R and D on automatic modeling methods for Monte Carlo codes FLUKA
International Nuclear Information System (INIS)
Wang Dianxi; Hu Liqin; Wang Guozhong; Zhao Zijia; Nie Fanzhi; Wu Yican; Long Pengcheng
2013-01-01
FLUKA is a fully integrated particle physics Monte Carlo simulation package. It is necessary to create the geometry models before calculation. However, it is time- consuming and error-prone to describe the geometry models manually. This study developed an automatic modeling method which could automatically convert computer-aided design (CAD) geometry models into FLUKA models. The conversion program was integrated into CAD/image-based automatic modeling program for nuclear and radiation transport simulation (MCAM). Its correctness has been demonstrated. (authors)
Automatic modeling for the Monte Carlo transport code Geant4
International Nuclear Information System (INIS)
Nie Fanzhi; Hu Liqin; Wang Guozhong; Wang Dianxi; Wu Yican; Wang Dong; Long Pengcheng; FDS Team
2015-01-01
Geant4 is a widely used Monte Carlo transport simulation package. Its geometry models could be described in Geometry Description Markup Language (GDML), but it is time-consuming and error-prone to describe the geometry models manually. This study implemented the conversion between computer-aided design (CAD) geometry models and GDML models. This method has been Studied based on Multi-Physics Coupling Analysis Modeling Program (MCAM). The tests, including FDS-Ⅱ model, demonstrated its accuracy and feasibility. (authors)
Automatic modeling for the monte carlo transport TRIPOLI code
International Nuclear Information System (INIS)
Zhang Junjun; Zeng Qin; Wu Yican; Wang Guozhong; FDS Team
2010-01-01
TRIPOLI, developed by CEA, France, is Monte Carlo particle transport simulation code. It has been widely applied to nuclear physics, shielding design, evaluation of nuclear safety. However, it is time-consuming and error-prone to manually describe the TRIPOLI input file. This paper implemented bi-directional conversion between CAD model and TRIPOLI model. Its feasibility and efficiency have been demonstrated by several benchmarking examples. (authors)
CAD-based Monte Carlo automatic modeling method based on primitive solid
International Nuclear Information System (INIS)
Wang, Dong; Song, Jing; Yu, Shengpeng; Long, Pengcheng; Wang, Yongliang
2016-01-01
Highlights: • We develop a method which bi-convert between CAD model and primitive solid. • This method was improved from convert method between CAD model and half space. • This method was test by ITER model and validated the correctness and efficiency. • This method was integrated in SuperMC which could model for SuperMC and Geant4. - Abstract: Monte Carlo method has been widely used in nuclear design and analysis, where geometries are described with primitive solids. However, it is time consuming and error prone to describe a primitive solid geometry, especially for a complicated model. To reuse the abundant existed CAD models and conveniently model with CAD modeling tools, an automatic modeling method for accurate prompt modeling between CAD model and primitive solid is needed. An automatic modeling method for Monte Carlo geometry described by primitive solid was developed which could bi-convert between CAD model and Monte Carlo geometry represented by primitive solids. While converting from CAD model to primitive solid model, the CAD model was decomposed into several convex solid sets, and then corresponding primitive solids were generated and exported. While converting from primitive solid model to the CAD model, the basic primitive solids were created and related operation was done. This method was integrated in the SuperMC and was benchmarked with ITER benchmark model. The correctness and efficiency of this method were demonstrated.
Automatic modeling for the Monte Carlo transport code Geant4 in MCAM
International Nuclear Information System (INIS)
Nie Fanzhi; Hu Liqin; Wang Guozhong; Wang Dianxi; Wu Yican; Wang Dong; Long Pengcheng; FDS Team
2014-01-01
Geant4 is a widely used Monte Carlo transport simulation package. Its geometry models could be described in geometry description markup language (GDML), but it is time-consuming and error-prone to describe the geometry models manually. This study implemented the conversion between computer-aided design (CAD) geometry models and GDML models. The conversion program was integrated into Multi-Physics Coupling Analysis Modeling Program (MCAM). The tests, including FDS-Ⅱ model, demonstrated its accuracy and feasibility. (authors)
International Nuclear Information System (INIS)
Ibrahim, Ahmad M.; Wilson, Paul P.H.; Sawan, Mohamed E.; Mosher, Scott W.; Peplow, Douglas E.; Wagner, John C.; Evans, Thomas M.; Grove, Robert E.
2015-01-01
The CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques dramatically increase the efficiency of neutronics modeling, but their use in the accurate design analysis of very large and geometrically complex nuclear systems has been limited by the large number of processors and memory requirements for their preliminary deterministic calculations and final Monte Carlo calculation. Three mesh adaptivity algorithms were developed to reduce the memory requirements of CADIS and FW-CADIS without sacrificing their efficiency improvement. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as much geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility. Using these algorithms resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation and, additionally, increased the efficiency of the Monte Carlo simulation by a factor of at least 3.4. The three algorithms enabled this difficult calculation to be accurately solved using an FW-CADIS simulation on a regular computer cluster, eliminating the need for a world-class super computer
Directory of Open Access Journals (Sweden)
Atsushi M. Ito
2017-08-01
Full Text Available The diffusion process of hydrogen and helium in plasma-facing material depends on the grain boundary structures. Whether a grain boundary accelerates or limits the diffusion speed of these impurity atoms is not well understood. In the present work, we proposed the automatic modeling of a kinetic Monte-Carlo (KMC simulation to treat an asymmetric grain boundary structure that corresponds to target samples used in fusion material experiments for retention and permeation. In this method, local minimum energy sites and migration paths for impurity atoms in the grain boundary structure are automatically found using localized molecular dynamics. The grain boundary structure was generated with the Voronoi diagram. Consequently, we demonstrate that the KMC simulation for the diffusion process of impurity atoms in the generated grain boundary structure of tungsten material can be performed.
Energy Technology Data Exchange (ETDEWEB)
Qin, N; Shen, C; Tian, Z; Jiang, S; Jia, X [UT Southwestern Medical Ctr, Dallas, TX (United States)
2016-06-15
Purpose: Monte Carlo (MC) simulation is typically regarded as the most accurate dose calculation method for proton therapy. Yet for real clinical cases, the overall accuracy also depends on that of the MC beam model. Commissioning a beam model to faithfully represent a real beam requires finely tuning a set of model parameters, which could be tedious given the large number of pencil beams to commmission. This abstract reports an automatic beam-model commissioning method for pencil-beam scanning proton therapy via an optimization approach. Methods: We modeled a real pencil beam with energy and spatial spread following Gaussian distributions. Mean energy, and energy and spatial spread are model parameters. To commission against a real beam, we first performed MC simulations to calculate dose distributions of a set of ideal (monoenergetic, zero-size) pencil beams. Dose distribution for a real pencil beam is hence linear superposition of doses for those ideal pencil beams with weights in the Gaussian form. We formulated the commissioning task as an optimization problem, such that the calculated central axis depth dose and lateral profiles at several depths match corresponding measurements. An iterative algorithm combining conjugate gradient method and parameter fitting was employed to solve the optimization problem. We validated our method in simulation studies. Results: We calculated dose distributions for three real pencil beams with nominal energies 83, 147 and 199 MeV using realistic beam parameters. These data were regarded as measurements and used for commission. After commissioning, average difference in energy and beam spread between determined values and ground truth were 4.6% and 0.2%. With the commissioned model, we recomputed dose. Mean dose differences from measurements were 0.64%, 0.20% and 0.25%. Conclusion: The developed automatic MC beam-model commissioning method for pencil-beam scanning proton therapy can determine beam model parameters with
Automatic fission source convergence criteria for Monte Carlo criticality calculations
International Nuclear Information System (INIS)
Shim, Hyung Jin; Kim, Chang Hyo
2005-01-01
The Monte Carlo criticality calculations for the multiplication factor and the power distribution in a nuclear system require knowledge of stationary or fundamental-mode fission source distribution (FSD) in the system. Because it is a priori unknown, so-called inactive cycle Monte Carlo (MC) runs are performed to determine it. The inactive cycle MC runs should be continued until the FSD converges to the stationary FSD. Obviously, if one stops them prematurely, the MC calculation results may have biases because the followup active cycles may be run with the non-stationary FSD. Conversely, if one performs the inactive cycle MC runs more than necessary, one is apt to waste computing time because inactive cycle MC runs are used to elicit the fundamental-mode FSD only. In the absence of suitable criteria for terminating the inactive cycle MC runs, one cannot but rely on empiricism in deciding how many inactive cycles one should conduct for a given problem. Depending on the problem, this may introduce biases into Monte Carlo estimates of the parameters one tries to calculate. The purpose of this paper is to present new fission source convergence criteria designed for the automatic termination of inactive cycle MC runs
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.; Dean, D.J.; Langanke, K.
1997-01-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; the resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo (SMMC) methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, the thermal and rotational behavior of rare-earth and γ-soft nuclei, and the calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. (orig.)
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.
1996-01-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of γ-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs
MDTS: automatic complex materials design using Monte Carlo tree search
Dieb, Thaer M.; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji
2017-12-01
Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.
Automatic differentiation algorithms in model analysis
Huiskes, M.J.
2002-01-01
Title: Automatic differentiation algorithms in model analysis
Author: M.J. Huiskes
Date: 19 March, 2002
In this thesis automatic differentiation algorithms and derivative-based methods
Automatic terrain modeling using transfinite element analysis
Collier, Nathan; Calo, Victor M.
2010-01-01
An automatic procedure for modeling terrain is developed based on L2 projection-based interpolation of discrete terrain data onto transfinite function spaces. The function space is refined automatically by the use of image processing techniques
Monte Carlo simulation of Markov unreliability models
International Nuclear Information System (INIS)
Lewis, E.E.; Boehm, F.
1984-01-01
A Monte Carlo method is formulated for the evaluation of the unrealibility of complex systems with known component failure and repair rates. The formulation is in terms of a Markov process allowing dependences between components to be modeled and computational efficiencies to be achieved in the Monte Carlo simulation. Two variance reduction techniques, forced transition and failure biasing, are employed to increase computational efficiency of the random walk procedure. For an example problem these result in improved computational efficiency by more than three orders of magnitudes over analog Monte Carlo. The method is generalized to treat problems with distributed failure and repair rate data, and a batching technique is introduced and shown to result in substantial increases in computational efficiency for an example problem. A method for separating the variance due to the data uncertainty from that due to the finite number of random walks is presented. (orig.)
Shell model the Monte Carlo way
International Nuclear Information System (INIS)
Ormand, W.E.
1995-01-01
The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined
Shell model the Monte Carlo way
Energy Technology Data Exchange (ETDEWEB)
Ormand, W.E.
1995-03-01
The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined.
Automatic Monte-Carlo tuning for minimum bias events at the LHC
Energy Technology Data Exchange (ETDEWEB)
Kama, Sami
2010-06-22
The Large Hadron Collider near Geneva Switzerland will ultimately collide protons at a center-of-mass energy of 14 TeV and 40 MHz bunch crossing rate with a luminosity of L=10{sup 34} cm{sup -2}s{sup -1}. At each bunch crossing about 20 soft proton-proton interactions are expected to happen. In order to study new phenomena and improve our current knowledge of the physics these events must be understood. However, the physics of soft interactions are not completely known at such high energies. Different phenomenological models, trying to explain these interactions, are implemented in several Monte-Carlo (MC) programs such as PYTHIA, PHOJET and EPOS. Some parameters in such MC programs can be tuned to improve the agreement with the data. In this thesis a new method for tuning the MC programs, based on Genetic Algorithms and distributed analysis techniques have been presented. This method represents the first and fully automated MC tuning technique that is based on true MC distributions. It is an alternative to parametrization-based automatic tuning. This new method is used in finding new tunes for PYTHIA 6 and 8. These tunes are compared to the tunes found by alternative methods, such as the PROFESSOR framework and manual tuning, and found to be equivalent or better. Charged particle multiplicity, dN{sub ch}/d{eta}, Lorentz-invariant yield, transverse momentum and mean transverse momentum distributions at various center-of-mass energies are generated using default tunes of EPOS, PHOJET and the Genetic Algorithm tunes of PYTHIA 6 and 8. These distributions are compared to measurements from UA5, CDF, CMS and ATLAS in order to investigate the best model available. Their predictions for the ATLAS detector at LHC energies have been investigated both with generator level and full detector simulation studies. Comparison with the data did not favor any model implemented in the generators, but EPOS is found to describe investigated distributions better. New data from ATLAS and
Automatic Monte-Carlo tuning for minimum bias events at the LHC
International Nuclear Information System (INIS)
Kama, Sami
2010-01-01
The Large Hadron Collider near Geneva Switzerland will ultimately collide protons at a center-of-mass energy of 14 TeV and 40 MHz bunch crossing rate with a luminosity of L=10 34 cm -2 s -1 . At each bunch crossing about 20 soft proton-proton interactions are expected to happen. In order to study new phenomena and improve our current knowledge of the physics these events must be understood. However, the physics of soft interactions are not completely known at such high energies. Different phenomenological models, trying to explain these interactions, are implemented in several Monte-Carlo (MC) programs such as PYTHIA, PHOJET and EPOS. Some parameters in such MC programs can be tuned to improve the agreement with the data. In this thesis a new method for tuning the MC programs, based on Genetic Algorithms and distributed analysis techniques have been presented. This method represents the first and fully automated MC tuning technique that is based on true MC distributions. It is an alternative to parametrization-based automatic tuning. This new method is used in finding new tunes for PYTHIA 6 and 8. These tunes are compared to the tunes found by alternative methods, such as the PROFESSOR framework and manual tuning, and found to be equivalent or better. Charged particle multiplicity, dN ch /dη, Lorentz-invariant yield, transverse momentum and mean transverse momentum distributions at various center-of-mass energies are generated using default tunes of EPOS, PHOJET and the Genetic Algorithm tunes of PYTHIA 6 and 8. These distributions are compared to measurements from UA5, CDF, CMS and ATLAS in order to investigate the best model available. Their predictions for the ATLAS detector at LHC energies have been investigated both with generator level and full detector simulation studies. Comparison with the data did not favor any model implemented in the generators, but EPOS is found to describe investigated distributions better. New data from ATLAS and CMS show higher
Monte Carlo models: Quo vadimus?
Energy Technology Data Exchange (ETDEWEB)
Wang, Xin-Nian
2001-01-01
Coherence, multiple scattering and the interplay between soft and hard processes are discussed. These physics phenomena are essential for understanding the nuclear dependences of rapidity density and p{sub T} spectra in high-energy heavy-ion collisions. The RHIC data have shown the onset of hard processes and indications of high p{sub T} spectra suppression due to parton energy loss. Within the pQCD parton model, the combination of azimuthal anisotropy ({nu}{sub 2}) and hadron spectra suppression at large p{sub T} can help one to determine the initial gluon density in heavy-ion collisions at RHIC.
Monte Carlo models: Quo vadimus?
International Nuclear Information System (INIS)
Wang, Xin-Nian
2001-01-01
Coherence, multiple scattering and the interplay between soft and hard processes are discussed. These physics phenomena are essential for understanding the nuclear dependences of rapidity density and p T spectra in high-energy heavy-ion collisions. The RHIC data have shown the onset of hard processes and indications of high p T spectra suppression due to parton energy loss. Within the pQCD parton model, the combination of azimuthal anisotropy (ν 2 ) and hadron spectra suppression at large p T can help one to determine the initial gluon density in heavy-ion collisions at RHIC
Development of ANJOYMC Program for Automatic Generation of Monte Carlo Cross Section Libraries
International Nuclear Information System (INIS)
Kim, Kang Seog; Lee, Chung Chan
2007-03-01
The NJOY code developed at Los Alamos National Laboratory is to generate the cross section libraries in ACE format for the Monte Carlo codes such as MCNP and McCARD by processing the evaluated nuclear data in ENDF/B format. It takes long time to prepare all the NJOY input files for hundreds of nuclides with various temperatures, and there can be some errors in the input files. In order to solve these problems, ANJOYMC program has been developed. By using a simple user input deck, this program is not only to generate all the NJOY input files automatically, but also to generate a batch file to perform all the NJOY calculations. The ANJOYMC program is written in Fortran90 and can be executed under the WINDOWS and LINUX operating systems in Personal Computer. Cross section libraries in ACE format can be generated in a short time and without an error by using a simple user input deck
Application of MCAM in generating Monte Carlo model for ITER port limiter
International Nuclear Information System (INIS)
Lu Lei; Li Ying; Ding Aiping; Zeng Qin; Huang Chenyu; Wu Yican
2007-01-01
On the basis of the pre-processing and conversion functions supplied by MCAM (Monte-Carlo Particle Transport Calculated Automatic Modeling System), this paper performed the generation of ITER Port Limiter MC (Monte-Carlo) calculation model from the CAD engineering model. The result was validated by using reverse function of MCAM and MCNP PLOT 2D cross-section drawing program. the successful application of MCAM to ITER Port Limiter demonstrates that MCAM is capable of dramatically increasing the efficiency and accuracy to generate MC calculation models from CAD engineering models with complex geometry comparing with the traditional manual modeling method. (authors)
Image based Monte Carlo modeling for computational phantom
International Nuclear Information System (INIS)
Cheng, M.; Wang, W.; Zhao, K.; Fan, Y.; Long, P.; Wu, Y.
2013-01-01
Full text of the publication follows. The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verification of the models for Monte Carlo (MC) simulation are very tedious, error-prone and time-consuming. In addition, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling. The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients (Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection. (authors)
A neurocomputational model of automatic sequence production.
Helie, Sebastien; Roeder, Jessica L; Vucovich, Lauren; Rünger, Dennis; Ashby, F Gregory
2015-07-01
Most behaviors unfold in time and include a sequence of submovements or cognitive activities. In addition, most behaviors are automatic and repeated daily throughout life. Yet, relatively little is known about the neurobiology of automatic sequence production. Past research suggests a gradual transfer from the associative striatum to the sensorimotor striatum, but a number of more recent studies challenge this role of the BG in automatic sequence production. In this article, we propose a new neurocomputational model of automatic sequence production in which the main role of the BG is to train cortical-cortical connections within the premotor areas that are responsible for automatic sequence production. The new model is used to simulate four different data sets from human and nonhuman animals, including (1) behavioral data (e.g., RTs), (2) electrophysiology data (e.g., single-neuron recordings), (3) macrostructure data (e.g., TMS), and (4) neurological circuit data (e.g., inactivation studies). We conclude with a comparison of the new model with existing models of automatic sequence production and discuss a possible new role for the BG in automaticity and its implication for Parkinson's disease.
International Nuclear Information System (INIS)
Tian, Zhen; Jia, Xun; Jiang, Steve B; Graves, Yan Jiang
2014-01-01
Monte Carlo (MC) simulation is commonly considered as the most accurate method for radiation dose calculations. Commissioning of a beam model in the MC code against a clinical linear accelerator beam is of crucial importance for its clinical implementation. In this paper, we propose an automatic commissioning method for our GPU-based MC dose engine, gDPM. gDPM utilizes a beam model based on a concept of phase-space-let (PSL). A PSL contains a group of particles that are of the same type and close in space and energy. A set of generic PSLs was generated by splitting a reference phase-space file. Each PSL was associated with a weighting factor, and in dose calculations the particle carried a weight corresponding to the PSL where it was from. Dose for each PSL in water was pre-computed, and hence the dose in water for a whole beam under a given set of PSL weighting factors was the weighted sum of the PSL doses. At the commissioning stage, an optimization problem was solved to adjust the PSL weights in order to minimize the difference between the calculated dose and measured one. Symmetry and smoothness regularizations were utilized to uniquely determine the solution. An augmented Lagrangian method was employed to solve the optimization problem. To validate our method, a phase-space file of a Varian TrueBeam 6 MV beam was used to generate the PSLs for 6 MV beams. In a simulation study, we commissioned a Siemens 6 MV beam on which a set of field-dependent phase-space files was available. The dose data of this desired beam for different open fields and a small off-axis open field were obtained by calculating doses using these phase-space files. The 3D γ-index test passing rate within the regions with dose above 10% of d max dose for those open fields tested was improved averagely from 70.56 to 99.36% for 2%/2 mm criteria and from 32.22 to 89.65% for 1%/1 mm criteria. We also tested our commissioning method on a six-field head-and-neck cancer IMRT plan. The
Automatic terrain modeling using transfinite element analysis
Collier, Nathan
2010-05-31
An automatic procedure for modeling terrain is developed based on L2 projection-based interpolation of discrete terrain data onto transfinite function spaces. The function space is refined automatically by the use of image processing techniques to detect regions of high error and the flexibility of the transfinite interpolation to add degrees of freedom to these areas. Examples are shown of a section of the Palo Duro Canyon in northern Texas.
Radiation Modeling with Direct Simulation Monte Carlo
Carlson, Ann B.; Hassan, H. A.
1991-01-01
Improvements in the modeling of radiation in low density shock waves with direct simulation Monte Carlo (DSMC) are the subject of this study. A new scheme to determine the relaxation collision numbers for excitation of electronic states is proposed. This scheme attempts to move the DSMC programs toward a more detailed modeling of the physics and more reliance on available rate data. The new method is compared with the current modeling technique and both techniques are compared with available experimental data. The differences in the results are evaluated. The test case is based on experimental measurements from the AVCO-Everett Research Laboratory electric arc-driven shock tube of a normal shock wave in air at 10 km/s and .1 Torr. The new method agrees with the available data as well as the results from the earlier scheme and is more easily extrapolated to di erent ow conditions.
Monte Carlo methods and models in finance and insurance
Korn, Ralf; Kroisandt, Gerald
2010-01-01
Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...
Automatic Flight Controller With Model Inversion
Meyer, George; Smith, G. Allan
1992-01-01
Automatic digital electronic control system based on inverse-model-follower concept being developed for proposed vertical-attitude-takeoff-and-landing airplane. Inverse-model-follower control places inverse mathematical model of dynamics of controlled plant in series with control actuators of controlled plant so response of combination of model and plant to command is unity. System includes feedback to compensate for uncertainties in mathematical model and disturbances imposed from without.
Monte Carlo modelling of TRIGA research reactor
El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.
2010-10-01
The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucléaires de la Maâmora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S( α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file "up259". The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.
Next Generation Model 8800 Automatic TLD Reader
International Nuclear Information System (INIS)
Velbeck, K.J.; Streetz, K.L.; Rotunda, J.E.
1999-01-01
BICRON NE has developed an advanced version of the Model 8800 Automatic TLD Reader. Improvements in the reader include a Windows NT TM -based operating system and a Pentium microprocessor for the host controller, a servo-controlled transport, a VGA display, mouse control, and modular assembly. This high capacity reader will automatically read fourteen hundred TLD Cards in one loading. Up to four elements in a card can be heated without mechanical contact, using hot nitrogen gas. Improvements in performance include an increased throughput rate and more precise card positioning. Operation is simplified through easy-to-read Windows-type screens. Glow curves are displayed graphically along with light intensity, temperature, and channel scaling. Maintenance and diagnostic aids are included for easier troubleshooting. A click of a mouse will command actions that are displayed in easy-to-understand English words. Available options include an internal 90 Sr irradiator, automatic TLD calibration, and two different extremity monitoring modes. Results from testing include reproducibility, reader stability, linearity, detection threshold, residue, primary power supply voltage and frequency, transient voltage, drop testing, and light leakage. (author)
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.; Liang, Faming; Zhou, Lan; Carroll, Raymond J.
2010-01-01
model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order
forecasting with nonlinear time series model: a monte-carlo
African Journals Online (AJOL)
PUBLICATIONS1
Carlo method of forecasting using a special nonlinear time series model, called logistic smooth transition ... We illustrate this new method using some simulation ..... in MATLAB 7.5.0. ... process (DGP) using the logistic smooth transi-.
CAD-based automatic modeling method for Geant4 geometry model through MCAM
International Nuclear Information System (INIS)
Wang, D.; Nie, F.; Wang, G.; Long, P.; LV, Z.
2013-01-01
The full text of publication follows. Geant4 is a widely used Monte Carlo transport simulation package. Before calculating using Geant4, the calculation model need be established which could be described by using Geometry Description Markup Language (GDML) or C++ language. However, it is time-consuming and error-prone to manually describe the models by GDML. Automatic modeling methods have been developed recently, but there are some problems that exist in most present modeling programs, specially some of them were not accurate or adapted to specifically CAD format. To convert the GDML format models to CAD format accurately, a Geant4 Computer Aided Design (CAD) based modeling method was developed for automatically converting complex CAD geometry model into GDML geometry model. The essence of this method was dealing with CAD model represented with boundary representation (B-REP) and GDML model represented with constructive solid geometry (CSG). At first, CAD model was decomposed to several simple solids which had only one close shell. And then the simple solid was decomposed to convex shell set. Then corresponding GDML convex basic solids were generated by the boundary surfaces getting from the topological characteristic of a convex shell. After the generation of these solids, GDML model was accomplished with series boolean operations. This method was adopted in CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport (MCAM), and tested with several models including the examples in Geant4 install package. The results showed that this method could convert standard CAD model accurately, and can be used for Geant4 automatic modeling. (authors)
Studies of Monte Carlo Modelling of Jets at ATLAS
Kar, Deepak; The ATLAS collaboration
2017-01-01
The predictions of different Monte Carlo generators for QCD jet production, both in multijets and for jets produced in association with other objects, are presented. Recent improvements in showering Monte Carlos provide new tools for assessing systematic uncertainties associated with these jets. Studies of the dependence of physical observables on the choice of shower tune parameters and new prescriptions for assessing systematic uncertainties associated with the choice of shower model and tune are presented.
Monte Carlo modelling for neutron guide losses
International Nuclear Information System (INIS)
Cser, L.; Rosta, L.; Toeroek, Gy.
1989-09-01
In modern research reactors, neutron guides are commonly used for beam conducting. The neutron guide is a well polished or equivalently smooth glass tube covered inside by sputtered or evaporated film of natural Ni or 58 Ni isotope where the neutrons are totally reflected. A Monte Carlo calculation was carried out to establish the real efficiency and the spectral as well as spatial distribution of the neutron beam at the end of a glass mirror guide. The losses caused by mechanical inaccuracy and mirror quality were considered and the effects due to the geometrical arrangement were analyzed. (author) 2 refs.; 2 figs
Automatic variance reduction for Monte Carlo simulations via the local importance function transform
International Nuclear Information System (INIS)
Turner, S.A.
1996-02-01
The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of ''real'' particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ''black box''. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases
Convex-based void filling method for CAD-based Monte Carlo geometry modeling
International Nuclear Information System (INIS)
Yu, Shengpeng; Cheng, Mengyun; Song, Jing; Long, Pengcheng; Hu, Liqin
2015-01-01
Highlights: • We present a new void filling method named CVF for CAD based MC geometry modeling. • We describe convex based void description based and quality-based space subdivision. • The results showed improvements provided by CVF for both modeling and MC calculation efficiency. - Abstract: CAD based automatic geometry modeling tools have been widely applied to generate Monte Carlo (MC) calculation geometry for complex systems according to CAD models. Automatic void filling is one of the main functions in the CAD based MC geometry modeling tools, because the void space between parts in CAD models is traditionally not modeled while MC codes such as MCNP need all the problem space to be described. A dedicated void filling method, named Convex-based Void Filling (CVF), is proposed in this study for efficient void filling and concise void descriptions. The method subdivides all the problem space into disjointed regions using Quality based Subdivision (QS) and describes the void space in each region with complementary descriptions of the convex volumes intersecting with that region. It has been implemented in SuperMC/MCAM, the Multiple-Physics Coupling Analysis Modeling Program, and tested on International Thermonuclear Experimental Reactor (ITER) Alite model. The results showed that the new method reduced both automatic modeling time and MC calculation time
Genetic Programming for Automatic Hydrological Modelling
Chadalawada, Jayashree; Babovic, Vladan
2017-04-01
One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach
Aspects of perturbative QCD in Monte Carlo shower models
International Nuclear Information System (INIS)
Gottschalk, T.D.
1986-01-01
The perturbative QCD content of Monte Carlo models for high energy hadron-hadron scattering is examined. Particular attention is given to the recently developed backwards evolution formalism for initial state parton showers, and the merging of parton shower evolution with hard scattering cross sections. Shower estimates of K-factors are discussed, and a simple scheme is presented for incorporating 2 → QCD cross sections into shower model calculations without double counting. Additional issues in the development of hard scattering Monte Carlo models are summarized. 69 references, 20 figures
Hidden Markov models in automatic speech recognition
Wrzoskowicz, Adam
1993-11-01
This article describes a method for constructing an automatic speech recognition system based on hidden Markov models (HMMs). The author discusses the basic concepts of HMM theory and the application of these models to the analysis and recognition of speech signals. The author provides algorithms which make it possible to train the ASR system and recognize signals on the basis of distinct stochastic models of selected speech sound classes. The author describes the specific components of the system and the procedures used to model and recognize speech. The author discusses problems associated with the choice of optimal signal detection and parameterization characteristics and their effect on the performance of the system. The author presents different options for the choice of speech signal segments and their consequences for the ASR process. The author gives special attention to the use of lexical, syntactic, and semantic information for the purpose of improving the quality and efficiency of the system. The author also describes an ASR system developed by the Speech Acoustics Laboratory of the IBPT PAS. The author discusses the results of experiments on the effect of noise on the performance of the ASR system and describes methods of constructing HMM's designed to operate in a noisy environment. The author also describes a language for human-robot communications which was defined as a complex multilevel network from an HMM model of speech sounds geared towards Polish inflections. The author also added mandatory lexical and syntactic rules to the system for its communications vocabulary.
Monte Carlo simulation models of breeding-population advancement.
J.N. King; G.R. Johnson
1993-01-01
Five generations of population improvement were modeled using Monte Carlo simulations. The model was designed to address questions that are important to the development of an advanced generation breeding population. Specifically we addressed the effects on both gain and effective population size of different mating schemes when creating a recombinant population for...
Towards a Revised Monte Carlo Neutral Particle Surface Interaction Model
International Nuclear Information System (INIS)
Stotler, D.P.
2005-01-01
The components of the neutral- and plasma-surface interaction model used in the Monte Carlo neutral transport code DEGAS 2 are reviewed. The idealized surfaces and processes handled by that model are inadequate for accurately simulating neutral transport behavior in present day and future fusion devices. We identify some of the physical processes missing from the model, such as mixed materials and implanted hydrogen, and make some suggestions for improving the model
Applying Hierarchical Model Calibration to Automatically Generated Items.
Williamson, David M.; Johnson, Matthew S.; Sinharay, Sandip; Bejar, Isaac I.
This study explored the application of hierarchical model calibration as a means of reducing, if not eliminating, the need for pretesting of automatically generated items from a common item model prior to operational use. Ultimately the successful development of automatic item generation (AIG) systems capable of producing items with highly similar…
Calibration and Monte Carlo modelling of neutron long counters
Tagziria, H
2000-01-01
The Monte Carlo technique has become a very powerful tool in radiation transport as full advantage is taken of enhanced cross-section data, more powerful computers and statistical techniques, together with better characterisation of neutron and photon source spectra. At the National Physical Laboratory, calculations using the Monte Carlo radiation transport code MCNP-4B have been combined with accurate measurements to characterise two long counters routinely used to standardise monoenergetic neutron fields. New and more accurate response function curves have been produced for both long counters. A novel approach using Monte Carlo methods has been developed, validated and used to model the response function of the counters and determine more accurately their effective centres, which have always been difficult to establish experimentally. Calculations and measurements agree well, especially for the De Pangher long counter for which details of the design and constructional material are well known. The sensitivit...
Profit Forecast Model Using Monte Carlo Simulation in Excel
Directory of Open Access Journals (Sweden)
Petru BALOGH
2014-01-01
Full Text Available Profit forecast is very important for any company. The purpose of this study is to provide a method to estimate the profit and the probability of obtaining the expected profit. Monte Carlo methods are stochastic techniques–meaning they are based on the use of random numbers and probability statistics to investigate problems. Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities they will occur for any choice of action. Our example of Monte Carlo simulation in Excel will be a simplified profit forecast model. Each step of the analysis will be described in detail. The input data for the case presented: the number of leads per month, the percentage of leads that result in sales, , the cost of a single lead, the profit per sale and fixed cost, allow obtaining profit and associated probabilities of achieving.
Monte Carlo investigation of the one-dimensional Potts model
International Nuclear Information System (INIS)
Karma, A.S.; Nolan, M.J.
1983-01-01
Monte Carlo results are presented for a variety of one-dimensional dynamical q-state Potts models. Our calculations confirm the expected universal value z = 2 for the dynamic scaling exponent. Our results also indicate that an increase in q at fixed correlation length drives the dynamics into the scaling regime
A novel Monte Carlo approach to hybrid local volatility models
A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)
2017-01-01
textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.
Yet another Monte Carlo study of the Schwinger model
International Nuclear Information System (INIS)
Sogo, K.; Kimura, N.
1986-01-01
Some methodological improvements are introduced in the quantum Monte Carlo simulation of the 1 + 1 dimensional quantum electrodynamics (the Schwinger model). Properties at finite temperatures are investigated, concentrating on the existence of the chirality transition and of the deconfinement transition. (author)
Reservoir Modeling Combining Geostatistics with Markov Chain Monte Carlo Inversion
DEFF Research Database (Denmark)
Zunino, Andrea; Lange, Katrine; Melnikova, Yulia
2014-01-01
We present a study on the inversion of seismic reflection data generated from a synthetic reservoir model. Our aim is to invert directly for rock facies and porosity of the target reservoir zone. We solve this inverse problem using a Markov chain Monte Carlo (McMC) method to handle the nonlinear...
Yet another Monte Carlo study of the Schwinger model
International Nuclear Information System (INIS)
Sogo, K.; Kimura, N.
1986-03-01
Some methodological improvements are introduced in the quantum Monte Carlo simulation of the 1 + 1 dimensional quantum electrodynamics (the Schwinger model). Properties at finite temperatures are investigated, concentrating on the existence of the chirality transition and of the deconfinement transition. (author)
De Geyter, G.; Baes, M.; Fritz, J.; Camps, P.
2013-02-01
We present FitSKIRT, a method to efficiently fit radiative transfer models to UV/optical images of dusty galaxies. These images have the advantage that they have better spatial resolution compared to FIR/submm data. FitSKIRT uses the GAlib genetic algorithm library to optimize the output of the SKIRT Monte Carlo radiative transfer code. Genetic algorithms prove to be a valuable tool in handling the multi- dimensional search space as well as the noise induced by the random nature of the Monte Carlo radiative transfer code. FitSKIRT is tested on artificial images of a simulated edge-on spiral galaxy, where we gradually increase the number of fitted parameters. We find that we can recover all model parameters, even if all 11 model parameters are left unconstrained. Finally, we apply the FitSKIRT code to a V-band image of the edge-on spiral galaxy NGC 4013. This galaxy has been modeled previously by other authors using different combinations of radiative transfer codes and optimization methods. Given the different models and techniques and the complexity and degeneracies in the parameter space, we find reasonable agreement between the different models. We conclude that the FitSKIRT method allows comparison between different models and geometries in a quantitative manner and minimizes the need of human intervention and biasing. The high level of automation makes it an ideal tool to use on larger sets of observed data.
The Role of Item Models in Automatic Item Generation
Gierl, Mark J.; Lai, Hollis
2012-01-01
Automatic item generation represents a relatively new but rapidly evolving research area where cognitive and psychometric theories are used to produce tests that include items generated using computer technology. Automatic item generation requires two steps. First, test development specialists create item models, which are comparable to templates…
Monte Carlo Euler approximations of HJM term structure financial models
Björk, Tomas
2012-11-22
We present Monte Carlo-Euler methods for a weak approximation problem related to the Heath-Jarrow-Morton (HJM) term structure model, based on Itô stochastic differential equations in infinite dimensional spaces, and prove strong and weak error convergence estimates. The weak error estimates are based on stochastic flows and discrete dual backward problems, and they can be used to identify different error contributions arising from time and maturity discretization as well as the classical statistical error due to finite sampling. Explicit formulas for efficient computation of sharp error approximation are included. Due to the structure of the HJM models considered here, the computational effort devoted to the error estimates is low compared to the work to compute Monte Carlo solutions to the HJM model. Numerical examples with known exact solution are included in order to show the behavior of the estimates. © 2012 Springer Science+Business Media Dordrecht.
Monte Carlo Euler approximations of HJM term structure financial models
Bjö rk, Tomas; Szepessy, Anders; Tempone, Raul; Zouraris, Georgios E.
2012-01-01
We present Monte Carlo-Euler methods for a weak approximation problem related to the Heath-Jarrow-Morton (HJM) term structure model, based on Itô stochastic differential equations in infinite dimensional spaces, and prove strong and weak error convergence estimates. The weak error estimates are based on stochastic flows and discrete dual backward problems, and they can be used to identify different error contributions arising from time and maturity discretization as well as the classical statistical error due to finite sampling. Explicit formulas for efficient computation of sharp error approximation are included. Due to the structure of the HJM models considered here, the computational effort devoted to the error estimates is low compared to the work to compute Monte Carlo solutions to the HJM model. Numerical examples with known exact solution are included in order to show the behavior of the estimates. © 2012 Springer Science+Business Media Dordrecht.
Creation of voxel-based models for paediatric dosimetry from automatic segmentation methods
International Nuclear Information System (INIS)
Acosta, O.; Li, R.; Ourselin, S.; Caon, M.
2006-01-01
Full text: The first computational models representing human anatomy were mathematical phantoms, but still far from accurate representations of human body. These models have been used with radiation transport codes (Monte Carlo) to estimate organ doses from radiological procedures. Although new medical imaging techniques have recently allowed the construction of voxel-based models based on the real anatomy, few children models from individual CT or MRI data have been reported [1,3]. For pediatric dosimetry purposes, a large range of voxel models by ages is required since scaling the anatomy from existing models is not sufficiently accurate. The small number of models available arises from the small number of CT or MRI data sets of children available and the long amount of time required to segment the data sets. The existing models have been constructed by manual segmentation slice by slice and using simple thresholding techniques. In medical image segmentation, considerable difficulties appear when applying classical techniques like thresholding or simple edge detection. Until now, any evidence of more accurate or near-automatic methods used in construction of child voxel models exists. We aim to construct a range of pediatric voxel models, integrating automatic or semi-automatic 3D segmentation techniques. In this paper we present the first stage of this work using pediatric CT data.
Discrete Model Reference Adaptive Control System for Automatic Profiling Machine
Directory of Open Access Journals (Sweden)
Peng Song
2012-01-01
Full Text Available Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules are proven. The results of simulation show that adaptive control system has favorable dynamic performances.
Monte Carlo Modelling of Mammograms : Development and Validation
Energy Technology Data Exchange (ETDEWEB)
Spyrou, G; Panayiotakis, G [Univercity of Patras, School of Medicine, Medical Physics Department, 265 00 Patras (Greece); Bakas, A [Technological Educational Institution of Athens, Department of Radiography, 122 10 Athens (Greece); Tzanakos, G [University of Athens, Department of Physics, Divission of Nuclear and Particle Physics, 157 71 Athens (Greece)
1999-12-31
A software package using Monte Carlo methods has been developed for the simulation of x-ray mammography. A simplified geometry of the mammographic apparatus has been considered along with the software phantom of compressed breast. This phantom may contain inhomogeneities of various compositions and sizes at any point. Using this model one can produce simulated mammograms. Results that demonstrate the validity of this simulation are presented. (authors) 16 refs, 4 figs
GPU based Monte Carlo for PET image reconstruction: detector modeling
International Nuclear Information System (INIS)
Légrády; Cserkaszky, Á; Lantos, J.; Patay, G.; Bükki, T.
2011-01-01
Monte Carlo (MC) calculations and Graphical Processing Units (GPUs) are almost like the dedicated hardware designed for the specific task given the similarities between visible light transport and neutral particle trajectories. A GPU based MC gamma transport code has been developed for Positron Emission Tomography iterative image reconstruction calculating the projection from unknowns to data at each iteration step taking into account the full physics of the system. This paper describes the simplified scintillation detector modeling and its effect on convergence. (author)
Monte Carlo Modelling of Mammograms : Development and Validation
International Nuclear Information System (INIS)
Spyrou, G.; Panayiotakis, G.; Bakas, A.; Tzanakos, G.
1998-01-01
A software package using Monte Carlo methods has been developed for the simulation of x-ray mammography. A simplified geometry of the mammographic apparatus has been considered along with the software phantom of compressed breast. This phantom may contain inhomogeneities of various compositions and sizes at any point. Using this model one can produce simulated mammograms. Results that demonstrate the validity of this simulation are presented. (authors)
PASSENGER TRAFFIC MOVEMENT MODELLING BY THE CELLULAR-AUTOMAT APPROACH
Directory of Open Access Journals (Sweden)
T. Mikhaylovskaya
2009-01-01
Full Text Available The mathematical model of passenger traffic movement developed on the basis of the cellular-automat approach is considered. The program realization of the cellular-automat model of pedastrians streams movement in pedestrian subways at presence of obstacles, at subway structure narrowing is presented. The optimum distances between the obstacles and the angle of subway structure narrowing providing pedastrians stream safe movement and traffic congestion occurance are determined.
Quantum Monte Carlo Simulation of Frustrated Kondo Lattice Models
Sato, Toshihiro; Assaad, Fakher F.; Grover, Tarun
2018-03-01
The absence of the negative sign problem in quantum Monte Carlo simulations of spin and fermion systems has different origins. World-line based algorithms for spins require positivity of matrix elements whereas auxiliary field approaches for fermions depend on symmetries such as particle-hole symmetry. For negative-sign-free spin and fermionic systems, we show that one can formulate a negative-sign-free auxiliary field quantum Monte Carlo algorithm that allows Kondo coupling of fermions with the spins. Using this general approach, we study a half-filled Kondo lattice model on the honeycomb lattice with geometric frustration. In addition to the conventional Kondo insulator and antiferromagnetically ordered phases, we find a partial Kondo screened state where spins are selectively screened so as to alleviate frustration, and the lattice rotation symmetry is broken nematically.
Monte Carlo Numerical Models for Nuclear Logging Applications
Directory of Open Access Journals (Sweden)
Fusheng Li
2012-06-01
Full Text Available Nuclear logging is one of most important logging services provided by many oil service companies. The main parameters of interest are formation porosity, bulk density, and natural radiation. Other services are also provided from using complex nuclear logging tools, such as formation lithology/mineralogy, etc. Some parameters can be measured by using neutron logging tools and some can only be measured by using a gamma ray tool. To understand the response of nuclear logging tools, the neutron transport/diffusion theory and photon diffusion theory are needed. Unfortunately, for most cases there are no analytical answers if complex tool geometry is involved. For many years, Monte Carlo numerical models have been used by nuclear scientists in the well logging industry to address these challenges. The models have been widely employed in the optimization of nuclear logging tool design, and the development of interpretation methods for nuclear logs. They have also been used to predict the response of nuclear logging systems for forward simulation problems. In this case, the system parameters including geometry, materials and nuclear sources, etc., are pre-defined and the transportation and interactions of nuclear particles (such as neutrons, photons and/or electrons in the regions of interest are simulated according to detailed nuclear physics theory and their nuclear cross-section data (probability of interacting. Then the deposited energies of particles entering the detectors are recorded and tallied and the tool responses to such a scenario are generated. A general-purpose code named Monte Carlo N– Particle (MCNP has been the industry-standard for some time. In this paper, we briefly introduce the fundamental principles of Monte Carlo numerical modeling and review the physics of MCNP. Some of the latest developments of Monte Carlo Models are also reviewed. A variety of examples are presented to illustrate the uses of Monte Carlo numerical models
International Nuclear Information System (INIS)
Bourauel, Peter; Nabbi, Rahim; Biel, Wolfgang; Forrest, Robin
2009-01-01
The MCNP 3D Monte Carlo computer code is used not only for criticality calculations of nuclear systems but also to simulate transports of radiation and particles. The findings so obtained about neutron flux distribution and the associated spectra allow information about materials activation, nuclear heating, and radiation damage to be obtained by means of activation codes such as FISPACT. The stochastic character of particle and radiation transport processes normally links findings to the materials cells making up the geometry model of MCNP. Where high spatial resolution is required for the activation calculations with FISPACT, fine segmentation of the MCNP geometry becomes compulsory, which implies considerable expense for the modeling process. For this reason, an alternative simulation technique has been developed in an effort to automate and optimize data transfer between MCNP and FISPACT. (orig.)
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 ...
Monte Carlo modeling of human tooth optical coherence tomography imaging
International Nuclear Information System (INIS)
Shi, Boya; Meng, Zhuo; Wang, Longzhi; Liu, Tiegen
2013-01-01
We present a Monte Carlo model for optical coherence tomography (OCT) imaging of human tooth. The model is implemented by combining the simulation of a Gaussian beam with simulation for photon propagation in a two-layer human tooth model with non-parallel surfaces through a Monte Carlo method. The geometry and the optical parameters of the human tooth model are chosen on the basis of the experimental OCT images. The results show that the simulated OCT images are qualitatively consistent with the experimental ones. Using the model, we demonstrate the following: firstly, two types of photons contribute to the information of morphological features and noise in the OCT image of a human tooth, respectively. Secondly, the critical imaging depth of the tooth model is obtained, and it is found to decrease significantly with increasing mineral loss, simulated as different enamel scattering coefficients. Finally, the best focus position is located below and close to the dental surface by analysis of the effect of focus positions on the OCT signal and critical imaging depth. We anticipate that this modeling will become a powerful and accurate tool for a preliminary numerical study of the OCT technique on diseases of dental hard tissue in human teeth. (paper)
Skin fluorescence model based on the Monte Carlo technique
Churmakov, Dmitry Y.; Meglinski, Igor V.; Piletsky, Sergey A.; Greenhalgh, Douglas A.
2003-10-01
The novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account spatial distribution of fluorophores following the collagen fibers packing, whereas in epidermis and stratum corneum the distribution of fluorophores assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the NIR spectral region, while fluorescence of sensor layer embedded in epidermis is localized at the adjusted depth. The model is also able to simulate the skin fluorescence spectra.
Neuro-fuzzy system modeling based on automatic fuzzy clustering
Institute of Scientific and Technical Information of China (English)
Yuangang TANG; Fuchun SUN; Zengqi SUN
2005-01-01
A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.
Inter Genre Similarity Modelling For Automatic Music Genre Classification
Bagci, Ulas; Erzin, Engin
2009-01-01
Music genre classification is an essential tool for music information retrieval systems and it has been finding critical applications in various media platforms. Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modelling (IGS) to improve the performance of automatic music genre classification. Inter-genre similarity information is extracted over the mis-classified feature population....
Conditional Monte Carlo randomization tests for regression models.
Parhat, Parwen; Rosenberger, William F; Diao, Guoqing
2014-08-15
We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.
Monte Carlo technique for very large ising models
Kalle, C.; Winkelmann, V.
1982-08-01
Rebbi's multispin coding technique is improved and applied to the kinetic Ising model with size 600*600*600. We give the central part of our computer program (for a CDC Cyber 76), which will be helpful also in a simulation of smaller systems, and describe the other tricks necessary to go to large lattices. The magnetization M at T=1.4* T c is found to decay asymptotically as exp(-t/2.90) if t is measured in Monte Carlo steps per spin, and M( t = 0) = 1 initially.
Novel extrapolation method in the Monte Carlo shell model
International Nuclear Information System (INIS)
Shimizu, Noritaka; Abe, Takashi; Utsuno, Yutaka; Mizusaki, Takahiro; Otsuka, Takaharu; Honma, Michio
2010-01-01
We propose an extrapolation method utilizing energy variance in the Monte Carlo shell model to estimate the energy eigenvalue and observables accurately. We derive a formula for the energy variance with deformed Slater determinants, which enables us to calculate the energy variance efficiently. The feasibility of the method is demonstrated for the full pf-shell calculation of 56 Ni, and the applicability of the method to a system beyond the current limit of exact diagonalization is shown for the pf+g 9/2 -shell calculation of 64 Ge.
Shell-model Monte Carlo studies of nuclei
International Nuclear Information System (INIS)
Dean, D.J.
1997-01-01
The pair content and structure of nuclei near N = Z are described in the frwnework of shell-model Monte Carlo (SMMC) calculations. Results include the enhancement of J=0 T=1 proton-neutron pairing at N=Z nuclei, and the maxked difference of thermal properties between even-even and odd-odd N=Z nuclei. Additionally, a study of the rotational properties of the T=1 (ground state), and T=0 band mixing seen in 74 Rb is presented
Automatic generation of anatomic characteristics from cerebral aneurysm surface models.
Neugebauer, M; Lawonn, K; Beuing, O; Preim, B
2013-03-01
Computer-aided research on cerebral aneurysms often depends on a polygonal mesh representation of the vessel lumen. To support a differentiated, anatomy-aware analysis, it is necessary to derive anatomic descriptors from the surface model. We present an approach on automatic decomposition of the adjacent vessels into near- and far-vessel regions and computation of the axial plane. We also exemplarily present two applications of the geometric descriptors: automatic computation of a unique vessel order and automatic viewpoint selection. Approximation methods are employed to analyze vessel cross-sections and the vessel area profile along the centerline. The resulting transition zones between near- and far- vessel regions are used as input for an optimization process to compute the axial plane. The unique vessel order is defined via projection into the plane space of the axial plane. The viewing direction for the automatic viewpoint selection is derived from the normal vector of the axial plane. The approach was successfully applied to representative data sets exhibiting a broad variability with respect to the configuration of their adjacent vessels. A robustness analysis showed that the automatic decomposition is stable against noise. A survey with 4 medical experts showed a broad agreement with the automatically defined transition zones. Due to the general nature of the underlying algorithms, this approach is applicable to most of the likely aneurysm configurations in the cerebral vasculature. Additional geometric information obtained during automatic decomposition can support correction in case the automatic approach fails. The resulting descriptors can be used for various applications in the field of visualization, exploration and analysis of cerebral aneurysms.
Monte Carlo modeling of the Fastscan whole body counter response
International Nuclear Information System (INIS)
Graham, H.R.; Waller, E.J.
2015-01-01
Monte Carlo N-Particle (MCNP) was used to make a model of the Fastscan for the purpose of calibration. Two models were made one for the Pickering Nuclear Site, and one for the Darlington Nuclear Site. Once these models were benchmarked and found to be in good agreement, simulations were run to study the effect different sized phantoms had on the detected response, and the shielding effect of torso fat was not negligible. Simulations into the nature of a source being positioned externally on the anterior or posterior of a person were also conducted to determine a ratio that could be used to determine if a source is externally or internally placed. (author)
Automatic Detection and Resolution of Lexical Ambiguity in Process Models
Pittke, F.; Leopold, H.; Mendling, J.
2015-01-01
System-related engineering tasks are often conducted using process models. In this context, it is essential that these models do not contain structural or terminological inconsistencies. To this end, several automatic analysis techniques have been proposed to support quality assurance. While formal
Modeling granular phosphor screens by Monte Carlo methods
International Nuclear Information System (INIS)
Liaparinos, Panagiotis F.; Kandarakis, Ioannis S.; Cavouras, Dionisis A.; Delis, Harry B.; Panayiotakis, George S.
2006-01-01
The intrinsic phosphor properties are of significant importance for the performance of phosphor screens used in medical imaging systems. In previous analytical-theoretical and Monte Carlo studies on granular phosphor materials, values of optical properties, and light interaction cross sections were found by fitting to experimental data. These values were then employed for the assessment of phosphor screen imaging performance. However, it was found that, depending on the experimental technique and fitting methodology, the optical parameters of a specific phosphor material varied within a wide range of values, i.e., variations of light scattering with respect to light absorption coefficients were often observed for the same phosphor material. In this study, x-ray and light transport within granular phosphor materials was studied by developing a computational model using Monte Carlo methods. The model was based on the intrinsic physical characteristics of the phosphor. Input values required to feed the model can be easily obtained from tabulated data. The complex refractive index was introduced and microscopic probabilities for light interactions were produced, using Mie scattering theory. Model validation was carried out by comparing model results on x-ray and light parameters (x-ray absorption, statistical fluctuations in the x-ray to light conversion process, number of emitted light photons, output light spatial distribution) with previous published experimental data on Gd 2 O 2 S:Tb phosphor material (Kodak Min-R screen). Results showed the dependence of the modulation transfer function (MTF) on phosphor grain size and material packing density. It was predicted that granular Gd 2 O 2 S:Tb screens of high packing density and small grain size may exhibit considerably better resolution and light emission properties than the conventional Gd 2 O 2 S:Tb screens, under similar conditions (x-ray incident energy, screen thickness)
Preliminary validation of a Monte Carlo model for IMRT fields
International Nuclear Information System (INIS)
Wright, Tracy; Lye, Jessica; Mohammadi, Mohammad
2011-01-01
Full text: A Monte Carlo model of an Elekta linac, validated for medium to large (10-30 cm) symmetric fields, has been investigated for small, irregular and asymmetric fields suitable for IMRT treatments. The model has been validated with field segments using radiochromic film in solid water. The modelled positions of the multileaf collimator (MLC) leaves have been validated using EBT film, In the model, electrons with a narrow energy spectrum are incident on the target and all components of the linac head are included. The MLC is modelled using the EGSnrc MLCE component module. For the validation, a number of single complex IMRT segments with dimensions approximately 1-8 cm were delivered to film in solid water (see Fig, I), The same segments were modelled using EGSnrc by adjusting the MLC leaf positions in the model validated for 10 cm symmetric fields. Dose distributions along the centre of each MLC leaf as determined by both methods were compared. A picket fence test was also performed to confirm the MLC leaf positions. 95% of the points in the modelled dose distribution along the leaf axis agree with the film measurement to within 1%/1 mm for dose difference and distance to agreement. Areas of most deviation occur in the penumbra region. A system has been developed to calculate the MLC leaf positions in the model for any planned field size.
Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods
Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.
2014-12-01
Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.
Using suggestion to model different types of automatic writing.
Walsh, E; Mehta, M A; Oakley, D A; Guilmette, D N; Gabay, A; Halligan, P W; Deeley, Q
2014-05-01
Our sense of self includes awareness of our thoughts and movements, and our control over them. This feeling can be altered or lost in neuropsychiatric disorders as well as in phenomena such as "automatic writing" whereby writing is attributed to an external source. Here, we employed suggestion in highly hypnotically suggestible participants to model various experiences of automatic writing during a sentence completion task. Results showed that the induction of hypnosis, without additional suggestion, was associated with a small but significant reduction of control, ownership, and awareness for writing. Targeted suggestions produced a double dissociation between thought and movement components of writing, for both feelings of control and ownership, and additionally, reduced awareness of writing. Overall, suggestion produced selective alterations in the control, ownership, and awareness of thought and motor components of writing, thus enabling key aspects of automatic writing, observed across different clinical and cultural settings, to be modelled. Copyright © 2014. Published by Elsevier Inc.
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.
2010-06-01
The authors consider the analysis of hierarchical longitudinal functional data based upon a functional principal components approach. In contrast to standard frequentist approaches to selecting the number of principal components, the authors do model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order to overcome this, the authors show how to apply Stochastic Approximation Monte Carlo (SAMC) to this problem, a method that has the potential to explore the entire space and does not become trapped in local extrema. The combination of reversible jump methods and SAMC in hierarchical longitudinal functional data is simplified by a polar coordinate representation of the principal components. The approach is easy to implement and does well in simulated data in determining the distribution of the number of principal components, and in terms of its frequentist estimation properties. Empirical applications are also presented.
Modeling Dynamic Objects in Monte Carlo Particle Transport Calculations
International Nuclear Information System (INIS)
Yegin, G.
2008-01-01
In this study, the Multi-Geometry geometry modeling technique was improved in order to handle moving objects in a Monte Carlo particle transport calculation. In the Multi-Geometry technique, the geometry is a superposition of objects not surfaces. By using this feature, we developed a new algorithm which allows a user to make enable or disable geometry elements during particle transport. A disabled object can be ignored at a certain stage of a calculation and switching among identical copies of the same object located adjacent poins during a particle simulation corresponds to the movement of that object in space. We called this powerfull feature as Dynamic Multi-Geometry technique (DMG) which is used for the first time in Brachy Dose Monte Carlo code to simulate HDR brachytherapy treatment systems. Our results showed that having disabled objects in a geometry does not effect calculated dose values. This technique is also suitable to be used in other areas such as IMRT treatment planning systems
Monte Carlo modelling of Schottky diode for rectenna simulation
Bernuchon, E.; Aniel, F.; Zerounian, N.; Grimault-Jacquin, A. S.
2017-09-01
Before designing a detector circuit, the electrical parameters extraction of the Schottky diode is a critical step. This article is based on a Monte-Carlo (MC) solver of the Boltzmann Transport Equation (BTE) including different transport mechanisms at the metal-semiconductor contact such as image force effect or tunneling. The weight of tunneling and thermionic current is quantified according to different degrees of tunneling modelling. The I-V characteristic highlights the dependence of the ideality factor and the current saturation with bias. Harmonic Balance (HB) simulation on a rectifier circuit within Advanced Design System (ADS) software shows that considering non-linear ideality factor and saturation current for the electrical model of the Schottky diode does not seem essential. Indeed, bias independent values extracted in forward regime on I-V curve are sufficient. However, the non-linear series resistance extracted from a small signal analysis (SSA) strongly influences the conversion efficiency at low input powers.
Shell model Monte Carlo investigation of rare earth nuclei
International Nuclear Information System (INIS)
White, J. A.; Koonin, S. E.; Dean, D. J.
2000-01-01
We utilize the shell model Monte Carlo method to study the structure of rare earth nuclei. This work demonstrates the first systematic full oscillator shell with intruder calculations in such heavy nuclei. Exact solutions of a pairing plus quadrupole Hamiltonian are compared with the static path approximation in several dysprosium isotopes from A=152 to 162, including the odd mass A=153. Some comparisons are also made with Hartree-Fock-Bogoliubov results from Baranger and Kumar. Basic properties of these nuclei at various temperatures and spin are explored. These include energy, deformation, moments of inertia, pairing channel strengths, band crossing, and evolution of shell model occupation numbers. Exact level densities are also calculated and, in the case of 162 Dy, compared with experimental data. (c) 2000 The American Physical Society
Monte Carlo model of diagnostic X-ray dosimetry
International Nuclear Information System (INIS)
Khrutchinsky, Arkady; Kutsen, Semion; Gatskevich, George
2008-01-01
Full text: A Monte Carlo simulation of absorbed dose distribution in patient's tissues is often used in a dosimetry assessment of X-ray examinations. The results of such simulations in Belarus are presented in the report based on an anthropomorphic tissue-equivalent Rando-like physical phantom. The phantom corresponds to an adult 173 cm high and of 73 kg and consists of a torso and a head made of tissue-equivalent plastics which model soft (muscular), bone, and lung tissues. It consists of 39 layers (each 25 mm thick), including 10 head and neck ones, 16 chest and 13 pelvis ones. A tomographic model of the phantom has been developed from its CT-scan images with a voxel size of 0.88 x 0.88 x 4 mm 3 . A necessary pixelization in Mathematics-based in-house program was carried out for the phantom to be used in the radiation transport code MCNP-4b. The final voxel size of 14.2 x 14.2 x 8 mm 3 was used for the reasonable computer consuming calculations of absorbed dose in tissues and organs in various diagnostic X-ray examinations. MCNP point detectors allocated through body slices obtained as a result of the pixelization were used to calculate the absorbed dose. X-ray spectra generated by the empirical TASMIP model were verified on the X-ray units MEVASIM and SIREGRAPH CF. Absorbed dose distributions in the phantom volume were determined by the corresponding Monte Carlo simulations with a set of point detectors. Doses in organs of the adult phantom computed from the absorbed dose distributions by another Mathematics-based in-house program were estimated for 22 standard organs for various standard X-ray examinations. The results of Monte Carlo simulations were compared with the results of direct measurements of the absorbed dose in the phantom on the X-ray unit SIREGRAPH CF with the calibrated thermo-luminescent dosimeter DTU-01. The measurements were carried out in specified locations of different layers in heart, lungs, liver, pancreas, and stomach at high voltage of
Model-Based Reasoning in Humans Becomes Automatic with Training.
Directory of Open Access Journals (Sweden)
Marcos Economides
2015-09-01
Full Text Available Model-based and model-free reinforcement learning (RL have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.
Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation
DEFF Research Database (Denmark)
Mangado Lopez, Nerea; Ceresa, Mario; Duchateau, Nicolas
2016-01-01
. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical μCT images. Then, by fitting the statistical model to a patient......'s CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns......Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging...
Small-Scale Helicopter Automatic Autorotation : Modeling, Guidance, and Control
Taamallah, S.
2015-01-01
Our research objective consists in developing a, model-based, automatic safety recovery system, for a small-scale helicopter Unmanned Aerial Vehicle (UAV) in autorotation, i.e. an engine OFF flight condition, that safely flies and lands the helicopter to a pre-specified ground location. In pursuit
Automatic 3D modeling of the urban landscape
Esteban, I.; Dijk, J.; Groen, F.
2010-01-01
In this paper we present a fully automatic system for building 3D models of urban areas at the street level. We propose a novel approach for the accurate estimation of the scale consistent camera pose given two previous images. We employ a new method for global optimization and use a novel sampling
Using UML to Model Web Services for Automatic Composition
Amal Elgammal; Mohamed El-Sharkawi
2010-01-01
There is a great interest paid to the web services paradigm nowadays. One of the most important problems related to the web service paradigm is the automatic composition of web services. Several frameworks have been proposed to achieve this novel goal. The most recent and richest framework (model) is the Colombo model. However, even for experienced developers, working with Colombo formalisms is low-level, very complex and timeconsuming. We propose to use UML (Unified Modeling Language) to mod...
Automatic balancing of 3D models
DEFF Research Database (Denmark)
Christiansen, Asger Nyman; Schmidt, Ryan; Bærentzen, Jakob Andreas
2014-01-01
3D printing technologies allow for more diverse shapes than are possible with molds and the cost of making just one single object is negligible compared to traditional production methods. However, not all shapes are suitable for 3D print. One of the remaining costs is therefore human time spent......, in these cases, we will apply a rotation of the object which only deforms the shape a little near the base. No user input is required but it is possible to specify manufacturing constraints related to specific 3D print technologies. Several models have successfully been balanced and printed using both polyjet...... is solved by creating cavities of air and distributing dense materials inside the model. Consequently, the surface is not deformed. However, printing materials with significantly different densities is often not possible and adding cavities of air is often not enough to make the model balance. Consequently...
Modelling a gamma irradiation process using the Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Soares, Gabriela A.; Pereira, Marcio T., E-mail: gas@cdtn.br, E-mail: mtp@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2011-07-01
In gamma irradiation service it is of great importance the evaluation of absorbed dose in order to guarantee the service quality. When physical structure and human resources are not available for performing dosimetry in each product irradiated, the appliance of mathematic models may be a solution. Through this, the prediction of the delivered dose in a specific product, irradiated in a specific position and during a certain period of time becomes possible, if validated with dosimetry tests. At the gamma irradiation facility of CDTN, equipped with a Cobalt-60 source, the Monte Carlo method was applied to perform simulations of products irradiations and the results were compared with Fricke dosimeters irradiated under the same conditions of the simulations. The first obtained results showed applicability of this method, with a linear relation between simulation and experimental results. (author)
Monte Carlo Modeling of Crystal Channeling at High Energies
Schoofs, Philippe; Cerutti, Francesco
Charged particles entering a crystal close to some preferred direction can be trapped in the electromagnetic potential well existing between consecutive planes or strings of atoms. This channeling effect can be used to extract beam particles if the crystal is bent beforehand. Crystal channeling is becoming a reliable and efficient technique for collimating beams and removing halo particles. At CERN, the installation of silicon crystals in the LHC is under scrutiny by the UA9 collaboration with the goal of investigating if they are a viable option for the collimation system upgrade. This thesis describes a new Monte Carlo model of planar channeling which has been developed from scratch in order to be implemented in the FLUKA code simulating particle transport and interactions. Crystal channels are described through the concept of continuous potential taking into account thermal motion of the lattice atoms and using Moliere screening function. The energy of the particle transverse motion determines whether or n...
Modelling a gamma irradiation process using the Monte Carlo method
International Nuclear Information System (INIS)
Soares, Gabriela A.; Pereira, Marcio T.
2011-01-01
In gamma irradiation service it is of great importance the evaluation of absorbed dose in order to guarantee the service quality. When physical structure and human resources are not available for performing dosimetry in each product irradiated, the appliance of mathematic models may be a solution. Through this, the prediction of the delivered dose in a specific product, irradiated in a specific position and during a certain period of time becomes possible, if validated with dosimetry tests. At the gamma irradiation facility of CDTN, equipped with a Cobalt-60 source, the Monte Carlo method was applied to perform simulations of products irradiations and the results were compared with Fricke dosimeters irradiated under the same conditions of the simulations. The first obtained results showed applicability of this method, with a linear relation between simulation and experimental results. (author)
A Monte Carlo Simulation Framework for Testing Cosmological Models
Directory of Open Access Journals (Sweden)
Heymann Y.
2014-10-01
Full Text Available We tested alternative cosmologies using Monte Carlo simulations based on the sam- pling method of the zCosmos galactic survey. The survey encompasses a collection of observable galaxies with respective redshifts that have been obtained for a given spec- troscopic area of the sky. Using a cosmological model, we can convert the redshifts into light-travel times and, by slicing the survey into small redshift buckets, compute a curve of galactic density over time. Because foreground galaxies obstruct the images of more distant galaxies, we simulated the theoretical galactic density curve using an average galactic radius. By comparing the galactic density curves of the simulations with that of the survey, we could assess the cosmologies. We applied the test to the expanding-universe cosmology of de Sitter and to a dichotomous cosmology.
Fast Appearance Modeling for Automatic Primary Video Object Segmentation.
Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong
2016-02-01
Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.
Ensemble bayesian model averaging using markov chain Monte Carlo sampling
Energy Technology Data Exchange (ETDEWEB)
Vrugt, Jasper A [Los Alamos National Laboratory; Diks, Cees G H [NON LANL; Clark, Martyn P [NON LANL
2008-01-01
Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery etal. Mon Weather Rev 133: 1155-1174, 2(05)) has recommended the Expectation-Maximization (EM) algorithm for BMA model training, even though global convergence of this algorithm cannot be guaranteed. In this paper, we compare the performance of the EM algorithm and the recently developed Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm for estimating the BMA weights and variances. Simulation experiments using 48-hour ensemble data of surface temperature and multi-model stream-flow forecasts show that both methods produce similar results, and that their performance is unaffected by the length of the training data set. However, MCMC simulation with DREAM is capable of efficiently handling a wide variety of BMA predictive distributions, and provides useful information about the uncertainty associated with the estimated BMA weights and variances.
Automatization of hydrodynamic modelling in a Floreon+ system
Ronovsky, Ales; Kuchar, Stepan; Podhoranyi, Michal; Vojtek, David
2017-07-01
The paper describes fully automatized hydrodynamic modelling as a part of the Floreon+ system. The main purpose of hydrodynamic modelling in the disaster management is to provide an accurate overview of the hydrological situation in a given river catchment. Automatization of the process as a web service could provide us with immediate data based on extreme weather conditions, such as heavy rainfall, without the intervention of an expert. Such a service can be used by non scientific users such as fire-fighter operators or representatives of a military service organizing evacuation during floods or river dam breaks. The paper describes the whole process beginning with a definition of a schematization necessary for hydrodynamic model, gathering of necessary data and its processing for a simulation, the model itself and post processing of a result and visualization on a web service. The process is demonstrated on a real data collected during floods in our Moravian-Silesian region in 2010.
Monte Carlo simulations of lattice models for single polymer systems
Hsu, Hsiao-Ping
2014-10-01
Single linear polymer chains in dilute solutions under good solvent conditions are studied by Monte Carlo simulations with the pruned-enriched Rosenbluth method up to the chain length N ˜ O(10^4). Based on the standard simple cubic lattice model (SCLM) with fixed bond length and the bond fluctuation model (BFM) with bond lengths in a range between 2 and sqrt{10}, we investigate the conformations of polymer chains described by self-avoiding walks on the simple cubic lattice, and by random walks and non-reversible random walks in the absence of excluded volume interactions. In addition to flexible chains, we also extend our study to semiflexible chains for different stiffness controlled by a bending potential. The persistence lengths of chains extracted from the orientational correlations are estimated for all cases. We show that chains based on the BFM are more flexible than those based on the SCLM for a fixed bending energy. The microscopic differences between these two lattice models are discussed and the theoretical predictions of scaling laws given in the literature are checked and verified. Our simulations clarify that a different mapping ratio between the coarse-grained models and the atomistically realistic description of polymers is required in a coarse-graining approach due to the different crossovers to the asymptotic behavior.
Monte Carlo simulations of lattice models for single polymer systems
International Nuclear Information System (INIS)
Hsu, Hsiao-Ping
2014-01-01
Single linear polymer chains in dilute solutions under good solvent conditions are studied by Monte Carlo simulations with the pruned-enriched Rosenbluth method up to the chain length N∼O(10 4 ). Based on the standard simple cubic lattice model (SCLM) with fixed bond length and the bond fluctuation model (BFM) with bond lengths in a range between 2 and √(10), we investigate the conformations of polymer chains described by self-avoiding walks on the simple cubic lattice, and by random walks and non-reversible random walks in the absence of excluded volume interactions. In addition to flexible chains, we also extend our study to semiflexible chains for different stiffness controlled by a bending potential. The persistence lengths of chains extracted from the orientational correlations are estimated for all cases. We show that chains based on the BFM are more flexible than those based on the SCLM for a fixed bending energy. The microscopic differences between these two lattice models are discussed and the theoretical predictions of scaling laws given in the literature are checked and verified. Our simulations clarify that a different mapping ratio between the coarse-grained models and the atomistically realistic description of polymers is required in a coarse-graining approach due to the different crossovers to the asymptotic behavior
Developing Automatic Student Motivation Modeling System
Destarianto, P.; Etikasari, B.; Agustianto, K.
2018-01-01
Achievement motivation is one of the internal factors in encouraging a person to perform the best activity in achieving its goals. The importance of achievement motivation must be possessed as an incentive to compete so that the person will always strive to achieve success and avoid failure. Based on this, the system is developed to determine the achievement motivation of students, so that students can do self-reflection in improving achievement motivation. The test results of the system using Naïve Bayes Classifier showed an average rate of accuracy of 91,667% in assessing student achievement motivation. By modeling the students ‘motivation generated by the system, students’ achievement motivation level can be known. This class of motivation will be used to determine appropriate counseling decisions, and ultimately is expected to improve student achievement motivation.
A general graphical user interface for automatic reliability modeling
Liceaga, Carlos A.; Siewiorek, Daniel P.
1991-01-01
Reported here is a general Graphical User Interface (GUI) for automatic reliability modeling of Processor Memory Switch (PMS) structures using a Markov model. This GUI is based on a hierarchy of windows. One window has graphical editing capabilities for specifying the system's communication structure, hierarchy, reconfiguration capabilities, and requirements. Other windows have field texts, popup menus, and buttons for specifying parameters and selecting actions. An example application of the GUI is given.
MEMOPS: data modelling and automatic code generation.
Fogh, Rasmus H; Boucher, Wayne; Ionides, John M C; Vranken, Wim F; Stevens, Tim J; Laue, Ernest D
2010-03-25
In recent years the amount of biological data has exploded to the point where much useful information can only be extracted by complex computational analyses. Such analyses are greatly facilitated by metadata standards, both in terms of the ability to compare data originating from different sources, and in terms of exchanging data in standard forms, e.g. when running processes on a distributed computing infrastructure. However, standards thrive on stability whereas science tends to constantly move, with new methods being developed and old ones modified. Therefore maintaining both metadata standards, and all the code that is required to make them useful, is a non-trivial problem. Memops is a framework that uses an abstract definition of the metadata (described in UML) to generate internal data structures and subroutine libraries for data access (application programming interfaces--APIs--currently in Python, C and Java) and data storage (in XML files or databases). For the individual project these libraries obviate the need for writing code for input parsing, validity checking or output. Memops also ensures that the code is always internally consistent, massively reducing the need for code reorganisation. Across a scientific domain a Memops-supported data model makes it easier to support complex standards that can capture all the data produced in a scientific area, share them among all programs in a complex software pipeline, and carry them forward to deposition in an archive. The principles behind the Memops generation code will be presented, along with example applications in Nuclear Magnetic Resonance (NMR) spectroscopy and structural biology.
Monte Carlo Modeling the UCN τ Magneto-Gravitational Trap
Holley, A. T.; UCNτ Collaboration
2016-09-01
The current uncertainty in our knowledge of the free neutron lifetime is dominated by the nearly 4 σ discrepancy between complementary ``beam'' and ``bottle'' measurement techniques. An incomplete assessment of systematic effects is the most likely explanation for this difference and must be addressed in order to realize the potential of both approaches. The UCN τ collaboration has constructed a large-volume magneto-gravitational trap that eliminates the material interactions which complicated the interpretation of previous bottle experiments. This is accomplished using permanent NdFeB magnets in a bowl-shaped Halbach array to confine polarized UCN from the sides and below and the earth's gravitational field to trap them from above. New in situ detectors that count surviving UCN provide a means of empirically assessing residual systematic effects. The interpretation of that data, and its implication for experimental configurations with enhanced precision, can be bolstered by Monte Carlo models of the current experiment which provide the capability for stable tracking of trapped UCN and detailed modeling of their polarization. Work to develop such models and their comparison with data acquired during our first extensive set of systematics studies will be discussed.
Monte Carlo modelling of large scale NORM sources using MCNP.
Wallace, J D
2013-12-01
The representative Monte Carlo modelling of large scale planar sources (for comparison to external environmental radiation fields) is undertaken using substantial diameter and thin profile planar cylindrical sources. The relative impact of source extent, soil thickness and sky-shine are investigated to guide decisions relating to representative geometries. In addition, the impact of source to detector distance on the nature of the detector response, for a range of source sizes, has been investigated. These investigations, using an MCNP based model, indicate a soil cylinder of greater than 20 m diameter and of no less than 50 cm depth/height, combined with a 20 m deep sky section above the soil cylinder, are needed to representatively model the semi-infinite plane of uniformly distributed NORM sources. Initial investigation of the effect of detector placement indicate that smaller source sizes may be used to achieve a representative response at shorter source to detector distances. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.
AUTOMATIC TEXTURE MAPPING OF ARCHITECTURAL AND ARCHAEOLOGICAL 3D MODELS
Directory of Open Access Journals (Sweden)
T. P. Kersten
2012-07-01
Full Text Available Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.
Automatic Texture Mapping of Architectural and Archaeological 3d Models
Kersten, T. P.; Stallmann, D.
2012-07-01
Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage) algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.
Automatic paper sliceform design from 3D solid models.
Le-Nguyen, Tuong-Vu; Low, Kok-Lim; Ruiz, Conrado; Le, Sang N
2013-11-01
A paper sliceform or lattice-style pop-up is a form of papercraft that uses two sets of parallel paper patches slotted together to make a foldable structure. The structure can be folded flat, as well as fully opened (popped-up) to make the two sets of patches orthogonal to each other. Automatic design of paper sliceforms is still not supported by existing computational models and remains a challenge. We propose novel geometric formulations of valid paper sliceform designs that consider the stability, flat-foldability and physical realizability of the designs. Based on a set of sufficient construction conditions, we also present an automatic algorithm for generating valid sliceform designs that closely depict the given 3D solid models. By approximating the input models using a set of generalized cylinders, our method significantly reduces the search space for stable and flat-foldable sliceforms. To ensure the physical realizability of the designs, the algorithm automatically generates slots or slits on the patches such that no two cycles embedded in two different patches are interlocking each other. This guarantees local pairwise assembility between patches, which is empirically shown to lead to global assembility. Our method has been demonstrated on a number of example models, and the output designs have been successfully made into real paper sliceforms.
International Nuclear Information System (INIS)
Aristovich, K Y; Khan, S H
2010-01-01
Realistic computer modelling of biological objects requires building of very accurate and realistic computer models based on geometric and material data, type, and accuracy of numerical analyses. This paper presents some of the automatic tools and algorithms that were used to build accurate and realistic 3D finite element (FE) model of whole-brain. These models were used to solve the forward problem in magnetic field tomography (MFT) based on Magnetoencephalography (MEG). The forward problem involves modelling and computation of magnetic fields produced by human brain during cognitive processing. The geometric parameters of the model were obtained from accurate Magnetic Resonance Imaging (MRI) data and the material properties - from those obtained from Diffusion Tensor MRI (DTMRI). The 3D FE models of the brain built using this approach has been shown to be very accurate in terms of both geometric and material properties. The model is stored on the computer in Computer-Aided Parametrical Design (CAD) format. This allows the model to be used in a wide a range of methods of analysis, such as finite element method (FEM), Boundary Element Method (BEM), Monte-Carlo Simulations, etc. The generic model building approach presented here could be used for accurate and realistic modelling of human brain and many other biological objects.
Mesoscopic kinetic Monte Carlo modeling of organic photovoltaic device characteristics
Kimber, Robin G. E.; Wright, Edward N.; O'Kane, Simon E. J.; Walker, Alison B.; Blakesley, James C.
2012-12-01
Measured mobility and current-voltage characteristics of single layer and photovoltaic (PV) devices composed of poly{9,9-dioctylfluorene-co-bis[N,N'-(4-butylphenyl)]bis(N,N'-phenyl-1,4-phenylene)diamine} (PFB) and poly(9,9-dioctylfluorene-co-benzothiadiazole) (F8BT) have been reproduced by a mesoscopic model employing the kinetic Monte Carlo (KMC) approach. Our aim is to show how to avoid the uncertainties common in electrical transport models arising from the need to fit a large number of parameters when little information is available, for example, a single current-voltage curve. Here, simulation parameters are derived from a series of measurements using a self-consistent “building-blocks” approach, starting from data on the simplest systems. We found that site energies show disorder and that correlations in the site energies and a distribution of deep traps must be included in order to reproduce measured charge mobility-field curves at low charge densities in bulk PFB and F8BT. The parameter set from the mobility-field curves reproduces the unipolar current in single layers of PFB and F8BT and allows us to deduce charge injection barriers. Finally, by combining these disorder descriptions and injection barriers with an optical model, the external quantum efficiency and current densities of blend and bilayer organic PV devices can be successfully reproduced across a voltage range encompassing reverse and forward bias, with the recombination rate the only parameter to be fitted, found to be 1×107 s-1. These findings demonstrate an approach that removes some of the arbitrariness present in transport models of organic devices, which validates the KMC as an accurate description of organic optoelectronic systems, and provides information on the microscopic origins of the device behavior.
Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation.
Mangado, Nerea; Ceresa, Mario; Duchateau, Nicolas; Kjer, Hans Martin; Vera, Sergio; Dejea Velardo, Hector; Mistrik, Pavel; Paulsen, Rasmus R; Fagertun, Jens; Noailly, Jérôme; Piella, Gemma; González Ballester, Miguel Ángel
2016-08-01
Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical μCT images. Then, by fitting the statistical model to a patient's CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns constitutive parameters to all components of the finite element model. This model can then be used to study in silico the effects of the electrical stimulation of the cochlear implant. Results are shown on a total of 25 models of patients. In all cases, a final mesh suitable for finite element simulations was obtained, in an average time of 94 s. The framework has proven to be fast and robust, and is promising for a detailed prognosis of the cochlear implantation surgery.
Automatic generation of Fortran programs for algebraic simulation models
International Nuclear Information System (INIS)
Schopf, W.; Rexer, G.; Ruehle, R.
1978-04-01
This report documents a generator program by which econometric simulation models formulated in an application-orientated language can be transformed automatically in a Fortran program. Thus the model designer is able to build up, test and modify models without the need of a Fortran programmer. The development of a computer model is therefore simplified and shortened appreciably; in chapter 1-3 of this report all rules are presented for the application of the generator to the model design. Algebraic models including exogeneous and endogeneous time series variables, lead and lag function can be generated. In addition, to these language elements, Fortran sequences can be applied to the formulation of models in the case of complex model interrelations. Automatically the generated model is a module of the program system RSYST III and is therefore able to exchange input and output data with the central data bank of the system and in connection with the method library modules can be used to handle planning problems. (orig.) [de
Investigation of a Monte Carlo model for chemical reactions
International Nuclear Information System (INIS)
Hamm, R.N.; Turner, J.E.; Stabin, M.G.
1998-01-01
Monte Carlo computer simulations are in use at a number of laboratories for calculating time-dependent yields, which can be compared with experiments in the radiolysis of water. We report here on calculations to investigate the validity and consistency of the procedures used for simulating chemical reactions in our code, RADLYS. Model calculations were performed of the rate constants themselves. The rates thus determined showed an expected rapid decline over the first few hundred ps and a very gradual decline thereafter out to the termination of the calculations at 4.5 ns. Results are reported for different initial concentrations and numbers of reactive species. Generally, the calculated rate constants are smallest when the initial concentrations of the reactants are largest. It is found that inhomogeneities that quickly develop in the initial random spatial distribution of reactants persist in time as a result of subsequent chemical reactions, and thus conditions may poorly approximate those assumed from diffusion theory. We also investigated the reaction of a single species of one type placed among a large number of randomly distributed species of another type with which it could react. The distribution of survival times of the single species was calculated by using three different combinations of the diffusion constants for the two species, as is sometimes discussed in diffusion theory. The three methods gave virtually identical results. (orig.)
Monte Carlo Modeling Electronuclear Processes in Cascade Subcritical Reactor
Bznuni, S A; Zhamkochyan, V M; Polyanskii, A A; Sosnin, A N; Khudaverdian, A G
2000-01-01
Accelerator driven subcritical cascade reactor composed of the main thermal neutron reactor constructed analogous to the core of the VVER-1000 reactor and a booster-reactor, which is constructed similar to the core of the BN-350 fast breeder reactor, is taken as a model example. It is shown by means of Monte Carlo calculations that such system is a safe energy source (k_{eff}=0.94-0.98) and it is capable of transmuting produced radioactive wastes (neutron flux density in the thermal zone is PHI^{max} (r,z)=10^{14} n/(cm^{-2} s^{-1}), neutron flux in the fast zone is respectively equal PHI^{max} (r,z)=2.25 cdot 10^{15} n/(cm^{-2} s^{-1}) if the beam current of the proton accelerator is k_{eff}=0.98 and I=5.3 mA). Suggested configuration of the "cascade" reactor system essentially reduces the requirements on the proton accelerator current.
Monte Carlo modeling of ion chamber performance using MCNP.
Wallace, J D
2012-12-01
Ion Chambers have a generally flat energy response with some deviations at very low (2 MeV) energies. Some improvements in the low energy response can be achieved through use of high atomic number gases, such as argon and xenon, and higher chamber pressures. This work looks at the energy response of high pressure xenon-filled ion chambers using the MCNP Monte Carlo package to develop geometric models of a commercially available high pressure ion chamber (HPIC). The use of the F6 tally as an estimator of the energy deposited in a region of interest per unit mass, and the underlying assumptions associated with its use are described. The effect of gas composition, chamber gas pressure, chamber wall thickness, and chamber holder wall thicknesses on energy response are investigated and reported. The predicted energy response curve for the HPIC was found to be similar to that reported by other investigators. These investigations indicate that improvements to flatten the overall energy response of the HPIC down to 70 keV could be achieved through use of 3 mm-thick stainless steel walls for the ion chamber.
On an efficient multiple time step Monte Carlo simulation of the SABR model
Leitao Rodriguez, A.; Grzelak, L.A.; Oosterlee, C.W.
2017-01-01
In this paper, we will present a multiple time step Monte Carlo simulation technique for pricing options under the Stochastic Alpha Beta Rho model. The proposed method is an extension of the one time step Monte Carlo method that we proposed in an accompanying paper Leitao et al. [Appl. Math.
A Monte Carlo reflectance model for soil surfaces with three-dimensional structure
Cooper, K. D.; Smith, J. A.
1985-01-01
A Monte Carlo soil reflectance model has been developed to study the effect of macroscopic surface irregularities larger than the wavelength of incident flux. The model treats incoherent multiple scattering from Lambertian facets distributed on a periodic surface. Resulting bidirectional reflectance distribution functions are non-Lambertian and compare well with experimental trends reported in the literature. Examples showing the coupling of the Monte Carlo soil model to an adding bidirectional canopy of reflectance model are also given.
Automatic Generation of 3D Building Models with Multiple Roofs
Institute of Scientific and Technical Information of China (English)
Kenichi Sugihara; Yoshitugu Hayashi
2008-01-01
Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons' edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.
Tobon-Gomez, Catalina; Butakoff, Constantine; Aguade, Santiago; Sukno, Federico; Moragas, Gloria; Frangi, Alejandro F
2008-11-01
Active shape models bear a great promise for model-based medical image analysis. Their practical use, though, is undermined due to the need to train such models on large image databases. Automatic building of point distribution models (PDMs) has been successfully addressed and a number of autolandmarking techniques are currently available. However, the need for strategies to automatically build intensity models around each landmark has been largely overlooked in the literature. This work demonstrates the potential of creating intensity models automatically by simulating image generation. We show that it is possible to reuse a 3D PDM built from computed tomography (CT) to segment gated single photon emission computed tomography (gSPECT) studies. Training is performed on a realistic virtual population where image acquisition and formation have been modeled using the SIMIND Monte Carlo simulator and ASPIRE image reconstruction software, respectively. The dataset comprised 208 digital phantoms (4D-NCAT) and 20 clinical studies. The evaluation is accomplished by comparing point-to-surface and volume errors against a proper gold standard. Results show that gSPECT studies can be successfully segmented by models trained under this scheme with subvoxel accuracy. The accuracy in estimated LV function parameters, such as end diastolic volume, end systolic volume, and ejection fraction, ranged from 90.0% to 94.5% for the virtual population and from 87.0% to 89.5% for the clinical population.
Sky-Radiance Models for Monte Carlo Radiative Transfer Applications
Santos, I.; Dalimonte, D.; Santos, J. P.
2012-04-01
Photon-tracing can be initialized through sky-radiance (Lsky) distribution models when executing Monte Carlo simulations for ocean color studies. To be effective, the Lsky model should: 1) properly represent sky-radiance features of interest; 2) require low computing time; and 3) depend on a limited number of input parameters. The present study verifies the satisfiability of these prerequisite by comparing results from different Lsky formulations. Specifically, two Lsky models were considered as reference cases because of their different approach among solutions presented in the literature. The first model, developed by the Harrisson and Coombes (HC), is based on a parametric expression where the sun geometry is the unique input. The HC model is one of the sky-radiance analytical distribution applied in state-of-art simulations for ocean optics. The coefficients of the HC model were set upon broad-band field measurements and the result is a model that requires a few implementation steps. The second model, implemented by Zibordi and Voss (ZV), is based on physical expressions that accounts for the optical thickness of permanent gases, aerosol, ozone and water vapour at specific wavelengths. Inter-comparisons between normalized ^LskyZV and ^LskyHC (i.e., with unitary scalar irradiance) are discussed by means of individual polar maps and percent difference between sky-radiance distributions. Sky-radiance cross-sections are presented as well. Considered cases include different sun zenith values and wavelengths (i.e., λ=413, 490 and 665 nm, corresponding to selected center-bands of the MEdium Resolution Imaging Spectrometer MERIS). Results have shown a significant convergence between ^LskyHC and ^LskyZV at 665 nm. Differences between models increase with the sun zenith and mostly with wavelength. For Instance, relative differences up to 50% between ^ L skyHC and ^ LskyZV can be observed in the antisolar region for λ=665 nm and θ*=45°. The effects of these
Utility of Monte Carlo Modelling for Holdup Measurements.
Energy Technology Data Exchange (ETDEWEB)
Belian, Anthony P.; Russo, P. A. (Phyllis A.); Weier, Dennis R. (Dennis Ray),
2005-01-01
Non-destructive assay (NDA) measurements performed to locate and quantify holdup in the Oak Ridge K25 enrichment cascade used neutron totals counting and low-resolution gamma-ray spectroscopy. This facility housed the gaseous diffusion process for enrichment of uranium, in the form of UF{sub 6} gas, from {approx} 20% to 93%. Inventory of {sup 235}U inventory in K-25 is all holdup. These buildings have been slated for decontaminatino and decommissioning. The NDA measurements establish the inventory quantities and will be used to assure criticality safety and meet criteria for waste analysis and transportation. The tendency to err on the side of conservatism for the sake of criticality safety in specifying total NDA uncertainty argues, in the interests of safety and costs, for obtaining the best possible value of uncertainty at the conservative confidence level for each item of process equipment. Variable deposit distribution is a complex systematic effect (i.e., determined by multiple independent variables) on the portable NDA results for very large and bulk converters that contributes greatly to total uncertainty for holdup in converters measured by gamma or neutron NDA methods. Because the magnitudes of complex systematic effects are difficult to estimate, computational tools are important for evaluating those that are large. Motivated by very large discrepancies between gamma and neutron measurements of high-mass converters with gamma results tending to dominate, the Monte Carlo code MCNP has been used to determine the systematic effects of deposit distribution on gamma and neutron results for {sup 235}U holdup mass in converters. This paper details the numerical methodology used to evaluate large systematic effects unique to each measurement type, validates the methodology by comparison with measurements, and discusses how modeling tools can supplement the calibration of instruments used for holdup measurements by providing realistic values at well
Automatic Generation of Symbolic Model for Parameterized Synchronous Systems
Institute of Scientific and Technical Information of China (English)
Wei-Wen Xu
2004-01-01
With the purpose of making the verification of parameterized system more general and easier, in this paper, a new and intuitive language PSL (Parameterized-system Specification Language) is proposed to specify a class of parameterized synchronous systems. From a PSL script, an automatic method is proposed to generate a constraint-based symbolic model. The model can concisely symbolically represent the collections of global states by counting the number of processes in a given state. Moreover, a theorem has been proved that there is a simulation relation between the original system and its symbolic model. Since the abstract and symbolic techniques are exploited in the symbolic model, state-explosion problem in traditional verification methods is efficiently avoided. Based on the proposed symbolic model, a reachability analysis procedure is implemented using ANSI C++ on UNIX platform. Thus, a complete tool for verifying the parameterized synchronous systems is obtained and tested for some cases. The experimental results show that the method is satisfactory.
Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.
Yang, Qian; Sing-Long, Carlos A; Reed, Evan J
2017-08-01
We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.
International Nuclear Information System (INIS)
Cetnar, Jerzy
2014-01-01
The recent development of MCB - Monte Carlo Continuous Energy Burn-up code is directed towards advanced description of modern reactors, including double heterogeneity structures that exist in HTR-s. In this, we exploit the advantages of MCB methodology in integrated approach, where physics, neutronics, burnup, reprocessing, non-stationary process modeling (control rod operation) and refined spatial modeling are carried in a single flow. This approach allows for implementations of advanced statistical options like analysis of error propagation, perturbation in time domain, sensitivity and source convergence analyses. It includes statistical analysis of burnup process, emitted particle collection, thermal-hydraulic coupling, automatic power profile calculations, advanced procedures of burnup step normalization and enhanced post processing capabilities. (author)
Monte Carlo study of superconductivity in the three-band Emery model
International Nuclear Information System (INIS)
Frick, M.; Pattnaik, P.C.; Morgenstern, I.; Newns, D.M.; von der Linden, W.
1990-01-01
We have examined the three-band Hubbard model for the copper oxide planes in high-temperature superconductors using the projector quantum Monte Carlo method. We find no evidence for s-wave superconductivity
Model Considerations for Memory-based Automatic Music Transcription
Albrecht, Štěpán; Šmídl, Václav
2009-12-01
The problem of automatic music description is considered. The recorded music is modeled as a superposition of known sounds from a library weighted by unknown weights. Similar observation models are commonly used in statistics and machine learning. Many methods for estimation of the weights are available. These methods differ in the assumptions imposed on the weights. In Bayesian paradigm, these assumptions are typically expressed in the form of prior probability density function (pdf) on the weights. In this paper, commonly used assumptions about music signal are summarized and complemented by a new assumption. These assumptions are translated into pdfs and combined into a single prior density using combination of pdfs. Validity of the model is tested in simulation using synthetic data.
An automatic fault management model for distribution networks
Energy Technology Data Exchange (ETDEWEB)
Lehtonen, M; Haenninen, S [VTT Energy, Espoo (Finland); Seppaenen, M [North-Carelian Power Co (Finland); Antila, E; Markkila, E [ABB Transmit Oy (Finland)
1998-08-01
An automatic computer model, called the FI/FL-model, for fault location, fault isolation and supply restoration is presented. The model works as an integrated part of the substation SCADA, the AM/FM/GIS system and the medium voltage distribution network automation systems. In the model, three different techniques are used for fault location. First, by comparing the measured fault current to the computed one, an estimate for the fault distance is obtained. This information is then combined, in order to find the actual fault point, with the data obtained from the fault indicators in the line branching points. As a third technique, in the absence of better fault location data, statistical information of line section fault frequencies can also be used. For combining the different fault location information, fuzzy logic is used. As a result, the probability weights for the fault being located in different line sections, are obtained. Once the faulty section is identified, it is automatically isolated by remote control of line switches. Then the supply is restored to the remaining parts of the network. If needed, reserve connections from other adjacent feeders can also be used. During the restoration process, the technical constraints of the network are checked. Among these are the load carrying capacity of line sections, voltage drop and the settings of relay protection. If there are several possible network topologies, the model selects the technically best alternative. The FI/IL-model has been in trial use at two substations of the North-Carelian Power Company since November 1996. This chapter lists the practical experiences during the test use period. Also the benefits of this kind of automation are assessed and future developments are outlined
Simplest Validation of the HIJING Monte Carlo Model
Uzhinsky, V.V.
2003-01-01
Fulfillment of the energy-momentum conservation law, as well as the charge, baryon and lepton number conservation is checked for the HIJING Monte Carlo program in $pp$-interactions at $\\sqrt{s}=$ 200, 5500, and 14000 GeV. It is shown that the energy is conserved quite well. The transverse momentum is not conserved, the deviation from zero is at the level of 1--2 GeV/c, and it is connected with the hard jet production. The deviation is absent for soft interactions. Charge, baryon and lepton numbers are conserved. Azimuthal symmetry of the Monte Carlo events is studied, too. It is shown that there is a small signature of a "flow". The situation with the symmetry gets worse for nucleus-nucleus interactions.
Pushing the limits of Monte Carlo simulations for the three-dimensional Ising model
Ferrenberg, Alan M.; Xu, Jiahao; Landau, David P.
2018-04-01
While the three-dimensional Ising model has defied analytic solution, various numerical methods like Monte Carlo, Monte Carlo renormalization group, and series expansion have provided precise information about the phase transition. Using Monte Carlo simulation that employs the Wolff cluster flipping algorithm with both 32-bit and 53-bit random number generators and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising Model, with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, e.g., logarithmic derivatives of magnetization and derivatives of magnetization cumulants, we have obtained the critical inverse temperature Kc=0.221 654 626 (5 ) and the critical exponent of the correlation length ν =0.629 912 (86 ) with precision that exceeds all previous Monte Carlo estimates.
Automatic anatomy recognition via multiobject oriented active shape models.
Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A
2010-12-01
This paper studies the feasibility of developing an automatic anatomy recognition (AAR) system in clinical radiology and demonstrates its operation on clinical 2D images. The anatomy recognition method described here consists of two main components: (a) multiobject generalization of OASM and (b) object recognition strategies. The OASM algorithm is generalized to multiple objects by including a model for each object and assigning a cost structure specific to each object in the spirit of live wire. The delineation of multiobject boundaries is done in MOASM via a three level dynamic programming algorithm, wherein the first level is at pixel level which aims to find optimal oriented boundary segments between successive landmarks, the second level is at landmark level which aims to find optimal location for the landmarks, and the third level is at the object level which aims to find optimal arrangement of object boundaries over all objects. The object recognition strategy attempts to find that pose vector (consisting of translation, rotation, and scale component) for the multiobject model that yields the smallest total boundary cost for all objects. The delineation and recognition accuracies were evaluated separately utilizing routine clinical chest CT, abdominal CT, and foot MRI data sets. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF and FPVF). The recognition accuracy was assessed (1) in terms of the size of the space of the pose vectors for the model assembly that yielded high delineation accuracy, (2) as a function of the number of objects and objects' distribution and size in the model, (3) in terms of the interdependence between delineation and recognition, and (4) in terms of the closeness of the optimum recognition result to the global optimum. When multiple objects are included in the model, the delineation accuracy in terms of TPVF can be improved to 97%-98% with a low FPVF of 0.1%-0.2%. Typically, a
Model-based automatic generation of grasping regions
Bloss, David A.
1993-01-01
The problem of automatically generating stable regions for a robotic end effector on a target object, given a model of the end effector and the object is discussed. In order to generate grasping regions, an initial valid grasp transformation from the end effector to the object is obtained based on form closure requirements, and appropriate rotational and translational symmetries are associated with that transformation in order to construct a valid, continuous grasping region. The main result of this algorithm is a list of specific, valid grasp transformations of the end effector to the target object, and the appropriate combinations of translational and rotational symmetries associated with each specific transformation in order to produce a continuous grasp region.
Improving system modeling accuracy with Monte Carlo codes
International Nuclear Information System (INIS)
Johnson, A.S.
1996-01-01
The use of computer codes based on Monte Carlo methods to perform criticality calculations has become common-place. Although results frequently published in the literature report calculated k eff values to four decimal places, people who use the codes in their everyday work say that they only believe the first two decimal places of any result. The lack of confidence in the computed k eff values may be due to the tendency of the reported standard deviation to underestimate errors associated with the Monte Carlo process. The standard deviation as reported by the codes is the standard deviation of the mean of the k eff values for individual generations in the computer simulation, not the standard deviation of the computed k eff value compared with the physical system. A more subtle problem with the standard deviation of the mean as reported by the codes is that all the k eff values from the separate generations are not statistically independent since the k eff of a given generation is a function of k eff of the previous generation, which is ultimately based on the starting source. To produce a standard deviation that is more representative of the physical system, statistically independent values of k eff are needed
Towards Automatic Semantic Labelling of 3D City Models
Rook, M.; Biljecki, F.; Diakité, A. A.
2016-10-01
The lack of semantic information in many 3D city models is a considerable limiting factor in their use, as a lot of applications rely on semantics. Such information is not always available, since it is not collected at all times, it might be lost due to data transformation, or its lack may be caused by non-interoperability in data integration from other sources. This research is a first step in creating an automatic workflow that semantically labels plain 3D city model represented by a soup of polygons, with semantic and thematic information, as defined in the CityGML standard. The first step involves the reconstruction of the topology, which is used in a region growing algorithm that clusters upward facing adjacent triangles. Heuristic rules, embedded in a decision tree, are used to compute a likeliness score for these regions that either represent the ground (terrain) or a RoofSurface. Regions with a high likeliness score, to one of the two classes, are used to create a decision space, which is used in a support vector machine (SVM). Next, topological relations are utilised to select seeds that function as a start in a region growing algorithm, to create regions of triangles of other semantic classes. The topological relationships of the regions are used in the aggregation of the thematic building features. Finally, the level of detail is detected to generate the correct output in CityGML. The results show an accuracy between 85 % and 99 % in the automatic semantic labelling on four different test datasets. The paper is concluded by indicating problems and difficulties implying the next steps in the research.
Exploring uncertainty in glacier mass balance modelling with Monte Carlo simulation
Machguth, H.; Purves, R.S.; Oerlemans, J.; Hoelzle, M.; Paul, F.
2008-01-01
By means of Monte Carlo simulations we calculated uncertainty in modelled cumulative mass balance over 400 days at one particular point on the tongue of Morteratsch Glacier, Switzerland, using a glacier energy balance model of intermediate complexity. Before uncertainty assessment, the model was
Electricity prices forecasting by automatic dynamic harmonic regression models
International Nuclear Information System (INIS)
Pedregal, Diego J.; Trapero, Juan R.
2007-01-01
The changes experienced by electricity markets in recent years have created the necessity for more accurate forecast tools of electricity prices, both for producers and consumers. Many methodologies have been applied to this aim, but in the view of the authors, state space models are not yet fully exploited. The present paper proposes a univariate dynamic harmonic regression model set up in a state space framework for forecasting prices in these markets. The advantages of the approach are threefold. Firstly, a fast automatic identification and estimation procedure is proposed based on the frequency domain. Secondly, the recursive algorithms applied offer adaptive predictions that compare favourably with respect to other techniques. Finally, since the method is based on unobserved components models, explicit information about trend, seasonal and irregular behaviours of the series can be extracted. This information is of great value to the electricity companies' managers in order to improve their strategies, i.e. it provides management innovations. The good forecast performance and the rapid adaptability of the model to changes in the data are illustrated with actual prices taken from the PJM interconnection in the US and for the Spanish market for the year 2002. (author)
Microscopic imaging through turbid media Monte Carlo modeling and applications
Gu, Min; Deng, Xiaoyuan
2015-01-01
This book provides a systematic introduction to the principles of microscopic imaging through tissue-like turbid media in terms of Monte-Carlo simulation. It describes various gating mechanisms based on the physical differences between the unscattered and scattered photons and method for microscopic image reconstruction, using the concept of the effective point spread function. Imaging an object embedded in a turbid medium is a challenging problem in physics as well as in biophotonics. A turbid medium surrounding an object under inspection causes multiple scattering, which degrades the contrast, resolution and signal-to-noise ratio. Biological tissues are typically turbid media. Microscopic imaging through a tissue-like turbid medium can provide higher resolution than transillumination imaging in which no objective is used. This book serves as a valuable reference for engineers and scientists working on microscopy of tissue turbid media.
Implementation of a Monte Carlo based inverse planning model for clinical IMRT with MCNP code
International Nuclear Information System (INIS)
He, Tongming Tony
2003-01-01
Inaccurate dose calculations and limitations of optimization algorithms in inverse planning introduce systematic and convergence errors to treatment plans. This work was to implement a Monte Carlo based inverse planning model for clinical IMRT aiming to minimize the aforementioned errors. The strategy was to precalculate the dose matrices of beamlets in a Monte Carlo based method followed by the optimization of beamlet intensities. The MCNP 4B (Monte Carlo N-Particle version 4B) code was modified to implement selective particle transport and dose tallying in voxels and efficient estimation of statistical uncertainties. The resulting performance gain was over eleven thousand times. Due to concurrent calculation of multiple beamlets of individual ports, hundreds of beamlets in an IMRT plan could be calculated within a practical length of time. A finite-sized point source model provided a simple and accurate modeling of treatment beams. The dose matrix calculations were validated through measurements in phantoms. Agreements were better than 1.5% or 0.2 cm. The beamlet intensities were optimized using a parallel platform based optimization algorithm that was capable of escape from local minima and preventing premature convergence. The Monte Carlo based inverse planning model was applied to clinical cases. The feasibility and capability of Monte Carlo based inverse planning for clinical IMRT was demonstrated. Systematic errors in treatment plans of a commercial inverse planning system were assessed in comparison with the Monte Carlo based calculations. Discrepancies in tumor doses and critical structure doses were up to 12% and 17%, respectively. The clinical importance of Monte Carlo based inverse planning for IMRT was demonstrated
DEFF Research Database (Denmark)
Fournier, David A.; Skaug, Hans J.; Ancheta, Johnoel
2011-01-01
Many criteria for statistical parameter estimation, such as maximum likelihood, are formulated as a nonlinear optimization problem.Automatic Differentiation Model Builder (ADMB) is a programming framework based on automatic differentiation, aimed at highly nonlinear models with a large number...... of such a feature is the generic implementation of Laplace approximation of high-dimensional integrals for use in latent variable models. We also review the literature in which ADMB has been used, and discuss future development of ADMB as an open source project. Overall, the main advantages ofADMB are flexibility...
A model based method for automatic facial expression recognition
Kuilenburg, H. van; Wiering, M.A.; Uyl, M. den
2006-01-01
Automatic facial expression recognition is a research topic with interesting applications in the field of human-computer interaction, psychology and product marketing. The classification accuracy for an automatic system which uses static images as input is however largely limited by the image
Importance estimation in Monte Carlo modelling of neutron and photon transport
International Nuclear Information System (INIS)
Mickael, M.W.
1992-01-01
The estimation of neutron and photon importance in a three-dimensional geometry is achieved using a coupled Monte Carlo and diffusion theory calculation. The parameters required for the solution of the multigroup adjoint diffusion equation are estimated from an analog Monte Carlo simulation of the system under investigation. The solution of the adjoint diffusion equation is then used as an estimate of the particle importance in the actual simulation. This approach provides an automated and efficient variance reduction method for Monte Carlo simulations. The technique has been successfully applied to Monte Carlo simulation of neutron and coupled neutron-photon transport in the nuclear well-logging field. The results show that the importance maps obtained in a few minutes of computer time using this technique are in good agreement with Monte Carlo generated importance maps that require prohibitive computing times. The application of this method to Monte Carlo modelling of the response of neutron porosity and pulsed neutron instruments has resulted in major reductions in computation time. (Author)
Modelling of electron contamination in clinical photon beams for Monte Carlo dose calculation
International Nuclear Information System (INIS)
Yang, J; Li, J S; Qin, L; Xiong, W; Ma, C-M
2004-01-01
The purpose of this work is to model electron contamination in clinical photon beams and to commission the source model using measured data for Monte Carlo treatment planning. In this work, a planar source is used to represent the contaminant electrons at a plane above the upper jaws. The source size depends on the dimensions of the field size at the isocentre. The energy spectra of the contaminant electrons are predetermined using Monte Carlo simulations for photon beams from different clinical accelerators. A 'random creep' method is employed to derive the weight of the electron contamination source by matching Monte Carlo calculated monoenergetic photon and electron percent depth-dose (PDD) curves with measured PDD curves. We have integrated this electron contamination source into a previously developed multiple source model and validated the model for photon beams from Siemens PRIMUS accelerators. The EGS4 based Monte Carlo user code BEAM and MCSIM were used for linac head simulation and dose calculation. The Monte Carlo calculated dose distributions were compared with measured data. Our results showed good agreement (less than 2% or 2 mm) for 6, 10 and 18 MV photon beams
NRMC - A GPU code for N-Reverse Monte Carlo modeling of fluids in confined media
Sánchez-Gil, Vicente; Noya, Eva G.; Lomba, Enrique
2017-08-01
NRMC is a parallel code for performing N-Reverse Monte Carlo modeling of fluids in confined media [V. Sánchez-Gil, E.G. Noya, E. Lomba, J. Chem. Phys. 140 (2014) 024504]. This method is an extension of the usual Reverse Monte Carlo method to obtain structural models of confined fluids compatible with experimental diffraction patterns, specifically designed to overcome the problem of slow diffusion that can appear under conditions of tight confinement. Most of the computational time in N-Reverse Monte Carlo modeling is spent in the evaluation of the structure factor for each trial configuration, a calculation that can be easily parallelized. Implementation of the structure factor evaluation in NVIDIA® CUDA so that the code can be run on GPUs leads to a speed up of up to two orders of magnitude.
