup of 4.4 based on a simulation phantom containing 5 x 5 x 5 mm{sup 3} water voxels. The code was also tested on the 80 node IBM RS/6000 cluster at the Maui High Performance Computing Center (NHPCC). A non-dedicated system of 75 processors produces a wall clock speedup of 29 relative to one SUN SPARC2 computer.
Cramer, S.N.
1984-01-01
The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described.
NASA Astrophysics Data System (ADS)
Fraser, Danielle
In radiation therapy an uncertainty in the delivered dose always exists because anatomic changes are unpredictable and patient specific. Image guided radiation therapy (IGRT) relies on imaging in the treatment room to monitor the tumour and surrounding tissue to ensure their prescribed position in the radiation beam. The goal of this thesis was to determine the dosimetric impact on the misaligned radiation therapy target for three cancer sites due to common setup errors; organ motion, tumour tissue deformation, changes in body habitus, and treatment planning errors. For this purpose, a novel 3D ultrasound system (Restitu, Resonant Medical, Inc.) was used to acquire a reference image of the target in the computed tomography simulation room at the time of treatment planning, to acquire daily images in the treatment room at the time of treatment delivery, and to compare the daily images to the reference image. The measured differences in position and volume between daily and reference geometries were incorporated into Monte Carlo (MC) dose calculations. The EGSnrc (National Research Council, Canada) family of codes was used to model Varian linear accelerators and patient specific beam parameters, as well as to estimate the dose to the target and organs at risk under several different scenarios. After validating the necessity of MC dose calculations in the pelvic region, the impact of interfraction prostate motion, and subsequent patient realignment under the treatment beams, on the delivered dose was investigated. For 32 patients it is demonstrated that using 3D conformal radiation therapy techniques and a 7 mm margin, the prescribed dose to the prostate, rectum, and bladder is recovered within 0.5% of that planned when patient setup is corrected for prostate motion, despite the beams interacting with a new external surface and internal tissue boundaries. In collaboration with the manufacturer, the ultrasound system was adapted from transabdominal imaging to neck
The applicability of certain Monte Carlo methods to the analysis of interacting polymers
Krapp, D.M. Jr.
1998-05-01
The authors consider polymers, modeled as self-avoiding walks with interactions on a hexagonal lattice, and examine the applicability of certain Monte Carlo methods for estimating their mean properties at equilibrium. Specifically, the authors use the pivoting algorithm of Madras and Sokal and Metroplis rejection to locate the phase transition, which is known to occur at {beta}{sub crit} {approx} 0.99, and to recalculate the known value of the critical exponent {nu} {approx} 0.58 of the system for {beta} = {beta}{sub crit}. Although the pivoting-Metropolis algorithm works well for short walks (N < 300), for larger N the Metropolis criterion combined with the self-avoidance constraint lead to an unacceptably small acceptance fraction. In addition, the algorithm becomes effectively non-ergodic, getting trapped in valleys whose centers are local energy minima in phase space, leading to convergence towards different values of {nu}. The authors use a variety of tools, e.g. entropy estimation and histograms, to improve the results for large N, but they are only of limited effectiveness. Their estimate of {beta}{sub crit} using smaller values of N is 1.01 {+-} 0.01, and the estimate for {nu} at this value of {beta} is 0.59 {+-} 0.005. They conclude that even a seemingly simple system and a Monte Carlo algorithm which satisfies, in principle, ergodicity and detailed balance conditions, can in practice fail to sample phase space accurately and thus not allow accurate estimations of thermal averages. This should serve as a warning to people who use Monte Carlo methods in complicated polymer folding calculations. The structure of the phase space combined with the algorithm itself can lead to surprising behavior, and simply increasing the number of samples in the calculation does not necessarily lead to more accurate results.
Monte Carlo analysis of germanium detector performance in slow positron beam experiments
NASA Astrophysics Data System (ADS)
Heikinheimo, J.; Tuominen, R.; Tuomisto, F.
2016-01-01
Positron annihilation Doppler broadening spectroscopy is one of the most popular positron annihilation vacancy characterization techniques in experimental materials research. The measurements are often carried out with a slow positron beam setup, which enables depth profiling of the samples. The key measurement devices of Doppler broadening spectroscopy setups are high-purity germanium detectors. Since Doppler broadening spectroscopy is one of the standard techniques in defect characterization, there is a demand to evaluate different kinds of factors that might have an effect on the results. Here we report the results of Monte Carlo simulations of detector response in different geometries and compare the data to experiments.
Markov chain Monte Carlo methods for statistical analysis of RF photonic devices.
Piels, Molly; Zibar, Darko
2016-02-01
The microwave reflection coefficient is commonly used to characterize the impedance of high-speed optoelectronic devices. Error and uncertainty in equivalent circuit parameters measured using this data are systematically evaluated. The commonly used nonlinear least-squares method for estimating uncertainty is shown to give unsatisfactory and incorrect results due to the nonlinear relationship between the circuit parameters and the measured data. Markov chain Monte Carlo methods are shown to provide superior results, both for individual devices and for assessing within-die variation. PMID:26906783
Lenhard, Karim
2012-06-20
To enable traceability of imaging spectrometer data, the associated measurement uncertainties have to be provided reliably. Here a new tool for a Monte-Carlo-type measurement uncertainty propagation for the uncertainties that originate from the spectrometer itself is described. For this, an instrument model of the imaging spectrometer ROSIS is used. Combined uncertainties are then derived for radiometrically and spectrally calibrated data using a synthetic at-sensor radiance spectrum as input. By coupling this new software tool with an inverse modeling program, the measurement uncertainties are propagated for an exemplary water data product. PMID:22722281
Monte Carlo analysis of lobular gas-surface scattering in tubes applied to thermal transpiration
NASA Technical Reports Server (NTRS)
Smith, J. D.; Raquet, C. A.
1972-01-01
A model of rarefied gas flow in tubes was developed which combines a lobular distribution with diffuse reflection at the wall. The model with Monte Carlo techniques was used to explain previously observed deviations in the free molecular thermal transpiration ratio which suggest molecules can have a greater tube transmission probability in a hot-to-cold direction than in a cold-to-hot direction. The model yields correct magnitudes of transmission probability ratios for helium in Pyrex tubing (1.09 to 1.14), and some effects of wall-temperature distribution, tube surface roughness, tube dimensions, gas temperature, and gas molecular mass.
Analysis and Monte Carlo simulation of near-terminal aircraft flight paths
NASA Technical Reports Server (NTRS)
Schiess, J. R.; Matthews, C. G.
1982-01-01
The flight paths of arriving and departing aircraft at an airport are stochastically represented. Radar data of the aircraft movements are used to decompose the flight paths into linear and curvilinear segments. Variables which describe the segments are derived, and the best fitting probability distributions of the variables, based on a sample of flight paths, are found. Conversely, given information on the probability distribution of the variables, generation of a random sample of flight paths in a Monte Carlo simulation is discussed. Actual flight paths at Dulles International Airport are analyzed and simulated.
Monte Carlo variance reduction
NASA Technical Reports Server (NTRS)
Byrn, N. R.
1980-01-01
Computer program incorporates technique that reduces variance of forward Monte Carlo method for given amount of computer time in determining radiation environment in complex organic and inorganic systems exposed to significant amounts of radiation.
NASA Astrophysics Data System (ADS)
Sanattalab, Ehsan; SalmanOgli, Ahmad; Piskin, Erhan
2016-04-01
We investigated the tumor-targeted nanoparticles that influence heat generation. We suppose that all nanoparticles are fully functionalized and can find the target using active targeting methods. Unlike the commonly used methods, such as chemotherapy and radiotherapy, the treatment procedure proposed in this study is purely noninvasive, which is considered to be a significant merit. It is found that the localized heat generation due to targeted nanoparticles is significantly higher than other areas. By engineering the optical properties of nanoparticles, including scattering, absorption coefficients, and asymmetry factor (cosine scattering angle), the heat generated in the tumor's area reaches to such critical state that can burn the targeted tumor. The amount of heat generated by inserting smart agents, due to the surface Plasmon resonance, will be remarkably high. The light-matter interactions and trajectory of incident photon upon targeted tissues are simulated by MIE theory and Monte Carlo method, respectively. Monte Carlo method is a statistical one by which we can accurately probe the photon trajectories into a simulation area.