Automatic Modelling of Rubble Mound Breakwaters from LIDAR Data
Bueno, M.; Díaz-Vilariño, L.; González-Jorge, H.; Martínez-Sánchez, J.; Arias, P.
2015-08-01
Rubble mound breakwaters maintenance is critical to the protection of beaches and ports. LiDAR systems provide accurate point clouds from the emerged part of the structure that can be modelled to make it more useful and easy to handle. This work introduces a methodology for the automatic modelling of breakwaters with armour units of cube shape. The algorithm is divided in three main steps: normal vector computation, plane segmentation, and cube reconstruction. Plane segmentation uses the normal orientation of the points and the edge length of the cube. Cube reconstruction uses the intersection of three perpendicular planes and the edge length. Three point clouds cropped from the main point cloud of the structure are used for the tests. The number of cubes detected is around 56 % for two of the point clouds and 32 % for the third one over the total physical cubes. Accuracy assessment is done by comparison with manually drawn cubes calculating the differences between the vertexes. It ranges between 6.4 cm and 15 cm. Computing time ranges between 578.5 s and 8018.2 s. The computing time increases with the number of cubes and the requirements of collision detection.
Monte Carlo simulation of diblock copolymer microphases by means of a 'fast' off-lattice model
DEFF Research Database (Denmark)
Besold, Gerhard; Hassager, O.; Mouritsen, Ole G.
1999-01-01
We present a mesoscopic off-lattice model for the simulation of diblock copolymer melts by Monte Carlo techniques. A single copolymer molecule is modeled as a discrete Edwards chain consisting of two blocks with vertices of type A and B, respectively. The volume interaction is formulated in terms...
Modelling of the RA-1 reactor using a Monte Carlo code
International Nuclear Information System (INIS)
Quinteiro, Guillermo F.; Calabrese, Carlos R.
2000-01-01
It was carried out for the first time, a model of the Argentine RA-1 reactor using the MCNP Monte Carlo code. This model was validated using data for experimental neutron and gamma measurements at different energy ranges and locations. In addition, the resulting fluxes were compared with the data obtained using a 3D diffusion code. (author)
Parameter uncertainty and model predictions: a review of Monte Carlo results
International Nuclear Information System (INIS)
Gardner, R.H.; O'Neill, R.V.
1979-01-01
Studies of parameter variability by Monte Carlo analysis are reviewed using repeated simulations of the model with randomly selected parameter values. At the beginning of each simulation, parameter values are chosen from specific frequency distributions. This process is continued for a number of iterations sufficient to converge on an estimate of the frequency distribution of the output variables. The purpose was to explore the general properties of error propagaton in models. Testing the implicit assumptions of analytical methods and pointing out counter-intuitive results produced by the Monte Carlo approach are additional points covered
Monte Carlo Simulations of Compressible Ising Models: Do We Understand Them?
Landau, D. P.; Dünweg, B.; Laradji, M.; Tavazza, F.; Adler, J.; Cannavaccioulo, L.; Zhu, X.
Extensive Monte Carlo simulations have begun to shed light on our understanding of phase transitions and universality classes for compressible Ising models. A comprehensive analysis of a Landau-Ginsburg-Wilson hamiltonian for systems with elastic degrees of freedom resulted in the prediction that there should be four distinct cases that would have different behavior, depending upon symmetries and thermodynamic constraints. We shall provide an account of the results of careful Monte Carlo simulations for a simple compressible Ising model that can be suitably modified so as to replicate all four cases.
Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm
International Nuclear Information System (INIS)
Takaishi, Tetsuya
2013-01-01
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.
International Nuclear Information System (INIS)
Stern, R.E.; Song, J.; Work, D.B.
2017-01-01
The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.
Automatic prediction of facial trait judgments: appearance vs. structural models.
Directory of Open Access Journals (Sweden)
Mario Rojas
Full Text Available Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a derive a facial trait judgment model from training data and b predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations and classification rules (4 rules suggest that a prediction of perception of facial traits is learnable by both holistic and structural approaches; b the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.
Energy Technology Data Exchange (ETDEWEB)
Quinteiro, Guillermo F; Calabrese, Carlos R [Comision Nacional de Energia Atomica, General San Martin (Argentina). Dept. de Reactores y Centrales Nucleares
2000-07-01
It was carried out for the first time, a model of the Argentine RA-1 reactor using the MCNP Monte Carlo code. This model was validated using data for experimental neutron and gamma measurements at different energy ranges and locations. In addition, the resulting fluxes were compared with the data obtained using a 3D diffusion code. (author)
International Nuclear Information System (INIS)
Davis, J. E.; Eddy, M. J.; Sutton, T. M.; Altomari, T. J.
2007-01-01
Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces - a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation. (authors)
A Monte Carlo Investigation of the Box-Cox Model and a Nonlinear Least Squares Alternative.
Showalter, Mark H
1994-01-01
This paper reports a Monte Carlo study of the Box-Cox model and a nonlinear least squares alternative. Key results include the following: the transformation parameter in the Box-Cox model appears to be inconsistently estimated in the presence of conditional heteroskedasticity; the constant term in both the Box-Cox and the nonlinear least squares models is poorly estimated in small samples; conditional mean forecasts tend to underestimate their true value in the Box-Cox model when the transfor...
Markov chain Monte Carlo methods in directed graphical models
DEFF Research Database (Denmark)
Højbjerre, Malene
Directed graphical models present data possessing a complex dependence structure, and MCMC methods are computer-intensive simulation techniques to approximate high-dimensional intractable integrals, which emerge in such models with incomplete data. MCMC computations in directed graphical models h...
Quasi-Monte Carlo methods: applications to modeling of light transport in tissue
Schafer, Steven A.
1996-05-01
Monte Carlo modeling of light propagation can accurately predict the distribution of light in scattering materials. A drawback of Monte Carlo methods is that they converge inversely with the square root of the number of iterations. Theoretical considerations suggest that convergence which scales inversely with the first power of the number of iterations is possible. We have previously shown that one can obtain at least a portion of that improvement by using van der Corput sequences in place of a conventional pseudo-random number generator. Here, we present our further analysis, and show that quasi-Monte Carlo methods do have limited applicability to light scattering problems. We also discuss potential improvements which may increase the applicability.
Model unspecific search in CMS. Treatment of insufficient Monte Carlo statistics
Energy Technology Data Exchange (ETDEWEB)
Lieb, Jonas; Albert, Andreas; Duchardt, Deborah; Hebbeker, Thomas; Knutzen, Simon; Meyer, Arnd; Pook, Tobias; Roemer, Jonas [III. Physikalisches Institut A, RWTH Aachen University (Germany)
2016-07-01
In 2015, the CMS detector recorded proton-proton collisions at an unprecedented center of mass energy of √(s)=13 TeV. The Model Unspecific Search in CMS (MUSiC) offers an analysis approach of these data which is complementary to dedicated analyses: By taking all produced final states into consideration, MUSiC is sensitive to indicators of new physics appearing in final states that are usually not investigated. In a two step process, MUSiC first classifies events according to their physics content and then searches kinematic distributions for the most significant deviations between Monte Carlo simulations and observed data. Such a general approach introduces its own set of challenges. One of them is the treatment of situations with insufficient Monte Carlo statistics. Complementing introductory presentations on the MUSiC event selection and classification, this talk will present a method of dealing with the issue of low Monte Carlo statistics.
A Monte Carlo modeling alternative for the API Gamma Ray Calibration Facility
International Nuclear Information System (INIS)
Galford, J.E.
2017-01-01
The gamma ray pit at the API Calibration Facility, located on the University of Houston campus, defines the API unit for natural gamma ray logs used throughout the petroleum logging industry. Future use of the facility is uncertain. An alternative method is proposed to preserve the gamma ray API unit definition as an industry standard by using Monte Carlo modeling to obtain accurate counting rate-to-API unit conversion factors for gross-counting and spectral gamma ray tool designs. - Highlights: • A Monte Carlo alternative is proposed to replace empirical calibration procedures. • The proposed Monte Carlo alternative preserves the original API unit definition. • MCNP source and materials descriptions are provided for the API gamma ray pit. • Simulated results are presented for several wireline logging tool designs. • The proposed method can be adapted for use with logging-while-drilling tools.
International Nuclear Information System (INIS)
Carl Stern; Martin Lee
1999-01-01
Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models
Carl-Stern
1999-01-01
Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models.
Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation
Minasny, B.; Vrugt, J.A.; McBratney, A.B.
2011-01-01
This paper demonstrates for the first time the use of Markov Chain Monte Carlo (MCMC) simulation for parameter inference in model-based soil geostatistics. We implemented the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm to jointly summarize the posterior
Monte Carlo study of the phase diagram for the two-dimensional Z(4) model
International Nuclear Information System (INIS)
Carneiro, G.M.; Pol, M.E.; Zagury, N.
1982-05-01
The phase diagram of the two-dimensional Z(4) model on a square lattice is determined using a Monte Carlo method. The results of this simulation confirm the general features of the phase diagram predicted theoretically for the ferromagnetic case, and show the existence of a new phase with perpendicular order. (Author) [pt
International Nuclear Information System (INIS)
Ranft, J.; Schiller, A.
1984-01-01
Lattice versions with restricted suppersymmetry of simple (1+1)-dimensional supersymmetric models are numerically studied using a local hamiltonian Monte Carlo method. The pattern of supersymmetry breaking closely follows the expectations of Bartels and Bronzan obtain in an alternative lattice formulation. (orig.)
DEFF Research Database (Denmark)
Tycho, Andreas; Jørgensen, Thomas Martini; Andersen, Peter E.
2002-01-01
A Monte Carlo (MC) method for modeling optical coherence tomography (OCT) measurements of a diffusely reflecting discontinuity emb edded in a scattering medium is presented. For the first time to the authors' knowledge it is shown analytically that the applicability of an MC approach to this opti...
Vrugt, J.A.; Braak, ter C.J.F.; Clark, M.P.; Hyman, J.M.; Robinson, B.A.
2008-01-01
There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled
SKIRT: The design of a suite of input models for Monte Carlo radiative transfer simulations
Baes, M.; Camps, P.
2015-09-01
The Monte Carlo method is the most popular technique to perform radiative transfer simulations in a general 3D geometry. The algorithms behind and acceleration techniques for Monte Carlo radiative transfer are discussed extensively in the literature, and many different Monte Carlo codes are publicly available. On the contrary, the design of a suite of components that can be used for the distribution of sources and sinks in radiative transfer codes has received very little attention. The availability of such models, with different degrees of complexity, has many benefits. For example, they can serve as toy models to test new physical ingredients, or as parameterised models for inverse radiative transfer fitting. For 3D Monte Carlo codes, this requires algorithms to efficiently generate random positions from 3D density distributions. We describe the design of a flexible suite of components for the Monte Carlo radiative transfer code SKIRT. The design is based on a combination of basic building blocks (which can be either analytical toy models or numerical models defined on grids or a set of particles) and the extensive use of decorators that combine and alter these building blocks to more complex structures. For a number of decorators, e.g. those that add spiral structure or clumpiness, we provide a detailed description of the algorithms that can be used to generate random positions. Advantages of this decorator-based design include code transparency, the avoidance of code duplication, and an increase in code maintainability. Moreover, since decorators can be chained without problems, very complex models can easily be constructed out of simple building blocks. Finally, based on a number of test simulations, we demonstrate that our design using customised random position generators is superior to a simpler design based on a generic black-box random position generator.
A measurement-based generalized source model for Monte Carlo dose simulations of CT scans.
Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun
2017-03-07
The goal of this study is to develop a generalized source model for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1 mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients' CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology.
A measurement-based generalized source model for Monte Carlo dose simulations of CT scans
Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun
2017-03-01
The goal of this study is to develop a generalized source model for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1 mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients’ CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology.
ModelMage: a tool for automatic model generation, selection and management.
Flöttmann, Max; Schaber, Jörg; Hoops, Stephan; Klipp, Edda; Mendes, Pedro
2008-01-01
Mathematical modeling of biological systems usually involves implementing, simulating, and discriminating several candidate models that represent alternative hypotheses. Generating and managing these candidate models is a tedious and difficult task and can easily lead to errors. ModelMage is a tool that facilitates management of candidate models. It is designed for the easy and rapid development, generation, simulation, and discrimination of candidate models. The main idea of the program is to automatically create a defined set of model alternatives from a single master model. The user provides only one SBML-model and a set of directives from which the candidate models are created by leaving out species, modifiers or reactions. After generating models the software can automatically fit all these models to the data and provides a ranking for model selection, in case data is available. In contrast to other model generation programs, ModelMage aims at generating only a limited set of models that the user can precisely define. ModelMage uses COPASI as a simulation and optimization engine. Thus, all simulation and optimization features of COPASI are readily incorporated. ModelMage can be downloaded from http://sysbio.molgen.mpg.de/modelmage and is distributed as free software.
[Modeling and implementation method for the automatic biochemistry analyzer control system].
Wang, Dong; Ge, Wan-cheng; Song, Chun-lin; Wang, Yun-guang
2009-03-01
In this paper the system structure The automatic biochemistry analyzer is a necessary instrument for clinical diagnostics. First of is analyzed. The system problems description and the fundamental principles for dispatch are brought forward. Then this text puts emphasis on the modeling for the automatic biochemistry analyzer control system. The objects model and the communications model are put forward. Finally, the implementation method is designed. It indicates that the system based on the model has good performance.
The design of control algorithm for automatic start-up model of HWRR
International Nuclear Information System (INIS)
Guo Wenqi
1990-01-01
The design of control algorithm for automatic start-up model of HWRR (Heavy Water Research Reactor), the calculation of μ value and the application of digital compensator are described. Finally The flow diagram of the automatic start-up and digital compensator program for HWRR are given
forecasting with nonlinear time series model: a monte-carlo
African Journals Online (AJOL)
PUBLICATIONS1
erated recursively up to any step greater than one. For nonlinear time series model, point forecast for step one can be done easily like in the linear case but forecast for a step greater than or equal to ..... London. Franses, P. H. (1998). Time series models for business and Economic forecasting, Cam- bridge University press.
Monte Carlo sensitivity analysis of an Eulerian large-scale air pollution model
International Nuclear Information System (INIS)
Dimov, I.; Georgieva, R.; Ostromsky, Tz.
2012-01-01
Variance-based approaches for global sensitivity analysis have been applied and analyzed to study the sensitivity of air pollutant concentrations according to variations of rates of chemical reactions. The Unified Danish Eulerian Model has been used as a mathematical model simulating a remote transport of air pollutants. Various Monte Carlo algorithms for numerical integration have been applied to compute Sobol's global sensitivity indices. A newly developed Monte Carlo algorithm based on Sobol's quasi-random points MCA-MSS has been applied for numerical integration. It has been compared with some existing approaches, namely Sobol's ΛΠ τ sequences, an adaptive Monte Carlo algorithm, the plain Monte Carlo algorithm, as well as, eFAST and Sobol's sensitivity approaches both implemented in SIMLAB software. The analysis and numerical results show advantages of MCA-MSS for relatively small sensitivity indices in terms of accuracy and efficiency. Practical guidelines on the estimation of Sobol's global sensitivity indices in the presence of computational difficulties have been provided. - Highlights: ► Variance-based global sensitivity analysis is performed for the air pollution model UNI-DEM. ► The main effect of input parameters dominates over higher-order interactions. ► Ozone concentrations are influenced mostly by variability of three chemical reactions rates. ► The newly developed MCA-MSS for multidimensional integration is compared with other approaches. ► More precise approaches like MCA-MSS should be applied when the needed accuracy has not been achieved.
Perturbation analysis for Monte Carlo continuous cross section models
International Nuclear Information System (INIS)
Kennedy, Chris B.; Abdel-Khalik, Hany S.
2011-01-01
Sensitivity analysis, including both its forward and adjoint applications, collectively referred to hereinafter as Perturbation Analysis (PA), is an essential tool to complete Uncertainty Quantification (UQ) and Data Assimilation (DA). PA-assisted UQ and DA have traditionally been carried out for reactor analysis problems using deterministic as opposed to stochastic models for radiation transport. This is because PA requires many model executions to quantify how variations in input data, primarily cross sections, affect variations in model's responses, e.g. detectors readings, flux distribution, multiplication factor, etc. Although stochastic models are often sought for their higher accuracy, their repeated execution is at best computationally expensive and in reality intractable for typical reactor analysis problems involving many input data and output responses. Deterministic methods however achieve computational efficiency needed to carry out the PA analysis by reducing problem dimensionality via various spatial and energy homogenization assumptions. This however introduces modeling error components into the PA results which propagate to the following UQ and DA analyses. The introduced errors are problem specific and therefore are expected to limit the applicability of UQ and DA analyses to reactor systems that satisfy the introduced assumptions. This manuscript introduces a new method to complete PA employing a continuous cross section stochastic model and performed in a computationally efficient manner. If successful, the modeling error components introduced by deterministic methods could be eliminated, thereby allowing for wider applicability of DA and UQ results. Two MCNP models demonstrate the application of the new method - a Critical Pu Sphere (Jezebel), a Pu Fast Metal Array (Russian BR-1). The PA is completed for reaction rate densities, reaction rate ratios, and the multiplication factor. (author)
Absorbed dose in fibrotic microenvironment models employing Monte Carlo simulation
International Nuclear Information System (INIS)
Zambrano Ramírez, O.D.; Rojas Calderón, E.L.; Azorín Vega, E.P.; Ferro Flores, G.; Martínez Caballero, E.
2015-01-01
The presence or absence of fibrosis and yet more, the multimeric and multivalent nature of the radiopharmaceutical have recently been reported to have an effect on the radiation absorbed dose in tumor microenvironment models. Fibroblast and myofibroblast cells produce the extracellular matrix by the secretion of proteins which provide structural and biochemical support to cells. The reactive and reparative mechanisms triggered during the inflammatory process causes the production and deposition of extracellular matrix proteins, the abnormal excessive growth of the connective tissue leads to fibrosis. In this work, microenvironment (either not fibrotic or fibrotic) models composed of seven spheres representing cancer cells of 10 μm in diameter each with a 5 μm diameter inner sphere (cell nucleus) were created in two distinct radiation transport codes (PENELOPE and MCNP). The purpose of creating these models was to determine the radiation absorbed dose in the nucleus of cancer cells, based on previously reported radiopharmaceutical retain (by HeLa cells) percentages of the 177 Lu-Tyr 3 -octreotate (monomeric) and 177 Lu-Tyr 3 -octreotate-AuNP (multimeric) radiopharmaceuticals. A comparison in the results between the PENELOPE and MCNP was done. We found a good agreement in the results of the codes. The percent difference between the increase percentages of the absorbed dose in the not fibrotic model with respect to the fibrotic model of the codes PENELOPE and MCNP was found to be under 1% for both radiopharmaceuticals. (authors)
Energy Technology Data Exchange (ETDEWEB)
Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)
2016-02-15
A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.
Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia
2012-01-01
Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.
An enhanced model for automatically extracting topic phrase from ...
African Journals Online (AJOL)
The key benefit foreseen from this automatic document classification is not only related to search engines, but also to many other fields like, document organization, text filtering and semantic index managing. Key words: Keyphrase extraction, machine learning, search engine snippet, document classification, topic tracking ...
Adaptable three-dimensional Monte Carlo modeling of imaged blood vessels in skin
Pfefer, T. Joshua; Barton, Jennifer K.; Chan, Eric K.; Ducros, Mathieu G.; Sorg, Brian S.; Milner, Thomas E.; Nelson, J. Stuart; Welch, Ashley J.
1997-06-01
In order to reach a higher level of accuracy in simulation of port wine stain treatment, we propose to discard the typical layered geometry and cylindrical blood vessel assumptions made in optical models and use imaging techniques to define actual tissue geometry. Two main additions to the typical 3D, weighted photon, variable step size Monte Carlo routine were necessary to achieve this goal. First, optical low coherence reflectometry (OLCR) images of rat skin were used to specify a 3D material array, with each entry assigned a label to represent the type of tissue in that particular voxel. Second, the Monte Carlo algorithm was altered so that when a photon crosses into a new voxel, the remaining path length is recalculated using the new optical properties, as specified by the material array. The model has shown good agreement with data from the literature. Monte Carlo simulations using OLCR images of asymmetrically curved blood vessels show various effects such as shading, scattering-induced peaks at vessel surfaces, and directionality-induced gradients in energy deposition. In conclusion, this augmentation of the Monte Carlo method can accurately simulate light transport for a wide variety of nonhomogeneous tissue geometries.
The structure of liquid water by polarized neutron diffraction and reverse Monte Carlo modelling.
Temleitner, László; Pusztai, László; Schweika, Werner
2007-08-22
The coherent static structure factor of water has been investigated by polarized neutron diffraction. Polarization analysis allows us to separate the huge incoherent scattering background from hydrogen and to obtain high quality data of the coherent scattering from four different mixtures of liquid H(2)O and D(2)O. The information obtained by the variation of the scattering contrast confines the configurational space of water and is used by the reverse Monte Carlo technique to model the total structure factors. Structural characteristics have been calculated directly from the resulting sets of particle coordinates. Consistency with existing partial pair correlation functions, derived without the application of polarized neutrons, was checked by incorporating them into our reverse Monte Carlo calculations. We also performed Monte Carlo simulations of a hard sphere system, which provides an accurate estimate of the information content of the measured data. It is shown that the present combination of polarized neutron scattering and reverse Monte Carlo structural modelling is a promising approach towards a detailed understanding of the microscopic structure of water.
Automatic Generation of Test Cases from UML Models
Directory of Open Access Journals (Sweden)
Constanza Pérez
2018-04-01
Full Text Available [Context] The growing demand for high-quality software has caused the industry to incorporate processes to enable them to comply with these standards, but increasing the cost of development. A strategy to reduce this cost is to incorporate quality evaluations from early stages of software development. A technique that facilitates this evaluation is the model-based testing, which allows to generate test cases at early phases using as input the conceptual models of the system. [Objective] In this paper, we introduce TCGen, a tool that enables the automatic generation of abstract test cases starting from UML conceptual models. [Method] The design and implementation of TCGen, a technique that applies different testing criteria to class diagrams and state transition diagrams to generates test cases, is presented as a model-based testing approach. To do that, TCGen uses UML models, which are widely used at industry and a set of algorithms that recognize the concepts in the models in order to generate abstract test cases. [Results] An exploratory experimental evaluation has been performed to compare the TCGen tool with traditional testing. [Conclusions] Even though the exploratory evaluation shows promising results, it is necessary to perform more empirical evaluations in order to generalize the results. Abstract (in Spanish: [Contexto] La creciente demanda de software de alta calidad ha provocado que la industria incorpore procesos para permitirles cumplir con estos estándares, pero aumentando el costo del desarrollo. Una estrategia para reducir este costo es incorporar evaluaciones de calidad desde las primeras etapas del desarrollo del software. Una técnica que facilita esta evaluación es la prueba basada en modelos, que permite generar casos de prueba en fases tempranas utilizando como entrada los modelos conceptuales del sistema. [Objetivo] En este artículo, presentamos TCGen, una herramienta que permite la generación automática de casos de
Modelling the IRSN's radio-photo-luminescent dosimeter using the MCPNX Monte Carlo code
International Nuclear Information System (INIS)
Hocine, N.; Donadille, L.; Huet, Ch.; Itie, Ch.
2010-01-01
The authors report the modelling of the new radio-photo-luminescent (RPL) dosimeter of the IRSN using the MCPNX Monte Carlo code. The Hp(10) and Hp(0, 07) dose equivalents are computed for different irradiation configurations involving photonic beams (gamma and X) defined according to the ISO 4037-1 standard. Results are compared to experimental measurements performed on the RPL dosimeter. The agreement is good and the model is thus validated
Path Tracking Control of Automatic Parking Cloud Model considering the Influence of Time Delay
Directory of Open Access Journals (Sweden)
Yiding Hua
2017-01-01
Full Text Available This paper establishes the kinematic model of the automatic parking system and analyzes the kinematic constraints of the vehicle. Furthermore, it solves the problem where the traditional automatic parking system model fails to take into account the time delay. Firstly, based on simulating calculation, the influence of time delay on the dynamic trajectory of a vehicle in the automatic parking system is analyzed under the transverse distance Dlateral between different target spaces. Secondly, on the basis of cloud model, this paper utilizes the tracking control of an intelligent path closer to human intelligent behavior to further study the Cloud Generator-based parking path tracking control method and construct a vehicle path tracking control model. Moreover, tracking and steering control effects of the model are verified through simulation analysis. Finally, the effectiveness and timeliness of automatic parking controller in the aspect of path tracking are tested through a real vehicle experiment.
Monte Carlo based toy model for fission process
International Nuclear Information System (INIS)
Kurniadi, R.; Waris, A.; Viridi, S.
2014-01-01
There are many models and calculation techniques to obtain visible image of fission yield process. In particular, fission yield can be calculated by using two calculations approach, namely macroscopic approach and microscopic approach. This work proposes another calculation approach in which the nucleus is treated as a toy model. Hence, the fission process does not represent real fission process in nature completely. The toy model is formed by Gaussian distribution of random number that randomizes distance like the distance between particle and central point. The scission process is started by smashing compound nucleus central point into two parts that are left central and right central points. These three points have different Gaussian distribution parameters such as mean (μ CN , μ L , μ R ), and standard deviation (σ CN , σ L , σ R ). By overlaying of three distributions, the number of particles (N L , N R ) that are trapped by central points can be obtained. This process is iterated until (N L , N R ) become constant numbers. Smashing process is repeated by changing σ L and σ R , randomly
Monte Carlo Analysis of Reservoir Models Using Seismic Data and Geostatistical Models
Zunino, A.; Mosegaard, K.; Lange, K.; Melnikova, Y.; Hansen, T. M.
2013-12-01
We present a study on the analysis of petroleum reservoir models consistent with seismic data and geostatistical constraints performed on a synthetic reservoir model. Our aim is to invert directly for structure and rock bulk properties of the target reservoir zone. To infer the rock facies, porosity and oil saturation seismology alone is not sufficient but a rock physics model must be taken into account, which links the unknown properties to the elastic parameters. We then combine a rock physics model with a simple convolutional approach for seismic waves to invert the "measured" seismograms. To solve this inverse problem, we employ a Markov chain Monte Carlo (MCMC) method, because it offers the possibility to handle non-linearity, complex and multi-step forward models and provides realistic estimates of uncertainties. However, for large data sets the MCMC method may be impractical because of a very high computational demand. To face this challenge one strategy is to feed the algorithm with realistic models, hence relying on proper prior information. To address this problem, we utilize an algorithm drawn from geostatistics to generate geologically plausible models which represent samples of the prior distribution. The geostatistical algorithm learns the multiple-point statistics from prototype models (in the form of training images), then generates thousands of different models which are accepted or rejected by a Metropolis sampler. To further reduce the computation time we parallelize the software and run it on multi-core machines. The solution of the inverse problem is then represented by a collection of reservoir models in terms of facies, porosity and oil saturation, which constitute samples of the posterior distribution. We are finally able to produce probability maps of the properties we are interested in by performing statistical analysis on the collection of solutions.
Monte Carlo simulations of a model for opinion formation
Bordogna, C. M.; Albano, E. V.
2007-04-01
A model for opinion formation based on the Theory of Social Impact is presented and studied by means of numerical simulations. Individuals with two states of opinion are impacted due to social interactions with: i) members of the society, ii) a strong leader with a well-defined opinion and iii) the mass media that could either support or compete with the leader. Due to that competition, the average opinion of the social group exhibits phase-transition like behaviour between different states of opinion.
Strain in the mesoscale kinetic Monte Carlo model for sintering
DEFF Research Database (Denmark)
Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.
2014-01-01
anisotropic strains for homogeneous powder compacts with aspect ratios different from unity. It is shown that the line direction biases shrinkage strains in proportion the compact dimension aspect ratios. A new algorithm that corrects this bias in strains is proposed; the direction for collapsing the column...... densification by vacancy annihilation removes an isolated pore site at a grain boundary and collapses a column of sites extending from the vacancy to the surface of sintering compact, through the center of mass of the nearest grain. Using this algorithm, the existing published kMC models are shown to produce...
International Nuclear Information System (INIS)
Allam, Kh. A.
2017-01-01
In this work, a new methodology is developed based on Monte Carlo simulation for tunnels and mines external dose calculation. Tunnels external dose evaluation model of a cylindrical shape of finite thickness with an entrance and with or without exit. A photon transportation model was applied for exposure dose calculations. A new software based on Monte Carlo solution was designed and programmed using Delphi programming language. The variation of external dose due to radioactive nuclei in a mine tunnel and the corresponding experimental data lies in the range 7.3 19.9%. The variation of specific external dose rate with position in, tunnel building material density and composition were studied. The given new model has more flexible for real external dose in any cylindrical tunnel structure calculations. (authors)
Setup of HDRK-Man voxel model in Geant4 Monte Carlo code
Energy Technology Data Exchange (ETDEWEB)
Jeong, Jong Hwi; Cho, Sung Koo; Kim, Chan Hyeong [Hanyang Univ., Seoul (Korea, Republic of); Choi, Sang Hyoun [Inha Univ., Incheon (Korea, Republic of); Cho, Kun Woo [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2008-10-15
Many different voxel models, developed using tomographic images of human body, are used in various fields including both ionizing and non-ionizing radiation fields. Recently a high-quality voxel model/ named HDRK-Man, was constructed at Hanyang University and used to calculate the dose conversion coefficients (DCC) values for external photon and neutron beams using the MCNPX Monte Carlo code. The objective of the present study is to set up the HDRK-Man model in Geant4 in order to use it in more advanced calculations such as 4-D Monte Carlo simulations and space dosimetry studies involving very high energy particles. To that end, the HDRK-Man was ported to Geant4 and used to calculate the DCC values for external photon beams. The calculated values were then compared with the results of the MCNPX code. In addition, a computational Linux cluster was built to improve the computing speed in Geant4.
Randomly dispersed particle fuel model in the PSG Monte Carlo neutron transport code
International Nuclear Information System (INIS)
Leppaenen, J.
2007-01-01
High-temperature gas-cooled reactor fuels are composed of thousands of microscopic fuel particles, randomly dispersed in a graphite matrix. The modelling of such geometry is complicated, especially using continuous-energy Monte Carlo codes, which are unable to apply any deterministic corrections in the calculation. This paper presents the geometry routine developed for modelling randomly dispersed particle fuels using the PSG Monte Carlo reactor physics code. The model is based on the delta-tracking method, and it takes into account the spatial self-shielding effects and the random dispersion of the fuel particles. The calculation routine is validated by comparing the results to reference MCNP4C calculations using uranium and plutonium based fuels. (authors)
Flat-histogram methods in quantum Monte Carlo simulations: Application to the t-J model
International Nuclear Information System (INIS)
Diamantis, Nikolaos G.; Manousakis, Efstratios
2016-01-01
We discuss that flat-histogram techniques can be appropriately applied in the sampling of quantum Monte Carlo simulation in order to improve the statistical quality of the results at long imaginary time or low excitation energy. Typical imaginary-time correlation functions calculated in quantum Monte Carlo are subject to exponentially growing errors as the range of imaginary time grows and this smears the information on the low energy excitations. We show that we can extract the low energy physics by modifying the Monte Carlo sampling technique to one in which configurations which contribute to making the histogram of certain quantities flat are promoted. We apply the diagrammatic Monte Carlo (diag-MC) method to the motion of a single hole in the t-J model and we show that the implementation of flat-histogram techniques allows us to calculate the Green's function in a wide range of imaginary-time. In addition, we show that applying the flat-histogram technique alleviates the “sign”-problem associated with the simulation of the single-hole Green's function at long imaginary time. (paper)
DEFF Research Database (Denmark)
Nathan, R.P.; Thomas, P.J.; Jain, M.
2003-01-01
and identify the likely size of these effects on D-e distributions. The study employs the MCNP 4C Monte Carlo electron/photon transport model, supported by an experimental validation of the code in several case studies. We find good agreement between the experimental measurements and the Monte Carlo...
A vectorized Monte Carlo code for modeling photon transport in SPECT
International Nuclear Information System (INIS)
Smith, M.F.; Floyd, C.E. Jr.; Jaszczak, R.J.
1993-01-01
A vectorized Monte Carlo computer code has been developed for modeling photon transport in single photon emission computed tomography (SPECT). The code models photon transport in a uniform attenuating region and photon detection by a gamma camera. It is adapted from a history-based Monte Carlo code in which photon history data are stored in scalar variables and photon histories are computed sequentially. The vectorized code is written in FORTRAN77 and uses an event-based algorithm in which photon history data are stored in arrays and photon history computations are performed within DO loops. The indices of the DO loops range over the number of photon histories, and these loops may take advantage of the vector processing unit of our Stellar GS1000 computer for pipelined computations. Without the use of the vector processor the event-based code is faster than the history-based code because of numerical optimization performed during conversion to the event-based algorithm. When only the detection of unscattered photons is modeled, the event-based code executes 5.1 times faster with the use of the vector processor than without; when the detection of scattered and unscattered photons is modeled the speed increase is a factor of 2.9. Vectorization is a valuable way to increase the performance of Monte Carlo code for modeling photon transport in SPECT
International Nuclear Information System (INIS)
Taillade, Frédéric; Dumont, Eric; Belin, Etienne
2008-01-01
We propose an analytical model for backscattered luminance in fog and derive an expression for the visibility signal-to-noise ratio as a function of meteorological visibility distance. The model uses single scattering processes. It is based on the Mie theory and the geometry of the optical device (emitter and receiver). In particular, we present an overlap function and take the phase function of fog into account. The results of the backscattered luminance obtained with our analytical model are compared to simulations made using the Monte Carlo method based on multiple scattering processes. An excellent agreement is found in that the discrepancy between the results is smaller than the Monte Carlo standard uncertainties. If we take no account of the geometry of the optical device, the results of the model-estimated backscattered luminance differ from the simulations by a factor 20. We also conclude that the signal-to-noise ratio computed with the Monte Carlo method and our analytical model is in good agreement with experimental results since the mean difference between the calculations and experimental measurements is smaller than the experimental uncertainty
Monte Carlo modeling of ion beam induced secondary electrons
Energy Technology Data Exchange (ETDEWEB)
Huh, U., E-mail: uhuh@vols.utk.edu [Biochemistry & Cellular & Molecular Biology, University of Tennessee, Knoxville, TN 37996-0840 (United States); Cho, W. [Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996-2100 (United States); Joy, D.C. [Biochemistry & Cellular & Molecular Biology, University of Tennessee, Knoxville, TN 37996-0840 (United States); Center for Nanophase Materials Science, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)
2016-09-15
Ion induced secondary electrons (iSE) can produce high-resolution images ranging from a few eV to 100 keV over a wide range of materials. The interpretation of such images requires knowledge of the secondary electron yields (iSE δ) for each of the elements and materials present and as a function of the incident beam energy. Experimental data for helium ions are currently limited to 40 elements and six compounds while other ions are not well represented. To overcome this limitation, we propose a simple procedure based on the comprehensive work of Berger et al. Here we show that between the energy range of 10–100 keV the Berger et al. data for elements and compounds can be accurately represented by a single universal curve. The agreement between the limited experimental data that is available and the predictive model is good, and has been found to provide reliable yield data for a wide range of elements and compounds. - Highlights: • The Universal ASTAR Yield Curve was derived from data recently published by NIST. • IONiSE incorporated with the Curve will predict iSE yield for elements and compounds. • This approach can also handle other ion beams by changing basic scattering profile.
Energy Technology Data Exchange (ETDEWEB)
Garcia, Marie-Paule, E-mail: marie-paule.garcia@univ-brest.fr; Villoing, Daphnée [UMR 1037 INSERM/UPS, CRCT, 133 Route de Narbonne, 31062 Toulouse (France); McKay, Erin [St George Hospital, Gray Street, Kogarah, New South Wales 2217 (Australia); Ferrer, Ludovic [ICO René Gauducheau, Boulevard Jacques Monod, St Herblain 44805 (France); Cremonesi, Marta; Botta, Francesca; Ferrari, Mahila [European Institute of Oncology, Via Ripamonti 435, Milano 20141 (Italy); Bardiès, Manuel [UMR 1037 INSERM/UPS, CRCT, 133 Route de Narbonne, Toulouse 31062 (France)
2015-12-15
Purpose: The TestDose platform was developed to generate scintigraphic imaging protocols and associated dosimetry by Monte Carlo modeling. TestDose is part of a broader project (www.dositest.com) whose aim is to identify the biases induced by different clinical dosimetry protocols. Methods: The TestDose software allows handling the whole pipeline from virtual patient generation to resulting planar and SPECT images and dosimetry calculations. The originality of their approach relies on the implementation of functional segmentation for the anthropomorphic model representing a virtual patient. Two anthropomorphic models are currently available: 4D XCAT and ICRP 110. A pharmacokinetic model describes the biodistribution of a given radiopharmaceutical in each defined compartment at various time-points. The Monte Carlo simulation toolkit GATE offers the possibility to accurately simulate scintigraphic images and absorbed doses in volumes of interest. The TestDose platform relies on GATE to reproduce precisely any imaging protocol and to provide reference dosimetry. For image generation, TestDose stores user’s imaging requirements and generates automatically command files used as input for GATE. Each compartment is simulated only once and the resulting output is weighted using pharmacokinetic data. Resulting compartment projections are aggregated to obtain the final image. For dosimetry computation, emission data are stored in the platform database and relevant GATE input files are generated for the virtual patient model and associated pharmacokinetics. Results: Two samples of software runs are given to demonstrate the potential of TestDose. A clinical imaging protocol for the Octreoscan™ therapeutical treatment was implemented using the 4D XCAT model. Whole-body “step and shoot” acquisitions at different times postinjection and one SPECT acquisition were generated within reasonable computation times. Based on the same Octreoscan™ kinetics, a dosimetry
A sequential Monte Carlo model of the combined GB gas and electricity network
International Nuclear Information System (INIS)
Chaudry, Modassar; Wu, Jianzhong; Jenkins, Nick
2013-01-01
A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties. -- Highlights: •A Monte Carlo model of the combined GB gas and electricity network was developed. •Reliability indices are calculated for the combined GB gas and electricity system. •The efficacy of doubling GB gas storage capacity on reliability of the energy system is assessed. •Integrated reliability indices could be used to assess the impact of investment in energy assets
International Nuclear Information System (INIS)
Peterson, S W; Polf, J; Archambault, L; Beddar, S; Bues, M; Ciangaru, G; Smith, A
2009-01-01
The purpose of this study is to validate the accuracy of a Monte Carlo calculation model of a proton magnetic beam scanning delivery nozzle developed using the Geant4 toolkit. The Monte Carlo model was used to produce depth dose and lateral profiles, which were compared to data measured in the clinical scanning treatment nozzle at several energies. Comparisons were also made between measured and simulated off-axis profiles to test the accuracy of the model's magnetic steering. Comparison of the 80% distal dose fall-off values for the measured and simulated depth dose profiles agreed to within 1 mm for the beam energies evaluated. Agreement of the full width at half maximum values for the measured and simulated lateral fluence profiles was within 1.3 mm for all energies. The position of measured and simulated spot positions for the magnetically steered beams agreed to within 0.7 mm of each other. Based on these results, we found that the Geant4 Monte Carlo model of the beam scanning nozzle has the ability to accurately predict depth dose profiles, lateral profiles perpendicular to the beam axis and magnetic steering of a proton beam during beam scanning proton therapy.
Monte Carlo evaluation of path integral for the nuclear shell model
International Nuclear Information System (INIS)
Lang, G.H.
1993-01-01
The authors present a path-integral formulation of the nuclear shell model using auxillary fields; the path-integral is evaluated by Monte Carlo methods. The method scales favorably with valence-nucleon number and shell-model basis: full-basis calculations are demonstrated up to the rare-earth region, which cannot be treated by other methods. Observables are calculated for the ground state and in a thermal ensemble. Dynamical correlations are obtained, from which strength functions are extracted through the Maximum Entropy method. Examples in the s-d shell, where exact diagonalization can be carried out, compared well with exact results. The open-quotes sign problemclose quotes generic to quantum Monte Carlo calculations is found to be absent in the attractive pairing-plus-multipole interactions. The formulation is general for interacting fermion systems and is well suited for parallel computation. The authors have implemented it on the Intel Touchstone Delta System, achieving better than 99% parallelization
MONTE CARLO ANALYSES OF THE YALINA THERMAL FACILITY WITH SERPENT STEREOLITHOGRAPHY GEOMETRY MODEL
Energy Technology Data Exchange (ETDEWEB)
Talamo, A.; Gohar, Y.
2015-01-01
This paper analyzes the YALINA Thermal subcritical assembly of Belarus using two different Monte Carlo transport programs, SERPENT and MCNP. The MCNP model is based on combinatorial geometry and universes hierarchy, while the SERPENT model is based on Stereolithography geometry. The latter consists of unstructured triangulated surfaces defined by the normal and vertices. This geometry format is used by 3D printers and it has been created by: the CUBIT software, MATLAB scripts, and C coding. All the Monte Carlo simulations have been performed using the ENDF/B-VII.0 nuclear data library. Both MCNP and SERPENT share the same geometry specifications, which describe the facility details without using any material homogenization. Three different configurations have been studied with different number of fuel rods. The three fuel configurations use 216, 245, or 280 fuel rods, respectively. The numerical simulations show that the agreement between SERPENT and MCNP results is within few tens of pcms.
Use of Monte Carlo modeling approach for evaluating risk and environmental compliance
International Nuclear Information System (INIS)
Higley, K.A.; Strenge, D.L.
1988-09-01
Evaluating compliance with environmental regulations, specifically those regulations that pertain to human exposure, can be a difficult task. Historically, maximum individual or worst-case exposures have been calculated as a basis for evaluating risk or compliance with such regulations. However, these calculations may significantly overestimate exposure and may not provide a clear understanding of the uncertainty in the analysis. The use of Monte Carlo modeling techniques can provide a better understanding of the potential range of exposures and the likelihood of high (worst-case) exposures. This paper compares the results of standard exposure estimation techniques with the Monte Carlo modeling approach. The authors discuss the potential application of this approach for demonstrating regulatory compliance, along with the strengths and weaknesses of the approach. Suggestions on implementing this method as a routine tool in exposure and risk analyses are also presented. 16 refs., 5 tabs
Implementation of a Monte Carlo method to model photon conversion for solar cells
International Nuclear Information System (INIS)
Canizo, C. del; Tobias, I.; Perez-Bedmar, J.; Pan, A.C.; Luque, A.
2008-01-01
A physical model describing different photon conversion mechanisms is presented in the context of photovoltaic applications. To solve the resulting system of equations, a Monte Carlo ray-tracing model is implemented, which takes into account the coupling of the photon transport phenomena to the non-linear rate equations describing luminescence. It also separates the generation of rays from the two very different sources of photons involved (the sun and the luminescence centers). The Monte Carlo simulator presented in this paper is proposed as a tool to help in the evaluation of candidate materials for up- and down-conversion. Some application examples are presented, exploring the range of values that the most relevant parameters describing the converter should have in order to give significant gain in photocurrent
Testing Lorentz Invariance Emergence in the Ising Model using Monte Carlo simulations
Dias Astros, Maria Isabel
2017-01-01
In the context of the Lorentz invariance as an emergent phenomenon at low energy scales to study quantum gravity a system composed by two 3D interacting Ising models (one with an anisotropy in one direction) was proposed. Two Monte Carlo simulations were run: one for the 2D Ising model and one for the target model. In both cases the observables (energy, magnetization, heat capacity and magnetic susceptibility) were computed for different lattice sizes and a Binder cumulant introduced in order to estimate the critical temperature of the systems. Moreover, the correlation function was calculated for the 2D Ising model.
Monte Carlo study of radiation-induced demagnetization using the two-dimensional Ising model
International Nuclear Information System (INIS)
Samin, Adib; Cao, Lei
2015-01-01
A simple radiation-damage model based on the Ising model for magnets is proposed to study the effects of radiation on the magnetism of permanent magnets. The model is studied in two dimensions using a Monte Carlo simulation, and it accounts for the radiation through the introduction of a localized heat pulse. The model exhibits qualitative agreement with experimental results, and it clearly elucidates the role that the coercivity and the radiation particle’s energy play in the process. A more quantitative agreement with experiment will entail accounting for the long-range dipole–dipole interactions and the crystalline anisotropy.
Monte Carlo study of radiation-induced demagnetization using the two-dimensional Ising model
Energy Technology Data Exchange (ETDEWEB)
Samin, Adib; Cao, Lei
2015-10-01
A simple radiation-damage model based on the Ising model for magnets is proposed to study the effects of radiation on the magnetism of permanent magnets. The model is studied in two dimensions using a Monte Carlo simulation, and it accounts for the radiation through the introduction of a localized heat pulse. The model exhibits qualitative agreement with experimental results, and it clearly elucidates the role that the coercivity and the radiation particle’s energy play in the process. A more quantitative agreement with experiment will entail accounting for the long-range dipole–dipole interactions and the crystalline anisotropy.
Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox
DEFF Research Database (Denmark)
Nonejad, Nima
This paper details Particle Markov chain Monte Carlo techniques for analysis of unobserved component time series models using several economic data sets. PMCMC combines the particle filter with the Metropolis-Hastings algorithm. Overall PMCMC provides a very compelling, computationally fast...... and efficient framework for estimation. These advantages are used to for instance estimate stochastic volatility models with leverage effect or with Student-t distributed errors. We also model changing time series characteristics of the US inflation rate by considering a heteroskedastic ARFIMA model where...
Monte Carlo modeling of neutron imaging at the SINQ spallation source
International Nuclear Information System (INIS)
Lebenhaft, J.R.; Lehmann, E.H.; Pitcher, E.J.; McKinney, G.W.
2003-01-01
Modeling of the Swiss Spallation Neutron Source (SINQ) has been used to demonstrate the neutron radiography capability of the newly released MPI-version of the MCNPX Monte Carlo code. A detailed MCNPX model was developed of SINQ and its associated neutron transmission radiography (NEUTRA) facility. Preliminary validation of the model was performed by comparing the calculated and measured neutron fluxes in the NEUTRA beam line, and a simulated radiography image was generated for a sample consisting of steel tubes containing different materials. This paper describes the SINQ facility, provides details of the MCNPX model, and presents preliminary results of the neutron imaging. (authors)
State-to-state models of vibrational relaxation in Direct Simulation Monte Carlo (DSMC)
Oblapenko, G. P.; Kashkovsky, A. V.; Bondar, Ye A.
2017-02-01
In the present work, the application of state-to-state models of vibrational energy exchanges to the Direct Simulation Monte Carlo (DSMC) is considered. A state-to-state model for VT transitions of vibrational energy in nitrogen and oxygen, based on the application of the inverse Laplace transform to results of quasiclassical trajectory calculations (QCT) of vibrational energy transitions, along with the Forced Harmonic Oscillator (FHO) state-to-state model is implemented in DSMC code and applied to flows around blunt bodies. Comparisons are made with the widely used Larsen-Borgnakke model and the in uence of multi-quantum VT transitions is assessed.
Su, Peiran; Eri, Qitai; Wang, Qiang
2014-04-10
Optical roughness was introduced into the bidirectional reflectance distribution function (BRDF) model to simulate the reflectance characteristics of thermal radiation. The optical roughness BRDF model stemmed from the influence of surface roughness and wavelength on the ray reflectance calculation. This model was adopted to simulate real metal emissivity. The reverse Monte Carlo method was used to display the distribution of reflectance rays. The numerical simulations showed that the optical roughness BRDF model can calculate the wavelength effect on emissivity and simulate the real metal emissivity variance with incidence angles.
Topological excitations and Monte-Carlo simulation of the Abelian-Higgs model
International Nuclear Information System (INIS)
Ranft, J.
1981-01-01
The phase structure and topological excitations, in particular the magnetic monopole current density, are investigated in a Monte-Carlo simulation of the lattice version of the four-dimensional Abelian-Higgs model. The monopole current density is found to be large in the confinement phase and rapidly decreasing in the Coulomb and Higgs phases. This result supports the view that confinement is neglected with the condensation of monopole-antimonopole pairs
Computer simulation of stochastic processes through model-sampling (Monte Carlo) techniques.
Sheppard, C W.
1969-03-01
A simple Monte Carlo simulation program is outlined which can be used for the investigation of random-walk problems, for example in diffusion, or the movement of tracers in the blood circulation. The results given by the simulation are compared with those predicted by well-established theory, and it is shown how the model can be expanded to deal with drift, and with reflexion from or adsorption at a boundary.
Extrapolation method in the Monte Carlo Shell Model and its applications
International Nuclear Information System (INIS)
Shimizu, Noritaka; Abe, Takashi; Utsuno, Yutaka; Mizusaki, Takahiro; Otsuka, Takaharu; Honma, Michio
2011-01-01
We demonstrate how the energy-variance extrapolation method works using the sequence of the approximated wave functions obtained by the Monte Carlo Shell Model (MCSM), taking 56 Ni with pf-shell as an example. The extrapolation method is shown to work well even in the case that the MCSM shows slow convergence, such as 72 Ge with f5pg9-shell. The structure of 72 Se is also studied including the discussion of the shape-coexistence phenomenon.
International Nuclear Information System (INIS)
Pérez-Andújar, Angélica; Zhang, Rui; Newhauser, Wayne
2013-01-01
Purpose: Stray neutron radiation is of concern after radiation therapy, especially in children, because of the high risk it might carry for secondary cancers. Several previous studies predicted the stray neutron exposure from proton therapy, mostly using Monte Carlo simulations. Promising attempts to develop analytical models have also been reported, but these were limited to only a few proton beam energies. The purpose of this study was to develop an analytical model to predict leakage neutron equivalent dose from passively scattered proton beams in the 100-250-MeV interval.Methods: To develop and validate the analytical model, the authors used values of equivalent dose per therapeutic absorbed dose (H/D) predicted with Monte Carlo simulations. The authors also characterized the behavior of the mean neutron radiation-weighting factor, w R , as a function of depth in a water phantom and distance from the beam central axis.Results: The simulated and analytical predictions agreed well. On average, the percentage difference between the analytical model and the Monte Carlo simulations was 10% for the energies and positions studied. The authors found that w R was highest at the shallowest depth and decreased with depth until around 10 cm, where it started to increase slowly with depth. This was consistent among all energies.Conclusion: Simple analytical methods are promising alternatives to complex and slow Monte Carlo simulations to predict H/D values. The authors' results also provide improved understanding of the behavior of w R which strongly depends on depth, but is nearly independent of lateral distance from the beam central axis
Systematic vacuum study of the ITER model cryopump by test particle Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Luo, Xueli; Haas, Horst; Day, Christian [Institute for Technical Physics, Karlsruhe Institute of Technology, P.O. Box 3640, 76021 Karlsruhe (Germany)
2011-07-01
The primary pumping systems on the ITER torus are based on eight tailor-made cryogenic pumps because not any standard commercial vacuum pump can meet the ITER working criteria. This kind of cryopump can provide high pumping speed, especially for light gases, by the cryosorption on activated charcoal at 4.5 K. In this paper we will present the systematic Monte Carlo simulation results of the model pump in a reduced scale by ProVac3D, a new Test Particle Monte Carlo simulation program developed by KIT. The simulation model has included the most important mechanical structures such as sixteen cryogenic panels working at 4.5 K, the 80 K radiation shield envelope with baffles, the pump housing, inlet valve and the TIMO (Test facility for the ITER Model Pump) test facility. Three typical gas species, i.e., deuterium, protium and helium are simulated. The pumping characteristics have been obtained. The result is in good agreement with the experiment data up to the gas throughput of 1000 sccm, which marks the limit for free molecular flow. This means that ProVac3D is a useful tool in the design of the prototype cryopump of ITER. Meanwhile, the capture factors at different critical positions are calculated. They can be used as the important input parameters for a follow-up Direct Simulation Monte Carlo (DSMC) simulation for higher gas throughput.
Energy Technology Data Exchange (ETDEWEB)
Murata, Isao [Osaka Univ., Suita (Japan); Mori, Takamasa; Nakagawa, Masayuki; Itakura, Hirofumi
1996-03-01
The method to calculate neutronics parameters of a core composed of randomly distributed spherical fuels has been developed based on a statistical geometry model with a continuous energy Monte Carlo method. This method was implemented in a general purpose Monte Carlo code MCNP, and a new code MCNP-CFP had been developed. This paper describes the model and method how to use it and the validation results. In the Monte Carlo calculation, the location of a spherical fuel is sampled probabilistically along the particle flight path from the spatial probability distribution of spherical fuels, called nearest neighbor distribution (NND). This sampling method was validated through the following two comparisons: (1) Calculations of inventory of coated fuel particles (CFPs) in a fuel compact by both track length estimator and direct evaluation method, and (2) Criticality calculations for ordered packed geometries. This method was also confined by applying to an analysis of the critical assembly experiment at VHTRC. The method established in the present study is quite unique so as to a probabilistic model of the geometry with a great number of spherical fuels distributed randomly. Realizing the speed-up by vector or parallel computations in future, it is expected to be widely used in calculation of a nuclear reactor core, especially HTGR cores. (author).