Analysis of Correlated Coupling of Monte Carlo Forward and Adjoint Histories
Ueki, Taro; Hoogenboom, J.E.; Kloosterman, J. L.
2001-02-15
In Monte Carlo correlated coupling, forward and adjoint particle histories are initiated in exactly opposite directions at an arbitrarily placed surface between a physical source and a physical detector. It is shown that this coupling calculation can become more efficient than standard forward calculations. In many cases, the basic form of correlated coupling is less efficient than standard forward calculations. This inherent inefficiency can be overcome by applying a black absorber perturbation to either the forward or the adjoint problem and by processing the product of batch averages as one statistical entity. The usage of the black absorber is based on the invariance of the response flow integral with a material perturbation in either the physical detector side volume in the forward problem or the physical source side volume in the adjoint problem. The batch-average product processing makes use of a quadratic increase of the nonzero coupled-score probability. All the developments have been done in such a way that improved efficiency schemes available in widely distributed Monte Carlo codes can be applied to both the forward and adjoint simulations. Also, the physical meaning of the black absorber perturbation is interpreted based on surface crossing and is numerically validated. In addition, the immediate reflection at the intermediate surface with a controlled direction change is investigated within the invariance framework. This approach can be advantageous for a void streaming problem.
Sensitivity analysis of an asymmetric Monte Carlo beam model of a Siemens Primus accelerator.
Schreiber, Eric C; Sawkey, Daren L; Faddegon, Bruce A
2012-01-01
The assumption of cylindrical symmetry in radiotherapy accelerator models can pose a challenge for precise Monte Carlo modeling. This assumption makes it difficult to account for measured asymmetries in clinical dose distributions. We have performed a sensitivity study examining the effect of varying symmetric and asymmetric beam and geometric parameters of a Monte Carlo model for a Siemens PRIMUS accelerator. The accelerator and dose output were simulated using modified versions of BEAMnrc and DOSXYZnrc that allow lateral offsets of accelerator components and lateral and angular offsets for the incident electron beam. Dose distributions were studied for 40 × 40 cm² fields. The resulting dose distributions were analyzed for changes in flatness, symmetry, and off-axis ratio (OAR). The electron beam parameters having the greatest effect on the resulting dose distributions were found to be electron energy and angle of incidence, as high as 5% for a 0.25° deflection. Electron spot size and lateral offset of the electron beam were found to have a smaller impact. Variations in photon target thickness were found to have a small effect. Small lateral offsets of the flattening filter caused significant variation to the OAR. In general, the greatest sensitivity to accelerator parameters could be observed for higher energies and off-axis ratios closer to the central axis. Lateral and angular offsets of beam and accelerator components have strong effects on dose distributions, and should be included in any high-accuracy beam model. PMID:22402376
Bianchini, G.; Burgio, N.; Carta, M.; Peluso, V.; Fabrizio, V.; Ricci, L.
2012-07-01
The GUINEVERE experiment (Generation of Uninterrupted Intense Neutrons at the lead Venus Reactor) is an experimental program in support of the ADS technology presently carried out at SCK-CEN in Mol (Belgium). In the experiment a modified lay-out of the original thermal VENUS critical facility is coupled to an accelerator, built by the French body CNRS in Grenoble, working in both continuous and pulsed mode and delivering 14 MeV neutrons by bombardment of deuterons on a tritium-target. The modified lay-out of the facility consists of a fast subcritical core made of 30% U-235 enriched metallic Uranium in a lead matrix. Several off-line and on-line reactivity measurement techniques will be investigated during the experimental campaign. This report is focused on the simulation by deterministic (ERANOS French code) and Monte Carlo (MCNPX US code) calculations of three reactivity measurement techniques, Slope ({alpha}-fitting), Area-ratio and Source-jerk, applied to a GUINEVERE subcritical configuration (namely SC1). The inferred reactivity, in dollar units, by the Area-ratio method shows an overall agreement between the two deterministic and Monte Carlo computational approaches, whereas the MCNPX Source-jerk results are affected by large uncertainties and allow only partial conclusions about the comparison. Finally, no particular spatial dependence of the results is observed in the case of the GUINEVERE SC1 subcritical configuration. (authors)
Monte Carlo Analysis of Pion Contribution to Absorbed Dose from Galactic Cosmic Rays
NASA Technical Reports Server (NTRS)
Aghara, S.K.; Battnig, S.R.; Norbury, J.W.; Singleterry, R.C.
2009-01-01
Accurate knowledge of the physics of interaction, particle production and transport is necessary to estimate the radiation damage to equipment used on spacecraft and the biological effects of space radiation. For long duration astronaut missions, both on the International Space Station and the planned manned missions to Moon and Mars, the shielding strategy must include a comprehensive knowledge of the secondary radiation environment. The distribution of absorbed dose and dose equivalent is a function of the type, energy and population of these secondary products. Galactic cosmic rays (GCR) comprised of protons and heavier nuclei have energies from a few MeV per nucleon to the ZeV region, with the spectra reaching flux maxima in the hundreds of MeV range. Therefore, the MeV - GeV region is most important for space radiation. Coincidentally, the pion production energy threshold is about 280 MeV. The question naturally arises as to how important these particles are with respect to space radiation problems. The space radiation transport code, HZETRN (High charge (Z) and Energy TRaNsport), currently used by NASA, performs neutron, proton and heavy ion transport explicitly, but it does not take into account the production and transport of mesons, photons and leptons. In this paper, we present results from the Monte Carlo code MCNPX (Monte Carlo N-Particle eXtended), showing the effect of leptons and mesons when they are produced and transported in a GCR environment.
NASA Astrophysics Data System (ADS)
Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.
2013-12-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The
NASA Astrophysics Data System (ADS)
Houska, Tobias; Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz
2014-05-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the Van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 x 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape
Lagerlöf, Jakob H.; Kindblom, Jon; Bernhardt, Peter
2014-09-15
Purpose: To construct a Monte Carlo (MC)-based simulation model for analyzing the dependence of tumor oxygen distribution on different variables related to tumor vasculature [blood velocity, vessel-to-vessel proximity (vessel proximity), and inflowing oxygen partial pressure (pO{sub 2})]. Methods: A voxel-based tissue model containing parallel capillaries with square cross-sections (sides of 10 μm) was constructed. Green's function was used for diffusion calculations and Michaelis-Menten's kinetics to manage oxygen consumption. The model was tuned to approximately reproduce the oxygenational status of a renal carcinoma; the depth oxygenation curves (DOC) were fitted with an analytical expression to facilitate rapid MC simulations of tumor oxygen distribution. DOCs were simulated with three variables at three settings each (blood velocity, vessel proximity, and inflowing pO{sub 2}), which resulted in 27 combinations of conditions. To create a model that simulated variable oxygen distributions, the oxygen tension at a specific point was randomly sampled with trilinear interpolation in the dataset from the first simulation. Six correlations between blood velocity, vessel proximity, and inflowing pO{sub 2} were hypothesized. Variable models with correlated parameters were compared to each other and to a nonvariable, DOC-based model to evaluate the differences in simulated oxygen distributions and tumor radiosensitivities for different tumor sizes. Results: For tumors with radii ranging from 5 to 30 mm, the nonvariable DOC model tended to generate normal or log-normal oxygen distributions, with a cut-off at zero. The pO{sub 2} distributions simulated with the six-variable DOC models were quite different from the distributions generated with the nonvariable DOC model; in the former case the variable models simulated oxygen distributions that were more similar to in vivo results found in the literature. For larger tumors, the oxygen distributions became truncated in the