Svensson, Andreas; Schön, Thomas B.; Lindsten, Fredrik
2018-05-01
Probabilistic (or Bayesian) modeling and learning offers interesting possibilities for systematic representation of uncertainty using probability theory. However, probabilistic learning often leads to computationally challenging problems. Some problems of this type that were previously intractable can now be solved on standard personal computers thanks to recent advances in Monte Carlo methods. In particular, for learning of unknown parameters in nonlinear state-space models, methods based on the particle filter (a Monte Carlo method) have proven very useful. A notoriously challenging problem, however, still occurs when the observations in the state-space model are highly informative, i.e. when there is very little or no measurement noise present, relative to the amount of process noise. The particle filter will then struggle in estimating one of the basic components for probabilistic learning, namely the likelihood p (data | parameters). To this end we suggest an algorithm which initially assumes that there is substantial amount of artificial measurement noise present. The variance of this noise is sequentially decreased in an adaptive fashion such that we, in the end, recover the original problem or possibly a very close approximation of it. The main component in our algorithm is a sequential Monte Carlo (SMC) sampler, which gives our proposed method a clear resemblance to the SMC2 method. Another natural link is also made to the ideas underlying the approximate Bayesian computation (ABC). We illustrate it with numerical examples, and in particular show promising results for a challenging Wiener-Hammerstein benchmark problem.
Directory of Open Access Journals (Sweden)
Longge Zhang
2013-01-01
Full Text Available Two automatic robust model predictive control strategies are presented for uncertain polytopic linear plants with input and output constraints. A sequence of nested geometric proportion asymptotically stable ellipsoids and controllers is constructed offline first. Then the feedback controllers are automatically selected with the receding horizon online in the first strategy. Finally, a modified automatic offline robust MPC approach is constructed to improve the closed system's performance. The new proposed strategies not only reduce the conservatism but also decrease the online computation. Numerical examples are given to illustrate their effectiveness.
Energy Technology Data Exchange (ETDEWEB)
Tian, Z; Folkerts, M; Jiang, S; Jia, X [UT Southwestern Medical Ctr, Dallas, TX (United States); Li, Y [Beihang University, Beijing (China)
2016-06-15
Purpose: We have previously developed a GPU-OpenCL-based MC dose engine named goMC with built-in analytical linac beam model. To move goMC towards routine clinical use, we have developed an automatic beam-commissioning method, and an efficient source sampling strategy to facilitate dose calculations for real treatment plans. Methods: Our commissioning method is to automatically adjust the relative weights among the sub-sources, through an optimization process minimizing the discrepancies between calculated dose and measurements. Six models built for Varian Truebeam linac photon beams (6MV, 10MV, 15MV, 18MV, 6MVFFF, 10MVFFF) were commissioned using measurement data acquired at our institution. To facilitate dose calculations for real treatment plans, we employed inverse sampling method to efficiently incorporate MLC leaf-sequencing into source sampling. Specifically, instead of sampling source particles control-point by control-point and rejecting the particles blocked by MLC, we assigned a control-point index to each sampled source particle, according to MLC leaf-open duration of each control-point at the pixel where the particle intersects the iso-center plane. Results: Our auto-commissioning method decreased distance-to-agreement (DTA) of depth dose at build-up regions by 36.2% averagely, making it within 1mm. Lateral profiles were better matched for all beams, with biggest improvement found at 15MV for which root-mean-square difference was reduced from 1.44% to 0.50%. Maximum differences of output factors were reduced to less than 0.7% for all beams, with largest decrease being from1.70% to 0.37% found at 10FFF. Our new sampling strategy was tested on a Head&Neck VMAT patient case. Achieving clinically acceptable accuracy, the new strategy could reduce the required history number by a factor of ∼2.8 given a statistical uncertainty level and hence achieve a similar speed-up factor. Conclusion: Our studies have demonstrated the feasibility and effectiveness of
Monte Carlo tests of the Rasch model based on scalability coefficients
DEFF Research Database (Denmark)
Christensen, Karl Bang; Kreiner, Svend
2010-01-01
that summarizes the number of Guttman errors in the data matrix. These coefficients are shown to yield efficient tests of the Rasch model using p-values computed using Markov chain Monte Carlo methods. The power of the tests of unequal item discrimination, and their ability to distinguish between local dependence......For item responses fitting the Rasch model, the assumptions underlying the Mokken model of double monotonicity are met. This makes non-parametric item response theory a natural starting-point for Rasch item analysis. This paper studies scalability coefficients based on Loevinger's H coefficient...
Monte Carlo tools for Beyond the Standard Model Physics , April 14-16
DEFF Research Database (Denmark)
Badger...[], Simon; Christensen, Christian Holm; Dalsgaard, Hans Hjersing
2011-01-01
This workshop aims to gather together theorists and experimentalists interested in developing and using Monte Carlo tools for Beyond the Standard Model Physics in an attempt to be prepared for the analysis of data focusing on the Large Hadron Collider. Since a large number of excellent tools....... To identify promising models (or processes) for which the tools have not yet been constructed and start filling up these gaps. To propose ways to streamline the process of going from models to events, i.e. to make the process more user-friendly so that more people can get involved and perform serious collider...
Automatic digital surface model (DSM) generation from aerial imagery data
Zhou, Nan; Cao, Shixiang; He, Hongyan; Xing, Kun; Yue, Chunyu
2018-04-01
Aerial sensors are widely used to acquire imagery for photogrammetric and remote sensing application. In general, the images have large overlapped region, which provide a lot of redundant geometry and radiation information for matching. This paper presents a POS supported dense matching procedure for automatic DSM generation from aerial imagery data. The method uses a coarse-to-fine hierarchical strategy with an effective combination of several image matching algorithms: image radiation pre-processing, image pyramid generation, feature point extraction and grid point generation, multi-image geometrically constraint cross-correlation (MIG3C), global relaxation optimization, multi-image geometrically constrained least squares matching (MIGCLSM), TIN generation and point cloud filtering. The image radiation pre-processing is used in order to reduce the effects of the inherent radiometric problems and optimize the images. The presented approach essentially consists of 3 components: feature point extraction and matching procedure, grid point matching procedure and relational matching procedure. The MIGCLSM method is used to achieve potentially sub-pixel accuracy matches and identify some inaccurate and possibly false matches. The feasibility of the method has been tested on different aerial scale images with different landcover types. The accuracy evaluation is based on the comparison between the automatic extracted DSMs derived from the precise exterior orientation parameters (EOPs) and the POS.
International Nuclear Information System (INIS)
Mayeed, M.S.; Kato, T.
2014-01-01
Applying the reptation algorithm to a simplified perfluoro polyether Z off-lattice polymer model an NVT Monte Carlo simulation has been performed. Bulk condition has been simulated first to compare the average radius of gyration with the bulk experimental results. Then the model is tested for its ability to describe dynamics. After this, it is applied to observe the replenishment of nano scale ultrathin liquid films on solid flat carbon surfaces. The replenishment rate for trenches of different widths (8, 12, and 16 nms for several molecular weights) between two films of perfluoro polyether Z from the Monte Carlo simulation is compared to that obtained solving the diffusion equation using the experimental diffusion coefficients of Ma et al. (1999), with room condition in both cases. Replenishment per Monte Carlo cycle seems to be a constant multiple of replenishment per second at least up to 2 nm replenished film thickness of the trenches over the carbon surface. Considerable good agreement has been achieved here between the experimental results and the dynamics of molecules using reptation moves in the ultrathin liquid films on solid surfaces.
A Full-Body Layered Deformable Model for Automatic Model-Based Gait Recognition
Lu, Haiping; Plataniotis, Konstantinos N.; Venetsanopoulos, Anastasios N.
2007-12-01
This paper proposes a full-body layered deformable model (LDM) inspired by manually labeled silhouettes for automatic model-based gait recognition from part-level gait dynamics in monocular video sequences. The LDM is defined for the fronto-parallel gait with 22 parameters describing the human body part shapes (widths and lengths) and dynamics (positions and orientations). There are four layers in the LDM and the limbs are deformable. Algorithms for LDM-based human body pose recovery are then developed to estimate the LDM parameters from both manually labeled and automatically extracted silhouettes, where the automatic silhouette extraction is through a coarse-to-fine localization and extraction procedure. The estimated LDM parameters are used for model-based gait recognition by employing the dynamic time warping for matching and adopting the combination scheme in AdaBoost.M2. While the existing model-based gait recognition approaches focus primarily on the lower limbs, the estimated LDM parameters enable us to study full-body model-based gait recognition by utilizing the dynamics of the upper limbs, the shoulders and the head as well. In the experiments, the LDM-based gait recognition is tested on gait sequences with differences in shoe-type, surface, carrying condition and time. The results demonstrate that the recognition performance benefits from not only the lower limb dynamics, but also the dynamics of the upper limbs, the shoulders and the head. In addition, the LDM can serve as an analysis tool for studying factors affecting the gait under various conditions.
Leung, Roger; Cheung, Howard; Gang, Hong; Ye, Wenjing
2010-01-01
Squeeze-film damping on microresonators is a significant damping source even when the surrounding gas is highly rarefied. This article presents a general modeling approach based on Monte Carlo (MC) simulations for the prediction of squeeze
Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood e...
AUTOMATIC 3D BUILDING MODEL GENERATIONS WITH AIRBORNE LiDAR DATA
Directory of Open Access Journals (Sweden)
N. Yastikli
2017-11-01
Full Text Available LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified
Automatic 3d Building Model Generations with Airborne LiDAR Data
Yastikli, N.; Cetin, Z.
2017-11-01
LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D
Modeling dose-rate on/over the surface of cylindrical radio-models using Monte Carlo methods
International Nuclear Information System (INIS)
Xiao Xuefu; Ma Guoxue; Wen Fuping; Wang Zhongqi; Wang Chaohui; Zhang Jiyun; Huang Qingbo; Zhang Jiaqiu; Wang Xinxing; Wang Jun
2004-01-01
Objective: To determine the dose-rates on/over the surface of 10 cylindrical radio-models, which belong to the Metrology Station of Radio-Geological Survey of CNNC. Methods: The dose-rates on/over the surface of 10 cylindrical radio-models were modeled using the famous Monte Carlo code-MCNP. The dose-rates on/over the surface of 10 cylindrical radio-models were measured by a high gas pressurized ionization chamber dose-rate meter, respectively. The values of dose-rate modeled using MCNP code were compared with those obtained by authors in the present experimental measurement, and with those obtained by other workers previously. Some factors causing the discrepancy between the data obtained by authors using MCNP code and the data obtained using other methods are discussed in this paper. Results: The data of dose-rates on/over the surface of 10 cylindrical radio-models, obtained using MCNP code, were in good agreement with those obtained by other workers using the theoretical method. They were within the discrepancy of ±5% in general, and the maximum discrepancy was less than 10%. Conclusions: As if each factor needed for the Monte Carlo code is correct, the dose-rates on/over the surface of cylindrical radio-models modeled using the Monte Carlo code are correct with an uncertainty of 3%
Monte Carlo Studies of Phase Separation in Compressible 2-dim Ising Models
Mitchell, S. J.; Landau, D. P.
2006-03-01
Using high resolution Monte Carlo simulations, we study time-dependent domain growth in compressible 2-dim ferromagnetic (s=1/2) Ising models with continuous spin positions and spin-exchange moves [1]. Spins interact with slightly modified Lennard-Jones potentials, and we consider a model with no lattice mismatch and one with 4% mismatch. For comparison, we repeat calculations for the rigid Ising model [2]. For all models, large systems (512^2) and long times (10^ 6 MCS) are examined over multiple runs, and the growth exponent is measured in the asymptotic scaling regime. For the rigid model and the compressible model with no lattice mismatch, the growth exponent is consistent with the theoretically expected value of 1/3 [1] for Model B type growth. However, we find that non-zero lattice mismatch has a significant and unexpected effect on the growth behavior.Supported by the NSF.[1] D.P. Landau and K. Binder, A Guide to Monte Carlo Simulations in Statistical Physics, second ed. (Cambridge University Press, New York, 2005).[2] J. Amar, F. Sullivan, and R.D. Mountain, Phys. Rev. B 37, 196 (1988).
History and future perspectives of the Monte Carlo shell model -from Alphleet to K computer-
International Nuclear Information System (INIS)
Shimizu, Noritaka; Otsuka, Takaharu; Utsuno, Yutaka; Mizusaki, Takahiro; Honma, Michio; Abe, Takashi
2013-01-01
We report a history of the developments of the Monte Carlo shell model (MCSM). The MCSM was proposed in order to perform large-scale shell-model calculations which direct diagonalization method cannot reach. Since 1999 PC clusters were introduced for parallel computation of the MCSM. Since 2011 we participated the High Performance Computing Infrastructure Strategic Program and developed a new MCSM code for current massively parallel computers such as K computer. We discuss future perspectives concerning a new framework and parallel computation of the MCSM by incorporating conjugate gradient method and energy-variance extrapolation
Monte Carlo modelling of the Belgian materials testing reactor BR2: present status
International Nuclear Information System (INIS)
Verboomen, B.; Aoust, Th.; Raedt, Ch. de; Beeckmans de West-Meerbeeck, A.
2001-01-01
A very detailed 3-D MCNP-4B model of the BR2 reactor was developed to perform all neutron and gamma calculations needed for the design of new experimental irradiation rigs. The Monte Carlo model of BR2 includes the nearly exact geometrical representation of fuel elements (now with their axially varying burn-up), of partially inserted control and regulating rods, of experimental devices and of radioisotope production rigs. The multiple level-geometry possibilities of MCNP-4B are fully exploited to obtain sufficiently flexible tools to cope with the very changing core loading. (orig.)
Quantum Monte Carlo simulation for S=1 Heisenberg model with uniaxial anisotropy
International Nuclear Information System (INIS)
Tsukamoto, Mitsuaki; Batista, Cristian; Kawashima, Naoki
2007-01-01
We perform quantum Monte Carlo simulations for S=1 Heisenberg model with an uniaxial anisotropy. The system exhibits a phase transition as we vary the anisotropy and a long range order appears at a finite temperature when the exchange interaction J is comparable to the uniaxial anisotropy D. We investigate quantum critical phenomena of this model and obtain the line of the phase transition which approaches a power-law with logarithmic corrections at low temperature. We derive the form of logarithmic corrections analytically and compare it to our simulation results
Monte Carlo simulations of the NJL model near the nonzero temperature phase transition
International Nuclear Information System (INIS)
Strouthos, Costas; Christofi, Stavros
2005-01-01
We present results from numerical simulations of the Nambu-Jona-Lasinio model with an SU(2)xSU(2) chiral symmetry and N c = 4,8, and 16 quark colors at nonzero temperature. We performed the simulations by utilizing the hybrid Monte Carlo and hybrid Molecular Dynamics algorithms. We show that the model undergoes a second order phase transition. The critical exponents measured are consistent with the classical 3d O(4) universality class and hence in accordance with the dimensional reduction scenario. We also show that the Ginzburg region is suppressed by a factor of 1/N c in accordance with previous analytical predictions. (author)
Modeling of the YALINA booster facility by the Monte Carlo code MONK
International Nuclear Information System (INIS)
Talamo, A.; Gohar, Y.; Kondev, F.; Kiyavitskaya, H.; Serafimovich, I.; Bournos, V.; Fokov, Y.; Routkovskaya, C.
2007-01-01
The YALINA-Booster facility has been modeled according to the benchmark specifications defined for the IAEA activity without any geometrical homogenization using the Monte Carlo codes MONK and MCNP/MCNPX/MCB. The MONK model perfectly matches the MCNP one. The computational analyses have been extended through the MCB code, which is an extension of the MCNP code with burnup capability because of its additional feature for analyzing source driven multiplying assemblies. The main neutronics arameters of the YALINA-Booster facility were calculated using these computer codes with different nuclear data libraries based on ENDF/B-VI-0, -6, JEF-2.2, and JEF-3.1.
Modeling the cathode region of noble gas mixture discharges using Monte Carlo simulation
International Nuclear Information System (INIS)
Donko, Z.; Janossy, M.
1992-10-01
A model of the cathode dark space of DC glow discharges was developed in order to study the effects caused by mixing small amounts (≤2%) of other noble gases (Ne, Ar, Kr and Xe) to He. The motion of charged particles was described by Monte Carlo simulation. Several discharge parameters (electron and ion energy distribution functions, electron and ion current densities, reduced ionization coefficients, and current density-voltage characteristics) were obtained. Small amounts of admixtures were found to modify significantly the discharge parameters. Current density-voltage characteristics obtained from the model showed good agreement with experimental data. (author) 40 refs.; 14 figs
Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm
International Nuclear Information System (INIS)
Takaishi, Tetsuya
2014-01-01
The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the HMCA, we find that the 2MNI is more efficient than the conventional leapfrog integrator. We also find that the autocorrelation time of the volatility variables sampled by the HMCA is very short. Thus it is concluded that the HMCA with the 2MNI is an efficient algorithm for parameter estimations of the RSV model
Design and evaluation of a Monte Carlo based model of an orthovoltage treatment system
International Nuclear Information System (INIS)
Penchev, Petar; Maeder, Ulf; Fiebich, Martin; Zink, Klemens; University Hospital Marburg
2015-01-01
The aim of this study was to develop a flexible framework of an orthovoltage treatment system capable of calculating and visualizing dose distributions in different phantoms and CT datasets. The framework provides a complete set of various filters, applicators and X-ray energies and therefore can be adapted to varying studies or be used for educational purposes. A dedicated user friendly graphical interface was developed allowing for easy setup of the simulation parameters and visualization of the results. For the Monte Carlo simulations the EGSnrc Monte Carlo code package was used. Building the geometry was accomplished with the help of the EGSnrc C++ class library. The deposited dose was calculated according to the KERMA approximation using the track-length estimator. The validation against measurements showed a good agreement within 4-5% deviation, down to depths of 20% of the depth dose maximum. Furthermore, to show its capabilities, the validated model was used to calculate the dose distribution on two CT datasets. Typical Monte Carlo calculation time for these simulations was about 10 minutes achieving an average statistical uncertainty of 2% on a standard PC. However, this calculation time depends strongly on the used CT dataset, tube potential, filter material/thickness and applicator size.
Automatic discovery of the communication network topology for building a supercomputer model
Sobolev, Sergey; Stefanov, Konstantin; Voevodin, Vadim
2016-10-01
The Research Computing Center of Lomonosov Moscow State University is developing the Octotron software suite for automatic monitoring and mitigation of emergency situations in supercomputers so as to maximize hardware reliability. The suite is based on a software model of the supercomputer. The model uses a graph to describe the computing system components and their interconnections. One of the most complex components of a supercomputer that needs to be included in the model is its communication network. This work describes the proposed approach for automatically discovering the Ethernet communication network topology in a supercomputer and its description in terms of the Octotron model. This suite automatically detects computing nodes and switches, collects information about them and identifies their interconnections. The application of this approach is demonstrated on the "Lomonosov" and "Lomonosov-2" supercomputers.
Development of a cerebral circulation model for the automatic control of brain physiology.
Utsuki, T
2015-01-01
In various clinical guidelines of brain injury, intracranial pressure (ICP), cerebral blood flow (CBF) and brain temperature (BT) are essential targets for precise management for brain resuscitation. In addition, the integrated automatic control of BT, ICP, and CBF is required for improving therapeutic effects and reducing medical costs and staff burden. Thus, a new model of cerebral circulation was developed in this study for integrative automatic control. With this model, the CBF and cerebral perfusion pressure of a normal adult male were regionally calculated according to cerebrovascular structure, blood viscosity, blood distribution, CBF autoregulation, and ICP. The analysis results were consistent with physiological knowledge already obtained with conventional studies. Therefore, the developed model is potentially available for the integrative control of the physiological state of the brain as a reference model of an automatic control system, or as a controlled object in various control simulations.
Comparison of nonstationary generalized logistic models based on Monte Carlo simulation
Directory of Open Access Journals (Sweden)
S. Kim
2015-06-01
Full Text Available Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstationarity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.
MONTE CARLO SIMULATION MODEL OF ENERGETIC PROTON TRANSPORT THROUGH SELF-GENERATED ALFVEN WAVES
Energy Technology Data Exchange (ETDEWEB)
Afanasiev, A.; Vainio, R., E-mail: alexandr.afanasiev@helsinki.fi [Department of Physics, University of Helsinki (Finland)
2013-08-15
A new Monte Carlo simulation model for the transport of energetic protons through self-generated Alfven waves is presented. The key point of the model is that, unlike the previous ones, it employs the full form (i.e., includes the dependence on the pitch-angle cosine) of the resonance condition governing the scattering of particles off Alfven waves-the process that approximates the wave-particle interactions in the framework of quasilinear theory. This allows us to model the wave-particle interactions in weak turbulence more adequately, in particular, to implement anisotropic particle scattering instead of isotropic scattering, which the previous Monte Carlo models were based on. The developed model is applied to study the transport of flare-accelerated protons in an open magnetic flux tube. Simulation results for the transport of monoenergetic protons through the spectrum of Alfven waves reveal that the anisotropic scattering leads to spatially more distributed wave growth than isotropic scattering. This result can have important implications for diffusive shock acceleration, e.g., affect the scattering mean free path of the accelerated particles in and the size of the foreshock region.
Zhu, Gaofeng; Li, Xin; Ma, Jinzhu; Wang, Yunquan; Liu, Shaomin; Huang, Chunlin; Zhang, Kun; Hu, Xiaoli
2018-04-01
Sequential Monte Carlo (SMC) samplers have become increasing popular for estimating the posterior parameter distribution with the non-linear dependency structures and multiple modes often present in hydrological models. However, the explorative capabilities and efficiency of the sampler depends strongly on the efficiency in the move step of SMC sampler. In this paper we presented a new SMC sampler entitled the Particle Evolution Metropolis Sequential Monte Carlo (PEM-SMC) algorithm, which is well suited to handle unknown static parameters of hydrologic model. The PEM-SMC sampler is inspired by the works of Liang and Wong (2001) and operates by incorporating the strengths of the genetic algorithm, differential evolution algorithm and Metropolis-Hasting algorithm into the framework of SMC. We also prove that the sampler admits the target distribution to be a stationary distribution. Two case studies including a multi-dimensional bimodal normal distribution and a conceptual rainfall-runoff hydrologic model by only considering parameter uncertainty and simultaneously considering parameter and input uncertainty show that PEM-SMC sampler is generally superior to other popular SMC algorithms in handling the high dimensional problems. The study also indicated that it may be important to account for model structural uncertainty by using multiplier different hydrological models in the SMC framework in future study.
Monte Carlo Modelling of Single-Crystal Diffuse Scattering from Intermetallics
Directory of Open Access Journals (Sweden)
Darren J. Goossens
2016-02-01
Full Text Available Single-crystal diffuse scattering (SCDS reveals detailed structural insights into materials. In particular, it is sensitive to two-body correlations, whereas traditional Bragg peak-based methods are sensitive to single-body correlations. This means that diffuse scattering is sensitive to ordering that persists for just a few unit cells: nanoscale order, sometimes referred to as “local structure”, which is often crucial for understanding a material and its function. Metals and alloys were early candidates for SCDS studies because of the availability of large single crystals. While great progress has been made in areas like ab initio modelling and molecular dynamics, a place remains for Monte Carlo modelling of model crystals because of its ability to model very large systems; important when correlations are relatively long (though still finite in range. This paper briefly outlines, and gives examples of, some Monte Carlo methods appropriate for the modelling of SCDS from metallic compounds, and considers data collection as well as analysis. Even if the interest in the material is driven primarily by magnetism or transport behaviour, an understanding of the local structure can underpin such studies and give an indication of nanoscale inhomogeneity.
The Physical Models and Statistical Procedures Used in the RACER Monte Carlo Code
International Nuclear Information System (INIS)
Sutton, T.M.; Brown, F.B.; Bischoff, F.G.; MacMillan, D.B.; Ellis, C.L.; Ward, J.T.; Ballinger, C.T.; Kelly, D.J.; Schindler, L.
1999-01-01
This report describes the MCV (Monte Carlo - Vectorized)Monte Carlo neutron transport code [Brown, 1982, 1983; Brown and Mendelson, 1984a]. MCV is a module in the RACER system of codes that is used for Monte Carlo reactor physics analysis. The MCV module contains all of the neutron transport and statistical analysis functions of the system, while other modules perform various input-related functions such as geometry description, material assignment, output edit specification, etc. MCV is very closely related to the 05R neutron Monte Carlo code [Irving et al., 1965] developed at Oak Ridge National Laboratory. 05R evolved into the 05RR module of the STEMB system, which was the forerunner of the RACER system. Much of the overall logic and physics treatment of 05RR has been retained and, indeed, the original verification of MCV was achieved through comparison with STEMB results. MCV has been designed to be very computationally efficient [Brown, 1981, Brown and Martin, 1984b; Brown, 1986]. It was originally programmed to make use of vector-computing architectures such as those of the CDC Cyber- 205 and Cray X-MP. MCV was the first full-scale production Monte Carlo code to effectively utilize vector-processing capabilities. Subsequently, MCV was modified to utilize both distributed-memory [Sutton and Brown, 1994] and shared memory parallelism. The code has been compiled and run on platforms ranging from 32-bit UNIX workstations to clusters of 64-bit vector-parallel supercomputers. The computational efficiency of the code allows the analyst to perform calculations using many more neutron histories than is practical with most other Monte Carlo codes, thereby yielding results with smaller statistical uncertainties. MCV also utilizes variance reduction techniques such as survival biasing, splitting, and rouletting to permit additional reduction in uncertainties. While a general-purpose neutron Monte Carlo code, MCV is optimized for reactor physics calculations. It has the
A new method for automatic discontinuity traces sampling on rock mass 3D model
Umili, G.; Ferrero, A.; Einstein, H. H.
2013-02-01
A new automatic method for discontinuity traces mapping and sampling on a rock mass digital model is described in this work. The implemented procedure allows one to automatically identify discontinuity traces on a Digital Surface Model: traces are detected directly as surface breaklines, by means of maximum and minimum principal curvature values of the vertices that constitute the model surface. Color influence and user errors, that usually characterize the trace mapping on images, are eliminated. Also trace sampling procedures based on circular windows and circular scanlines have been implemented: they are used to infer trace data and to calculate values of mean trace length, expected discontinuity diameter and intensity of rock discontinuities. The method is tested on a case study: results obtained applying the automatic procedure on the DSM of a rock face are compared to those obtained performing a manual sampling on the orthophotograph of the same rock face.
Directory of Open Access Journals (Sweden)
Mansoor Ahmed Siddiqui
2017-06-01
Full Text Available This research work is aimed at optimizing the availability of a framework comprising of two units linked together in series configuration utilizing Markov Model and Monte Carlo (MC Simulation techniques. In this article, effort has been made to develop a maintenance model that incorporates three distinct states for each unit, while taking into account their different levels of deterioration. Calculations are carried out using the proposed model for two distinct cases of corrective repair, namely perfect and imperfect repairs, with as well as without opportunistic maintenance. Initially, results are accomplished using an analytical technique i.e., Markov Model. Validation of the results achieved is later carried out with the help of MC Simulation. In addition, MC Simulation based codes also work well for the frameworks that follow non-exponential failure and repair rates, and thus overcome the limitations offered by the Markov Model.
Monte Carlo based statistical power analysis for mediation models: methods and software.
Zhang, Zhiyong
2014-12-01
The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.
New-generation Monte Carlo shell model for the K computer era
International Nuclear Information System (INIS)
Shimizu, Noritaka; Abe, Takashi; Yoshida, Tooru; Otsuka, Takaharu; Tsunoda, Yusuke; Utsuno, Yutaka; Mizusaki, Takahiro; Honma, Michio
2012-01-01
We present a newly enhanced version of the Monte Carlo shell-model (MCSM) method by incorporating the conjugate gradient method and energy-variance extrapolation. This new method enables us to perform large-scale shell-model calculations that the direct diagonalization method cannot reach. This new-generation framework of the MCSM provides us with a powerful tool to perform very advanced large-scale shell-model calculations on current massively parallel computers such as the K computer. We discuss the validity of this method in ab initio calculations of light nuclei, and propose a new method to describe the intrinsic wave function in terms of the shell-model picture. We also apply this new MCSM to the study of neutron-rich Cr and Ni isotopes using conventional shell-model calculations with an inert 40 Ca core and discuss how the magicity of N = 28, 40, 50 remains or is broken. (author)
Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin
Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.
A Monte Carlo model for 3D grain evolution during welding
Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena
2017-09-01
Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bézier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. The model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.
Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz Ram model
Morin, Mario A.; Ficarazzo, Francesco
2006-04-01
Rock fragmentation is considered the most important aspect of production blasting because of its direct effects on the costs of drilling and blasting and on the economics of the subsequent operations of loading, hauling and crushing. Over the past three decades, significant progress has been made in the development of new technologies for blasting applications. These technologies include increasingly sophisticated computer models for blast design and blast performance prediction. Rock fragmentation depends on many variables such as rock mass properties, site geology, in situ fracturing and blasting parameters and as such has no complete theoretical solution for its prediction. However, empirical models for the estimation of size distribution of rock fragments have been developed. In this study, a blast fragmentation Monte Carlo-based simulator, based on the Kuz-Ram fragmentation model, has been developed to predict the entire fragmentation size distribution, taking into account intact and joints rock properties, the type and properties of explosives and the drilling pattern. Results produced by this simulator were quite favorable when compared with real fragmentation data obtained from a blast quarry. It is anticipated that the use of Monte Carlo simulation will increase our understanding of the effects of rock mass and explosive properties on the rock fragmentation by blasting, as well as increase our confidence in these empirical models. This understanding will translate into improvements in blasting operations, its corresponding costs and the overall economics of open pit mines and rock quarries.
Fission yield calculation using toy model based on Monte Carlo simulation
International Nuclear Information System (INIS)
Jubaidah; Kurniadi, Rizal
2015-01-01
Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (R c ), mean of left curve (μ L ) and mean of right curve (μ R ), deviation of left curve (σ L ) and deviation of right curve (σ R ). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90
Fission yield calculation using toy model based on Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Jubaidah, E-mail: jubaidah@student.itb.ac.id [Nuclear Physics and Biophysics Division, Department of Physics, Bandung Institute of Technology. Jl. Ganesa No. 10 Bandung – West Java, Indonesia 40132 (Indonesia); Physics Department, Faculty of Mathematics and Natural Science – State University of Medan. Jl. Willem Iskandar Pasar V Medan Estate – North Sumatera, Indonesia 20221 (Indonesia); Kurniadi, Rizal, E-mail: rijalk@fi.itb.ac.id [Nuclear Physics and Biophysics Division, Department of Physics, Bandung Institute of Technology. Jl. Ganesa No. 10 Bandung – West Java, Indonesia 40132 (Indonesia)
2015-09-30
Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (R{sub c}), mean of left curve (μ{sub L}) and mean of right curve (μ{sub R}), deviation of left curve (σ{sub L}) and deviation of right curve (σ{sub R}). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90
Automatic Model-Based Generation of Parameterized Test Cases Using Data Abstraction
Calamé, Jens R.; Ioustinova, Natalia; Romijn, J.M.T.; Smith, G.; van de Pol, Jan Cornelis
2007-01-01
Developing test suites is a costly and error-prone process. Model-based test generation tools facilitate this process by automatically generating test cases from system models. The applicability of these tools, however, depends on the size of the target systems. Here, we propose an approach to
Studies on top-quark Monte Carlo modelling for Top2016
The ATLAS collaboration
2016-01-01
This note summarises recent studies on Monte Carlo simulation setups of top-quark pair production used by the ATLAS experiment and presents a new method to deal with interference effects for the $Wt$ single-top-quark production which is compared against previous techniques. The main focus for the top-quark pair production is on the improvement of the modelling of the Powheg generator interfaced to the Pythia8 and Herwig7 shower generators. The studies are done using unfolded data at centre-of-mass energies of 7, 8, and 13 TeV.
A study of potential energy curves from the model space quantum Monte Carlo method
Energy Technology Data Exchange (ETDEWEB)
Ohtsuka, Yuhki; Ten-no, Seiichiro, E-mail: tenno@cs.kobe-u.ac.jp [Department of Computational Sciences, Graduate School of System Informatics, Kobe University, Nada-ku, Kobe 657-8501 (Japan)
2015-12-07
We report on the first application of the model space quantum Monte Carlo (MSQMC) to potential energy curves (PECs) for the excited states of C{sub 2}, N{sub 2}, and O{sub 2} to validate the applicability of the method. A parallel MSQMC code is implemented with the initiator approximation to enable efficient sampling. The PECs of MSQMC for various excited and ionized states are compared with those from the Rydberg-Klein-Rees and full configuration interaction methods. The results indicate the usefulness of MSQMC for precise PECs in a wide range obviating problems concerning quasi-degeneracy.
A Monte Carlo modeling alternative for the API Gamma Ray Calibration Facility.
Galford, J E
2017-04-01
The gamma ray pit at the API Calibration Facility, located on the University of Houston campus, defines the API unit for natural gamma ray logs used throughout the petroleum logging industry. Future use of the facility is uncertain. An alternative method is proposed to preserve the gamma ray API unit definition as an industry standard by using Monte Carlo modeling to obtain accurate counting rate-to-API unit conversion factors for gross-counting and spectral gamma ray tool designs. Copyright © 2017 Elsevier Ltd. All rights reserved.
Model study of an automatic controller of the IBR-2 pulsed reactor
International Nuclear Information System (INIS)
Pepelyshev, Yu.N.; Popov, A.K.
2007-01-01
For calculation of power transients in the IBR-2 reactor a special mathematical model of dynamics taking into account the discontinuous jump of reactivity by an automatic controller with the step motor is created. In the model the nonlinear dependence of the energy of power pulse on the reactivity and the influence of warming up of the reactor on the reactivity by means of introduction of a nonlinear feedback 'power-pulse energy - reactivity' are taken into account. With the help of the model the transients of relative deviation of power-pulse energy are calculated at various (random, mixed and regular) reactivity disturbances at the reactor mean power 1.475 MW. It is shown that to improve the quality of processes the choice of such regular values of parameters of the automatic controller is expedient, at which the least effect of smoothing of a signal acting on an automatic controller and the least speed of an automatic controller are provided, and the reduction of efficiency of one step of the automatic controller and introduction of a five-percent dead space are also expedient
Liukkonen, Mimmi K; Mononen, Mika E; Tanska, Petri; Saarakkala, Simo; Nieminen, Miika T; Korhonen, Rami K
2017-10-01
Manual segmentation of articular cartilage from knee joint 3D magnetic resonance images (MRI) is a time consuming and laborious task. Thus, automatic methods are needed for faster and reproducible segmentations. In the present study, we developed a semi-automatic segmentation method based on radial intensity profiles to generate 3D geometries of knee joint cartilage which were then used in computational biomechanical models of the knee joint. Six healthy volunteers were imaged with a 3T MRI device and their knee cartilages were segmented both manually and semi-automatically. The values of cartilage thicknesses and volumes produced by these two methods were compared. Furthermore, the influences of possible geometrical differences on cartilage stresses and strains in the knee were evaluated with finite element modeling. The semi-automatic segmentation and 3D geometry construction of one knee joint (menisci, femoral and tibial cartilages) was approximately two times faster than with manual segmentation. Differences in cartilage thicknesses, volumes, contact pressures, stresses, and strains between segmentation methods in femoral and tibial cartilage were mostly insignificant (p > 0.05) and random, i.e. there were no systematic differences between the methods. In conclusion, the devised semi-automatic segmentation method is a quick and accurate way to determine cartilage geometries; it may become a valuable tool for biomechanical modeling applications with large patient groups.
Modelling of scintillator based flat-panel detectors with Monte-Carlo simulations
International Nuclear Information System (INIS)
Reims, N; Sukowski, F; Uhlmann, N
2011-01-01
Scintillator based flat panel detectors are state of the art in the field of industrial X-ray imaging applications. Choosing the proper system and setup parameters for the vast range of different applications can be a time consuming task, especially when developing new detector systems. Since the system behaviour cannot always be foreseen easily, Monte-Carlo (MC) simulations are keys to gain further knowledge of system components and their behaviour for different imaging conditions. In this work we used two Monte-Carlo based models to examine an indirect converting flat panel detector, specifically the Hamamatsu C9312SK. We focused on the signal generation in the scintillation layer and its influence on the spatial resolution of the whole system. The models differ significantly in their level of complexity. The first model gives a global description of the detector based on different parameters characterizing the spatial resolution. With relatively small effort a simulation model can be developed which equates the real detector regarding signal transfer. The second model allows a more detailed insight of the system. It is based on the well established cascade theory, i.e. describing the detector as a cascade of elemental gain and scattering stages, which represent the built in components and their signal transfer behaviour. In comparison to the first model the influence of single components especially the important light spread behaviour in the scintillator can be analysed in a more differentiated way. Although the implementation of the second model is more time consuming both models have in common that a relatively small amount of system manufacturer parameters are needed. The results of both models were in good agreement with the measured parameters of the real system.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-11-01
simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
Nguyen, Ngoc Minh; Corff, Sylvain Le; Moulines, Éric
2017-12-01
This paper focuses on sequential Monte Carlo approximations of smoothing distributions in conditionally linear and Gaussian state spaces. To reduce Monte Carlo variance of smoothers, it is typical in these models to use Rao-Blackwellization: particle approximation is used to sample sequences of hidden regimes while the Gaussian states are explicitly integrated conditional on the sequence of regimes and observations, using variants of the Kalman filter/smoother. The first successful attempt to use Rao-Blackwellization for smoothing extends the Bryson-Frazier smoother for Gaussian linear state space models using the generalized two-filter formula together with Kalman filters/smoothers. More recently, a forward-backward decomposition of smoothing distributions mimicking the Rauch-Tung-Striebel smoother for the regimes combined with backward Kalman updates has been introduced. This paper investigates the benefit of introducing additional rejuvenation steps in all these algorithms to sample at each time instant new regimes conditional on the forward and backward particles. This defines particle-based approximations of the smoothing distributions whose support is not restricted to the set of particles sampled in the forward or backward filter. These procedures are applied to commodity markets which are described using a two-factor model based on the spot price and a convenience yield for crude oil data.
Towards an automatic model transformation mechanism from UML state machines to DEVS models
Directory of Open Access Journals (Sweden)
Ariel González
2015-08-01
Full Text Available The development of complex event-driven systems requires studies and analysis prior to deployment with the goal of detecting unwanted behavior. UML is a language widely used by the software engineering community for modeling these systems through state machines, among other mechanisms. Currently, these models do not have appropriate execution and simulation tools to analyze the real behavior of systems. Existing tools do not provide appropriate libraries (sampling from a probability distribution, plotting, etc. both to build and to analyze models. Modeling and simulation for design and prototyping of systems are widely used techniques to predict, investigate and compare the performance of systems. In particular, the Discrete Event System Specification (DEVS formalism separates the modeling and simulation; there are several tools available on the market that run and collect information from DEVS models. This paper proposes a model transformation mechanism from UML state machines to DEVS models in the Model-Driven Development (MDD context, through the declarative QVT Relations language, in order to perform simulations using tools, such as PowerDEVS. A mechanism to validate the transformation is proposed. Moreover, examples of application to analyze the behavior of an automatic banking machine and a control system of an elevator are presented.
Iterative optimisation of Monte Carlo detector models using measurements and simulations
Energy Technology Data Exchange (ETDEWEB)
Marzocchi, O., E-mail: olaf@marzocchi.net [European Patent Office, Rijswijk (Netherlands); Leone, D., E-mail: debora.leone@kit.edu [Institute for Nuclear Waste Disposal, Karlsruhe Institute of Technology, Karlsruhe (Germany)
2015-04-11
This work proposes a new technique to optimise the Monte Carlo models of radiation detectors, offering the advantage of a significantly lower user effort and therefore an improved work efficiency compared to the prior techniques. The method consists of four steps, two of which are iterative and suitable for automation using scripting languages. The four steps consist in the acquisition in the laboratory of measurement data to be used as reference; the modification of a previously available detector model; the simulation of a tentative model of the detector to obtain the coefficients of a set of linear equations; the solution of the system of equations and the update of the detector model. Steps three and four can be repeated for more accurate results. This method avoids the “try and fail” approach typical of the prior techniques.
Multi-chain Markov chain Monte Carlo methods for computationally expensive models
Huang, M.; Ray, J.; Ren, H.; Hou, Z.; Bao, J.
2017-12-01
Markov chain Monte Carlo (MCMC) methods are used to infer model parameters from observational data. The parameters are inferred as probability densities, thus capturing estimation error due to sparsity of the data, and the shortcomings of the model. Multiple communicating chains executing the MCMC method have the potential to explore the parameter space better, and conceivably accelerate the convergence to the final distribution. We present results from tests conducted with the multi-chain method to show how the acceleration occurs i.e., for loose convergence tolerances, the multiple chains do not make much of a difference. The ensemble of chains also seems to have the ability to accelerate the convergence of a few chains that might start from suboptimal starting points. Finally, we show the performance of the chains in the estimation of O(10) parameters using computationally expensive forward models such as the Community Land Model, where the sampling burden is distributed over multiple chains.
Three-dimensional Monte Carlo model of pulsed-laser treatment of cutaneous vascular lesions
Milanič, Matija; Majaron, Boris
2011-12-01
We present a three-dimensional Monte Carlo model of optical transport in skin with a novel approach to treatment of side boundaries of the volume of interest. This represents an effective way to overcome the inherent limitations of ``escape'' and ``mirror'' boundary conditions and enables high-resolution modeling of skin inclusions with complex geometries and arbitrary irradiation patterns. The optical model correctly reproduces measured values of diffuse reflectance for normal skin. When coupled with a sophisticated model of thermal transport and tissue coagulation kinetics, it also reproduces realistic values of radiant exposure thresholds for epidermal injury and for photocoagulation of port wine stain blood vessels in various skin phototypes, with or without application of cryogen spray cooling.
Collectivity in heavy nuclei in the shell model Monte Carlo approach
International Nuclear Information System (INIS)
Özen, C.; Alhassid, Y.; Nakada, H.
2014-01-01
The microscopic description of collectivity in heavy nuclei in the framework of the configuration-interaction shell model has been a major challenge. The size of the model space required for the description of heavy nuclei prohibits the use of conventional diagonalization methods. We have overcome this difficulty by using the shell model Monte Carlo (SMMC) method, which can treat model spaces that are many orders of magnitude larger than those that can be treated by conventional methods. We identify a thermal observable that can distinguish between vibrational and rotational collectivity and use it to describe the crossover from vibrational to rotational collectivity in families of even-even rare-earth isotopes. We calculate the state densities in these nuclei and find them to be in close agreement with experimental data. We also calculate the collective enhancement factors of the corresponding level densities and find that their decay with excitation energy is correlated with the pairing and shape phase transitions. (author)
International Nuclear Information System (INIS)
Courtine, Fabien
2007-03-01
The thesis proceeded in the context of dating by thermoluminescence. This method requires laboratory measurements of the natural radioactivity. For that purpose, we have been using a germanium spectrometer. To refine the calibration of this one, we modelled it by using a Monte-Carlo computer code: Geant4. We developed a geometrical model which takes into account the presence of inactive zones and zones of poor charge-collection within the germanium crystal. The parameters of the model were adjusted by comparison with experimental results obtained with a source of 137 Cs. It appeared that the form of the inactive zones is less simple than is presented in the specialized literature. This model was widened to the case of a more complex source, with cascade effect and angular correlations between photons: the 60 Co. Lastly, applied to extended sources, it gave correct results and allowed us to validate the simulation of matrix effect. (author)
Li, Shu; The ATLAS collaboration
2017-01-01
We present the Monte Carlo(MC) setup used by ATLAS to model multi-boson processes in √s = 13 TeV proton-proton collisions. The baseline Monte Carlo generators are compared with each other in key kinematic distributions of the processes under study. Sample normalization and systematic uncertainties are discussed.
Clinical Management and Burden of Prostate Cancer: A Markov Monte Carlo Model
Sanyal, Chiranjeev; Aprikian, Armen; Cury, Fabio; Chevalier, Simone; Dragomir, Alice
2014-01-01
Background Prostate cancer (PCa) is the most common non-skin cancer among men in developed countries. Several novel treatments have been adopted by healthcare systems to manage PCa. Most of the observational studies and randomized trials on PCa have concurrently evaluated fewer treatments over short follow-up. Further, preceding decision analytic models on PCa management have not evaluated various contemporary management options. Therefore, a contemporary decision analytic model was necessary to address limitations to the literature by synthesizing the evidence on novel treatments thereby forecasting short and long-term clinical outcomes. Objectives To develop and validate a Markov Monte Carlo model for the contemporary clinical management of PCa, and to assess the clinical burden of the disease from diagnosis to end-of-life. Methods A Markov Monte Carlo model was developed to simulate the management of PCa in men 65 years and older from diagnosis to end-of-life. Health states modeled were: risk at diagnosis, active surveillance, active treatment, PCa recurrence, PCa recurrence free, metastatic castrate resistant prostate cancer, overall and PCa death. Treatment trajectories were based on state transition probabilities derived from the literature. Validation and sensitivity analyses assessed the accuracy and robustness of model predicted outcomes. Results Validation indicated model predicted rates were comparable to observed rates in the published literature. The simulated distribution of clinical outcomes for the base case was consistent with sensitivity analyses. Predicted rate of clinical outcomes and mortality varied across risk groups. Life expectancy and health adjusted life expectancy predicted for the simulated cohort was 20.9 years (95%CI 20.5–21.3) and 18.2 years (95% CI 17.9–18.5), respectively. Conclusion Study findings indicated contemporary management strategies improved survival and quality of life in patients with PCa. This model could be used
The First 24 Years of Reverse Monte Carlo Modelling, Budapest, Hungary, 20-22 September 2012
Keen, David A.; Pusztai, László
2013-11-01
This special issue contains a collection of papers reflecting the content of the fifth workshop on reverse Monte Carlo (RMC) methods, held in a hotel on the banks of the Danube in the Budapest suburbs in the autumn of 2012. Over fifty participants gathered to hear talks and discuss a broad range of science based on the RMC technique in very convivial surroundings. Reverse Monte Carlo modelling is a method for producing three-dimensional disordered structural models in quantitative agreement with experimental data. The method was developed in the late 1980s and has since achieved wide acceptance within the scientific community [1], producing an average of over 90 papers and 1200 citations per year over the last five years. It is particularly suitable for the study of the structures of liquid and amorphous materials, as well as the structural analysis of disordered crystalline systems. The principal experimental data that are modelled are obtained from total x-ray or neutron scattering experiments, using the reciprocal space structure factor and/or the real space pair distribution function (PDF). Additional data might be included from extended x-ray absorption fine structure spectroscopy (EXAFS), Bragg peak intensities or indeed any measured data that can be calculated from a three-dimensional atomistic model. It is this use of total scattering (diffuse and Bragg), rather than just the Bragg peak intensities more commonly used for crystalline structure analysis, which enables RMC modelling to probe the often important deviations from the average crystal structure, to probe the structures of poorly crystalline or nanocrystalline materials, and the local structures of non-crystalline materials where only diffuse scattering is observed. This flexibility across various condensed matter structure-types has made the RMC method very attractive in a wide range of disciplines, as borne out in the contents of this special issue. It is however important to point out that since
Automatic generation of groundwater model hydrostratigraphy from AEM resistivity and boreholes
DEFF Research Database (Denmark)
Marker, Pernille Aabye; Foged, N.; Christiansen, A. V.
2014-01-01
Regional hydrological models are important tools in water resources management. Model prediction uncertainty is primarily due to structural (geological) non-uniqueness which makes sampling of the structural model space necessary to estimate prediction uncertainties. Geological structures and hete...... and discharge observations. The method was applied to field data collected at a Danish field site. Our results show that a competitive hydrological model can be constructed from the AEM dataset using the automatic procedure outlined above....
Automatic fitting of spiking neuron models to electrophysiological recordings
Directory of Open Access Journals (Sweden)
Cyrille Rossant
2010-03-01
Full Text Available Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains that can run in parallel on graphics processing units (GPUs. The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.
AUTOMATIC MESH GENERATION OF 3—D GEOMETRIC MODELS
Institute of Scientific and Technical Information of China (English)
刘剑飞
2003-01-01
In this paper the presentation of the ball-packing method is reviewed, and a schemeto generate mesh for complex 3-D geometric models is given, which consists of 4 steps: (1) createnodes in 3-D models by ball-packing method, (2) connect nodes to generate mesh by 3-D Delaunaytriangulation, (3) retrieve the boundary of the model after Delaunay triangulation, (4) improve themesh.
AUTOMATIC MESH GENERATION OF 3-D GEOMETRIC MODELS
Institute of Scientific and Technical Information of China (English)
刘剑飞
2003-01-01
In this paper the presentation of the ball-packing method is reviewed,and a scheme to generate mesh for complex 3-D geometric models is given,which consists of 4 steps:(1)create nodes in 3-D models by ball-packing method,(2)connect nodes to generate mesh by 3-D Delaunay triangulation,(3)retrieve the boundary of the model after Delaunay triangulation,(4)improve the mesh.
Energy Technology Data Exchange (ETDEWEB)
Leoevey, H.; Roemisch, W. [Humboldt-Univ., Berlin (Germany)
2015-07-01
We discuss progress in quasi Monte Carlo methods for numerical calculation integrals or expected values and justify why these methods are more efficient than the classic Monte Carlo methods. Quasi Monte Carlo methods are found to be particularly efficient if the integrands have a low effective dimension. That's why We also discuss the concept of effective dimension and prove on the example of a stochastic Optimization model of the energy industry that such models can posses a low effective dimension. Modern quasi Monte Carlo methods are therefore for such models very promising. [German] Wir diskutieren Fortschritte bei Quasi-Monte Carlo Methoden zur numerischen Berechnung von Integralen bzw. Erwartungswerten und begruenden warum diese Methoden effizienter sind als die klassischen Monte Carlo Methoden. Quasi-Monte Carlo Methoden erweisen sich als besonders effizient, falls die Integranden eine geringe effektive Dimension besitzen. Deshalb diskutieren wir auch den Begriff effektive Dimension und weisen am Beispiel eines stochastischen Optimierungsmodell aus der Energiewirtschaft nach, dass solche Modelle eine niedrige effektive Dimension besitzen koennen. Moderne Quasi-Monte Carlo Methoden sind deshalb fuer solche Modelle sehr erfolgversprechend.
Parameter sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis
Energy Technology Data Exchange (ETDEWEB)
Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control
2006-06-15
The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.
Building executable biological pathway models automatically from BioPAX
Willemsen, Timo; Feenstra, Anton; Groth, Paul
2013-01-01
The amount of biological data exposed in semantic formats is steadily increasing. In particular, pathway information (a model of how molecules interact within a cell) from databases such as KEGG and WikiPathways are available in a standard RDF-based format BioPAX. However, these models are
Automatic extraction of process categories from process model collections
Malinova, M.; Dijkman, R.M.; Mendling, J.; Lohmann, N.; Song, M.; Wohed, P.
2014-01-01
Many organizations build up their business process management activities in an incremental way. As a result, there is no overarching structure defined at the beginning. However, as business process modeling initiatives often yield hundreds to thousands of process models, there is a growing need for
Towards automatic model based controller design for reconfigurable plants
DEFF Research Database (Denmark)
Michelsen, Axel Gottlieb; Stoustrup, Jakob; Izadi-Zamanabadi, Roozbeh
2008-01-01
This paper introduces model-based Plug and Play Process Control, a novel concept for process control, which allows a model-based control system to be reconfigured when a sensor or an actuator is plugged into a controlled process. The work reported in this paper focuses on composing a monolithic m...
AUTOMATIC CALIBRATION OF A STOCHASTIC-LAGRANGIAN TRANSPORT MODEL (SLAM)
Numerical models are a useful tool in evaluating and designing NAPL remediation systems. Traditional constitutive finite difference and finite element models are complex and expensive to apply. For this reason, this paper presents the application of a simplified stochastic-Lagran...
Fast Monte Carlo-simulator with full collimator and detector response modelling for SPECT
International Nuclear Information System (INIS)
Sohlberg, A.O.; Kajaste, M.T.
2012-01-01
Monte Carlo (MC)-simulations have proved to be a valuable tool in studying single photon emission computed tomography (SPECT)-reconstruction algorithms. Despite their popularity, the use of Monte Carlo-simulations is still often limited by their large computation demand. This is especially true in situations where full collimator and detector modelling with septal penetration, scatter and X-ray fluorescence needs to be included. This paper presents a rapid and simple MC-simulator, which can effectively reduce the computation times. The simulator was built on the convolution-based forced detection principle, which can markedly lower the number of simulated photons. Full collimator and detector response look-up tables are pre-simulated and then later used in the actual MC-simulations to model the system response. The developed simulator was validated by comparing it against 123 I point source measurements made with a clinical gamma camera system and against 99m Tc software phantom simulations made with the SIMIND MC-package. The results showed good agreement between the new simulator, measurements and the SIMIND-package. The new simulator provided near noise-free projection data in approximately 1.5 min per projection with 99m Tc, which was less than one-tenth of SIMIND's time. The developed MC-simulator can markedly decrease the simulation time without sacrificing image quality. (author)
Kinetic Monte-Carlo modeling of hydrogen retention and re-emission from Tore Supra deposits
International Nuclear Information System (INIS)
Rai, A.; Schneider, R.; Warrier, M.; Roubin, P.; Martin, C.; Richou, M.