Kuselman, Ilya; Pennecchi, Francesca; Epstein, Malka; Fajgelj, Ales; Ellison, Stephen L R
2014-12-01
Monte Carlo simulation of expert judgments on human errors in a chemical analysis was used for determination of distributions of the error quantification scores (scores of likelihood and severity, and scores of effectiveness of a laboratory quality system in prevention of the errors). The simulation was based on modeling of an expert behavior: confident, reasonably doubting and irresolute expert judgments were taken into account by means of different probability mass functions (pmfs). As a case study, 36 scenarios of human errors which may occur in elemental analysis of geological samples by ICP-MS were examined. Characteristics of the score distributions for three pmfs of an expert behavior were compared. Variability of the scores, as standard deviation of the simulated score values from the distribution mean, was used for assessment of the score robustness. A range of the score values, calculated directly from elicited data and simulated by a Monte Carlo method for different pmfs, was also discussed from the robustness point of view. It was shown that robustness of the scores, obtained in the case study, can be assessed as satisfactory for the quality risk management and improvement of a laboratory quality system against human errors. PMID:25159436
Densmore, Jeffery D.
2011-02-20
We perform an asymptotic analysis of the spatial discretization of radiation absorption and re-emission in Implicit Monte Carlo (IMC), a Monte Carlo technique for simulating nonlinear radiative transfer. Specifically, we examine the approximation of absorption and re-emission by a spatially continuous artificial-scattering process and either a piecewise-constant or piecewise-linear emission source within each spatial cell. We consider three asymptotic scalings representing (i) a time step that resolves the mean-free time, (ii) a Courant limit on the time-step size, and (iii) a fixed time step that does not depend on any asymptotic scaling. For the piecewise-constant approximation, we show that only the third scaling results in a valid discretization of the proper diffusion equation, which implies that IMC may generate inaccurate solutions with optically large spatial cells if time steps are refined. However, we also demonstrate that, for a certain class of problems, the piecewise-linear approximation yields an appropriate discretized diffusion equation under all three scalings. We therefore expect IMC to produce accurate solutions for a wider range of time-step sizes when the piecewise-linear instead of piecewise-constant discretization is employed. We demonstrate the validity of our analysis with a set of numerical examples.
Perfetti, Christopher M.; Rearden, Bradley T.
2016-03-01
The sensitivity and uncertainty analysis tools of the ORNL SCALE nuclear modeling and simulation code system that have been developed over the last decade have proven indispensable for numerous application and design studies for nuclear criticality safety and reactor physics. SCALE contains tools for analyzing the uncertainty in the eigenvalue of critical systems, but cannot quantify uncertainty in important neutronic parameters such as multigroup cross sections, fuel fission rates, activation rates, and neutron fluence rates with realistic three-dimensional Monte Carlo simulations. A more complete understanding of the sources of uncertainty in these design-limiting parameters could lead to improvements in processmore » optimization, reactor safety, and help inform regulators when setting operational safety margins. A novel approach for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was recently explored as academic research and has been found to accurately and rapidly calculate sensitivity coefficients in criticality safety applications. The work presented here describes a new method, known as the GEAR-MC method, which extends the CLUTCH theory for calculating eigenvalue sensitivity coefficients to enable sensitivity coefficient calculations and uncertainty analysis for a generalized set of neutronic responses using high-fidelity continuous-energy Monte Carlo calculations. Here, several criticality safety systems were examined to demonstrate proof of principle for the GEAR-MC method, and GEAR-MC was seen to produce response sensitivity coefficients that agreed well with reference direct perturbation sensitivity coefficients.« less
NASA Astrophysics Data System (ADS)
Inyang, Samuel Okon; Chamberlain, Alan
2016-03-01
The use of a dual electron multileaf collimator (eMLC) to collimate therapeutic electron beam without the use of cutouts has been previously shown to be feasible. Further Monte Carlo simulations were performed in this study to verify the nature and appearance of the isodose distribution in water phantom of irregular electron beams delivered by the eMLC. Electron fields used in this study were selected to reflect those used in electron beam therapy. Results of this study show that the isodose distribution in a water phantom obtained from the simulation of irregular electron beams through the eMLC conforms to the pattern of the eMLC used in the delivery of the beam. It is therefore concluded that the dual eMLC could deliver isodose distributions reflecting the pattern of the eMLC field that was used in the delivery of the beam.