2009-01-01
A multi-scale model has been developed to study the reactive-diffusive transport of hydrogen in porous graphite [A. Rai, R. Schneider, M. Warrier, J. Nucl. Mater. (submitted for publication). http://dx.doi.org/10.1016/j.jnucmat.2007.08.013.]. The deposits found on the leading edge of the neutralizer of Tore Supra are multi-scale in nature, consisting of micropores with typical size lower than 2 nm (∼11%), mesopores (∼5%) and macropores with a typical size more than 50 nm [C. Martin, M. Richou, W. Sakaily, B. Pegourie, C. Brosset, P. Roubin, J. Nucl. Mater. 363-365 (2007) 1251]. Kinetic Monte-Carlo (KMC) has been used to study the hydrogen transport at meso-scales. Recombination rate and the diffusion coefficient calculated at the meso-scale was used as an input to scale up and analyze the hydrogen transport at macro-scale. A combination of KMC and MCD (Monte-Carlo diffusion) method was used at macro-scales. Flux dependence of hydrogen recycling has been studied. The retention and re-emission analysis of the model has been extended to study the chemical erosion process based on the Kueppers-Hopf cycle [M. Wittmann, J. Kueppers, J. Nucl. Mater. 227 (1996) 186].
Energy Technology Data Exchange (ETDEWEB)
Zakova, Jitka [Department of Nuclear and Reactor Physics, Royal Institute of Technology, KTH, Roslagstullsbacken 21, S-10691 Stockholm (Sweden)], E-mail: jitka.zakova@neutron.kth.se; Talamo, Alberto [Nuclear Engineering Division, Argonne National Laboratory, ANL, 9700 South Cass Avenue, Argonne, IL 60439 (United States)], E-mail: alby@anl.gov
2008-05-15
Modeling of prismatic high temperature reactors requires a high precision description due to the triple heterogeneity of the core and also to the random distribution of fuel particles inside the fuel pins. On the latter issue, even with the most advanced Monte Carlo techniques, some approximation often arises while assessing the criticality level: first, a regular lattice of TRISO particles inside the fuel pins and, second, the cutting of TRISO particles by the fuel boundaries. We utilized two of the most accurate Monte Codes: MONK and MCNP, which are both used for licensing nuclear power plants in United Kingdom and in the USA, respectively, to evaluate the influence of the two previous approximations on estimating the criticality level of the Gas Turbine Modular Helium Reactor. The two codes exactly shared the same geometry and nuclear data library, ENDF/B, and only modeled different lattices of TRISO particles inside the fuel pins. More precisely, we investigated the difference between a regular lattice that cuts TRISO particles and a random lattice that axially repeats a region containing over 3000 non-cut particles. We have found that both Monte Carlo codes provide similar excesses of reactivity, provided that they share the same approximations.
Study on Quantification for Multi-unit Seismic PSA Model using Monte Carlo Sampling
International Nuclear Information System (INIS)
Oh, Kyemin; Han, Sang Hoon; Jang, Seung-cheol; Park, Jin Hee; Lim, Ho-Gon; Yang, Joon Eon; Heo, Gyunyoung
2015-01-01
In existing PSA, frequency for accident sequences occurred in single-unit has been estimated. While multi-unit PSA has to consider various combinations because accident sequence in each units can be different. However, it is difficult to quantify all of combination between inter-units using traditional method such as Minimal Cut Upper Bound (MCUB). For this reason, we used Monte Carlo sampling as a method to quantify multi-unit PSA model. In this paper, Monte Carlo method was used to quantify multi-unit PSA model. The advantage of this method is to consider all of combinations by the increase of number of unit and to calculate nearly exact value compared to other method. However, it is difficult to get detailed information such as minimal cut sets and accident sequence. To solve partially this problem, FTeMC was modified. In multi-unit PSA, quantification for both internal and external multi-unit accidents is the significant issue. Although our result above mentioned was one of the case studies to check application of method suggested in this paper, it is expected that this method can be used in practical assessment for multi-unit risk
Pfefer, T Joshua; Wang, Quanzeng; Drezek, Rebekah A
2011-11-01
Computational approaches for simulation of light-tissue interactions have provided extensive insight into biophotonic procedures for diagnosis and therapy. However, few studies have addressed simulation of time-resolved fluorescence (TRF) in tissue and none have combined Monte Carlo simulations with standard TRF processing algorithms to elucidate approaches for cancer detection in layered biological tissue. In this study, we investigate how illumination-collection parameters (e.g., collection angle and source-detector separation) influence the ability to measure fluorophore lifetime and tissue layer thickness. Decay curves are simulated with a Monte Carlo TRF light propagation model. Multi-exponential iterative deconvolution is used to determine lifetimes and fractional signal contributions. The ability to detect changes in mucosal thickness is optimized by probes that selectively interrogate regions superficial to the mucosal-submucosal boundary. Optimal accuracy in simultaneous determination of lifetimes in both layers is achieved when each layer contributes 40-60% of the signal. These results indicate that depth-selective approaches to TRF have the potential to enhance disease detection in layered biological tissue and that modeling can play an important role in probe design optimization. Published by Elsevier Ireland Ltd.
Nonlinear Monte Carlo model of superdiffusive shock acceleration with magnetic field amplification
Bykov, Andrei M.; Ellison, Donald C.; Osipov, Sergei M.
2017-03-01
Fast collisionless shocks in cosmic plasmas convert their kinetic energy flow into the hot downstream thermal plasma with a substantial fraction of energy going into a broad spectrum of superthermal charged particles and magnetic fluctuations. The superthermal particles can penetrate into the shock upstream region producing an extended shock precursor. The cold upstream plasma flow is decelerated by the force provided by the superthermal particle pressure gradient. In high Mach number collisionless shocks, efficient particle acceleration is likely coupled with turbulent magnetic field amplification (MFA) generated by the anisotropic distribution of accelerated particles. This anisotropy is determined by fast particle transport, making the problem strongly nonlinear and multiscale. Here, we present a nonlinear Monte Carlo model of collisionless shock structure with superdiffusive propagation of high-energy Fermi accelerated particles coupled to particle acceleration and MFA, which affords a consistent description of strong shocks. A distinctive feature of the Monte Carlo technique is that it includes the full angular anisotropy of the particle distribution at all precursor positions. The model reveals that the superdiffusive transport of energetic particles (i.e., Lévy-walk propagation) generates a strong quadruple anisotropy in the precursor particle distribution. The resultant pressure anisotropy of the high-energy particles produces a nonresonant mirror-type instability that amplifies compressible wave modes with wavelengths longer than the gyroradii of the highest-energy protons produced by the shock.
Fully automatic adjoints: a robust and efficient mechanism for generating adjoint ocean models
Ham, D. A.; Farrell, P. E.; Funke, S. W.; Rognes, M. E.
2012-04-01
The problem of generating and maintaining adjoint models is sufficiently difficult that typically only the most advanced and well-resourced community ocean models achieve it. There are two current technologies which each suffer from their own limitations. Algorithmic differentiation, also called automatic differentiation, is employed by models such as the MITGCM [2] and the Alfred Wegener Institute model FESOM [3]. This technique is very difficult to apply to existing code, and requires a major initial investment to prepare the code for automatic adjoint generation. AD tools may also have difficulty with code employing modern software constructs such as derived data types. An alternative is to formulate the adjoint differential equation and to discretise this separately. This approach, known as the continuous adjoint and employed in ROMS [4], has the disadvantage that two different model code bases must be maintained and manually kept synchronised as the model develops. The discretisation of the continuous adjoint is not automatically consistent with that of the forward model, producing an additional source of error. The alternative presented here is to formulate the flow model in the high level language UFL (Unified Form Language) and to automatically generate the model using the software of the FEniCS project. In this approach it is the high level code specification which is differentiated, a task very similar to the formulation of the continuous adjoint [5]. However since the forward and adjoint models are generated automatically, the difficulty of maintaining them vanishes and the software engineering process is therefore robust. The scheduling and execution of the adjoint model, including the application of an appropriate checkpointing strategy is managed by libadjoint [1]. In contrast to the conventional algorithmic differentiation description of a model as a series of primitive mathematical operations, libadjoint employs a new abstraction of the simulation
Transport appraisal and Monte Carlo simulation by use of the CBA-DK model
DEFF Research Database (Denmark)
Salling, Kim Bang; Leleur, Steen
2011-01-01
calculation, where risk analysis is carried out using Monte Carlo simulation. Special emphasis has been placed on the separation between inherent randomness in the modeling system and lack of knowledge. These two concepts have been defined in terms of variability (ontological uncertainty) and uncertainty......This paper presents the Danish CBA-DK software model for assessment of transport infrastructure projects. The assessment model is based on both a deterministic calculation following the cost-benefit analysis (CBA) methodology in a Danish manual from the Ministry of Transport and on a stochastic...... (epistemic uncertainty). After a short introduction to deterministic calculation resulting in some evaluation criteria a more comprehensive evaluation of the stochastic calculation is made. Especially, the risk analysis part of CBA-DK, with considerations about which probability distributions should be used...
Kinetic Monte Carlo modeling of chemical reactions coupled with heat transfer.
Castonguay, Thomas C; Wang, Feng
2008-03-28
In this paper, we describe two types of effective events for describing heat transfer in a kinetic Monte Carlo (KMC) simulation that may involve stochastic chemical reactions. Simulations employing these events are referred to as KMC-TBT and KMC-PHE. In KMC-TBT, heat transfer is modeled as the stochastic transfer of "thermal bits" between adjacent grid points. In KMC-PHE, heat transfer is modeled by integrating the Poisson heat equation for a short time. Either approach is capable of capturing the time dependent system behavior exactly. Both KMC-PHE and KMC-TBT are validated by simulating pure heat transfer in a rod and a square and modeling a heated desorption problem where exact numerical results are available. KMC-PHE is much faster than KMC-TBT and is used to study the endothermic desorption of a lattice gas. Interesting findings from this study are reported.
Dynamic Value at Risk: A Comparative Study Between Heteroscedastic Models and Monte Carlo Simulation
Directory of Open Access Journals (Sweden)
José Lamartine Távora Junior
2006-12-01
Full Text Available The objective of this paper was to analyze the risk management of a portfolio composed by Petrobras PN, Telemar PN and Vale do Rio Doce PNA stocks. It was verified if the modeling of Value-at-Risk (VaR through the place Monte Carlo simulation with volatility of GARCH family is supported by hypothesis of efficient market. The results have shown that the statistic evaluation in inferior to dynamics, evidencing that the dynamic analysis supplies support to the hypothesis of efficient market of the Brazilian share holding market, in opposition of some empirical evidences. Also, it was verified that the GARCH models of volatility is enough to accommodate the variations of the shareholding Brazilian market, since the model is capable to accommodate the great dynamic of the Brazilian market.
Abbas, Ismail; Rovira, Joan; Casanovas, Josep
2007-05-01
The patient recruitment process of clinical trials is an essential element which needs to be designed properly. In this paper we describe different simulation models under continuous and discrete time assumptions for the design of recruitment in clinical trials. The results of hypothetical examples of clinical trial recruitments are presented. The recruitment time is calculated and the number of recruited patients is quantified for a given time and probability of recruitment. The expected delay and the effective recruitment durations are estimated using both continuous and discrete time modeling. The proposed type of Monte Carlo simulation Markov models will enable optimization of the recruitment process and the estimation and the calibration of its parameters to aid the proposed clinical trials. A continuous time simulation may minimize the duration of the recruitment and, consequently, the total duration of the trial.
Monte Carlo impurity transport modeling in the DIII-D transport
International Nuclear Information System (INIS)
Evans, T.E.; Finkenthal, D.F.
1998-04-01
A description of the carbon transport and sputtering physics contained in the Monte Carlo Impurity (MCI) transport code is given. Examples of statistically significant carbon transport pathways are examined using MCI's unique tracking visualizer and a mechanism for enhanced carbon accumulation on the high field side of the divertor chamber is discussed. Comparisons between carbon emissions calculated with MCI and those measured in the DIII-D tokamak are described. Good qualitative agreement is found between 2D carbon emission patterns calculated with MCI and experimentally measured carbon patterns. While uncertainties in the sputtering physics, atomic data, and transport models have made quantitative comparisons with experiments more difficult, recent results using a physics based model for physical and chemical sputtering has yielded simulations with about 50% of the total carbon radiation measured in the divertor. These results and plans for future improvement in the physics models and atomic data are discussed
DEFF Research Database (Denmark)
Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan
2008-01-01
uncertainty estimation (GLUE) procedure based on Markov chain Monte Carlo sampling is applied in order to improve the performance of the methodology in estimating parameters and posterior output distributions. The description of the spatial variations of the hydrological processes is accounted for by defining......In recent years, there has been an increase in the application of distributed, physically-based and integrated hydrological models. Many questions regarding how to properly calibrate and validate distributed models and assess the uncertainty of the estimated parameters and the spatially......-site validation must complement the usual time validation. In this study, we develop, through an application, a comprehensive framework for multi-criteria calibration and uncertainty assessment of distributed physically-based, integrated hydrological models. A revised version of the generalized likelihood...
Monte Carlo modelling of germanium crystals that are tilted and have rounded front edges
International Nuclear Information System (INIS)
Gasparro, Joel; Hult, Mikael; Johnston, Peter N.; Tagziria, Hamid
2008-01-01
Gamma-ray detection efficiencies and cascade summing effects in germanium detectors are often calculated using Monte Carlo codes based on a computer model of the detection system. Such a model can never fully replicate reality and it is important to understand how various parameters affect the results. This work concentrates on quantifying two issues, namely (i) the effect of having a Ge-crystal that is tilted inside the cryostat and (ii) the effect of having a model of a Ge-crystal with rounded edges (bulletization). The effect of the tilting is very small (in the order of per mille) when the tilting angles are within a realistic range. The effect of the rounded edges is, however, relatively large (5-10% or higher) particularly for gamma-ray energies below 100 keV
Monte Carlo modelling of germanium crystals that are tilted and have rounded front edges
Energy Technology Data Exchange (ETDEWEB)
Gasparro, Joel [EC-JRC-IRMM, Institute for Reference Materials and Measurements, Retieseweg 111, B-2440 Geel (Belgium); Hult, Mikael [EC-JRC-IRMM, Institute for Reference Materials and Measurements, Retieseweg 111, B-2440 Geel (Belgium)], E-mail: mikael.hult@ec.europa.eu; Johnston, Peter N. [Applied Physics, Royal Melbourne Institute of Technology, GPO Box 2476V, Melbourne 3001 (Australia); Tagziria, Hamid [EC-JRC-IPSC, Institute for the Protection and the Security of the Citizen, Via E. Fermi 1, I-21020 Ispra (Vatican City State, Holy See,) (Italy)
2008-09-01
Gamma-ray detection efficiencies and cascade summing effects in germanium detectors are often calculated using Monte Carlo codes based on a computer model of the detection system. Such a model can never fully replicate reality and it is important to understand how various parameters affect the results. This work concentrates on quantifying two issues, namely (i) the effect of having a Ge-crystal that is tilted inside the cryostat and (ii) the effect of having a model of a Ge-crystal with rounded edges (bulletization). The effect of the tilting is very small (in the order of per mille) when the tilting angles are within a realistic range. The effect of the rounded edges is, however, relatively large (5-10% or higher) particularly for gamma-ray energies below 100 keV.
Monte Carlo modeling of fiber-scintillator flow-cell radiation detector geometry
International Nuclear Information System (INIS)
Rucker, T.L.; Ross, H.H.; Tennessee Univ., Knoxville; Schweitzer, G.K.
1988-01-01
A Monte Carlo computer calculation is described which models the geometric efficiency of a fiber-scintillator flow-cell radiation detector designed to detect radiolabeled compounds in liquid chromatography eluates. By using special mathematical techniques, an efficiency prediction with a precision of 1% is obtained after generating only 1000 random events. Good agreement is seen between predicted and experimental efficiency except for very low energy beta emission where the geometric limitation on efficiency is overcome by pulse height limitations which the model does not consider. The modeling results show that in the test system, the detection efficiency for low energy beta emitters is limited primarily by light generation and collection rather than geometry. (orig.)
Modelling phase separation in Fe-Cr system using different atomistic kinetic Monte Carlo techniques
International Nuclear Information System (INIS)
Castin, N.; Bonny, G.; Terentyev, D.; Lavrentiev, M.Yu.; Nguyen-Manh, D.
2011-01-01
Atomistic kinetic Monte Carlo (AKMC) simulations were performed to study α-α' phase separation in Fe-Cr alloys. Two different energy models and two approaches to estimate the local vacancy migration barriers were used. The energy models considered are a two-band model Fe-Cr potential and a cluster expansion, both fitted to ab initio data. The classical Kang-Weinberg decomposition, based on the total energy change of the system, and an Artificial Neural Network (ANN), employed as a regression tool were used to predict the local vacancy migration barriers 'on the fly'. The results are compared with experimental thermal annealing data and differences between the applied AKMC approaches are discussed. The ability of the ANN regression method to accurately predict migration barriers not present in the training list is also addressed by performing cross-check calculations using the nudged elastic band method.
Martin-Bragado, I.; Castrillo, P.; Jaraiz, M.; Pinacho, R.; Rubio, J. E.; Barbolla, J.; Moroz, V.
2005-09-01
Atomistic process simulation is expected to play an important role for the development of next generations of integrated circuits. This work describes an approach for modeling electric charge effects in a three-dimensional atomistic kinetic Monte Carlo process simulator. The proposed model has been applied to the diffusion of electrically active boron and arsenic atoms in silicon. Several key aspects of the underlying physical mechanisms are discussed: (i) the use of the local Debye length to smooth out the atomistic point-charge distribution, (ii) algorithms to correctly update the charge state in a physically accurate and computationally efficient way, and (iii) an efficient implementation of the drift of charged particles in an electric field. High-concentration effects such as band-gap narrowing and degenerate statistics are also taken into account. The efficiency, accuracy, and relevance of the model are discussed.
A Monte Carlo-based model for simulation of digital chest tomo-synthesis
International Nuclear Information System (INIS)
Ullman, G.; Dance, D. R.; Sandborg, M.; Carlsson, G. A.; Svalkvist, A.; Baath, M.
2010-01-01
The aim of this work was to calculate synthetic digital chest tomo-synthesis projections using a computer simulation model based on the Monte Carlo method. An anthropomorphic chest phantom was scanned in a computed tomography scanner, segmented and included in the computer model to allow for simulation of realistic high-resolution X-ray images. The input parameters to the model were adapted to correspond to the VolumeRAD chest tomo-synthesis system from GE Healthcare. Sixty tomo-synthesis projections were calculated with projection angles ranging from + 15 to -15 deg. The images from primary photons were calculated using an analytical model of the anti-scatter grid and a pre-calculated detector response function. The contributions from scattered photons were calculated using an in-house Monte Carlo-based model employing a number of variance reduction techniques such as the collision density estimator. Tomographic section images were reconstructed by transferring the simulated projections into the VolumeRAD system. The reconstruction was performed for three types of images using: (i) noise-free primary projections, (ii) primary projections including contributions from scattered photons and (iii) projections as in (ii) with added correlated noise. The simulated section images were compared with corresponding section images from projections taken with the real, anthropomorphic phantom from which the digital voxel phantom was originally created. The present article describes a work in progress aiming towards developing a model intended for optimisation of chest tomo-synthesis, allowing for simulation of both existing and future chest tomo-synthesis systems. (authors)
Using a Monte Carlo model to predict dosimetric properties of small radiotherapy photon fields
International Nuclear Information System (INIS)
Scott, Alison J. D.; Nahum, Alan E.; Fenwick, John D.
2008-01-01
Accurate characterization of small-field dosimetry requires measurements to be made with precisely aligned specialized detectors and is thus time consuming and error prone. This work explores measurement differences between detectors by using a Monte Carlo model matched to large-field data to predict properties of smaller fields. Measurements made with a variety of detectors have been compared with calculated results to assess their validity and explore reasons for differences. Unshielded diodes are expected to produce some of the most useful data, as their small sensitive cross sections give good resolution whilst their energy dependence is shown to vary little with depth in a 15 MV linac beam. Their response is shown to be constant with field size over the range 1-10 cm, with a correction of 3% needed for a field size of 0.5 cm. BEAMnrc has been used to create a 15 MV beam model, matched to dosimetric data for square fields larger than 3 cm, and producing small-field profiles and percentage depth doses (PDDs) that agree well with unshielded diode data for field sizes down to 0.5 cm. For fields sizes of 1.5 cm and above, little detector-to-detector variation exists in measured output factors, however for a 0.5 cm field a relative spread of 18% is seen between output factors measured with different detectors--values measured with the diamond and pinpoint detectors lying below that of the unshielded diode, with the shielded diode value being higher. Relative to the corrected unshielded diode measurement, the Monte Carlo modeled output factor is 4.5% low, a discrepancy that is probably due to the focal spot fluence profile and source occlusion modeling. The large-field Monte Carlo model can, therefore, currently be used to predict small-field profiles and PDDs measured with an unshielded diode. However, determination of output factors for the smallest fields requires a more detailed model of focal spot fluence and source occlusion.
Full modelling of the MOSAIC animal PET system based on the GATE Monte Carlo simulation code
International Nuclear Information System (INIS)
Merheb, C; Petegnief, Y; Talbot, J N
2007-01-01
Positron emission tomography (PET) systems dedicated to animal imaging are now widely used for biological studies. The scanner performance strongly depends on the design and the characteristics of the system. Many parameters must be optimized like the dimensions and type of crystals, geometry and field-of-view (FOV), sampling, electronics, lightguide, shielding, etc. Monte Carlo modelling is a powerful tool to study the effect of each of these parameters on the basis of realistic simulated data. Performance assessment in terms of spatial resolution, count rates, scatter fraction and sensitivity is an important prerequisite before the model can be used instead of real data for a reliable description of the system response function or for optimization of reconstruction algorithms. The aim of this study is to model the performance of the Philips Mosaic(TM) animal PET system using a comprehensive PET simulation code in order to understand and describe the origin of important factors that influence image quality. We use GATE, a Monte Carlo simulation toolkit for a realistic description of the ring PET model, the detectors, shielding, cap, electronic processing and dead times. We incorporate new features to adjust signal processing to the Anger logic underlying the Mosaic(TM) system. Special attention was paid to dead time and energy spectra descriptions. Sorting of simulated events in a list mode format similar to the system outputs was developed to compare experimental and simulated sensitivity and scatter fractions for different energy thresholds using various models of phantoms describing rat and mouse geometries. Count rates were compared for both cylindrical homogeneous phantoms. Simulated spatial resolution was fitted to experimental data for 18 F point sources at different locations within the FOV with an analytical blurring function for electronic processing effects. Simulated and measured sensitivities differed by less than 3%, while scatter fractions agreed
Constraint optimization model of a scheduling problem for a robotic arm in automatic systems
DEFF Research Database (Denmark)
Kristiansen, Ewa; Smith, Stephen F.; Kristiansen, Morten
2014-01-01
are characteristics of the painting process application itself. Unlike spot-welding, painting tasks require movement of the entire robot arm. In addition to minimizing intertask duration, the scheduler must strive to maximize painting quality and the problem is formulated as a multi-objective optimization problem....... The scheduling model is implemented as a stand-alone module using constraint programming, and integrated with a larger automatic system. The results of a number of simulation experiments with simple parts are reported, both to characterize the functionality of the scheduler and to illustrate the operation...... of the entire software system for automatic generation of robot programs for painting....
A Method for Modeling the Virtual Instrument Automatic Test System Based on the Petri Net
Institute of Scientific and Technical Information of China (English)
MA Min; CHEN Guang-ju
2005-01-01
Virtual instrument is playing the important role in automatic test system. This paper introduces a composition of a virtual instrument automatic test system and takes the VXIbus based a test software platform which is developed by CAT lab of the UESTC as an example. Then a method to model this system based on Petri net is proposed. Through this method, we can analyze the test task scheduling to prevent the deadlock or resources conflict. At last, this paper analyzes the feasibility of this method.
Unidirectional high fiber content composites: Automatic 3D FE model generation and damage simulation
DEFF Research Database (Denmark)
Qing, Hai; Mishnaevsky, Leon
2009-01-01
A new method and a software code for the automatic generation of 3D micromechanical FE models of unidirectional long-fiber-reinforced composite (LFRC) with high fiber volume fraction with random fiber arrangement are presented. The fiber arrangement in the cross-section is generated through random...
Automatic generation of medium-detailed 3D models of buildings based on CAD data
Dominguez-Martin, B.; Van Oosterom, P.; Feito-Higueruela, F.R.; Garcia-Fernandez, A.L.; Ogayar-Anguita, C.J.
2015-01-01
We present the preliminary results of a work in progress which aims to obtain a software system able to automatically generate a set of diverse 3D building models with a medium level of detail, that is, more detailed that a mere parallelepiped, but not as detailed as a complete geometric
Polomčić, Dušan M.; Bajić, Dragoljub I.; Močević, Jelena M.
2015-01-01
The calibration process of hydrodynamic model is done usually manually by 'testing' with different values of hydrogeological parameters and hydraulic characteristics of the boundary conditions. By using the PEST program, automatic calibration of models has been introduced, and it has proved to significantly reduce the subjective influence of the model creator on results. With the relatively new approach of PEST, i.e. with the introduction of so-called 'pilot points', the concept of homogeneou...
Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model Generation for ns-3
2015-12-01
more protocols (especially at different layers of the OSI model ), implementing an inference engine to extract inter- and intrapacket dependencies, and...ARL-TR-7543 ● DEC 2015 US Army Research Laboratory Automatic Traffic-Based Internet Control Message Protocol (ICMP) Model ...ICMP) Model Generation for ns-3 by Jaime C Acosta and Felipe Jovel Survivability/Lethality Analysis Directorate, ARL Felipe Sotelo and Caesar
Calibration of Automatically Generated Items Using Bayesian Hierarchical Modeling.
Johnson, Matthew S.; Sinharay, Sandip
For complex educational assessments, there is an increasing use of "item families," which are groups of related items. However, calibration or scoring for such an assessment requires fitting models that take into account the dependence structure inherent among the items that belong to the same item family. C. Glas and W. van der Linden…
Automatic Welding Control Using a State Variable Model.
1979-06-01
A-A10 610 NAVEAL POSTGRADUATE SCH4O.M CEAY CA0/ 13/ SAUTOMATIC WELDING CONTROL USING A STATE VARIABLE MODEL.W()JUN 79 W V "my UNCLASSIFIED...taverse Drive Unit // Jbint Path /Fixed Track 34 (servomotor positioning). Additional controls of heave (vertical), roll (angular rotation about the
Automatic Relevance Determination for multi-way models
DEFF Research Database (Denmark)
Mørup, Morten; Hansen, Lars Kai
2009-01-01
of components of data within the Tucker and CP structure. For the Tucker and CP model the approach performs better than heuristics such as the Bayesian Information Criterion, Akaikes Information Criterion, DIFFIT and the numerical convex hull (NumConvHull) while operating only at the cost of estimating...... is available for download at www.erpwavelab.org....
On Automatic Modeling and Use of Domain-specific Ontologies
DEFF Research Database (Denmark)
Andreasen, Troels; Knappe, Rasmus; Bulskov, Henrik
2005-01-01
In this paper, we firstly introduce an approach to the modeling of a domain-specific ontology for use in connection with a given document collection. Secondly, we present a methodology for deriving conceptual similarity from the domain-specific ontology. Adopted for ontology representation is a s...
International Nuclear Information System (INIS)
Zazula, J.M.
1988-01-01
The self-learning Monte Carlo technique has been implemented to the commonly used general purpose neutron transport code MORSE, in order to enhance sampling of the particle histories that contribute to a detector response. The parameters of all the biasing techniques available in MORSE, i.e. of splitting, Russian roulette, source and collision outgoing energy importance sampling, path length transformation and additional biasing of the source angular distribution are optimized. The learning process is iteratively performed after each batch of particles, by retrieving the data concerning the subset of histories that passed the detector region and energy range in the previous batches. This procedure has been tested on two sample problems in nuclear geophysics, where an unoptimized Monte Carlo calculation is particularly inefficient. The results are encouraging, although the presented method does not directly minimize the variance and the convergence of our algorithm is restricted by the statistics of successful histories from previous random walk. Further applications for modeling of the nuclear logging measurements seem to be promising. 11 refs., 2 figs., 3 tabs. (author)
A virtual source method for Monte Carlo simulation of Gamma Knife Model C
Energy Technology Data Exchange (ETDEWEB)
Kim, Tae Hoon; Kim, Yong Kyun [Hanyang University, Seoul (Korea, Republic of); Chung, Hyun Tai [Seoul National University College of Medicine, Seoul (Korea, Republic of)
2016-05-15
The Monte Carlo simulation method has been used for dosimetry of radiation treatment. Monte Carlo simulation is the method that determines paths and dosimetry of particles using random number. Recently, owing to the ability of fast processing of the computers, it is possible to treat a patient more precisely. However, it is necessary to increase the simulation time to improve the efficiency of accuracy uncertainty. When generating the particles from the cobalt source in a simulation, there are many particles cut off. So it takes time to simulate more accurately. For the efficiency, we generated the virtual source that has the phase space distribution which acquired a single gamma knife channel. We performed the simulation using the virtual sources on the 201 channel and compared the measurement with the simulation using virtual sources and real sources. A virtual source file was generated to reduce the simulation time of a Gamma Knife Model C. Simulations with a virtual source executed about 50 times faster than the original source code and there was no statistically significant difference in simulated results.
A virtual source method for Monte Carlo simulation of Gamma Knife Model C
International Nuclear Information System (INIS)
Kim, Tae Hoon; Kim, Yong Kyun; Chung, Hyun Tai
2016-01-01
The Monte Carlo simulation method has been used for dosimetry of radiation treatment. Monte Carlo simulation is the method that determines paths and dosimetry of particles using random number. Recently, owing to the ability of fast processing of the computers, it is possible to treat a patient more precisely. However, it is necessary to increase the simulation time to improve the efficiency of accuracy uncertainty. When generating the particles from the cobalt source in a simulation, there are many particles cut off. So it takes time to simulate more accurately. For the efficiency, we generated the virtual source that has the phase space distribution which acquired a single gamma knife channel. We performed the simulation using the virtual sources on the 201 channel and compared the measurement with the simulation using virtual sources and real sources. A virtual source file was generated to reduce the simulation time of a Gamma Knife Model C. Simulations with a virtual source executed about 50 times faster than the original source code and there was no statistically significant difference in simulated results
Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model
International Nuclear Information System (INIS)
Cubasch, U.; Santer, B.D.; Hegerl, G.; Hoeck, H.; Maier-Reimer, E.; Mikolajwicz, U.; Stoessel, A.; Voss, R.
1992-01-01
The Monte Carlo approach, which has increasingly been used during the last decade in the field of extended range weather forecasting, has been applied for climate change experiments. Four integrations with a global coupled ocean-atmosphere model have been started from different initial conditions, but with the same greenhouse gas forcing according to the IPCC scenario A. All experiments have been run for a period of 50 years. The results indicate that the time evolution of the global mean warming depends strongly on the initial state of the climate system. It can vary between 6 and 31 years. The Monte Carlo approach delivers information about both the mean response and the statistical significance of the response. While the individual members of the ensemble show a considerable variation in the climate change pattern of temperature after 50 years, the ensemble mean climate change pattern closely resembles the pattern obtained in a 100 year integration and is, at least over most of the land areas, statistically significant. The ensemble averaged sea-level change due to thermal expansion is significant in the global mean and locally over wide regions of the Pacific. The hydrological cycle is also significantly enhanced in the global mean, but locally the changes in precipitation and soil moisture are masked by the variability of the experiments. (orig.)
Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki
2014-09-01
Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.
A three-dimensional self-learning kinetic Monte Carlo model: application to Ag(111)
International Nuclear Information System (INIS)
Latz, Andreas; Brendel, Lothar; Wolf, Dietrich E
2012-01-01
The reliability of kinetic Monte Carlo (KMC) simulations depends on accurate transition rates. The self-learning KMC method (Trushin et al 2005 Phys. Rev. B 72 115401) combines the accuracy of rates calculated from a realistic potential with the efficiency of a rate catalog, using a pattern recognition scheme. This work expands the original two-dimensional method to three dimensions. The concomitant huge increase in the number of rate calculations on the fly needed can be avoided by setting up an initial database, containing exact activation energies calculated for processes gathered from a simpler KMC model. To provide two representative examples, the model is applied to the diffusion of Ag monolayer islands on Ag(111), and the homoepitaxial growth of Ag on Ag(111) at low temperatures.
Monte Carlo method for critical systems in infinite volume: The planar Ising model.
Herdeiro, Victor; Doyon, Benjamin
2016-10-01
In this paper we propose a Monte Carlo method for generating finite-domain marginals of critical distributions of statistical models in infinite volume. The algorithm corrects the problem of the long-range effects of boundaries associated to generating critical distributions on finite lattices. It uses the advantage of scale invariance combined with ideas of the renormalization group in order to construct a type of "holographic" boundary condition that encodes the presence of an infinite volume beyond it. We check the quality of the distribution obtained in the case of the planar Ising model by comparing various observables with their infinite-plane prediction. We accurately reproduce planar two-, three-, and four-point of spin and energy operators. We also define a lattice stress-energy tensor, and numerically obtain the associated conformal Ward identities and the Ising central charge.
Development of numerical models for Monte Carlo simulations of Th-Pb fuel assembly
Directory of Open Access Journals (Sweden)
Oettingen Mikołaj
2017-01-01
Full Text Available The thorium-uranium fuel cycle is a promising alternative against uranium-plutonium fuel cycle, but it demands many advanced research before starting its industrial application in commercial nuclear reactors. The paper presents the development of the thorium-lead (Th-Pb fuel assembly numerical models for the integral irradiation experiments. The Th-Pb assembly consists of a hexagonal array of ThO2 fuel rods and metallic Pb rods. The design of the assembly allows different combinations of rods for various types of irradiations and experimental measurements. The numerical model of the Th-Pb assembly was designed for the numerical simulations with the continuous energy Monte Carlo Burnup code (MCB implemented on the supercomputer Prometheus of the Academic Computer Centre Cyfronet AGH.
Hybrid transport and diffusion modeling using electron thermal transport Monte Carlo SNB in DRACO
Chenhall, Jeffrey; Moses, Gregory
2017-10-01
The iSNB (implicit Schurtz Nicolai Busquet) multigroup diffusion electron thermal transport method is adapted into an Electron Thermal Transport Monte Carlo (ETTMC) transport method to better model angular and long mean free path non-local effects. Previously, the ETTMC model had been implemented in the 2D DRACO multiphysics code and found to produce consistent results with the iSNB method. Current work is focused on a hybridization of the computationally slower but higher fidelity ETTMC transport method with the computationally faster iSNB diffusion method in order to maximize computational efficiency. Furthermore, effects on the energy distribution of the heat flux divergence are studied. Work to date on the hybrid method will be presented. This work was supported by Sandia National Laboratories and the Univ. of Rochester Laboratory for Laser Energetics.
Measurement and Monte Carlo modeling of the spatial response of scintillation screens
Energy Technology Data Exchange (ETDEWEB)
Pistrui-Maximean, S.A. [CNDRI (NDT using Ionizing Radiation) Laboratory, INSA-Lyon, 69621 Villeurbanne (France)], E-mail: spistrui@gmail.com; Letang, J.M. [CNDRI (NDT using Ionizing Radiation) Laboratory, INSA-Lyon, 69621 Villeurbanne (France)], E-mail: jean-michel.letang@insa-lyon.fr; Freud, N. [CNDRI (NDT using Ionizing Radiation) Laboratory, INSA-Lyon, 69621 Villeurbanne (France); Koch, A. [Thales Electron Devices, 38430 Moirans (France); Walenta, A.H. [Detectors and Electronics Department, FB Physik, Siegen University, 57068 Siegen (Germany); Montarou, G. [Corpuscular Physics Laboratory, Blaise Pascal University, 63177 Aubiere (France); Babot, D. [CNDRI (NDT using Ionizing Radiation) Laboratory, INSA-Lyon, 69621 Villeurbanne (France)
2007-11-01
In this article, we propose a detailed protocol to carry out measurements of the spatial response of scintillation screens and to assess the agreement with simulated results. The experimental measurements have been carried out using a practical implementation of the slit method. A Monte Carlo simulation model of scintillator screens, implemented with the toolkit Geant4, has been used to study the influence of the acquisition setup parameters and to compare with the experimental results. An algorithm of global stochastic optimization based on a localized random search method has been implemented to adjust the optical parameters (optical scattering and absorption coefficients). The algorithm has been tested for different X-ray tube voltages (40, 70 and 100 kV). A satisfactory convergence between the results simulated with the optimized model and the experimental measurements is obtained.
International Nuclear Information System (INIS)
Gelß, Patrick; Matera, Sebastian; Schütte, Christof
2016-01-01
In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO 2 (110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.
Monte Carlo simulation of a statistical mechanical model of multiple protein sequence alignment.
Kinjo, Akira R
2017-01-01
A grand canonical Monte Carlo (MC) algorithm is presented for studying the lattice gas model (LGM) of multiple protein sequence alignment, which coherently combines long-range interactions and variable-length insertions. MC simulations are used for both parameter optimization of the model and production runs to explore the sequence subspace around a given protein family. In this Note, I describe the details of the MC algorithm as well as some preliminary results of MC simulations with various temperatures and chemical potentials, and compare them with the mean-field approximation. The existence of a two-state transition in the sequence space is suggested for the SH3 domain family, and inappropriateness of the mean-field approximation for the LGM is demonstrated.
Gelß, Patrick; Matera, Sebastian; Schütte, Christof
2016-06-01
In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO2(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.
Energy Technology Data Exchange (ETDEWEB)
Gelß, Patrick, E-mail: p.gelss@fu-berlin.de; Matera, Sebastian, E-mail: matera@math.fu-berlin.de; Schütte, Christof, E-mail: schuette@mi.fu-berlin.de
2016-06-01
In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO{sub 2}(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.
The SGHWR version of the Monte Carlo code W-MONTE. Part 1. The theoretical model
International Nuclear Information System (INIS)
Allen, F.R.
1976-03-01
W-MONTE provides a multi-group model of neutron transport in the exact geometry of a reactor lattice using Monte Carlo methods. It is currently restricted to uniform axial properties. Material data is normally obtained from a preliminary WIMS lattice calculation in the transport group structure. The SGHWR version has been required for analysis of zero energy experiments and special aspects of power reactor lattices, such as the unmoderated lattice region above the moderator when drained to dump height. Neutron transport is modelled for a uniform infinite lattice, simultaneously treating the cases of no leakage, radial leakage or axial leakage only, and the combined effects of radial and axial leakage. Multigroup neutron balance edits are incorporated for the separate effects of radial and axial leakage to facilitate the analysis of leakage and to provide effective diffusion theory parameters for core representation in reactor cores. (author)
Huang, Guanghui; Wan, Jianping; Chen, Hui
2013-02-01
Nonlinear stochastic differential equation models with unobservable state variables are now widely used in analysis of PK/PD data. Unobservable state variables are usually estimated with extended Kalman filter (EKF), and the unknown pharmacokinetic parameters are usually estimated by maximum likelihood estimator. However, EKF is inadequate for nonlinear PK/PD models, and MLE is known to be biased downwards. A density-based Monte Carlo filter (DMF) is proposed to estimate the unobservable state variables, and a simulation-based M estimator is proposed to estimate the unknown parameters in this paper, where a genetic algorithm is designed to search the optimal values of pharmacokinetic parameters. The performances of EKF and DMF are compared through simulations for discrete time and continuous time systems respectively, and it is found that the results based on DMF are more accurate than those given by EKF with respect to mean absolute error. Copyright © 2012 Elsevier Ltd. All rights reserved.
Dore, C.; Murphy, M.
2013-02-01
This paper outlines a new approach for generating digital heritage models from laser scan or photogrammetric data using Historic Building Information Modelling (HBIM). HBIM is a plug-in for Building Information Modelling (BIM) software that uses parametric library objects and procedural modelling techniques to automate the modelling stage. The HBIM process involves a reverse engineering solution whereby parametric interactive objects representing architectural elements are mapped onto laser scan or photogrammetric survey data. A library of parametric architectural objects has been designed from historic manuscripts and architectural pattern books. These parametric objects were built using an embedded programming language within the ArchiCAD BIM software called Geometric Description Language (GDL). Procedural modelling techniques have been implemented with the same language to create a parametric building façade which automatically combines library objects based on architectural rules and proportions. Different configurations of the façade are controlled by user parameter adjustment. The automatically positioned elements of the façade can be subsequently refined using graphical editing while overlaying the model with orthographic imagery. Along with this semi-automatic method for generating façade models, manual plotting of library objects can also be used to generate a BIM model from survey data. After the 3D model has been completed conservation documents such as plans, sections, elevations and 3D views can be automatically generated for conservation projects.
Directory of Open Access Journals (Sweden)
Mauricio Arriagada-Benítez
2017-10-01
Full Text Available Configurable process models are frequently used to represent business workflows and other discrete event systems among different branches of large organizations: they unify commonalities shared by all branches and describe their differences, at the same time. The configuration of such models is usually done manually, which is challenging. On the one hand, when the number of configurable nodes in the configurable process model grows, the size of the search space increases exponentially. On the other hand, the person performing the configuration may lack the holistic perspective to make the right choice for all configurable nodes at the same time, since choices influence each other. Nowadays, information systems that support the execution of business processes create event data reflecting how processes are performed. In this article, we propose three strategies (based on exhaustive search, genetic algorithms and a greedy heuristic that use event data to automatically derive a process model from a configurable process model that better represents the characteristics of the process in a specific branch. These strategies have been implemented in our proposed framework and tested in both business-like event logs as recorded in a higher educational enterprise resource planning system and a real case scenario involving a set of Dutch municipalities.
Guerra, J. G.; Rubiano, J. G.; Winter, G.; Guerra, A. G.; Alonso, H.; Arnedo, M. A.; Tejera, A.; Mosqueda, F.; Martel, P.; Bolivar, J. P.
2018-02-01
The aim of this paper is to characterize two HPGe gamma-ray detectors used in two different laboratories for environmental radioactivity measurements, so as to perform efficiency calibrations by means of Monte Carlo Simulation. To achieve such an aim, methodologies developed in previous papers have been applied, based on the automatic optimization of the model of detector, so that the differences between computational and reference FEPEs are minimized. In this work, such reference FEPEs have been obtained experimentally from several measurements of the IAEA RGU-1 reference material for specific source-detector arrangements. The models of both detectors built through these methodologies have been validated by comparing with experimental results for several reference materials and different measurement geometries, showing deviations below 10% in most cases.
International Nuclear Information System (INIS)
Stute, Simon
2010-01-01
Positron Emission Tomography (PET) is a medical imaging technique that plays a major role in oncology, especially using "1"8F-Fluoro-Deoxyglucose. However, PET images suffer from a modest spatial resolution and from high noise. As a result, there is still no consensus on how tumor metabolically active volume and tumor uptake should be characterized. In the meantime, research groups keep producing new methods for such characterizations that need to be assessed. A Monte Carlo simulation based method has been developed to produce simulated PET images of patients suffering from cancer, indistinguishable from clinical images, and for which all parameters are known. The method uses high resolution PET images from patient acquisitions, from which the physiological heterogeneous activity distribution can be modeled. It was shown that the performance of quantification methods on such highly realistic simulated images are significantly lower and more variable than using simple phantom studies. Fourteen different quantification methods were also compared in realistic conditions using a group of such simulated patients. In addition, the proposed method was extended to simulate serial PET scans in the context of patient monitoring, including a modeling of the tumor changes, as well as the variability over time of non-tumoral physiological activity distribution. Monte Carlo simulations were also used to study the detection probability inside the crystals of the tomograph. A model of the crystal response was derived and included in the system matrix involved in tomographic reconstruction. The resulting reconstruction method was compared with other sophisticated methods for modeling the detector response in the image space, proposed in the literature. We demonstrated the superiority of the proposed method over equivalent approaches on simulated data, and illustrated its robustness on clinical data. For a same noise level, it is possible to reconstruct PET images offering a
Model-Driven Engineering: Automatic Code Generation and Beyond
2015-03-01
herein to any specific commercial product, process, or service by trade name, trade mark, manufacturer , or otherwise, does not necessarily constitute or...export of an Extensible Markup Language (XML) representation of the model. The XML Metadata Interchange (XMI) is an OMG standard for representing...overall company financial results for the past 3 years. What financial re- sults are you projecting for the next year? 1.2.5.2 Percentage of Gross
International Nuclear Information System (INIS)
Serfontein, Dawid E.; Mulder, Eben J.; Reitsma, Frederik
2014-01-01
A computer code was developed for the semi-automatic translation of input models for the VSOP-A diffusion neutronics simulation code to the format of the newer VSOP 99/05 code. In this paper, this algorithm is presented as a generic method for producing codes for the automatic translation of input models from the format of one code version to another, or even to that of a completely different code. Normally, such translations are done manually. However, input model files, such as for the VSOP codes, often are very large and may consist of many thousands of numeric entries that make no particular sense to the human eye. Therefore the task, of for instance nuclear regulators, to verify the accuracy of such translated files can be very difficult and cumbersome. This may cause translation errors not to be picked up, which may have disastrous consequences later on when a reactor with such a faulty design is built. Therefore a generic algorithm for producing such automatic translation codes may ease the translation and verification process to a great extent. It will also remove human error from the process, which may significantly enhance the accuracy and reliability of the process. The developed algorithm also automatically creates a verification log file which permanently record the names and values of each variable used, as well as the list of meanings of all the possible values. This should greatly facilitate reactor licensing applications
Energy Technology Data Exchange (ETDEWEB)
Serfontein, Dawid E., E-mail: Dawid.Serfontein@nwu.ac.za [School of Mechanical and Nuclear Engineering, North West University (PUK-Campus), PRIVATE BAG X6001 (Internal Post Box 360), Potchefstroom 2520 (South Africa); Mulder, Eben J. [School of Mechanical and Nuclear Engineering, North West University (South Africa); Reitsma, Frederik [Calvera Consultants (South Africa)
2014-05-01
A computer code was developed for the semi-automatic translation of input models for the VSOP-A diffusion neutronics simulation code to the format of the newer VSOP 99/05 code. In this paper, this algorithm is presented as a generic method for producing codes for the automatic translation of input models from the format of one code version to another, or even to that of a completely different code. Normally, such translations are done manually. However, input model files, such as for the VSOP codes, often are very large and may consist of many thousands of numeric entries that make no particular sense to the human eye. Therefore the task, of for instance nuclear regulators, to verify the accuracy of such translated files can be very difficult and cumbersome. This may cause translation errors not to be picked up, which may have disastrous consequences later on when a reactor with such a faulty design is built. Therefore a generic algorithm for producing such automatic translation codes may ease the translation and verification process to a great extent. It will also remove human error from the process, which may significantly enhance the accuracy and reliability of the process. The developed algorithm also automatically creates a verification log file which permanently record the names and values of each variable used, as well as the list of meanings of all the possible values. This should greatly facilitate reactor licensing applications.
International Nuclear Information System (INIS)
Caon, M.
2010-01-01
Full text: Medical imaging provides two-dimensional pictures of the human internal anatomy from which may be constructed a three-dimensional model of organs and tissues suitable for calculation of dose from radiation. Diagnostic CT provides the greatest exposure to radiation per examination and the frequency of CT examination is high. Esti mates of dose from diagnostic radiography are still determined from data derived from geometric models (rather than anatomical models), models scaled from adult bodies (rather than bodies of children) and CT scanner hardware that is no longer used. The aim of anatomical modelling is to produce a mathematical representation of internal anatomy that has organs of realistic size, shape and positioning. The organs and tissues are represented by a great many cuboidal volumes (voxels). The conversion of medical images to voxels is called segmentation and on completion every pixel in an image is assigned to a tissue or organ. Segmentation is time consuming. An image processing pack age is used to identify organ boundaries in each image. Thirty to forty tomographic voxel models of anatomy have been reported in the literature. Each model is of an individual, or a composite from several individuals. Images of children are particularly scarce. So there remains a need for more paediatric anatomical models. I am working on segmenting ''William'' who is 368 PET-CT images from head to toe of a seven year old boy. William will be used for Monte Carlo dose calculations of dose from CT examination using a simulated modern CT scanner.
Lu, Dan; Ricciuto, Daniel; Walker, Anthony; Safta, Cosmin; Munger, William
2017-09-01
Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.
Automatic generation of computable implementation guides from clinical information models.
Boscá, Diego; Maldonado, José Alberto; Moner, David; Robles, Montserrat
2015-06-01
Clinical information models are increasingly used to describe the contents of Electronic Health Records. Implementation guides are a common specification mechanism used to define such models. They contain, among other reference materials, all the constraints and rules that clinical information must obey. However, these implementation guides typically are oriented to human-readability, and thus cannot be processed by computers. As a consequence, they must be reinterpreted and transformed manually into an executable language such as Schematron or Object Constraint Language (OCL). This task can be difficult and error prone due to the big gap between both representations. The challenge is to develop a methodology for the specification of implementation guides in such a way that humans can read and understand easily and at the same time can be processed by computers. In this paper, we propose and describe a novel methodology that uses archetypes as basis for generation of implementation guides. We use archetypes to generate formal rules expressed in Natural Rule Language (NRL) and other reference materials usually included in implementation guides such as sample XML instances. We also generate Schematron rules from NRL rules to be used for the validation of data instances. We have implemented these methods in LinkEHR, an archetype editing platform, and exemplify our approach by generating NRL rules and implementation guides from EN ISO 13606, openEHR, and HL7 CDA archetypes. Copyright © 2015 Elsevier Inc. All rights reserved.
Component simulation in problems of calculated model formation of automatic machine mechanisms
Directory of Open Access Journals (Sweden)
Telegin Igor
2017-01-01
Full Text Available The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gaps in kinematic pairs, friction forces, design and technological loads. As an example in the paper there are considered a formalization of stages in the computer model formation of the cutting mechanism in cold stamping automatic machine AV1818 and methods of for the computation of their parameters on the basis of its solid-state model.
Implementation of 3D models in the Monte Carlo code MCNP
International Nuclear Information System (INIS)
Lopes, Vivaldo; Millian, Felix M.; Guevara, Maria Victoria M.; Garcia, Fermin; Sena, Isaac; Menezes, Hugo
2009-01-01
On the area of numerical dosimetry Applied to medical physics, the scientific community focuses on the elaboration of new hybrids models based on 3D models. But different steps of the process of simulation with 3D models needed improvement and optimization in order to expedite the calculations and accuracy using this methodology. This project was developed with the aim of optimize the process of introduction of 3D models within the simulation code of radiation transport by Monte Carlo (MCNP). The fast implementation of these models on the simulation code allows the estimation of the dose deposited on the patient organs on a more personalized way, increasing the accuracy with this on the estimates and reducing the risks to health, caused by ionizing radiations. The introduction o these models within the MCNP was made through a input file, that was constructed through a sequence of images, bi-dimensional in the 3D model, generated using the program '3DSMAX', imported by the program 'TOMO M C' and thus, introduced as INPUT FILE of the MCNP code. (author)
Hong-Ghi Min
2011-01-01
Using Monte Carlo simulation of the Portfolio-balance model of the exchange rates, we report finite sample properties of the GMM estimator for testing over-identifying restrictions in the simultaneous equations model. F-form of Sargans statistic performs better than its chi-squared form while Hansens GMM statistic has the smallest bias.
Kieftenbeld, Vincent; Natesan, Prathiba
2012-01-01
Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…
International Nuclear Information System (INIS)
Severin, V.P.
2007-01-01
The mathematical modeling of automatic control systems of reactor facility WWER-1000 with various regulator types is considered. The linear and nonlinear models of neutron power control systems of nuclear reactor WWER-1000 with various group numbers of delayed neutrons are designed. The results of optimization of direct quality indexes of neutron power control systems of nuclear reactor WWER-1000 are designed. The identification and optimization of level control systems with various regulator types of steam generator are executed
Modelling the adoption of automatic milking systems in Noord-Holland
Matteo Floridi; Fabio Bartolini; Jack Peerlings; Nico Polman; Davide Viaggi
2013-01-01
Innovation and new technology adoption represent two central elements for the business and industry development process in agriculture. One of the most relevant innovations in dairy farms is the robotisation of the milking process through the adoption of Automatic Milking Systems (AMS). The purpose of this paper is to assess the impact of selected Common Agricultural Policy measures on the adoption of AMS in dairy farms. The model developed is a dynamic farm-household model that is able to si...
Nakano, Masaru; Kubota, Fumiko; Inamori, Yutaka; Mitsuyuki, Keiji
Manufacturing system designers should concentrate on designing and planning manufacturing systems instead of spending their efforts on creating the simulation models to verify the design. This paper proposes a method and its tool to navigate the designers through the engineering process and generate the simulation model automatically from the design results. The design agent also supports collaborative design projects among different companies or divisions with distributed engineering and distributed simulation techniques. The idea was implemented and applied to a factory planning process.
Component simulation in problems of calculated model formation of automatic machine mechanisms
Telegin Igor; Kozlov Alexander; Zhirkov Alexander
2017-01-01
The paper deals with the problems of the component simulation method application in the problems of the automation of the mechanical system model formation with the further possibility of their CAD-realization. The purpose of the investigations mentioned consists in the automation of the CAD-model formation of high-speed mechanisms in automatic machines and in the analysis of dynamic processes occurred in their units taking into account their elasto-inertial properties, power dissipation, gap...