NASA Astrophysics Data System (ADS)
Richter, S.; Pinard, P. T.
2016-02-01
Electron probe microanalysis and focussed ion beam milling are combined to improve the sensitivity and applicability of depth profiling quantification. With the nanoscale milling capabilities of the ion beam, very shallow bevels are milled by using a special preparation procedure to reduce any curtaining effect and minimize Ga ions implantation. A Ni/Cr multilayered specimen is used to evaluate the depth resolution. The best results are obtained by a well-focussed electron beam offered by a field-emission microprobe. A new evaluation algorithm is presented to quantify the structure in terms of mass thicknesses or if the density is known in terms of real thicknesses. The quantification procedure is based on Monte Carlo simulations where calculated k-ratios (calibrated X-ray intensities) are compared to the experimental ones to find the optimal structure. In comparison with an ion milled cross-section, the proposed bevel technique is more sensitive and provides more information about the material's structure.
Analysis of Light Transport Features in Stone Fruits Using Monte Carlo Simulation
Ding, Chizhu; Shi, Shuning; Chen, Jianjun; Wei, Wei; Tan, Zuojun
2015-01-01
The propagation of light in stone fruit tissue was modeled using the Monte Carlo (MC) method. Peaches were used as the representative model of stone fruits. The effects of the fruit core and the skin on light transport features in the peaches were assessed. It is suggested that the skin, flesh and core should be separately considered with different parameters to accurately simulate light propagation in intact stone fruit. The detection efficiency was evaluated by the percentage of effective photons and the detection sensitivity of the flesh tissue. The fruit skin decreases the detection efficiency, especially in the region close to the incident point. The choices of the source-detector distance, detection angle and source intensity were discussed. Accurate MC simulations may result in better insight into light propagation in stone fruit and aid in achieving the optimal fruit quality inspection without extensive experimental measurements. PMID:26469695
A Monte Carlo analysis of the liquid xenon TPC as gamma ray telescope
NASA Technical Reports Server (NTRS)
Aprile, E.; Bolotnikov, A.; Chen, D.; Mukherjee, R.
1992-01-01
Extensive Monte Carlo modeling of a coded aperture x ray telescope based on a high resolution liquid xenon TPC has been performed. Results on efficiency, background reduction capability and source flux sensitivity are presented. We discuss in particular the development of a reconstruction algorithm for events with multiple interaction points. From the energy and spatial information, the kinematics of Compton scattering is used to identify and reduce background events, as well as to improve the detector response in the few MeV region. Assuming a spatial resolution of 1 mm RMS and an energy resolution of 4.5 percent FWHM at 1 MeV, the algorithm is capable of reducing by an order of magnitude the background rate expected at balloon altitude, thus significantly improving the telescope sensitivity.
Analysis of vibrational-translational energy transfer using the direct simulation Monte Carlo method
NASA Technical Reports Server (NTRS)
Boyd, Iain D.
1991-01-01
A new model is proposed for energy transfer between the vibrational and translational modes for use in the direct simulation Monte Carlo method (DSMC). The model modifies the Landau-Teller theory for a harmonic oscillator and the rate transition is related to an experimental correlation for the vibrational relaxation time. Assessment of the model is made with respect to three different computations: relaxation in a heat bath, a one-dimensional shock wave, and hypersonic flow over a two-dimensional wedge. These studies verify that the model achieves detailed balance, and excellent agreement with experimental data is obtained in the shock wave calculation. The wedge flow computation reveals that the usual phenomenological method for simulating vibrational nonequilibrium in the DSMC technique predicts much higher vibrational temperatures in the wake region.