Automatic Conversion of a Conceptual Model to a Standard Multi-view Web Services Definition
Directory of Open Access Journals (Sweden)
Anass Misbah
2018-03-01
Full Text Available Information systems are becoming more and more heterogeneous and here comes the need to have more generic transformation algorithms and more automatic generation Meta rules. In fact, the large number of terminals, devices, operating systems, platforms and environments require a high level of adaptation. Therefore, it is becoming more and more difficult to validate, generate and implement manually models, designs and codes.Web services are one of the technologies that are used massively nowadays; hence, it is considered as one of technologies that require the most automatic rules of validation and automation. Many previous works have dealt with Web services by proposing new concepts such as Multi-view Web services, standard WSDL implementation of Multi-view Web services and even further Generic Meta rules for automatic generation of Multi-view Web services.In this work we will propose a new way of generating Multi-view Web ser-vices, which is based on an engine algorithm that takes as input both an initial Conceptual Model and user’s matrix and then unroll a generic algorithm to gen-erate dynamically a validated set of points of view. This set of points of view will be transformed to a standard WSDL implementation of Multi-view Web services by means of the automatic transformation Meta rules.
Zeng, Xueqiang; Luo, Gang
2017-12-01
Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.
International Nuclear Information System (INIS)
Paul P.H. Wilson
2005-01-01
The development of Monte Carlo techniques for isotopic inventory analysis has been explored in order to facilitate the modeling of systems with flowing streams of material through varying neutron irradiation environments. This represents a novel application of Monte Carlo methods to a field that has traditionally relied on deterministic solutions to systems of first-order differential equations. The Monte Carlo techniques were based largely on the known modeling techniques of Monte Carlo radiation transport, but with important differences, particularly in the area of variance reduction and efficiency measurement. The software that was developed to implement and test these methods now provides a basis for validating approximate modeling techniques that are available to deterministic methodologies. The Monte Carlo methods have been shown to be effective in reproducing the solutions of simple problems that are possible using both stochastic and deterministic methods. The Monte Carlo methods are also effective for tracking flows of materials through complex systems including the ability to model removal of individual elements or isotopes in the system. Computational performance is best for flows that have characteristic times that are large fractions of the system lifetime. As the characteristic times become short, leading to thousands or millions of passes through the system, the computational performance drops significantly. Further research is underway to determine modeling techniques to improve performance within this range of problems. This report describes the technical development of Monte Carlo techniques for isotopic inventory analysis. The primary motivation for this solution methodology is the ability to model systems of flowing material being exposed to varying and stochastically varying radiation environments. The methodology was developed in three stages: analog methods which model each atom with true reaction probabilities (Section 2), non-analog methods
ICF target 2D modeling using Monte Carlo SNB electron thermal transport in DRACO
Chenhall, Jeffrey; Cao, Duc; Moses, Gregory
2016-10-01
The iSNB (implicit Schurtz Nicolai Busquet multigroup diffusion electron thermal transport method is adapted into a Monte Carlo (MC) transport method to better model angular and long mean free path non-local effects. The MC model was first implemented in the 1D LILAC code to verify consistency with the iSNB model. Implementation of the MC SNB model in the 2D DRACO code enables higher fidelity non-local thermal transport modeling in 2D implosions such as polar drive experiments on NIF. The final step is to optimize the MC model by hybridizing it with a MC version of the iSNB diffusion method. The hybrid method will combine the efficiency of a diffusion method in intermediate mean free path regions with the accuracy of a transport method in long mean free path regions allowing for improved computational efficiency while maintaining accuracy. Work to date on the method will be presented. This work was supported by Sandia National Laboratories and the Univ. of Rochester Laboratory for Laser Energetics.
Dynamic connectivity algorithms for Monte Carlo simulations of the random-cluster model
International Nuclear Information System (INIS)
Elçi, Eren Metin; Weigel, Martin
2014-01-01
We review Sweeny's algorithm for Monte Carlo simulations of the random cluster model. Straightforward implementations suffer from the problem of computational critical slowing down, where the computational effort per edge operation scales with a power of the system size. By using a tailored dynamic connectivity algorithm we are able to perform all operations with a poly-logarithmic computational effort. This approach is shown to be efficient in keeping online connectivity information and is of use for a number of applications also beyond cluster-update simulations, for instance in monitoring droplet shape transitions. As the handling of the relevant data structures is non-trivial, we provide a Python module with a full implementation for future reference.
3D Monte Carlo model with direct photon flux recording for optimal optogenetic light delivery
Shin, Younghoon; Kim, Dongmok; Lee, Jihoon; Kwon, Hyuk-Sang
2017-02-01
Configuring the light power emitted from the optical fiber is an essential first step in planning in-vivo optogenetic experiments. However, diffusion theory, which was adopted for optogenetic research, precluded accurate estimates of light intensity in the semi-diffusive region where the primary locus of the stimulation is located. We present a 3D Monte Carlo model that provides an accurate and direct solution for light distribution in this region. Our method directly records the photon trajectory in the separate volumetric grid planes for the near-source recording efficiency gain, and it incorporates a 3D brain mesh to support both homogeneous and heterogeneous brain tissue. We investigated the light emitted from optical fibers in brain tissue in 3D, and we applied the results to design optimal light delivery parameters for precise optogenetic manipulation by considering the fiber output power, wavelength, fiber-to-target distance, and the area of neural tissue activation.
Constrained-path quantum Monte Carlo approach for non-yrast states within the shell model
Energy Technology Data Exchange (ETDEWEB)
Bonnard, J. [INFN, Sezione di Padova, Padova (Italy); LPC Caen, ENSICAEN, Universite de Caen, CNRS/IN2P3, Caen (France); Juillet, O. [LPC Caen, ENSICAEN, Universite de Caen, CNRS/IN2P3, Caen (France)
2016-04-15
The present paper intends to present an extension of the constrained-path quantum Monte Carlo approach allowing to reconstruct non-yrast states in order to reach the complete spectroscopy of nuclei within the interacting shell model. As in the yrast case studied in a previous work, the formalism involves a variational symmetry-restored wave function assuming two central roles. First, it guides the underlying Brownian motion to improve the efficiency of the sampling. Second, it constrains the stochastic paths according to the phaseless approximation to control sign or phase problems that usually plague fermionic QMC simulations. Proof-of-principle results in the sd valence space are reported. They prove the ability of the scheme to offer remarkably accurate binding energies for both even- and odd-mass nuclei irrespective of the considered interaction. (orig.)
CERN. Geneva
2012-01-01
We present our effort for the creation of a new software library of geometrical primitives, which are used for solid modelling in Monte Carlo detector simulations. We plan to replace and unify current geometrical primitive classes in the CERN software projects Geant4 and ROOT with this library. Each solid is represented by a C++ class with methods suited for measuring distances of particles from the surface of a solid and for determination as to whether the particles are located inside, outside or on the surface of the solid. We use numerical tolerance for determining whether the particles are located on the surface. The class methods also contain basic support for visualization. We use dedicated test suites for validation of the shape codes. These include also special performance and numerical value comparison tests for help with analysis of possible candidates of class methods as well as to verify that our new implementation proposals were designed and implemented properly. Currently, bridge classes are u...
Monte Carlo based geometrical model for efficiency calculation of an n-type HPGe detector
Energy Technology Data Exchange (ETDEWEB)
Padilla Cabal, Fatima, E-mail: fpadilla@instec.c [Instituto Superior de Tecnologias y Ciencias Aplicadas, ' Quinta de los Molinos' Ave. Salvador Allende, esq. Luaces, Plaza de la Revolucion, Ciudad de la Habana, CP 10400 (Cuba); Lopez-Pino, Neivy; Luis Bernal-Castillo, Jose; Martinez-Palenzuela, Yisel; Aguilar-Mena, Jimmy; D' Alessandro, Katia; Arbelo, Yuniesky; Corrales, Yasser; Diaz, Oscar [Instituto Superior de Tecnologias y Ciencias Aplicadas, ' Quinta de los Molinos' Ave. Salvador Allende, esq. Luaces, Plaza de la Revolucion, Ciudad de la Habana, CP 10400 (Cuba)
2010-12-15
A procedure to optimize the geometrical model of an n-type detector is described. Sixteen lines from seven point sources ({sup 241}Am, {sup 133}Ba, {sup 22}Na, {sup 60}Co, {sup 57}Co, {sup 137}Cs and {sup 152}Eu) placed at three different source-to-detector distances (10, 20 and 30 cm) were used to calibrate a low-background gamma spectrometer between 26 and 1408 keV. Direct Monte Carlo techniques using the MCNPX 2.6 and GEANT 4 9.2 codes, and a semi-empirical procedure were performed to obtain theoretical efficiency curves. Since discrepancies were found between experimental and calculated data using the manufacturer parameters of the detector, a detail study of the crystal dimensions and the geometrical configuration is carried out. The relative deviation with experimental data decreases from a mean value of 18-4%, after the parameters were optimized.
Monte Carlo evidence for the gluon-chain model of QCD string formation
International Nuclear Information System (INIS)
Greensite, J.; San Francisco State Univ., CA
1988-08-01
The Monte Carlo method is used to calculate the overlaps string vertical stroken gluons>, where Ψ string [A] is the Yang-Mills wavefunctional due to a static quark-antiquark pair, and vertical stroken gluons > are orthogonal trial states containing n=0, 1, or 2 gluon operators multiplying the true ground state. The calculation is carried out for SU(2) lattice gauge theory in Coulomb gauge, in D=4 dimensions. It is found that the string state is dominated, at small qanti q separations, by the vacuum ('no-gluon') state, at larger separations by the 1-gluon state, and, at the largest separations attempted, the 2-gluon state begins to dominate. This behavior is in qualitative agreement with the gluon-chain model, which is a large-N colors motivated theory of QCD string formation. (orig.)
Calibration of lung counter using a CT model of Torso phantom and Monte Carlo method
International Nuclear Information System (INIS)
Zhang Binquan; Ma Jizeng; Yang Duanjie; Liu Liye; Cheng Jianping
2006-01-01
Tomography image of a Torso phantom was obtained from CT-Scan. The Torso phantom represents the trunk of an adult man that is 170 cm high and weight of 65 kg. After these images were segmented, cropped, and resized, a 3-dimension voxel phantom was created. The voxel phantom includes more than 2 million voxels, which size was 2.73 mm x 2.73 mm x 3 mm. This model could be used for the calibration of lung counter with Monte Carlo method. On the assumption that radioactive material was homogeneously distributed throughout the lung, counting efficiencies of a HPGe detector in different positions were calculated as Adipose Mass fraction (AMF) was different in the soft tissue in chest. The results showed that counting efficiencies of the lung counter changed up to 67% for 17.5 keV γ ray and 20% for 25 keV γ ray when AMF changed from 0 to 40%. (authors)
DEFF Research Database (Denmark)
Wang, Kemin; Jiang, Zhengtao; Wang, Yongbin
2012-01-01
, whenever the number of node-n and related parameters vary, we can create the PRISM model file rapidly and then we can use PRISM model checker to verify ralated system properties. At the end of this study, we analyzed and verified the availability distributions of the Distributed Cluster Rendering System......In this study, we proposed a Continuous Time Markov Chain Model towards the availability of n-node clusters of Distributed Rendering System. It's an infinite one, we formalized it, based on the model, we implemented a software, which can automatically model with PRISM language. With the tool...
The ACR-program for automatic finite element model generation for part through cracks
International Nuclear Information System (INIS)
Leinonen, M.S.; Mikkola, T.P.J.
1989-01-01
The ACR-program (Automatic Finite Element Model Generation for Part Through Cracks) has been developed at the Technical Research Centre of Finland (VTT) for automatic finite element model generation for surface flaws using three dimensional solid elements. Circumferential or axial cracks can be generated on the inner or outer surface of a cylindrical or toroidal geometry. Several crack forms are available including the standard semi-elliptical surface crack. The program can be used in the development of automated systems for fracture mechanical analyses of structures. The tests for the accuracy of the FE-mesh have been started with two-dimensional models. The results indicate that the accuracy of the standard mesh is sufficient for practical analyses. Refinement of the standard mesh is needed in analyses with high load levels well over the limit load of the structure
Energy Technology Data Exchange (ETDEWEB)
Yoon, Jihyung; Jung, Jae Won, E-mail: jungj@ecu.edu [Department of Physics, East Carolina University, Greenville, North Carolina 27858 (United States); Kim, Jong Oh [Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania 15232 (United States); Yeo, Inhwan [Department of Radiation Medicine, Loma Linda University Medical Center, Loma Linda, California 92354 (United States)
2016-05-15
Purpose: To develop and evaluate a fast Monte Carlo (MC) dose calculation model of electronic portal imaging device (EPID) based on its effective atomic number modeling in the XVMC code. Methods: A previously developed EPID model, based on the XVMC code by density scaling of EPID structures, was modified by additionally considering effective atomic number (Z{sub eff}) of each structure and adopting a phase space file from the EGSnrc code. The model was tested under various homogeneous and heterogeneous phantoms and field sizes by comparing the calculations in the model with measurements in EPID. In order to better evaluate the model, the performance of the XVMC code was separately tested by comparing calculated dose to water with ion chamber (IC) array measurement in the plane of EPID. Results: In the EPID plane, calculated dose to water by the code showed agreement with IC measurements within 1.8%. The difference was averaged across the in-field regions of the acquired profiles for all field sizes and phantoms. The maximum point difference was 2.8%, affected by proximity of the maximum points to penumbra and MC noise. The EPID model showed agreement with measured EPID images within 1.3%. The maximum point difference was 1.9%. The difference dropped from the higher value of the code by employing the calibration that is dependent on field sizes and thicknesses for the conversion of calculated images to measured images. Thanks to the Z{sub eff} correction, the EPID model showed a linear trend of the calibration factors unlike those of the density-only-scaled model. The phase space file from the EGSnrc code sharpened penumbra profiles significantly, improving agreement of calculated profiles with measured profiles. Conclusions: Demonstrating high accuracy, the EPID model with the associated calibration system may be used for in vivo dosimetry of radiation therapy. Through this study, a MC model of EPID has been developed, and their performance has been rigorously
Automatic mesh adaptivity for CADIS and FW-CADIS neutronics modeling of difficult shielding problems
International Nuclear Information System (INIS)
Ibrahim, A. M.; Peplow, D. E.; Mosher, S. W.; Wagner, J. C.; Evans, T. M.; Wilson, P. P.; Sawan, M. E.
2013-01-01
The CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques dramatically increase the efficiency of neutronics modeling, but their use in the accurate design analysis of very large and geometrically complex nuclear systems has been limited by the large number of processors and memory requirements for their preliminary deterministic calculations and final Monte Carlo calculation. Three mesh adaptivity algorithms were developed to reduce the memory requirements of CADIS and FW-CADIS without sacrificing their efficiency improvement. First, a macro-material approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as much geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm de-couples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility. Using these algorithms resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation and, additionally, increased the efficiency of the Monte Carlo simulation by a factor of at least 3.4. The three algorithms enabled this difficult calculation to be accurately solved using an FW-CADIS simulation on a regular computer cluster, obviating the need for a world-class super computer. (authors)
Faught, Austin M; Davidson, Scott E; Fontenot, Jonas; Kry, Stephen F; Etzel, Carol; Ibbott, Geoffrey S; Followill, David S
2017-09-01
The Imaging and Radiation Oncology Core Houston (IROC-H) (formerly the Radiological Physics Center) has reported varying levels of agreement in their anthropomorphic phantom audits. There is reason to believe one source of error in this observed disagreement is the accuracy of the dose calculation algorithms and heterogeneity corrections used. To audit this component of the radiotherapy treatment process, an independent dose calculation tool is needed. Monte Carlo multiple source models for Elekta 6 MV and 10 MV therapeutic x-ray beams were commissioned based on measurement of central axis depth dose data for a 10 × 10 cm 2 field size and dose profiles for a 40 × 40 cm 2 field size. The models were validated against open field measurements consisting of depth dose data and dose profiles for field sizes ranging from 3 × 3 cm 2 to 30 × 30 cm 2 . The models were then benchmarked against measurements in IROC-H's anthropomorphic head and neck and lung phantoms. Validation results showed 97.9% and 96.8% of depth dose data passed a ±2% Van Dyk criterion for 6 MV and 10 MV models respectively. Dose profile comparisons showed an average agreement using a ±2%/2 mm criterion of 98.0% and 99.0% for 6 MV and 10 MV models respectively. Phantom plan comparisons were evaluated using ±3%/2 mm gamma criterion, and averaged passing rates between Monte Carlo and measurements were 87.4% and 89.9% for 6 MV and 10 MV models respectively. Accurate multiple source models for Elekta 6 MV and 10 MV x-ray beams have been developed for inclusion in an independent dose calculation tool for use in clinical trial audits. © 2017 American Association of Physicists in Medicine.
Kadoura, Ahmad
2011-06-06
Lennard‐Jones (L‐J) and Buckingham exponential‐6 (exp‐6) potential models were used to produce isotherms for methane at temperatures below and above critical one. Molecular simulation approach, particularly Monte Carlo simulations, were employed to create these isotherms working with both canonical and Gibbs ensembles. Experiments in canonical ensemble with each model were conducted to estimate pressures at a range of temperatures above methane critical temperature. Results were collected and compared to experimental data existing in literature; both models showed an elegant agreement with the experimental data. In parallel, experiments below critical temperature were run in Gibbs ensemble using L‐J model only. Upon comparing results with experimental ones, a good fit was obtained with small deviations. The work was further developed by adding some statistical studies in order to achieve better understanding and interpretation to the estimated quantities by the simulation. Methane phase diagrams were successfully reproduced by an efficient molecular simulation technique with different potential models. This relatively simple demonstration shows how powerful molecular simulation methods could be, hence further applications on more complicated systems are considered. Prediction of phase behavior of elemental sulfur in sour natural gases has been an interesting and challenging field in oil and gas industry. Determination of elemental sulfur solubility conditions helps avoiding all kinds of problems caused by its dissolution in gas production and transportation processes. For this purpose, further enhancement to the methods used is to be considered in order to successfully simulate elemental sulfur phase behavior in sour natural gases mixtures.
Unified description of pf-shell nuclei by the Monte Carlo shell model calculations
Energy Technology Data Exchange (ETDEWEB)
Mizusaki, Takahiro; Otsuka, Takaharu [Tokyo Univ. (Japan). Dept. of Physics; Honma, Michio
1998-03-01
The attempts to solve shell model by new methods are briefed. The shell model calculation by quantum Monte Carlo diagonalization which was proposed by the authors is a more practical method, and it became to be known that it can solve the problem with sufficiently good accuracy. As to the treatment of angular momentum, in the method of the authors, deformed Slater determinant is used as the basis, therefore, for making angular momentum into the peculiar state, projected operator is used. The space determined dynamically is treated mainly stochastically, and the energy of the multibody by the basis formed as the result is evaluated and selectively adopted. The symmetry is discussed, and the method of decomposing shell model space into dynamically determined space and the product of spin and isospin spaces was devised. The calculation processes are shown with the example of {sup 50}Mn nuclei. The calculation of the level structure of {sup 48}Cr with known exact energy can be done with the accuracy of peculiar absolute energy value within 200 keV. {sup 56}Ni nuclei are the self-conjugate nuclei of Z=N=28. The results of the shell model calculation of {sup 56}Ni nucleus structure by using the interactions of nuclear models are reported. (K.I.)
Modeling a secular trend by Monte Carlo simulation of height biased migration in a spatial network.
Groth, Detlef
2017-04-01
Background: In a recent Monte Carlo simulation, the clustering of body height of Swiss military conscripts within a spatial network with characteristic features of the natural Swiss geography was investigated. In this study I examined the effect of migration of tall individuals into network hubs on the dynamics of body height within the whole spatial network. The aim of this study was to simulate height trends. Material and methods: Three networks were used for modeling, a regular rectangular fishing net like network, a real world example based on the geographic map of Switzerland, and a random network. All networks contained between 144 and 148 districts and between 265-307 road connections. Around 100,000 agents were initially released with average height of 170 cm, and height standard deviation of 6.5 cm. The simulation was started with the a priori assumption that height variation within a district is limited and also depends on height of neighboring districts (community effect on height). In addition to a neighborhood influence factor, which simulates a community effect, body height dependent migration of conscripts between adjacent districts in each Monte Carlo simulation was used to re-calculate next generation body heights. In order to determine the direction of migration for taller individuals, various centrality measures for the evaluation of district importance within the spatial network were applied. Taller individuals were favored to migrate more into network hubs, backward migration using the same number of individuals was random, not biased towards body height. Network hubs were defined by the importance of a district within the spatial network. The importance of a district was evaluated by various centrality measures. In the null model there were no road connections, height information could not be delivered between the districts. Results: Due to the favored migration of tall individuals into network hubs, average body height of the hubs, and later
Development of a randomized 3D cell model for Monte Carlo microdosimetry simulations
Energy Technology Data Exchange (ETDEWEB)
Douglass, Michael; Bezak, Eva; Penfold, Scott [School of Chemistry and Physics, University of Adelaide, North Terrace, Adelaide 5005, South Australia (Australia) and Department of Medical Physics, Royal Adelaide Hospital, North Terrace, Adelaide 5000, South Australia (Australia)
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.
A Monte Carlo risk assessment model for acrylamide formation in French fries.
Cummins, Enda; Butler, Francis; Gormley, Ronan; Brunton, Nigel
2009-10-01
The objective of this study is to estimate the likely human exposure to the group 2a carcinogen, acrylamide, from French fries by Irish consumers by developing a quantitative risk assessment model using Monte Carlo simulation techniques. Various stages in the French-fry-making process were modeled from initial potato harvest, storage, and processing procedures. The model was developed in Microsoft Excel with the @Risk add-on package. The model was run for 10,000 iterations using Latin hypercube sampling. The simulated mean acrylamide level in French fries was calculated to be 317 microg/kg. It was found that females are exposed to smaller levels of acrylamide than males (mean exposure of 0.20 microg/kg bw/day and 0.27 microg/kg bw/day, respectively). Although the carcinogenic potency of acrylamide is not well known, the simulated probability of exceeding the average chronic human dietary intake of 1 microg/kg bw/day (as suggested by WHO) was 0.054 and 0.029 for males and females, respectively. A sensitivity analysis highlighted the importance of the selection of appropriate cultivars with known low reducing sugar levels for French fry production. Strict control of cooking conditions (correlation coefficient of 0.42 and 0.35 for frying time and temperature, respectively) and blanching procedures (correlation coefficient -0.25) were also found to be important in ensuring minimal acrylamide formation.
Parsons, Neal; Levin, Deborah A; van Duin, Adri C T; Zhu, Tong
2014-12-21
The Direct Simulation Monte Carlo (DSMC) method typically used for simulating hypersonic Earth re-entry flows requires accurate total collision cross sections and reaction probabilities. However, total cross sections are often determined from extrapolations of relatively low-temperature viscosity data, so their reliability is unknown for the high temperatures observed in hypersonic flows. Existing DSMC reaction models accurately reproduce experimental equilibrium reaction rates, but the applicability of these rates to the strong thermal nonequilibrium observed in hypersonic shocks is unknown. For hypersonic flows, these modeling issues are particularly relevant for nitrogen, the dominant species of air. To rectify this deficiency, the Molecular Dynamics/Quasi-Classical Trajectories (MD/QCT) method is used to accurately compute collision and reaction cross sections for the N2(Σg+1)-N2(Σg+1) collision pair for conditions expected in hypersonic shocks using a new potential energy surface developed using a ReaxFF fit to recent advanced ab initio calculations. The MD/QCT-computed reaction probabilities were found to exhibit better physical behavior and predict less dissociation than the baseline total collision energy reaction model for strong nonequilibrium conditions expected in a shock. The MD/QCT reaction model compared well with computed equilibrium reaction rates and shock-tube data. In addition, the MD/QCT-computed total cross sections were found to agree well with established variable hard sphere total cross sections.
International Nuclear Information System (INIS)
Parsons, Neal; Levin, Deborah A.; Duin, Adri C. T. van; Zhu, Tong
2014-01-01
The Direct Simulation Monte Carlo (DSMC) method typically used for simulating hypersonic Earth re-entry flows requires accurate total collision cross sections and reaction probabilities. However, total cross sections are often determined from extrapolations of relatively low-temperature viscosity data, so their reliability is unknown for the high temperatures observed in hypersonic flows. Existing DSMC reaction models accurately reproduce experimental equilibrium reaction rates, but the applicability of these rates to the strong thermal nonequilibrium observed in hypersonic shocks is unknown. For hypersonic flows, these modeling issues are particularly relevant for nitrogen, the dominant species of air. To rectify this deficiency, the Molecular Dynamics/Quasi-Classical Trajectories (MD/QCT) method is used to accurately compute collision and reaction cross sections for the N 2 ( 1 Σ g + )-N 2 ( 1 Σ g + ) collision pair for conditions expected in hypersonic shocks using a new potential energy surface developed using a ReaxFF fit to recent advanced ab initio calculations. The MD/QCT-computed reaction probabilities were found to exhibit better physical behavior and predict less dissociation than the baseline total collision energy reaction model for strong nonequilibrium conditions expected in a shock. The MD/QCT reaction model compared well with computed equilibrium reaction rates and shock-tube data. In addition, the MD/QCT-computed total cross sections were found to agree well with established variable hard sphere total cross sections
Monte Carlo modeling of a conventional X-ray computed tomography scanner for gel dosimetry purposes.
Hayati, Homa; Mesbahi, Asghar; Nazarpoor, Mahmood
2016-01-01
Our purpose in the current study was to model an X-ray CT scanner with the Monte Carlo (MC) method for gel dosimetry. In this study, a conventional CT scanner with one array detector was modeled with use of the MCNPX MC code. The MC calculated photon fluence in detector arrays was used for image reconstruction of a simple water phantom as well as polyacrylamide polymer gel (PAG) used for radiation therapy. Image reconstruction was performed with the filtered back-projection method with a Hann filter and the Spline interpolation method. Using MC results, we obtained the dose-response curve for images of irradiated gel at different absorbed doses. A spatial resolution of about 2 mm was found for our simulated MC model. The MC-based CT images of the PAG gel showed a reliable increase in the CT number with increasing absorbed dose for the studied gel. Also, our results showed that the current MC model of a CT scanner can be used for further studies on the parameters that influence the usability and reliability of results, such as the photon energy spectra and exposure techniques in X-ray CT gel dosimetry.
Assessing the convergence of LHS Monte Carlo simulations of wastewater treatment models.
Benedetti, Lorenzo; Claeys, Filip; Nopens, Ingmar; Vanrolleghem, Peter A
2011-01-01
Monte Carlo (MC) simulation appears to be the only currently adopted tool to estimate global sensitivities and uncertainties in wastewater treatment modelling. Such models are highly complex, dynamic and non-linear, requiring long computation times, especially in the scope of MC simulation, due to the large number of simulations usually required. However, no stopping rule to decide on the number of simulations required to achieve a given confidence in the MC simulation results has been adopted so far in the field. In this work, a pragmatic method is proposed to minimize the computation time by using a combination of several criteria. It makes no use of prior knowledge about the model, is very simple, intuitive and can be automated: all convenient features in engineering applications. A case study is used to show an application of the method, and the results indicate that the required number of simulations strongly depends on the model output(s) selected, and on the type and desired accuracy of the analysis conducted. Hence, no prior indication is available regarding the necessary number of MC simulations, but the proposed method is capable of dealing with these variations and stopping the calculations after convergence is reached.
3D Monte Carlo model of optical transport in laser-irradiated cutaneous vascular malformations
Majaron, Boris; Milanič, Matija; Jia, Wangcun; Nelson, J. S.
2010-11-01
We have developed a three-dimensional Monte Carlo (MC) model of optical transport in skin and applied it to analysis of port wine stain treatment with sequential laser irradiation and intermittent cryogen spray cooling. Our MC model extends the approaches of the popular multi-layer model by Wang et al.1 to three dimensions, thus allowing treatment of skin inclusions with more complex geometries and arbitrary irradiation patterns. To overcome the obvious drawbacks of either "escape" or "mirror" boundary conditions at the lateral boundaries of the finely discretized volume of interest (VOI), photons exiting the VOI are propagated in laterally infinite tissue layers with appropriate optical properties, until they loose all their energy, escape into the air, or return to the VOI, but the energy deposition outside of the VOI is not computed and recorded. After discussing the selection of tissue parameters, we apply the model to analysis of blood photocoagulation and collateral thermal damage in treatment of port wine stain (PWS) lesions with sequential laser irradiation and intermittent cryogen spray cooling.
EURADOS intercomparison exercise on Monte Carlo modelling of a medical linear accelerator.
Caccia, Barbara; Le Roy, Maïwenn; Blideanu, Valentin; Andenna, Claudio; Arun, Chairmadurai; Czarnecki, Damian; El Bardouni, Tarek; Gschwind, Régine; Huot, Nicolas; Martin, Eric; Zink, Klemens; Zoubair, Mariam; Price, Robert; de Carlan, Loïc
2017-01-01
In radiotherapy, Monte Carlo (MC) methods are considered a gold standard to calculate accurate dose distributions, particularly in heterogeneous tissues. EURADOS organized an international comparison with six participants applying different MC models to a real medical linear accelerator and to one homogeneous and four heterogeneous dosimetric phantoms. The aim of this exercise was to identify, by comparison of different MC models with a complete experimental dataset, critical aspects useful for MC users to build and calibrate a simulation and perform a dosimetric analysis. Results show on average a good agreement between simulated and experimental data. However, some significant differences have been observed especially in presence of heterogeneities. Moreover, the results are critically dependent on the different choices of the initial electron source parameters. This intercomparison allowed the participants to identify some critical issues in MC modelling of a medical linear accelerator. Therefore, the complete experimental dataset assembled for this intercomparison will be available to all the MC users, thus providing them an opportunity to build and calibrate a model for a real medical linear accelerator.
Kinetic Monte Carlo Potts Model for Simulating a High Burnup Structure in UO2
International Nuclear Information System (INIS)
Oh, Jae-Yong; Koo, Yang-Hyun; Lee, Byung-Ho
2008-01-01
A Potts model, based on the kinetic Monte Carlo method, was originally developed for magnetic domain evolutions, but it was also proposed as a model for a grain growth in polycrystals due to similarities between Potts domain structures and grain structures. It has modeled various microstructural phenomena such as grain growths, a recrystallization, a sintering, and so on. A high burnup structure (HBS) is observed in the periphery of a high burnup UO 2 fuel. Although its formation mechanism is not clearly understood yet, its characteristics are well recognized: The HBS microstructure consists of very small grains and large bubbles instead of original as-sintered grains. A threshold burnup for the HBS is observed at a local burnup 60-80 Gwd/tM, and the threshold temperature is 1000-1200 .deg. C. Concerning a energy stability, the HBS can be created if the system energy of the HBS is lower than that of the original structure in an irradiated UO 2 . In this paper, a Potts model was implemented for simulating the HBS by calculating system energies, and the simulation results were compared with the HBS characteristics mentioned above
Direct Simulation Monte Carlo Application of the Three Dimensional Forced Harmonic Oscillator Model
2017-12-07
NUMBER (Include area code) 07 December 2017 Journal Article 24 February 2017 - 31 December 2017 Direct Simulation Monte Carlo Application of the...is proposed. The implementation employs precalculated lookup tables for transition probabilities and is suitable for the direct simulation Monte Carlo...method. It takes into account the microscopic reversibility between the excitation and deexcitation processes , and it satisfies the detailed balance
Derwent, Richard G.; Parrish, David D.; Galbally, Ian E.; Stevenson, David S.; Doherty, Ruth M.; Naik, Vaishali; Young, Paul J.
2018-05-01
Recognising that global tropospheric ozone models have many uncertain input parameters, an attempt has been made to employ Monte Carlo sampling to quantify the uncertainties in model output that arise from global tropospheric ozone precursor emissions and from ozone production and destruction in a global Lagrangian chemistry-transport model. Ninety eight quasi-randomly Monte Carlo sampled model runs were completed and the uncertainties were quantified in tropospheric burdens and lifetimes of ozone, carbon monoxide and methane, together with the surface distribution and seasonal cycle in ozone. The results have shown a satisfactory degree of convergence and provide a first estimate of the likely uncertainties in tropospheric ozone model outputs. There are likely to be diminishing returns in carrying out many more Monte Carlo runs in order to refine further these outputs. Uncertainties due to model formulation were separately addressed using the results from 14 Atmospheric Chemistry Coupled Climate Model Intercomparison Project (ACCMIP) chemistry-climate models. The 95% confidence ranges surrounding the ACCMIP model burdens and lifetimes for ozone, carbon monoxide and methane were somewhat smaller than for the Monte Carlo estimates. This reflected the situation where the ACCMIP models used harmonised emissions data and differed only in their meteorological data and model formulations whereas a conscious effort was made to describe the uncertainties in the ozone precursor emissions and in the kinetic and photochemical data in the Monte Carlo runs. Attention was focussed on the model predictions of the ozone seasonal cycles at three marine boundary layer stations: Mace Head, Ireland, Trinidad Head, California and Cape Grim, Tasmania. Despite comprehensively addressing the uncertainties due to global emissions and ozone sources and sinks, none of the Monte Carlo runs were able to generate seasonal cycles that matched the observations at all three MBL stations. Although
LEARNING VECTOR QUANTIZATION FOR ADAPTED GAUSSIAN MIXTURE MODELS IN AUTOMATIC SPEAKER IDENTIFICATION
Directory of Open Access Journals (Sweden)
IMEN TRABELSI
2017-05-01
Full Text Available Speaker Identification (SI aims at automatically identifying an individual by extracting and processing information from his/her voice. Speaker voice is a robust a biometric modality that has a strong impact in several application areas. In this study, a new combination learning scheme has been proposed based on Gaussian mixture model-universal background model (GMM-UBM and Learning vector quantization (LVQ for automatic text-independent speaker identification. Features vectors, constituted by the Mel Frequency Cepstral Coefficients (MFCC extracted from the speech signal are used to train the New England subset of the TIMIT database. The best results obtained (90% for gender- independent speaker identification, 97 % for male speakers and 93% for female speakers for test data using 36 MFCC features.
Arendt, Carli A.; Aciego, Sarah M.; Hetland, Eric A.
2015-05-01
The implementation of isotopic tracers as constraints on source contributions has become increasingly relevant to understanding Earth surface processes. Interpretation of these isotopic tracers has become more accessible with the development of Bayesian Monte Carlo (BMC) mixing models, which allow uncertainty in mixing end-members and provide methodology for systems with multicomponent mixing. This study presents an open source multiple isotope BMC mixing model that is applicable to Earth surface environments with sources exhibiting distinct end-member isotopic signatures. Our model is first applied to new δ18O and δD measurements from the Athabasca Glacier, which showed expected seasonal melt evolution trends and vigorously assessed the statistical relevance of the resulting fraction estimations. To highlight the broad applicability of our model to a variety of Earth surface environments and relevant isotopic systems, we expand our model to two additional case studies: deriving melt sources from δ18O, δD, and 222Rn measurements of Greenland Ice Sheet bulk water samples and assessing nutrient sources from ɛNd and 87Sr/86Sr measurements of Hawaiian soil cores. The model produces results for the Greenland Ice Sheet and Hawaiian soil data sets that are consistent with the originally published fractional contribution estimates. The advantage of this method is that it quantifies the error induced by variability in the end-member compositions, unrealized by the models previously applied to the above case studies. Results from all three case studies demonstrate the broad applicability of this statistical BMC isotopic mixing model for estimating source contribution fractions in a variety of Earth surface systems.
International Nuclear Information System (INIS)
Pohjola, J.; Turunen, J.; Lipping, T.
2009-07-01
In this report creation of the digital elevation model of Olkiluoto area incorporating a large area of seabed is described. The modeled area covers 960 square kilometers and the apparent resolution of the created elevation model was specified to be 2.5 x 2.5 meters. Various elevation data like contour lines and irregular elevation measurements were used as source data in the process. The precision and reliability of the available source data varied largely. Digital elevation model (DEM) comprises a representation of the elevation of the surface of the earth in particular area in digital format. DEM is an essential component of geographic information systems designed for the analysis and visualization of the location-related data. DEM is most often represented either in raster or Triangulated Irregular Network (TIN) format. After testing several methods the thin plate spline interpolation was found to be best suited for the creation of the elevation model. The thin plate spline method gave the smallest error in the test where certain amount of points was removed from the data and the resulting model looked most natural. In addition to the elevation data the confidence interval at each point of the new model was required. The Monte Carlo simulation method was selected for this purpose. The source data points were assigned probability distributions according to what was known about their measurement procedure and from these distributions 1 000 (20 000 in the first version) values were drawn for each data point. Each point of the newly created DEM had thus as many realizations. The resulting high resolution DEM will be used in modeling the effects of land uplift and evolution of the landscape in the time range of 10 000 years from the present. This time range comes from the requirements set for the spent nuclear fuel repository site. (orig.)
Model of Random Polygon Particles for Concrete and Mesh Automatic Subdivision
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In order to study the constitutive behavior of concrete in mesoscopic level, a new method is proposed in this paper. This method uses random polygon particles to simulate full grading broken aggregates of concrete. Based on computational geometry, we carry out the automatic generation of the triangle finite element mesh for the model of random polygon particles of concrete. The finite element mesh generated in this paper is also applicable to many other numerical methods.
Marjanovic, Nicolas; Le Floch, Soizig; Jaffrelot, Morgan; L'Her, Erwan
2014-05-01
In the absence of endotracheal intubation, the manual bag-valve-mask (BVM) is the most frequently used ventilation technique during resuscitation. The efficiency of other devices has been poorly studied. The bench-test study described here was designed to evaluate the effectiveness of an automatic, manually triggered system, and to compare it with manual BVM ventilation. A respiratory system bench model was assembled using a lung simulator connected to a manikin to simulate a patient with unprotected airways. Fifty health-care providers from different professional groups (emergency physicians, residents, advanced paramedics, nurses, and paramedics; n = 10 per group) evaluated manual BVM ventilation, and compared it with an automatic manually triggered device (EasyCPR). Three pathological situations were simulated (restrictive, obstructive, normal). Standard ventilation parameters were recorded; the ergonomics of the system were assessed by the health-care professionals using a standard numerical scale once the recordings were completed. The tidal volume fell within the standard range (400-600 mL) for 25.6% of breaths (0.6-45 breaths) using manual BVM ventilation, and for 28.6% of breaths (0.3-80 breaths) using the automatic manually triggered device (EasyCPR) (P < .0002). Peak inspiratory airway pressure was lower using the automatic manually triggered device (EasyCPR) (10.6 ± 5 vs 15.9 ± 10 cm H2O, P < .001). The ventilation rate fell consistently within the guidelines, in the case of the automatic manually triggered device (EasyCPR) only (10.3 ± 2 vs 17.6 ± 6, P < .001). Significant pulmonary overdistention was observed when using the manual BVM device during the normal and obstructive sequences. The nurses and paramedics considered the ergonomics of the automatic manually triggered device (EasyCPR) to be better than those of the manual device. The use of an automatic manually triggered device may improve ventilation efficiency and decrease the risk of
Shell-model Monte Carlo simulations of the BCS-BEC crossover in few-fermion systems
DEFF Research Database (Denmark)
Zinner, Nikolaj Thomas; Mølmer, Klaus; Özen, C.
2009-01-01
We study a trapped system of fermions with a zero-range two-body interaction using the shell-model Monte Carlo method, providing ab initio results for the low particle number limit where mean-field theory is not applicable. We present results for the N-body energies as function of interaction...
International Nuclear Information System (INIS)
Lopez, M. A.; Broggio, D.; Capello, K.; Cardenas-Mendez, E.; El-Faramawy, N.; Franck, D.; James, A. C.; Kramer, G. H.; Lacerenza, G.; Lynch, T. P.; Navarro, J. F.; Navarro, T.; Perez, B.; Ruehm, W.; Tolmachev, S. Y.; Weitzenegger, E.
2011-01-01
A collaboration of the EURADOS working group on 'Internal Dosimetry' and the United States Transuranium and Uranium Registries (USTUR) has taken place to carry out an intercomparison on measurements and Monte Carlo modelling determining americium deposited in the bone of a USTUR leg phantom. Preliminary results and conclusions of this intercomparison exercise are presented here. (authors)
Monte Carlo simulations with Symanzik's improved actions in the lattice 0(3) non-linear sigma-model
International Nuclear Information System (INIS)
Berg, B.; Montvay, I.; Meyer, S.
1983-10-01
The scaling properties of the lattice 0(3) non-linear delta-model are studied. The mass-gap, energy-momentum dispersion, correlation functions are measured by numerical Monte Carlo methods. Symanzik's tree-level and 1-loop improved actions are compared to the standard (nearest neigbour) action. (orig.)
Nightingale, M.P.; Blöte, H.W.J.
1996-01-01
The principle and the efficiency of the Monte Carlo transfer-matrix algorithm are discussed. Enhancements of this algorithm are illustrated by applications to several phase transitions in lattice spin models. We demonstrate how the statistical noise can be reduced considerably by a similarity
Hofstede, ter F.; Wedel, M.
1998-01-01
This study investigates the effects of time aggregation in discrete and continuous-time hazard models. A Monte Carlo study is conducted in which data are generated according to various continuous and discrete-time processes, and aggregated into daily, weekly and monthly intervals. These data are
Modeling of the 3RS tau protein with self-consistent field method and Monte Carlo simulation
Leermakers, F.A.M.; Jho, Y.S.; Zhulina, E.B.
2010-01-01
Using a model with amino acid resolution of the 196 aa N-terminus of the 3RS tau protein, we performed both a Monte Carlo study and a complementary self-consistent field (SCF) analysis to obtain detailed information on conformational properties of these moieties near a charged plane (mimicking the
Mesta, M.; van Eersel, H.; Coehoorn, R.; Bobbert, P.A.
2016-01-01
Triplet-triplet annihilation (TTA) and triplet-polaron quenching (TPQ) in organic light-emitting devices (OLEDs) lead to a roll-off of the internal quantum efficiency (IQE) with increasing current density J. We employ a kinetic Monte Carlo modeling study to analyze the measured IQE and color balance
Walker, Jeffrey A
2016-01-01
Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori . Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R) methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness) on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set). The original analysis of these data used a linear model (GLS) of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on mean CTRA expression. The standardized effects of Hedonia and Eudaimonia on CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS) linear models and generalized estimating equation (GEE) models. The OLS estimates were tested using O'Brien's OLS test, Anderson's permutation [Formula: see text]-test, two permutation F -tests (including GlobalAncova), and a rotation z -test (Roast). The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors) of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset. GLS estimates are inconsistent between data sets, and, in each dataset, at least one coefficient is large and highly statistically significant. By contrast, effects estimated by OLS or GEE are very small, especially relative to the standard errors. Bootstrap and permutation GLS distributions suggest that the GLS results in
Directory of Open Access Journals (Sweden)
Jeffrey A. Walker
2016-10-01
Full Text Available Background Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori. Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set. The original analysis of these data used a linear model (GLS of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on mean CTRA expression. Methods The standardized effects of Hedonia and Eudaimonia on CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS linear models and generalized estimating equation (GEE models. The OLS estimates were tested using O’Brien’s OLS test, Anderson’s permutation ${r}_{F}^{2}$ r F 2 -test, two permutation F-tests (including GlobalAncova, and a rotation z-test (Roast. The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset. Results GLS estimates are inconsistent between data sets, and, in each dataset, at least one coefficient is large and highly statistically significant. By contrast, effects estimated by OLS or GEE are very small, especially relative to the standard errors. Bootstrap and permutation GLS
GIS Data Based Automatic High-Fidelity 3D Road Network Modeling
Wang, Jie; Shen, Yuzhong
2011-01-01
3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks
Grammar-based Automatic 3D Model Reconstruction from Terrestrial Laser Scanning Data
Yu, Q.; Helmholz, P.; Belton, D.; West, G.
2014-04-01
The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules. Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account.
Directory of Open Access Journals (Sweden)
Animesh Agarwal
2017-09-01
Full Text Available We present a hierarchical coarse-graining framework for modeling semidilute polymer solutions, based on the wavelet-accelerated Monte Carlo (WAMC method. This framework forms a hierarchy of resolutions to model polymers at length scales that cannot be reached via atomistic or even standard coarse-grained simulations. Previously, it was applied to simulations examining the structure of individual polymer chains in solution using up to four levels of coarse-graining (Ismail et al., J. Chem. Phys., 2005, 122, 234901 and Ismail et al., J. Chem. Phys., 2005, 122, 234902, recovering the correct scaling behavior in the coarse-grained representation. In the present work, we extend this method to the study of polymer solutions, deriving the bonded and non-bonded potentials between coarse-grained superatoms from the single chain statistics. A universal scaling function is obtained, which does not require recalculation of the potentials as the scale of the system is changed. To model semi-dilute polymer solutions, we assume the intermolecular potential between the coarse-grained beads to be equal to the non-bonded potential, which is a reasonable approximation in the case of semidilute systems. Thus, a minimal input of microscopic data is required for simulating the systems at the mesoscopic scale. We show that coarse-grained polymer solutions can reproduce results obtained from the more detailed atomistic system without a significant loss of accuracy.
Energy Technology Data Exchange (ETDEWEB)
Oh, Kye Min [KHNP Central Research Institute, Daejeon (Korea, Republic of); Han, Sang Hoon; Park, Jin Hee; Lim, Ho Gon; Yang, Joon Yang [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of)
2017-06-15
In Korea, many nuclear power plants operate at a single site based on geographical characteristics, but the population density near the sites is higher than that in other countries. Thus, multiunit accidents are a more important consideration than in other countries and should be addressed appropriately. Currently, there are many issues related to a multiunit probabilistic safety assessment (PSA). One of them is the quantification of a multiunit PSA model. A traditional PSA uses a Boolean manipulation of the fault tree in terms of the minimal cut set. However, such methods have some limitations when rare event approximations cannot be used effectively or a very small truncation limit should be applied to identify accident sequence combinations for a multiunit site. In particular, it is well known that seismic risk in terms of core damage frequency can be overestimated because there are many events that have a high failure probability. In this study, we propose a quantification method based on a Monte Carlo approach for a multiunit PSA model. This method can consider all possible accident sequence combinations in a multiunit site and calculate a more exact value for events that have a high failure probability. An example model for six identical units at a site was also developed and quantified to confirm the applicability of the proposed method.
Mathematical modeling, analysis and Markov Chain Monte Carlo simulation of Ebola epidemics
Tulu, Thomas Wetere; Tian, Boping; Wu, Zunyou
Ebola virus infection is a severe infectious disease with the highest case fatality rate which become the global public health treat now. What makes the disease the worst of all is no specific effective treatment available, its dynamics is not much researched and understood. In this article a new mathematical model incorporating both vaccination and quarantine to study the dynamics of Ebola epidemic has been developed and comprehensively analyzed. The existence as well as uniqueness of the solution to the model is also verified and the basic reproduction number is calculated. Besides, stability conditions are also checked and finally simulation is done using both Euler method and one of the top ten most influential algorithm known as Markov Chain Monte Carlo (MCMC) method. Different rates of vaccination to predict the effect of vaccination on the infected individual over time and that of quarantine are discussed. The results show that quarantine and vaccination are very effective ways to control Ebola epidemic. From our study it was also seen that there is less possibility of an individual for getting Ebola virus for the second time if they survived his/her first infection. Last but not least real data has been fitted to the model, showing that it can used to predict the dynamic of Ebola epidemic.
Modeling Monte Carlo of multileaf collimators using the code GEANT4
Energy Technology Data Exchange (ETDEWEB)
Oliveira, Alex C.H.; Lima, Fernando R.A., E-mail: oliveira.ach@yahoo.com, E-mail: falima@cnen.gov.br [Centro Regional de Ciencias Nucleares do Nordeste (CRCN-NE/CNEN-PE), Recife, PE (Brazil); Lima, Luciano S.; Vieira, Jose W., E-mail: lusoulima@yahoo.com.br [Instituto Federal de Educacao, Ciencia e Tecnologia de Pernambuco (IFPE), Recife, PE (Brazil)
2014-07-01
Radiotherapy uses various techniques and equipment for local treatment of cancer. The equipment most often used in radiotherapy to the patient irradiation is linear accelerator (Linac). Among the many algorithms developed for evaluation of dose distributions in radiotherapy planning, the algorithms based on Monte Carlo (MC) methods have proven to be very promising in terms of accuracy by providing more realistic results. The MC simulations for applications in radiotherapy are divided into two parts. In the first, the simulation of the production of the radiation beam by the Linac is performed and then the phase space is generated. The phase space contains information such as energy, position, direction, etc. of millions of particles (photons, electrons, positrons). In the second part the simulation of the transport of particles (sampled phase space) in certain configurations of irradiation field is performed to assess the dose distribution in the patient (or phantom). Accurate modeling of the Linac head is of particular interest in the calculation of dose distributions for intensity modulated radiation therapy (IMRT), where complex intensity distributions are delivered using a multileaf collimator (MLC). The objective of this work is to describe a methodology for modeling MC of MLCs using code Geant4. To exemplify this methodology, the Varian Millennium 120-leaf MLC was modeled, whose physical description is available in BEAMnrc Users Manual (20 11). The dosimetric characteristics (i.e., penumbra, leakage, and tongue-and-groove effect) of this MLC were evaluated. The results agreed with data published in the literature concerning the same MLC. (author)
Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model
Directory of Open Access Journals (Sweden)
Davide Viganò
2016-01-01
Full Text Available Compactness, reliability, readiness, and construction simplicity of solid rocket motors make them very appealing for commercial launcher missions and embarked systems. Solid propulsion grants high thrust-to-weight ratio, high volumetric specific impulse, and a Technology Readiness Level of 9. However, solid rocket systems are missing any throttling capability at run-time, since pressure-time evolution is defined at the design phase. This lack of mission flexibility makes their missions sensitive to deviations of performance from nominal behavior. For this reason, the reliability of predictions and reproducibility of performances represent a primary goal in this field. This paper presents an analysis of SRM performance uncertainties throughout the implementation of a quasi-1D numerical model of motor internal ballistics based on Shapiro’s equations. The code is coupled with a Monte Carlo algorithm to evaluate statistics and propagation of some peculiar uncertainties from design data to rocker performance parameters. The model has been set for the reproduction of a small-scale rocket motor, discussing a set of parametric investigations on uncertainty propagation across the ballistic model.
Natto, S A; Lewis, D G; Ryde, S J
1998-01-01
The Monte Carlo computer code MCNP (version 4A) has been used to develop a personal computer-based model of the Swansea in vivo neutron activation analysis (IVNAA) system. The model included specification of the neutron source (252Cf), collimators, reflectors and shielding. The MCNP model was 'benchmarked' against fast neutron and thermal neutron fluence data obtained experimentally from the IVNAA system. The Swansea system allows two irradiation geometries using 'short' and 'long' collimators, which provide alternative dose rates for IVNAA. The data presented here relate to the short collimator, although results of similar accuracy were obtained using the long collimator. The fast neutron fluence was measured in air at a series of depths inside the collimator. The measurements agreed with the MCNP simulation within the statistical uncertainty (5-10%) of the calculations. The thermal neutron fluence was measured and calculated inside the cuboidal water phantom. The depth of maximum thermal fluence was 3.2 cm (measured) and 3.0 cm (calculated). The width of the 50% thermal fluence level across the phantom at its mid-depth was found to be the same by both MCNP and experiment. This benchmarking exercise has given us a high degree of confidence in MCNP as a tool for the design of IVNAA systems.
International Nuclear Information System (INIS)
Rojas T, J.; Instituto Peruano de Energia Nuclear, Lima; Manrique C, E.; Torres T, E.
2002-01-01
Using monte Carlo simulation have been carried out an atomistic description of the structure and ordering processes in the system Cu-Au in a two-dimensional model. The ABV model of the alloy is a system of N atoms A and B, located in rigid lattice with some vacant sites. In the model we assume pair wise interactions between nearest neighbors with constant ordering energy J = 0,03 eV. The dynamics was introduced by means of a vacancy that exchanges of place with any atom of its neighbors. The simulations were carried out in a square lattice with 1024 and 4096 particles, using periodic boundary conditions to avoid border effects. We calculate the first two parameters of short range order of Warren-Cowley as function of the concentration and temperature. It was also studied the probabilities of formation of different atomic clusters that consist of 9 atoms as function of the concentration of the alloy and temperatures in a wide range of values. In some regions of temperature and concentration it was observed compositional and thermal polymorphism
Matthews, Samuel J.; O'Neill, Craig; Lackie, Mark A.
2017-06-01
Gravity gradiometry has a long legacy, with airborne/marine applications as well as surface applications receiving renewed recent interest. Recent instrumental advances has led to the emergence of downhole gravity gradiometry applications that have the potential for greater resolving power than borehole gravity alone. This has promise in both the petroleum and geosequestration industries; however, the effect of inherent uncertainties in the ability of downhole gravity gradiometry to resolve a subsurface signal is unknown. Here, we utilise the open source modelling package, Fatiando a Terra, to model both the gravity and gravity gradiometry responses of a subsurface body. We use a Monte Carlo approach to vary the geological structure and reference densities of the model within preset distributions. We then perform 100 000 simulations to constrain the mean response of the buried body as well as uncertainties in these results. We varied our modelled borehole to be either centred on the anomaly, adjacent to the anomaly (in the x-direction), and 2500 m distant to the anomaly (also in the x-direction). We demonstrate that gravity gradiometry is able to resolve a reservoir-scale modelled subsurface density variation up to 2500 m away, and that certain gravity gradient components (Gzz, Gxz, and Gxx) are particularly sensitive to this variation in gravity/gradiometry above the level of uncertainty in the model. The responses provided by downhole gravity gradiometry modelling clearly demonstrate a technique that can be utilised in determining a buried density contrast, which will be of particular use in the emerging industry of CO2 geosequestration. The results also provide a strong benchmark for the development of newly emerging prototype downhole gravity gradiometers.