Vittengl, Jeffrey R.; Clark, Lee Anna; Thase, Michael E.; Jarrett, Robin B.
2015-01-01
Sudden gains are relatively large, quick, stable drops in symptom scores during treatment of depression that may (or may not) signal important therapeutic events. We review what is known and unknown currently about the prevalence, causes, and outcomes of sudden gains. We argue that valid identification of sudden gains (vs. random fluctuations in symptoms and gradual gains) is prerequisite to their understanding. In Monte Carlo simulations, three popular criterion sets showed inadequate power to detect sudden gains and many false positives due to (a) testing multiple intervals for sudden gains, (b) finite retest reliability of symptom measures, and (c) failure to account for gradual gains. Sudden gains in published clinical datasets appear similar in form and frequency to false positives in the simulations. We discuss the need to develop psychometrically sound methods to detect sudden gains and to differentiate sudden from random and gradual gains. PMID:26478724
Analysis of aerial survey data on Florida manatee using Markov chain Monte Carlo.
Craig, B A; Newton, M A; Garrott, R A; Reynolds, J E; Wilcox, J R
1997-06-01
We assess population trends of the Atlantic coast population of Florida manatee, Trichechus manatus latirostris, by reanalyzing aerial survey data collected between 1982 and 1992. To do so, we develop an explicit biological model that accounts for the method by which the manatees are counted, the mammals' movement between surveys, and the behavior of the population total over time. Bayesian inference, enabled by Markov chain Monte Carlo, is used to combine the survey data with the biological model. We compute marginal posterior distributions for all model parameters and predictive distributions for future counts. Several conclusions, such as a decreasing population growth rate and low sighting probabilities, are consistent across different prior specifications. PMID:9192449
Photoelectric Franck-Hertz experiment and its kinetic analysis by Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Magyar, Péter; Korolov, Ihor; Donkó, Zoltán
2012-05-01
The electrical characteristics of a photoelectric Franck-Hertz cell are measured in argon gas over a wide range of pressure, covering conditions where elastic collisions play an important role, as well as conditions where ionization becomes significant. Photoelectron pulses are induced by the fourth harmonic UV light of a diode-pumped Nd:YAG laser. The electron kinetics, which is far more complex compared to the naive picture of the Franck-Hertz experiment, is analyzed via Monte Carlo simulation. The computations provide the electrical characteristics of the cell, the energy and velocity distribution functions, and the transport parameters of the electrons, as well as the rate coefficients of different elementary processes. A good agreement is obtained between the cell's measured and calculated electrical characteristics, the peculiarities of which are understood by the simulation studies.
Korostil, Igor A; Peters, Gareth W; Cornebise, Julien; Regan, David G
2013-05-20
A Bayesian statistical model and estimation methodology based on forward projection adaptive Markov chain Monte Carlo is developed in order to perform the calibration of a high-dimensional nonlinear system of ordinary differential equations representing an epidemic model for human papillomavirus types 6 and 11 (HPV-6, HPV-11). The model is compartmental and involves stratification by age, gender and sexual-activity group. Developing this model and a means to calibrate it efficiently is relevant because HPV is a very multi-typed and common sexually transmitted infection with more than 100 types currently known. The two types studied in this paper, types 6 and 11, are causing about 90% of anogenital warts. We extend the development of a sexual mixing matrix on the basis of a formulation first suggested by Garnett and Anderson, frequently used to model sexually transmitted infections. In particular, we consider a stochastic mixing matrix framework that allows us to jointly estimate unknown attributes and parameters of the mixing matrix along with the parameters involved in the calibration of the HPV epidemic model. This matrix describes the sexual interactions between members of the population under study and relies on several quantities that are a priori unknown. The Bayesian model developed allows one to estimate jointly the HPV-6 and HPV-11 epidemic model parameters as well as unknown sexual mixing matrix parameters related to assortativity. Finally, we explore the ability of an extension to the class of adaptive Markov chain Monte Carlo algorithms to incorporate a forward projection strategy for the ordinary differential equation state trajectories. Efficient exploration of the Bayesian posterior distribution developed for the ordinary differential equation parameters provides a challenge for any Markov chain sampling methodology, hence the interest in adaptive Markov chain methods. We conclude with simulation studies on synthetic and recent actual data. PMID
Analysis of uncertainties in Monte Carlo simulated organ dose for chest CT
NASA Astrophysics Data System (ADS)
Muryn, John S.; Morgan, Ashraf G.; Segars, W. P.; Liptak, Chris L.; Dong, Frank F.; Primak, Andrew N.; Li, Xiang
2015-03-01
In Monte Carlo simulation of organ dose for a chest CT scan, many input parameters are required (e.g., half-value layer of the x-ray energy spectrum, effective beam width, and anatomical coverage of the scan). The input parameter values are provided by the manufacturer, measured experimentally, or determined based on typical clinical practices. The goal of this study was to assess the uncertainties in Monte Carlo simulated organ dose as a result of using input parameter values that deviate from the truth (clinical reality). Organ dose from a chest CT scan was simulated for a standard-size female phantom using a set of reference input parameter values (treated as the truth). To emulate the situation in which the input parameter values used by the researcher may deviate from the truth, additional simulations were performed in which errors were purposefully introduced into the input parameter values, the effects of which on organ dose per CTDIvol were analyzed. Our study showed that when errors in half value layer were within ± 0.5 mm Al, the errors in organ dose per CTDIvol were less than 6%. Errors in effective beam width of up to 3 mm had negligible effect (< 2.5%) on organ dose. In contrast, when the assumed anatomical center of the patient deviated from the true anatomical center by 5 cm, organ dose errors of up to 20% were introduced. Lastly, when the assumed extra scan length was longer by 4 cm than the true value, dose errors of up to 160% were found. The results answer the important question: to what level of accuracy each input parameter needs to be determined in order to obtain accurate organ dose results.
Womersley, J. . Dept. of Physics)
1992-10-01
The D0 detector at the Fermilab Tevatron began its first data taking run in May 1992. For analysis of the expected 25 pb[sup [minus]1] data sample, roughly half a million simulated events will be needed. The GEANT-based Monte Carlo program used to generate these events is described, together with comparisons to test beam data. Some novel techniques used to speed up execution and simplify geometrical input are described.
Bashkatov, A N; Genina, Elina A; Kochubei, V I; Tuchin, Valerii V
2006-12-31
Based on the digital image analysis and inverse Monte-Carlo method, the proximate analysis method is deve-loped and the optical properties of hairs of different types are estimated in three spectral ranges corresponding to three colour components. The scattering and absorption properties of hairs are separated for the first time by using the inverse Monte-Carlo method. The content of different types of melanin in hairs is estimated from the absorption coefficient. It is shown that the dominating type of melanin in dark hairs is eumelanin, whereas in light hairs pheomelanin dominates. (special issue devoted to multiple radiation scattering in random media)
NASA Astrophysics Data System (ADS)
Idiri, Z.; Mazrou, H.; Beddek, S.; Amokrane, A.; Azbouche, A.
2007-07-01
The present paper describes the optimization of sample dimensions of a 241Am-Be neutron source-based Prompt gamma neutron activation analysis (PGNAA) setup devoted for in situ environmental water rejects analysis. The optimal dimensions have been achieved following extensive Monte Carlo neutron flux calculations using MCNP5 computer code. A validation process has been performed for the proposed preliminary setup with measurements of thermal neutron flux by activation technique of indium foils, bare and with cadmium covered sheet. Sensitive calculations were subsequently performed to simulate real conditions of in situ analysis by determining thermal neutron flux perturbations in samples according to chlorine and organic matter concentrations changes. The desired optimal sample dimensions were finally achieved once established constraints regarding neutron damage to semi-conductor gamma detector, pulse pile-up, dead time and radiation hazards were fully met.