International Nuclear Information System (INIS)
Gasco, C.; Anton, M. P.; Ampudia, J.
2003-01-01
The introduction of macros in try calculation sheets allows the automatic application of various dating models using unsupported ''210 Pb data from a data base. The calculation books the contain the models have been modified to permit the implementation of these macros. The Marine and Aquatic Radioecology group of CIEMAT (MARG) will be involved in new European Projects, thus new models have been developed. This report contains a detailed description of: a) the new implement macros b) the design of a dating Menu in the calculation sheet and c) organization and structure of the data base. (Author) 4 refs
Guo, Changning; Doub, William H; Kauffman, John F
2010-08-01
Monte Carlo simulations were applied to investigate the propagation of uncertainty in both input variables and response measurements on model prediction for nasal spray product performance design of experiment (DOE) models in the first part of this study, with an initial assumption that the models perfectly represent the relationship between input variables and the measured responses. In this article, we discard the initial assumption, and extended the Monte Carlo simulation study to examine the influence of both input variable variation and product performance measurement variation on the uncertainty in DOE model coefficients. The Monte Carlo simulations presented in this article illustrate the importance of careful error propagation during product performance modeling. Our results show that the error estimates based on Monte Carlo simulation result in smaller model coefficient standard deviations than those from regression methods. This suggests that the estimated standard deviations from regression may overestimate the uncertainties in the model coefficients. Monte Carlo simulations provide a simple software solution to understand the propagation of uncertainty in complex DOE models so that design space can be specified with statistically meaningful confidence levels. (c) 2010 Wiley-Liss, Inc. and the American Pharmacists Association
A fast fiducial marker tracking model for fully automatic alignment in electron tomography
Han, Renmin; Zhang, Fa; Gao, Xin
2017-01-01
Automatic alignment, especially fiducial marker-based alignment, has become increasingly important due to the high demand of subtomogram averaging and the rapid development of large-field electron microscopy. Among the alignment steps, fiducial marker tracking is a crucial one that determines the quality of the final alignment. Yet, it is still a challenging problem to track the fiducial markers accurately and effectively in a fully automatic manner.In this paper, we propose a robust and efficient scheme for fiducial marker tracking. Firstly, we theoretically prove the upper bound of the transformation deviation of aligning the positions of fiducial markers on two micrographs by affine transformation. Secondly, we design an automatic algorithm based on the Gaussian mixture model to accelerate the procedure of fiducial marker tracking. Thirdly, we propose a divide-and-conquer strategy against lens distortions to ensure the reliability of our scheme. To our knowledge, this is the first attempt that theoretically relates the projection model with the tracking model. The real-world experimental results further support our theoretical bound and demonstrate the effectiveness of our algorithm. This work facilitates the fully automatic tracking for datasets with a massive number of fiducial markers.The C/C ++ source code that implements the fast fiducial marker tracking is available at https://github.com/icthrm/gmm-marker-tracking. Markerauto 1.6 version or later (also integrated in the AuTom platform at http://ear.ict.ac.cn/) offers a complete implementation for fast alignment, in which fast fiducial marker tracking is available by the
A fast fiducial marker tracking model for fully automatic alignment in electron tomography
Han, Renmin
2017-10-20
Automatic alignment, especially fiducial marker-based alignment, has become increasingly important due to the high demand of subtomogram averaging and the rapid development of large-field electron microscopy. Among the alignment steps, fiducial marker tracking is a crucial one that determines the quality of the final alignment. Yet, it is still a challenging problem to track the fiducial markers accurately and effectively in a fully automatic manner.In this paper, we propose a robust and efficient scheme for fiducial marker tracking. Firstly, we theoretically prove the upper bound of the transformation deviation of aligning the positions of fiducial markers on two micrographs by affine transformation. Secondly, we design an automatic algorithm based on the Gaussian mixture model to accelerate the procedure of fiducial marker tracking. Thirdly, we propose a divide-and-conquer strategy against lens distortions to ensure the reliability of our scheme. To our knowledge, this is the first attempt that theoretically relates the projection model with the tracking model. The real-world experimental results further support our theoretical bound and demonstrate the effectiveness of our algorithm. This work facilitates the fully automatic tracking for datasets with a massive number of fiducial markers.The C/C ++ source code that implements the fast fiducial marker tracking is available at https://github.com/icthrm/gmm-marker-tracking. Markerauto 1.6 version or later (also integrated in the AuTom platform at http://ear.ict.ac.cn/) offers a complete implementation for fast alignment, in which fast fiducial marker tracking is available by the
Monte Carlo modeling of Lead-Cooled Fast Reactor in adiabatic equilibrium state
Energy Technology Data Exchange (ETDEWEB)
Stanisz, Przemysław, E-mail: pstanisz@agh.edu.pl; Oettingen, Mikołaj, E-mail: moettin@agh.edu.pl; Cetnar, Jerzy, E-mail: cetnar@mail.ftj.agh.edu.pl
2016-05-15
Graphical abstract: - Highlights: • We present the Monte Carlo modeling of the LFR in the adiabatic equilibrium state. • We assess the adiabatic equilibrium fuel composition using the MCB code. • We define the self-adjusting process of breeding gain by the control rod operation. • The designed LFR can work in the adiabatic cycle with zero fuel breeding. - Abstract: Nuclear power would appear to be the only energy source able to satisfy the global energy demand while also achieving a significant reduction of greenhouse gas emissions. Moreover, it can provide a stable and secure source of electricity, and plays an important role in many European countries. However, nuclear power generation from its birth has been doomed by the legacy of radioactive nuclear waste. In addition, the looming decrease in the available resources of fissile U235 may influence the future sustainability of nuclear energy. The integrated solution to both problems is not trivial, and postulates the introduction of a closed-fuel cycle strategy based on breeder reactors. The perfect choice of a novel reactor system fulfilling both requirements is the Lead-Cooled Fast Reactor operating in the adiabatic equilibrium state. In such a state, the reactor converts depleted or natural uranium into plutonium while consuming any self-generated minor actinides and transferring only fission products as waste. We present the preliminary design of a Lead-Cooled Fast Reactor operating in the adiabatic equilibrium state with the Monte Carlo Continuous Energy Burnup Code – MCB. As a reference reactor model we apply the core design developed initially under the framework of the European Lead-cooled SYstem (ELSY) project and refined in the follow-up Lead-cooled European Advanced DEmonstration Reactor (LEADER) project. The major objective of the study is to show to what extent the constraints of the adiabatic cycle are maintained and to indicate the phase space for further improvements. The analysis
Monte Carlo modelling of damage to haemopoietic stem cells from internally deposited alpha-emitters
International Nuclear Information System (INIS)
Utteridge, T.D.; University of South Australia, Pooraka, SA; Charlton, D.E.; Turner, M.S.; Beddoe, A.H.; Leong, A. S-Y.; Milios, J.; Fazzalari, N.; To, L.B.
1996-01-01
Full text: Monte Carlo modelling of alpha particle radiation dose to haemopoietic stem cells from radon decay in human marrow fat cells was undertaken following Richardson et al's (Brit J Radiol, 64, 608-624, 1991) proposition that such exposure could induce leukaemia, and epidemiological observations that uranium miners have not developed an excess of leukaemia (Tomasek L. et al, Lancet, 341, 919-923, 1993). The dose to haemopoietic stem cells from alpha emitting radiopharmaceuticals proposed for radiotherapy is also important in risk assessment. Haemopoietic stem cells (presumed to be the targets for leukaemia) were identified as CD34+CD38- mononuclear cells (Terstappen LWMM et al, Blood, 77, 1218-1227, 1991) and their diameters measured using image analysis. The distribution of stem cell distances from fat cells was also measured. The model was used with Monte Carlo treatment of the alpha particle flux from radon and its short lived decay products to estimate (a) the dose and LET distributions for the three stem cell diameters; (b) the number of passages per hit; and (c) stem cell survival. The stem cell population exhibited a trimodal distribution, with mean diameters of 5.7, 11.6 and 14.8 μm; a trimodal distribution has previously been identified in mice (Visser J et al, Exper Hematol Today, 21-27, 1977). At 40% fat in a human lumbar vertebra 3 section, approximately half the stem cells were located on, or very close to the edge, of fat cells in marrow sections. This agrees with the predicted distribution of distances between fat and stem cells obtained using a 3-D model with randomly distributed stem cells. At an air activity of 20 Bq m -3 (ie the UK average indoor radon concentration used by Richardson et al mentioned above) about 0.1 stem cells per person-year were hit and survived; at 100 Bq m -3 about 1 stem cell per person-year was hit and survived. Across the range of radon concentrations encountered in residential and underground miner exposures
A Direct Simulation Monte Carlo Model Of Thermal Escape From Titan
Johnson, Robert E.; Tucker, O. J.
2008-09-01
Recent analysis of density profiles vs. altitude from the Ion Neutral Mass Spectrometer (INMS) on Cassini (Waite et al. 2005) suggest Titan could have loss a significant amount of atmosphere in 4 Gyr at present escape rates (e.g., Johnson 2008). Strobel 2008 applied a slow hydrodynamic escape model to Titan's atmosphere using solar heating below the exobase to drive upward thermal conduction and power escape. However, near the exobase continuum models become problematic as a result of the increasing rarefaction in the atmosphere. The microscopic nature of DSMC is directly suitable to model atmosphere flow in nominal exobase region (e.g., Michael et. al. 2005). Our Preliminary DSMC models have shown no evidence for slow hydrodynamic escape of N2 and CH4 from Titan's atmosphere using boundary conditions normalized to the atmospheric properties in Strobel (2008). In this paper we use a 1D radial Direct Simulation Monte Carlo (DSMC) model of heating in Titan's upper atmosphere to estimate the escape rate as a function of the Jean's parameter. In this way we can test under what conditions the suggested deviations from Jeans escape would occur. In addition, we will be able to extract the necessary energy deposition to power the heavy molecule loss rates suggested in recent models (Strobel 2008; Yelle et. al. 2008). Michael, M. Johnson, R.E. 2005 Energy Deposition of pickup ions and heating of Titan's atmosphere. Planat. Sp. Sci. 53, 1510-1514 Johnson, R.E., "Sputtering and Heating of Titan's Upper Atmosphere", Proc Royal Soc. (London) (2008) Strobel, D.F. 2008 Titan's hydrodynamically escaping atmosphere. Icarus 193, 588-594 Yelle, R.V., J. Cui and I. C.F. Muller-Wodarg 2008 Methane Escape from Titan's Atmosphere. J. Geophys. Res in press Waite, J.H., Jr., Niemann, H.B., Yelle, R.V. et al. 2005 Ion Neutral Mass Spectrometer Results from the First Flyby of Titan. Science 308, 982-986
International Nuclear Information System (INIS)
Ballone, P.; Pastore, G.; Tosi, M.P.
1986-02-01
Interfacial properties of an ionic fluid next to a uniformly charged planar wall are studied in the restricted primitive model by both theoretical and Monte Carlo methods. The system is a 1:1 fluid of equisized charged hard spheres in a state appropriate to 1M aqueous electrolyte solutions. The interfacial density profiles of counterions and coions are evaluated by extending the hypernetted chain approximation (HNC) to include the leading bridge diagrams for the wall-ion correlations. The theoretical results compare well with those of grand canonical Monte Carlo computations of Torrie and Valleau over the whole range of surface charge density considered by these authors, thus resolving the earlier disagreement between statistical mechanical theories and simulation data at large charge densities. In view of the importance of the model as a testing ground for theories of the diffuse layer, the Monte Carlo calculations are tested by considering alternative choices for the basic simulation cell and are extended so as to allow an evaluation of the differential capacitance of the model interface by two independent methods. These involve numerical differentiation of the mean potential drop as a function of the surface charge density or alternatively an appropriate use of a fluctuation theory formula for the capacitance. The results of these two Monte Carlo approaches consistently indicate an initially smooth increase of the diffuse layer capacitance followed by structure at large charge densities, this behaviour being connected with layering of counterions as already revealed in the density profiles reported by Torrie and Valleau. (author)
GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes
Directory of Open Access Journals (Sweden)
Nakayama Yoichi
2006-03-01
Full Text Available Abstract Background Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. Results We developed the Genome-based Modeling (GEM System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. Conclusion The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.
Energy Technology Data Exchange (ETDEWEB)
Davidson, Scott E., E-mail: sedavids@utmb.edu [Radiation Oncology, The University of Texas Medical Branch, Galveston, Texas 77555 (United States); Cui, Jing [Radiation Oncology, University of Southern California, Los Angeles, California 90033 (United States); Kry, Stephen; Ibbott, Geoffrey S.; Followill, David S. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States); Vicic, Milos [Department of Applied Physics, University of Belgrade, Belgrade 11000 (Serbia); White, R. Allen [Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States)
2016-08-15
Purpose: A dose calculation tool, which combines the accuracy of the dose planning method (DPM) Monte Carlo code and the versatility of a practical analytical multisource model, which was previously reported has been improved and validated for the Varian 6 and 10 MV linear accelerators (linacs). The calculation tool can be used to calculate doses in advanced clinical application studies. One shortcoming of current clinical trials that report dose from patient plans is the lack of a standardized dose calculation methodology. Because commercial treatment planning systems (TPSs) have their own dose calculation algorithms and the clinical trial participant who uses these systems is responsible for commissioning the beam model, variation exists in the reported calculated dose distributions. Today’s modern linac is manufactured to tight specifications so that variability within a linac model is quite low. The expectation is that a single dose calculation tool for a specific linac model can be used to accurately recalculate dose from patient plans that have been submitted to the clinical trial community from any institution. The calculation tool would provide for a more meaningful outcome analysis. Methods: The analytical source model was described by a primary point source, a secondary extra-focal source, and a contaminant electron source. Off-axis energy softening and fluence effects were also included. The additions of hyperbolic functions have been incorporated into the model to correct for the changes in output and in electron contamination with field size. A multileaf collimator (MLC) model is included to facilitate phantom and patient dose calculations. An offset to the MLC leaf positions was used to correct for the rudimentary assumed primary point source. Results: Dose calculations of the depth dose and profiles for field sizes 4 × 4 to 40 × 40 cm agree with measurement within 2% of the maximum dose or 2 mm distance to agreement (DTA) for 95% of the data
Directory of Open Access Journals (Sweden)
C. Xu
2016-06-01
Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.
Single-site Lennard-Jones models via polynomial chaos surrogates of Monte Carlo molecular simulation
Energy Technology Data Exchange (ETDEWEB)
Kadoura, Ahmad, E-mail: ahmad.kadoura@kaust.edu.sa, E-mail: adil.siripatana@kaust.edu.sa, E-mail: shuyu.sun@kaust.edu.sa, E-mail: omar.knio@kaust.edu.sa; Sun, Shuyu, E-mail: ahmad.kadoura@kaust.edu.sa, E-mail: adil.siripatana@kaust.edu.sa, E-mail: shuyu.sun@kaust.edu.sa, E-mail: omar.knio@kaust.edu.sa [Computational Transport Phenomena Laboratory, The Earth Sciences and Engineering Department, The Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900 (Saudi Arabia); Siripatana, Adil, E-mail: ahmad.kadoura@kaust.edu.sa, E-mail: adil.siripatana@kaust.edu.sa, E-mail: shuyu.sun@kaust.edu.sa, E-mail: omar.knio@kaust.edu.sa; Hoteit, Ibrahim, E-mail: ibrahim.hoteit@kaust.edu.sa [Earth Fluid Modeling and Predicting Group, The Earth Sciences and Engineering Department, The Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900 (Saudi Arabia); Knio, Omar, E-mail: ahmad.kadoura@kaust.edu.sa, E-mail: adil.siripatana@kaust.edu.sa, E-mail: shuyu.sun@kaust.edu.sa, E-mail: omar.knio@kaust.edu.sa [Uncertainty Quantification Center, The Applied Mathematics and Computational Science Department, The Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900 (Saudi Arabia)
2016-06-07
In this work, two Polynomial Chaos (PC) surrogates were generated to reproduce Monte Carlo (MC) molecular simulation results of the canonical (single-phase) and the NVT-Gibbs (two-phase) ensembles for a system of normalized structureless Lennard-Jones (LJ) particles. The main advantage of such surrogates, once generated, is the capability of accurately computing the needed thermodynamic quantities in a few seconds, thus efficiently replacing the computationally expensive MC molecular simulations. Benefiting from the tremendous computational time reduction, the PC surrogates were used to conduct large-scale optimization in order to propose single-site LJ models for several simple molecules. Experimental data, a set of supercritical isotherms, and part of the two-phase envelope, of several pure components were used for tuning the LJ parameters (ε, σ). Based on the conducted optimization, excellent fit was obtained for different noble gases (Ar, Kr, and Xe) and other small molecules (CH{sub 4}, N{sub 2}, and CO). On the other hand, due to the simplicity of the LJ model used, dramatic deviations between simulation and experimental data were observed, especially in the two-phase region, for more complex molecules such as CO{sub 2} and C{sub 2} H{sub 6}.
A Monte Carlo model for the intermittent plasticity of micro-pillars
International Nuclear Information System (INIS)
Ng, K S; Ngan, A H W
2008-01-01
Earlier compression experiments on micrometre-sized aluminium pillars, fabricated by focused-ion beam milling, using a flat-punch nanoindenter revealed that post-yield deformation during constant-rate loading was jerky with interspersing strain bursts and linear elastic segments. Under load hold, the pillars crept mainly by means of sporadic strain bursts. In this work, a Monte Carlo simulation model is developed, with two statistics gathered from the load-ramp experiments as input, to account for the jerky deformation during the load ramp as well as load hold. Under load-ramp conditions, the simulations successfully captured other experimental observations made independently from the two inputs, namely, the diverging behaviour of the jerky stress–strain response at higher stresses, the increase in burst frequency and burst size with stress and the overall power-law distribution of the burst size. The model also predicts creep behaviour agreeable with the experimental observations, namely, the occurrence of sporadic bursts with frequency depending on stress, creep time and pillar dimensions
A stochastic Markov chain approach for tennis: Monte Carlo simulation and modeling
Aslam, Kamran
This dissertation describes the computational formulation of probability density functions (pdfs) that facilitate head-to-head match simulations in tennis along with ranking systems developed from their use. A background on the statistical method used to develop the pdfs , the Monte Carlo method, and the resulting rankings are included along with a discussion on ranking methods currently being used both in professional sports and in other applications. Using an analytical theory developed by Newton and Keller in [34] that defines a tennis player's probability of winning a game, set, match and single elimination tournament, a computational simulation has been developed in Matlab that allows further modeling not previously possible with the analytical theory alone. Such experimentation consists of the exploration of non-iid effects, considers the concept the varying importance of points in a match and allows an unlimited number of matches to be simulated between unlikely opponents. The results of these studies have provided pdfs that accurately model an individual tennis player's ability along with a realistic, fair and mathematically sound platform for ranking them.
Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases
Pfeiffer, M.; Nizenkov, P.; Mirza, A.; Fasoulas, S.
2016-02-01
Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn's Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methods are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder.
Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases
International Nuclear Information System (INIS)
Pfeiffer, M.; Nizenkov, P.; Mirza, A.; Fasoulas, S.
2016-01-01
Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn’s Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methods are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder
Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases
Energy Technology Data Exchange (ETDEWEB)
Pfeiffer, M., E-mail: mpfeiffer@irs.uni-stuttgart.de; Nizenkov, P., E-mail: nizenkov@irs.uni-stuttgart.de; Mirza, A., E-mail: mirza@irs.uni-stuttgart.de; Fasoulas, S., E-mail: fasoulas@irs.uni-stuttgart.de [Institute of Space Systems, University of Stuttgart, Pfaffenwaldring 29, D-70569 Stuttgart (Germany)
2016-02-15
Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn’s Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methods are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder.
Monte Carlo modeling of neutron and gamma-ray imaging systems
International Nuclear Information System (INIS)
Hall, J.
1996-04-01
Detailed numerical prototypes are essential to design of efficient and cost-effective neutron and gamma-ray imaging systems. We have exploited the unique capabilities of an LLNL-developed radiation transport code (COG) to develop code modules capable of simulating the performance of neutron and gamma-ray imaging systems over a wide range of source energies. COG allows us to simulate complex, energy-, angle-, and time-dependent radiation sources, model 3-dimensional system geometries with ''real world'' complexity, specify detailed elemental and isotopic distributions and predict the responses of various types of imaging detectors with full Monte Carlo accuray. COG references detailed, evaluated nuclear interaction databases allowingusers to account for multiple scattering, energy straggling, and secondary particle production phenomena which may significantly effect the performance of an imaging system by may be difficult or even impossible to estimate using simple analytical models. This work presents examples illustrating the use of these routines in the analysis of industrial radiographic systems for thick target inspection, nonintrusive luggage and cargoscanning systems, and international treaty verification
Neutron and gamma sensitivities of self-powered detectors: Monte Carlo modelling
Energy Technology Data Exchange (ETDEWEB)
Vermeeren, Ludo [SCK-CEN, Nuclear Research Centre, Boeretang 200, B-2400 Mol, (Belgium)
2015-07-01
This paper deals with the development of a detailed Monte Carlo approach for the calculation of the absolute neutron sensitivity of SPNDs, which makes use of the MCNP code. We will explain the calculation approach, including the activation and beta emission steps, the gamma-electron interactions, the charge deposition in the various detector parts and the effect of the space charge field in the insulator. The model can also be applied for the calculation of the gamma sensitivity of self-powered detectors and for the radiation-induced currents in signal cables. The model yields detailed information on the various contributions to the sensor currents, with distinct response times. Results for the neutron sensitivity of various types of SPNDs are in excellent agreement with experimental data obtained at the BR2 research reactor. For typical neutron to gamma flux ratios, the calculated gamma induced SPND currents are significantly lower than the neutron induced currents. The gamma sensitivity depends very strongly upon the immediate detector surroundings and on the gamma spectrum. Our calculation method opens the way to a reliable on-line determination of the absolute in-pile thermal neutron flux. (authors)
Application of a Monte Carlo linac model in routine verifications of dose calculations
International Nuclear Information System (INIS)
Linares Rosales, H. M.; Alfonso Laguardia, R.; Lara Mas, E.; Popescu, T.
2015-01-01
The analysis of some parameters of interest in Radiotherapy Medical Physics based on an experimentally validated Monte Carlo model of an Elekta Precise lineal accelerator, was performed for 6 and 15 Mv photon beams. The simulations were performed using the EGSnrc code. As reference for simulations, the optimal beam parameters values (energy and FWHM) previously obtained were used. Deposited dose calculations in water phantoms were done, on typical complex geometries commonly are used in acceptance and quality control tests, such as irregular and asymmetric fields. Parameters such as MLC scatter, maximum opening or closing position, and the separation between them were analyzed from calculations in water. Similarly simulations were performed on phantoms obtained from CT studies of real patients, making comparisons of the dose distribution calculated with EGSnrc and the dose distribution obtained from the computerized treatment planning systems (TPS) used in routine clinical plans. All the results showed a great agreement with measurements, finding all of them within tolerance limits. These results allowed the possibility of using the developed model as a robust verification tool for validating calculations in very complex situation, where the accuracy of the available TPS could be questionable. (Author)
Single-site Lennard-Jones models via polynomial chaos surrogates of Monte Carlo molecular simulation
Kadoura, Ahmad Salim
2016-06-01
In this work, two Polynomial Chaos (PC) surrogates were generated to reproduce Monte Carlo (MC) molecular simulation results of the canonical (single-phase) and the NVT-Gibbs (two-phase) ensembles for a system of normalized structureless Lennard-Jones (LJ) particles. The main advantage of such surrogates, once generated, is the capability of accurately computing the needed thermodynamic quantities in a few seconds, thus efficiently replacing the computationally expensive MC molecular simulations. Benefiting from the tremendous computational time reduction, the PC surrogates were used to conduct large-scale optimization in order to propose single-site LJ models for several simple molecules. Experimental data, a set of supercritical isotherms, and part of the two-phase envelope, of several pure components were used for tuning the LJ parameters (ε, σ). Based on the conducted optimization, excellent fit was obtained for different noble gases (Ar, Kr, and Xe) and other small molecules (CH4, N2, and CO). On the other hand, due to the simplicity of the LJ model used, dramatic deviations between simulation and experimental data were observed, especially in the two-phase region, for more complex molecules such as CO2 and C2 H6.
Modelling of a general purpose irradiation chamber using a Monte Carlo particle transport code
International Nuclear Information System (INIS)
Dhiyauddin Ahmad Fauzi; Sheik, F.O.A.; Nurul Fadzlin Hasbullah
2013-01-01
Full-text: The aim of this research is to stimulate the effectiveness use of a general purpose irradiation chamber to contain pure neutron particles obtained from a research reactor. The secondary neutron and gamma particles dose discharge from the chamber layers will be used as a platform to estimate the safe dimension of the chamber. The chamber, made up of layers of lead (Pb), shielding, polyethylene (PE), moderator and commercial grade aluminium (Al) cladding is proposed for the use of interacting samples with pure neutron particles in a nuclear reactor environment. The estimation was accomplished through simulation based on general Monte Carlo N-Particle transport code using Los Alamos MCNPX software. Simulations were performed on the model of the chamber subjected to high neutron flux radiation and its gamma radiation product. The model of neutron particle used is based on the neutron source found in PUSPATI TRIGA MARK II research reactor which holds a maximum flux value of 1 x 10 12 neutron/ cm 2 s. The expected outcomes of this research are zero gamma dose in the core of the chamber and neutron dose rate of less than 10 μSv/ day discharge from the chamber system. (author)
Energy Technology Data Exchange (ETDEWEB)
Chiapetto, M., E-mail: mchiapet@sckcen.be [SCK-CEN, Nuclear Materials Science Institute, Boeretang 200, B-2400 Mol (Belgium); Unité Matériaux Et Transformations (UMET), UMR 8207, Université de Lille 1, ENSCL, F-59600 Villeneuve d’Ascq Cedex (France); Messina, L. [DEN-Service de Recherches de Métallurgie Physique, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette (France); KTH Royal Institute of Technology, Roslagstullsbacken 21, SE-114 21 Stockholm (Sweden); Becquart, C.S. [Unité Matériaux Et Transformations (UMET), UMR 8207, Université de Lille 1, ENSCL, F-59600 Villeneuve d’Ascq Cedex (France); Olsson, P. [KTH Royal Institute of Technology, Roslagstullsbacken 21, SE-114 21 Stockholm (Sweden); Malerba, L. [SCK-CEN, Nuclear Materials Science Institute, Boeretang 200, B-2400 Mol (Belgium)
2017-02-15
This work presents a revised set of parameters to be used in an Object kinetic Monte Carlo model to simulate the microstructure evolution under neutron irradiation of reactor pressure vessel steels at the operational temperature of light water reactors (∼300 °C). Within a “grey-alloy” approach, a more physical description than in a previous work is used to translate the effect of Mn and Ni solute atoms on the defect cluster diffusivity reduction. The slowing down of self-interstitial clusters, due to the interaction between solutes and crowdions in Fe is now parameterized using binding energies from the latest DFT calculations and the solute concentration in the matrix from atom-probe experiments. The mobility of vacancy clusters in the presence of Mn and Ni solute atoms was also modified on the basis of recent DFT results, thereby removing some previous approximations. The same set of parameters was seen to predict the correct microstructure evolution for two different types of alloys, under very different irradiation conditions: an Fe-C-MnNi model alloy, neutron irradiated at a relatively high flux, and a high-Mn, high-Ni RPV steel from the Swedish Ringhals reactor surveillance program. In both cases, the predicted self-interstitial loop density matches the experimental solute cluster density, further corroborating the surmise that the MnNi-rich nanofeatures form by solute enrichment of immobilized small interstitial loops, which are invisible to the electron microscope.
Torres, Lizeth
2017-01-01
This book focuses on the analysis and design of advanced techniques for on-line automatic computational monitoring of pipelines and pipe networks. It discusses how to improve the systems’ security considering mathematical models of the flow, historical flow rate and pressure data, with the main goal of reducing the number of sensors installed along a pipeline. The techniques presented in the book have been implemented in digital systems to enhance the abilities of the pipeline network’s operators in recognizing anomalies. A real leak scenario in a Mexican water pipeline is used to illustrate the benefits of these techniques in locating the position of a leak. Intended for an interdisciplinary audience, the book addresses researchers and professionals in the areas of mechanical, civil and control engineering. It covers topics on fluid mechanics, instrumentation, automatic control, signal processing, computing, construction and diagnostic technologies.
An automatic rat brain extraction method based on a deformable surface model.
Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M
2013-08-15
The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
T. A. Mikhailova
2016-01-01
Full Text Available In the paper the algorithm of modeling of continuous low-temperature free-radical butadiene-styrene copolymerization process in emulsion based on the Monte-Carlo method is offered. This process is the cornerstone of industrial production butadiene – styrene synthetic rubber which is the most widespread large-capacity rubber of general purpose. Imitation of growth of each macromolecule of the formed copolymer and tracking of the processes happening to it is the basis of algorithm of modeling. Modeling is carried out taking into account residence-time distribution of particles in system that gives the chance to research the process proceeding in the battery of consistently connected polymerization reactors. At the same time each polymerization reactor represents the continuous stirred tank reactor. Since the process is continuous, it is considered continuous addition of portions to the reaction mixture in the first reactor of battery. The constructed model allows to research molecular-weight and viscous characteristics of the formed copolymerization product, to predict the mass content of butadiene and styrene in copolymer, to carry out calculation of molecular-weight distribution of the received product at any moment of conducting process. According to the results of computational experiments analyzed the influence of mode of the process of the regulator introduced during the maintaining on change of characteristics of the formed butadiene-styrene copolymer. As the considered process takes place with participation of monomers of two types, besides listed the model allows to research compositional heterogeneity of the received product that is to carry out calculation of composite distribution and distribution of macromolecules for the size and structure. On the basis of the proposed algorithm created the software tool that allows you to keep track of changes in the characteristics of the resulting product in the dynamics.
International Nuclear Information System (INIS)
Weathers, J.B.; Luck, R.; Weathers, J.W.
2009-01-01
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
Energy Technology Data Exchange (ETDEWEB)
Weathers, J.B. [Shock, Noise, and Vibration Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: James.Weathers@ngc.com; Luck, R. [Department of Mechanical Engineering, Mississippi State University, 210 Carpenter Engineering Building, P.O. Box ME, Mississippi State, MS 39762-5925 (United States)], E-mail: Luck@me.msstate.edu; Weathers, J.W. [Structural Analysis Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: Jeffrey.Weathers@ngc.com
2009-11-15
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
International Nuclear Information System (INIS)
Parent, Laure; Seco, Joao; Evans, Phil M.; Fielding, Andrew; Dance, David R.
2006-01-01
This study focused on predicting the electronic portal imaging device (EPID) image of intensity modulated radiation treatment (IMRT) fields in the absence of attenuation material in the beam with Monte Carlo methods. As IMRT treatments consist of a series of segments of various sizes that are not always delivered on the central axis, large spectral variations may be observed between the segments. The effect of these spectral variations on the EPID response was studied with fields of various sizes and off-axis positions. A detailed description of the EPID was implemented in a Monte Carlo model. The EPID model was validated by comparing the EPID output factors for field sizes between 1x1 and 26x26 cm 2 at the isocenter. The Monte Carlo simulations agreed with the measurements to within 1.5%. The Monte Carlo model succeeded in predicting the EPID response at the center of the fields of various sizes and offsets to within 1% of the measurements. Large variations (up to 29%) of the EPID response were observed between the various offsets. The EPID response increased with field size and with field offset for most cases. The Monte Carlo model was then used to predict the image of a simple test IMRT field delivered on the beam axis and with an offset. A variation of EPID response up to 28% was found between the on- and off-axis delivery. Finally, two clinical IMRT fields were simulated and compared to the measurements. For all IMRT fields, simulations and measurements agreed within 3%--0.2 cm for 98% of the pixels. The spectral variations were quantified by extracting from the spectra at the center of the fields the total photon yield (Y total ), the photon yield below 1 MeV (Y low ), and the percentage of photons below 1 MeV (P low ). For the studied cases, a correlation was shown between the EPID response variation and Y total , Y low , and P low
Spirou, Spiridon V; Papadimitroulas, Panagiotis; Liakou, Paraskevi; Georgoulias, Panagiotis; Loudos, George
2015-09-01
To present and evaluate a new methodology to investigate the effect of attenuation correction (AC) in single-photon emission computed tomography (SPECT) using textural features analysis, Monte Carlo techniques, and a computational anthropomorphic model. The GATE Monte Carlo toolkit was used to simulate SPECT experiments using the XCAT computational anthropomorphic model, filled with a realistic biodistribution of (99m)Tc-N-DBODC. The simulated gamma camera was the Siemens ECAM Dual-Head, equipped with a parallel hole lead collimator, with an image resolution of 3.54 × 3.54 mm(2). Thirty-six equispaced camera positions, spanning a full 360° arc, were simulated. Projections were calculated after applying a ± 20% energy window or after eliminating all scattered photons. The activity of the radioisotope was reconstructed using the MLEM algorithm. Photon attenuation was accounted for by calculating the radiological pathlength in a perpendicular line from the center of each voxel to the gamma camera. Twenty-two textural features were calculated on each slice, with and without AC, using 16 and 64 gray levels. A mask was used to identify only those pixels that belonged to each organ. Twelve of the 22 features showed almost no dependence on AC, irrespective of the organ involved. In both the heart and the liver, the mean and SD were the features most affected by AC. In the liver, six features were affected by AC only on some slices. Depending on the slice, skewness decreased by 22-34% with AC, kurtosis by 35-50%, long-run emphasis mean by 71-91%, and long-run emphasis range by 62-95%. In contrast, gray-level non-uniformity mean increased by 78-218% compared with the value without AC and run percentage mean by 51-159%. These results were not affected by the number of gray levels (16 vs. 64) or the data used for reconstruction: with the energy window or without scattered photons. The mean and SD were the main features affected by AC. In the heart, no other feature was
Automatic Generation of Cycle-Approximate TLMs with Timed RTOS Model Support
Hwang, Yonghyun; Schirner, Gunar; Abdi, Samar
This paper presents a technique for automatically generating cycle-approximate transaction level models (TLMs) for multi-process applications mapped to embedded platforms. It incorporates three key features: (a) basic block level timing annotation, (b) RTOS model integration, and (c) RTOS overhead delay modeling. The inputs to TLM generation are application C processes and their mapping to processors in the platform. A processor data model, including pipelined datapath, memory hierarchy and branch delay model is used to estimate basic block execution delays. The delays are annotated to the C code, which is then integrated with a generated SystemC RTOS model. Our abstract RTOS provides dynamic scheduling and inter-process communication (IPC) with processor- and RTOS-specific pre-characterized timing. Our experiments using a MP3 decoder and a JPEG encoder show that timed TLMs, with integrated RTOS models, can be automatically generated in less than a minute. Our generated TLMs simulated three times faster than real-time and showed less than 10% timing error compared to board measurements.
Automatic creation of Markov models for reliability assessment of safety instrumented systems
International Nuclear Information System (INIS)
Guo Haitao; Yang Xianhui
2008-01-01
After the release of new international functional safety standards like IEC 61508, people care more for the safety and availability of safety instrumented systems. Markov analysis is a powerful and flexible technique to assess the reliability measurements of safety instrumented systems, but it is fallible and time-consuming to create Markov models manually. This paper presents a new technique to automatically create Markov models for reliability assessment of safety instrumented systems. Many safety related factors, such as failure modes, self-diagnostic, restorations, common cause and voting, are included in Markov models. A framework is generated first based on voting, failure modes and self-diagnostic. Then, repairs and common-cause failures are incorporated into the framework to build a complete Markov model. Eventual simplification of Markov models can be done by state merging. Examples given in this paper show how explosively the size of Markov model increases as the system becomes a little more complicated as well as the advancement of automatic creation of Markov models
Exploring cluster Monte Carlo updates with Boltzmann machines
Wang, Lei
2017-11-01
Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.
Exploring cluster Monte Carlo updates with Boltzmann machines.
Wang, Lei
2017-11-01
Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.
International Nuclear Information System (INIS)
Alcaraz, Olga; Trullàs, Joaquim; Tahara, Shuta; Kawakita, Yukinobu; Takeda, Shin’ichi
2016-01-01
The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å −1 related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.
Energy Technology Data Exchange (ETDEWEB)
Alcaraz, Olga; Trullàs, Joaquim, E-mail: quim.trullas@upc.edu [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Campus Nord UPC B4-B5, 08034 Barcelona (Spain); Tahara, Shuta [Department of Physics and Earth Sciences, Faculty of Science, University of the Ryukyus, Okinawa 903-0213 (Japan); Kawakita, Yukinobu [J-PARC Center, Japan Atomic Energy Agency (JAEA), Ibaraki 319-1195 (Japan); Takeda, Shin’ichi [Department of Physics, Faculty of Sciences, Kyushu University, Fukuoka 819-0395 (Japan)
2016-09-07
The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å{sup −1} related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.
Automatic generation of statistical pose and shape models for articulated joints.
Xin Chen; Graham, Jim; Hutchinson, Charles; Muir, Lindsay
2014-02-01
Statistical analysis of motion patterns of body joints is potentially useful for detecting and quantifying pathologies. However, building a statistical motion model across different subjects remains a challenging task, especially for a complex joint like the wrist. We present a novel framework for simultaneous registration and segmentation of multiple 3-D (CT or MR) volumes of different subjects at various articulated positions. The framework starts with a pose model generated from 3-D volumes captured at different articulated positions of a single subject (template). This initial pose model is used to register the template volume to image volumes from new subjects. During this process, the Grow-Cut algorithm is used in an iterative refinement of the segmentation of the bone along with the pose parameters. As each new subject is registered and segmented, the pose model is updated, improving the accuracy of successive registrations. We applied the algorithm to CT images of the wrist from 25 subjects, each at five different wrist positions and demonstrated that it performed robustly and accurately. More importantly, the resulting segmentations allowed a statistical pose model of the carpal bones to be generated automatically without interaction. The evaluation results show that our proposed framework achieved accurate registration with an average mean target registration error of 0.34 ±0.27 mm. The automatic segmentation results also show high consistency with the ground truth obtained semi-automatically. Furthermore, we demonstrated the capability of the resulting statistical pose and shape models by using them to generate a measurement tool for scaphoid-lunate dissociation diagnosis, which achieved 90% sensitivity and specificity.
International Nuclear Information System (INIS)
Orkoulas, G.; Panagiotopoulos, A.Z.
1994-01-01
In this work, we investigate the liquid--vapor phase transition of the restricted primitive model of ionic fluids. We show that at the low temperatures where the phase transition occurs, the system cannot be studied by conventional molecular simulation methods because convergence to equilibrium is slow. To accelerate convergence, we propose cluster Monte Carlo moves capable of moving more than one particle at a time. We then address the issue of charged particle transfers in grand canonical and Gibbs ensemble Monte Carlo simulations, for which we propose a biased particle insertion/destruction scheme capable of sampling short interparticle distances. We compute the chemical potential for the restricted primitive model as a function of temperature and density from grand canonical Monte Carlo simulations and the phase envelope from Gibbs Monte Carlo simulations. Our calculated phase coexistence curve is in agreement with recent results of Caillol obtained on the four-dimensional hypersphere and our own earlier Gibbs ensemble simulations with single-ion transfers, with the exception of the critical temperature, which is lower in the current calculations. Our best estimates for the critical parameters are T * c =0.053, ρ * c =0.025. We conclude with possible future applications of the biased techniques developed here for phase equilibrium calculations for ionic fluids
Directory of Open Access Journals (Sweden)
Kępisty Grzegorz
2015-09-01
Full Text Available In this paper, we compare the methodology of different time-step models in the context of Monte Carlo burnup calculations for nuclear reactors. We discuss the differences between staircase step model, slope model, bridge scheme and stochastic implicit Euler method proposed in literature. We focus on the spatial stability of depletion procedure and put additional emphasis on the problem of normalization of neutron source strength. Considered methodology has been implemented in our continuous energy Monte Carlo burnup code (MCB5. The burnup simulations have been performed using the simplified high temperature gas-cooled reactor (HTGR system with and without modeling of control rod withdrawal. Useful conclusions have been formulated on the basis of results.
Single-site Lennard-Jones models via polynomial chaos surrogates of Monte Carlo molecular simulation
Kadoura, Ahmad Salim; Siripatana, Adil; Sun, Shuyu; Knio, Omar; Hoteit, Ibrahim
2016-01-01
In this work, two Polynomial Chaos (PC) surrogates were generated to reproduce Monte Carlo (MC) molecular simulation results of the canonical (single-phase) and the NVT-Gibbs (two-phase) ensembles for a system of normalized structureless Lennard
Zhang, D.; Liao, Q.
2016-12-01
The Bayesian inference provides a convenient framework to solve statistical inverse problems. In this method, the parameters to be identified are treated as random variables. The prior knowledge, the system nonlinearity, and the measurement errors can be directly incorporated in the posterior probability density function (PDF) of the parameters. The Markov chain Monte Carlo (MCMC) method is a powerful tool to generate samples from the posterior PDF. However, since the MCMC usually requires thousands or even millions of forward simulations, it can be a computationally intensive endeavor, particularly when faced with large-scale flow and transport models. To address this issue, we construct a surrogate system for the model responses in the form of polynomials by the stochastic collocation method. In addition, we employ interpolation based on the nested sparse grids and takes into account the different importance of the parameters, under the condition of high random dimensions in the stochastic space. Furthermore, in case of low regularity such as discontinuous or unsmooth relation between the input parameters and the output responses, we introduce an additional transform process to improve the accuracy of the surrogate model. Once we build the surrogate system, we may evaluate the likelihood with very little computational cost. We analyzed the convergence rate of the forward solution and the surrogate posterior by Kullback-Leibler divergence, which quantifies the difference between probability distributions. The fast convergence of the forward solution implies fast convergence of the surrogate posterior to the true posterior. We also tested the proposed algorithm on water-flooding two-phase flow reservoir examples. The posterior PDF calculated from a very long chain with direct forward simulation is assumed to be accurate. The posterior PDF calculated using the surrogate model is in reasonable agreement with the reference, revealing a great improvement in terms of
Evtushenko, V. F.; Myshlyaev, L. P.; Makarov, G. V.; Ivushkin, K. A.; Burkova, E. V.
2016-10-01
The structure of multi-variant physical and mathematical models of control system is offered as well as its application for adjustment of automatic control system (ACS) of production facilities on the example of coal processing plant.
Wang, Yuting; Xu, Lixin
2010-01-01
In this paper, the holographic dark energy model with new infrared (IR) cut-off for both the flat case and the non-flat case are confronted with the combined constraints of current cosmological observations: type Ia Supernovae, Baryon Acoustic Oscillations, current Cosmic Microwave Background, and the observational hubble data. By utilizing the Markov Chain Monte Carlo (MCMC) method, we obtain the best fit values of the parameters with $1\\sigma, 2\\sigma$ errors in the flat model: $\\Omega_{b}h...
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.
International Nuclear Information System (INIS)
Blevin, H.A.; Fletcher, J.; Hunter, S.R.
1978-05-01
In a recent paper, a Monte-Carlo simulation of electron swarms in hydrogen using an isotropic scattering model was reported. In this previous work discrepancies between the predicted and measured electron transport parameters were observed. In this paper a far more realistic anisotropic scattering model is used. Good agreement between predicted and experimental data is observed and the simulation code has been used to calculate various parameters which are not directly measurable
A virtual source model for Monte Carlo simulation of helical tomotherapy.
Yuan, Jiankui; Rong, Yi; Chen, Quan
2015-01-08
The purpose of this study was to present a Monte Carlo (MC) simulation method based on a virtual source, jaw, and MLC model to calculate dose in patient for helical tomotherapy without the need of calculating phase-space files (PSFs). Current studies on the tomotherapy MC simulation adopt a full MC model, which includes extensive modeling of radiation source, primary and secondary jaws, and multileaf collimator (MLC). In the full MC model, PSFs need to be created at different scoring planes to facilitate the patient dose calculations. In the present work, the virtual source model (VSM) we established was based on the gold standard beam data of a tomotherapy unit, which can be exported from the treatment planning station (TPS). The TPS-generated sinograms were extracted from the archived patient XML (eXtensible Markup Language) files. The fluence map for the MC sampling was created by incorporating the percentage leaf open time (LOT) with leaf filter, jaw penumbra, and leaf latency contained from sinogram files. The VSM was validated for various geometry setups and clinical situations involving heterogeneous media and delivery quality assurance (DQA) cases. An agreement of < 1% was obtained between the measured and simulated results for percent depth doses (PDDs) and open beam profiles for all three jaw settings in the VSM commissioning. The accuracy of the VSM leaf filter model was verified in comparing the measured and simulated results for a Picket Fence pattern. An agreement of < 2% was achieved between the presented VSM and a published full MC model for heterogeneous phantoms. For complex clinical head and neck (HN) cases, the VSM-based MC simulation of DQA plans agreed with the film measurement with 98% of planar dose pixels passing on the 2%/2 mm gamma criteria. For patient treatment plans, results showed comparable dose-volume histograms (DVHs) for planning target volumes (PTVs) and organs at risk (OARs). Deviations observed in this study were consistent
Development of the Automatic Modeling System for Reaction Mechanisms Using REX+JGG
Takahashi, Takahiro; Kawai, Kohei; Nakai, Hiroyuki; Ema, Yoshinori
The identification of appropriate reaction models is very helpful for developing chemical vapor deposition (CVD) processes. In this study, we developed an automatic modeling system that analyzes experimental data on the cross- sectional shapes of films deposited on substrates with nanometer- or micrometer-sized trenches. The system then identifies a suitable reaction model to describe the film deposition. The inference engine used by the system to model the reaction mechanism was designed using real-coded genetic algorithms (RCGAs): a generation alternation model named "just generation gap" (JGG) and a real-coded crossover named "real-coded ensemble crossover" (REX). We studied the effect of REX+JGG on the system's performance, and found that the system with REX+JGG was the most accurate and reliable at model identification among the algorithms that we studied.
Sengupta, D.; Gao, L.; Wilcox, E. M.; Beres, N. D.; Moosmüller, H.; Khlystov, A.
2017-12-01
wavelength range (300 nm - 2000 nm). Results will be compared with the SNICAR model to better understand the differences in snow albedo computation between plane-parallel methods and the statistical Monte Carlo methods.
Comparison of serological and milk tests for bovine brucellosis using a Monte Carlo simulation model
Directory of Open Access Journals (Sweden)
V. Caporale
2004-01-01
Full Text Available European Union (EU Directive 97/12/EC allows the trade of cattle within the EU of animals originating from an 'officially brucellosis-free herd'. To qualify for this status, a number of different programmes must be implemented. Each EU Member Country is free to decide which procedure to use to qualify herds. The authors conducted a study to compare the merits and costs of testing programmes given in the Directive and of some alternative testing strategies. The effectiveness of testing programmes was evaluated by a Monte Carlo simulation model. Programmes listed in the Directive do not appear to have identical sensitivity and specificity. Simulations of the programmes showed that milk testing may be more effective and efficient than blood testing to identify infected herds. Results indicated that it could be advisable that legislation, rather than defining very detailed procedures both for laboratory tests and testing programmes, should establish minimal requirements in terms of efficacy of testing procedures (i.e. the probability of detecting an infected herd.
Monte Carlo simulations of the Spin-2 Blume-Emery-Griffiths model
International Nuclear Information System (INIS)
Iwashita, Takashi; Uragami, Kakuko; Muraoka, Yoshinori; Kinoshita, Takehiro; Idogaki, Toshihiro
2010-01-01
The magnetic properties of the spin S = 2 Ising system with the bilinear exchange interaction J 1 S iz S jz , the biquadratic exchange interaction J 2 S iz 2 S jz 2 and the single-ion anisotropy DS iz 2 are discussed by making use of the Monte Carlo (MC) simulation for the magnetization z >, sub-lattice magnetizations z (A)> and z (B)>, the magnetic specific heat C M and spin structures. This Ising spin system of S = 2 with interactions J 1 and J 2 and with anisotropy D corresponds to the spin-2 Blume-Emery-Griffiths model. The phase diagram of this Ising spin system on a two-dimensional square lattice has been obtained for exchange parameter J 2 /J 1 and anisotropy parameter D/J 1 . The shapes of the temperature dependence of sublattice magnetizations z (A)> and z (B)> are related with abnormal behavior of temperature dependence of z > at low temperatures and affected significantly by the single-ion anisotropy D. The staggered quadrupolar (SQ) ordering turns out to be different largely between Ising systems with the single-ion anisotropy (D ≠ 0) and without the one (D 0).
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.
Aoun, Bachir
2016-05-05
A new Reverse Monte Carlo (RMC) package "fullrmc" for atomic or rigid body and molecular, amorphous, or crystalline materials is presented. fullrmc main purpose is to provide a fully modular, fast and flexible software, thoroughly documented, complex molecules enabled, written in a modern programming language (python, cython, C and C++ when performance is needed) and complying to modern programming practices. fullrmc approach in solving an atomic or molecular structure is different from existing RMC algorithms and software. In a nutshell, traditional RMC methods and software randomly adjust atom positions until the whole system has the greatest consistency with a set of experimental data. In contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While fullrmc allows running traditional RMC modeling, the uniqueness of this approach resides in its ability to customize grouping atoms in any convenient way with no additional programming efforts and to apply smart and more physically meaningful moves to the defined groups of atoms. In addition, fullrmc provides a unique way with almost no additional computational cost to recur a group's selection, allowing the system to go out of local minimas by refining a group's position or exploring through and beyond not allowed positions and energy barriers the unrestricted three dimensional space around a group. © 2016 Wiley Periodicals, Inc.
Monte Carlo modeling for realizing optimized management of failed fuel replacement
International Nuclear Information System (INIS)
Morishita, Kazunori; Yamamoto, Yasunori; Nakasuji, Toshiki
2014-01-01
Fuel cladding is one of the key components in a fission reactor to keep confining radioactive materials inside a fuel tube. During reactor operation, the cladding is however sometimes breached and radioactive materials leak from the fuel ceramic pellet into the coolant water through the breach. The primary coolant water is therefore monitored so that any leak is quickly detected, where the coolant water is periodically sampled and the concentration of, for example the radioactive iodine 131 (I-131), is measured. Depending on the measured concentration, the faulty fuel assembly with leaking rod is removed from the reactor and replaced by new one immediately or at the next refueling. In the present study, an effort has been made to develop a methodology to optimize the management for replacement of failed fuels due to cladding failures using the I-131 concentration measured in the sampled coolant water. A model numerical equation is proposed to describe the time evolution of I-131 concentration due to fuel leaks, and is then solved using the Monte-Carlo method as a function of sampling rate. Our results have indicated that, in order to achieve the rationalized management of failed fuels, higher resolution to detect a small amount of I-131 is not necessarily required but more frequent sampling is favorable. (author)
Dana, Nicholas; Sowers, Timothy; Karpiouk, Andrei; Vanderlaan, Donald; Emelianov, Stanislav
2017-10-01
Coronary heart disease (the presence of coronary atherosclerotic plaques) is a significant health problem in the industrialized world. A clinical method to accurately visualize and characterize atherosclerotic plaques is needed. Intravascular photoacoustic (IVPA) imaging is being developed to fill this role, but questions remain regarding optimal imaging wavelengths. We utilized a Monte Carlo optical model to simulate IVPA excitation in coronary tissues, identifying optimal wavelengths for plaque characterization. Near-infrared wavelengths (≤1800 nm) were simulated, and single- and dual-wavelength data were analyzed for accuracy of plaque characterization. Results indicate light penetration is best in the range of 1050 to 1370 nm, where 5% residual fluence can be achieved at clinically relevant depths of ≥2 mm in arteries. Across the arterial wall, fluence may vary by over 10-fold, confounding plaque characterization. For single-wavelength results, plaque segmentation accuracy peaked at 1210 and 1720 nm, though correlation was poor (blood, a primary and secondary wavelength near 1210 and 1350 nm, respectively, may offer the best implementation of dual-wavelength IVPA imaging. These findings could guide the development of a cost-effective clinical system by highlighting optimal wavelengths and improving plaque characterization.
Monte Carlo Modeling of Sodium in Mercury's Exosphere During the First Two MESSENGER Flybys
Burger, Matthew H.; Killen, Rosemary M.; Vervack, Ronald J., Jr.; Bradley, E. Todd; McClintock, William E.; Sarantos, Menelaos; Benna, Mehdi; Mouawad, Nelly
2010-01-01
We present a Monte Carlo model of the distribution of neutral sodium in Mercury's exosphere and tail using data from the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) on the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft during the first two flybys of the planet in January and September 2008. We show that the dominant source mechanism for ejecting sodium from the surface is photon-stimulated desorption (PSD) and that the desorption rate is limited by the diffusion rate of sodium from the interior of grains in the regolith to the topmost few monolayers where PSD is effective. In the absence of ion precipitation, we find that the sodium source rate is limited to approximately 10(exp 6) - 10(exp 7) per square centimeter per second, depending on the sticking efficiency of exospheric sodium that returns to the surface. The diffusion rate must be at least a factor of 5 higher in regions of ion precipitation to explain the MASCS observations during the second MESSENGER f1yby. We estimate that impact vaporization of micrometeoroids may provide up to 15% of the total sodium source rate in the regions observed. Although sputtering by precipitating ions was found not to be a significant source of sodium during the MESSENGER flybys, ion precipitation is responsible for increasing the source rate at high latitudes through ion-enhanced diffusion.
Monte Carlo study of the double and super-exchange model with lattice distortion
Energy Technology Data Exchange (ETDEWEB)
Suarez, J R; Vallejo, E; Navarro, O [Instituto de Investigaciones en Materiales, Universidad Nacional Autonoma de Mexico, Apartado Postal 70-360, 04510 Mexico D. F. (Mexico); Avignon, M, E-mail: jrsuarez@iim.unam.m [Institut Neel, Centre National de la Recherche Scientifique (CNRS) and Universite Joseph Fourier, BP 166, 38042 Grenoble Cedex 9 (France)
2009-05-01
In this work a magneto-elastic phase transition was obtained in a linear chain due to the interplay between magnetism and lattice distortion in a double and super-exchange model. It is considered a linear chain consisting of localized classical spins interacting with itinerant electrons. Due to the double exchange interaction, localized spins tend to align ferromagnetically. This ferromagnetic tendency is expected to be frustrated by anti-ferromagnetic super-exchange interactions between neighbor localized spins. Additionally, lattice parameter is allowed to have small changes, which contributes harmonically to the energy of the system. Phase diagram is obtained as a function of the electron density and the super-exchange interaction using a Monte Carlo minimization. At low super-exchange interaction energy phase transition between electron-full ferromagnetic distorted and electron-empty anti-ferromagnetic undistorted phases occurs. In this case all electrons and lattice distortions were found within the ferromagnetic domain. For high super-exchange interaction energy, phase transition between two site distorted periodic arrangement of independent magnetic polarons ordered anti-ferromagnetically and the electron-empty anti-ferromagnetic undistorted phase was found. For this high interaction energy, Wigner crystallization, lattice distortion and charge distribution inside two-site polarons were obtained.
Modeling the biophysical effects in a carbon beam delivery line by using Monte Carlo simulations
Cho, Ilsung; Yoo, SeungHoon; Cho, Sungho; Kim, Eun Ho; Song, Yongkeun; Shin, Jae-ik; Jung, Won-Gyun
2016-09-01
The Relative biological effectiveness (RBE) plays an important role in designing a uniform dose response for ion-beam therapy. In this study, the biological effectiveness of a carbon-ion beam delivery system was investigated using Monte Carlo simulations. A carbon-ion beam delivery line was designed for the Korea Heavy Ion Medical Accelerator (KHIMA) project. The GEANT4 simulation tool kit was used to simulate carbon-ion beam transport into media. An incident energy carbon-ion beam with energy in the range between 220 MeV/u and 290 MeV/u was chosen to generate secondary particles. The microdosimetric-kinetic (MK) model was applied to describe the RBE of 10% survival in human salivary-gland (HSG) cells. The RBE weighted dose was estimated as a function of the penetration depth in the water phantom along the incident beam's direction. A biologically photon-equivalent Spread Out Bragg Peak (SOBP) was designed using the RBE-weighted absorbed dose. Finally, the RBE of mixed beams was predicted as a function of the depth in the water phantom.
Reliability of Monte Carlo simulations in modeling neutron yields from a shielded fission source
Energy Technology Data Exchange (ETDEWEB)
McArthur, Matthew S., E-mail: matthew.s.mcarthur@gmail.com; Rees, Lawrence B., E-mail: Lawrence_Rees@byu.edu; Czirr, J. Bart, E-mail: czirr@juno.com
2016-08-11
Using the combination of a neutron-sensitive {sup 6}Li glass scintillator detector with a neutron-insensitive {sup 7}Li glass scintillator detector, we are able to make an accurate measurement of the capture rate of fission neutrons on {sup 6}Li. We used this detector with a {sup 252}Cf neutron source to measure the effects of both non-borated polyethylene and 5% borated polyethylene shielding on detection rates over a range of shielding thicknesses. Both of these measurements were compared with MCNP calculations to determine how well the calculations reproduced the measurements. When the source is highly shielded, the number of interactions experienced by each neutron prior to arriving at the detector is large, so it is important to compare Monte Carlo modeling with actual experimental measurements. MCNP reproduces the data fairly well, but it does generally underestimate detector efficiency both with and without polyethylene shielding. For non-borated polyethylene it underestimates the measured value by an average of 8%. This increases to an average of 11% for borated polyethylene.
Monte Carlo modeling of transport in PbSe nanocrystal films
Energy Technology Data Exchange (ETDEWEB)
Carbone, I., E-mail: icarbone@ucsc.edu; Carter, S. A. [University of California, Santa Cruz, California 95060 (United States); Zimanyi, G. T. [University of California, Davis, California 95616 (United States)
2013-11-21
A Monte Carlo hopping model was developed to simulate electron and hole transport in nanocrystalline PbSe films. Transport is carried out as a series of thermally activated hopping events between neighboring sites on a cubic lattice. Each site, representing an individual nanocrystal, is assigned a size-dependent electronic structure, and the effects of particle size, charging, interparticle coupling, and energetic disorder on electron and hole mobilities were investigated. Results of simulated field-effect measurements confirm that electron mobilities and conductivities at constant carrier densities increase with particle diameter by an order of magnitude up to 5 nm and begin to decrease above 6 nm. We find that as particle size increases, fewer hops are required to traverse the same distance and that site energy disorder significantly inhibits transport in films composed of smaller nanoparticles. The dip in mobilities and conductivities at larger particle sizes can be explained by a decrease in tunneling amplitudes and by charging penalties that are incurred more frequently when carriers are confined to fewer, larger nanoparticles. Using a nearly identical set of parameter values as the electron simulations, hole mobility simulations confirm measurements that increase monotonically with particle size over two orders of magnitude.
Verification of the VEF photon beam model for dose calculations by the voxel-Monte-Carlo-algorithm
International Nuclear Information System (INIS)
Kriesen, S.; Fippel, M.
2005-01-01
The VEF linac head model (VEF, virtual energy fluence) was developed at the University of Tuebingen to determine the primary fluence for calculations of dose distributions in patients by the Voxel-Monte-Carlo-Algorithm (XVMC). This analytical model can be fitted to any therapy accelerator head by measuring only a few basic dose data; therefore, time-consuming Monte-Carlo simulations of the linac head become unnecessary. The aim of the present study was the verification of the VEF model by means of water-phantom measurements, as well as the comparison of this system with a common analytical linac head model of a commercial planning system (TMS, formerly HELAX or MDS Nordion, respectively). The results show that both the VEF and the TMS models can very well simulate the primary fluence. However, the VEF model proved superior in the simulations of scattered radiation and in the calculations of strongly irregular MLC fields. Thus, an accurate and clinically practicable tool for the determination of the primary fluence for Monte-Carlo-Simulations with photons was established, especially for the use in IMRT planning. (orig.)
Kriesen, Stephan; Fippel, Matthias
2005-01-01
The VEF linac head model (VEF, virtual energy fluence) was developed at the University of Tübingen to determine the primary fluence for calculations of dose distributions in patients by the Voxel-Monte-Carlo-Algorithm (XVMC). This analytical model can be fitted to any therapy accelerator head by measuring only a few basic dose data; therefore, time-consuming Monte-Carlo simulations of the linac head become unnecessary. The aim of the present study was the verification of the VEF model by means of water-phantom measurements, as well as the comparison of this system with a common analytical linac head model of a commercial planning system (TMS, formerly HELAX or MDS Nordion, respectively). The results show that both the VEF and the TMS models can very well simulate the primary fluence. However, the VEF model proved superior in the simulations of scattered radiation and in the calculations of strongly irregular MLC fields. Thus, an accurate and clinically practicable tool for the determination of the primary fluence for Monte-Carlo-Simulations with photons was established, especially for the use in IMRT planning.
Method for Automatic Selection of Parameters in Normal Tissue Complication Probability Modeling.
Christophides, Damianos; Appelt, Ane L; Gusnanto, Arief; Lilley, John; Sebag-Montefiore, David
2018-07-01
To present a fully automatic method to generate multiparameter normal tissue complication probability (NTCP) models and compare its results with those of a published model, using the same patient cohort. Data were analyzed from 345 rectal cancer patients treated with external radiation therapy to predict the risk of patients developing grade 1 or ≥2 cystitis. In total, 23 clinical factors were included in the analysis as candidate predictors of cystitis. Principal component analysis was used to decompose the bladder dose-volume histogram into 8 principal components, explaining more than 95% of the variance. The data set of clinical factors and principal components was divided into training (70%) and test (30%) data sets, with the training data set used by the algorithm to compute an NTCP model. The first step of the algorithm was to obtain a bootstrap sample, followed by multicollinearity reduction using the variance inflation factor and genetic algorithm optimization to determine an ordinal logistic regression model that minimizes the Bayesian information criterion. The process was repeated 100 times, and the model with the minimum Bayesian information criterion was recorded on each iteration. The most frequent model was selected as the final "automatically generated model" (AGM). The published model and AGM were fitted on the training data sets, and the risk of cystitis was calculated. The 2 models had no significant differences in predictive performance, both for the training and test data sets (P value > .05) and found similar clinical and dosimetric factors as predictors. Both models exhibited good explanatory performance on the training data set (P values > .44), which was reduced on the test data sets (P values < .05). The predictive value of the AGM is equivalent to that of the expert-derived published model. It demonstrates potential in saving time, tackling problems with a large number of parameters, and standardizing variable selection in NTCP
Microscopic calculation of level densities: the shell model Monte Carlo approach
International Nuclear Information System (INIS)
Alhassid, Yoram
2012-01-01
The shell model Monte Carlo (SMMC) approach provides a powerful technique for the microscopic calculation of level densities in model spaces that are many orders of magnitude larger than those that can be treated by conventional methods. We discuss a number of developments: (i) Spin distribution. We used a spin projection method to calculate the exact spin distribution of energy levels as a function of excitation energy. In even-even nuclei we find an odd-even staggering effect (in spin). Our results were confirmed in recent analysis of experimental data. (ii) Heavy nuclei. The SMMC approach was extended to heavy nuclei. We have studied the crossover between vibrational and rotational collectivity in families of samarium and neodymium isotopes in model spaces of dimension approx. 10 29 . We find good agreement with experimental results for both state densities and 2 > (where J is the total spin). (iii) Collective enhancement factors. We have calculated microscopically the vibrational and rotational enhancement factors of level densities versus excitation energy. We find that the decay of these enhancement factors in heavy nuclei is correlated with the pairing and shape phase transitions. (iv) Odd-even and odd-odd nuclei. The projection on an odd number of particles leads to a sign problem in SMMC. We discuss a novel method to calculate state densities in odd-even and odd-odd nuclei despite the sign problem. (v) State densities versus level densities. The SMMC approach has been used extensively to calculate state densities. However, experiments often measure level densities (where levels are counted without including their spin degeneracies.) A spin projection method enables us to also calculate level densities in SMMC. We have calculated the SMMC level density of 162 Dy and found it to agree well with experiments
A Monte Carlo Approach to Modeling Wildfire Risk on Changing Landscapes
Burzynski, A. M.; Beavers, A.
2016-12-01
The U.S. Department of Defense (DoD) maintains approximately 28 million acres of land across 420 of their largest installations. These sites harbored 425 federally listed Threatened and Endangered species as of 2013, representing a density of rare species that is several times greater than any other land management agency in the U.S. This is a major driver of DoD natural resources policy and many of these species are affected by wildland fire, both positively and negatively. Military installations collectively experience thousands of wildfires per year, and the majority of ignitions are caused by mission and training activities that can be planned to accommodate fire risk. Motivated by the need for accurately modeled wildfire under the unique land-use conditions of military installations and the assessment of risk exposure at installations throughout the U.S., we developed custom, FARSITE-based scientific software that applies a Monte Carlo approach to wildfire risk analysis. This simulation accounts for the dynamics of vegetation and weather over time, as well as the spatial and temporal distribution of wildfire ignitions, and can be applied to landscapes up to several million acres in size. The data-driven simulation provides insight that feeds directly into mitigation decision-making and can be used to assess future risk scenarios, both real and hypothetical. We highlight an example of a future scenario comparing wildfire behavior between unmitigated fuels and one in which a prescribed burn program is implemented. The same process can be used for a variety of scenarios including changes in vegetation (e.g. new or altered grazing regimes, extreme weather, or drought) and changes in spatiotemporal ignition probability. The modeling capabilities that we apply to predicting wildfire risk on military lands are also relevant to the greater scientific community for modeling wildland fire in the context of environmental change, historical ecology, or climate change.
A single-source photon source model of a linear accelerator for Monte Carlo dose calculation.
Nwankwo, Obioma; Glatting, Gerhard; Wenz, Frederik; Fleckenstein, Jens
2017-01-01
To introduce a new method of deriving a virtual source model (VSM) of a linear accelerator photon beam from a phase space file (PSF) for Monte Carlo (MC) dose calculation. A PSF of a 6 MV photon beam was generated by simulating the interactions of primary electrons with the relevant geometries of a Synergy linear accelerator (Elekta AB, Stockholm, Sweden) and recording the particles that reach a plane 16 cm downstream the electron source. Probability distribution functions (PDFs) for particle positions and energies were derived from the analysis of the PSF. These PDFs were implemented in the VSM using inverse transform sampling. To model particle directions, the phase space plane was divided into a regular square grid. Each element of the grid corresponds to an area of 1 mm2 in the phase space plane. The average direction cosines, Pearson correlation coefficient (PCC) between photon energies and their direction cosines, as well as the PCC between the direction cosines were calculated for each grid element. Weighted polynomial surfaces were then fitted to these 2D data. The weights are used to correct for heteroscedasticity across the phase space bins. The directions of the particles created by the VSM were calculated from these fitted functions. The VSM was validated against the PSF by comparing the doses calculated by the two methods for different square field sizes. The comparisons were performed with profile and gamma analyses. The doses calculated with the PSF and VSM agree to within 3% /1 mm (>95% pixel pass rate) for the evaluated fields. A new method of deriving a virtual photon source model of a linear accelerator from a PSF file for MC dose calculation was developed. Validation results show that the doses calculated with the VSM and the PSF agree to within 3% /1 mm.
A single-source photon source model of a linear accelerator for Monte Carlo dose calculation.
Directory of Open Access Journals (Sweden)
Obioma Nwankwo
Full Text Available To introduce a new method of deriving a virtual source model (VSM of a linear accelerator photon beam from a phase space file (PSF for Monte Carlo (MC dose calculation.A PSF of a 6 MV photon beam was generated by simulating the interactions of primary electrons with the relevant geometries of a Synergy linear accelerator (Elekta AB, Stockholm, Sweden and recording the particles that reach a plane 16 cm downstream the electron source. Probability distribution functions (PDFs for particle positions and energies were derived from the analysis of the PSF. These PDFs were implemented in the VSM using inverse transform sampling. To model particle directions, the phase space plane was divided into a regular square grid. Each element of the grid corresponds to an area of 1 mm2 in the phase space plane. The average direction cosines, Pearson correlation coefficient (PCC between photon energies and their direction cosines, as well as the PCC between the direction cosines were calculated for each grid element. Weighted polynomial surfaces were then fitted to these 2D data. The weights are used to correct for heteroscedasticity across the phase space bins. The directions of the particles created by the VSM were calculated from these fitted functions. The VSM was validated against the PSF by comparing the doses calculated by the two methods for different square field sizes. The comparisons were performed with profile and gamma analyses.The doses calculated with the PSF and VSM agree to within 3% /1 mm (>95% pixel pass rate for the evaluated fields.A new method of deriving a virtual photon source model of a linear accelerator from a PSF file for MC dose calculation was developed. Validation results show that the doses calculated with the VSM and the PSF agree to within 3% /1 mm.
Kirkby, Charles; Ghasroddashti, Esmaeel; Kovalchuk, Anna; Kolb, Bryan; Kovalchuk, Olga
2013-09-01
In radiation biology, rats are often irradiated, but the precise dose distributions are often lacking, particularly in areas that receive scatter radiation. We used a non-dedicated set of resources to calculate detailed dose distributions, including doses to peripheral organs well outside of the primary field, in common rat exposure settings. We conducted a detailed dose reconstruction in a rat through an analog to the conventional human treatment planning process. The process consisted of: (i) Characterizing source properties of an X-ray irradiator system, (ii) acquiring a computed tomography (CT) scan of a rat model, and (iii) using a Monte Carlo (MC) dose calculation engine to generate the dose distribution within the rat model. We considered cranial and liver irradiation scenarios where the rest of the body was protected by a lead shield. Organs of interest were the brain, liver and gonads. The study also included paired scenarios where the dose to adjacent, shielded rats was determined as a potential control for analysis of bystander effects. We established the precise doses and dose distributions delivered to the peripheral organs in single and paired rats. Mean doses to non-targeted organs in irradiated rats ranged from 0.03-0.1% of the reference platform dose. Mean doses to the adjacent rat peripheral organs were consistent to within 10% those of the directly irradiated rat. This work provided details of dose distributions in rat models under common irradiation conditions and established an effective scenario for delivering only scattered radiation consistent with that in a directly irradiated rat.
A Monte Carlo multiple source model applied to radiosurgery narrow photon beams
International Nuclear Information System (INIS)
Chaves, A.; Lopes, M.C.; Alves, C.C.; Oliveira, C.; Peralta, L.; Rodrigues, P.; Trindade, A.
2004-01-01
Monte Carlo (MC) methods are nowadays often used in the field of radiotherapy. Through successive steps, radiation fields are simulated, producing source Phase Space Data (PSD) that enable a dose calculation with good accuracy. Narrow photon beams used in radiosurgery can also be simulated by MC codes. However, the poor efficiency in simulating these narrow photon beams produces PSD whose quality prevents calculating dose with the required accuracy. To overcome this difficulty, a multiple source model was developed that enhances the quality of the reconstructed PSD, reducing also the time and storage capacities. This multiple source model was based on the full MC simulation, performed with the MC code MCNP4C, of the Siemens Mevatron KD2 (6 MV mode) linear accelerator head and additional collimators. The full simulation allowed the characterization of the particles coming from the accelerator head and from the additional collimators that shape the narrow photon beams used in radiosurgery treatments. Eight relevant photon virtual sources were identified from the full characterization analysis. Spatial and energy distributions were stored in histograms for the virtual sources representing the accelerator head components and the additional collimators. The photon directions were calculated for virtual sources representing the accelerator head components whereas, for the virtual sources representing the additional collimators, they were recorded into histograms. All these histograms were included in the MC code, DPM code and using a sampling procedure that reconstructed the PSDs, dose distributions were calculated in a water phantom divided in 20000 voxels of 1x1x5 mm 3 . The model accurately calculates dose distributions in the water phantom for all the additional collimators; for depth dose curves, associated errors at 2σ were lower than 2.5% until a depth of 202.5 mm for all the additional collimators and for profiles at various depths, deviations between measured
AUTOMATIC TEXTURE RECONSTRUCTION OF 3D CITY MODEL FROM OBLIQUE IMAGES
Directory of Open Access Journals (Sweden)
J. Kang
2016-06-01
Full Text Available In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.
Matsumoto, Monica M. S.; Beig, Niha G.; Udupa, Jayaram K.; Archer, Steven; Torigian, Drew A.
2014-03-01
Lung cancer is associated with the highest cancer mortality rates among men and women in the United States. The accurate and precise identification of the lymph node stations on computed tomography (CT) images is important for staging disease and potentially for prognosticating outcome in patients with lung cancer, as well as for pretreatment planning and response assessment purposes. To facilitate a standard means of referring to lymph nodes, the International Association for the Study of Lung Cancer (IASLC) has recently proposed a definition of the different lymph node stations and zones in the thorax. However, nodal station identification is typically performed manually by visual assessment in clinical radiology. This approach leaves room for error due to the subjective and potentially ambiguous nature of visual interpretation, and is labor intensive. We present a method of automatically recognizing the mediastinal IASLC-defined lymph node stations by modifying a hierarchical fuzzy modeling approach previously developed for body-wide automatic anatomy recognition (AAR) in medical imagery. Our AAR-lymph node (AAR-LN) system follows the AAR methodology and consists of two steps. In the first step, the various lymph node stations are manually delineated on a set of CT images following the IASLC definitions. These delineations are then used to build a fuzzy hierarchical model of the nodal stations which are considered as 3D objects. In the second step, the stations are automatically located on any given CT image of the thorax by using the hierarchical fuzzy model and object recognition algorithms. Based on 23 data sets used for model building, 22 independent data sets for testing, and 10 lymph node stations, a mean localization accuracy of within 1-6 voxels has been achieved by the AAR-LN system.
A Monte Carlo model for mean glandular dose evaluation in spot compression mammography.
Sarno, Antonio; Dance, David R; van Engen, Ruben E; Young, Kenneth C; Russo, Paolo; Di Lillo, Francesca; Mettivier, Giovanni; Bliznakova, Kristina; Fei, Baowei; Sechopoulos, Ioannis
2017-07-01
To characterize the dependence of normalized glandular dose (DgN) on various breast model and image acquisition parameters during spot compression mammography and other partial breast irradiation conditions, and evaluate alternative previously proposed dose-related metrics for this breast imaging modality. Using Monte Carlo simulations with both simple homogeneous breast models and patient-specific breasts, three different dose-related metrics for spot compression mammography were compared: the standard DgN, the normalized glandular dose to only the directly irradiated portion of the breast (DgNv), and the DgN obtained by the product of the DgN for full field irradiation and the ratio of the mid-height area of the irradiated breast to the entire breast area (DgN M ). How these metrics vary with field-of-view size, spot area thickness, x-ray energy, spot area and position, breast shape and size, and system geometry was characterized for the simple breast model and a comparison of the simple model results to those with patient-specific breasts was also performed. The DgN in spot compression mammography can vary considerably with breast area. However, the difference in breast thickness between the spot compressed area and the uncompressed area does not introduce a variation in DgN. As long as the spot compressed area is completely within the breast area and only the compressed breast portion is directly irradiated, its position and size does not introduce a variation in DgN for the homogeneous breast model. As expected, DgN is lower than DgNv for all partial breast irradiation areas, especially when considering spot compression areas within the clinically used range. DgN M underestimates DgN by 6.7% for a W/Rh spectrum at 28 kVp and for a 9 × 9 cm 2 compression paddle. As part of the development of a new breast dosimetry model, a task undertaken by the American Association of Physicists in Medicine and the European Federation of Organizations of Medical Physics
NASCENT: an automatic protein interaction network generation tool for non-model organisms.
Banky, Daniel; Ordog, Rafael; Grolmusz, Vince
2009-04-24
Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.
An effective automatic procedure for testing parameter identifiability of HIV/AIDS models.
Saccomani, Maria Pia
2011-08-01
Realistic HIV models tend to be rather complex and many recent models proposed in the literature could not yet be analyzed by traditional identifiability testing techniques. In this paper, we check a priori global identifiability of some of these nonlinear HIV models taken from the recent literature, by using a differential algebra algorithm based on previous work of the author. The algorithm is implemented in a software tool, called DAISY (Differential Algebra for Identifiability of SYstems), which has been recently released (DAISY is freely available on the web site http://www.dei.unipd.it/~pia/ ). The software can be used to automatically check global identifiability of (linear and) nonlinear models described by polynomial or rational differential equations, thus providing a general and reliable tool to test global identifiability of several HIV models proposed in the literature. It can be used by researchers with a minimum of mathematical background.
Kobayashi, Kiyoshi; Suzuki, Tohru S.
2018-03-01
A new algorithm for the automatic estimation of an equivalent circuit and the subsequent parameter optimization is developed by combining the data-mining concept and complex least-squares method. In this algorithm, the program generates an initial equivalent-circuit model based on the sampling data and then attempts to optimize the parameters. The basic hypothesis is that the measured impedance spectrum can be reproduced by the sum of the partial-impedance spectra presented by the resistor, inductor, resistor connected in parallel to a capacitor, and resistor connected in parallel to an inductor. The adequacy of the model is determined by using a simple artificial-intelligence function, which is applied to the output function of the Levenberg-Marquardt module. From the iteration of model modifications, the program finds an adequate equivalent-circuit model without any user input to the equivalent-circuit model.
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
Integrated Cost and Schedule using Monte Carlo Simulation of a CPM Model - 12419
Energy Technology Data Exchange (ETDEWEB)
Hulett, David T. [Hulett and Associates, LLC (United States); Nosbisch, Michael R. [Project Time and Cost, Inc. (United States)
2012-07-01
This discussion of the recommended practice (RP) 57R-09 of AACE International defines the integrated analysis of schedule and cost risk to estimate the appropriate level of cost and schedule contingency reserve on projects. The main contribution of this RP is to include the impact of schedule risk on cost risk and hence on the need for cost contingency reserves. Additional benefits include the prioritizing of the risks to cost, some of which are risks to schedule, so that risk mitigation may be conducted in a cost-effective way, scatter diagrams of time-cost pairs for developing joint targets of time and cost, and probabilistic cash flow which shows cash flow at different levels of certainty. Integrating cost and schedule risk into one analysis based on the project schedule loaded with costed resources from the cost estimate provides both: (1) more accurate cost estimates than if the schedule risk were ignored or incorporated only partially, and (2) illustrates the importance of schedule risk to cost risk when the durations of activities using labor-type (time-dependent) resources are risky. Many activities such as detailed engineering, construction or software development are mainly conducted by people who need to be paid even if their work takes longer than scheduled. Level-of-effort resources, such as the project management team, are extreme examples of time-dependent resources, since if the project duration exceeds its planned duration the cost of these resources will increase over their budgeted amount. The integrated cost-schedule risk analysis is based on: - A high quality CPM schedule with logic tight enough so that it will provide the correct dates and critical paths during simulation automatically without manual intervention. - A contingency-free estimate of project costs that is loaded on the activities of the schedule. - Resolves inconsistencies between cost estimate and schedule that often creep into those documents as project execution proceeds
Corazza, Stefano; Gambaretto, Emiliano; Mündermann, Lars; Andriacchi, Thomas P
2010-04-01
A novel approach for the automatic generation of a subject-specific model consisting of morphological and joint location information is described. The aim is to address the need for efficient and accurate model generation for markerless motion capture (MMC) and biomechanical studies. The algorithm applied and expanded on previous work on human shapes space by embedding location information for ten joint centers in a subject-specific free-form surface. The optimal locations of joint centers in the 3-D mesh were learned through linear regression over a set of nine subjects whose joint centers were known. The model was shown to be sufficiently accurate for both kinematic (joint centers) and morphological (shape of the body) information to allow accurate tracking with MMC systems. The automatic model generation algorithm was applied to 3-D meshes of different quality and resolution such as laser scans and visual hulls. The complete method was tested using nine subjects of different gender, body mass index (BMI), age, and ethnicity. Experimental training error and cross-validation errors were 19 and 25 mm, respectively, on average over the joints of the ten subjects analyzed in the study.
International Nuclear Information System (INIS)
Mazzurana, M; Sandrini, L; Vaccari, A; Malacarne, C; Cristoforetti, L; Pontalti, R
2003-01-01
Complex permittivity values have a dominant role in the overall consideration of interaction between radiofrequency electromagnetic fields and living matter, and in related applications such as electromagnetic dosimetry. There are still some concerns about the accuracy of published data and about their variability due to the heterogeneous nature of biological tissues. The aim of this study is to provide an alternative semi-automatic method by which numerical dielectric human models for dosimetric studies can be obtained. Magnetic resonance imaging (MRI) tomography was used to acquire images. A new technique was employed to correct nonuniformities in the images and frequency-dependent transfer functions to correlate image intensity with complex permittivity were used. The proposed method provides frequency-dependent models in which permittivity and conductivity vary with continuity-even in the same tissue-reflecting the intrinsic realistic spatial dispersion of such parameters. The human model is tested with an FDTD (finite difference time domain) algorithm at different frequencies; the results of layer-averaged and whole-body-averaged SAR (specific absorption rate) are compared with published work, and reasonable agreement has been found. Due to the short time needed to obtain a whole body model, this semi-automatic method may be suitable for efficient study of various conditions that can determine large differences in the SAR distribution, such as body shape, posture, fat-to-muscle ratio, height and weight
Automatic, Global and Dynamic Student Modeling in a Ubiquitous Learning Environment
Directory of Open Access Journals (Sweden)
Sabine Graf
2009-03-01
Full Text Available Ubiquitous learning allows students to learn at any time and any place. Adaptivity plays an important role in ubiquitous learning, aiming at providing students with adaptive and personalized learning material, activities, and information at the right place and the right time. However, for providing rich adaptivity, the student model needs to be able to gather a variety of information about the students. In this paper, an automatic, global, and dynamic student modeling approach is introduced, which aims at identifying and frequently updating information about students’ progress, learning styles, interests and knowledge level, problem solving abilities, preferences for using the system, social connectivity, and current location. This information is gathered in an automatic way, using students’ behavior and actions in different learning situations provided by different components/services of the ubiquitous learning environment. By providing a comprehensive student model, students can be supported by rich adaptivity in every component/service of the learning environment. Furthermore, the information in the student model can help in giving teachers a better understanding about the students’ learning process.
Directory of Open Access Journals (Sweden)
Polomčić Dušan M.
2015-01-01
Full Text Available The calibration process of hydrodynamic model is done usually manually by 'testing' with different values of hydrogeological parameters and hydraulic characteristics of the boundary conditions. By using the PEST program, automatic calibration of models has been introduced, and it has proved to significantly reduce the subjective influence of the model creator on results. With the relatively new approach of PEST, i.e. with the introduction of so-called 'pilot points', the concept of homogeneous zones with parameter values of porous media or zones with the given boundary conditions has been outdated. However, the consequence of this kind of automatic calibration is that a significant amount of time is required to perform the calculation. The duration of calibration is measured in hours, sometimes even days. PEST contains two modules for the shortening of that process - Parallel PEST and BeoPEST. The paper presents performed experiments and analysis of different cases of PEST module usage, based on which the reduction in the time required to calibrate the model is done.
USING AFFORDABLE DATA CAPTURING DEVICES FOR AUTOMATIC 3D CITY MODELLING
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B. Alizadehashrafi
2017-11-01
Full Text Available In this research project, many movies from UTM Kolej 9, Skudai, Johor Bahru (See Figure 1 were taken by AR. Drone 2. Since the AR drone 2.0 has liquid lens, while flying there were significant distortions and deformations on the converted pictures of the movies. Passive remote sensing (RS applications based on image matching and Epipolar lines such as Agisoft PhotoScan have been tested to create the point clouds and mesh along with 3D models and textures. As the result was not acceptable (See Figure 2, the previous Dynamic Pulse Function based on Ruby programming language were enhanced and utilized to create the 3D models automatically in LoD3. The accuracy of the final 3D model is almost 10 to 20 cm. After rectification and parallel projection of the photos based on some tie points and targets, all the parameters were measured and utilized as an input to the system to create the 3D model automatically in LoD3 in a very high accuracy.
Using Affordable Data Capturing Devices for Automatic 3d City Modelling
Alizadehashrafi, B.; Abdul-Rahman, A.
2017-11-01
In this research project, many movies from UTM Kolej 9, Skudai, Johor Bahru (See Figure 1) were taken by AR. Drone 2. Since the AR drone 2.0 has liquid lens, while flying there were significant distortions and deformations on the converted pictures of the movies. Passive remote sensing (RS) applications based on image matching and Epipolar lines such as Agisoft PhotoScan have been tested to create the point clouds and mesh along with 3D models and textures. As the result was not acceptable (See Figure 2), the previous Dynamic Pulse Function based on Ruby programming language were enhanced and utilized to create the 3D models automatically in LoD3. The accuracy of the final 3D model is almost 10 to 20 cm. After rectification and parallel projection of the photos based on some tie points and targets, all the parameters were measured and utilized as an input to the system to create the 3D model automatically in LoD3 in a very high accuracy.
Monte Carlo analysis of an ODE Model of the Sea Urchin Endomesoderm Network
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Klipp Edda
2009-08-01
Full Text Available Abstract Background Gene Regulatory Networks (GRNs control the differentiation, specification and function of cells at the genomic level. The levels of interactions within large GRNs are of enormous depth and complexity. Details about many GRNs are emerging, but in most cases it is unknown to what extent they control a given process, i.e. the grade of completeness is uncertain. This uncertainty stems from limited experimental data, which is the main bottleneck for creating detailed dynamical models of cellular processes. Parameter estimation for each node is often infeasible for very large GRNs. We propose a method, based on random parameter estimations through Monte-Carlo simulations to measure completeness grades of GRNs. Results We developed a heuristic to assess the completeness of large GRNs, using ODE simulations under different conditions and randomly sampled parameter sets to detect parameter-invariant effects of perturbations. To test this heuristic, we constructed the first ODE model of the whole sea urchin endomesoderm GRN, one of the best studied large GRNs. We find that nearly 48% of the parameter-invariant effects correspond with experimental data, which is 65% of the expected optimal agreement obtained from a submodel for which kinetic parameters were estimated and used for simulations. Randomized versions of the model reproduce only 23.5% of the experimental data. Conclusion The method described in this paper enables an evaluation of network topologies of GRNs without requiring any parameter values. The benefit of this method is exemplified in the first mathematical analysis of the complete Endomesoderm Network Model. The predictions we provide deliver candidate nodes in the network that are likely to be erroneous or miss unknown connections, which may need additional experiments to improve the network topology. This mathematical model can serve as a scaffold for detailed and more realistic models. We propose that our method can
Target dose conversion modeling from pencil beam (PB) to Monte Carlo (MC) for lung SBRT
International Nuclear Information System (INIS)
Zheng, Dandan; Zhu, Xiaofeng; Zhang, Qinghui; Liang, Xiaoying; Zhen, Weining; Lin, Chi; Verma, Vivek; Wang, Shuo; Wahl, Andrew; Lei, Yu; Zhou, Sumin; Zhang, Chi
2016-01-01
A challenge preventing routine clinical implementation of Monte Carlo (MC)-based lung SBRT is the difficulty of reinterpreting historical outcome data calculated with inaccurate dose algorithms, because the target dose was found to decrease to varying degrees when recalculated with MC. The large variability was previously found to be affected by factors such as tumour size, location, and lung density, usually through sub-group comparisons. We hereby conducted a pilot study to systematically and quantitatively analyze these patient factors and explore accurate target dose conversion models, so that large-scale historical outcome data can be correlated with more accurate MC dose without recalculation. Twenty-one patients that underwent SBRT for early-stage lung cancer were replanned with 6MV 360° dynamic conformal arcs using pencil-beam (PB) and recalculated with MC. The percent D95 difference (PB-MC) was calculated for the PTV and GTV. Using single linear regression, this difference was correlated with the following quantitative patient indices: maximum tumour diameter (MaxD); PTV and GTV volumes; minimum distance from tumour to soft tissue (dmin); and mean density and standard deviation of the PTV, GTV, PTV margin, lung, and 2 mm, 15 mm, 50 mm shells outside the PTV. Multiple linear regression and artificial neural network (ANN) were employed to model multiple factors and improve dose conversion accuracy. Single linear regression with PTV D95 deficiency identified the strongest correlation on mean-density (location) indices, weaker on lung density, and the weakest on size indices, with the following R 2 values in decreasing orders: shell2mm (0.71), PTV (0.68), PTV margin (0.65), shell15mm (0.62), shell50mm (0.49), lung (0.40), dmin (0.22), GTV (0.19), MaxD (0.17), PTV volume (0.15), and GTV volume (0.08). A multiple linear regression model yielded the significance factor of 3.0E-7 using two independent features: mean density of shell2mm (P = 1.6E-7) and PTV volume
SU-F-T-371: Development of a Linac Monte Carlo Model to Calculate Surface Dose
Energy Technology Data Exchange (ETDEWEB)
Prajapati, S; Yan, Y; Gifford, K [UT MD Anderson Cancer Center, Houston, TX (United States)
2016-06-15
Purpose: To generate and validate a linac Monte Carlo (MC) model for surface dose prediction. Methods: BEAMnrc V4-2.4.0 was used to model 6 and 18 MV photon beams for a commercially available linac. DOSXYZnrc V4-2.4.0 calculated 3D dose distributions in water. Percent depth dose (PDD) and beam profiles were extracted for comparison to measured data. Surface dose and at depths in the buildup region was measured with radiochromic film at 100 cm SSD for 4 × 4 cm{sup 2} and 10 × 10 cm{sup 2} collimator settings for open and MLC collimated fields. For the 6 MV beam, films were placed at depths ranging from 0.015 cm to 2 cm and for 18 MV, 0.015 cm to 3.5 cm in Solid Water™. Films were calibrated for both photon energies at their respective dmax. PDDs and profiles were extracted from the film and compared to the MC data. The MC model was adjusted to match measured PDD and profiles. Results: For the 6 MV beam, the mean error(ME) in PDD between film and MC for open fields was 1.9%, whereas it was 2.4% for MLC. For the 18 MV beam, the ME in PDD for open fields was 2% and was 3.5% for MLC. For the 6 MV beam, the average root mean square(RMS) deviation for the central 80% of the beam profile for open fields was 1.5%, whereas it was 1.6% for MLC. For the 18 MV beam, the maximum RMS for open fields was 3%, and was 3.1% for MLC. Conclusion: The MC model of a linac agreed to within 4% of film measurements for depths ranging from the surface to dmax. Therefore, the MC linac model can predict surface dose for clinical applications. Future work will focus on adjusting the linac MC model to reduce RMS error and improve accuracy.
Aqueous corrosion of borosilicate glasses: experiments, modeling and Monte-Carlo simulations
International Nuclear Information System (INIS)
Ledieu, A.
2004-10-01
This work is concerned with the corrosion of borosilicate glasses with variable oxide contents. The originality of this study is the complementary use of experiments and numerical simulations. This study is expected to contribute to a better understanding of the corrosion of nuclear waste confinement glasses. First, the corrosion of glasses containing only silicon, boron and sodium oxides has been studied. The kinetics of leaching show that the rate of leaching and the final degree of corrosion sharply depend on the boron content through a percolation mechanism. For some glass contents and some conditions of leaching, the layer which appears at the glass surface stops the release of soluble species (boron and sodium). This altered layer (also called the gel layer) has been characterized with nuclear magnetic resonance (NMR) and small angle X-ray scattering (SAXS) techniques. Second, additional elements have been included in the glass composition. It appears that calcium, zirconium or aluminum oxides strongly modify the final degree of corrosion so that the percolation properties of the boron sub-network is no more a sufficient explanation to account for the behavior of these glasses. Meanwhile, we have developed a theoretical model, based on the dissolution and the reprecipitation of the silicon. Kinetic Monte Carlo simulations have been used in order to test several concepts such as the boron percolation, the local reactivity of weakly soluble elements and the restructuring of the gel layer. This model has been fully validated by comparison with the results on the three oxide glasses. Then, it has been used as a comprehensive tool to investigate the paradoxical behavior of the aluminum and zirconium glasses: although these elements slow down the corrosion kinetics, they lead to a deeper final degree of corrosion. The main contribution of this work is that the final degree of corrosion of borosilicate glasses results from the competition of two opposite mechanisms
Water leaching of borosilicate glasses: experiments, modeling and Monte Carlo simulations
International Nuclear Information System (INIS)
Ledieu, A.
2004-10-01
This work is concerned with the corrosion of borosilicate glasses with variable oxide contents. The originality of this study is the complementary use of experiments and numerical simulations. This study is expected to contribute to a better understanding of the corrosion of nuclear waste confinement glasses. First, the corrosion of glasses containing only silicon, boron and sodium oxides has been studied. The kinetics of leaching show that the rate of leaching and the final degree of corrosion sharply depend on the boron content through a percolation mechanism. For some glass contents and some conditions of leaching, the layer which appears at the glass surface stops the release of soluble species (boron and sodium). This altered layer (also called the gel layer) has been characterized with nuclear magnetic resonance (NMR) and small angle X-ray scattering (SAXS) techniques. Second, additional elements have been included in the glass composition. It appears that calcium, zirconium or aluminum oxides strongly modify the final degree of corrosion so that the percolation properties of the boron sub-network is no more a sufficient explanation to account for the behavior of these glasses. Meanwhile, we have developed a theoretical model, based on the dissolution and the reprecipitation of the silicon. Kinetic Monte Carlo simulations have been used in order to test several concepts such as the boron percolation, the local reactivity of weakly soluble elements and the restructuring of the gel layer. This model has been fully validated by comparison with the results on the three oxide glasses. Then, it has been used as a comprehensive tool to investigate the paradoxical behavior of the aluminum and zirconium glasses: although these elements slow down the corrosion kinetics, they lead to a deeper final degree of corrosion. The main contribution of this work is that the final degree of corrosion of borosilicate glasses results from the competition of two opposite mechanisms
A Monte Carlo modeling on charging effect for structures with arbitrary geometries
Li, C.; Mao, S. F.; Zou, Y. B.; Li, Yong Gang; Zhang, P.; Li, H. M.; Ding, Z. J.
2018-04-01
Insulating materials usually suffer charging effects when irradiated by charged particles. In this paper, we present a Monte Carlo study on the charging effect caused by electron beam irradiation for sample structures with any complex geometry. When transporting in an insulating solid, electrons encounter elastic and inelastic scattering events; the Mott cross section and a Lorentz-type dielectric function are respectively employed to describe such scatterings. In addition, the band gap and the electron–long optical phonon interaction are taken into account. The electronic excitation in inelastic scattering causes generation of electron–hole pairs; these negative and positive charges establish an inner electric field, which in turn induces the drift of charges to be trapped by impurities, defects, vacancies etc in the solid, where the distributions of trapping sites are assumed to have uniform density. Under charging conditions, the inner electric field distorts electron trajectories, and the surface electric potential dynamically alters secondary electron emission. We present, in this work, an iterative modeling method for a self-consistent calculation of electric potential; the method has advantages in treating any structure with arbitrary complex geometry, in comparison with the image charge method—which is limited to a quite simple boundary geometry. Our modeling is based on: the combination of the finite triangle mesh method for an arbitrary geometry construction; a self-consistent method for the spatial potential calculation; and a full dynamic description for the motion of deposited charges. Example calculations have been done to simulate secondary electron yield of SiO2 for a semi-infinite solid, the charging for a heterostructure of SiO2 film grown on an Au substrate, and SEM imaging of a SiO2 line structure with rough surfaces and SiO2 nanoparticles with irregular shapes. The simulations have explored interesting interlaced charge layer distribution
Comprehensive modeling of solid phase epitaxial growth using Lattice Kinetic Monte Carlo
International Nuclear Information System (INIS)
Martin-Bragado, Ignacio
2013-01-01
Damage evolution of irradiated silicon is, and has been, a topic of interest for the last decades for its applications to the semiconductor industry. In particular, sometimes, the damage is heavy enough to collapse the lattice and to locally amorphize the silicon, while in other cases amorphization is introduced explicitly to improve other implanted profiles. Subsequent annealing of the implanted samples heals the amorphized regions through Solid Phase Epitaxial Regrowth (SPER). SPER is a complicated process. It is anisotropic, it generates defects in the recrystallized silicon, it has a different amorphous/crystalline (A/C) roughness for each orientation, leaving pits in Si(1 1 0), and in Si(1 1 1) it produces two modes of recrystallization with different rates. The recently developed code MMonCa has been used to introduce a physically-based comprehensive model using Lattice Kinetic Monte Carlo that explains all the above singularities of silicon SPER. The model operates by having, as building blocks, the silicon lattice microconfigurations and their four twins. It detects the local configurations, assigns microscopical growth rates, and reconstructs the positions of the lattice locally with one of those building blocks. The overall results reproduce the (a) anisotropy as a result of the different growth rates, (b) localization of SPER induced defects, (c) roughness trends of the A/C interface, (d) pits on Si(1 1 0) regrown surfaces, and (e) bimodal Si(1 1 1) growth. It also provides physical insights of the nature and shape of deposited defects and how they assist in the occurrence of all the above effects
Energy Technology Data Exchange (ETDEWEB)
Carasco, C., E-mail: cedric.carasco@cea.fr [CEA, DEN, Cadarache, Nuclear Measurement Laboratory, F-13108 Saint-Paul-lez-Durance (France)
2012-07-15
In neutron Time-of-Flight (TOF) measurements performed with fast organic scintillation detectors, both pulse arrival time and amplitude are relevant. Monte Carlo simulation can be used to calculate the time-energy dependant neutron flux at the detector position. To convert the flux into a pulse height spectrum, one must calculate the detector response function for mono-energetic neutrons. MCNP can be used to design TOF systems, but standard MCNP versions cannot reliably calculate the energy deposited by fast neutrons in the detector since multiple scattering effects must be taken into account in an analog way, the individual recoil particles energy deposit being summed with the appropriate scintillation efficiency. In this paper, the energy response function of 2 Double-Prime Multiplication-Sign 2 Double-Prime and 5 Double-Prime Multiplication-Sign 5 Double-Prime liquid scintillation BC-501 A (Bicron) detectors to fast neutrons ranging from 20 keV to 5.0 MeV is computed with GEANT4 to be coupled with MCNPX through the 'MCNP Output Data Analysis' software developed under ROOT (). - Highlights: Black-Right-Pointing-Pointer GEANT4 has been used to model organic scintillators response to neutrons up to 5 MeV. Black-Right-Pointing-Pointer The response of 2 Double-Prime Multiplication-Sign 2 Double-Prime and 5 Double-Prime Multiplication-Sign 5 Double-Prime BC501A detectors has been parameterized with simple functions. Black-Right-Pointing-Pointer Parameterization will allow the modeling of neutron Time of Flight measurements with MCNP using tools based on CERN's ROOT.
Assessment of mean annual flood damage using simple hydraulic modeling and Monte Carlo simulation
Oubennaceur, K.; Agili, H.; Chokmani, K.; Poulin, J.; Marceau, P.
2016-12-01
Floods are the most frequent and the most damaging natural disaster in Canada. The issue of assessing and managing the risk related to this disaster has become increasingly crucial for both local and national authorities. Brigham, a municipality located in southern Quebec Province, is one of the heavily affected regions by this disaster because of frequent overflows of the Yamaska River reaching two to three times per year. Since Irene Hurricane which struck the region in 2011, causing considerable socio-economic damage, the implementation of mitigation measures has become a major priority for this municipality. To do this, a preliminary study to evaluate the risk to which this region is exposed is essential. Conventionally, approaches only based on the characterization of the hazard (e.g. floodplains extensive, flood depth) are generally adopted to study the risk of flooding. In order to improve the knowledge of this risk, a Monte Carlo simulation approach combining information on the hazard with vulnerability-related aspects has been developed. This approach integrates three main components: (1) hydrologic modelling aiming to establish a probability-discharge function which associate each measured discharge to its probability of occurrence (2) hydraulic modeling that aims to establish the relationship between the discharge and the water stage at each building (3) damage study that aims to assess the buildings damage using damage functions. The damage is estimated according to the water depth defined as the difference between the water level and the elevation of the building's first floor. The application of the proposed approach allows estimating the annual average cost of damage caused by floods on buildings. The obtained results will be useful for authorities to support their decisions on risk management and prevention against this disaster.
Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M
2014-04-01
Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H&N) carcinoma. Hyperthermia treatment planning (HTP) guided H&N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Automatically generated 3D patient models can be introduced in the clinic for H&N HTP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
International Nuclear Information System (INIS)
Verhaart, René F.; Fortunati, Valerio; Verduijn, Gerda M.; Walsum, Theo van; Veenland, Jifke F.; Paulides, Margarethus M.
2014-01-01
Background and purpose: Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H and N) carcinoma. Hyperthermia treatment planning (HTP) guided H and N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. Material and methods: CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Results: Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Conclusions: Automatically generated 3D patient models can be introduced in the clinic for H and N HTP
Directory of Open Access Journals (Sweden)
Qi Chen
2014-12-01
Full Text Available Intelligent seamline selection for image mosaicking is an area of active research in the fields of massive data processing, computer vision, photogrammetry and remote sensing. In mosaicking applications for digital orthophoto maps (DOMs, the visual transition in mosaics is mainly caused by differences in positioning accuracy, image tone and relief displacement of high ground objects between overlapping DOMs. Among these three factors, relief displacement, which prevents the seamless mosaicking of images, is relatively more difficult to address. To minimize visual discontinuities, many optimization algorithms have been studied for the automatic selection of seamlines to avoid high ground objects. Thus, a new automatic seamline selection algorithm using a digital surface model (DSM is proposed. The main idea of this algorithm is to guide a seamline toward a low area on the basis of the elevation information in a DSM. Given that the elevation of a DSM is not completely synchronous with a DOM, a new model, called the orthoimage elevation synchronous model (OESM, is derived and introduced. OESM can accurately reflect the elevation information for each DOM unit. Through the morphological processing of the OESM data in the overlapping area, an initial path network is obtained for seamline selection. Subsequently, a cost function is defined on the basis of several measurements, and Dijkstra’s algorithm is adopted to determine the least-cost path from the initial network. Finally, the proposed algorithm is employed for automatic seamline network construction; the effective mosaic polygon of each image is determined, and a seamless mosaic is generated. The experiments with three different datasets indicate that the proposed method meets the requirements for seamline network construction. In comparative trials, the generated seamlines pass through fewer ground objects with low time consumption.
Kipp, Dylan; Ganesan, Venkat
2013-06-01
We develop a kinetic Monte Carlo model for photocurrent generation in organic solar cells that demonstrates improved agreement with experimental illuminated and dark current-voltage curves. In our model, we introduce a charge injection rate prefactor to correct for the electrode grid-size and electrode charge density biases apparent in the coarse-grained approximation of the electrode as a grid of single occupancy, charge-injecting reservoirs. We use the charge injection rate prefactor to control the portion of dark current attributed to each of four kinds of charge injection. By shifting the dark current between electrode-polymer pairs, we align the injection timescales and expand the applicability of the method to accommodate ohmic energy barriers. We consider the device characteristics of the ITO/PEDOT/PSS:PPDI:PBTT:Al system and demonstrate the manner in which our model captures the device charge densities unique to systems with small injection energy barriers. To elucidate the defining characteristics of our model, we first demonstrate the manner in which charge accumulation and band bending affect the shape and placement of the various current-voltage regimes. We then discuss the influence of various model parameters upon the current-voltage characteristics.
International Nuclear Information System (INIS)
Lagerlöf, Jakob H.; Kindblom, Jon; Bernhardt, Peter
2014-01-01
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 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 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 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 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 lower
Optimization of the Monte Carlo code for modeling of photon migration in tissue.
Zołek, Norbert S; Liebert, Adam; Maniewski, Roman
2006-10-01
The Monte Carlo method is frequently used to simulate light transport in turbid media because of its simplicity and flexibility, allowing to analyze complicated geometrical structures. Monte Carlo simulations are, however, time consuming because of the necessity to track the paths of individual photons. The time consuming computation is mainly associated with the calculation of the logarithmic and trigonometric functions as well as the generation of pseudo-random numbers. In this paper, the Monte Carlo algorithm was developed and optimized, by approximation of the logarithmic and trigonometric functions. The approximations were based on polynomial and rational functions, and the errors of these approximations are less than 1% of the values of the original functions. The proposed algorithm was verified by simulations of the time-resolved reflectance at several source-detector separations. The results of the calculation using the approximated algorithm were compared with those of the Monte Carlo simulations obtained with an exact computation of the logarithm and trigonometric functions as well as with the solution of the diffusion equation. The errors of the moments of the simulated distributions of times of flight of photons (total number of photons, mean time of flight and variance) are less than 2% for a range of optical properties, typical of living tissues. The proposed approximated algorithm allows to speed up the Monte Carlo simulations by a factor of 4. The developed code can be used on parallel machines, allowing for further acceleration.
Directory of Open Access Journals (Sweden)
M. Kotbi
2013-03-01
Full Text Available The choice of appropriate interaction models is among the major disadvantages of conventional methods such as Molecular Dynamics (MD and Monte Carlo (MC simulations. On the other hand, the so-called Reverse Monte Carlo (RMC method, based on experimental data, can be applied without any interatomic and/or intermolecular interactions. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term into the acceptance criteria. This method is referred to as the Hybrid Reverse Monte Carlo (HRMC method. The idea of this paper is to test the validity of a combined potential model of coulomb and Lennard-Jones in a Fluoride glass system BaMnMF7 (M = Fe,V using HRMC method. The results show a good agreement between experimental and calculated characteristics, as well as a meaningful improvement in partial pair distribution functions (PDFs. We suggest that this model should be used in calculating the structural properties and in describing the average correlations between components of fluoride glass or a similar system. We also suggest that HRMC could be useful as a tool for testing the interaction potential models, as well as for conventional applications.
Li, Shu; The ATLAS collaboration
2017-01-01
Proceeding for the poster presentation at LHCP2017, Shanghai, China on the topic of "Monte Carlo modeling of Standard Model multi-boson production processes for $\\sqrt{s} = 13$ TeV ATLAS analyses" (ATL-PHYS-SLIDE-2017-265 https://cds.cern.ch/record/2265389) Deadline: 01/09/2017
Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods
Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.
2011-12-01
Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion