Monte Carlo methods in ICF

International Nuclear Information System (INIS)

Zimmerman, George B.

1997-01-01

Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials

Applications of Monte Carlo codes to a study of gamma-ray buildup factors, skyshine and duct streaming

Energy Technology Data Exchange (ETDEWEB)

Hirayama, H. [High Energy Accelerator Research Organization (KEK), Ibaraki (Japan)

2001-07-01

Many shielding calculations for gamma-rays have continued to rely on point-kernel methods incorporating buildup factor data. Line beam or conical beam response functions, which are calculated using a Monte Carlo code, for skyshine problems are useful to estimate the skyshine dose from various facilities. A simple calculation method for duct streaming was proposed using the parameters calculated by the Monte Carlo code. It is therefore important to study, improve and produce basic parameters related to old, but still important, problems in the fields of radiation shielding using the Monte Carlo code. In this paper, these studies performed by several groups in Japan as applications of the Monte Carlo method are discussed. (orig.)

Monte Carlo methods in ICF

International Nuclear Information System (INIS)

Zimmerman, G.B.

1997-01-01

Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials. copyright 1997 American Institute of Physics

Monte Carlo simulation of the HEGRA cosmic ray detector performance

Energy Technology Data Exchange (ETDEWEB)

Martinez, S. [Universidad Complutense de Madrid (Spain). Dept. de Fisica Atomica, Molecular y Nuclear; Arqueros, F. [Universidad Complutense de Madrid (Spain). Dept. de Fisica Atomica, Molecular y Nuclear; Fonseca, V. [Universidad Complutense de Madrid (Spain). Dept. de Fisica Atomica, Molecular y Nuclear; Karle, A. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, D80805 Munich (Germany); Lorenz, E. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, D80805 Munich (Germany); Plaga, R. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, D80805 Munich (Germany); Rozanska, M. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, D80805 Munich (Germany)]|[Institute of Nuclear Physics, ul.Kawiory 26a, PL30-055 Cracow (Poland)

1995-04-21

Models of the scintillator and wide-angle air Cherenkov (AIROBICC) arrays of the HEGRA experiment are described here. Their response to extensive air showers generated by cosmic rays in the 10 to 1000 TeV range has been assessed using a detailed Monte Carlo simulation of air shower development and associated Cherenkov emission. Protons, {gamma}-rays and oxygen and iron nuclei have been considered as primary particles. For both arrays, the angular resolution as determined from the Monte Carlo simulation is compared with experimental data. Shower size N{sub e} can be reconstructed from the scintillator signals with an error ranging from 10% (N{sub e}=2x10{sup 5}) to 35% (N{sub e}=3x10{sup 3}). The energy threshold of AIROBICC is 14 TeV for primary gammas and 27 TeV for protons and an angular resolution of 0.25 can be obtained. The measurement of the Cherenkov light at 90 m from the shower core provides an accurate determination of primary energy E{sub 0} as far as the nature of the primary particle is known. For gammas an error in the energy prediction ranging from 8% (E{sub 0}=5x10{sup 14} eV) to 15% (E{sub 0}=2x10{sup 13} eV) is achieved. This detector is therefore a powerful tool for {gamma}-ray astronomy. ((orig.)).

An experimental and Monte Carlo investigation of the energy dependence of alanine/EPR dosimetry: I. Clinical x-ray beams

International Nuclear Information System (INIS)

Zeng, G G; McEwen, M R; Rogers, D W O; Klassen, N V

2004-01-01

The energy dependence of alanine/EPR dosimetry, in terms of absorbed dose-to-water for clinical 6, 10, 25 MV x-rays and 60 Co rays was investigated by measurements and Monte Carlo (MC) calculations. The dose rates were traceable to the NRC primary standard for absorbed dose, a sealed water calorimetry. The electron paramagnetic resonance (EPR) spectra of irradiated pellets were measured using a Bruker EMX 081 EPR spectrometer. The DOSRZnrc Monte Carlo code of the EGSnrc system was used to simulate the experimental conditions with BEAM code calculated input spectra of x-rays and γ-rays. Within the experimental uncertainty of 0.5%, the alanine EPR response to absorbed dose-to-water for x-rays was not dependent on beam quality from 6 MV to 25 MV, but on average, it was about 0.6% lower than its response to 60 Co gamma rays. Combining experimental data with Monte Carlo calculations, it is found that the alanine/EPR response per unit absorbed dose-to-alanine is the same for clinical x-rays and 60 Co gamma rays within the uncertainty of 0.6%. Monte Carlo simulations showed that neither the presence of PMMA holder nor varying the dosimeter thickness between 1 mm and 5 mm has significant effect on the energy dependence of alanine/EPR dosimetry within the calculation uncertainty of 0.3%

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography*

Science.gov (United States)

Paixão, Lucas; Oliveira, Bruno Beraldo; Viloria, Carolina; de Oliveira, Marcio Alves; Teixeira, Maria Helena Araújo; Nogueira, Maria do Socorro

2015-01-01

Objective Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Materials and Methods Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Results Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. Conclusion The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography. PMID:26811553

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography

Directory of Open Access Journals (Sweden)

Lucas Paixão

2015-12-01

Full Text Available Abstract Objective: Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Materials and Methods: Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Results: Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. Conclusion: The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography.

Design of a tritium gas cell for beta-ray induced X-ray spectrometry using Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Hara, Masanori, E-mail: masahara@ctg.u-toyama.ac.jp [Hydrogen Isotope Research Center, Organization for Promotion of Research, University of Toyama, 3190 Gofuku, Toyama City, Toyama 930-8555 (Japan); Abe, Shinsuke; Matsuyama, Masao [Hydrogen Isotope Research Center, Organization for Promotion of Research, University of Toyama, 3190 Gofuku, Toyama City, Toyama 930-8555 (Japan); Aso, Tsukasa [Electronics and Computer Engineering, National Institute of Technology, Toyama College, 1-2 Ebie-neriya, Imizu City, Toyama 933-0293 (Japan); Tatenuma, Katsuyoshi; Kawakami, Tomohiko; Ito, Takeshi [KAKEN Company Limited, 1044 Horimachi, Mito City, Ibaraki 310-0903 (Japan)

2017-06-15

Highlights: • Beta-ray induced X-ray spectrometry (BIXS) is a method for tritium gas analysis. • Gas cell for BIXS was designed by Monte Carlo simulations. • The optimum thickness of the gold layer on a beryllium window was around 150 nm. • This simulation model considered the self-absorption with increasing the cell length. - Abstract: One of the methods used for tritium gas analysis is beta-ray induced X-ray spectrometry (BIXS). Gas cell design is important in this method. The structure of the gas cell for BIXS was optimized by Monte Carlo simulation of beta-ray induced X-ray spectra in various window geometries using the Geant4 tool kit (version 10.01.p02). The simulated spectrum from tritium decay fitted the observed one, and the simulation model was used to obtain the cell parameters for BIXS. The optimum thickness of the gold layer on a beryllium window was around 150 nm. This simulation model also considered the relationship between self-absorption by hydrogen gas and the cell length. Self-absorption increased with increasing cell length and the relationship between the sample pressure and cell length was formulated.

A Monte Carlo error simulation applied to calibration-free X-ray diffraction phase analysis

International Nuclear Information System (INIS)

Braun, G.E.

1986-01-01

Quantitative phase analysis of a system of n phases can be effected without the need for calibration standards provided at least n different mixtures of these phases are available. A series of linear equations relating diffracted X-ray intensities, weight fractions and quantitation factors coupled with mass balance relationships can be solved for the unknown weight fractions and factors. Uncertainties associated with the measured X-ray intensities, owing to counting of random X-ray quanta, are used to estimate the errors in the calculated parameters utilizing a Monte Carlo simulation. The Monte Carlo approach can be generalized and applied to any quantitative X-ray diffraction phase analysis method. Two examples utilizing mixtures of CaCO 3 , Fe 2 O 3 and CaF 2 with an α-SiO 2 (quartz) internal standard illustrate the quantitative method and corresponding error analysis. One example is well conditioned; the other is poorly conditioned and, therefore, very sensitive to errors in the measured intensities. (orig.)

A Monte Carlo modeling alternative for the API Gamma Ray Calibration Facility.

Science.gov (United States)

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.

Monte Carlo simulation of discrete γ-ray detectors

International Nuclear Information System (INIS)

Bakkali, A.; Tamda, N.; Parmentier, M.; Chavanelle, J.; Pousse, A.; Kastler, B.

2005-01-01

Needs in medical diagnosis, especially for early and reliable breast cancer detection, lead us to consider developments in scintillation crystals and position sensitive photomultiplier tubes (PSPMT) in order to develop a high-resolution medium field γ-ray imaging device. However the ideal detector for γ-rays represents a compromise between many conflicting requirements. In order to optimize different parameters involved in the detection process, we have developed a Monte Carlo simulation software. Its aim was to study the light distribution produced by a gamma photon interacting with a pixellated scintillation crystal coupled to a PSPMT array. Several crystal properties were taken into account as well as the intrinsic response of PSPMTs. Images obtained by simulations are compared with experimental results. Agreement between simulation and experimental results validate our simulation model

An intercomparison of Monte Carlo codes used for in-situ gamma-ray spectrometry

International Nuclear Information System (INIS)

Hurtado, S.; Villa, M.

2010-01-01

In-situ gamma-ray spectrometry is widely used for monitoring of natural as well as man-made radionuclides and corresponding gamma fields in the environment or working places. It finds effective application in the operational and accidental monitoring of nuclear facilities and their vicinity, waste depositories, radioactive contamination measurements and environmental mapping or geological prospecting. In order to determine accurate radionuclide concentrations in these research fields, Monte Carlo codes have recently been used to obtain the efficiency calibration of in-situ gamma-ray detectors. This work presents an inter-comparison between two Monte Carlo codes applied to in-situ gamma-ray spectrometry. On the commercial market, Canberra has its LABSOCS/ISOCS software which is relatively inexpensive. The ISOCS mathematical efficiency calibration software uses a combination of Monte Carlo calculations and discrete ordinate attenuation computations. Efficiencies can be generated in a few minutes in the field and can be modified easily if needed. However, it has been reported in the literature that ISOCS computation method is accurate on average only within 5%, and additionally in order to use LABSOCS/ISOCS it is necessary a previous characterization of the detector by Canberra, which is an expensive process. On the other hand, the multipurpose and open source GEANT4 takes significant computer time and presents a non-friendly but powerful toolkit, independent of the manufacturer of the detector. Different experimental measurements of calibrated sources were performed with a Canberra portable HPGe detector and compared to the results obtained using both Monte Carlo codes. Furthermore, a variety of efficiency calibrations for different radioactive source distributions were calculated and tested, like plane shapes or containers filled with different materials such as soil, water, etc. LabSOCS simulated efficiencies for medium and high energies were given within an

Monte Carlo simulation for the design of industrial gamma-ray transmission tomography

International Nuclear Information System (INIS)

Kim, Jongbum; Jung, Sunghee; Moon, Jinho; Kwon, Taekyong; Cho, Gyuseong

2011-01-01

The Monte Carlo simulation and experiment were carried out for a large-scale industrial gamma ray tomographic scanning geometry. The geometry of the tomographic system has a moving source with 16 stationary detectors. This geometry is advantageous for the diagnosis of a large-scale industrial plant. The simulation data was carried out for the phantom with 32 views, 16 detectors, and a different energy bin. The simulation data was processed to be used for image reconstruction. Image reconstruction was performed by a Diagonally-Scaled Gradient-Ascent algorithm for simulation data. Experiments were conducted in a 78 cm diameter column filled with polypropylene grains. Sixteen 0.5-inch-thick and 1 inch long NaI(Tl) cylindrical detectors, and 20 mCi of 137 Cs radioactive source were used. The experimental results were compared to the simulation data. The experimental results were similar to Monte Carlo simulation results. This result showed that the Monte Carlo simulation is useful for predicting the result of the industrial gamma tomographic scan method And it can also give a solution for designing the industrial gamma tomography system and preparing the field experiment. (author)

Monte Carlo calculations of neutron and gamm-ray energy spectra for fusion-reactor shield design: comparison with experiment

International Nuclear Information System (INIS)

Santoro, R.T.; Barnes, J.M.

1983-08-01

Neutron and gamma-ray spectra resulting from the interactions of approx. 14-MeV neutrons in laminated slabs of stainless steel type-304 and borated polyethylene have been calculated using the Monte Carlo code MCNP. The calculated spectra are compared with measured data as a function of slab thickness and material composition and as a function of detector location behind the slabs. Comparisons of the differential energy spectra are made for neutrons with energies above 850 keV and for gamma rays with energies above 750 keV. The measured neutron spectra and those calculated using Monte Carlo methods agree within 5% to 50% depending on the slab thickness and composition and neutron energy. The agreement between the measured and calculated gamma-ray energy spectra is also within this range. The MCNP data are also in favorable agreement with attenuated data calculated previously by discrete ordinates transport methods and the Monte Carlo code SAM-CE

A Monte Carlo simulation of scattering reduction in spectral x-ray computed tomography

DEFF Research Database (Denmark)

Busi, Matteo; Olsen, Ulrik Lund; Bergbäck Knudsen, Erik

2017-01-01

In X-ray computed tomography (CT), scattered radiation plays an important role in the accurate reconstruction of the inspected object, leading to a loss of contrast between the different materials in the reconstruction volume and cupping artifacts in the images. We present a Monte Carlo simulation...

Monte-Carlo background simulations of present and future detectors in x-ray astronomy

Science.gov (United States)

Tenzer, C.; Kendziorra, E.; Santangelo, A.

2008-07-01

Reaching a low-level and well understood internal instrumental background is crucial for the scientific performance of an X-ray detector and, therefore, a main objective of the instrument designers. Monte-Carlo simulations of the physics processes and interactions taking place in a space-based X-ray detector as a result of its orbital environment can be applied to explain the measured background of existing missions. They are thus an excellent tool to predict and optimize the background of future observatories. Weak points of a design and the main sources of the background can be identified and methods to reduce them can be implemented and studied within the simulations. Using the Geant4 Monte-Carlo toolkit, we have created a simulation environment for space-based detectors and we present results of such background simulations for XMM-Newton's EPIC pn-CCD camera. The environment is also currently used to estimate and optimize the background of the future instruments Simbol-X and eRosita.

Monte Carlo simulation of dose enhancement effect of X-ray at Au/Si interface

International Nuclear Information System (INIS)

Wu Zhengxin; He Chengfa; Lu Wu; Guo Qi; Yu Xin; Zhang Lei; Deng Wei; Zheng Qiwen; ARKIN Abulim

2013-01-01

Background: The dose enhancement factor of X-ray was found in 1970s, because of its bad damage to electronic devices. Purpose: This paper is mainly to calculate the dose-enhancement factor at Au/Si interfaces. Methods: The gradient distribution of dose with X-rays has been studied at and near the interface of Au/Si by Monte-Carlo simulation of particle transportation. The mechanism of dose enhancement is discussed based on the principles of interaction of photon with matter. A 3D Au/Si model has been established by MCNP5 program and the dose-enhancement factors of different thicknesses Au/Si interfaces were calculated by Monte Carlo method. Results: The calculated results demonstrate that there exists a stronger dose-enhancement in the Si side near the interface when the energy of X-ray is 30-300 keV. Conclusions: When the thickness of Au is 0-10 μm, dose-enhancement factor of X-ray increases along with the increase of the thickness of Au, when the thickness of Au exceeds 10 μm, dose-enhancement factor of X-ray decreases along with the increase of the thickness of Au. (authors)

Monte Carlo shielding analyses using an automated biasing procedure

International Nuclear Information System (INIS)

Tang, J.S.; Hoffman, T.J.

1988-01-01

A systematic and automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete ordinates calculation are used to generate biasing parameters for a Monte Carlo calculation. The entire procedure of adjoint calculation, biasing parameters generation, and Monte Carlo calculation has been automated. The automated biasing procedure has been applied to several realistic deep-penetration shipping cask problems. The results obtained for neutron and gamma-ray transport indicate that with the automated biasing procedure Monte Carlo shielding calculations of spent-fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost

Monte Carlo methods

Directory of Open Access Journals (Sweden)

Bardenet Rémi

2013-07-01

Full Text Available Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC methods. We give intuition on the theoretical justification of the algorithms as well as practical advice, trying to relate both. We discuss the application of Monte Carlo in experimental physics, and point to landmarks in the literature for the curious reader.

Monte Carlo simulation of gas Cerenkov detectors

International Nuclear Information System (INIS)

Mack, J.M.; Jain, M.; Jordan, T.M.

1984-01-01

Theoretical study of selected gamma-ray and electron diagnostic necessitates coupling Cerenkov radiation to electron/photon cascades. A Cerenkov production model and its incorporation into a general geometry Monte Carlo coupled electron/photon transport code is discussed. A special optical photon ray-trace is implemented using bulk optical properties assigned to each Monte Carlo zone. Good agreement exists between experimental and calculated Cerenkov data in the case of a carbon-dioxide gas Cerenkov detector experiment. Cerenkov production and threshold data are presented for a typical carbon-dioxide gas detector that converts a 16.7 MeV photon source to Cerenkov light, which is collected by optics and detected by a photomultiplier

Monte Carlo simulations for stereotactic radiotherapy system with various kilo-voltage x-ray energy

International Nuclear Information System (INIS)

Deloar, H.M.; Kunieda, E.; Kawase, T.; Kubo, Atsushi; Saitoh, H.; Myojoyama, A.; Ozaki, M.; Fujisaki, T.; Saito, K.

2005-01-01

Stereotactic radiotherapy (SRT) of lung tumors with a narrow and precise medium energy x-ray beam where the homogeneous high dose area will be confined within the tumors are desirable. A conventional x-ray CT with medium energy x-ray has been modified to develop a radiotherapy system for lung SRT. A cylindrical collimator (0.3 cm φ) made of tungsten was introduced to collimate the X-ray beam. The system was simulated with BEAMnrc(EGS4) Monte Carlo code and various x-ray energy spectra were generated to investigate the dose distributions with our kilo-voltage SRT system. Experiments were performed to acquire the energy spectra of 100, 120 and 135 kVp (kilo-voltage peak) from CT measurements and those results were compared with the spectra obtained from Monte Carlo simulations. Verifications of percentage of dose depth (PDD) for 120 and 147.5 kVp were investigated in a water phantom with experiments and Monte Carlo simulations. Finally dose distributions of 120, 135, 147.5, 200, 250, 300, 350, 400, 500 kVp spectra were investigated with lung phantom and human lung. The Percentage of Depth Dose (PDD) in the water phantom calculated from the experimental and simulated spectra of 120 and 147.5 kVp show good agreement with each other. The PDD of 147.5 and 120 kVp spectra at 9 cm depth was approximately 10% and 9%, respectively. Dose distributions around the lung tumor in the phantom and human for all x-ray energies were almost uniform but in the case of the human lung absorptions of dose at ribs for the energy lower than 135 kVp was more than 35% and those absorptions for the energy spectra of 147.5 kVp and above was less than 30%. This absorption gradually decreases with increasing x-ray energies. Uniform dose distributions in the lung region of human and thorax phantom demonstrated the possibility of SRT system with medium energy X-ray. A detail performance of this system as a kilo-voltage conformal radiotherapy is under investigations. (author)

Evaluation of high packing density powder X-ray screens by Monte Carlo methods

International Nuclear Information System (INIS)

Liaparinos, P.; Kandarakis, I.; Cavouras, D.; Kalivas, N.; Delis, H.; Panayiotakis, G.

2007-01-01

Phosphor materials are employed in intensifying screens of both digital and conventional X-ray imaging detectors. High packing density powder screens have been developed (e.g. screens in ceramic form) exhibiting high-resolution and light emission properties, and thus contributing to improved image transfer characteristics and higher radiation to light conversion efficiency. For the present study, a custom Monte Carlo simulation program was used in order to examine the performance of ceramic powder screens, under various radiographic conditions. The model was developed using Mie scattering theory for the description of light interactions, based on the physical characteristics (e.g. complex refractive index, light wavelength) of the phosphor material. Monte Carlo simulations were carried out assuming: (a) X-ray photon energy ranging from 18 up to 49 keV, (b) Gd 2 O 2 S:Tb phosphor material with packing density of 70% and grain size of 7 μm and (c) phosphor thickness ranging between 30 and 70 mg/cm 2 . The variation of the Modulation Transfer Function (MTF) and the Luminescence Efficiency (LE) with respect to the X-ray energy and the phosphor thickness was evaluated. Both aforementioned imaging characteristics were shown to take high values at 49 keV X-ray energy and 70 mg/cm 2 phosphor thickness. It was found that high packing density screens may be appropriate for use in medical radiographic systems

Monte Carlo simulation of x-ray spectra in diagnostic radiology and mammography using MCNP4C

Energy Technology Data Exchange (ETDEWEB)

Ay, M R [Department of Physics and Nuclear Sciences, AmirKabir University of Technology, Tehran (Iran, Islamic Republic of); Shahriari, M [Department of Nuclear Engineering, Shahid Beheshti University, Tehran (Iran, Islamic Republic of); Sarkar, S [Department of Medical Physics, Tehran University of Medical Science, Tehran (Iran, Islamic Republic of); Adib, M [TPP Co., GE Medical Systems, Iran Authorized Distributor, Tehran (Iran, Islamic Republic of); Zaidi, H [Division of Nuclear Medicine, Geneva University Hospital, 1211 Geneva (Switzerland)

2004-11-07

The general purpose Monte Carlo N-particle radiation transport computer code (MCNP4C) was used for the simulation of x-ray spectra in diagnostic radiology and mammography. The electrons were transported until they slow down and stop in the target. Both bremsstrahlung and characteristic x-ray production were considered in this work. We focus on the simulation of various target/filter combinations to investigate the effect of tube voltage, target material and filter thickness on x-ray spectra in the diagnostic radiology and mammography energy ranges. The simulated x-ray spectra were compared with experimental measurements and spectra calculated by IPEM report number 78. In addition, the anode heel effect and off-axis x-ray spectra were assessed for different anode angles and target materials and the results were compared with EGS4-based Monte Carlo simulations and measured data. Quantitative evaluation of the differences between our Monte Carlo simulated and comparison spectra was performed using student's t-test statistical analysis. Generally, there is a good agreement between the simulated x-ray and comparison spectra, although there are systematic differences between the simulated and reference spectra especially in the K-characteristic x-rays intensity. Nevertheless, no statistically significant differences have been observed between IPEM spectra and the simulated spectra. It has been shown that the difference between MCNP simulated spectra and IPEM spectra in the low energy range is the result of the overestimation of characteristic photons following the normalization procedure. The transmission curves produced by MCNP4C have good agreement with the IPEM report especially for tube voltages of 50 kV and 80 kV. The systematic discrepancy for higher tube voltages is the result of systematic differences between the corresponding spectra.

Monte Carlo simulation of x-ray spectra in diagnostic radiology and mammography using MCNP4C

Science.gov (United States)

Ay, M. R.; Shahriari, M.; Sarkar, S.; Adib, M.; Zaidi, H.

2004-11-01

The general purpose Monte Carlo N-particle radiation transport computer code (MCNP4C) was used for the simulation of x-ray spectra in diagnostic radiology and mammography. The electrons were transported until they slow down and stop in the target. Both bremsstrahlung and characteristic x-ray production were considered in this work. We focus on the simulation of various target/filter combinations to investigate the effect of tube voltage, target material and filter thickness on x-ray spectra in the diagnostic radiology and mammography energy ranges. The simulated x-ray spectra were compared with experimental measurements and spectra calculated by IPEM report number 78. In addition, the anode heel effect and off-axis x-ray spectra were assessed for different anode angles and target materials and the results were compared with EGS4-based Monte Carlo simulations and measured data. Quantitative evaluation of the differences between our Monte Carlo simulated and comparison spectra was performed using student's t-test statistical analysis. Generally, there is a good agreement between the simulated x-ray and comparison spectra, although there are systematic differences between the simulated and reference spectra especially in the K-characteristic x-rays intensity. Nevertheless, no statistically significant differences have been observed between IPEM spectra and the simulated spectra. It has been shown that the difference between MCNP simulated spectra and IPEM spectra in the low energy range is the result of the overestimation of characteristic photons following the normalization procedure. The transmission curves produced by MCNP4C have good agreement with the IPEM report especially for tube voltages of 50 kV and 80 kV. The systematic discrepancy for higher tube voltages is the result of systematic differences between the corresponding spectra.

The FLUKA Monte Carlo, Non-Perturbative QCD and Cosmic Ray Cascades

International Nuclear Information System (INIS)

Battistoni, G.

2005-01-01

The FLUKA Monte Carlo code, presently used in cosmic ray physics, contains packages to sample soft hadronic processes which are built according to the Dual Parton Model. This is a phenomenological model capable of reproducing many of the features of hadronic collisions in the non perturbative QCD regime. The basic principles of the model are summarized and, as an example, the associated Lambda-K production is discussed. This is a process which has some relevance for the calculation of atmospheric neutrino fluxes

Monte Carlo simulation of x-ray spectra in mammography

Energy Technology Data Exchange (ETDEWEB)

Ng, K.P. [Department of Optometry and Radiography, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (China). E-mail: benngkp at netvigator.com; Kwok, C.S.; Ng, K.P.; Tang, F.H. [Department of Optometry and Radiography, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (China)

2000-05-01

A model for generating x-ray spectra in mammography is presented. This model used the ITS version 3 Monte Carlo code for simulating the radiation transport. Various target/filter combinations such as tungsten/aluminium, molybdenum/molybdenum, molybdenum/rhodium and rhodium/rhodium were used in the simulation. Both bremsstrahlung and characteristic x-ray production were included in the model. The simulated x-ray emission spectra were compared with two sets of spectra, those of Boone et al (1997 Med. Phys. 24 1863-74) and IPEM report 78. The {chi}{sup 2} test was used for the overall goodness of fit of the spectral data. There is good agreement between the simulated x-ray spectra and the comparison spectra as the test yielded a probability value of nearly 1. When the transmitted x-ray spectra for specific target/filter combinations were generated and compared with a measured molybdenum/rhodium spectrum and spectra generated in IPEM report 78, close agreement is also observed. This was demonstrated by the probability value for the {chi}{sup 2} test being almost 1 for all the cases. However, minor differences between the simulated spectra and the 'standard' ones are observed. (author)

Monte Carlo simulation of x-ray spectra in mammography

International Nuclear Information System (INIS)

Ng, K.P.

2000-01-01

A model for generating x-ray spectra in mammography is presented. This model used the ITS version 3 Monte Carlo code for simulating the radiation transport. Various target/filter combinations such as tungsten/aluminium, molybdenum/molybdenum, molybdenum/rhodium and rhodium/rhodium were used in the simulation. Both bremsstrahlung and characteristic x-ray production were included in the model. The simulated x-ray emission spectra were compared with two sets of spectra, those of Boone et al (1997 Med. Phys. 24 1863-74) and IPEM report 78. The χ 2 test was used for the overall goodness of fit of the spectral data. There is good agreement between the simulated x-ray spectra and the comparison spectra as the test yielded a probability value of nearly 1. When the transmitted x-ray spectra for specific target/filter combinations were generated and compared with a measured molybdenum/rhodium spectrum and spectra generated in IPEM report 78, close agreement is also observed. This was demonstrated by the probability value for the χ 2 test being almost 1 for all the cases. However, minor differences between the simulated spectra and the 'standard' ones are observed. (author)

Monte Carlo Methods in ICF (LIRPP Vol. 13)

Science.gov (United States)

Zimmerman, George B.

2016-10-01

Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved SOX in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.

Exploring Monte Carlo methods

CERN Document Server

Dunn, William L

2012-01-01

Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble

Specialized Monte Carlo codes versus general-purpose Monte Carlo codes

International Nuclear Information System (INIS)

Moskvin, Vadim; DesRosiers, Colleen; Papiez, Lech; Lu, Xiaoyi

2002-01-01

The possibilities of Monte Carlo modeling for dose calculations and optimization treatment are quite limited in radiation oncology applications. The main reason is that the Monte Carlo technique for dose calculations is time consuming while treatment planning may require hundreds of possible cases of dose simulations to be evaluated for dose optimization. The second reason is that general-purpose codes widely used in practice, require an experienced user to customize them for calculations. This paper discusses the concept of Monte Carlo code design that can avoid the main problems that are preventing wide spread use of this simulation technique in medical physics. (authors)

Monte Carlo principles and applications

Energy Technology Data Exchange (ETDEWEB)

Raeside, D E [Oklahoma Univ., Oklahoma City (USA). Health Sciences Center

1976-03-01

The principles underlying the use of Monte Carlo methods are explained, for readers who may not be familiar with the approach. The generation of random numbers is discussed, and the connection between Monte Carlo methods and random numbers is indicated. Outlines of two well established Monte Carlo sampling techniques are given, together with examples illustrating their use. The general techniques for improving the efficiency of Monte Carlo calculations are considered. The literature relevant to the applications of Monte Carlo calculations in medical physics is reviewed.

Monte Carlo and analytic simulations in nanoparticle-enhanced radiation therapy

Directory of Open Access Journals (Sweden)

Paro AD

2016-09-01

Full Text Available Autumn D Paro,1 Mainul Hossain,2 Thomas J Webster,1,3,4 Ming Su1,4 1Department of Chemical Engineering, Northeastern University, Boston, MA, USA; 2NanoScience Technology Center and School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida, USA; 3Excellence for Advanced Materials Research, King Abdulaziz University, Jeddah, Saudi Arabia; 4Wenzhou Institute of Biomaterials and Engineering, Chinese Academy of Science, Wenzhou Medical University, Zhejiang, People’s Republic of China Abstract: Analytical and Monte Carlo simulations have been used to predict dose enhancement factors in nanoparticle-enhanced X-ray radiation therapy. Both simulations predict an increase in dose enhancement in the presence of nanoparticles, but the two methods predict different levels of enhancement over the studied energy, nanoparticle materials, and concentration regime for several reasons. The Monte Carlo simulation calculates energy deposited by electrons and photons, while the analytical one only calculates energy deposited by source photons and photoelectrons; the Monte Carlo simulation accounts for electron–hole recombination, while the analytical one does not; and the Monte Carlo simulation randomly samples photon or electron path and accounts for particle interactions, while the analytical simulation assumes a linear trajectory. This study demonstrates that the Monte Carlo simulation will be a better choice to evaluate dose enhancement with nanoparticles in radiation therapy. Keywords: nanoparticle, dose enhancement, Monte Carlo simulation, analytical simulation, radiation therapy, tumor cell, X-ray 

11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

CERN Document Server

Nuyens, Dirk

2016-01-01

This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.

Monte Carlo studies of ZEPLIN III

CERN Document Server

Dawson, J; Davidge, D C R; Gillespie, J R; Howard, A S; Jones, W G; Joshi, M; Lebedenko, V N; Sumner, T J; Quenby, J J

2002-01-01

A Monte Carlo simulation of a two-phase xenon dark matter detector, ZEPLIN III, has been achieved. Results from the analysis of a simulated data set are presented, showing primary and secondary signal distributions from low energy gamma ray events.

Monte Carlo Simulation for Statistical Decay of Compound Nucleus

Directory of Open Access Journals (Sweden)

Chadwick M.B.

2012-02-01

Full Text Available We perform Monte Carlo simulations for neutron and γ-ray emissions from a compound nucleus based on the Hauser-Feshbach statistical theory. This Monte Carlo Hauser-Feshbach (MCHF method calculation, which gives us correlated information between emitted particles and γ-rays. It will be a powerful tool in many applications, as nuclear reactions can be probed in a more microscopic way. We have been developing the MCHF code, CGM, which solves the Hauser-Feshbach theory with the Monte Carlo method. The code includes all the standard models that used in a standard Hauser-Feshbach code, namely the particle transmission generator, the level density module, interface to the discrete level database, and so on. CGM can emit multiple neutrons, as long as the excitation energy of the compound nucleus is larger than the neutron separation energy. The γ-ray competition is always included at each compound decay stage, and the angular momentum and parity are conserved. Some calculations for a fission fragment 140Xe are shown as examples of the MCHF method, and the correlation between the neutron and γ-ray is discussed.

Monte Carlo simulation of X-ray imaging and spectroscopy experiments using quadric geometry and variance reduction techniques

Science.gov (United States)

Golosio, Bruno; Schoonjans, Tom; Brunetti, Antonio; Oliva, Piernicola; Masala, Giovanni Luca

2014-03-01

The simulation of X-ray imaging experiments is often performed using deterministic codes, which can be relatively fast and easy to use. However, such codes are generally not suitable for the simulation of even slightly more complex experimental conditions, involving, for instance, first-order or higher-order scattering, X-ray fluorescence emissions, or more complex geometries, particularly for experiments that combine spatial resolution with spectral information. In such cases, simulations are often performed using codes based on the Monte Carlo method. In a simple Monte Carlo approach, the interaction position of an X-ray photon and the state of the photon after an interaction are obtained simply according to the theoretical probability distributions. This approach may be quite inefficient because the final channels of interest may include only a limited region of space or photons produced by a rare interaction, e.g., fluorescent emission from elements with very low concentrations. In the field of X-ray fluorescence spectroscopy, this problem has been solved by combining the Monte Carlo method with variance reduction techniques, which can reduce the computation time by several orders of magnitude. In this work, we present a C++ code for the general simulation of X-ray imaging and spectroscopy experiments, based on the application of the Monte Carlo method in combination with variance reduction techniques, with a description of sample geometry based on quadric surfaces. We describe the benefits of the object-oriented approach in terms of code maintenance, the flexibility of the program for the simulation of different experimental conditions and the possibility of easily adding new modules. Sample applications in the fields of X-ray imaging and X-ray spectroscopy are discussed. Catalogue identifier: AERO_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERO_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland

Particle-gamma and particle-particle correlations in nuclear reactions using Monte Carlo Hauser-Feshback model

Energy Technology Data Exchange (ETDEWEB)

Kawano, Toshihiko [Los Alamos National Laboratory; Talou, Patrick [Los Alamos National Laboratory; Watanabe, Takehito [Los Alamos National Laboratory; Chadwick, Mark [Los Alamos National Laboratory

2010-01-01

Monte Carlo simulations for particle and {gamma}-ray emissions from an excited nucleus based on the Hauser-Feshbach statistical theory are performed to obtain correlated information between emitted particles and {gamma}-rays. We calculate neutron induced reactions on {sup 51}V to demonstrate unique advantages of the Monte Carlo method. which are the correlated {gamma}-rays in the neutron radiative capture reaction, the neutron and {gamma}-ray correlation, and the particle-particle correlations at higher energies. It is shown that properties in nuclear reactions that are difficult to study with a deterministic method can be obtained with the Monte Carlo simulations.

Assessment of the suitability of different random number generators for Monte Carlo simulations in gamma-ray spectrometry

International Nuclear Information System (INIS)

Cornejo Diaz, N.; Vergara Gil, A.; Jurado Vargas, M.

2010-01-01

The Monte Carlo method has become a valuable numerical laboratory framework in which to simulate complex physical systems. It is based on the generation of pseudo-random number sequences by numerical algorithms called random generators. In this work we assessed the suitability of different well-known random number generators for the simulation of gamma-ray spectrometry systems during efficiency calibrations. The assessment was carried out in two stages. The generators considered (Delphi's linear congruential, mersenne twister, XorShift, multiplier with carry, universal virtual array, and non-periodic logistic map based generator) were first evaluated with different statistical empirical tests, including moments, correlations, uniformity, independence of terms and the DIEHARD battery of tests. In a second step, an application-specific test was conducted by implementing the generators in our Monte Carlo program DETEFF and comparing the results obtained with them. The calculations were performed with two different CPUs, for a typical HpGe detector and a water sample in Marinelli geometry, with gamma-rays between 59 and 1800 keV. For the Non-periodic Logistic Map based generator, dependence of the most significant bits was evident. This explains the bias, in excess of 5%, of the efficiency values obtained with this generator. The results of the application-specific assessment and the statistical performance of the other algorithms studied indicate their suitability for the Monte Carlo simulation of gamma-ray spectrometry systems for efficiency calculations.

Assessment of the suitability of different random number generators for Monte Carlo simulations in gamma-ray spectrometry.

Science.gov (United States)

Díaz, N Cornejo; Gil, A Vergara; Vargas, M Jurado

2010-03-01

The Monte Carlo method has become a valuable numerical laboratory framework in which to simulate complex physical systems. It is based on the generation of pseudo-random number sequences by numerical algorithms called random generators. In this work we assessed the suitability of different well-known random number generators for the simulation of gamma-ray spectrometry systems during efficiency calibrations. The assessment was carried out in two stages. The generators considered (Delphi's linear congruential, mersenne twister, XorShift, multiplier with carry, universal virtual array, and non-periodic logistic map based generator) were first evaluated with different statistical empirical tests, including moments, correlations, uniformity, independence of terms and the DIEHARD battery of tests. In a second step, an application-specific test was conducted by implementing the generators in our Monte Carlo program DETEFF and comparing the results obtained with them. The calculations were performed with two different CPUs, for a typical HpGe detector and a water sample in Marinelli geometry, with gamma-rays between 59 and 1800 keV. For the Non-periodic Logistic Map based generator, dependence of the most significant bits was evident. This explains the bias, in excess of 5%, of the efficiency values obtained with this generator. The results of the application-specific assessment and the statistical performance of the other algorithms studied indicate their suitability for the Monte Carlo simulation of gamma-ray spectrometry systems for efficiency calculations. Copyright 2009 Elsevier Ltd. All rights reserved.

Characterization of an extrapolation chamber for low-energy X-rays: Experimental and Monte Carlo preliminary results

Energy Technology Data Exchange (ETDEWEB)

Neves, Lucio P., E-mail: lpneves@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN), Comissao Nacional de Energia Nuclear, Av. Prof. Lineu Prestes 2242, 05508-000 Sao Paulo, SP (Brazil); Silva, Eric A.B., E-mail: ebrito@usp.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN), Comissao Nacional de Energia Nuclear, Av. Prof. Lineu Prestes 2242, 05508-000 Sao Paulo, SP (Brazil); Perini, Ana P., E-mail: aperini@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN), Comissao Nacional de Energia Nuclear, Av. Prof. Lineu Prestes 2242, 05508-000 Sao Paulo, SP (Brazil); Maidana, Nora L., E-mail: nmaidana@if.usp.br [Universidade de Sao Paulo, Instituto de Fisica, Travessa R 187, 05508-900 Sao Paulo, SP (Brazil); Caldas, Linda V.E., E-mail: lcaldas@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN), Comissao Nacional de Energia Nuclear, Av. Prof. Lineu Prestes 2242, 05508-000 Sao Paulo, SP (Brazil)

2012-07-15

The extrapolation chamber is a parallel-plate ionization chamber that allows variation of its air-cavity volume. In this work, an experimental study and MCNP-4C Monte Carlo code simulations of an ionization chamber designed and constructed at the Calibration Laboratory at IPEN to be used as a secondary dosimetry standard for low-energy X-rays are reported. The results obtained were within the international recommendations, and the simulations showed that the components of the extrapolation chamber may influence its response up to 11.0%. - Highlights: Black-Right-Pointing-Pointer A homemade extrapolation chamber was studied experimentally and with Monte Carlo. Black-Right-Pointing-Pointer It was characterized as a secondary dosimetry standard, for low energy X-rays. Black-Right-Pointing-Pointer Several characterization tests were performed and the results were satisfactory. Black-Right-Pointing-Pointer Simulation showed that its components may influence the response up to 11.0%. Black-Right-Pointing-Pointer This chamber may be used as a secondary standard at our laboratory.

Monte Carlo simulation of photon scattering in x-ray absorption imaging of high-intensity discharge lamps

Energy Technology Data Exchange (ETDEWEB)

Curry, J J, E-mail: jjcurry@nist.go [National Institute of Standards and Technology, Gaithersburg, MD 20899-8422 (United States)

2010-06-16

Coherent and incoherent scattering of x-rays during x-ray absorption imaging of high-intensity discharge lamps have been studied with Monte Carlo simulations developed specifically for this purpose. The Monte Carlo code is described and some initial results are discussed. Coherent scattering, because of its angular concentration in the forward direction, is found to be the most significant scattering mechanism. Incoherent scattering, although comparably strong, is not as significant because it results primarily in photons being scattered in the rearward direction and therefore out of the detector. Coherent scattering interferes with the detected absorption signal because the path of a scattered photon through the object to be imaged is unknown. Although scattering is usually a small effect, it can be significant in regions of high contrast. At the discharge/wall interface, as many as 50% of the detected photons are scattered photons. The effect of scattering on analysis of Hg distributions has not yet been quantified.

On the use of stochastic approximation Monte Carlo for Monte Carlo integration

KAUST Repository

Liang, Faming

2009-03-01

The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration via a dynamically weighted estimator by calling some results from the literature of nonhomogeneous Markov chains. Our numerical results indicate that SAMC can yield significant savings over conventional Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, for the problems for which the energy landscape is rugged. © 2008 Elsevier B.V. All rights reserved.

On the use of stochastic approximation Monte Carlo for Monte Carlo integration

KAUST Repository

Liang, Faming

2009-01-01

The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration

Monte-Carlo estimation of the inflight performance of the GEMS satellite x-ray polarimeter

Science.gov (United States)

Kitaguchi, Takao; Tamagawa, Toru; Hayato, Asami; Enoto, Teruaki; Yoshikawa, Akifumi; Kaneko, Kenta; Takeuchi, Yoko; Black, Kevin; Hill, Joanne; Jahoda, Keith; Krizmanic, John; Sturner, Steven; Griffiths, Scott; Kaaret, Philip; Marlowe, Hannah

2014-07-01

We report a Monte-Carlo estimation of the in-orbit performance of a cosmic X-ray polarimeter designed to be installed on the focal plane of a small satellite. The simulation uses GEANT for the transport of photons and energetic particles and results from Magboltz for the transport of secondary electrons in the detector gas. We validated the simulation by comparing spectra and modulation curves with actual data taken with radioactive sources and an X-ray generator. We also estimated the in-orbit background induced by cosmic radiation in low Earth orbit.

Monte Carlo simulation of the neutron-induced prompt γ ray spectroscopy of the CW abandoned by Japan

International Nuclear Information System (INIS)

Wang Bairong; Yang Zhongping; Zhang Wenzhong

2005-01-01

This paper introduced the principle of identifying the chemical weapon by neutron-induced prompt γ ray, simulated and analyzed the neutron-induced prompt γ ray spectroscopy of chemical weapon abandoned by Japan in the different condition, using the MCNP-4C Monte Carlo program, whereby supply important datum and reference for the aftertime deeper research and disposal of Japan-abandoned chemical weapon. (authors)

Vectorized Monte Carlo

International Nuclear Information System (INIS)

Brown, F.B.

1981-01-01

Examination of the global algorithms and local kernels of conventional general-purpose Monte Carlo codes shows that multigroup Monte Carlo methods have sufficient structure to permit efficient vectorization. A structured multigroup Monte Carlo algorithm for vector computers is developed in which many particle events are treated at once on a cell-by-cell basis. Vectorization of kernels for tracking and variance reduction is described, and a new method for discrete sampling is developed to facilitate the vectorization of collision analysis. To demonstrate the potential of the new method, a vectorized Monte Carlo code for multigroup radiation transport analysis was developed. This code incorporates many features of conventional general-purpose production codes, including general geometry, splitting and Russian roulette, survival biasing, variance estimation via batching, a number of cutoffs, and generalized tallies of collision, tracklength, and surface crossing estimators with response functions. Predictions of vectorized performance characteristics for the CYBER-205 were made using emulated coding and a dynamic model of vector instruction timing. Computation rates were examined for a variety of test problems to determine sensitivities to batch size and vector lengths. Significant speedups are predicted for even a few hundred particles per batch, and asymptotic speedups by about 40 over equivalent Amdahl 470V/8 scalar codes arepredicted for a few thousand particles per batch. The principal conclusion is that vectorization of a general-purpose multigroup Monte Carlo code is well worth the significant effort required for stylized coding and major algorithmic changes

Adjoint electron Monte Carlo calculations

International Nuclear Information System (INIS)

Jordan, T.M.

1986-01-01

Adjoint Monte Carlo is the most efficient method for accurate analysis of space systems exposed to natural and artificially enhanced electron environments. Recent adjoint calculations for isotropic electron environments include: comparative data for experimental measurements on electronics boxes; benchmark problem solutions for comparing total dose prediction methodologies; preliminary assessment of sectoring methods used during space system design; and total dose predictions on an electronics package. Adjoint Monte Carlo, forward Monte Carlo, and experiment are in excellent agreement for electron sources that simulate space environments. For electron space environments, adjoint Monte Carlo is clearly superior to forward Monte Carlo, requiring one to two orders of magnitude less computer time for relatively simple geometries. The solid-angle sectoring approximations used for routine design calculations can err by more than a factor of 2 on dose in simple shield geometries. For critical space systems exposed to severe electron environments, these potential sectoring errors demand the establishment of large design margins and/or verification of shield design by adjoint Monte Carlo/experiment

Analysis of the design of an X-ray tube using Monte Carlo

International Nuclear Information System (INIS)

Pena V, J. D.; Sosa A, M. A.; Ceron, P. V.; Vallejo, M. A.; Vega C, H. R.

2017-10-01

In this paper we present the Monte Carlo analysis of the X-rays produced by a rotating X-ray tube of the Siemens brand that is used in tomographs for clinical use. The work was done with the MCNP6 code with which the tube was modeled and the primary X-ray spectra produced during the interaction of monoenergetic electrons of 130 keV were calculated. The X-ray spectra were obtained by varying some parameters such as: the angle of the anode (15 to 20 degrees), the type of target (Tungsten, Molybdenum and Rhodium) and the thickness of the filter (3, 5, 10 and 15 mm). In order to have a good statistic 10 7 stories were used. Though the estimators f2 and f5 the X-ray spectra and the total fluencies were estimated. This information will be used to calculate the dose absorbed in the lens and the thyroid gland in patients undergoing radio diagnosis procedures. (Author)

Monte Carlo: Basics

OpenAIRE

Murthy, K. P. N.

2001-01-01

An introduction to the basics of Monte Carlo is given. The topics covered include, sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, central limit theorem (stable distribution, Levy distribution), random numbers (generation and testing), random sampling techniques (inversion, rejection, sampling from a Gaussian, Metropolis sampling), analogue Monte Carlo and Importance sampling (exponential b...

EGS-Ray, a program for the visualization of Monte-Carlo calculations in the radiation physics

International Nuclear Information System (INIS)

Kleinschmidt, C.

2001-01-01

A Windows program is introduced which allows a relatively easy and interactive access to Monte Carlo techniques in clinical radiation physics. Furthermore, this serves as a visualization tool of the methodology and the results of Monte Carlo simulations. The program requires only little effort to formulate and calculate a Monte Carlo problem. The Monte Carlo module of the program is based on the well-known EGS4/PRESTA code. The didactic features of the program are presented using several examples common to the routine of the clinical radiation physicist. (orig.) [de

MORSE Monte Carlo code

International Nuclear Information System (INIS)

Cramer, S.N.

1984-01-01

The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described

Monte Carlo Investigation of Phosphor Screens for X-ray Imaging

International Nuclear Information System (INIS)

Lim, Chang Hwy; Cheong, Min Ho; Cho, Min Kook; Shon, Choel Soon; Kim, Ho Kyung

2006-01-01

In order to detect X rays with pixel detectors, there are two technical methods; a direct detection using photoconductive material that permits the conversion of the incident X rays into the signal charges, and an indirect detection using scintillation material that converts the incident X rays into the optical photons. Therefore, two-dimensional (2D) photosensitive pixel array is necessary for the indirect-detection scheme. Terbium-doped gadolinium oxysulfide (Gd 2 O 2 S:Tb) phosphor screen is the most popular X-ray converter, and often employed to the digital radiographic system owing to its well-known technology and easy handling in size, thickness, and flexibility. Furthermore, the cost is effective. In cascaded imaging chains of the indirect-detection system, the phosphor screen is served as the first stage. Since the image signal-to-noise ratio (SNR) is irreversible through the cascaded system, the phosphor screen is largely responsible for the eventual image quality. For the various radiation qualities suggested by IEC (International Electrotechnical Commission, Report 1267), we have investigated important physical quantities of Gd 2 O 2 S:Tb screen with a wide range of coverages (34 . 135 mg/cm 2 ) by using Monte Carlo calculations. The results will be useful for the optimal design of digital X-ray imaging systems

BACKWARD AND FORWARD MONTE CARLO METHOD IN POLARIZED RADIATIVE TRANSFER

Energy Technology Data Exchange (ETDEWEB)

Yong, Huang; Guo-Dong, Shi; Ke-Yong, Zhu, E-mail: huangy_zl@263.net [School of Aeronautical Science and Engineering, Beihang University, Beijing 100191 (China)

2016-03-20

In general, the Stocks vector cannot be calculated in reverse in the vector radiative transfer. This paper presents a novel backward and forward Monte Carlo simulation strategy to study the vector radiative transfer in the participated medium. A backward Monte Carlo process is used to calculate the ray trajectory and the endpoint of the ray. The Stocks vector is carried out by a forward Monte Carlo process. A one-dimensional graded index semi-transparent medium was presented as the physical model and the thermal emission consideration of polarization was studied in the medium. The solution process to non-scattering, isotropic scattering, and the anisotropic scattering medium, respectively, is discussed. The influence of the optical thickness and albedo on the Stocks vector are studied. The results show that the U, V-components of the apparent Stocks vector are very small, but the Q-component of the apparent Stocks vector is relatively larger, which cannot be ignored.

Improved Monte Carlo modelling of multi-energy a-rays penetration through thick stratified shielding slabs

International Nuclear Information System (INIS)

Bakos, G.C.

2001-01-01

This paper deals with the application of Monte Carlo method for the calculation of dose build up factor of, mixed 1.37 and 2.75 MeV, a-rays penetration through stratified shielding slabs. Six double layer shielding slabs namely, 12 A l+Fe, 12 A l+Pb, 6 F e+Al, 6 F e+Pb, 4 P b+Al, 4 P b+Fe were examined. Furthermore, experimental and theoretical results are also presented. The experimental results were taken from the experimental facility installed at the Universities Research reactor Center (Risley, UK). Activated Na2SO3 solution provided a uniform Na-24 disc source of a-rays at both energies (1.37 and 2.75 MeV) with equal intensity. The theoretical results were calculated using the Bowman and Trubey formula. This formula takes into account an exponentially decaying function of the shield thickness (in mfp) to the end point of the multi-layer slab. The experimental and theoretical results were used to evaluate the simulation results produced from a Monte Carlo program (DUTMONCA code) which was developed in Democritus University of Thrace (Xanthi, Greece). The DUTMONCA code was written in Pascal language and run on an Intel PIII-800 microprocessor. The developed code (which is an improved version of an existing Monte Carlo program) has the ability to produce good results for thick shielding slabs overcoming the problems encountered in older version program. The simulation results are compared with experimental and theoretical results. Good agreement can be observed, even for thick layer shielding slabs, although there are some wayward experimental values which are due to sources of error associated with the experimental procedure

Monte Carlo theory and practice

International Nuclear Information System (INIS)

James, F.

1987-01-01

Historically, the first large-scale calculations to make use of the Monte Carlo method were studies of neutron scattering and absorption, random processes for which it is quite natural to employ random numbers. Such calculations, a subset of Monte Carlo calculations, are known as direct simulation, since the 'hypothetical population' of the narrower definition above corresponds directly to the real population being studied. The Monte Carlo method may be applied wherever it is possible to establish equivalence between the desired result and the expected behaviour of a stochastic system. The problem to be solved may already be of a probabilistic or statistical nature, in which case its Monte Carlo formulation will usually be a straightforward simulation, or it may be of a deterministic or analytic nature, in which case an appropriate Monte Carlo formulation may require some imagination and may appear contrived or artificial. In any case, the suitability of the method chosen will depend on its mathematical properties and not on its superficial resemblance to the problem to be solved. The authors show how Monte Carlo techniques may be compared with other methods of solution of the same physical problem

Monte Carlo Methods in Physics

International Nuclear Information System (INIS)

Santoso, B.

1997-01-01

Method of Monte Carlo integration is reviewed briefly and some of its applications in physics are explained. A numerical experiment on random generators used in the monte Carlo techniques is carried out to show the behavior of the randomness of various methods in generating them. To account for the weight function involved in the Monte Carlo, the metropolis method is used. From the results of the experiment, one can see that there is no regular patterns of the numbers generated, showing that the program generators are reasonably good, while the experimental results, shows a statistical distribution obeying statistical distribution law. Further some applications of the Monte Carlo methods in physics are given. The choice of physical problems are such that the models have available solutions either in exact or approximate values, in which comparisons can be mode, with the calculations using the Monte Carlo method. Comparison show that for the models to be considered, good agreement have been obtained

The integral first collision kernel method for gamma-ray skyshine analysis[Skyshine; Gamma-ray; First collision kernel; Monte Carlo calculation

Energy Technology Data Exchange (ETDEWEB)

Sheu, R.-D.; Chui, C.-S.; Jiang, S.-H. E-mail: shjiang@mx.nthu.edu.tw

2003-12-01

A simplified method, based on the integral of the first collision kernel, is presented for performing gamma-ray skyshine calculations for the collimated sources. The first collision kernels were calculated in air for a reference air density by use of the EGS4 Monte Carlo code. These kernels can be applied to other air densities by applying density corrections. The integral first collision kernel (IFCK) method has been used to calculate two of the ANSI/ANS skyshine benchmark problems and the results were compared with a number of other commonly used codes. Our results were generally in good agreement with others but only spend a small fraction of the computation time required by the Monte Carlo calculations. The scheme of the IFCK method for dealing with lots of source collimation geometry is also presented in this study.

Analysis of the design of an X-ray tube using Monte Carlo; Analisis del diseno de un tubo de rayos X mediante Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

Pena V, J. D.; Sosa A, M. A.; Ceron, P. V.; Vallejo, M. A. [Universidad de Guanajuato, Division de Ciencias e Ingenierias, Loma del Bosque No. 103, Lomas del Campestre, 37150 Leon, Guanajuato (Mexico); Vega C, H. R., E-mail: jd.penavidal@ugto.mx [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98060 Zacatecas, Zac. (Mexico)

2017-10-15

In this paper we present the Monte Carlo analysis of the X-rays produced by a rotating X-ray tube of the Siemens brand that is used in tomographs for clinical use. The work was done with the MCNP6 code with which the tube was modeled and the primary X-ray spectra produced during the interaction of monoenergetic electrons of 130 keV were calculated. The X-ray spectra were obtained by varying some parameters such as: the angle of the anode (15 to 20 degrees), the type of target (Tungsten, Molybdenum and Rhodium) and the thickness of the filter (3, 5, 10 and 15 mm). In order to have a good statistic 10{sup 7} stories were used. Though the estimators f2 and f5 the X-ray spectra and the total fluencies were estimated. This information will be used to calculate the dose absorbed in the lens and the thyroid gland in patients undergoing radio diagnosis procedures. (Author)

Monte Carlo techniques in radiation therapy

CERN Document Server

Verhaegen, Frank

2013-01-01

Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data. With Monte Carlo-based treatment planning tools now available from commercial vendors, a complete transition to Monte Carlo-based dose calculation methods in radiotherapy could likely take place in the next decade. Monte Carlo Techniques in Radiation Therapy explores the use of Monte Carlo methods for modeling various features of internal and external radiation sources, including light ion beams. The book-the first of its kind-addresses applications of the Monte Carlo particle transport simulation technique in radiation therapy, mainly focusing on external beam radiotherapy and brachytherapy. It presents the mathematical and technical aspects of the methods in particle transport simulations. The book also discusses the modeling of medical linacs and other irradiation devices; issues specific...

Statistical implications in Monte Carlo depletions - 051

International Nuclear Information System (INIS)

Zhiwen, Xu; Rhodes, J.; Smith, K.

2010-01-01

As a result of steady advances of computer power, continuous-energy Monte Carlo depletion analysis is attracting considerable attention for reactor burnup calculations. The typical Monte Carlo analysis is set up as a combination of a Monte Carlo neutron transport solver and a fuel burnup solver. Note that the burnup solver is a deterministic module. The statistical errors in Monte Carlo solutions are introduced into nuclide number densities and propagated along fuel burnup. This paper is towards the understanding of the statistical implications in Monte Carlo depletions, including both statistical bias and statistical variations in depleted fuel number densities. The deterministic Studsvik lattice physics code, CASMO-5, is modified to model the Monte Carlo depletion. The statistical bias in depleted number densities is found to be negligible compared to its statistical variations, which, in turn, demonstrates the correctness of the Monte Carlo depletion method. Meanwhile, the statistical variation in number densities generally increases with burnup. Several possible ways of reducing the statistical errors are discussed: 1) to increase the number of individual Monte Carlo histories; 2) to increase the number of time steps; 3) to run additional independent Monte Carlo depletion cases. Finally, a new Monte Carlo depletion methodology, called the batch depletion method, is proposed, which consists of performing a set of independent Monte Carlo depletions and is thus capable of estimating the overall statistical errors including both the local statistical error and the propagated statistical error. (authors)

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

Monte Carlo simulation for IRRMA

International Nuclear Information System (INIS)

Gardner, R.P.; Liu Lianyan

2000-01-01

Monte Carlo simulation is fast becoming a standard approach for many radiation applications that were previously treated almost entirely by experimental techniques. This is certainly true for Industrial Radiation and Radioisotope Measurement Applications - IRRMA. The reasons for this include: (1) the increased cost and inadequacy of experimentation for design and interpretation purposes; (2) the availability of low cost, large memory, and fast personal computers; and (3) the general availability of general purpose Monte Carlo codes that are increasingly user-friendly, efficient, and accurate. This paper discusses the history and present status of Monte Carlo simulation for IRRMA including the general purpose (GP) and specific purpose (SP) Monte Carlo codes and future needs - primarily from the experience of the authors

Population synthesis of radio and gamma-ray millisecond pulsars using Markov Chain Monte Carlo techniques

Science.gov (United States)

Gonthier, Peter L.; Koh, Yew-Meng; Kust Harding, Alice

2016-04-01

We present preliminary results of a new population synthesis of millisecond pulsars (MSP) from the Galactic disk using Markov Chain Monte Carlo techniques to better understand the model parameter space. We include empirical radio and gamma-ray luminosity models that are dependent on the pulsar period and period derivative with freely varying exponents. The magnitudes of the model luminosities are adjusted to reproduce the number of MSPs detected by a group of thirteen radio surveys as well as the MSP birth rate in the Galaxy and the number of MSPs detected by Fermi. We explore various high-energy emission geometries like the slot gap, outer gap, two pole caustic and pair starved polar cap models. The parameters associated with the birth distributions for the mass accretion rate, magnetic field, and period distributions are well constrained. With the set of four free parameters, we employ Markov Chain Monte Carlo simulations to explore the model parameter space. We present preliminary comparisons of the simulated and detected distributions of radio and gamma-ray pulsar characteristics. We estimate the contribution of MSPs to the diffuse gamma-ray background with a special focus on the Galactic Center.We express our gratitude for the generous support of the National Science Foundation (RUI: AST-1009731), Fermi Guest Investigator Program and the NASA Astrophysics Theory and Fundamental Program (NNX09AQ71G).

Cosmic rays Monte Carlo simulations for the Extreme Energy Events Project

CERN Document Server

Abbrescia, M; Aiola, S; Antolini, R; Avanzini, C; Baldini Ferroli, R; Bencivenni, G; Bossini, E; Bressan, E; Chiavassa, A; Cicalò, C; Cifarelli, L; Coccia, E; De Gruttola, D; De Pasquale, S; Di Giovanni, A; D'Incecco, M; Dreucci, M; Fabbri, F L; Frolov, V; Garbini, M; Gemme, G; Gnesi, I; Gustavino, C; Hatzifotiadou, D; La Rocca, P; Li, S; Librizzi, F; Maggiora, A; Massai, M; Miozzi, S; Panareo, M; Paoletti, R; Perasso, L; Pilo, F; Piragino, G; Regano, A; Riggi, F; Righini, G C; Sartorelli, G; Scapparone, E; Scribano, A; Selvi, M; Serci, S; Siddi, E; Spandre, G; Squarcia, S; Taiuti, M; Tosello, F; Votano, L; Williams, M C S; Yánez, G; Zichichi, A; Zuyeuski, R

2014-01-01

The Extreme Energy Events Project (EEE Project) is an innovative experiment to study very high energy cosmic rays by means of the detection of the associated air shower muon component. It consists of a network of tracking detectors installed inside Italian High Schools. Each tracking detector, called EEE telescope, is composed of three Multigap Resistive Plate Chambers (MRPCs). At present, 43 telescopes are installed and taking data, opening the way for the detection of far away coincidences over a total area of about 3 × 10 5 km 2 . In this paper we present the Monte Carlo simulations that have been performed to predict the expected coincidence rate between distant EEE telescopes.

MCViNE – An object oriented Monte Carlo neutron ray tracing simulation package

Energy Technology Data Exchange (ETDEWEB)

Lin, Jiao Y.Y., E-mail: linjiao@ornl.gov [Caltech Center for Advanced Computing Research, California Institute of Technology (United States); Department of Applied Physics and Materials Science, California Institute of Technology (United States); Neutron Data Analysis and Visualization Division, Oak Ridge National Laboratory (United States); Smith, Hillary L. [Department of Applied Physics and Materials Science, California Institute of Technology (United States); Granroth, Garrett E., E-mail: granrothge@ornl.gov [Neutron Data Analysis and Visualization Division, Oak Ridge National Laboratory (United States); Abernathy, Douglas L.; Lumsden, Mark D.; Winn, Barry; Aczel, Adam A. [Quantum Condensed Matter Division, Oak Ridge National Laboratory (United States); Aivazis, Michael [Caltech Center for Advanced Computing Research, California Institute of Technology (United States); Fultz, Brent, E-mail: btf@caltech.edu [Department of Applied Physics and Materials Science, California Institute of Technology (United States)

2016-02-21

MCViNE (Monte-Carlo VIrtual Neutron Experiment) is an open-source Monte Carlo (MC) neutron ray-tracing software for performing computer modeling and simulations that mirror real neutron scattering experiments. We exploited the close similarity between how instrument components are designed and operated and how such components can be modeled in software. For example we used object oriented programming concepts for representing neutron scatterers and detector systems, and recursive algorithms for implementing multiple scattering. Combining these features together in MCViNE allows one to handle sophisticated neutron scattering problems in modern instruments, including, for example, neutron detection by complex detector systems, and single and multiple scattering events in a variety of samples and sample environments. In addition, MCViNE can use simulation components from linear-chain-based MC ray tracing packages which facilitates porting instrument models from those codes. Furthermore it allows for components written solely in Python, which expedites prototyping of new components. These developments have enabled detailed simulations of neutron scattering experiments, with non-trivial samples, for time-of-flight inelastic instruments at the Spallation Neutron Source. Examples of such simulations for powder and single-crystal samples with various scattering kernels, including kernels for phonon and magnon scattering, are presented. With simulations that closely reproduce experimental results, scattering mechanisms can be turned on and off to determine how they contribute to the measured scattering intensities, improving our understanding of the underlying physics.

X-ray scattering in X-ray fluorescence spectra with X-ray tube excitation - Modelling, experiment, and Monte-Carlo simulation

International Nuclear Information System (INIS)

Hodoroaba, V.-D.; Radtke, M.; Vincze, L.; Rackwitz, V.; Reuter, D.

2010-01-01

X-ray scattering may contribute significantly to the spectral background of X-ray fluorescence (XRF) spectra. Based on metrological measurements carried out with a scanning electron microscope (SEM) having attached a well characterised X-ray source (polychromatic X-ray tube) and a calibrated energy dispersive X-ray spectrometer (EDS) the accuracy of a physical model for X-ray scattering is systematically evaluated for representative samples. The knowledge of the X-ray spectrometer efficiency, but also of the spectrometer response functions makes it possible to define a physical spectral background of XRF spectra. Background subtraction relying on purely mathematical procedures is state-of-the-art. The results produced by the analytical model are at least as reliable as those obtained by Monte-Carlo simulations, even without considering the very challenging contribution of multiple scattering. Special attention has been paid to Compton broadening. Relevant applications of the implementation of the analytical model presented in this paper are the prediction of the limits of detection for particular cases or the determination of the transmission of X-ray polycapillary lenses.

SU-F-T-575: Verification of a Monte-Carlo Small Field SRS/SBRT Dose Calculation System

International Nuclear Information System (INIS)

Sudhyadhom, A; McGuinness, C; Descovich, M

2016-01-01

Purpose: To develop a methodology for validation of a Monte-Carlo dose calculation model for robotic small field SRS/SBRT deliveries. Methods: In a robotic treatment planning system, a Monte-Carlo model was iteratively optimized to match with beam data. A two-part analysis was developed to verify this model. 1) The Monte-Carlo model was validated in a simulated water phantom versus a Ray-Tracing calculation on a single beam collimator-by-collimator calculation. 2) The Monte-Carlo model was validated to be accurate in the most challenging situation, lung, by acquiring in-phantom measurements. A plan was created and delivered in a CIRS lung phantom with film insert. Separately, plans were delivered in an in-house created lung phantom with a PinPoint chamber insert within a lung simulating material. For medium to large collimator sizes, a single beam was delivered to the phantom. For small size collimators (10, 12.5, and 15mm), a robotically delivered plan was created to generate a uniform dose field of irradiation over a 2×2cm 2 area. Results: Dose differences in simulated water between Ray-Tracing and Monte-Carlo were all within 1% at dmax and deeper. Maximum dose differences occurred prior to dmax but were all within 3%. Film measurements in a lung phantom show high correspondence of over 95% gamma at the 2%/2mm level for Monte-Carlo. Ion chamber measurements for collimator sizes of 12.5mm and above were within 3% of Monte-Carlo calculated values. Uniform irradiation involving the 10mm collimator resulted in a dose difference of ∼8% for both Monte-Carlo and Ray-Tracing indicating that there may be limitations with the dose calculation. Conclusion: We have developed a methodology to validate a Monte-Carlo model by verifying that it matches in water and, separately, that it corresponds well in lung simulating materials. The Monte-Carlo model and algorithm tested may have more limited accuracy for 10mm fields and smaller.

The Monte Carlo simulation of the neutron-induced prompt gamma ray spectroscopy of the CW abandoned by Japan

International Nuclear Information System (INIS)

Wang Bairong; Yang Zhongping; Zhan Wenzhong

2003-01-01

This paper introduced the principle of identifying the chemical weapon abandoned by Japan by neutron-induced prompt gamma ray. Using the MCNP-4C Monte Carlo program, this paper simulated and analyzed the neutron-induced prompt gamma ray spectroscopy of chemical weapon abandoned by Japan, whereby supply important datum and reference for the aftertime deeper research and disposal of Japan-abandoned chemical weapon. (authors)

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

(U) Introduction to Monte Carlo Methods

Energy Technology Data Exchange (ETDEWEB)

Hungerford, Aimee L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-03-20

Monte Carlo methods are very valuable for representing solutions to particle transport problems. Here we describe a “cook book” approach to handling the terms in a transport equation using Monte Carlo methods. Focus is on the mechanics of a numerical Monte Carlo code, rather than the mathematical foundations of the method.

Hybrid SN/Monte Carlo research and results

International Nuclear Information System (INIS)

Baker, R.S.

1993-01-01

The neutral particle transport equation is solved by a hybrid method that iteratively couples regions where deterministic (S N ) and stochastic (Monte Carlo) methods are applied. The Monte Carlo and S N regions are fully coupled in the sense that no assumption is made about geometrical separation or decoupling. The hybrid Monte Carlo/S N method provides a new means of solving problems involving both optically thick and optically thin regions that neither Monte Carlo nor S N is well suited for by themselves. The hybrid method has been successfully applied to realistic shielding problems. The vectorized Monte Carlo algorithm in the hybrid method has been ported to the massively parallel architecture of the Connection Machine. Comparisons of performance on a vector machine (Cray Y-MP) and the Connection Machine (CM-2) show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when realistic problems requiring variance reduction are considered. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well

Population Synthesis of Radio and Y-ray Normal, Isolated Pulsars Using Markov Chain Monte Carlo

Science.gov (United States)

Billman, Caleb; Gonthier, P. L.; Harding, A. K.

2013-04-01

We present preliminary results of a population statistics study of normal pulsars (NP) from the Galactic disk using Markov Chain Monte Carlo techniques optimized according to two different methods. The first method compares the detected and simulated cumulative distributions of series of pulsar characteristics, varying the model parameters to maximize the overall agreement. The advantage of this method is that the distributions do not have to be binned. The other method varies the model parameters to maximize the log of the maximum likelihood obtained from the comparisons of four-two dimensional distributions of radio and γ-ray pulsar characteristics. The advantage of this method is that it provides a confidence region of the model parameter space. The computer code simulates neutron stars at birth using Monte Carlo procedures and evolves them to the present assuming initial spatial, kick velocity, magnetic field, and period distributions. Pulsars are spun down to the present and given radio and γ-ray emission characteristics, implementing an empirical γ-ray luminosity model. A comparison group of radio NPs detected in ten-radio surveys is used to normalize the simulation, adjusting the model radio luminosity to match a birth rate. We include the Fermi pulsars in the forthcoming second pulsar catalog. We present preliminary results comparing the simulated and detected distributions of radio and γ-ray NPs along with a confidence region in the parameter space of the assumed models. We express our gratitude for the generous support of the National Science Foundation (REU and RUI), Fermi Guest Investigator Program and the NASA Astrophysics Theory and Fundamental Program.

A new Monte Carlo code for simulation of the effect of irregular surfaces on X-ray spectra

Energy Technology Data Exchange (ETDEWEB)

Brunetti, Antonio, E-mail: brunetti@uniss.it; Golosio, Bruno

2014-04-01

Generally, quantitative X-ray fluorescence (XRF) analysis estimates the content of chemical elements in a sample based on the areas of the fluorescence peaks in the energy spectrum. Besides the concentration of the elements, the peak areas depend also on the geometrical conditions. In fact, the estimate of the peak areas is simple if the sample surface is smooth and if the spectrum shows a good statistic (large-area peaks). For this reason often the sample is prepared as a pellet. However, this approach is not always feasible, for instance when cultural heritage or valuable samples must be analyzed. In this case, the sample surface cannot be smoothed. In order to address this problem, several works have been reported in the literature, based on experimental measurements on a few sets of specific samples or on Monte Carlo simulations. The results obtained with the first approach are limited by the specific class of samples analyzed, while the second approach cannot be applied to arbitrarily irregular surfaces. The present work describes a more general analysis tool based on a new fast Monte Carlo algorithm, which is virtually able to simulate any kind of surface. At the best of our knowledge, it is the first Monte Carlo code with this option. A study of the influence of surface irregularities on the measured spectrum is performed and some results reported. - Highlights: • We present a fast Monte Carlo code with the possibility to simulate any irregularly rough surfaces. • We show applications to multilayer measurements. • Real time simulations are available.

Monte Carlo Simulations of Neutron Oil well Logging Tools

International Nuclear Information System (INIS)

Azcurra, Mario

2002-01-01

Monte Carlo simulations of simple neutron oil well logging tools into typical geological formations are presented.The simulated tools consist of both 14 MeV pulsed and continuous Am-Be neutron sources with time gated and continuous gamma ray detectors respectively.The geological formation consists of pure limestone with 15% absolute porosity in a wide range of oil saturation.The particle transport was performed with the Monte Carlo N-Particle Transport Code System, MCNP-4B.Several gamma ray spectra were obtained at the detector position that allow to perform composition analysis of the formation.In particular, the ratio C/O was analyzed as an indicator of oil saturation.Further calculations are proposed to simulate actual detector responses in order to contribute to understand the relation between the detector response with the formation composition

Monte Carlo simulations of neutron oil well logging tools

International Nuclear Information System (INIS)

Azcurra, Mario O.; Zamonsky, Oscar M.

2003-01-01

Monte Carlo simulations of simple neutron oil well logging tools into typical geological formations are presented. The simulated tools consist of both 14 MeV pulsed and continuous Am-Be neutron sources with time gated and continuous gamma ray detectors respectively. The geological formation consists of pure limestone with 15% absolute porosity in a wide range of oil saturation. The particle transport was performed with the Monte Carlo N-Particle Transport Code System, MCNP-4B. Several gamma ray spectra were obtained at the detector position that allow to perform composition analysis of the formation. In particular, the ratio C/O was analyzed as an indicator of oil saturation. Further calculations are proposed to simulate actual detector responses in order to contribute to understand the relation between the detector response with the formation composition. (author)

Evaluation of the Neutron Detector Response for Cosmic Ray Energy Spectrum by Monte Carlo Transport Simulation

International Nuclear Information System (INIS)

Pazianotto, Mauricio T.; Carlson, Brett V.; Federico, Claudio A.; Gonzalez, Odair L.

2011-01-01

Neutrons generated by the interaction of cosmic rays with the atmosphere make an important contribution to the dose accumulated in electronic circuits and aircraft crew members at flight altitude. High-energy neutrons are produced in spallation reactions and intranuclear cascade processes by primary cosmic-ray particle interactions with atoms in the atmosphere. These neutrons can produce secondary neutrons and also undergo a moderation process due to atmosphere interactions, resulting in a wider energy spectrum, ranging from thermal energies (0.025 eV) to energies of several hundreds of MeV. The Long-Counter (LC) detector is a widely used neutron detector designed to measure the directional flux of neutrons with about constant response over a wide energy range (thermal to 20 MeV). ). Its calibration process and the determination of its energy response for the wide-energy of cosmic ray induced neutron spectrum is a very difficult process due to the lack of installations with these capabilities. The goal of this study is to assess the behavior of the response of a Long Counter using the Monte Carlo (MC) computational code MCNPX (Monte Carlo N-Particle eXtended). The dependence of the Long Counter response on the angle of incidence, as well as on the neutron energy, will be carefully investigated, compared with the experimental data previously obtained with 241 Am-Be and 252 Cf neutron sources and extended to the neutron spectrum produced by cosmic rays. (Author)

PCXMC. A PC-based Monte Carlo program for calculating patient doses in medical x-ray examinations

International Nuclear Information System (INIS)

Tapiovaara, M.; Lakkisto, M.; Servomaa, A.

1997-02-01

The report describes PCXMC, a Monte Carlo program for calculating patients' organ doses and the effective dose in medical x-ray examinations. The organs considered are: the active bone marrow, adrenals, brain, breasts, colon (upper and lower large intestine), gall bladder, heats, kidneys, liver, lungs, muscle, oesophagus, ovaries, pancreas, skeleton, skin, small intestine, spleen, stomach, testes, thymes, thyroid, urinary bladder, and uterus. (42 refs.)

Monte Carlo method for calculating the radiation skyshine produced by electron accelerators

Energy Technology Data Exchange (ETDEWEB)

Kong Chaocheng [Department of Engineering Physics, Tsinghua University Beijing 100084 (China)]. E-mail: kongchaocheng@tsinghua.org.cn; Li Quanfeng [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Chen Huaibi [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Du Taibin [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Cheng Cheng [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Tang Chuanxiang [Department of Engineering Physics, Tsinghua University Beijing 100084 (China); Zhu Li [Laboratory of Radiation and Environmental Protection, Tsinghua University, Beijing 100084 (China); Zhang Hui [Laboratory of Radiation and Environmental Protection, Tsinghua University, Beijing 100084 (China); Pei Zhigang [Laboratory of Radiation and Environmental Protection, Tsinghua University, Beijing 100084 (China); Ming Shenjin [Laboratory of Radiation and Environmental Protection, Tsinghua University, Beijing 100084 (China)

2005-06-01

Using the MCNP4C Monte Carlo code, the X-ray skyshine produced by 9 MeV, 15 MeV and 21 MeV electron linear accelerators were calculated respectively with a new two-step method combined with the split and roulette variance reduction technique. Results of the Monte Carlo simulation, the empirical formulas used for skyshine calculation and the dose measurements were analyzed and compared. In conclusion, the skyshine dose measurements agreed reasonably with the results computed by the Monte Carlo method, but deviated from computational results given by empirical formulas. The effect on skyshine dose caused by different structures of accelerator head is also discussed in this paper.

Lectures on Monte Carlo methods

CERN Document Server

Madras, Neal

2001-01-01

Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati

Monte Carlo simulation in nuclear medicine

International Nuclear Information System (INIS)

Morel, Ch.

2007-01-01

The Monte Carlo method allows for simulating random processes by using series of pseudo-random numbers. It became an important tool in nuclear medicine to assist in the design of new medical imaging devices, optimise their use and analyse their data. Presently, the sophistication of the simulation tools allows the introduction of Monte Carlo predictions in data correction and image reconstruction processes. The availability to simulate time dependent processes opens up new horizons for Monte Carlo simulation in nuclear medicine. In a near future, these developments will allow to tackle simultaneously imaging and dosimetry issues and soon, case system Monte Carlo simulations may become part of the nuclear medicine diagnostic process. This paper describes some Monte Carlo method basics and the sampling methods that were developed for it. It gives a referenced list of different simulation software used in nuclear medicine and enumerates some of their present and prospective applications. (author)

Integration of Monte-Carlo ray tracing with a stochastic optimisation method: application to the design of solar receiver geometry.

Science.gov (United States)

Asselineau, Charles-Alexis; Zapata, Jose; Pye, John

2015-06-01

A stochastic optimisation method adapted to illumination and radiative heat transfer problems involving Monte-Carlo ray-tracing is presented. A solar receiver shape optimisation case study illustrates the advantages of the method and its potential: efficient receivers are identified using a moderate computational cost.

Monte Carlo Simulation of Complete X-Ray Spectra for Use in Scanning Electron Microscopy Analysis

International Nuclear Information System (INIS)

Roet, David; Van Espen, Piet

2003-01-01

Full Text: The interactions of keV electrons and photons with matter can be simulated accurately with the aid of the Monte Carlo (MC) technique. In scanning electron microscopy x-ray analysis (SEM-EDX) such simulations can be used to perform quantitative analysis using a Reverse Monte Carlo method even if the samples have irregular geometry. Alternatively the MC technique can generate spectra of standards for use in quantization with partial least squares regression. The feasibility of these alternatives to the more classical ZAF or phi-rho-Z quantification methods has been proven already. In order to be applicable for these purposes the MC-code needs to generate accurately only the characteristic K and L x-ray lines, but also the Bremsstrahlung continuum, i.e. the complete x-ray spectrum need to be simulated. Currently two types of MC simulation codes are available. Programs like Electron Flight Simulator and CASINO simulate characteristic x-rays due to electron interaction in a fast and efficient way but lack provision for the simulation of the continuum. On the other hand, programs like EGS4, MCNP4 and PENELOPE, originally developed for high energy (MeV- GeV) applications, are more complete but difficult to use and still slow, even on todays fastest computers. We therefore started the development of a dedicated MC simulation code for use in quantitative SEM-EDX work. The selection of the most appropriate cross section for the different interactions will be discussed and the results obtained will be compared with those obtained with existing MC programs. Examples of the application of MC simulations for quantitative analysis of samples with various composition will be given

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

Science.gov (United States)

Gastellu-Etchegorry, Jean-Philippe; Yin, Tiangang; Lauret, Nicolas; Grau, Eloi; Rubio, Jeremy; Cook, Bruce D.; Morton, Douglas C.; Sun, Guoqing

2016-01-01

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Advanced Multilevel Monte Carlo Methods

KAUST Repository

Jasra, Ajay

2017-04-24

This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.

Advanced Multilevel Monte Carlo Methods

KAUST Repository

Jasra, Ajay; Law, Kody; Suciu, Carina

2017-01-01

This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.

Monte Carlo - Advances and Challenges

International Nuclear Information System (INIS)

Brown, Forrest B.; Mosteller, Russell D.; Martin, William R.

2008-01-01

Abstract only, full text follows: With ever-faster computers and mature Monte Carlo production codes, there has been tremendous growth in the application of Monte Carlo methods to the analysis of reactor physics and reactor systems. In the past, Monte Carlo methods were used primarily for calculating k eff of a critical system. More recently, Monte Carlo methods have been increasingly used for determining reactor power distributions and many design parameters, such as β eff , l eff , τ, reactivity coefficients, Doppler defect, dominance ratio, etc. These advanced applications of Monte Carlo methods are now becoming common, not just feasible, but bring new challenges to both developers and users: Convergence of 3D power distributions must be assured; confidence interval bias must be eliminated; iterated fission probabilities are required, rather than single-generation probabilities; temperature effects including Doppler and feedback must be represented; isotopic depletion and fission product buildup must be modeled. This workshop focuses on recent advances in Monte Carlo methods and their application to reactor physics problems, and on the resulting challenges faced by code developers and users. The workshop is partly tutorial, partly a review of the current state-of-the-art, and partly a discussion of future work that is needed. It should benefit both novice and expert Monte Carlo developers and users. In each of the topic areas, we provide an overview of needs, perspective on past and current methods, a review of recent work, and discussion of further research and capabilities that are required. Electronic copies of all workshop presentations and material will be available. The workshop is structured as 2 morning and 2 afternoon segments: - Criticality Calculations I - convergence diagnostics, acceleration methods, confidence intervals, and the iterated fission probability, - Criticality Calculations II - reactor kinetics parameters, dominance ratio, temperature

Weighted-delta-tracking for Monte Carlo particle transport

International Nuclear Information System (INIS)

Morgan, L.W.G.; Kotlyar, D.

2015-01-01

Highlights: • This paper presents an alteration to the Monte Carlo Woodcock tracking technique. • The alteration improves computational efficiency within regions of high absorbers. • The rejection technique is replaced by a statistical weighting mechanism. • The modified Woodcock method is shown to be faster than standard Woodcock tracking. • The modified Woodcock method achieves a lower variance, given a specified accuracy. - Abstract: Monte Carlo particle transport (MCPT) codes are incredibly powerful and versatile tools to simulate particle behavior in a multitude of scenarios, such as core/criticality studies, radiation protection, shielding, medicine and fusion research to name just a small subset applications. However, MCPT codes can be very computationally expensive to run when the model geometry contains large attenuation depths and/or contains many components. This paper proposes a simple modification to the Woodcock tracking method used by some Monte Carlo particle transport codes. The Woodcock method utilizes the rejection method for sampling virtual collisions as a method to remove collision distance sampling at material boundaries. However, it suffers from poor computational efficiency when the sample acceptance rate is low. The proposed method removes rejection sampling from the Woodcock method in favor of a statistical weighting scheme, which improves the computational efficiency of a Monte Carlo particle tracking code. It is shown that the modified Woodcock method is less computationally expensive than standard ray-tracing and rejection-based Woodcock tracking methods and achieves a lower variance, given a specified accuracy

The structure of molten CuCl: Reverse Monte Carlo modeling with high-energy X-ray diffraction data and molecular dynamics of a polarizable ion model

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.

The structure of molten CuCl: Reverse Monte Carlo modeling with high-energy X-ray diffraction data and molecular dynamics of a polarizable ion model

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.

Three-dimensional Monte Carlo calculations of the neutron and γ-ray fluences in the TFTR diagnostic basement and comparisons with measurements

International Nuclear Information System (INIS)

Liew, S.L.; Ku, L.P.; Kolibal, J.G.

1985-10-01

Realistic calculations of the neutron and γ-ray fluences in the TFTR diagnostic basement have been carried out with three-dimensional Monte Carlo models. Comparisons with measurements show that the results are well within the experimental uncertainties

Monte Carlo simulation of gamma ray tomography for image reconstruction

Energy Technology Data Exchange (ETDEWEB)

Guedes, Karlos A.N.; Moura, Alex; Dantas, Carlos; Melo, Silvio; Lima, Emerson, E-mail: karlosguedes@hotmail.com [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil); Meric, Ilker [University of Bergen (Norway)

2015-07-01

The Monte Carlo simulations of known density and shape object was validate with Gamma Ray Tomography in static experiments. An aluminum half-moon piece placed inside a steel pipe was the MC simulation test object that was also measured by means of gamma ray transmission. Wall effect of the steel pipe due to irradiation geometry in a single pair source-detector tomography was evaluated by comparison with theoretical data. MCNPX code requires a defined geometry to each photon trajectory which practically prevents this usage for tomography reconstruction simulation. The solution was found by writing a program in Delphi language to create input files automation code. Simulations of tomography data by automated MNCPX code were carried out and validated by experimental data. Working in this sequence the produced data needed a databank to be stored. Experimental setup used a Cesium-137 isotopic radioactive source (7.4 × 109 Bq), and NaI(Tl) scintillation detector of (51 × 51) × 10−3 m crystal size coupled to a multichannel analyzer. A stainless steel tubes of 0,154 m internal diameter, 0.014 m thickness wall. The results show that the MCNPX simulation code adapted to automated input file is useful for generating a matrix data M(θ,t), of a computerized gamma ray tomography for any known density and regular shape object. Experimental validation used RMSE from gamma ray paths and from attenuation coefficient data. (author)

Fast sequential Monte Carlo methods for counting and optimization

CERN Document Server

Rubinstein, Reuven Y; Vaisman, Radislav

2013-01-01

A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the

The MC21 Monte Carlo Transport Code

International Nuclear Information System (INIS)

Sutton TM; Donovan TJ; Trumbull TH; Dobreff PS; Caro E; Griesheimer DP; Tyburski LJ; Carpenter DC; Joo H

2007-01-01

MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities

Monte Carlo Treatment Planning for Advanced Radiotherapy

DEFF Research Database (Denmark)

Cronholm, Rickard

This Ph.d. project describes the development of a workflow for Monte Carlo Treatment Planning for clinical radiotherapy plans. The workflow may be utilized to perform an independent dose verification of treatment plans. Modern radiotherapy treatment delivery is often conducted by dynamically...... modulating the intensity of the field during the irradiation. The workflow described has the potential to fully model the dynamic delivery, including gantry rotation during irradiation, of modern radiotherapy. Three corner stones of Monte Carlo Treatment Planning are identified: Building, commissioning...... and validation of a Monte Carlo model of a medical linear accelerator (i), converting a CT scan of a patient to a Monte Carlo compliant phantom (ii) and translating the treatment plan parameters (including beam energy, angles of incidence, collimator settings etc) to a Monte Carlo input file (iii). A protocol...

Monte carlo simulation for soot dynamics

KAUST Repository

Zhou, Kun

2012-01-01

A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

Monte Carlo method for polarized radiative transfer in gradient-index media

International Nuclear Information System (INIS)

Zhao, J.M.; Tan, J.Y.; Liu, L.H.

2015-01-01

Light transfer in gradient-index media generally follows curved ray trajectories, which will cause light beam to converge or diverge during transfer and induce the rotation of polarization ellipse even when the medium is transparent. Furthermore, the combined process of scattering and transfer along curved ray path makes the problem more complex. In this paper, a Monte Carlo method is presented to simulate polarized radiative transfer in gradient-index media that only support planar ray trajectories. The ray equation is solved to the second order to address the effect induced by curved ray trajectories. Three types of test cases are presented to verify the performance of the method, which include transparent medium, Mie scattering medium with assumed gradient index distribution, and Rayleigh scattering with realistic atmosphere refractive index profile. It is demonstrated that the atmospheric refraction has significant effect for long distance polarized light transfer. - Highlights: • A Monte Carlo method for polarized radiative transfer in gradient index media. • Effect of curved ray paths on polarized radiative transfer is considered. • Importance of atmospheric refraction for polarized light transfer is demonstrated

Statistical estimation Monte Carlo for unreliability evaluation of highly reliable system

International Nuclear Information System (INIS)

Xiao Gang; Su Guanghui; Jia Dounan; Li Tianduo

2000-01-01

Based on analog Monte Carlo simulation, statistical Monte Carlo methods for unreliable evaluation of highly reliable system are constructed, including direct statistical estimation Monte Carlo method and weighted statistical estimation Monte Carlo method. The basal element is given, and the statistical estimation Monte Carlo estimators are derived. Direct Monte Carlo simulation method, bounding-sampling method, forced transitions Monte Carlo method, direct statistical estimation Monte Carlo and weighted statistical estimation Monte Carlo are used to evaluate unreliability of a same system. By comparing, weighted statistical estimation Monte Carlo estimator has smallest variance, and has highest calculating efficiency

Applications to shielding design and others of monte carlo method

Energy Technology Data Exchange (ETDEWEB)

Ito, Daiichiro [Mitsui Engineering and Shipbuiding Co., Ltd., Tokyo (Japan)

2001-01-01

One-dimensional or two-dimensional Sn computer code (ANISN, DOT3.5, etc.) and a point attenuation kernel integral code (QAD, etc.) have been used widely for shielding design. Application examples of monte carlo method which could follow precisely the three-dimensional configuration of shielding structure are shown as follow: (1) CASTER cask has a complex structure which consists of a large number of fuel baskets (stainless steel), neutron moderators (polyethylene rods), the body (cast iron), and cooling fin. The R-{theta} model of Sn code DOT3.5 cannot follow closely the complex form of polyethylene rods and fuel baskets. A monte carlo code MORSE is used to ascertain the calculation results of DOT3.5. The discrepancy between the calculation results of DOT3.5 and MORSE was in 10% for dose rate at distance of 1 m from the cask surface. (2) The dose rates of an iron cell at 10 cm above the floor are calculated by the code QAD and the MORSE. The reflected components of gamma ray caused by the auxiliary floor shield (lead) are analyzed by the MORSE. (3) A monte carlo code MCNP4A is used for skyshine evaluation of spent fuel carrier ship 'ROKUEIMARU'. The direct and skyshine components of gamma ray and neutron flux are estimated at each center of engine room and wheel house. The skyshine dose rate of neutron flux is 5-15 times larger than the gamma ray. (M. Suetake)

Multilevel sequential Monte Carlo samplers

KAUST Repository

Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan

2016-01-01

In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

Multilevel sequential Monte Carlo samplers

KAUST Repository

Beskos, Alexandros

2016-08-29

In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

Applications of Monte Carlo method in Medical Physics

International Nuclear Information System (INIS)

Diez Rios, A.; Labajos, M.

1989-01-01

The basic ideas of Monte Carlo techniques are presented. Random numbers and their generation by congruential methods, which underlie Monte Carlo calculations are shown. Monte Carlo techniques to solve integrals are discussed. The evaluation of a simple monodimensional integral with a known answer, by means of two different Monte Carlo approaches are discussed. The basic principles to simualate on a computer photon histories reduce variance and the current applications in Medical Physics are commented. (Author)

Shielding requirements for constant-potential diagnostic x-ray beams determined by a Monte Carlo calculation

International Nuclear Information System (INIS)

Simpkin, D.J.

1989-01-01

A Monte Carlo calculation has been performed to determine the transmission of broad constant-potential x-ray beams through Pb, concrete, gypsum wallboard, steel and plate glass. The EGS4 code system was used with a simple broad-beam geometric model to generate exposure transmission curves for published 70, 100, 120 and 140-kVcp x-ray spectra. These curves are compared to measured three-phase generated x-ray transmission data in the literature and found to be reasonable. For calculation ease the data are fit to an equation previously shown to describe such curves quite well. These calculated transmission data are then used to create three-phase shielding tables for Pb and concrete, as well as other materials not available in Report No. 49 of the NCRP

Shielding requirements for constant-potential diagnostic x-ray beams determined by a Monte Carlo calculation.

Science.gov (United States)

Simpkin, D J

1989-02-01

A Monte Carlo calculation has been performed to determine the transmission of broad constant-potential x-ray beams through Pb, concrete, gypsum wallboard, steel and plate glass. The EGS4 code system was used with a simple broad-beam geometric model to generate exposure transmission curves for published 70, 100, 120 and 140-kVcp x-ray spectra. These curves are compared to measured three-phase generated x-ray transmission data in the literature and found to be reasonable. For calculation ease the data are fit to an equation previously shown to describe such curves quite well. These calculated transmission data are then used to create three-phase shielding tables for Pb and concrete, as well as other materials not available in Report No. 49 of the NCRP.

A monte carlo program for X-rays detection up to 1.4 MeV

International Nuclear Information System (INIS)

Manfredotti, C.; Nastasi, U.

1983-01-01

A monte carlo program has been developed to simulate X-ray spectral response in semiconductor detectors. Photons in the range from 5 KeV to 1.4 MeV are considered as emitted from a source of zero thickness aligned to the crystal axis and followed untill their complete energy loss or their escape from the crystal. The program allows the optimization of important parameters in a semiconductor detector, the study of influence on the spectra obtained and the determination of the energy behavior of efficiency and energy resolution. Some obtained results have been compared with experimental data

Experience with the Monte Carlo Method

Energy Technology Data Exchange (ETDEWEB)

Hussein, E M.A. [Department of Mechanical Engineering University of New Brunswick, Fredericton, N.B., (Canada)

2007-06-15

Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed.

Experience with the Monte Carlo Method

International Nuclear Information System (INIS)

Hussein, E.M.A.

2007-01-01

Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed

Monte Carlo alpha calculation

Energy Technology Data Exchange (ETDEWEB)

Brockway, D.; Soran, P.; Whalen, P.

1985-01-01

A Monte Carlo algorithm to efficiently calculate static alpha eigenvalues, N = ne/sup ..cap alpha..t/, for supercritical systems has been developed and tested. A direct Monte Carlo approach to calculating a static alpha is to simply follow the buildup in time of neutrons in a supercritical system and evaluate the logarithmic derivative of the neutron population with respect to time. This procedure is expensive, and the solution is very noisy and almost useless for a system near critical. The modified approach is to convert the time-dependent problem to a static ..cap alpha../sup -/eigenvalue problem and regress ..cap alpha.. on solutions of a/sup -/ k/sup -/eigenvalue problem. In practice, this procedure is much more efficient than the direct calculation, and produces much more accurate results. Because the Monte Carlo codes are intrinsically three-dimensional and use elaborate continuous-energy cross sections, this technique is now used as a standard for evaluating other calculational techniques in odd geometries or with group cross sections.

Monte Carlo simulations of neutron scattering instruments

International Nuclear Information System (INIS)

Aestrand, Per-Olof; Copenhagen Univ.; Lefmann, K.; Nielsen, K.

2001-01-01

A Monte Carlo simulation is an important computational tool used in many areas of science and engineering. The use of Monte Carlo techniques for simulating neutron scattering instruments is discussed. The basic ideas, techniques and approximations are presented. Since the construction of a neutron scattering instrument is very expensive, Monte Carlo software used for design of instruments have to be validated and tested extensively. The McStas software was designed with these aspects in mind and some of the basic principles of the McStas software will be discussed. Finally, some future prospects are discussed for using Monte Carlo simulations in optimizing neutron scattering experiments. (R.P.)

Simulation and study on the γ response spectrum of BGO detector by the application of monte carlo code MOCA

International Nuclear Information System (INIS)

Jia Wenbao; Chen Xiaowen; Xu Aiguo; Li Anmin

2010-01-01

Application of Monte Carlo method to build spectra library is useful to reduce experiment workload in Prompt Gamma Neutron Activation Analysis (PGNAA). The new Monte Carlo Code MOCA was used to simulate the response spectra of BGO detector for gamma rays from 137 Cs, 60 Co and neutron induced gamma rays from S and Ti. The results were compared with general code MCNP, show that the agreement of MOCA between simulation and experiment is better than MCNP. This research indicates that building spectra library by Monte Carlo method is feasible. (authors)

GEANT Monte Carlo simulations for the GREAT spectrometer

International Nuclear Information System (INIS)

Andreyev, A.N.; Butler, P.A.; Page, R.D.; Appelbe, D.E.; Jones, G.D.; Joss, D.T.; Herzberg, R.-D.; Regan, P.H.; Simpson, J.; Wadsworth, R.

2004-01-01

GEANT Monte Carlo simulations for the recently developed GREAT spectrometer are presented. Some novel applications of the spectrometer for γ-ray, conversion-electron and β-decay spectroscopy are discussed. The conversion-electron spectroscopy of heavy nuclei with strongly converted transitions and the extension of the recoil decay tagging method to β-decaying nuclei are considered in detail

Monte Carlo simulation for radiographic applications

International Nuclear Information System (INIS)

Tillack, G.R.; Bellon, C.

2003-01-01

Standard radiography simulators are based on the attenuation law complemented by built-up-factors (BUF) to describe the interaction of radiation with material. The assumption of BUF implies that scattered radiation reduces only the contrast in radiographic images. This simplification holds for a wide range of applications like weld inspection as known from practical experience. But only a detailed description of the different underlying interaction mechanisms is capable to explain effects like mottling or others that every radiographer has experienced in practice. The application of Monte Carlo models is capable to handle primary and secondary interaction mechanisms contributing to the image formation process like photon interactions (absorption, incoherent and coherent scattering including electron-binding effects, pair production) and electron interactions (electron tracing including X-Ray fluorescence and Bremsstrahlung production). It opens up possibilities like the separation of influencing factors and the understanding of the functioning of intensifying screen used in film radiography. The paper discusses the opportunities in applying the Monte Carlo method to investigate special features in radiography in terms of selected examples. (orig.) [de

Linear filtering applied to Monte Carlo criticality calculations

International Nuclear Information System (INIS)

Morrison, G.W.; Pike, D.H.; Petrie, L.M.

1975-01-01

A significant improvement in the acceleration of the convergence of the eigenvalue computed by Monte Carlo techniques has been developed by applying linear filtering theory to Monte Carlo calculations for multiplying systems. A Kalman filter was applied to a KENO Monte Carlo calculation of an experimental critical system consisting of eight interacting units of fissile material. A comparison of the filter estimate and the Monte Carlo realization was made. The Kalman filter converged in five iterations to 0.9977. After 95 iterations, the average k-eff from the Monte Carlo calculation was 0.9981. This demonstrates that the Kalman filter has the potential of reducing the calculational effort of multiplying systems. Other examples and results are discussed

Simulation of x-rays in refractive structure by the Monte Carlo method using the supercomputer SKIF

International Nuclear Information System (INIS)

Yaskevich, Yu.R.; Kravchenko, O.I.; Soroka, I.I.; Chembrovskij, A.G.; Kolesnik, A.S.; Serikova, N.V.; Petrov, P.V.; Kol'chevskij, N.N.

2013-01-01

Software 'Xray-SKIF' for the simulation of the X-rays in refractive structures by the Monte-Carlo method using the supercomputer SKIF BSU are developed. The program generates a large number of rays propagated from a source to the refractive structure. The ray trajectory under assumption of geometrical optics is calculated. Absorption is calculated for each ray inside of refractive structure. Dynamic arrays are used for results of calculation rays parameters, its restore the X-ray field distributions very fast at different position of detector. It was found that increasing the number of processors leads to proportional decreasing of calculation time: simulation of 10 8 X-rays using supercomputer with the number of processors from 1 to 30 run-times equal 3 hours and 6 minutes, respectively. 10 9 X-rays are calculated by software 'Xray-SKIF' which allows to reconstruct the X-ray field after refractive structure with a special resolution of 1 micron. (authors)

Burnup calculations using Monte Carlo method

International Nuclear Information System (INIS)

Ghosh, Biplab; Degweker, S.B.

2009-01-01

In the recent years, interest in burnup calculations using Monte Carlo methods has gained momentum. Previous burn up codes have used multigroup transport theory based calculations followed by diffusion theory based core calculations for the neutronic portion of codes. The transport theory methods invariably make approximations with regard to treatment of the energy and angle variables involved in scattering, besides approximations related to geometry simplification. Cell homogenisation to produce diffusion, theory parameters adds to these approximations. Moreover, while diffusion theory works for most reactors, it does not produce accurate results in systems that have strong gradients, strong absorbers or large voids. Also, diffusion theory codes are geometry limited (rectangular, hexagonal, cylindrical, and spherical coordinates). Monte Carlo methods are ideal to solve very heterogeneous reactors and/or lattices/assemblies in which considerable burnable poisons are used. The key feature of this approach is that Monte Carlo methods permit essentially 'exact' modeling of all geometrical detail, without resort to ene and spatial homogenization of neutron cross sections. Monte Carlo method would also be better for in Accelerator Driven Systems (ADS) which could have strong gradients due to the external source and a sub-critical assembly. To meet the demand for an accurate burnup code, we have developed a Monte Carlo burnup calculation code system in which Monte Carlo neutron transport code is coupled with a versatile code (McBurn) for calculating the buildup and decay of nuclides in nuclear materials. McBurn is developed from scratch by the authors. In this article we will discuss our effort in developing the continuous energy Monte Carlo burn-up code, McBurn. McBurn is intended for entire reactor core as well as for unit cells and assemblies. Generally, McBurn can do burnup of any geometrical system which can be handled by the underlying Monte Carlo transport code

Monte Carlo simulations for plasma physics

International Nuclear Information System (INIS)

Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X.

2000-07-01

Plasma behaviours are very complicated and the analyses are generally difficult. However, when the collisional processes play an important role in the plasma behaviour, the Monte Carlo method is often employed as a useful tool. For examples, in neutral particle injection heating (NBI heating), electron or ion cyclotron heating, and alpha heating, Coulomb collisions slow down high energetic particles and pitch angle scatter them. These processes are often studied by the Monte Carlo technique and good agreements can be obtained with the experimental results. Recently, Monte Carlo Method has been developed to study fast particle transports associated with heating and generating the radial electric field. Further it is applied to investigating the neoclassical transport in the plasma with steep gradients of density and temperatures which is beyong the conventional neoclassical theory. In this report, we briefly summarize the researches done by the present authors utilizing the Monte Carlo method. (author)

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography

Energy Technology Data Exchange (ETDEWEB)

Paixao, L.; Oliveira, B. B.; Nogueira, M. do S. [Centro de Desenvolvimento da Tecnologia Nuclear, Post-graduation in Science and Technology of Radiations, Minerals and Materials, Pte. Antonio Carlos 6.627, Pampulha, 31270-901 Belo Horizonte (Brazil); Viloria, C. [UFMG, Departamento de Engenharia Nuclear, Post-graduation in Nuclear Sciences and Techniques, Pte. Antonio Carlos 6.627, Pampulha, 31270-901 Belo Horizonte (Brazil); Alves de O, M. [UFMG, Department of Anatomy and Imaging, Prof. Alfredo Balena 190, 30130-100 Belo Horizonte (Brazil); Araujo T, M. H., E-mail: lpr@cdtn.br [Dr Maria Helena Araujo Teixeira Clinic, Guajajaras 40, 30180-100 Belo Horizonte (Brazil)

2014-08-15

It is widely accepted that the mean glandular dose (D{sub G}) for the glandular tissue is the more useful magnitude for characterizing the breast cancer risk. The procedure to estimate the D{sub G}, for being difficult to measure it directly in the breast, it is to make the use of conversion factors that relate incident air kerma (K{sub i}) at this dose. Generally, the conversion factors vary with the x-ray spectrum half-value layer and the breast composition and thickness. Several authors through computer simulations have calculated such factors by the Monte Carlo (Mc) method. Many spectral models for D{sub G} computer simulations purposes are available in the diagnostic range. One of the models available generates unfiltered spectra. In this work, the Monte Carlo EGSnrc code package with the C++ class library (eg spp) was employed to derive filtered tungsten x-ray spectra used in digital mammography systems. Filtered spectra for rhodium and aluminium filters were obtained for tube potentials between 26 and 32 kV. The half-value layer of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F and Mam Detector Platinum and 8201023-C Xi Base unit Platinum Plus w m As in a Hologic Selenia Dimensions system using a Direct Radiography mode. Calculated half-value layer values showed good agreement compared to those obtained experimentally. These results show that the filtered tungsten anode x-ray spectra and the EGSnrc Mc code can be used for D{sub G} determination in mammography. (Author)

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography

International Nuclear Information System (INIS)

Paixao, L.; Oliveira, B. B.; Nogueira, M. do S.; Viloria, C.; Alves de O, M.; Araujo T, M. H.

2014-08-01

It is widely accepted that the mean glandular dose (D G ) for the glandular tissue is the more useful magnitude for characterizing the breast cancer risk. The procedure to estimate the D G , for being difficult to measure it directly in the breast, it is to make the use of conversion factors that relate incident air kerma (K i ) at this dose. Generally, the conversion factors vary with the x-ray spectrum half-value layer and the breast composition and thickness. Several authors through computer simulations have calculated such factors by the Monte Carlo (Mc) method. Many spectral models for D G computer simulations purposes are available in the diagnostic range. One of the models available generates unfiltered spectra. In this work, the Monte Carlo EGSnrc code package with the C++ class library (eg spp) was employed to derive filtered tungsten x-ray spectra used in digital mammography systems. Filtered spectra for rhodium and aluminium filters were obtained for tube potentials between 26 and 32 kV. The half-value layer of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F and Mam Detector Platinum and 8201023-C Xi Base unit Platinum Plus w m As in a Hologic Selenia Dimensions system using a Direct Radiography mode. Calculated half-value layer values showed good agreement compared to those obtained experimentally. These results show that the filtered tungsten anode x-ray spectra and the EGSnrc Mc code can be used for D G determination in mammography. (Author)

Simulation study on the behavior of X-rays and gamma rays in an inhomogeneous medium using the Monte Carlo technique

International Nuclear Information System (INIS)

Murase, Kenya; Kataoka, Masaaki; Kawamura, Masashi; Tamada, Shuji; Hamamoto, Ken

1989-01-01

A computer program based on the Monte Carlo technique was developed for the analysis of the behavior of X-rays and gamma rays in an inhomogeneous medium. The statistical weight of a photon was introduced and the survival biasing method was used for reducing the statistical error. This computer program has the mass energy absorption and attenuation coefficients for 69 tissues and organs as a database file, and can be applied to various cases of inhomogeneity. The simulation and experimental results of the central axis percent-depth dose in an inhomogeneous phantom were in good agreement. This computer program will be useful for analysis on the behavior of X-rays and gamma rays in an inhomogeneous medium consisting of various tissues and organs, not only in radiotherapy treatment planning but also in diagnostic radiology and in the field treating radiation protection. (author)

Monte Carlo methods and models in finance and insurance

CERN Document Server

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...

Monte Carlo approaches to light nuclei

International Nuclear Information System (INIS)

Carlson, J.

1990-01-01

Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of 16 O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs

Monte Carlo approaches to light nuclei

Energy Technology Data Exchange (ETDEWEB)

Carlson, J.

1990-01-01

Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of {sup 16}O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs.

Simulation of the Interaction of X-rays with a Gas in an Ionization Chamber by the Monte Carlo Method; Simulacion Monte Carlo de la Interaccion de Rays X con el Gas de una Camara de Ionizacion

Energy Technology Data Exchange (ETDEWEB)

Grau Carles, A.; Garcia Gomez-Tejedor, G.

2001-07-01

The final objective of any ionization chamber is the measurement of the energy amount or radiation dose absorbed by the gas into the chamber. The final value depends on the composition of the gas, its density and temperature, the ionization chamber geometry, and type and intensity of the radiation. We describe a Monte Carlo simulation method, which allows one to compute the dose absorbed by the gas for a X-ray beam. Verification of model has been carried out by simulating the attenuation of standard X-ray radiation through the half value layers established in the ISO 4037 report, while assuming a Weibull type energy distribution for the incident photons. (Author) 6 refs.

Simulation and the Monte Carlo method

CERN Document Server

Rubinstein, Reuven Y

2016-01-01

Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...

Statistical analysis for discrimination of prompt gamma ray peak induced by high energy neutron: Monte Carlo simulation study

International Nuclear Information System (INIS)

Do-Kun Yoon; Joo-Young Jung; Tae Suk Suh; Seong-Min Han

2015-01-01

The purpose of this research is a statistical analysis for discrimination of prompt gamma ray peak induced by the 14.1 MeV neutron particles from spectra using Monte Carlo simulation. For the simulation, the information of 18 detector materials was used to simulate spectra by the neutron capture reaction. The discrimination of nine prompt gamma ray peaks from the simulation of each detector material was performed. We presented the several comparison indexes of energy resolution performance depending on the detector material using the simulation and statistics for the prompt gamma activation analysis. (author)

Lecture 1. Monte Carlo basics. Lecture 2. Adjoint Monte Carlo. Lecture 3. Coupled Forward-Adjoint calculations

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J.E. [Delft University of Technology, Interfaculty Reactor Institute, Delft (Netherlands)

2000-07-01

The Monte Carlo method is a statistical method to solve mathematical and physical problems using random numbers. The principle of the methods will be demonstrated for a simple mathematical problem and for neutron transport. Various types of estimators will be discussed, as well as generally applied variance reduction methods like splitting, Russian roulette and importance biasing. The theoretical formulation for solving eigenvalue problems for multiplying systems will be shown. Some reflections will be given about the applicability of the Monte Carlo method, its limitations and its future prospects for reactor physics calculations. Adjoint Monte Carlo is a Monte Carlo game to solve the adjoint neutron (or photon) transport equation. The adjoint transport equation can be interpreted in terms of simulating histories of artificial particles, which show properties of neutrons that move backwards in history. These particles will start their history at the detector from which the response must be estimated and give a contribution to the estimated quantity when they hit or pass through the neutron source. Application to multigroup transport formulation will be demonstrated Possible implementation for the continuous energy case will be outlined. The inherent advantages and disadvantages of the method will be discussed. The Midway Monte Carlo method will be presented for calculating a detector response due to a (neutron or photon) source. A derivation will be given of the basic formula for the Midway Monte Carlo method The black absorber technique, allowing for a cutoff of particle histories when reaching the midway surface in one of the calculations will be derived. An extension of the theory to coupled neutron-photon problems is given. The method will be demonstrated for an oil well logging problem, comprising a neutron source in a borehole and photon detectors to register the photons generated by inelastic neutron scattering. (author)

Lecture 1. Monte Carlo basics. Lecture 2. Adjoint Monte Carlo. Lecture 3. Coupled Forward-Adjoint calculations

International Nuclear Information System (INIS)

Hoogenboom, J.E.

2000-01-01

The Monte Carlo method is a statistical method to solve mathematical and physical problems using random numbers. The principle of the methods will be demonstrated for a simple mathematical problem and for neutron transport. Various types of estimators will be discussed, as well as generally applied variance reduction methods like splitting, Russian roulette and importance biasing. The theoretical formulation for solving eigenvalue problems for multiplying systems will be shown. Some reflections will be given about the applicability of the Monte Carlo method, its limitations and its future prospects for reactor physics calculations. Adjoint Monte Carlo is a Monte Carlo game to solve the adjoint neutron (or photon) transport equation. The adjoint transport equation can be interpreted in terms of simulating histories of artificial particles, which show properties of neutrons that move backwards in history. These particles will start their history at the detector from which the response must be estimated and give a contribution to the estimated quantity when they hit or pass through the neutron source. Application to multigroup transport formulation will be demonstrated Possible implementation for the continuous energy case will be outlined. The inherent advantages and disadvantages of the method will be discussed. The Midway Monte Carlo method will be presented for calculating a detector response due to a (neutron or photon) source. A derivation will be given of the basic formula for the Midway Monte Carlo method The black absorber technique, allowing for a cutoff of particle histories when reaching the midway surface in one of the calculations will be derived. An extension of the theory to coupled neutron-photon problems is given. The method will be demonstrated for an oil well logging problem, comprising a neutron source in a borehole and photon detectors to register the photons generated by inelastic neutron scattering. (author)

Status of the Monte Carlo library least-squares (MCLLS) approach for non-linear radiation analyzer problems

Science.gov (United States)

Gardner, Robin P.; Xu, Libai

2009-10-01

The Center for Engineering Applications of Radioisotopes (CEAR) has been working for over a decade on the Monte Carlo library least-squares (MCLLS) approach for treating non-linear radiation analyzer problems including: (1) prompt gamma-ray neutron activation analysis (PGNAA) for bulk analysis, (2) energy-dispersive X-ray fluorescence (EDXRF) analyzers, and (3) carbon/oxygen tool analysis in oil well logging. This approach essentially consists of using Monte Carlo simulation to generate the libraries of all the elements to be analyzed plus any other required background libraries. These libraries are then used in the linear library least-squares (LLS) approach with unknown sample spectra to analyze for all elements in the sample. Iterations of this are used until the LLS values agree with the composition used to generate the libraries. The current status of the methods (and topics) necessary to implement the MCLLS approach is reported. This includes: (1) the Monte Carlo codes such as CEARXRF, CEARCPG, and CEARCO for forward generation of the necessary elemental library spectra for the LLS calculation for X-ray fluorescence, neutron capture prompt gamma-ray analyzers, and carbon/oxygen tools; (2) the correction of spectral pulse pile-up (PPU) distortion by Monte Carlo simulation with the code CEARIPPU; (3) generation of detector response functions (DRF) for detectors with linear and non-linear responses for Monte Carlo simulation of pulse-height spectra; and (4) the use of the differential operator (DO) technique to make the necessary iterations for non-linear responses practical. In addition to commonly analyzed single spectra, coincidence spectra or even two-dimensional (2-D) coincidence spectra can also be used in the MCLLS approach and may provide more accurate results.

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

International Nuclear Information System (INIS)

Brown, Forrest B.; Univ. of New Mexico, Albuquerque, NM

2016-01-01

These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

Energy Technology Data Exchange (ETDEWEB)

Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Monte Carlo Methods, Codes, and Applications Group; Univ. of New Mexico, Albuquerque, NM (United States). Nuclear Engineering Dept.

2016-11-29

These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations

Monte Carlo Transport for Electron Thermal Transport

Science.gov (United States)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2015-11-01

The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.

Applications of FLUKA Monte Carlo code for nuclear and accelerator physics

CERN Document Server

Battistoni, Giuseppe; Brugger, Markus; Campanella, Mauro; Carboni, Massimo; Empl, Anton; Fasso, Alberto; Gadioli, Ettore; Cerutti, Francesco; Ferrari, Alfredo; Ferrari, Anna; Lantz, Matthias; Mairani, Andrea; Margiotta, M; Morone, Christina; Muraro, Silvia; Parodi, Katerina; Patera, Vincenzo; Pelliccioni, Maurizio; Pinsky, Lawrence; Ranft, Johannes; Roesler, Stefan; Rollet, Sofia; Sala, Paola R; Santana, Mario; Sarchiapone, Lucia; Sioli, Maximiliano; Smirnov, George; Sommerer, Florian; Theis, Christian; Trovati, Stefania; Villari, R; Vincke, Heinz; Vincke, Helmut; Vlachoudis, Vasilis; Vollaire, Joachim; Zapp, Neil

2011-01-01

FLUKA is a general purpose Monte Carlo code capable of handling all radiation components from thermal energies (for neutrons) or 1keV (for all other particles) to cosmic ray energies and can be applied in many different fields. Presently the code is maintained on Linux. The validity of the physical models implemented in FLUKA has been benchmarked against a variety of experimental data over a wide energy range, from accelerator data to cosmic ray showers in the Earth atmosphere. FLUKA is widely used for studies related both to basic research and to applications in particle accelerators, radiation protection and dosimetry, including the specific issue of radiation damage in space missions, radiobiology (including radiotherapy) and cosmic ray calculations. After a short description of the main features that make FLUKA valuable for these topics, the present paper summarizes some of the recent applications of the FLUKA Monte Carlo code in the nuclear as well high energy physics. In particular it addresses such top...

Monte-Carlo simulations of neutron shielding for the ATLAS forward region

CERN Document Server

Stekl, I; Kovalenko, V E; Vorobel, V; Leroy, C; Piquemal, F; Eschbach, R; Marquet, C

2000-01-01

The effectiveness of different types of neutron shielding for the ATLAS forward region has been studied by means of Monte-Carlo simulations and compared with the results of an experiment performed at the CERN PS. The simulation code is based on GEANT, FLUKA, MICAP and GAMLIB. GAMLIB is a new library including processes with gamma-rays produced in (n, gamma), (n, n'gamma) neutron reactions and is interfaced to the MICAP code. The effectiveness of different types of shielding against neutrons and gamma-rays, composed from different types of material, such as pure polyethylene, borated polyethylene, lithium-filled polyethylene, lead and iron, were compared. The results from Monte-Carlo simulations were compared to the results obtained from the experiment. The simulation results reproduce the experimental data well. This agreement supports the correctness of the simulation code used to describe the generation, spreading and absorption of neutrons (up to thermal energies) and gamma-rays in the shielding materials....

Generalized hybrid Monte Carlo - CMFD methods for fission source convergence

International Nuclear Information System (INIS)

Wolters, Emily R.; Larsen, Edward W.; Martin, William R.

2011-01-01

In this paper, we generalize the recently published 'CMFD-Accelerated Monte Carlo' method and present two new methods that reduce the statistical error in CMFD-Accelerated Monte Carlo. The CMFD-Accelerated Monte Carlo method uses Monte Carlo to estimate nonlinear functionals used in low-order CMFD equations for the eigenfunction and eigenvalue. The Monte Carlo fission source is then modified to match the resulting CMFD fission source in a 'feedback' procedure. The two proposed methods differ from CMFD-Accelerated Monte Carlo in the definition of the required nonlinear functionals, but they have identical CMFD equations. The proposed methods are compared with CMFD-Accelerated Monte Carlo on a high dominance ratio test problem. All hybrid methods converge the Monte Carlo fission source almost immediately, leading to a large reduction in the number of inactive cycles required. The proposed methods stabilize the fission source more efficiently than CMFD-Accelerated Monte Carlo, leading to a reduction in the number of active cycles required. Finally, as in CMFD-Accelerated Monte Carlo, the apparent variance of the eigenfunction is approximately equal to the real variance, so the real error is well-estimated from a single calculation. This is an advantage over standard Monte Carlo, in which the real error can be underestimated due to inter-cycle correlation. (author)

Effect of burst and recombination models for Monte Carlo transport of interacting carriers in a-Se x-ray detectors on Swank noise

Energy Technology Data Exchange (ETDEWEB)

Fang, Yuan, E-mail: yuan.fang@fda.hhs.gov [Division of Imaging and Applied Mathematics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993-0002 and Department of Electrical and Computer Engineering, The University of Waterloo, Waterloo, Ontario N2L 3G1 (Canada); Karim, Karim S. [Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1 (Canada); Badano, Aldo [Division of Imaging and Applied Mathematics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993-0002 (United States)

2014-01-15

Purpose: The authors describe the modification to a previously developed Monte Carlo model of semiconductor direct x-ray detector required for studying the effect of burst and recombination algorithms on detector performance. This work provides insight into the effect of different charge generation models for a-Se detectors on Swank noise and recombination fraction. Methods: The proposed burst and recombination models are implemented in the Monte Carlo simulation package, ARTEMIS, developed byFang et al. [“Spatiotemporal Monte Carlo transport methods in x-ray semiconductor detectors: Application to pulse-height spectroscopy in a-Se,” Med. Phys. 39(1), 308–319 (2012)]. The burst model generates a cloud of electron-hole pairs based on electron velocity, energy deposition, and material parameters distributed within a spherical uniform volume (SUV) or on a spherical surface area (SSA). A simple first-hit (FH) and a more detailed but computationally expensive nearest-neighbor (NN) recombination algorithms are also described and compared. Results: Simulated recombination fractions for a single electron-hole pair show good agreement with Onsager model for a wide range of electric field, thermalization distance, and temperature. The recombination fraction and Swank noise exhibit a dependence on the burst model for generation of many electron-hole pairs from a single x ray. The Swank noise decreased for the SSA compared to the SUV model at 4 V/μm, while the recombination fraction decreased for SSA compared to the SUV model at 30 V/μm. The NN and FH recombination results were comparable. Conclusions: Results obtained with the ARTEMIS Monte Carlo transport model incorporating drift and diffusion are validated with the Onsager model for a single electron-hole pair as a function of electric field, thermalization distance, and temperature. For x-ray interactions, the authors demonstrate that the choice of burst model can affect the simulation results for the generation

Effect of burst and recombination models for Monte Carlo transport of interacting carriers in a-Se x-ray detectors on Swank noise

International Nuclear Information System (INIS)

Fang, Yuan; Karim, Karim S.; Badano, Aldo

2014-01-01

Purpose: The authors describe the modification to a previously developed Monte Carlo model of semiconductor direct x-ray detector required for studying the effect of burst and recombination algorithms on detector performance. This work provides insight into the effect of different charge generation models for a-Se detectors on Swank noise and recombination fraction. Methods: The proposed burst and recombination models are implemented in the Monte Carlo simulation package, ARTEMIS, developed byFang et al. [“Spatiotemporal Monte Carlo transport methods in x-ray semiconductor detectors: Application to pulse-height spectroscopy in a-Se,” Med. Phys. 39(1), 308–319 (2012)]. The burst model generates a cloud of electron-hole pairs based on electron velocity, energy deposition, and material parameters distributed within a spherical uniform volume (SUV) or on a spherical surface area (SSA). A simple first-hit (FH) and a more detailed but computationally expensive nearest-neighbor (NN) recombination algorithms are also described and compared. Results: Simulated recombination fractions for a single electron-hole pair show good agreement with Onsager model for a wide range of electric field, thermalization distance, and temperature. The recombination fraction and Swank noise exhibit a dependence on the burst model for generation of many electron-hole pairs from a single x ray. The Swank noise decreased for the SSA compared to the SUV model at 4 V/μm, while the recombination fraction decreased for SSA compared to the SUV model at 30 V/μm. The NN and FH recombination results were comparable. Conclusions: Results obtained with the ARTEMIS Monte Carlo transport model incorporating drift and diffusion are validated with the Onsager model for a single electron-hole pair as a function of electric field, thermalization distance, and temperature. For x-ray interactions, the authors demonstrate that the choice of burst model can affect the simulation results for the generation

Monte Carlo simulation of radiative transfer in scattering, emitting, absorbing slab with gradient index

International Nuclear Information System (INIS)

Huang Yong; Liang Xingang; Xia Xinlin

2005-01-01

The Monte Carlo method is used to simulate the thermal emission of absorbing-emitting-scattering slab with gradient index. Three Monte Carlo ray-tracing strategies are considered. The first strategy is keeping the real distribution of the refractive index and to trace bundles in a curve route. The second strategy is discretizing the slab into sub-layers, each having constant refractive index. The bundle is traced in a straight route in each sub-layer and the reflection at the inner interface is taken into account. The third strategy is similar to the second one but only the total reflection at the inner interface is computed. Little difference is observed among the results of apparent thermal emission by these three different Monte Carlo ray tracing strategies. The results also show that the apparent hemispherical emissivity non-monotonously varies with increasing optical thickness of the slab with strong scattering gradient index. Many parameters can influence the apparent thermal emission greatly

Monte Carlo simulation for the estimation of iron in human whole ...

Indian Academy of Sciences (India)

2017-02-10

Feb 10, 2017 ... Monte Carlo N-particle (MCNP) code has been used to simulate the transport of gamma photon rays ... experimental data, and better than the theoretical XCOM values. ... tions in the materials, according to probability density.

MONTE CARLO RADIATION TRANSFER SIMULATIONS OF PHOTOSPHERIC EMISSION IN LONG-DURATION GAMMA-RAY BURSTS

Energy Technology Data Exchange (ETDEWEB)

Lazzati, Davide [Department of Physics, Oregon State University, 301 Weniger Hall, Corvallis, OR 97331 (United States)

2016-10-01

We present MCRaT, a Monte Carlo Radiation Transfer code for self-consistently computing the light curves and spectra of the photospheric emission from relativistic, unmagnetized jets. We apply MCRaT to a relativistic hydrodynamic simulation of a long-duration gamma-ray burst jet, and present the resulting light curves and time-dependent spectra for observers at various angles from the jet axis. We compare our results to observational results and find that photospheric emission is a viable model to explain the prompt phase of long-duration gamma-ray bursts at the peak frequency and above, but faces challenges when reproducing the flat spectrum below the peak frequency. We finally discuss possible limitations of these results both in terms of the hydrodynamics and the radiation transfer and how these limitations could affect the conclusions that we present.

Is Monte Carlo embarrassingly parallel?

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Delft Nuclear Consultancy, IJsselzoom 2, 2902 LB Capelle aan den IJssel (Netherlands)

2012-07-01

Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

Is Monte Carlo embarrassingly parallel?

International Nuclear Information System (INIS)

Hoogenboom, J. E.

2012-01-01

Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

The Monte Carlo event generator DPMJET-III

International Nuclear Information System (INIS)

Roesler, S.; Engel, R.

2001-01-01

A new version of the Monte Carlo event generator DPMJET is presented. It is a code system based on the Dual Parton Model and unifies all features of the DTUNUC-2, DPMJET-II and PHOJET1.12 event generators. DPMJET-III allows the simulation of hadron-hadron, hadron-nucleus, nucleus-nucleus, photon-hadron, photon-photon and photon-nucleus interactions from a few GeV up to the highest cosmic ray energies. (orig.)

Monte Carlo method for dose calculation due to oral X-rays

International Nuclear Information System (INIS)

Loureiro, Eduardo Cesar de Miranda

1998-06-01

The increasing utilization of oral X-rays, especially in youngsters and children, calls for the assessment of equivalent doses in their organs and tissues. With this purpose, a Monte Carlo code was adapted to simulate an X-ray source irradiating phantoms of the MIRD-5 type with different ages (10, 15 and 40 years old) to calculate the conversion coefficients which transform the exposure at skin to equivalent doses at several organs and tissues of interest. In order to check the computer program, simulations were performed for adult patients using the original code (ADAM.FOR developed at the GSF-Germany) and the adapted program (MCDRO.PAS). Good agreement between results obtained with both codes was observed. Irradiations of the incisive, canine and molar teeth were simulated. The conversion factors were calculated for the following organs and tissues: thyroid, active bone narrow (head and whole body), bone (facial skeleton, cranium and whole body), skin (head and whole body) and crystalline. Based on the obtained results, it follows that the younger the patient and the larger the field area, the higher the dose in assessed organs and tissues. The variation of the source-skin distance does not change the conversion coefficients. On the other hand, the increase in the voltage applied to the X-ray tube causes an increase in the calculated conversion coefficients. (author)

Mean field simulation for Monte Carlo integration

CERN Document Server

Del Moral, Pierre

2013-01-01

In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Marko

Variational Variance Reduction for Monte Carlo Criticality Calculations

International Nuclear Information System (INIS)

Densmore, Jeffery D.; Larsen, Edward W.

2001-01-01

A new variational variance reduction (VVR) method for Monte Carlo criticality calculations was developed. This method employs (a) a variational functional that is more accurate than the standard direct functional, (b) a representation of the deterministically obtained adjoint flux that is especially accurate for optically thick problems with high scattering ratios, and (c) estimates of the forward flux obtained by Monte Carlo. The VVR method requires no nonanalog Monte Carlo biasing, but it may be used in conjunction with Monte Carlo biasing schemes. Some results are presented from a class of criticality calculations involving alternating arrays of fuel and moderator regions

Monte Carlo Solutions for Blind Phase Noise Estimation

Directory of Open Access Journals (Sweden)

Çırpan Hakan

2009-01-01

Full Text Available This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN channels. The main contributions of the paper are (i the development of a Monte Carlo framework for phase noise estimation, with special attention to sequential importance sampling and Rao-Blackwellization, (ii the interpretation of existing Monte Carlo solutions within this generic framework, and (iii the derivation of a novel phase noise estimator. Contrary to the ad hoc phase noise estimators that have been proposed in the past, the estimators considered in this paper are derived from solid probabilistic and performance-determining arguments. Computer simulations demonstrate that, on one hand, the Monte Carlo phase noise estimators outperform the existing estimators and, on the other hand, our newly proposed solution exhibits a lower complexity than the existing Monte Carlo solutions.

Monte Carlo simulation of the ARGO

International Nuclear Information System (INIS)

Depaola, G.O.

1997-01-01

We use GEANT Monte Carlo code to design an outline of the geometry and simulate the performance of the Argentine gamma-ray observer (ARGO), a telescope based on silicon strip detector technlogy. The γ-ray direction is determined by geometrical means and the angular resolution is calculated for small variations of the basic design. The results show that the angular resolutions vary from a few degrees at low energies (∝50 MeV) to 0.2 , approximately, at high energies (>500 MeV). We also made simulations using as incoming γ-ray the energy spectrum of PKS0208-512 and PKS0528+134 quasars. Moreover, a method based on multiple scattering theory is also used to determine the incoming energy. We show that this method is applicable to energy spectrum. (orig.)

Monte Carlo based diffusion coefficients for LMFBR analysis

International Nuclear Information System (INIS)

Van Rooijen, Willem F.G.; Takeda, Toshikazu; Hazama, Taira

2010-01-01

A method based on Monte Carlo calculations is developed to estimate the diffusion coefficient of unit cells. The method uses a geometrical model similar to that used in lattice theory, but does not use the assumption of a separable fundamental mode used in lattice theory. The method uses standard Monte Carlo flux and current tallies, and the continuous energy Monte Carlo code MVP was used without modifications. Four models are presented to derive the diffusion coefficient from tally results of flux and partial currents. In this paper the method is applied to the calculation of a plate cell of the fast-spectrum critical facility ZEBRA. Conventional calculations of the diffusion coefficient diverge in the presence of planar voids in the lattice, but our Monte Carlo method can treat this situation without any problem. The Monte Carlo method was used to investigate the influence of geometrical modeling as well as the directional dependence of the diffusion coefficient. The method can be used to estimate the diffusion coefficient of complicated unit cells, the limitation being the capabilities of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained with deterministic codes. (author)

Efficiency of a bismuth-germanate scintillator: comparison of Monte Carlo calculations with measurements

International Nuclear Information System (INIS)

Hsu, H.H.; Dowdy, E.J.; Estes, G.P.; Lucas, M.C.; Mack, J.M.; Moss, C.E.; Hamm, M.E.

1983-01-01

Monte Carlo calculations of a bismuth-germanate scintillator's efficiency agree closely with experimental measurements. For this comparison, we studied the absolute gamma-ray photopeak efficiency of a scintillator (7.62 cm long by 7.62 cm in diameter) at several gamma-ray energies from 166 to 2615 keV at distances from 0.5 to 152.4 cm. Computer calculations were done in a two-dimensional cylindrical geometry with the Monte Carlo coupled photon-electron code CYLTRAN. For the experiment we measured 11 sources with simple spectra and precisely known strengths. The average deviation between the calculations and the measurements is 3%. Our calculated results also closely agree with recently published calculated results

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)

Computer system for Monte Carlo experimentation

International Nuclear Information System (INIS)

Grier, D.A.

1986-01-01

A new computer system for Monte Carlo Experimentation is presented. The new system speeds and simplifies the process of coding and preparing a Monte Carlo Experiment; it also encourages the proper design of Monte Carlo Experiments, and the careful analysis of the experimental results. A new functional language is the core of this system. Monte Carlo Experiments, and their experimental designs, are programmed in this new language; those programs are compiled into Fortran output. The Fortran output is then compiled and executed. The experimental results are analyzed with a standard statistics package such as Si, Isp, or Minitab or with a user-supplied program. Both the experimental results and the experimental design may be directly loaded into the workspace of those packages. The new functional language frees programmers from many of the details of programming an experiment. Experimental designs such as factorial, fractional factorial, or latin square are easily described by the control structures and expressions of the language. Specific mathematical modes are generated by the routines of the language

Random Numbers and Monte Carlo Methods

Science.gov (United States)

Scherer, Philipp O. J.

Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.

Self-absorption corrections of various sample-detector geometries in gamma-ray spectrometry using sample Monte Carlo Simulations

International Nuclear Information System (INIS)

Ahmad Saat; Appleby, P.G.; Nolan, P.J.

1997-01-01

Corrections for self-absorption in gamma-ray spectrometry have been developed using a simple Monte Carlo simulation technique. The simulation enables the calculation of gamma-ray path lengths in the sample which, using available data, can be used to calculate self-absorption correction factors. The simulation was carried out on three sample geometries: disk, Marinelli beaker, and cylinder (for well-type detectors). Mathematical models and experimental measurements are used to evaluate the simulations. A good agreement of within a few percents was observed. The simulation results are also in good agreement with those reported in the literature. The simulation code was carried out in FORTRAN 90,

LCG Monte-Carlo Data Base

CERN Document Server

Bartalini, P.; Kryukov, A.; Selyuzhenkov, Ilya V.; Sherstnev, A.; Vologdin, A.

2004-01-01

We present the Monte-Carlo events Data Base (MCDB) project and its development plans. MCDB facilitates communication between authors of Monte-Carlo generators and experimental users. It also provides a convenient book-keeping and an easy access to generator level samples. The first release of MCDB is now operational for the CMS collaboration. In this paper we review the main ideas behind MCDB and discuss future plans to develop this Data Base further within the CERN LCG framework.

Monte Carlo simulation of x-ray buildup factors of lead and its applications in shielding of diagnostic x-ray facilities

International Nuclear Information System (INIS)

Kharrati, Hedi; Agrebi, Amel; Karaoui, Mohamed-Karim

2007-01-01

X-ray buildup factors of lead in broad beam geometry for energies from 15 to 150 keV are determined using the general purpose Monte Carlo N-particle radiation transport computer code (MCNP4C). The obtained buildup factors data are fitted to a modified three parameter Archer et al. model for ease in calculating the broad beam transmission with computer at any tube potentials/filters combinations in diagnostic energies range. An example for their use to compute the broad beam transmission at 70, 100, 120, and 140 kVp is given. The calculated broad beam transmission is compared to data derived from literature, presenting good agreement. Therefore, the combination of the buildup factors data as determined and a mathematical model to generate x-ray spectra provide a computationally based solution to broad beam transmission for lead barriers in shielding x-ray facilities

Alternative implementations of the Monte Carlo power method

International Nuclear Information System (INIS)

Blomquist, R.N.; Gelbard, E.M.

2002-01-01

We compare nominal efficiencies, i.e. variances in power shapes for equal running time, of different versions of the Monte Carlo eigenvalue computation, as applied to criticality safety analysis calculations. The two main methods considered here are ''conventional'' Monte Carlo and the superhistory method, and both are used in criticality safety codes. Within each of these major methods, different variants are available for the main steps of the basic Monte Carlo algorithm. Thus, for example, different treatments of the fission process may vary in the extent to which they follow, in analog fashion, the details of real-world fission, or may vary in details of the methods by which they choose next-generation source sites. In general the same options are available in both the superhistory method and conventional Monte Carlo, but there seems not to have been much examination of the special properties of the two major methods and their minor variants. We find, first, that the superhistory method is just as efficient as conventional Monte Carlo and, secondly, that use of different variants of the basic algorithms may, in special cases, have a surprisingly large effect on Monte Carlo computational efficiency

Igo - A Monte Carlo Code For Radiotherapy Planning

International Nuclear Information System (INIS)

Goldstein, M.; Regev, D.

1999-01-01

The goal of radiation therapy is to deliver a lethal dose to the tumor, while minimizing the dose to normal tissues and vital organs. To carry out this task, it is critical to calculate correctly the 3-D dose delivered. Monte Carlo transport methods (especially the Adjoint Monte Carlo have the potential to provide more accurate predictions of the 3-D dose the currently used methods. IG0 is a Monte Carlo code derived from the general Monte Carlo Program - MCNP, tailored specifically for calculating the effects of radiation therapy. This paper describes the IG0 transport code, the PIG0 interface and some preliminary results

Monte Carlo techniques for analyzing deep-penetration problems

International Nuclear Information System (INIS)

Cramer, S.N.; Gonnord, J.; Hendricks, J.S.

1986-01-01

Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multigroup Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications

Odd-flavor Simulations by the Hybrid Monte Carlo

CERN Document Server

Takaishi, Tetsuya; Takaishi, Tetsuya; De Forcrand, Philippe

2001-01-01

The standard hybrid Monte Carlo algorithm is known to simulate even flavors QCD only. Simulations of odd flavors QCD, however, can be also performed in the framework of the hybrid Monte Carlo algorithm where the inverse of the fermion matrix is approximated by a polynomial. In this exploratory study we perform three flavors QCD simulations. We make a comparison of the hybrid Monte Carlo algorithm and the R-algorithm which also simulates odd flavors systems but has step-size errors. We find that results from our hybrid Monte Carlo algorithm are in agreement with those from the R-algorithm obtained at very small step-size.

An improved wavelength selection scheme for Monte Carlo solvers applied to hypersonic plasmas

International Nuclear Information System (INIS)

Feldick, Andrew; Modest, Michael F.

2011-01-01

A new databasing scheme is developed for Monte Carlo Ray Tracing methods applied to hypersonic planetary entry. In this scheme, the complex relationships for the emission wavelength selection of atomic and molecular species in nonequilibrium flows are simplified by developing random number relationships for individual transitions, as opposed to using relationships for the spectral emission coefficient of a given species. These new techniques speed up wavelength selection by about 2 orders of magnitude, and offer flexibility for use in weighted or part-spectrum Monte Carlo solvers.

Energy dispersive X-ray fluorescence spectroscopy/Monte Carlo simulation approach for the non-destructive analysis of corrosion patina-bearing alloys in archaeological bronzes: The case of the bowl from the Fareleira 3 site (Vidigueira, South Portugal)

Energy Technology Data Exchange (ETDEWEB)

Bottaini, C. [Hercules Laboratory, University of Évora, Palacio do Vimioso, Largo Marquês de Marialva 8, 7000-809 Évora (Portugal); Mirão, J. [Hercules Laboratory, University of Évora, Palacio do Vimioso, Largo Marquês de Marialva 8, 7000-809 Évora (Portugal); Évora Geophysics Centre, Rua Romão Ramalho 59, 7000 Évora (Portugal); Figuereido, M. [Archaeologist — Monte da Capelinha, Apartado 54, 7005, São Miguel de Machede, Évora (Portugal); Candeias, A. [Hercules Laboratory, University of Évora, Palacio do Vimioso, Largo Marquês de Marialva 8, 7000-809 Évora (Portugal); Évora Chemistry Centre, Rua Romão Ramalho 59, 7000 Évora (Portugal); Brunetti, A. [Department of Political Science and Communication, University of Sassari, Via Piandanna 2, 07100 Sassari (Italy); Schiavon, N., E-mail: schiavon@uevora.pt [Hercules Laboratory, University of Évora, Palacio do Vimioso, Largo Marquês de Marialva 8, 7000-809 Évora (Portugal); Évora Geophysics Centre, Rua Romão Ramalho 59, 7000 Évora (Portugal)

2015-01-01

Energy dispersive X-ray fluorescence (EDXRF) is a well-known technique for non-destructive and in situ analysis of archaeological artifacts both in terms of the qualitative and quantitative elemental composition because of its rapidity and non-destructiveness. In this study EDXRF and realistic Monte Carlo simulation using the X-ray Monte Carlo (XRMC) code package have been combined to characterize a Cu-based bowl from the Iron Age burial from Fareleira 3 (Southern Portugal). The artifact displays a multilayered structure made up of three distinct layers: a) alloy substrate; b) green oxidized corrosion patina; and c) brownish carbonate soil-derived crust. To assess the reliability of Monte Carlo simulation in reproducing the composition of the bulk metal of the objects without recurring to potentially damaging patina's and crust's removal, portable EDXRF analysis was performed on cleaned and patina/crust coated areas of the artifact. Patina has been characterized by micro X-ray Diffractometry (μXRD) and Back-Scattered Scanning Electron Microscopy + Energy Dispersive Spectroscopy (BSEM + EDS). Results indicate that the EDXRF/Monte Carlo protocol is well suited when a two-layered model is considered, whereas in areas where the patina + crust surface coating is too thick, X-rays from the alloy substrate are not able to exit the sample. - Highlights: • EDXRF/Monte Carlo simulation is used to characterize an archeological alloy. • EDXRF analysis was performed on cleaned and patina coated areas of the artifact. • EDXRF/Montes Carlo protocol is well suited when a two-layered model is considered. • When the patina is too thick, X-rays from substrate are unable to exit the sample.

Quantum Monte Carlo approaches for correlated systems

CERN Document Server

Becca, Federico

2017-01-01

Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference ...

Voxel-based Monte Carlo simulation of X-ray imaging and spectroscopy experiments

International Nuclear Information System (INIS)

Bottigli, U.; Brunetti, A.; Golosio, B.; Oliva, P.; Stumbo, S.; Vincze, L.; Randaccio, P.; Bleuet, P.; Simionovici, A.; Somogyi, A.

2004-01-01

A Monte Carlo code for the simulation of X-ray imaging and spectroscopy experiments in heterogeneous samples is presented. The energy spectrum, polarization and profile of the incident beam can be defined so that X-ray tube systems as well as synchrotron sources can be simulated. The sample is modeled as a 3D regular grid. The chemical composition and density is given at each point of the grid. Photoelectric absorption, fluorescent emission, elastic and inelastic scattering are included in the simulation. The core of the simulation is a fast routine for the calculation of the path lengths of the photon trajectory intersections with the grid voxels. The voxel representation is particularly useful for samples that cannot be well described by a small set of polyhedra. This is the case of most naturally occurring samples. In such cases, voxel-based simulations are much less expensive in terms of computational cost than simulations on a polygonal representation. The efficient scheme used for calculating the path lengths in the voxels and the use of variance reduction techniques make the code suitable for the detailed simulation of complex experiments on generic samples in a relatively short time. Examples of applications to X-ray imaging and spectroscopy experiments are discussed

Voxel-based Monte Carlo simulation of X-ray imaging and spectroscopy experiments

Energy Technology Data Exchange (ETDEWEB)

Bottigli, U. [Istituto di Matematica e Fisica dell' Universita di Sassari, via Vienna 2, 07100, Sassari (Italy); Sezione INFN di Cagliari (Italy); Brunetti, A. [Istituto di Matematica e Fisica dell' Universita di Sassari, via Vienna 2, 07100, Sassari (Italy); Golosio, B. [Istituto di Matematica e Fisica dell' Universita di Sassari, via Vienna 2, 07100, Sassari (Italy) and Sezione INFN di Cagliari (Italy)]. E-mail: golosio@uniss.it; Oliva, P. [Istituto di Matematica e Fisica dell' Universita di Sassari, via Vienna 2, 07100, Sassari (Italy); Stumbo, S. [Istituto di Matematica e Fisica dell' Universita di Sassari, via Vienna 2, 07100, Sassari (Italy); Vincze, L. [Department of Chemistry, University of Antwerp (Belgium); Randaccio, P. [Dipartimento di Fisica dell' Universita di Cagliari and Sezione INFN di Cagliari (Italy); Bleuet, P. [European Synchrotron Radiation Facility, Grenoble (France); Simionovici, A. [European Synchrotron Radiation Facility, Grenoble (France); Somogyi, A. [European Synchrotron Radiation Facility, Grenoble (France)

2004-10-08

A Monte Carlo code for the simulation of X-ray imaging and spectroscopy experiments in heterogeneous samples is presented. The energy spectrum, polarization and profile of the incident beam can be defined so that X-ray tube systems as well as synchrotron sources can be simulated. The sample is modeled as a 3D regular grid. The chemical composition and density is given at each point of the grid. Photoelectric absorption, fluorescent emission, elastic and inelastic scattering are included in the simulation. The core of the simulation is a fast routine for the calculation of the path lengths of the photon trajectory intersections with the grid voxels. The voxel representation is particularly useful for samples that cannot be well described by a small set of polyhedra. This is the case of most naturally occurring samples. In such cases, voxel-based simulations are much less expensive in terms of computational cost than simulations on a polygonal representation. The efficient scheme used for calculating the path lengths in the voxels and the use of variance reduction techniques make the code suitable for the detailed simulation of complex experiments on generic samples in a relatively short time. Examples of applications to X-ray imaging and spectroscopy experiments are discussed.

Track 4: basic nuclear science variance reduction for Monte Carlo criticality simulations. 6. Variational Variance Reduction for Monte Carlo Criticality Calculations

International Nuclear Information System (INIS)

Densmore, Jeffery D.; Larsen, Edward W.

2001-01-01

Recently, it has been shown that the figure of merit (FOM) of Monte Carlo source-detector problems can be enhanced by using a variational rather than a direct functional to estimate the detector response. The direct functional, which is traditionally employed in Monte Carlo simulations, requires an estimate of the solution of the forward problem within the detector region. The variational functional is theoretically more accurate than the direct functional, but it requires estimates of the solutions of the forward and adjoint source-detector problems over the entire phase-space of the problem. In recent work, we have performed Monte Carlo simulations using the variational functional by (a) approximating the adjoint solution deterministically and representing this solution as a function in phase-space and (b) estimating the forward solution using Monte Carlo. We have called this general procedure variational variance reduction (VVR). The VVR method is more computationally expensive per history than traditional Monte Carlo because extra information must be tallied and processed. However, the variational functional yields a more accurate estimate of the detector response. Our simulations have shown that the VVR reduction in variance usually outweighs the increase in cost, resulting in an increased FOM. In recent work on source-detector problems, we have calculated the adjoint solution deterministically and represented this solution as a linear-in-angle, histogram-in-space function. This procedure has several advantages over previous implementations: (a) it requires much less adjoint information to be stored and (b) it is highly efficient for diffusive problems, due to the accurate linear-in-angle representation of the adjoint solution. (Traditional variance-reduction methods perform poorly for diffusive problems.) Here, we extend this VVR method to Monte Carlo criticality calculations, which are often diffusive and difficult for traditional variance-reduction methods

Non statistical Monte-Carlo

International Nuclear Information System (INIS)

Mercier, B.

1985-04-01

We have shown that the transport equation can be solved with particles, like the Monte-Carlo method, but without random numbers. In the Monte-Carlo method, particles are created from the source, and are followed from collision to collision until either they are absorbed or they leave the spatial domain. In our method, particles are created from the original source, with a variable weight taking into account both collision and absorption. These particles are followed until they leave the spatial domain, and we use them to determine a first collision source. Another set of particles is then created from this first collision source, and tracked to determine a second collision source, and so on. This process introduces an approximation which does not exist in the Monte-Carlo method. However, we have analyzed the effect of this approximation, and shown that it can be limited. Our method is deterministic, gives reproducible results. Furthermore, when extra accuracy is needed in some region, it is easier to get more particles to go there. It has the same kind of applications: rather problems where streaming is dominant than collision dominated problems

Monte Carlo techniques for analyzing deep penetration problems

International Nuclear Information System (INIS)

Cramer, S.N.; Gonnord, J.; Hendricks, J.S.

1985-01-01

A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications

Monte Carlo techniques for analyzing deep penetration problems

International Nuclear Information System (INIS)

Cramer, S.N.; Gonnord, J.; Hendricks, J.S.

1985-01-01

A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications. 29 refs

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

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

Biases in Monte Carlo eigenvalue calculations

Energy Technology Data Exchange (ETDEWEB)

Gelbard, E.M.

1992-12-01

The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ``fixed-source`` case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (``replicated``) over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

Biases in Monte Carlo eigenvalue calculations

Energy Technology Data Exchange (ETDEWEB)

Gelbard, E.M.

1992-01-01

The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated ( replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

Biases in Monte Carlo eigenvalue calculations

International Nuclear Information System (INIS)

Gelbard, E.M.

1992-01-01

The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ''fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (''replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here

Importance iteration in MORSE Monte Carlo calculations

International Nuclear Information System (INIS)

Kloosterman, J.L.; Hoogenboom, J.E.

1994-01-01

An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example that shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation

Importance iteration in MORSE Monte Carlo calculations

International Nuclear Information System (INIS)

Kloosterman, J.L.; Hoogenboom, J.E.

1994-02-01

An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example, which shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation. (orig.)

Advanced Computational Methods for Monte Carlo Calculations

Energy Technology Data Exchange (ETDEWEB)

Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2018-01-12

This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.

Status of software for PGNAA bulk analysis by the Monte Carlo - Library Least-Squares (MCLLS) approach

International Nuclear Information System (INIS)

Gardner, R.P.; Zhang, W.; Metwally, W.A.

2005-01-01

The Center for Engineering Applications of Radioisotopes (CEAR) has been working for about ten years on the Monte Carlo - Library Least-Squares (MCLLS) approach for treating the nonlinear inverse analysis problem for PGNAA bulk analysis. This approach consists essentially of using Monte Carlo simulation to generate the libraries of all the elements to be analyzed plus any other required libraries. These libraries are then used in the linear Library Least-Squares (LLS) approach with unknown sample spectra to analyze for all elements in the sample. The other libraries include all sources of background which includes: (1) gamma-rays emitted by the neutron source, (2) prompt gamma-rays produced in the analyzer construction materials, (3) natural gamma-rays from K-40 and the uranium and thorium decay chains, and (4) prompt and decay gamma-rays produced in the NaI detector by neutron activation. A number of unforeseen problems have arisen in pursuing this approach including: (1) the neutron activation of the most common detector (NaI) used in bulk analysis PGNAA systems, (2) the nonlinearity of this detector, and (3) difficulties in obtaining detector response functions for this (and other) detectors. These problems have been addressed by CEAR recently and have either been solved or are almost solved at the present time. Development of Monte Carlo simulation for all of the libraries has been finished except the prompt gamma-ray library from the activation of the NaI detector. Treatment for the coincidence schemes for Na and particularly I must be first determined to complete the Monte Carlo simulation of this last library. (author)

Prospect on general software of Monte Carlo method

International Nuclear Information System (INIS)

Pei Lucheng

1992-01-01

This is a short paper on the prospect of Monte Carlo general software. The content consists of cluster sampling method, zero variance technique, self-improved method, and vectorized Monte Carlo method

Strategije drevesnega preiskovanja Monte Carlo

OpenAIRE

VODOPIVEC, TOM

2018-01-01

Po preboju pri igri go so metode drevesnega preiskovanja Monte Carlo (ang. Monte Carlo tree search – MCTS) sprožile bliskovit napredek agentov za igranje iger: raziskovalna skupnost je od takrat razvila veliko variant in izboljšav algoritma MCTS ter s tem zagotovila napredek umetne inteligence ne samo pri igrah, ampak tudi v številnih drugih domenah. Čeprav metode MCTS združujejo splošnost naključnega vzorčenja z natančnostjo drevesnega preiskovanja, imajo lahko v praksi težave s počasno konv...

Monte Carlo electron/photon transport

International Nuclear Information System (INIS)

Mack, J.M.; Morel, J.E.; Hughes, H.G.

1985-01-01

A review of nonplasma coupled electron/photon transport using Monte Carlo method is presented. Remarks are mainly restricted to linerarized formalisms at electron energies from 1 keV to 1000 MeV. Applications involving pulse-height estimation, transport in external magnetic fields, and optical Cerenkov production are discussed to underscore the importance of this branch of computational physics. Advances in electron multigroup cross-section generation is reported, and its impact on future code development assessed. Progress toward the transformation of MCNP into a generalized neutral/charged-particle Monte Carlo code is described. 48 refs

DXRaySMCS. First user friendly interface developed for prediction of diagnostic radiology X-ray spectra produced by Monte Carlo (MCNP-4C) simulation in Iran

International Nuclear Information System (INIS)

Bahreyni Toossi, M.T.; Zare, H.; Moradi Faradanbe, H.

2008-01-01

An accurate knowledge of the output energy spectra of an x-ray tube is essential in many areas of radiological studies. It forms the basis of almost all image quality simulations and enable system designers to predict patient dose more accurately. Many radiological physics problems that can be solved by Monte Carlo simulation methods require an x-ray spectra as input data. Computer simulation of x-ray spectra is one of the most important tools for investigation of patient dose and image quality in diagnostic radiology systems. In this work the general purpose Monte Carlo N-particle radiation transport computer code (MCNP-4C) was used for the simulation of x-ray spectra in diagnostic radiology, Electron's path in the target was followed until it's energy was reduced to 10 keV. A user friendly interface named 'Diagnostic X-ray Spectra by Monte Carlo Simulation (DXRaySMCS)' was developed to facilitate the application of MCNP-4C code for diagnostic radiology spectrum prediction. The program provides a user friendly interface for modifying the MCNP input file, launching the MCNP program to simulate electron and photon transport and processing the MCNP output file to yield a summary of the results (Relative Photon Number per Energy Bin). In this article the development and characteristics of DXRaySMCS are outlined. As part of the validation process, out put spectra for 46 diagnostic radiology system settings produced by DXRaySMCS were compared with the corresponding IPEM78. Generally, there is a good agreement between the two sets of spectra. No statistically significant differences have been observed between IPEM78 reported spectra and the simulated spectra generated in this study. (author)

Monte Carlo method for array criticality calculations

International Nuclear Information System (INIS)

Dickinson, D.; Whitesides, G.E.

1976-01-01

The Monte Carlo method for solving neutron transport problems consists of mathematically tracing paths of individual neutrons collision by collision until they are lost by absorption or leakage. The fate of the neutron after each collision is determined by the probability distribution functions that are formed from the neutron cross-section data. These distributions are sampled statistically to establish the successive steps in the neutron's path. The resulting data, accumulated from following a large number of batches, are analyzed to give estimates of k/sub eff/ and other collision-related quantities. The use of electronic computers to produce the simulated neutron histories, initiated at Los Alamos Scientific Laboratory, made the use of the Monte Carlo method practical for many applications. In analog Monte Carlo simulation, the calculation follows the physical events of neutron scattering, absorption, and leakage. To increase calculational efficiency, modifications such as the use of statistical weights are introduced. The Monte Carlo method permits the use of a three-dimensional geometry description and a detailed cross-section representation. Some of the problems in using the method are the selection of the spatial distribution for the initial batch, the preparation of the geometry description for complex units, and the calculation of error estimates for region-dependent quantities such as fluxes. The Monte Carlo method is especially appropriate for criticality safety calculations since it permits an accurate representation of interacting units of fissile material. Dissimilar units, units of complex shape, moderators between units, and reflected arrays may be calculated. Monte Carlo results must be correlated with relevant experimental data, and caution must be used to ensure that a representative set of neutron histories is produced

Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

KAUST Repository

Ben Issaid, Chaouki; Long, Quan; Scavino, Marco; Tempone, Raul

2015-01-01

Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.

Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

KAUST Repository

Ben Issaid, Chaouki

2015-01-07

Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.

'Odontologic dosimetric card' experiments and simulations using Monte Carlo methods

International Nuclear Information System (INIS)

Menezes, C.J.M.; Lima, R. de A.; Peixoto, J.E.; Vieira, J.W.

2008-01-01

The techniques for data processing, combined with the development of fast and more powerful computers, makes the Monte Carlo methods one of the most widely used tools in the radiation transport simulation. For applications in diagnostic radiology, this method generally uses anthropomorphic phantoms to evaluate the absorbed dose to patients during exposure. In this paper, some Monte Carlo techniques were used to simulation of a testing device designed for intra-oral X-ray equipment performance evaluation called Odontologic Dosimetric Card (CDO of 'Cartao Dosimetrico Odontologico' in Portuguese) for different thermoluminescent detectors. This paper used two computational models of exposition RXD/EGS4 and CDO/EGS4. In the first model, the simulation results are compared with experimental data obtained in the similar conditions. The second model, it presents the same characteristics of the testing device studied (CDO). For the irradiations, the X-ray spectra were generated by the IPEM report number 78, spectrum processor. The attenuated spectrum was obtained for IEC 61267 qualities and various additional filters for a Pantak 320 X-ray industrial equipment. The results obtained for the study of the copper filters used in the determination of the kVp were compared with experimental data, validating the model proposed for the characterization of the CDO. The results shower of the CDO will be utilized in quality assurance programs in order to guarantee that the equipment fulfill the requirements of the Norm SVS No. 453/98 MS (Brazil) 'Directives of Radiation Protection in Medical and Dental Radiodiagnostic'. We conclude that the EGS4 is a suitable code Monte Carlo to simulate thermoluminescent dosimeters and experimental procedures employed in the routine of the quality control laboratory in diagnostic radiology. (author)

Monte Carlo simulation on hard X-ray dose produced in interaction between high intensity laser and solid target

International Nuclear Information System (INIS)

Yang Bo; Qiu Rui; Li Junli; Zhang Hui

2014-01-01

The X-ray dose produced in the interaction between high intensity laser and solid target was studied by simulation using Monte Carlo code. Compared with experimental results, the calculation model was verified. The calculation model was used to study the effect on X-ray dose with different electron temperatures, target materials (including Au, Cu and PE) and thicknesses. The results indicate that the X-ray dose is mainly determined by the electron temperature, and will be affected by the target parameters. X-ray dose of Au is about 1.2 times that of Cu, and is about 5 times that of PE (polyethylene). In addition, compared with other target thickness, when target thickness is the mean range of electron in the target, X-ray dose is relatively large. These results will provide references on evaluating the ionizing radiation dose for laser devices. (authors)

Present status of transport code development based on Monte Carlo method

International Nuclear Information System (INIS)

Nakagawa, Masayuki

1985-01-01

The present status of development in Monte Carlo code is briefly reviewed. The main items are the followings; Application fields, Methods used in Monte Carlo code (geometry spectification, nuclear data, estimator and variance reduction technique) and unfinished works, Typical Monte Carlo codes and Merits of continuous energy Monte Carlo code. (author)

Coupling photon Monte Carlo simulation and CAD software. Application to X-ray nondestructive evaluation

International Nuclear Information System (INIS)

Tabary, J.; Gliere, A.

2001-01-01

A Monte Carlo radiation transport simulation program, EGS Nova, and a computer aided design software, BRL-CAD, have been coupled within the framework of Sindbad, a nondestructive evaluation (NDE) simulation system. In its current status, the program is very valuable in a NDE laboratory context, as it helps simulate the images due to the uncollided and scattered photon fluxes in a single NDE software environment, without having to switch to a Monte Carlo code parameters set. Numerical validations show a good agreement with EGS4 computed and published data. As the program's major drawback is the execution time, computational efficiency improvements are foreseen. (orig.)

Successful vectorization - reactor physics Monte Carlo code

International Nuclear Information System (INIS)

Martin, W.R.

1989-01-01

Most particle transport Monte Carlo codes in use today are based on the ''history-based'' algorithm, wherein one particle history at a time is simulated. Unfortunately, the ''history-based'' approach (present in all Monte Carlo codes until recent years) is inherently scalar and cannot be vectorized. In particular, the history-based algorithm cannot take advantage of vector architectures, which characterize the largest and fastest computers at the current time, vector supercomputers such as the Cray X/MP or IBM 3090/600. However, substantial progress has been made in recent years in developing and implementing a vectorized Monte Carlo algorithm. This algorithm follows portions of many particle histories at the same time and forms the basis for all successful vectorized Monte Carlo codes that are in use today. This paper describes the basic vectorized algorithm along with descriptions of several variations that have been developed by different researchers for specific applications. These applications have been mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas. The relative merits of the various approach schemes will be discussed and the present status of known vectorization efforts will be summarized along with available timing results, including results from the successful vectorization of 3-D general geometry, continuous energy Monte Carlo. (orig.)

Study of TXRF experimental system by Monte Carlo simulation

International Nuclear Information System (INIS)

Costa, Ana Cristina M.; Leitao, Roberta G.; Lopes, Ricardo T.; Anjos, Marcelino J.; Conti, Claudio C.

2011-01-01

The Total-Reflection X-ray Fluorescence (TXRF) technique offers unique possibilities to study the concentrations of a wide range of trace elements in various types of samples. Besides that, the TXRF technique is widely used to study the trace elements in biological, medical and environmental samples due to its multielemental character as well as simplicity of sample preparation and quantification methods used. In general the TXRF experimental setup is not simple and might require substantial experimental efforts. On the other hand, in recent years, experimental TXRF portable systems have been developed. It has motivated us to develop our own TXRF portable system. In this work we presented a first step in order to optimize a TXRF experimental setup using Monte Carlo simulation by MCNP code. The results found show that the Monte Carlo simulation method can be used to investigate the development of a TXRF experimental system before its assembly. (author)

Bayesian phylogeny analysis via stochastic approximation Monte Carlo

KAUST Repository

Cheon, Sooyoung; Liang, Faming

2009-01-01

in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method

Reflections on early Monte Carlo calculations

International Nuclear Information System (INIS)

Spanier, J.

1992-01-01

Monte Carlo methods for solving various particle transport problems developed in parallel with the evolution of increasingly sophisticated computer programs implementing diffusion theory and low-order moments calculations. In these early years, Monte Carlo calculations and high-order approximations to the transport equation were seen as too expensive to use routinely for nuclear design but served as invaluable aids and supplements to design with less expensive tools. The earliest Monte Carlo programs were quite literal; i.e., neutron and other particle random walk histories were simulated by sampling from the probability laws inherent in the physical system without distoration. Use of such analogue sampling schemes resulted in a good deal of time being spent in examining the possibility of lowering the statistical uncertainties in the sample estimates by replacing simple, and intuitively obvious, random variables by those with identical means but lower variances

Monte Carlo simulation of a CZT detector

International Nuclear Information System (INIS)

Chun, Sung Dae; Park, Se Hwan; Ha, Jang Ho; Kim, Han Soo; Cho, Yoon Ho; Kang, Sang Mook; Kim, Yong Kyun; Hong, Duk Geun

2008-01-01

CZT detector is one of the most promising radiation detectors for hard X-ray and γ-ray measurement. The energy spectrum of CZT detector has to be simulated to optimize the detector design. A CZT detector was fabricated with dimensions of 5x5x2 mm 3 . A Peltier cooler with a size of 40x40 mm 2 was installed below the fabricated CZT detector to reduce the operation temperature of the detector. Energy spectra of were measured with 59.5 keV γ-ray from 241 Am. A Monte Carlo code was developed to simulate the CZT energy spectrum, which was measured with a planar-type CZT detector, and the result was compared with the measured one. The simulation was extended to the CZT detector with strip electrodes. (author)

SU-C-204-06: Monte Carlo Dose Calculation for Kilovoltage X-Ray-Psoralen Activated Cancer Therapy (X-PACT): Preliminary Results

Energy Technology Data Exchange (ETDEWEB)

Mein, S [Duke University Medical Physics Graduate Program (United States); Gunasingha, R [Department of Radiation Safety, Duke University Medical Center (United States); Nolan, M [Department of Clinical Sciences, College of Veterinary Medicine, North Carolina State University (United States); Oldham, M; Adamson, J [Department of Radiation Oncology, Duke University Medical Center (United States)

2016-06-15

Purpose: X-PACT is an experimental cancer therapy where kV x-rays are used to photo-activate anti-cancer therapeutics through phosphor intermediaries (phosphors that absorb x-rays and re-radiate as UV light). Clinical trials in pet dogs are currently underway (NC State College of Veterinary Medicine) and an essential component is the ability to model the kV dose in these dogs. Here we report the commissioning and characterization of a Monte Carlo (MC) treatment planning simulation tool to calculate X-PACT radiation doses in canine trials. Methods: FLUKA multi-particle MC simulation package was used to simulate a standard X-PACT radiation treatment beam of 80kVp with the Varian OBI x-ray source geometry. The beam quality was verified by comparing measured and simulated attenuation of the beam by various thicknesses of aluminum (2–4.6 mm) under narrow beam conditions (HVL). The beam parameters at commissioning were then corroborated using MC, characterized and verified with empirically collected commissioning data, including: percent depth dose curves (PDD), back-scatter factors (BSF), collimator scatter factor(s), and heel effect, etc. All simulations were conducted for N=30M histories at M=100 iterations. Results: HVL and PDD simulation data agreed with an average percent error of 2.42%±0.33 and 6.03%±1.58, respectively. The mean square error (MSE) values for HVL and PDD (0.07% and 0.50%) were low, as expected; however, longer simulations are required to validate convergence to the expected values. Qualitatively, pre- and post-filtration source spectra matched well with 80kVp references generated via SPEKTR software. Further validation of commissioning data simulation is underway in preparation for first-time 3D dose calculations with canine CBCT data. Conclusion: We have prepared a Monte Carlo simulation capable of accurate dose calculation for use with ongoing X-PACT canine clinical trials. Preliminary results show good agreement with measured data and hold

Reconstruction of Monte Carlo replicas from Hessian parton distributions

Energy Technology Data Exchange (ETDEWEB)

Hou, Tie-Jiun [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Gao, Jun [INPAC, Shanghai Key Laboratory for Particle Physics and Cosmology,Department of Physics and Astronomy, Shanghai Jiao-Tong University, Shanghai 200240 (China); High Energy Physics Division, Argonne National Laboratory,Argonne, Illinois, 60439 (United States); Huston, Joey [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Nadolsky, Pavel [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Schmidt, Carl; Stump, Daniel [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Wang, Bo-Ting; Xie, Ke Ping [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Dulat, Sayipjamal [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); School of Physics Science and Technology, Xinjiang University,Urumqi, Xinjiang 830046 (China); Center for Theoretical Physics, Xinjiang University,Urumqi, Xinjiang 830046 (China); Pumplin, Jon; Yuan, C.P. [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States)

2017-03-20

We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation are converted into Monte-Carlo replicas by a numerical method that reproduces important properties of CT14 Hessian PDFs: the asymmetry of CT14 uncertainties and positivity of individual parton distributions. The ensembles of CT14 Monte-Carlo replicas constructed this way at NNLO and NLO are suitable for various collider applications, such as cross section reweighting. Master formulas for computation of asymmetric standard deviations in the Monte-Carlo representation are derived. A correction is proposed to address a bias in asymmetric uncertainties introduced by the Taylor series approximation. A numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.

Sampling from a polytope and hard-disk Monte Carlo

International Nuclear Information System (INIS)

Kapfer, Sebastian C; Krauth, Werner

2013-01-01

The hard-disk problem, the statics and the dynamics of equal two-dimensional hard spheres in a periodic box, has had a profound influence on statistical and computational physics. Markov-chain Monte Carlo and molecular dynamics were first discussed for this model. Here we reformulate hard-disk Monte Carlo algorithms in terms of another classic problem, namely the sampling from a polytope. Local Markov-chain Monte Carlo, as proposed by Metropolis et al. in 1953, appears as a sequence of random walks in high-dimensional polytopes, while the moves of the more powerful event-chain algorithm correspond to molecular dynamics evolution. We determine the convergence properties of Monte Carlo methods in a special invariant polytope associated with hard-disk configurations, and the implications for convergence of hard-disk sampling. Finally, we discuss parallelization strategies for event-chain Monte Carlo and present results for a multicore implementation

Problems in radiation shielding calculations with Monte Carlo methods

International Nuclear Information System (INIS)

Ueki, Kohtaro

1985-01-01

The Monte Carlo method is a very useful tool for solving a large class of radiation transport problem. In contrast with deterministic method, geometric complexity is a much less significant problem for Monte Carlo calculations. However, the accuracy of Monte Carlo calculations is of course, limited by statistical error of the quantities to be estimated. In this report, we point out some typical problems to solve a large shielding system including radiation streaming. The Monte Carlo coupling technique was developed to settle such a shielding problem accurately. However, the variance of the Monte Carlo results using the coupling technique of which detectors were located outside the radiation streaming, was still not enough. So as to bring on more accurate results for the detectors located outside the streaming and also for a multi-legged-duct streaming problem, a practicable way of ''Prism Scattering technique'' is proposed in the study. (author)

Cluster monte carlo method for nuclear criticality safety calculation

International Nuclear Information System (INIS)

Pei Lucheng

1984-01-01

One of the most important applications of the Monte Carlo method is the calculation of the nuclear criticality safety. The fair source game problem was presented at almost the same time as the Monte Carlo method was applied to calculating the nuclear criticality safety. The source iteration cost may be reduced as much as possible or no need for any source iteration. This kind of problems all belongs to the fair source game prolems, among which, the optimal source game is without any source iteration. Although the single neutron Monte Carlo method solved the problem without the source iteration, there is still quite an apparent shortcoming in it, that is, it solves the problem without the source iteration only in the asymptotic sense. In this work, a new Monte Carlo method called the cluster Monte Carlo method is given to solve the problem further

Wielandt acceleration for MCNP5 Monte Carlo eigenvalue calculations

International Nuclear Information System (INIS)

Brown, F.

2007-01-01

Monte Carlo criticality calculations use the power iteration method to determine the eigenvalue (k eff ) and eigenfunction (fission source distribution) of the fundamental mode. A recently proposed method for accelerating convergence of the Monte Carlo power iteration using Wielandt's method has been implemented in a test version of MCNP5. The method is shown to provide dramatic improvements in convergence rates and to greatly reduce the possibility of false convergence assessment. The method is effective and efficient, improving the Monte Carlo figure-of-merit for many problems. In addition, the method should eliminate most of the underprediction bias in confidence intervals for Monte Carlo criticality calculations. (authors)

Applications of the Monte Carlo method in radiation protection

International Nuclear Information System (INIS)

Kulkarni, R.N.; Prasad, M.A.

1999-01-01

This paper gives a brief introduction to the application of the Monte Carlo method in radiation protection. It may be noted that an exhaustive review has not been attempted. The special advantage of the Monte Carlo method has been first brought out. The fundamentals of the Monte Carlo method have next been explained in brief, with special reference to two applications in radiation protection. Some sample current applications have been reported in the end in brief as examples. They are, medical radiation physics, microdosimetry, calculations of thermoluminescence intensity and probabilistic safety analysis. The limitations of the Monte Carlo method have also been mentioned in passing. (author)

Pore-scale uncertainty quantification with multilevel Monte Carlo

KAUST Repository

Icardi, Matteo; Hoel, Haakon; Long, Quan; Tempone, Raul

2014-01-01

. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost

Current and future applications of Monte Carlo

International Nuclear Information System (INIS)

Zaidi, H.

2003-01-01

Full text: The use of radionuclides in medicine has a long history and encompasses a large area of applications including diagnosis and radiation treatment of cancer patients using either external or radionuclide radiotherapy. The 'Monte Carlo method'describes a very broad area of science, in which many processes, physical systems, and phenomena are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is as similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions (pdfs). As the number of individual events (called 'histories') is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. The use of the Monte Carlo method to simulate radiation transport has become the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides as well as the assessment of image quality and quantitative accuracy of radionuclide imaging. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the nuclear medicine community at large. Many of these questions will be answered when Monte Carlo techniques are implemented and used for more routine calculations and for in-depth investigations. In this paper, the conceptual role of the Monte Carlo method is briefly introduced and followed by a survey of its different applications in diagnostic and therapeutic

Quantum statistical Monte Carlo methods and applications to spin systems

International Nuclear Information System (INIS)

Suzuki, M.

1986-01-01

A short review is given concerning the quantum statistical Monte Carlo method based on the equivalence theorem that d-dimensional quantum systems are mapped onto (d+1)-dimensional classical systems. The convergence property of this approximate tansformation is discussed in detail. Some applications of this general appoach to quantum spin systems are reviewed. A new Monte Carlo method, ''thermo field Monte Carlo method,'' is presented, which is an extension of the projection Monte Carlo method at zero temperature to that at finite temperatures

TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

Energy Technology Data Exchange (ETDEWEB)

Badal, A [U.S. Food and Drug Administration (CDRH/OSEL), Silver Spring, MD (United States); Zbijewski, W [Johns Hopkins University, Baltimore, MD (United States); Bolch, W [University of Florida, Gainesville, FL (United States); Sechopoulos, I [Emory University, Atlanta, GA (United States)

2014-06-15

Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10{sup 7} xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the

TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

International Nuclear Information System (INIS)

Badal, A; Zbijewski, W; Bolch, W; Sechopoulos, I

2014-01-01

Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10 7 xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the virtual

SPQR: a Monte Carlo reactor kinetics code

International Nuclear Information System (INIS)

Cramer, S.N.; Dodds, H.L.

1980-02-01

The SPQR Monte Carlo code has been developed to analyze fast reactor core accident problems where conventional methods are considered inadequate. The code is based on the adiabatic approximation of the quasi-static method. This initial version contains no automatic material motion or feedback. An existing Monte Carlo code is used to calculate the shape functions and the integral quantities needed in the kinetics module. Several sample problems have been devised and analyzed. Due to the large statistical uncertainty associated with the calculation of reactivity in accident simulations, the results, especially at later times, differ greatly from deterministic methods. It was also found that in large uncoupled systems, the Monte Carlo method has difficulty in handling asymmetric perturbations

Optix: A Monte Carlo scintillation light transport code

Energy Technology Data Exchange (ETDEWEB)

Safari, M.J., E-mail: mjsafari@aut.ac.ir [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Afarideh, H. [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Ghal-Eh, N. [School of Physics, Damghan University, PO Box 36716-41167, Damghan (Iran, Islamic Republic of); Davani, F. Abbasi [Nuclear Engineering Department, Shahid Beheshti University, PO Box 1983963113, Tehran (Iran, Islamic Republic of)

2014-02-11

The paper reports on the capabilities of Monte Carlo scintillation light transport code Optix, which is an extended version of previously introduced code Optics. Optix provides the user a variety of both numerical and graphical outputs with a very simple and user-friendly input structure. A benchmarking strategy has been adopted based on the comparison with experimental results, semi-analytical solutions, and other Monte Carlo simulation codes to verify various aspects of the developed code. Besides, some extensive comparisons have been made against the tracking abilities of general-purpose MCNPX and FLUKA codes. The presented benchmark results for the Optix code exhibit promising agreements. -- Highlights: • Monte Carlo simulation of scintillation light transport in 3D geometry. • Evaluation of angular distribution of detected photons. • Benchmark studies to check the accuracy of Monte Carlo simulations.

Bayesian phylogeny analysis via stochastic approximation Monte Carlo

KAUST Repository

Cheon, Sooyoung

2009-11-01

Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.

Present status and future prospects of neutronics Monte Carlo

International Nuclear Information System (INIS)

Gelbard, E.M.

1990-01-01

It is fair to say that the Monte Carlo method, over the last decade, has grown steadily more important as a neutronics computational tool. Apparently this has happened for assorted reasons. Thus, for example, as the power of computers has increased, the cost of the method has dropped, steadily becoming less and less of an obstacle to its use. In addition, more and more sophisticated input processors have now made it feasible to model extremely complicated systems routinely with really remarkable fidelity. Finally, as we demand greater and greater precision in reactor calculations, Monte Carlo is often found to be the only method accurate enough for use in benchmarking. Cross section uncertainties are now almost the only inherent limitations in our Monte Carlo capabilities. For this reason Monte Carlo has come to occupy a special position, interposed between experiment and other computational techniques. More and more often deterministic methods are tested by comparison with Monte Carlo, and cross sections are tested by comparing Monte Carlo with experiment. In this way one can distinguish very clearly between errors due to flaws in our numerical methods, and those due to deficiencies in cross section files. The special role of Monte Carlo as a benchmarking tool, often the only available benchmarking tool, makes it crucially important that this method should be polished to perfection. Problems relating to Eigenvalue calculations, variance reduction and the use of advanced computers are reviewed in this paper. (author)

Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

Science.gov (United States)

Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

2018-02-01

Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

Neutron point-flux calculation by Monte Carlo

International Nuclear Information System (INIS)

Eichhorn, M.

1986-04-01

A survey of the usual methods for estimating flux at a point is given. The associated variance-reducing techniques in direct Monte Carlo games are explained. The multigroup Monte Carlo codes MC for critical systems and PUNKT for point source-point detector-systems are represented, and problems in applying the codes to practical tasks are discussed. (author)

Frequency domain Monte Carlo simulation method for cross power spectral density driven by periodically pulsed spallation neutron source using complex-valued weight Monte Carlo

International Nuclear Information System (INIS)

Yamamoto, Toshihiro

2014-01-01

Highlights: • The cross power spectral density in ADS has correlated and uncorrelated components. • A frequency domain Monte Carlo method to calculate the uncorrelated one is developed. • The method solves the Fourier transformed transport equation. • The method uses complex-valued weights to solve the equation. • The new method reproduces well the CPSDs calculated with time domain MC method. - Abstract: In an accelerator driven system (ADS), pulsed spallation neutrons are injected at a constant frequency. The cross power spectral density (CPSD), which can be used for monitoring the subcriticality of the ADS, is composed of the correlated and uncorrelated components. The uncorrelated component is described by a series of the Dirac delta functions that occur at the integer multiples of the pulse repetition frequency. In the present paper, a Monte Carlo method to solve the Fourier transformed neutron transport equation with a periodically pulsed neutron source term has been developed to obtain the CPSD in ADSs. Since the Fourier transformed flux is a complex-valued quantity, the Monte Carlo method introduces complex-valued weights to solve the Fourier transformed equation. The Monte Carlo algorithm used in this paper is similar to the one that was developed by the author of this paper to calculate the neutron noise caused by cross section perturbations. The newly-developed Monte Carlo algorithm is benchmarked to the conventional time domain Monte Carlo simulation technique. The CPSDs are obtained both with the newly-developed frequency domain Monte Carlo method and the conventional time domain Monte Carlo method for a one-dimensional infinite slab. The CPSDs obtained with the frequency domain Monte Carlo method agree well with those with the time domain method. The higher order mode effects on the CPSD in an ADS with a periodically pulsed neutron source are discussed

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.

Research on perturbation based Monte Carlo reactor criticality search

International Nuclear Information System (INIS)

Li Zeguang; Wang Kan; Li Yangliu; Deng Jingkang

2013-01-01

Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Traditional Monte Carlo criticality search method is suffered from large amount of individual criticality runs and uncertainty and fluctuation of Monte Carlo results. A new Monte Carlo criticality search method based on perturbation calculation is put forward in this paper to overcome the disadvantages of traditional method. By using only one criticality run to get initial k_e_f_f and differential coefficients of concerned parameter, the polynomial estimator of k_e_f_f changing function is solved to get the critical value of concerned parameter. The feasibility of this method was tested. The results show that the accuracy and efficiency of perturbation based criticality search method are quite inspiring and the method overcomes the disadvantages of traditional one. (authors)

Study of Gamma spectra by Monte Carlo simulation

International Nuclear Information System (INIS)

Cantaragiu, A.; Gheorghies, A.; Borcia, C.

2008-01-01

The purpose of this paper is obtaining gamma ray spectra by means of a scintillation detector applying the Monte Carlo statistic simulation method using the EGS4 program. The Monte Carlo algorithm implies that the physical system is described by the probability density function which allows generating random figures and the result is taken as an average of numbers which were observed. The EGS4 program allows the simulation of the following physical processes: the photo-electrical effect, the Compton effect, the electron positron pairs generation and the Rayleigh diffusion. The gamma rays recorded by the detector are converted into electrical pulses and the gamma ray spectra are acquired and processed by means of the Nomad Plus portable spectrometer connected to a computer. As a gamma ray sources 137Cs and 60Co are used whose spectra drawn and used for study the interaction of the gamma radiations with the scintillation detector. The parameters which varied during the acquisition of the gamma ray spectra are the distance between source and detector and the measuring time. Due to the statistical processes in the detector, the peak looks like a Gauss distribution. The identification of the gamma quantum energy value is achieved by the experimental spectra peaks, thus gathering information about the position of the peak, the width and the area of the peak respectively. By means of the EGS4 program a simulation is run using these parameters and an 'ideal' spectrum is obtained, a spectrum which is not influenced by the statistical processes which take place inside the detector. Then, the convolution of the spectra is achieved by means of a normalised Gauss function. There is a close match between the experimental results and those simulated in the EGS4 program because the interactions which occurred during the simulation have a statistical behaviour close to the real one. (authors)

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)

Monte Carlo learning/biasing experiment with intelligent random numbers

International Nuclear Information System (INIS)

Booth, T.E.

1985-01-01

A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs

Temperature variance study in Monte-Carlo photon transport theory

International Nuclear Information System (INIS)

Giorla, J.

1985-10-01

We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr

Monte Carlo applications to radiation shielding problems

International Nuclear Information System (INIS)

Subbaiah, K.V.

2009-01-01

Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling of physical and mathematical systems to compute their results. However, basic concepts of MC are both simple and straightforward and can be learned by using a personal computer. Uses of Monte Carlo methods require large amounts of random numbers, and it was their use that spurred the development of pseudorandom number generators, which were far quicker to use than the tables of random numbers which had been previously used for statistical sampling. In Monte Carlo simulation of radiation transport, the history (track) of a particle is viewed as a random sequence of free flights that end with an interaction event where the particle changes its direction of movement, loses energy and, occasionally, produces secondary particles. The Monte Carlo simulation of a given experimental arrangement (e.g., an electron beam, coming from an accelerator and impinging on a water phantom) consists of the numerical generation of random histories. To simulate these histories we need an interaction model, i.e., a set of differential cross sections (DCS) for the relevant interaction mechanisms. The DCSs determine the probability distribution functions (pdf) of the random variables that characterize a track; 1) free path between successive interaction events, 2) type of interaction taking place and 3) energy loss and angular deflection in a particular event (and initial state of emitted secondary particles, if any). Once these pdfs are known, random histories can be generated by using appropriate sampling methods. If the number of generated histories is large enough, quantitative information on the transport process may be obtained by simply averaging over the simulated histories. The Monte Carlo method yields the same information as the solution of the Boltzmann transport equation, with the same interaction model, but is easier to implement. In particular, the simulation of radiation

Evaluation of the self-absorption of 14C beta-rays in gel-suspension samples by Monte Carlo simulation

International Nuclear Information System (INIS)

Wakabayashi, G.; Nagao, K.; Okai, T.; Matoba, M.

2003-01-01

In order to investigate the self-absorption of the β-rays from 14 C in a gel-suspension sample, the Monte Carlo code, simulating the sequence of stages occurring in the sample, has been developed. The trajectory of the electron was calculated by the continuous slowing down approximation and the multiple Coulomb scattering theory. The effects of the self-absorption, strong quenching and particle size distribution of calcium carbonate on the output counting efficiency and the shape of the energy spectrum were evaluated. (author)

hybrid\\scriptsize{{MANTIS}}: a CPU-GPU Monte Carlo method for modeling indirect x-ray detectors with columnar scintillators

Science.gov (United States)

Sharma, Diksha; Badal, Andreu; Badano, Aldo

2012-04-01

The computational modeling of medical imaging systems often requires obtaining a large number of simulated images with low statistical uncertainty which translates into prohibitive computing times. We describe a novel hybrid approach for Monte Carlo simulations that maximizes utilization of CPUs and GPUs in modern workstations. We apply the method to the modeling of indirect x-ray detectors using a new and improved version of the code \\scriptsize{{MANTIS}}, an open source software tool used for the Monte Carlo simulations of indirect x-ray imagers. We first describe a GPU implementation of the physics and geometry models in fast\\scriptsize{{DETECT}}2 (the optical transport model) and a serial CPU version of the same code. We discuss its new features like on-the-fly column geometry and columnar crosstalk in relation to the \\scriptsize{{MANTIS}} code, and point out areas where our model provides more flexibility for the modeling of realistic columnar structures in large area detectors. Second, we modify \\scriptsize{{PENELOPE}} (the open source software package that handles the x-ray and electron transport in \\scriptsize{{MANTIS}}) to allow direct output of location and energy deposited during x-ray and electron interactions occurring within the scintillator. This information is then handled by optical transport routines in fast\\scriptsize{{DETECT}}2. A load balancer dynamically allocates optical transport showers to the GPU and CPU computing cores. Our hybrid\\scriptsize{{MANTIS}} approach achieves a significant speed-up factor of 627 when compared to \\scriptsize{{MANTIS}} and of 35 when compared to the same code running only in a CPU instead of a GPU. Using hybrid\\scriptsize{{MANTIS}}, we successfully hide hours of optical transport time by running it in parallel with the x-ray and electron transport, thus shifting the computational bottleneck from optical to x-ray transport. The new code requires much less memory than \\scriptsize{{MANTIS}} and, as a result

Randomized quasi-Monte Carlo simulation of fast-ion thermalization

Science.gov (United States)

Höök, L. J.; Johnson, T.; Hellsten, T.

2012-01-01

This work investigates the applicability of the randomized quasi-Monte Carlo method for simulation of fast-ion thermalization processes in fusion plasmas, e.g. for simulation of neutral beam injection and radio frequency heating. In contrast to the standard Monte Carlo method, the quasi-Monte Carlo method uses deterministic numbers instead of pseudo-random numbers and has a statistical weak convergence close to {O}(N^{-1}) , where N is the number of markers. We have compared different quasi-Monte Carlo methods for a neutral beam injection scenario, which is solved by many realizations of the associated stochastic differential equation, discretized with the Euler-Maruyama scheme. The statistical convergence of the methods is measured for time steps up to 214.

A high-quality multilayer structure characterization method based on X-ray fluorescence and Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Brunetti, Antonio; Golosio, Bruno [Universita degli Studi di Sassari, Dipartimento di Scienze Politiche, Scienze della Comunicazione e Ingegneria dell' Informazione, Sassari (Italy); Melis, Maria Grazia [Universita degli Studi di Sassari, Dipartimento di Storia, Scienze dell' Uomo e della Formazione, Sassari (Italy); Mura, Stefania [Universita degli Studi di Sassari, Dipartimento di Agraria e Nucleo di Ricerca sulla Desertificazione, Sassari (Italy)

2014-11-08

X-ray fluorescence (XRF) is a well known nondestructive technique. It is also applied to multilayer characterization, due to its possibility of estimating both composition and thickness of the layers. Several kinds of cultural heritage samples can be considered as a complex multilayer, such as paintings or decorated objects or some types of metallic samples. Furthermore, they often have rough surfaces and this makes a precise determination of the structure and composition harder. The standard quantitative XRF approach does not take into account this aspect. In this paper, we propose a novel approach based on a combined use of X-ray measurements performed with a polychromatic beam and Monte Carlo simulations. All the information contained in an X-ray spectrum is used. This approach allows obtaining a very good estimation of the sample contents both in terms of chemical elements and material thickness, and in this sense, represents an improvement of the possibility of XRF measurements. Some examples will be examined and discussed. (orig.)

A high-quality multilayer structure characterization method based on X-ray fluorescence and Monte Carlo simulation

International Nuclear Information System (INIS)

Brunetti, Antonio; Golosio, Bruno; Melis, Maria Grazia; Mura, Stefania

2015-01-01

X-ray fluorescence (XRF) is a well known nondestructive technique. It is also applied to multilayer characterization, due to its possibility of estimating both composition and thickness of the layers. Several kinds of cultural heritage samples can be considered as a complex multilayer, such as paintings or decorated objects or some types of metallic samples. Furthermore, they often have rough surfaces and this makes a precise determination of the structure and composition harder. The standard quantitative XRF approach does not take into account this aspect. In this paper, we propose a novel approach based on a combined use of X-ray measurements performed with a polychromatic beam and Monte Carlo simulations. All the information contained in an X-ray spectrum is used. This approach allows obtaining a very good estimation of the sample contents both in terms of chemical elements and material thickness, and in this sense, represents an improvement of the possibility of XRF measurements. Some examples will be examined and discussed. (orig.)

Development of three-dimensional program based on Monte Carlo and discrete ordinates bidirectional coupling method

International Nuclear Information System (INIS)

Han Jingru; Chen Yixue; Yuan Longjun

2013-01-01

The Monte Carlo (MC) and discrete ordinates (SN) are the commonly used methods in the design of radiation shielding. Monte Carlo method is able to treat the geometry exactly, but time-consuming in dealing with the deep penetration problem. The discrete ordinate method has great computational efficiency, but it is quite costly in computer memory and it suffers from ray effect. Single discrete ordinates method or single Monte Carlo method has limitation in shielding calculation for large complex nuclear facilities. In order to solve the problem, the Monte Carlo and discrete ordinates bidirectional coupling method is developed. The bidirectional coupling method is implemented in the interface program to transfer the particle probability distribution of MC and angular flux of discrete ordinates. The coupling method combines the advantages of MC and SN. The test problems of cartesian and cylindrical coordinate have been calculated by the coupling methods. The calculation results are performed with comparison to MCNP and TORT and satisfactory agreements are obtained. The correctness of the program is proved. (authors)

A Monte Carlo algorithm for the Vavilov distribution

International Nuclear Information System (INIS)

Yi, Chul-Young; Han, Hyon-Soo

1999-01-01

Using the convolution property of the inverse Laplace transform, an improved Monte Carlo algorithm for the Vavilov energy-loss straggling distribution of the charged particle is developed, which is relatively simple and gives enough accuracy to be used for most Monte Carlo applications

Adaptive Multilevel Monte Carlo Simulation

KAUST Repository

Hoel, H

2011-08-23

This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).

Nested Sampling with Constrained Hamiltonian Monte Carlo

OpenAIRE

Betancourt, M. J.

2010-01-01

Nested sampling is a powerful approach to Bayesian inference ultimately limited by the computationally demanding task of sampling from a heavily constrained probability distribution. An effective algorithm in its own right, Hamiltonian Monte Carlo is readily adapted to efficiently sample from any smooth, constrained distribution. Utilizing this constrained Hamiltonian Monte Carlo, I introduce a general implementation of the nested sampling algorithm.

Monte Carlo computation in the applied research of nuclear technology

International Nuclear Information System (INIS)

Xu Shuyan; Liu Baojie; Li Qin

2007-01-01

This article briefly introduces Monte Carlo Methods and their properties. It narrates the Monte Carlo methods with emphasis in their applications to several domains of nuclear technology. Monte Carlo simulation methods and several commonly used computer software to implement them are also introduced. The proposed methods are demonstrated by a real example. (authors)

Statistics of Monte Carlo methods used in radiation transport calculation

International Nuclear Information System (INIS)

Datta, D.

2009-01-01

Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport

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

Multiple histogram method and static Monte Carlo sampling

NARCIS (Netherlands)

Inda, M.A.; Frenkel, D.

2004-01-01

We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From

Forest canopy BRDF simulation using Monte Carlo method

NARCIS (Netherlands)

Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.

2006-01-01

Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.

Discrete Diffusion Monte Carlo for Electron Thermal Transport

Science.gov (United States)

Chenhall, Jeffrey; Cao, Duc; Wollaeger, Ryan; Moses, Gregory

2014-10-01

The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. is adapted to a Discrete Diffusion Monte Carlo (DDMC) solution method for eventual inclusion in a hybrid IMC-DDMC (Implicit Monte Carlo) method. The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the iSNB-DDMC method will be presented. This work was supported by Sandia National Laboratory - Albuquerque.

Monte Carlo techniques in diagnostic and therapeutic nuclear medicine

International Nuclear Information System (INIS)

Zaidi, H.

2002-01-01

Monte Carlo techniques have become one of the most popular tools in different areas of medical radiation physics following the development and subsequent implementation of powerful computing systems for clinical use. In particular, they have been extensively applied to simulate processes involving random behaviour and to quantify physical parameters that are difficult or even impossible to calculate analytically or to determine by experimental measurements. The use of the Monte Carlo method to simulate radiation transport turned out to be the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides. There is broad consensus in accepting that the earliest Monte Carlo calculations in medical radiation physics were made in the area of nuclear medicine, where the technique was used for dosimetry modelling and computations. Formalism and data based on Monte Carlo calculations, developed by the Medical Internal Radiation Dose (MIRD) committee of the Society of Nuclear Medicine, were published in a series of supplements to the Journal of Nuclear Medicine, the first one being released in 1968. Some of these pamphlets made extensive use of Monte Carlo calculations to derive specific absorbed fractions for electron and photon sources uniformly distributed in organs of mathematical phantoms. Interest in Monte Carlo-based dose calculations with β-emitters has been revived with the application of radiolabelled monoclonal antibodies to radioimmunotherapy. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the medical physics

Monte Carlo strategies in scientific computing

CERN Document Server

Liu, Jun S

2008-01-01

This paperback edition is a reprint of the 2001 Springer edition This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians It can also be used as the textbook for a graduate-level course on Monte Carlo methods Many problems discussed in the alter chapters can be potential thesis topics for masters’ or PhD students in statistics or computer science departments Jun Liu is Professor of Statistics at Harvard University, with a courtesy Professor appointment at Harvard Biostatistics Department Professor Liu was the recipient of the 2002 COPSS Presidents' Award, the most prestigious one for sta...

Off-diagonal expansion quantum Monte Carlo.

Science.gov (United States)

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

Prediction of beam hardening artefacts in computed tomography using Monte Carlo simulations

DEFF Research Database (Denmark)

Thomsen, M.; Bergbäck Knudsen, Erik; Willendrup, Peter Kjær

2015-01-01

We show how radiological images of both single and multi material samples can be simulated using the Monte Carlo simulation tool McXtrace and how these images can be used to make a three dimensional reconstruction. Good numerical agreement between the X-ray attenuation coefficient in experimental...

Dynamic bounds coupled with Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Rajabalinejad, M., E-mail: M.Rajabalinejad@tudelft.n [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands); Meester, L.E. [Delft Institute of Applied Mathematics, Delft University of Technology, Delft (Netherlands); Gelder, P.H.A.J.M. van; Vrijling, J.K. [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands)

2011-02-15

For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans.

Coded aperture optimization using Monte Carlo simulations

International Nuclear Information System (INIS)

Martineau, A.; Rocchisani, J.M.; Moretti, J.L.

2010-01-01

Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood Expectation-Maximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The aim of the algorithm is to reduce artifacts and improve the three-dimensional spatial resolution in the reconstructed images. Firstly, we present the validation of GATE (Geant4 Application for Emission Tomography) for Monte Carlo simulations of a coded mask installed on a clinical gamma camera. The coded mask modelling was validated by comparison between experimental and simulated data in terms of energy spectra, sensitivity and spatial resolution. In the second part of the study, we use the validated model to calculate the projection matrix with Monte Carlo simulations. A three-dimensional thyroid phantom study was performed to compare the performance of the three-dimensional MLEM reconstruction with conventional correlation method. The results indicate that the artifacts are reduced and three-dimensional spatial resolution is improved with the Monte Carlo-based MLEM reconstruction.

Variational Monte Carlo Technique

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 8. Variational Monte Carlo Technique: Ground State Energies of Quantum Mechanical Systems. Sukanta Deb. General Article Volume 19 Issue 8 August 2014 pp 713-739 ...

Randomized quasi-Monte Carlo simulation of fast-ion thermalization

International Nuclear Information System (INIS)

Höök, L J; Johnson, T; Hellsten, T

2012-01-01

This work investigates the applicability of the randomized quasi-Monte Carlo method for simulation of fast-ion thermalization processes in fusion plasmas, e.g. for simulation of neutral beam injection and radio frequency heating. In contrast to the standard Monte Carlo method, the quasi-Monte Carlo method uses deterministic numbers instead of pseudo-random numbers and has a statistical weak convergence close to O(N -1 ), where N is the number of markers. We have compared different quasi-Monte Carlo methods for a neutral beam injection scenario, which is solved by many realizations of the associated stochastic differential equation, discretized with the Euler-Maruyama scheme. The statistical convergence of the methods is measured for time steps up to 2 14 . (paper)

Usefulness of the Monte Carlo method in reliability calculations

International Nuclear Information System (INIS)

Lanore, J.M.; Kalli, H.

1977-01-01

Three examples of reliability Monte Carlo programs developed in the LEP (Laboratory for Radiation Shielding Studies in the Nuclear Research Center at Saclay) are presented. First, an uncertainty analysis is given for a simplified spray system; a Monte Carlo program PATREC-MC has been written to solve the problem with the system components given in the fault tree representation. The second program MONARC 2 has been written to solve the problem of complex systems reliability by the Monte Carlo simulation, here again the system (a residual heat removal system) is in the fault tree representation. Third, the Monte Carlo program MONARC was used instead of the Markov diagram to solve the simulation problem of an electric power supply including two nets and two stand-by diesels

Combinatorial nuclear level density by a Monte Carlo method

International Nuclear Information System (INIS)

Cerf, N.

1994-01-01

We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte Carlo simulation, making use of the Metropolis sampling scheme, allows a computationally fast estimate of the level density for many fermion systems in large shell model spaces. We emphasize the advantages of this Monte Carlo approach, particularly concerning the prediction of the spin and parity distributions of the excited states,and compare our results with those derived from a traditional combinatorial or a statistical method. Such a Monte Carlo technique seems very promising to determine accurate level densities in a large energy range for nuclear reaction calculations

Monte Carlo variance reduction approaches for non-Boltzmann tallies

International Nuclear Information System (INIS)

Booth, T.E.

1992-12-01

Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed

Monte Carlo simulation of the electron and X-ray depth distribution for quantitative electron probe microanalysis of PWR spent fuels

Energy Technology Data Exchange (ETDEWEB)

Kwon, Hyoung Mun; Lee, Hyung Kwon; Son, Young Zoon; Chun, Yong Bum [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2011-10-15

Electron probe microanalysis requires several corrections to quantify an element of a specimen. The X-rays produced by the primary beam are created at some depth in the specimen. This distribution is usually represented as the function {Phi}(pz), and it is possible to calculate the correction factors for atomic number and absorption effects. The electron and X-ray depth distributions for a quantitative electron probe micro analysis were simulated by the CASINO Monte Carlo program to quantify some elements of the PWR spent fuel with 50 GWd/tU of burnup and 2 years of cooling time

Monte Carlo simulation of the electron and X-ray depth distribution for quantitative electron probe microanalysis of PWR spent fuels

International Nuclear Information System (INIS)

Kwon, Hyoung Mun; Lee, Hyung Kwon; Son, Young Zoon; Chun, Yong Bum

2011-01-01

Electron probe microanalysis requires several corrections to quantify an element of a specimen. The X-rays produced by the primary beam are created at some depth in the specimen. This distribution is usually represented as the function Φ(pz), and it is possible to calculate the correction factors for atomic number and absorption effects. The electron and X-ray depth distributions for a quantitative electron probe micro analysis were simulated by the CASINO Monte Carlo program to quantify some elements of the PWR spent fuel with 50 GWd/tU of burnup and 2 years of cooling time

The vector and parallel processing of MORSE code on Monte Carlo Machine

International Nuclear Information System (INIS)

Hasegawa, Yukihiro; Higuchi, Kenji.

1995-11-01

Multi-group Monte Carlo Code for particle transport, MORSE is modified for high performance computing on Monte Carlo Machine Monte-4. The method and the results are described. Monte-4 was specially developed to realize high performance computing of Monte Carlo codes for particle transport, which have been difficult to obtain high performance in vector processing on conventional vector processors. Monte-4 has four vector processor units with the special hardware called Monte Carlo pipelines. The vectorization and parallelization of MORSE code and the performance evaluation on Monte-4 are described. (author)

Discrete diffusion Monte Carlo for frequency-dependent radiative transfer

International Nuclear Information System (INIS)

Densmore, Jeffery D.; Thompson, Kelly G.; Urbatsch, Todd J.

2011-01-01

Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations. In this paper, we develop an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency integrated diffusion equation for frequencies below a specified threshold. Above this threshold we employ standard Monte Carlo. With a frequency-dependent test problem, we confirm the increased efficiency of our new DDMC technique. (author)

Uncertainty analysis in Monte Carlo criticality computations

International Nuclear Information System (INIS)

Qi Ao

2011-01-01

Highlights: ► Two types of uncertainty methods for k eff Monte Carlo computations are examined. ► Sampling method has the least restrictions on perturbation but computing resources. ► Analytical method is limited to small perturbation on material properties. ► Practicality relies on efficiency, multiparameter applicability and data availability. - Abstract: Uncertainty analysis is imperative for nuclear criticality risk assessments when using Monte Carlo neutron transport methods to predict the effective neutron multiplication factor (k eff ) for fissionable material systems. For the validation of Monte Carlo codes for criticality computations against benchmark experiments, code accuracy and precision are measured by both the computational bias and uncertainty in the bias. The uncertainty in the bias accounts for known or quantified experimental, computational and model uncertainties. For the application of Monte Carlo codes for criticality analysis of fissionable material systems, an administrative margin of subcriticality must be imposed to provide additional assurance of subcriticality for any unknown or unquantified uncertainties. Because of a substantial impact of the administrative margin of subcriticality on economics and safety of nuclear fuel cycle operations, recently increasing interests in reducing the administrative margin of subcriticality make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k eff uncertainty analysis methods for Monte Carlo criticality computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage in the k eff uncertainty analysis due to uncertainties in both neutronic and non-neutronic parameters of fissionable material systems.

Modified Monte Carlo procedure for particle transport problems

International Nuclear Information System (INIS)

Matthes, W.

1978-01-01

The simulation of photon transport in the atmosphere with the Monte Carlo method forms part of the EURASEP-programme. The specifications for the problems posed for a solution were such, that the direct application of the analogue Monte Carlo method was not feasible. For this reason the standard Monte Carlo procedure was modified in the sense that additional properly weighted branchings at each collision and transport process in a photon history were introduced. This modified Monte Carlo procedure leads to a clear and logical separation of the essential parts of a problem and offers a large flexibility for variance reducing techniques. More complex problems, as foreseen in the EURASEP-programme (e.g. clouds in the atmosphere, rough ocean-surface and chlorophyl-distribution in the ocean) can be handled by recoding some subroutines. This collision- and transport-splitting procedure can of course be performed differently in different space- and energy regions. It is applied here only for a homogeneous problem

Radiation doses in volume-of-interest breast computed tomography—A Monte Carlo simulation study

Energy Technology Data Exchange (ETDEWEB)

Lai, Chao-Jen, E-mail: cjlai3711@gmail.com; Zhong, Yuncheng; Yi, Ying; Wang, Tianpeng; Shaw, Chris C. [Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030-4009 (United States)

2015-06-15

Purpose: Cone beam breast computed tomography (breast CT) with true three-dimensional, nearly isotropic spatial resolution has been developed and investigated over the past decade to overcome the problem of lesions overlapping with breast anatomical structures on two-dimensional mammographic images. However, the ability of breast CT to detect small objects, such as tissue structure edges and small calcifications, is limited. To resolve this problem, the authors proposed and developed a volume-of-interest (VOI) breast CT technique to image a small VOI using a higher radiation dose to improve that region’s visibility. In this study, the authors performed Monte Carlo simulations to estimate average breast dose and average glandular dose (AGD) for the VOI breast CT technique. Methods: Electron–Gamma-Shower system code-based Monte Carlo codes were used to simulate breast CT. The Monte Carlo codes estimated were validated using physical measurements of air kerma ratios and point doses in phantoms with an ion chamber and optically stimulated luminescence dosimeters. The validated full cone x-ray source was then collimated to simulate half cone beam x-rays to image digital pendant-geometry, hemi-ellipsoidal, homogeneous breast phantoms and to estimate breast doses with full field scans. 13-cm in diameter, 10-cm long hemi-ellipsoidal homogeneous phantoms were used to simulate median breasts. Breast compositions of 25% and 50% volumetric glandular fractions (VGFs) were used to investigate the influence on breast dose. The simulated half cone beam x-rays were then collimated to a narrow x-ray beam with an area of 2.5 × 2.5 cm{sup 2} field of view at the isocenter plane and to perform VOI field scans. The Monte Carlo results for the full field scans and the VOI field scans were then used to estimate the AGD for the VOI breast CT technique. Results: The ratios of air kerma ratios and dose measurement results from the Monte Carlo simulation to those from the physical

MCNP-X Monte Carlo Code Application for Mass Attenuation Coefficients of Concrete at Different Energies by Modeling 3 × 3 Inch NaI(Tl Detector and Comparison with XCOM and Monte Carlo Data

Directory of Open Access Journals (Sweden)

Huseyin Ozan Tekin

2016-01-01

Full Text Available Gamma-ray measurements in various research fields require efficient detectors. One of these research fields is mass attenuation coefficients of different materials. Apart from experimental studies, the Monte Carlo (MC method has become one of the most popular tools in detector studies. An NaI(Tl detector has been modeled, and, for a validation study of the modeled NaI(Tl detector, the absolute efficiency of 3 × 3 inch cylindrical NaI(Tl detector has been calculated by using the general purpose Monte Carlo code MCNP-X (version 2.4.0 and compared with previous studies in literature in the range of 661–2620 keV. In the present work, the applicability of MCNP-X Monte Carlo code for mass attenuation of concrete sample material as building material at photon energies 59.5 keV, 80 keV, 356 keV, 661.6 keV, 1173.2 keV, and 1332.5 keV has been tested by using validated NaI(Tl detector. The mass attenuation coefficients of concrete sample have been calculated. The calculated results agreed well with experimental and some other theoretical results. The results specify that this process can be followed to determine the data on the attenuation of gamma-rays with other required energies in other materials or in new complex materials. It can be concluded that data from Monte Carlo is a strong tool not only for efficiency studies but also for mass attenuation coefficients calculations.

Study on shielding design method of radiation streaming in a tokamak-type DT fusion reactor based on Monte Carlo calculation

International Nuclear Information System (INIS)

Sato, Satoshi

2003-09-01

In tokamak-type DT nuclear fusion reactor, there are various type slits and ducts in the blanket and the vacuum vessel. The helium production in the rewelding location of the blanket and the vacuum vessel, the nuclear properties in the super-conductive TF coil, e.g. the nuclear heating rate in the coil winding pack, are enhanced by the radiation streaming through the slits and ducts, and they are critical concern in the shielding design. The decay gamma ray dose rate around the duct penetrating the blanket and the vacuum vessel is also enhanced by the radiation streaming through the duct, and they are also critical concern from the view point of the human access to the cryostat during maintenance. In order to evaluate these nuclear properties with good accuracy, three dimensional Monte Carlo calculation is required but requires long calculation time. Therefore, the development of the effective simple design evaluation method for radiation streaming is substantially important. This study aims to establish the systematic evaluation method for the nuclear properties of the blanket, the vacuum vessel and the Toroidal Field (TF) coil taking into account the radiation streaming through various types of slits and ducts, based on three dimensional Monte Carlo calculation using the MNCP code, and for the decay gamma ray dose rates penetrated around the ducts. The present thesis describes three topics in five chapters as follows; 1) In Chapter 2, the results calculated by the Monte Carlo code, MCNP, are compared with those by the Sn code, DOT3.5, for the radiation streaming in the tokamak-type nuclear fusion reactor, for validating the results of the Sn calculation. From this comparison, the uncertainties of the Sn calculation results coming from the ray-effect and the effect due to approximation of the geometry are investigated whether the two dimensional Sn calculation can be applied instead of the Monte Carlo calculation. Through the study, it can be concluded that the

An Overview of the Monte Carlo Application ToolKit (MCATK)

Energy Technology Data Exchange (ETDEWEB)

Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-01-07

MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library designed to build specialized applications and designed to provide new functionality in existing general-purpose Monte Carlo codes like MCNP; it was developed with Agile software engineering methodologies under the motivation to reduce costs. The characteristics of MCATK can be summarized as follows: MCATK physics – continuous energy neutron-gamma transport with multi-temperature treatment, static eigenvalue (k and α) algorithms, time-dependent algorithm, fission chain algorithms; MCATK geometry – mesh geometries, solid body geometries. MCATK provides verified, unit-tested Monte Carlo components, flexibility in Monte Carlo applications development, and numerous tools such as geometry and cross section plotters. Recent work has involved deterministic and Monte Carlo analysis of stochastic systems. Static and dynamic analysis is discussed, and the results of a dynamic test problem are given.

Computed radiography simulation using the Monte Carlo code MCNPX

International Nuclear Information System (INIS)

Correa, S.C.A.; Souza, E.M.; Silva, A.X.; Lopes, R.T.

2009-01-01

Simulating x-ray images has been of great interest in recent years as it makes possible an analysis of how x-ray images are affected owing to relevant operating parameters. In this paper, a procedure for simulating computed radiographic images using the Monte Carlo code MCNPX is proposed. The sensitivity curve of the BaFBr image plate detector as well as the characteristic noise of a 16-bit computed radiography system were considered during the methodology's development. The results obtained confirm that the proposed procedure for simulating computed radiographic images is satisfactory, as it allows obtaining results comparable with experimental data. (author)

Computed radiography simulation using the Monte Carlo code MCNPX

Energy Technology Data Exchange (ETDEWEB)

Correa, S.C.A. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Centro Universitario Estadual da Zona Oeste (CCMAT)/UEZO, Av. Manuel Caldeira de Alvarenga, 1203, Campo Grande, 23070-200, Rio de Janeiro, RJ (Brazil); Souza, E.M. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Silva, A.X., E-mail: ademir@con.ufrj.b [PEN/COPPE-DNC/Poli CT, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil); Cassiano, D.H. [Instituto de Radioprotecao e Dosimetria/CNEN Av. Salvador Allende, s/n, Recreio, 22780-160, Rio de Janeiro, RJ (Brazil); Lopes, R.T. [Programa de Engenharia Nuclear/COPPE, Universidade Federal do Rio de Janeiro, Ilha do Fundao, Caixa Postal 68509, 21945-970, Rio de Janeiro, RJ (Brazil)

2010-09-15

Simulating X-ray images has been of great interest in recent years as it makes possible an analysis of how X-ray images are affected owing to relevant operating parameters. In this paper, a procedure for simulating computed radiographic images using the Monte Carlo code MCNPX is proposed. The sensitivity curve of the BaFBr image plate detector as well as the characteristic noise of a 16-bit computed radiography system were considered during the methodology's development. The results obtained confirm that the proposed procedure for simulating computed radiographic images is satisfactory, as it allows obtaining results comparable with experimental data.

Efficiency and accuracy of Monte Carlo (importance) sampling

NARCIS (Netherlands)

Waarts, P.H.

2003-01-01

Monte Carlo Analysis is often regarded as the most simple and accurate reliability method. Be-sides it is the most transparent method. The only problem is the accuracy in correlation with the efficiency. Monte Carlo gets less efficient or less accurate when very low probabilities are to be computed

Suppression of the initial transient in Monte Carlo criticality simulations; Suppression du regime transitoire initial des simulations Monte-Carlo de criticite

Energy Technology Data Exchange (ETDEWEB)

Richet, Y

2006-12-15

Criticality Monte Carlo calculations aim at estimating the effective multiplication factor (k-effective) for a fissile system through iterations simulating neutrons propagation (making a Markov chain). Arbitrary initialization of the neutron population can deeply bias the k-effective estimation, defined as the mean of the k-effective computed at each iteration. A simplified model of this cycle k-effective sequence is built, based on characteristics of industrial criticality Monte Carlo calculations. Statistical tests, inspired by Brownian bridge properties, are designed to discriminate stationarity of the cycle k-effective sequence. The initial detected transient is, then, suppressed in order to improve the estimation of the system k-effective. The different versions of this methodology are detailed and compared, firstly on a plan of numerical tests fitted on criticality Monte Carlo calculations, and, secondly on real criticality calculations. Eventually, the best methodologies observed in these tests are selected and allow to improve industrial Monte Carlo criticality calculations. (author)

Monte Carlo criticality analysis for dissolvers with neutron poison

International Nuclear Information System (INIS)

Yu, Deshun; Dong, Xiufang; Pu, Fuxiang.

1987-01-01

Criticality analysis for dissolvers with neutron poison is given on the basis of Monte Carlo method. In Monte Carlo calculations of thermal neutron group parameters for fuel pieces, neutron transport length is determined in terms of maximum cross section approach. A set of related effective multiplication factors (K eff ) are calculated by Monte Carlo method for the three cases. Related numerical results are quite useful for the design and operation of this kind of dissolver in the criticality safety analysis. (author)

Improvements for Monte Carlo burnup calculation

Energy Technology Data Exchange (ETDEWEB)

Shenglong, Q.; Dong, Y.; Danrong, S.; Wei, L., E-mail: qiangshenglong@tsinghua.org.cn, E-mail: d.yao@npic.ac.cn, E-mail: songdr@npic.ac.cn, E-mail: luwei@npic.ac.cn [Nuclear Power Inst. of China, Cheng Du, Si Chuan (China)

2015-07-01

Monte Carlo burnup calculation is development trend of reactor physics, there would be a lot of work to be done for engineering applications. Based on Monte Carlo burnup code MOI, non-fuel burnup calculation methods and critical search suggestions will be mentioned in this paper. For non-fuel burnup, mixed burnup mode will improve the accuracy of burnup calculation and efficiency. For critical search of control rod position, a new method called ABN based on ABA which used by MC21 will be proposed for the first time in this paper. (author)

Monte Carlo dose distributions for radiosurgery

International Nuclear Information System (INIS)

Perucha, M.; Leal, A.; Rincon, M.; Carrasco, E.

2001-01-01

The precision of Radiosurgery Treatment planning systems is limited by the approximations of their algorithms and by their dosimetrical input data. This fact is especially important in small fields. However, the Monte Carlo methods is an accurate alternative as it considers every aspect of particle transport. In this work an acoustic neurinoma is studied by comparing the dose distribution of both a planning system and Monte Carlo. Relative shifts have been measured and furthermore, Dose-Volume Histograms have been calculated for target and adjacent organs at risk. (orig.)

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.)

Quasi Monte Carlo methods for optimization models of the energy industry with pricing and load processes; Quasi-Monte Carlo Methoden fuer Optimierungsmodelle der Energiewirtschaft mit Preis- und Last-Prozessen

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.

Acceptance and implementation of a system of planning computerized based on Monte Carlo; Aceptacion y puesta en marcha de un sistema de planificacion comutarizada basado en Monte Carlo

Energy Technology Data Exchange (ETDEWEB)

Lopez-Tarjuelo, J.; Garcia-Molla, R.; Suan-Senabre, X. J.; Quiros-Higueras, J. Q.; Santos-Serra, A.; Marco-Blancas, N.; Calzada-Feliu, S.

2013-07-01

It has been done the acceptance for use clinical Monaco computerized planning system, based on an on a virtual model of the energy yield of the head of the linear electron Accelerator and that performs the calculation of the dose with an algorithm of x-rays (XVMC) based on Monte Carlo algorithm. (Author)

BREM5 electroweak Monte Carlo

International Nuclear Information System (INIS)

Kennedy, D.C. II.

1987-01-01

This is an update on the progress of the BREMMUS Monte Carlo simulator, particularly in its current incarnation, BREM5. The present report is intended only as a follow-up to the Mark II/Granlibakken proceedings, and those proceedings should be consulted for a complete description of the capabilities and goals of the BREMMUS program. The new BREM5 program improves on the previous version of BREMMUS, BREM2, in a number of important ways. In BREM2, the internal loop (oblique) corrections were not treated in consistent fashion, a deficiency that led to renormalization scheme-dependence; i.e., physical results, such as cross sections, were dependent on the method used to eliminate infinities from the theory. Of course, this problem cannot be tolerated in a Monte Carlo designed for experimental use. BREM5 incorporates a new way of treating the oblique corrections, as explained in the Granlibakken proceedings, that guarantees renormalization scheme-independence and dramatically simplifies the organization and calculation of radiative corrections. This technique is to be presented in full detail in a forthcoming paper. BREM5 is, at this point, the only Monte Carlo to contain the entire set of one-loop corrections to electroweak four-fermion processes and renormalization scheme-independence. 3 figures

PEPSI: a Monte Carlo generator for polarized leptoproduction

International Nuclear Information System (INIS)

Mankiewicz, L.

1992-01-01

We describe PEPSI (Polarized Electron Proton Scattering Interactions) a Monte Carlo program for the polarized deep inelastic leptoproduction mediated by electromagnetic interaction. The code is a modification of the LEPTO 4.3 Lund Monte Carlo for unpolarized scattering and requires the standard polarization-independent JETSET routines to perform fragmentation into final hadrons. (orig.)

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)

Iterative acceleration methods for Monte Carlo and deterministic criticality calculations

Energy Technology Data Exchange (ETDEWEB)

Urbatsch, T.J.

1995-11-01

If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.

Iterative acceleration methods for Monte Carlo and deterministic criticality calculations

International Nuclear Information System (INIS)

Urbatsch, T.J.

1995-11-01

If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors

Monte Carlo simulation for background study of geophysical inspection with cosmic-ray muons

Science.gov (United States)

Nishiyama, Ryuichi; Taketa, Akimichi; Miyamoto, Seigo; Kasahara, Katsuaki

2016-08-01

Several attempts have been made to obtain a radiographic image inside volcanoes using cosmic-ray muons (muography). Muography is expected to resolve highly heterogeneous density profiles near the surface of volcanoes. However, several prior works have failed to make clear observations due to contamination by background noise. The background contamination leads to an overestimation of the muon flux and consequently a significant underestimation of the density in the target mountains. To investigate the origin of the background noise, we performed a Monte Carlo simulation. The main components of the background noise in muography are found to be low-energy protons, electrons and muons in case of detectors without particle identification and with energy thresholds below 1 GeV. This result was confirmed by comparisons with actual observations of nuclear emulsions. This result will be useful for detector design in future works, and in addition some previous works of muography should be reviewed from the view point of background contamination.

Study on random number generator in Monte Carlo code

International Nuclear Information System (INIS)

Oya, Kentaro; Kitada, Takanori; Tanaka, Shinichi

2011-01-01

The Monte Carlo code uses a sequence of pseudo-random numbers with a random number generator (RNG) to simulate particle histories. A pseudo-random number has its own period depending on its generation method and the period is desired to be long enough not to exceed the period during one Monte Carlo calculation to ensure the correctness especially for a standard deviation of results. The linear congruential generator (LCG) is widely used as Monte Carlo RNG and the period of LCG is not so long by considering the increasing rate of simulation histories in a Monte Carlo calculation according to the remarkable enhancement of computer performance. Recently, many kinds of RNG have been developed and some of their features are better than those of LCG. In this study, we investigate the appropriate RNG in a Monte Carlo code as an alternative to LCG especially for the case of enormous histories. It is found that xorshift has desirable features compared with LCG, and xorshift has a larger period, a comparable speed to generate random numbers, a better randomness, and good applicability to parallel calculation. (author)

The use of Monte-Carlo codes for treatment planning in external-beam radiotherapy

International Nuclear Information System (INIS)

Alan, E.; Nahum, PhD.

2003-01-01

Monte Carlo simulation of radiation transport is a very powerful technique. There are basically no exact solutions to the Boltzmann transport equation. Even, the 'straightforward' situation (in radiotherapy) of an electron beam depth-dose distribution in water proves to be too difficult for analytical methods without making gross approximations such as ignoring energy-loss straggling, large-angle single scattering and Bremsstrahlung production. monte Carlo is essential when radiation is transport from one medium into another. As the particle (be it a neutron, photon, electron, proton) crosses the boundary then a new set of interaction cross-sections is simply read in and the simulation continues as though the new medium were infinite until the next boundary is encountered. Radiotherapy involves directing a beam of megavoltage x rays or electrons (occasionally protons) at a very complex object, the human body. Monte Carlo simulation has proved in valuable at many stages of the process of accurately determining the distribution of absorbed dose in the patient. Some of these applications will be reviewed here. (Rogers and al 1990; Andreo 1991; Mackie 1990). (N.C.)

Monte Carlo simulation experiments on box-type radon dosimeter

International Nuclear Information System (INIS)

Jamil, Khalid; Kamran, Muhammad; Illahi, Ahsan; Manzoor, Shahid

2014-01-01

Epidemiological studies show that inhalation of radon gas ( 222 Rn) may be carcinogenic especially to mine workers, people living in closed indoor energy conserved environments and underground dwellers. It is, therefore, of paramount importance to measure the 222 Rn concentrations (Bq/m 3 ) in indoors environments. For this purpose, box-type passive radon dosimeters employing ion track detector like CR-39 are widely used. Fraction of the number of radon alphas emitted in the volume of the box type dosimeter resulting in latent track formation on CR-39 is the latent track registration efficiency. Latent track registration efficiency is ultimately required to evaluate the radon concentration which consequently determines the effective dose and the radiological hazards. In this research, Monte Carlo simulation experiments were carried out to study the alpha latent track registration efficiency for box type radon dosimeter as a function of dosimeter’s dimensions and range of alpha particles in air. Two different self developed Monte Carlo simulation techniques were employed namely: (a) Surface ratio (SURA) method and (b) Ray hitting (RAHI) method. Monte Carlo simulation experiments revealed that there are two types of efficiencies i.e. intrinsic efficiency (η int ) and alpha hit efficiency (η hit ). The η int depends upon only on the dimensions of the dosimeter and η hit depends both upon dimensions of the dosimeter and range of the alpha particles. The total latent track registration efficiency is the product of both intrinsic and hit efficiencies. It has been concluded that if diagonal length of box type dosimeter is kept smaller than the range of alpha particle then hit efficiency is achieved as 100%. Nevertheless the intrinsic efficiency keeps playing its role. The Monte Carlo simulation experimental results have been found helpful to understand the intricate track registration mechanisms in the box type dosimeter. This paper explains that how radon

Monte Carlo simulation experiments on box-type radon dosimeter

Energy Technology Data Exchange (ETDEWEB)

Jamil, Khalid, E-mail: kjamil@comsats.edu.pk; Kamran, Muhammad; Illahi, Ahsan; Manzoor, Shahid

2014-11-11

Epidemiological studies show that inhalation of radon gas ({sup 222}Rn) may be carcinogenic especially to mine workers, people living in closed indoor energy conserved environments and underground dwellers. It is, therefore, of paramount importance to measure the {sup 222}Rn concentrations (Bq/m{sup 3}) in indoors environments. For this purpose, box-type passive radon dosimeters employing ion track detector like CR-39 are widely used. Fraction of the number of radon alphas emitted in the volume of the box type dosimeter resulting in latent track formation on CR-39 is the latent track registration efficiency. Latent track registration efficiency is ultimately required to evaluate the radon concentration which consequently determines the effective dose and the radiological hazards. In this research, Monte Carlo simulation experiments were carried out to study the alpha latent track registration efficiency for box type radon dosimeter as a function of dosimeter’s dimensions and range of alpha particles in air. Two different self developed Monte Carlo simulation techniques were employed namely: (a) Surface ratio (SURA) method and (b) Ray hitting (RAHI) method. Monte Carlo simulation experiments revealed that there are two types of efficiencies i.e. intrinsic efficiency (η{sub int}) and alpha hit efficiency (η{sub hit}). The η{sub int} depends upon only on the dimensions of the dosimeter and η{sub hit} depends both upon dimensions of the dosimeter and range of the alpha particles. The total latent track registration efficiency is the product of both intrinsic and hit efficiencies. It has been concluded that if diagonal length of box type dosimeter is kept smaller than the range of alpha particle then hit efficiency is achieved as 100%. Nevertheless the intrinsic efficiency keeps playing its role. The Monte Carlo simulation experimental results have been found helpful to understand the intricate track registration mechanisms in the box type dosimeter. This paper

Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z. [Institute of Applied Physics and Computational Mathematics, Beijing, 100094 (China)

2013-07-01

Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

International Nuclear Information System (INIS)

Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.

2013-01-01

Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

Monte Carlo method applied to medical physics

International Nuclear Information System (INIS)

Oliveira, C.; Goncalves, I.F.; Chaves, A.; Lopes, M.C.; Teixeira, N.; Matos, B.; Goncalves, I.C.; Ramalho, A.; Salgado, J.

2000-01-01

The main application of the Monte Carlo method to medical physics is dose calculation. This paper shows some results of two dose calculation studies and two other different applications: optimisation of neutron field for Boron Neutron Capture Therapy and optimization of a filter for a beam tube for several purposes. The time necessary for Monte Carlo calculations - the highest boundary for its intensive utilisation - is being over-passed with faster and cheaper computers. (author)

Simulation of the Interaction of X-rays with a Gas in an Ionization Chamber by the Monte Carlo Method

International Nuclear Information System (INIS)

Grau Carles, A.; Garcia Gomez-Tejedor, G.

2001-01-01

The final objective of any ionization chamber is the measurement of the energy amount or radiation dose absorbed by the gas into the chamber. The final value depends on the composition of the gas, its density and temperature, the ionization chamber geometry, and type and intensity of the radiation. We describe a Monte Carlo simulation method, which allows one to compute the dose absorbed by the gas for a X-ray beam. Verification of model has been carried out by simulating the attenuation of standard X-ray radiation through the half value layers established in the ISO 4037 report, while assuming a Weibull type energy distribution for the incident photons. (Author) 6 refs

A radiating shock evaluated using Implicit Monte Carlo Diffusion

International Nuclear Information System (INIS)

Cleveland, M.; Gentile, N.

2013-01-01

Implicit Monte Carlo [1] (IMC) has been shown to be very expensive when used to evaluate a radiation field in opaque media. Implicit Monte Carlo Diffusion (IMD) [2], which evaluates a spatial discretized diffusion equation using a Monte Carlo algorithm, can be used to reduce the cost of evaluating the radiation field in opaque media [2]. This work couples IMD to the hydrodynamics equations to evaluate opaque diffusive radiating shocks. The Lowrie semi-analytic diffusive radiating shock benchmark[a] is used to verify our implementation of the coupled system of equations. (authors)

The Monte Carlo method the method of statistical trials

CERN Document Server

Shreider, YuA

1966-01-01

The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio

Applicability of quasi-Monte Carlo for lattice systems

International Nuclear Information System (INIS)

Ammon, Andreas; Deutsches Elektronen-Synchrotron; Hartung, Tobias; Jansen, Karl; Leovey, Hernan; Griewank, Andreas; Mueller-Preussker, Michael

2013-11-01

This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over random observations generated from ordinary Monte Carlo simulations scales like N -1/2 , where N is the number of observations. By means of quasi-Monte Carlo methods it is possible to improve this scaling for certain problems to N -1 , or even further if the problems are regular enough. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling of all investigated observables in both cases.

Applicability of quasi-Monte Carlo for lattice systems

Energy Technology Data Exchange (ETDEWEB)

Ammon, Andreas [Berlin Humboldt-Univ. (Germany). Dept. of Physics; Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Hartung, Tobias [King' s College London (United Kingdom). Dept. of Mathematics; Jansen, Karl [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Leovey, Hernan; Griewank, Andreas [Berlin Humboldt-Univ. (Germany). Dept. of Mathematics; Mueller-Preussker, Michael [Berlin Humboldt-Univ. (Germany). Dept. of Physics

2013-11-15

This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over random observations generated from ordinary Monte Carlo simulations scales like N{sup -1/2}, where N is the number of observations. By means of quasi-Monte Carlo methods it is possible to improve this scaling for certain problems to N{sup -1}, or even further if the problems are regular enough. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling of all investigated observables in both cases.

Automated Monte Carlo biasing for photon-generated electrons near surfaces.

Energy Technology Data Exchange (ETDEWEB)

Franke, Brian Claude; Crawford, Martin James; Kensek, Ronald Patrick

2009-09-01

This report describes efforts to automate the biasing of coupled electron-photon Monte Carlo particle transport calculations. The approach was based on weight-windows biasing. Weight-window settings were determined using adjoint-flux Monte Carlo calculations. A variety of algorithms were investigated for adaptivity of the Monte Carlo tallies. Tree data structures were used to investigate spatial partitioning. Functional-expansion tallies were used to investigate higher-order spatial representations.

Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications

CERN Document Server

Kritzer, Peter; Pillichshammer, Friedrich; Winterhof, Arne

2014-01-01

The survey articles in this book focus on number theoretic point constructions, uniform distribution theory, and quasi-Monte Carlo methods. As deterministic versions of the Monte Carlo method, quasi-Monte Carlo rules enjoy increasing popularity, with many fruitful applications in mathematical practice, as for example in finance, computer graphics, and biology.

Clinical implementation of full Monte Carlo dose calculation in proton beam therapy

International Nuclear Information System (INIS)

Paganetti, Harald; Jiang, Hongyu; Parodi, Katia; Slopsema, Roelf; Engelsman, Martijn

2008-01-01

The goal of this work was to facilitate the clinical use of Monte Carlo proton dose calculation to support routine treatment planning and delivery. The Monte Carlo code Geant4 was used to simulate the treatment head setup, including a time-dependent simulation of modulator wheels (for broad beam modulation) and magnetic field settings (for beam scanning). Any patient-field-specific setup can be modeled according to the treatment control system of the facility. The code was benchmarked against phantom measurements. Using a simulation of the ionization chamber reading in the treatment head allows the Monte Carlo dose to be specified in absolute units (Gy per ionization chamber reading). Next, the capability of reading CT data information was implemented into the Monte Carlo code to model patient anatomy. To allow time-efficient dose calculation, the standard Geant4 tracking algorithm was modified. Finally, a software link of the Monte Carlo dose engine to the patient database and the commercial planning system was established to allow data exchange, thus completing the implementation of the proton Monte Carlo dose calculation engine ('DoC++'). Monte Carlo re-calculated plans are a valuable tool to revisit decisions in the planning process. Identification of clinically significant differences between Monte Carlo and pencil-beam-based dose calculations may also drive improvements of current pencil-beam methods. As an example, four patients (29 fields in total) with tumors in the head and neck regions were analyzed. Differences between the pencil-beam algorithm and Monte Carlo were identified in particular near the end of range, both due to dose degradation and overall differences in range prediction due to bony anatomy in the beam path. Further, the Monte Carlo reports dose-to-tissue as compared to dose-to-water by the planning system. Our implementation is tailored to a specific Monte Carlo code and the treatment planning system XiO (Computerized Medical Systems Inc

Exponential convergence on a continuous Monte Carlo transport problem

International Nuclear Information System (INIS)

Booth, T.E.

1997-01-01

For more than a decade, it has been known that exponential convergence on discrete transport problems was possible using adaptive Monte Carlo techniques. An adaptive Monte Carlo method that empirically produces exponential convergence on a simple continuous transport problem is described

Monte Carlo semi-empirical model for Si(Li) x-ray detector: Differences between nominal and fitted parameters

Energy Technology Data Exchange (ETDEWEB)

Lopez-Pino, N.; Padilla-Cabal, F.; Garcia-Alvarez, J. A.; Vazquez, L.; D' Alessandro, K.; Correa-Alfonso, C. M. [Departamento de Fisica Nuclear, Instituto Superior de Tecnologia y Ciencias Aplicadas (InSTEC) Ave. Salvador Allende y Luaces. Quinta de los Molinos. Habana 10600. A.P. 6163, La Habana (Cuba); Godoy, W.; Maidana, N. L.; Vanin, V. R. [Laboratorio do Acelerador Linear, Instituto de Fisica - Universidade de Sao Paulo Rua do Matao, Travessa R, 187, 05508-900, SP (Brazil)

2013-05-06

A detailed characterization of a X-ray Si(Li) detector was performed to obtain the energy dependence of efficiency in the photon energy range of 6.4 - 59.5 keV, which was measured and reproduced by Monte Carlo (MC) simulations. Significant discrepancies between MC and experimental values were found when the manufacturer parameters of the detector were used in the simulation. A complete Computerized Tomography (CT) detector scan allowed to find the correct crystal dimensions and position inside the capsule. The computed efficiencies with the resulting detector model differed with the measured values no more than 10% in most of the energy range.

Isotopic depletion with Monte Carlo

International Nuclear Information System (INIS)

Martin, W.R.; Rathkopf, J.A.

1996-06-01

This work considers a method to deplete isotopes during a time- dependent Monte Carlo simulation of an evolving system. The method is based on explicitly combining a conventional estimator for the scalar flux with the analytical solutions to the isotopic depletion equations. There are no auxiliary calculations; the method is an integral part of the Monte Carlo calculation. The method eliminates negative densities and reduces the variance in the estimates for the isotope densities, compared to existing methods. Moreover, existing methods are shown to be special cases of the general method described in this work, as they can be derived by combining a high variance estimator for the scalar flux with a low-order approximation to the analytical solution to the depletion equation

Multilevel sequential Monte-Carlo samplers

KAUST Repository

Jasra, Ajay

2016-01-01

Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

Multilevel sequential Monte-Carlo samplers

KAUST Repository

Jasra, Ajay

2016-01-05

Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

A flexible coupling scheme for Monte Carlo and thermal-hydraulics codes

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J. Eduard, E-mail: J.E.Hoogenboom@tudelft.nl [Delft University of Technology (Netherlands); Ivanov, Aleksandar; Sanchez, Victor, E-mail: Aleksandar.Ivanov@kit.edu, E-mail: Victor.Sanchez@kit.edu [Karlsruhe Institute of Technology, Institute of Neutron Physics and Reactor Technology, Eggenstein-Leopoldshafen (Germany); Diop, Cheikh, E-mail: Cheikh.Diop@cea.fr [CEA/DEN/DANS/DM2S/SERMA, Commissariat a l' Energie Atomique, Gif-sur-Yvette (France)

2011-07-01

A coupling scheme between a Monte Carlo code and a thermal-hydraulics code is being developed within the European NURISP project for comprehensive and validated reactor analysis. The scheme is flexible as it allows different Monte Carlo codes and different thermal-hydraulics codes to be used. At present the MCNP and TRIPOLI4 Monte Carlo codes can be used and the FLICA4 and SubChanFlow thermal-hydraulics codes. For all these codes only an original executable is necessary. A Python script drives the iterations between Monte Carlo and thermal-hydraulics calculations. It also calls a conversion program to merge a master input file for the Monte Carlo code with the appropriate temperature and coolant density data from the thermal-hydraulics calculation. Likewise it calls another conversion program to merge a master input file for the thermal-hydraulics code with the power distribution data from the Monte Carlo calculation. Special attention is given to the neutron cross section data for the various required temperatures in the Monte Carlo calculation. Results are shown for an infinite lattice of PWR fuel pin cells and a 3 x 3 fuel BWR pin cell cluster. Various possibilities for further improvement and optimization of the coupling system are discussed. (author)

A flexible coupling scheme for Monte Carlo and thermal-hydraulics codes

International Nuclear Information System (INIS)

Hoogenboom, J. Eduard; Ivanov, Aleksandar; Sanchez, Victor; Diop, Cheikh

2011-01-01

A coupling scheme between a Monte Carlo code and a thermal-hydraulics code is being developed within the European NURISP project for comprehensive and validated reactor analysis. The scheme is flexible as it allows different Monte Carlo codes and different thermal-hydraulics codes to be used. At present the MCNP and TRIPOLI4 Monte Carlo codes can be used and the FLICA4 and SubChanFlow thermal-hydraulics codes. For all these codes only an original executable is necessary. A Python script drives the iterations between Monte Carlo and thermal-hydraulics calculations. It also calls a conversion program to merge a master input file for the Monte Carlo code with the appropriate temperature and coolant density data from the thermal-hydraulics calculation. Likewise it calls another conversion program to merge a master input file for the thermal-hydraulics code with the power distribution data from the Monte Carlo calculation. Special attention is given to the neutron cross section data for the various required temperatures in the Monte Carlo calculation. Results are shown for an infinite lattice of PWR fuel pin cells and a 3 x 3 fuel BWR pin cell cluster. Various possibilities for further improvement and optimization of the coupling system are discussed. (author)

Calculation of organ doses from environmental gamma rays using human phantoms and Monte Carlo methods. Pt. 1

International Nuclear Information System (INIS)

Saito, K.; Petoussi, N.; Zankl, M.; Veit, R.; Jacob, P.; Drexler, G.

1990-01-01

Organ doses from environmental γ-rays (U-238, Th-232, K-40) were calculated using Monte Carlo methods for three typical sources of a semi-infinite volume source in the air, an infinite plane source in the ground and a volume source in the ground. γ-ray fields in the natural environment were simulated rigourously without approximations or simplifications in the intermediate steps except for the disturbance of the radiation field by the human body which was neglected. Organ doses were calculated for four anthropomorphic phantoms representing a baby, a child, a female and a male adult. The dose of a fetus is given by the dose to the uterus of the adult female. Air kerma and dose conversion factors normalised to air kerma and to source intensity are given for monoenergetic sources and for the natural radionuclides. (orig./HP)

Parallel MCNP Monte Carlo transport calculations with MPI

International Nuclear Information System (INIS)

Wagner, J.C.; Haghighat, A.

1996-01-01

The steady increase in computational performance has made Monte Carlo calculations for large/complex systems possible. However, in order to make these calculations practical, order of magnitude increases in performance are necessary. The Monte Carlo method is inherently parallel (particles are simulated independently) and thus has the potential for near-linear speedup with respect to the number of processors. Further, the ever-increasing accessibility of parallel computers, such as workstation clusters, facilitates the practical use of parallel Monte Carlo. Recognizing the nature of the Monte Carlo method and the trends in available computing, the code developers at Los Alamos National Laboratory implemented the message-passing general-purpose Monte Carlo radiation transport code MCNP (version 4A). The PVM package was chosen by the MCNP code developers because it supports a variety of communication networks, several UNIX platforms, and heterogeneous computer systems. This PVM version of MCNP has been shown to produce speedups that approach the number of processors and thus, is a very useful tool for transport analysis. Due to software incompatibilities on the local IBM SP2, PVM has not been available, and thus it is not possible to take advantage of this useful tool. Hence, it became necessary to implement an alternative message-passing library package into MCNP. Because the message-passing interface (MPI) is supported on the local system, takes advantage of the high-speed communication switches in the SP2, and is considered to be the emerging standard, it was selected

Monte Carlo systems used for treatment planning and dose verification

Energy Technology Data Exchange (ETDEWEB)

Brualla, Lorenzo [Universitaetsklinikum Essen, NCTeam, Strahlenklinik, Essen (Germany); Rodriguez, Miguel [Centro Medico Paitilla, Balboa (Panama); Lallena, Antonio M. [Universidad de Granada, Departamento de Fisica Atomica, Molecular y Nuclear, Granada (Spain)

2017-04-15

General-purpose radiation transport Monte Carlo codes have been used for estimation of the absorbed dose distribution in external photon and electron beam radiotherapy patients since several decades. Results obtained with these codes are usually more accurate than those provided by treatment planning systems based on non-stochastic methods. Traditionally, absorbed dose computations based on general-purpose Monte Carlo codes have been used only for research, owing to the difficulties associated with setting up a simulation and the long computation time required. To take advantage of radiation transport Monte Carlo codes applied to routine clinical practice, researchers and private companies have developed treatment planning and dose verification systems that are partly or fully based on fast Monte Carlo algorithms. This review presents a comprehensive list of the currently existing Monte Carlo systems that can be used to calculate or verify an external photon and electron beam radiotherapy treatment plan. Particular attention is given to those systems that are distributed, either freely or commercially, and that do not require programming tasks from the end user. These systems are compared in terms of features and the simulation time required to compute a set of benchmark calculations. (orig.) [German] Seit mehreren Jahrzehnten werden allgemein anwendbare Monte-Carlo-Codes zur Simulation des Strahlungstransports benutzt, um die Verteilung der absorbierten Dosis in der perkutanen Strahlentherapie mit Photonen und Elektronen zu evaluieren. Die damit erzielten Ergebnisse sind meist akkurater als solche, die mit nichtstochastischen Methoden herkoemmlicher Bestrahlungsplanungssysteme erzielt werden koennen. Wegen des damit verbundenen Arbeitsaufwands und der langen Dauer der Berechnungen wurden Monte-Carlo-Simulationen von Dosisverteilungen in der konventionellen Strahlentherapie in der Vergangenheit im Wesentlichen in der Forschung eingesetzt. Im Bemuehen, Monte-Carlo

Multilevel Monte Carlo in Approximate Bayesian Computation

KAUST Repository

Jasra, Ajay

2017-02-13

In the following article we consider approximate Bayesian computation (ABC) inference. We introduce a method for numerically approximating ABC posteriors using the multilevel Monte Carlo (MLMC). A sequential Monte Carlo version of the approach is developed and it is shown under some assumptions that for a given level of mean square error, this method for ABC has a lower cost than i.i.d. sampling from the most accurate ABC approximation. Several numerical examples are given.

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.)

A residual Monte Carlo method for discrete thermal radiative diffusion

International Nuclear Information System (INIS)

Evans, T.M.; Urbatsch, T.J.; Lichtenstein, H.; Morel, J.E.

2003-01-01

Residual Monte Carlo methods reduce statistical error at a rate of exp(-bN), where b is a positive constant and N is the number of particle histories. Contrast this convergence rate with 1/√N, which is the rate of statistical error reduction for conventional Monte Carlo methods. Thus, residual Monte Carlo methods hold great promise for increased efficiency relative to conventional Monte Carlo methods. Previous research has shown that the application of residual Monte Carlo methods to the solution of continuum equations, such as the radiation transport equation, is problematic for all but the simplest of cases. However, the residual method readily applies to discrete systems as long as those systems are monotone, i.e., they produce positive solutions given positive sources. We develop a residual Monte Carlo method for solving a discrete 1D non-linear thermal radiative equilibrium diffusion equation, and we compare its performance with that of the discrete conventional Monte Carlo method upon which it is based. We find that the residual method provides efficiency gains of many orders of magnitude. Part of the residual gain is due to the fact that we begin each timestep with an initial guess equal to the solution from the previous timestep. Moreover, fully consistent non-linear solutions can be obtained in a reasonable amount of time because of the effective lack of statistical noise. We conclude that the residual approach has great potential and that further research into such methods should be pursued for more general discrete and continuum systems

Contributon Monte Carlo

International Nuclear Information System (INIS)

Dubi, A.; Gerstl, S.A.W.

1979-05-01

The contributon Monte Carlo method is based on a new recipe to calculate target responses by means of volume integral of the contributon current in a region between the source and the detector. A comprehensive description of the method, its implementation in the general-purpose MCNP code, and results of the method for realistic nonhomogeneous, energy-dependent problems are presented. 23 figures, 10 tables

Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities

KAUST Repository

Cheon, Sooyoung

2013-02-16

Importance sampling and Markov chain Monte Carlo methods have been used in exact inference for contingency tables for a long time, however, their performances are not always very satisfactory. In this paper, we propose a stochastic approximation Monte Carlo importance sampling (SAMCIS) method for tackling this problem. SAMCIS is a combination of adaptive Markov chain Monte Carlo and importance sampling, which employs the stochastic approximation Monte Carlo algorithm (Liang et al., J. Am. Stat. Assoc., 102(477):305-320, 2007) to draw samples from an enlarged reference set with a known Markov basis. Compared to the existing importance sampling and Markov chain Monte Carlo methods, SAMCIS has a few advantages, such as fast convergence, ergodicity, and the ability to achieve a desired proportion of valid tables. The numerical results indicate that SAMCIS can outperform the existing importance sampling and Markov chain Monte Carlo methods: It can produce much more accurate estimates in much shorter CPU time than the existing methods, especially for the tables with high degrees of freedom. © 2013 Springer Science+Business Media New York.

Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities

KAUST Repository

Cheon, Sooyoung; Liang, Faming; Chen, Yuguo; Yu, Kai

2013-01-01

Importance sampling and Markov chain Monte Carlo methods have been used in exact inference for contingency tables for a long time, however, their performances are not always very satisfactory. In this paper, we propose a stochastic approximation Monte Carlo importance sampling (SAMCIS) method for tackling this problem. SAMCIS is a combination of adaptive Markov chain Monte Carlo and importance sampling, which employs the stochastic approximation Monte Carlo algorithm (Liang et al., J. Am. Stat. Assoc., 102(477):305-320, 2007) to draw samples from an enlarged reference set with a known Markov basis. Compared to the existing importance sampling and Markov chain Monte Carlo methods, SAMCIS has a few advantages, such as fast convergence, ergodicity, and the ability to achieve a desired proportion of valid tables. The numerical results indicate that SAMCIS can outperform the existing importance sampling and Markov chain Monte Carlo methods: It can produce much more accurate estimates in much shorter CPU time than the existing methods, especially for the tables with high degrees of freedom. © 2013 Springer Science+Business Media New York.

Bayesian Monte Carlo method

International Nuclear Information System (INIS)

Rajabalinejad, M.

2010-01-01

To reduce cost of Monte Carlo (MC) simulations for time-consuming processes, Bayesian Monte Carlo (BMC) is introduced in this paper. The BMC method reduces number of realizations in MC according to the desired accuracy level. BMC also provides a possibility of considering more priors. In other words, different priors can be integrated into one model by using BMC to further reduce cost of simulations. This study suggests speeding up the simulation process by considering the logical dependence of neighboring points as prior information. This information is used in the BMC method to produce a predictive tool through the simulation process. The general methodology and algorithm of BMC method are presented in this paper. The BMC method is applied to the simplified break water model as well as the finite element model of 17th Street Canal in New Orleans, and the results are compared with the MC and Dynamic Bounds methods.

SU-E-J-60: Efficient Monte Carlo Dose Calculation On CPU-GPU Heterogeneous Systems

Energy Technology Data Exchange (ETDEWEB)

Xiao, K; Chen, D. Z; Hu, X. S [University of Notre Dame, Notre Dame, IN (United States); Zhou, B [Altera Corp., San Jose, CA (United States)

2014-06-01

Purpose: It is well-known that the performance of GPU-based Monte Carlo dose calculation implementations is bounded by memory bandwidth. One major cause of this bottleneck is the random memory writing patterns in dose deposition, which leads to several memory efficiency issues on GPU such as un-coalesced writing and atomic operations. We propose a new method to alleviate such issues on CPU-GPU heterogeneous systems, which achieves overall performance improvement for Monte Carlo dose calculation. Methods: Dose deposition is to accumulate dose into the voxels of a dose volume along the trajectories of radiation rays. Our idea is to partition this procedure into the following three steps, which are fine-tuned for CPU or GPU: (1) each GPU thread writes dose results with location information to a buffer on GPU memory, which achieves fully-coalesced and atomic-free memory transactions; (2) the dose results in the buffer are transferred to CPU memory; (3) the dose volume is constructed from the dose buffer on CPU. We organize the processing of all radiation rays into streams. Since the steps within a stream use different hardware resources (i.e., GPU, DMA, CPU), we can overlap the execution of these steps for different streams by pipelining. Results: We evaluated our method using a Monte Carlo Convolution Superposition (MCCS) program and tested our implementation for various clinical cases on a heterogeneous system containing an Intel i7 quad-core CPU and an NVIDIA TITAN GPU. Comparing with a straightforward MCCS implementation on the same system (using both CPU and GPU for radiation ray tracing), our method gained 2-5X speedup without losing dose calculation accuracy. Conclusion: The results show that our new method improves the effective memory bandwidth and overall performance for MCCS on the CPU-GPU systems. Our proposed method can also be applied to accelerate other Monte Carlo dose calculation approaches. This research was supported in part by NSF under Grants CCF

Combined FDTD-Monte Carlo analysis and a novel design for ZnO scintillator rods in polycarbonate membrane for X-ray imaging

International Nuclear Information System (INIS)

Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar; Mohammadi, Mohammad

2017-01-01

A combination of Finite Difference Time Domain (FDTD) and Monte Carlo (MC) methods is proposed for simulation and analysis of ZnO microscintillators grown in polycarbonate membrane. A planar 10 keV X-ray source irradiating the detector is simulated by MC method, which provides the amount of absorbed X-ray energy in the assembly. The transport of generated UV scintillation light and its propagation in the detector was studied by the FDTD method. Detector responses to different probable scintillation sites and under different energies of X-ray source from 10 to 25 keV are reported. Finally, the tapered geometry for the scintillators is proposed, which shows enhanced spatial resolution in comparison to cylindrical geometry for imaging applications.

Combined FDTD-Monte Carlo analysis and a novel design for ZnO scintillator rods in polycarbonate membrane for X-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Mohammadian-Behbahani, Mohammad-Reza [Department of Energy Engineering and Physics, Amir-Kabir University of Technology (Tehran Polytechnic), Tehran (Iran, Islamic Republic of); School of Particles and Accelerators, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Saramad, Shahyar, E-mail: ssaramad@aut.ac.ir [Department of Energy Engineering and Physics, Amir-Kabir University of Technology (Tehran Polytechnic), Tehran (Iran, Islamic Republic of); School of Particles and Accelerators, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Mohammadi, Mohammad [Department of Electrical Engineering, Amir-Kabir University of Technology (Tehran Polytechnic), Tehran (Iran, Islamic Republic of); School of Particles and Accelerators, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of)

2017-05-01

A combination of Finite Difference Time Domain (FDTD) and Monte Carlo (MC) methods is proposed for simulation and analysis of ZnO microscintillators grown in polycarbonate membrane. A planar 10 keV X-ray source irradiating the detector is simulated by MC method, which provides the amount of absorbed X-ray energy in the assembly. The transport of generated UV scintillation light and its propagation in the detector was studied by the FDTD method. Detector responses to different probable scintillation sites and under different energies of X-ray source from 10 to 25 keV are reported. Finally, the tapered geometry for the scintillators is proposed, which shows enhanced spatial resolution in comparison to cylindrical geometry for imaging applications.

Closed-shell variational quantum Monte Carlo simulation for the ...

African Journals Online (AJOL)

Closed-shell variational quantum Monte Carlo simulation for the electric dipole moment calculation of hydrazine molecule using casino-code. ... Nigeria Journal of Pure and Applied Physics ... The variational quantum Monte Carlo (VQMC) technique used in this work employed the restricted Hartree-Fock (RHF) scheme.

New Approaches and Applications for Monte Carlo Perturbation Theory

Energy Technology Data Exchange (ETDEWEB)

Aufiero, Manuele; Bidaud, Adrien; Kotlyar, Dan; Leppänen, Jaakko; Palmiotti, Giuseppe; Salvatores, Massimo; Sen, Sonat; Shwageraus, Eugene; Fratoni, Massimiliano

2017-02-01

This paper presents some of the recent and new advancements in the extension of Monte Carlo Perturbation Theory methodologies and application. In particular, the discussed problems involve Brunup calculation, perturbation calculation based on continuous energy functions, and Monte Carlo Perturbation Theory in loosely coupled systems.

Recommender engine for continuous-time quantum Monte Carlo methods

Science.gov (United States)

Huang, Li; Yang, Yi-feng; Wang, Lei

2017-03-01

Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.

Rapid Monte Carlo Simulation of Gravitational Wave Galaxies

Science.gov (United States)

Breivik, Katelyn; Larson, Shane L.

2015-01-01

With the detection of gravitational waves on the horizon, astrophysical catalogs produced by gravitational wave observatories can be used to characterize the populations of sources and validate different galactic population models. Efforts to simulate gravitational wave catalogs and source populations generally focus on population synthesis models that require extensive time and computational power to produce a single simulated galaxy. Monte Carlo simulations of gravitational wave source populations can also be used to generate observation catalogs from the gravitational wave source population. Monte Carlo simulations have the advantes of flexibility and speed, enabling rapid galactic realizations as a function of galactic binary parameters with less time and compuational resources required. We present a Monte Carlo method for rapid galactic simulations of gravitational wave binary populations.

Characterization of a CLYC detector and validation of the Monte Carlo Simulation by measurement experiments

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyun Suk; Ye, Sung Joon [Seoul National University, Seoul (Korea, Republic of); Smith, Martin B.; Koslowsky, Martin R. [Bubble Technology Industries Inc., Chalk River (Canada); Kwak, Sung Woo [Korea Institute of Nuclear Nonproliferation And Control (KINAC), Daejeon (Korea, Republic of); Kim Gee Hyun [Sejong University, Seoul (Korea, Republic of)

2017-03-15

Simultaneous detection of neutrons and gamma rays have become much more practicable, by taking advantage of good gamma-ray discrimination properties using pulse shape discrimination (PSD) technique. Recently, we introduced a commercial CLYC system in Korea, and performed an initial characterization and simulation studies for the CLYC detector system to provide references for the future implementation of the dual-mode scintillator system in various studies and applications. We evaluated a CLYC detector with 95% 6Li enrichment using various gamma-ray sources and a 252Cf neutron source, with validation of our Monte Carlo simulation results via measurement experiments. Absolute full-energy peak efficiency values were calculated for gamma-ray sources and neutron source using MCNP6 and compared with measurement experiments of the calibration sources. In addition, behavioral characteristics of neutrons were validated by comparing simulations and experiments on neutron moderation with various polyethylene (PE) moderator thicknesses. Both results showed good agreements in overall characteristics of the gamma and neutron detection efficiencies, with consistent ⁓20% discrepancy. Furthermore, moderation of neutrons emitted from {sup 252}Cf showed similarities between the simulation and the experiment, in terms of their relative ratios depending on the thickness of the PE moderator. A CLYC detector system was characterized for its energy resolution and detection efficiency, and Monte Carlo simulations on the detector system was validated experimentally. Validation of the simulation results in overall trend of the CLYC detector behavior will provide the fundamental basis and validity of follow-up Monte Carlo simulation studies for the development of our dual-particle imager using a rotational modulation collimator.

Acceleration of monte Carlo solution by conjugate gradient method

International Nuclear Information System (INIS)

Toshihisa, Yamamoto

2005-01-01

The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)

Monte Carlo study of neutrino acceleration in supernova shocks

International Nuclear Information System (INIS)

Kazanas, Demosthenes; Ellison, D.C.; National Aeronautics and Space Administration, Greenbelt, MD

1981-01-01

The first order Fermi acceleration mechanism of cosmic rays in shocks may be at work for neutrinos in supernova shocks when the latter are at densities rho>10 13 g cm -3 at which the core material is opaque to neutrinos. A Monte Carlo approach to study this effect is employed and the emerging neutrino power law spectra are presented. The increased energy acquired by the neutrinos may facilitate their detection in supernova explosions and provide information about the physics of collapse

PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO

Directory of Open Access Journals (Sweden)

WAYAN ARTHINI

2012-09-01

Full Text Available Value at Risk (VaR is the maximum potential loss on a portfolio based on the probability at a certain time.  In this research, portfolio VaR values calculated from historical data and Monte Carlo simulation data. Historical data is processed so as to obtain stock returns, variance, correlation coefficient, and variance-covariance matrix, then the method of Markowitz sought proportion of each stock fund, and portfolio risk and return portfolio. The data was then simulated by Monte Carlo simulation, Exact Monte Carlo Simulation and Expected Monte Carlo Simulation. Exact Monte Carlo simulation have same returns and standard deviation  with historical data, while the Expected Monte Carlo Simulation satistic calculation similar to historical data. The results of this research is the portfolio VaR  with time horizon T=1, T=10, T=22 and the confidence level of 95 %, values obtained VaR between historical data and Monte Carlo simulation data with the method exact and expected. Value of VaR from both Monte Carlo simulation is greater than VaR historical data.

DXRaySMCS: a user-friendly interface developed for prediction of diagnostic radiology X-ray spectra produced by Monte Carlo (MCNP-4C) simulation.

Science.gov (United States)

Bahreyni Toossi, M T; Moradi, H; Zare, H

2008-01-01

In this work, the general purpose Monte Carlo N-particle radiation transport computer code (MCNP-4C) was used for the simulation of X-ray spectra in diagnostic radiology. The electron's path in the target was followed until its energy was reduced to 10 keV. A user-friendly interface named 'diagnostic X-ray spectra by Monte Carlo simulation (DXRaySMCS)' was developed to facilitate the application of MCNP-4C code for diagnostic radiology spectrum prediction. The program provides a user-friendly interface for: (i) modifying the MCNP input file, (ii) launching the MCNP program to simulate electron and photon transport and (iii) processing the MCNP output file to yield a summary of the results (relative photon number per energy bin). In this article, the development and characteristics of DXRaySMCS are outlined. As part of the validation process, output spectra for 46 diagnostic radiology system settings produced by DXRaySMCS were compared with the corresponding IPEM78. Generally, there is a good agreement between the two sets of spectra. No statistically significant differences have been observed between IPEM78 reported spectra and the simulated spectra generated in this study.

Monte Carlo methods for the reliability analysis of Markov systems

International Nuclear Information System (INIS)

Buslik, A.J.

1985-01-01

This paper presents Monte Carlo methods for the reliability analysis of Markov systems. Markov models are useful in treating dependencies between components. The present paper shows how the adjoint Monte Carlo method for the continuous time Markov process can be derived from the method for the discrete-time Markov process by a limiting process. The straightforward extensions to the treatment of mean unavailability (over a time interval) are given. System unavailabilities can also be estimated; this is done by making the system failed states absorbing, and not permitting repair from them. A forward Monte Carlo method is presented in which the weighting functions are related to the adjoint function. In particular, if the exact adjoint function is known then weighting factors can be constructed such that the exact answer can be obtained with a single Monte Carlo trial. Of course, if the exact adjoint function is known, there is no need to perform the Monte Carlo calculation. However, the formulation is useful since it gives insight into choices of the weight factors which will reduce the variance of the estimator

A general transform for variance reduction in Monte Carlo simulations

International Nuclear Information System (INIS)

Becker, T.L.; Larsen, E.W.

2011-01-01

This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)

Monte Carlo simulation of photon buildup factors for shielding materials in diagnostic x-ray facilities

International Nuclear Information System (INIS)

Kharrati, Hedi; Agrebi, Amel; Karoui, Mohamed Karim

2012-01-01

Purpose: A simulation of buildup factors for ordinary concrete, steel, lead, plate glass, lead glass, and gypsum wallboard in broad beam geometry for photons energies from 10 keV to 150 keV at 5 keV intervals is presented. Methods: Monte Carlo N-particle radiation transport computer code has been used to determine the buildup factors for the studied shielding materials. Results: An example concretizing the use of the obtained buildup factors data in computing the broad beam transmission for tube potentials at 70, 100, 120, and 140 kVp is given. The half value layer, the tenth value layer, and the equilibrium tenth value layer are calculated from the broad beam transmission for these tube potentials. Conclusions: The obtained values compared with those calculated from the published data show the ability of these data to predict shielding transmission curves. Therefore, the buildup factors data can be combined with primary, scatter, and leakage x-ray spectra to provide a computationally based solution to broad beam transmission for barriers in shielding x-ray facilities.

Monte Carlo simulation of photon buildup factors for shielding materials in diagnostic x-ray facilities.

Science.gov (United States)

Kharrati, Hedi; Agrebi, Amel; Karoui, Mohamed Karim

2012-10-01

A simulation of buildup factors for ordinary concrete, steel, lead, plate glass, lead glass, and gypsum wallboard in broad beam geometry for photons energies from 10 keV to 150 keV at 5 keV intervals is presented. Monte Carlo N-particle radiation transport computer code has been used to determine the buildup factors for the studied shielding materials. An example concretizing the use of the obtained buildup factors data in computing the broad beam transmission for tube potentials at 70, 100, 120, and 140 kVp is given. The half value layer, the tenth value layer, and the equilibrium tenth value layer are calculated from the broad beam transmission for these tube potentials. The obtained values compared with those calculated from the published data show the ability of these data to predict shielding transmission curves. Therefore, the buildup factors data can be combined with primary, scatter, and leakage x-ray spectra to provide a computationally based solution to broad beam transmission for barriers in shielding x-ray facilities.

A Monte Carlo approach to combating delayed completion of ...

African Journals Online (AJOL)

The objective of this paper is to unveil the relevance of Monte Carlo critical path analysis in resolving problem of delays in scheduled completion of development projects. Commencing with deterministic network scheduling, Monte Carlo critical path analysis was advanced by assigning probability distributions to task times.

Perturbation based Monte Carlo criticality search in density, enrichment and concentration

International Nuclear Information System (INIS)

Li, Zeguang; Wang, Kan; Deng, Jingkang

2015-01-01

Highlights: • A new perturbation based Monte Carlo criticality search method is proposed. • The method could get accurate results with only one individual criticality run. • The method is used to solve density, enrichment and concentration search problems. • Results show the feasibility and good performances of this method. • The relationship between results’ accuracy and perturbation order is discussed. - Abstract: Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Existing Monte Carlo criticality search methods need large amount of individual criticality runs and may have unstable results because of the uncertainties of criticality results. In this paper, a new perturbation based Monte Carlo criticality search method is proposed and discussed. This method only needs one individual criticality calculation with perturbation tallies to estimate k eff changing function using initial k eff and differential coefficients results, and solves polynomial equations to get the criticality search results. The new perturbation based Monte Carlo criticality search method is implemented in the Monte Carlo code RMC, and criticality search problems in density, enrichment and concentration are taken out. Results show that this method is quite inspiring in accuracy and efficiency, and has advantages compared with other criticality search methods

SU-F-T-619: Dose Evaluation of Specific Patient Plans Based On Monte Carlo Algorithm for a CyberKnife Stereotactic Radiosurgery System

Energy Technology Data Exchange (ETDEWEB)

Piao, J [PLA General Hospital, Beijing (China); PLA 302 Hospital, Beijing (China); Xu, S [PLA General Hospital, Beijing (China); Tsinghua University, Beijing (China); Wu, Z; Liu, Y [Tsinghua University, Beijing (China); Li, Y [Beihang University, Beijing (China); Qu, B [PLA General Hospital, Beijing (China); Duan, X [PLA 302 Hospital, Beijing (China)

2016-06-15

Purpose: This study will use Monte Carlo to simulate the Cyberknife system, and intend to develop the third-party tool to evaluate the dose verification of specific patient plans in TPS. Methods: By simulating the treatment head using the BEAMnrc and DOSXYZnrc software, the comparison between the calculated and measured data will be done to determine the beam parameters. The dose distribution calculated in the Raytracing, Monte Carlo algorithms of TPS (Multiplan Ver4.0.2) and in-house Monte Carlo simulation method for 30 patient plans, which included 10 head, lung and liver cases in each, were analyzed. The γ analysis with the combined 3mm/3% criteria would be introduced to quantitatively evaluate the difference of the accuracy between three algorithms. Results: More than 90% of the global error points were less than 2% for the comparison of the PDD and OAR curves after determining the mean energy and FWHM.The relative ideal Monte Carlo beam model had been established. Based on the quantitative evaluation of dose accuracy for three algorithms, the results of γ analysis shows that the passing rates (84.88±9.67% for head,98.83±1.05% for liver,98.26±1.87% for lung) of PTV in 30 plans between Monte Carlo simulation and TPS Monte Carlo algorithms were good. And the passing rates (95.93±3.12%,99.84±0.33% in each) of PTV in head and liver plans between Monte Carlo simulation and TPS Ray-tracing algorithms were also good. But the difference of DVHs in lung plans between Monte Carlo simulation and Ray-tracing algorithms was obvious, and the passing rate (51.263±38.964%) of γ criteria was not good. It is feasible that Monte Carlo simulation was used for verifying the dose distribution of patient plans. Conclusion: Monte Carlo simulation algorithm developed in the CyberKnife system of this study can be used as a reference tool for the third-party tool, which plays an important role in dose verification of patient plans. This work was supported in part by the grant

Monte Carlo numerical study of lattice field theories

International Nuclear Information System (INIS)

Gan Cheekwan; Kim Seyong; Ohta, Shigemi

1997-01-01

The authors are interested in the exact first-principle calculations of quantum field theories which are indeed exact ones. For quantum chromodynamics (QCD) at low energy scale, a nonperturbation method is needed, and the only known such method is the lattice method. The path integral can be evaluated by putting a system on a finite 4-dimensional volume and discretizing space time continuum into finite points, lattice. The continuum limit is taken by making the lattice infinitely fine. For evaluating such a finite-dimensional integral, the Monte Carlo numerical estimation of the path integral can be obtained. The calculation of light hadron mass in quenched lattice QCD with staggered quarks, 3-dimensional Thirring model calculation and the development of self-test Monte Carlo method have been carried out by using the RIKEN supercomputer. The motivation of this study, lattice QCD formulation, continuum limit, Monte Carlo update, hadron propagator, light hadron mass, auto-correlation and source size dependence are described on lattice QCD. The phase structure of the 3-dimensional Thirring model for a small 8 3 lattice has been mapped. The discussion on self-test Monte Carlo method is described again. (K.I.)

Continuous energy Monte Carlo method based lattice homogeinzation

International Nuclear Information System (INIS)

Li Mancang; Yao Dong; Wang Kan

2014-01-01

Based on the Monte Carlo code MCNP, the continuous energy Monte Carlo multi-group constants generation code MCMC has been developed. The track length scheme has been used as the foundation of cross section generation. The scattering matrix and Legendre components require special techniques, and the scattering event method has been proposed to solve this problem. Three methods have been developed to calculate the diffusion coefficients for diffusion reactor core codes and the Legendre method has been applied in MCMC. To the satisfaction of the equivalence theory, the general equivalence theory (GET) and the superhomogenization method (SPH) have been applied to the Monte Carlo method based group constants. The super equivalence method (SPE) has been proposed to improve the equivalence. GET, SPH and SPE have been implemented into MCMC. The numerical results showed that generating the homogenization multi-group constants via Monte Carlo method overcomes the difficulties in geometry and treats energy in continuum, thus provides more accuracy parameters. Besides, the same code and data library can be used for a wide range of applications due to the versatility. The MCMC scheme can be seen as a potential alternative to the widely used deterministic lattice codes. (authors)

PENENTUAN HARGA OPSI BELI TIPE ASIA DENGAN METODE MONTE CARLO-CONTROL VARIATE

Directory of Open Access Journals (Sweden)

NI NYOMAN AYU ARTANADI

2017-01-01

Full Text Available Option is a contract between the writer and the holder which entitles the holder to buy or sell an underlying asset at the maturity date for a specified price known as an exercise price. Asian option is a type of financial derivatives which the payoff taking the average value over the time series of the asset price. The aim of the study is to present the Monte Carlo-Control Variate as an extension of Standard Monte Carlo applied on the calculation of the Asian option price. Standard Monte Carlo simulations 10.000.000 generate standard error 0.06 and the option price convergent at Rp.160.00 while Monte Carlo-Control Variate simulations 100.000 generate standard error 0.01 and the option price convergent at Rp.152.00. This shows the Monte Carlo-Control Variate achieve faster option price toward convergent of the Monte Carlo Standar.

Implications of Monte Carlo Statistical Errors in Criticality Safety Assessments

International Nuclear Information System (INIS)

Pevey, Ronald E.

2005-01-01

Most criticality safety calculations are performed using Monte Carlo techniques because of Monte Carlo's ability to handle complex three-dimensional geometries. For Monte Carlo calculations, the more histories sampled, the lower the standard deviation of the resulting estimates. The common intuition is, therefore, that the more histories, the better; as a result, analysts tend to run Monte Carlo analyses as long as possible (or at least to a minimum acceptable uncertainty). For Monte Carlo criticality safety analyses, however, the optimization situation is complicated by the fact that procedures usually require that an extra margin of safety be added because of the statistical uncertainty of the Monte Carlo calculations. This additional safety margin affects the impact of the choice of the calculational standard deviation, both on production and on safety. This paper shows that, under the assumptions of normally distributed benchmarking calculational errors and exact compliance with the upper subcritical limit (USL), the standard deviation that optimizes production is zero, but there is a non-zero value of the calculational standard deviation that minimizes the risk of inadvertently labeling a supercritical configuration as subcritical. Furthermore, this value is shown to be a simple function of the typical benchmarking step outcomes--the bias, the standard deviation of the bias, the upper subcritical limit, and the number of standard deviations added to calculated k-effectives before comparison to the USL

Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

International Nuclear Information System (INIS)

Carter, L.L.; Hendricks, J.S.

1983-01-01

The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays

Biased Monte Carlo optimization: the basic approach

International Nuclear Information System (INIS)

Campioni, Luca; Scardovelli, Ruben; Vestrucci, Paolo

2005-01-01

It is well-known that the Monte Carlo method is very successful in tackling several kinds of system simulations. It often happens that one has to deal with rare events, and the use of a variance reduction technique is almost mandatory, in order to have Monte Carlo efficient applications. The main issue associated with variance reduction techniques is related to the choice of the value of the biasing parameter. Actually, this task is typically left to the experience of the Monte Carlo user, who has to make many attempts before achieving an advantageous biasing. A valuable result is provided: a methodology and a practical rule addressed to establish an a priori guidance for the choice of the optimal value of the biasing parameter. This result, which has been obtained for a single component system, has the notable property of being valid for any multicomponent system. In particular, in this paper, the exponential and the uniform biases of exponentially distributed phenomena are investigated thoroughly

Self-learning Monte Carlo (dynamical biasing)

International Nuclear Information System (INIS)

Matthes, W.

1981-01-01

In many applications the histories of a normal Monte Carlo game rarely reach the target region. An approximate knowledge of the importance (with respect to the target) may be used to guide the particles more frequently into the target region. A Monte Carlo method is presented in which each history contributes to update the importance field such that eventually most target histories are sampled. It is a self-learning method in the sense that the procedure itself: (a) learns which histories are important (reach the target) and increases their probability; (b) reduces the probabilities of unimportant histories; (c) concentrates gradually on the more important target histories. (U.K.)

RNA folding kinetics using Monte Carlo and Gillespie algorithms.

Science.gov (United States)

Clote, Peter; Bayegan, Amir H

2018-04-01

RNA secondary structure folding kinetics is known to be important for the biological function of certain processes, such as the hok/sok system in E. coli. Although linear algebra provides an exact computational solution of secondary structure folding kinetics with respect to the Turner energy model for tiny ([Formula: see text]20 nt) RNA sequences, the folding kinetics for larger sequences can only be approximated by binning structures into macrostates in a coarse-grained model, or by repeatedly simulating secondary structure folding with either the Monte Carlo algorithm or the Gillespie algorithm. Here we investigate the relation between the Monte Carlo algorithm and the Gillespie algorithm. We prove that asymptotically, the expected time for a K-step trajectory of the Monte Carlo algorithm is equal to [Formula: see text] times that of the Gillespie algorithm, where [Formula: see text] denotes the Boltzmann expected network degree. If the network is regular (i.e. every node has the same degree), then the mean first passage time (MFPT) computed by the Monte Carlo algorithm is equal to MFPT computed by the Gillespie algorithm multiplied by [Formula: see text]; however, this is not true for non-regular networks. In particular, RNA secondary structure folding kinetics, as computed by the Monte Carlo algorithm, is not equal to the folding kinetics, as computed by the Gillespie algorithm, although the mean first passage times are roughly correlated. Simulation software for RNA secondary structure folding according to the Monte Carlo and Gillespie algorithms is publicly available, as is our software to compute the expected degree of the network of secondary structures of a given RNA sequence-see http://bioinformatics.bc.edu/clote/RNAexpNumNbors .

OGRE, Monte-Carlo System for Gamma Transport Problems

International Nuclear Information System (INIS)

1984-01-01

1 - Nature of physical problem solved: The OGRE programme system was designed to calculate, by Monte Carlo methods, any quantity related to gamma-ray transport. The system is represented by two examples - OGRE-P1 and OGRE-G. The OGRE-P1 programme is a simple prototype which calculates dose rate on one side of a slab due to a plane source on the other side. The OGRE-G programme, a prototype of a programme utilizing a general-geometry routine, calculates dose rate at arbitrary points. A very general source description in OGRE-G may be employed by reading a tape prepared by the user. 2 - Method of solution: Case histories of gamma rays in the prescribed geometry are generated and analyzed to produce averages of any desired quantity which, in the case of the prototypes, are gamma-ray dose rates. The system is designed to achieve generality by ease of modification. No importance sampling is built into the prototypes, a very general geometry subroutine permits the treatment of complicated geometries. This is essentially the same routine used in the O5R neutron transport system. Boundaries may be either planes or quadratic surfaces, arbitrarily oriented and intersecting in arbitrary fashion. Cross section data is prepared by the auxiliary master cross section programme XSECT which may be used to originate, update, or edit the master cross section tape. The master cross section tape is utilized in the OGRE programmes to produce detailed tables of macroscopic cross sections which are used during the Monte Carlo calculations. 3 - Restrictions on the complexity of the problem: Maximum cross-section array information may be estimated by a given formula for a specific problem. The number of regions must be less than or equal to 50

Monte Carlo simulations to advance characterisation of landmines by pulsed fast/thermal neutron analysis

NARCIS (Netherlands)

Maucec, M.; Rigollet, C.

The performance of a detection system based on the pulsed fast/thermal neutron analysis technique was assessed using Monte Carlo simulations. The aim was to develop and implement simulation methods, to support and advance the data analysis techniques of the characteristic gamma-ray spectra,

A NEW MONTE CARLO METHOD FOR TIME-DEPENDENT NEUTRINO RADIATION TRANSPORT

International Nuclear Information System (INIS)

Abdikamalov, Ernazar; Ott, Christian D.; O'Connor, Evan; Burrows, Adam; Dolence, Joshua C.; Löffler, Frank; Schnetter, Erik

2012-01-01

Monte Carlo approaches to radiation transport have several attractive properties such as simplicity of implementation, high accuracy, and good parallel scaling. Moreover, Monte Carlo methods can handle complicated geometries and are relatively easy to extend to multiple spatial dimensions, which makes them potentially interesting in modeling complex multi-dimensional astrophysical phenomena such as core-collapse supernovae. The aim of this paper is to explore Monte Carlo methods for modeling neutrino transport in core-collapse supernovae. We generalize the Implicit Monte Carlo photon transport scheme of Fleck and Cummings and gray discrete-diffusion scheme of Densmore et al. to energy-, time-, and velocity-dependent neutrino transport. Using our 1D spherically-symmetric implementation, we show that, similar to the photon transport case, the implicit scheme enables significantly larger timesteps compared with explicit time discretization, without sacrificing accuracy, while the discrete-diffusion method leads to significant speed-ups at high optical depth. Our results suggest that a combination of spectral, velocity-dependent, Implicit Monte Carlo and discrete-diffusion Monte Carlo methods represents a robust approach for use in neutrino transport calculations in core-collapse supernovae. Our velocity-dependent scheme can easily be adapted to photon transport.

A NEW MONTE CARLO METHOD FOR TIME-DEPENDENT NEUTRINO RADIATION TRANSPORT

Energy Technology Data Exchange (ETDEWEB)

Abdikamalov, Ernazar; Ott, Christian D.; O' Connor, Evan [TAPIR, California Institute of Technology, MC 350-17, 1200 E California Blvd., Pasadena, CA 91125 (United States); Burrows, Adam; Dolence, Joshua C. [Department of Astrophysical Sciences, Princeton University, Peyton Hall, Ivy Lane, Princeton, NJ 08544 (United States); Loeffler, Frank; Schnetter, Erik, E-mail: abdik@tapir.caltech.edu [Center for Computation and Technology, Louisiana State University, 216 Johnston Hall, Baton Rouge, LA 70803 (United States)

2012-08-20

Monte Carlo approaches to radiation transport have several attractive properties such as simplicity of implementation, high accuracy, and good parallel scaling. Moreover, Monte Carlo methods can handle complicated geometries and are relatively easy to extend to multiple spatial dimensions, which makes them potentially interesting in modeling complex multi-dimensional astrophysical phenomena such as core-collapse supernovae. The aim of this paper is to explore Monte Carlo methods for modeling neutrino transport in core-collapse supernovae. We generalize the Implicit Monte Carlo photon transport scheme of Fleck and Cummings and gray discrete-diffusion scheme of Densmore et al. to energy-, time-, and velocity-dependent neutrino transport. Using our 1D spherically-symmetric implementation, we show that, similar to the photon transport case, the implicit scheme enables significantly larger timesteps compared with explicit time discretization, without sacrificing accuracy, while the discrete-diffusion method leads to significant speed-ups at high optical depth. Our results suggest that a combination of spectral, velocity-dependent, Implicit Monte Carlo and discrete-diffusion Monte Carlo methods represents a robust approach for use in neutrino transport calculations in core-collapse supernovae. Our velocity-dependent scheme can easily be adapted to photon transport.

Therapeutic Applications of Monte Carlo Calculations in Nuclear Medicine

International Nuclear Information System (INIS)

Coulot, J

2003-01-01

Monte Carlo techniques are involved in many applications in medical physics, and the field of nuclear medicine has seen a great development in the past ten years due to their wider use. Thus, it is of great interest to look at the state of the art in this domain, when improving computer performances allow one to obtain improved results in a dramatically reduced time. The goal of this book is to make, in 15 chapters, an exhaustive review of the use of Monte Carlo techniques in nuclear medicine, also giving key features which are not necessary directly related to the Monte Carlo method, but mandatory for its practical application. As the book deals with therapeutic' nuclear medicine, it focuses on internal dosimetry. After a general introduction on Monte Carlo techniques and their applications in nuclear medicine (dosimetry, imaging and radiation protection), the authors give an overview of internal dosimetry methods (formalism, mathematical phantoms, quantities of interest). Then, some of the more widely used Monte Carlo codes are described, as well as some treatment planning softwares. Some original techniques are also mentioned, such as dosimetry for boron neutron capture synovectomy. It is generally well written, clearly presented, and very well documented. Each chapter gives an overview of each subject, and it is up to the reader to investigate it further using the extensive bibliography provided. Each topic is discussed from a practical point of view, which is of great help for non-experienced readers. For instance, the chapter about mathematical aspects of Monte Carlo particle transport is very clear and helps one to apprehend the philosophy of the method, which is often a difficulty with a more theoretical approach. Each chapter is put in the general (clinical) context, and this allows the reader to keep in mind the intrinsic limitation of each technique involved in dosimetry (for instance activity quantitation). Nevertheless, there are some minor remarks to

Grain-boundary melting: A Monte Carlo study

DEFF Research Database (Denmark)

Besold, Gerhard; Mouritsen, Ole G.

1994-01-01

Grain-boundary melting in a lattice-gas model of a bicrystal is studied by Monte Carlo simulation using the grand canonical ensemble. Well below the bulk melting temperature T(m), a disordered liquidlike layer gradually emerges at the grain boundary. Complete interfacial wetting can be observed...... when the temperature approaches T(m) from below. Monte Carlo data over an extended temperature range indicate a logarithmic divergence w(T) approximately - ln(T(m)-T) of the width of the disordered layer w, in agreement with mean-field theory....

Analysis of error in Monte Carlo transport calculations

International Nuclear Information System (INIS)

Booth, T.E.

1979-01-01

The Monte Carlo method for neutron transport calculations suffers, in part, because of the inherent statistical errors associated with the method. Without an estimate of these errors in advance of the calculation, it is difficult to decide what estimator and biasing scheme to use. Recently, integral equations have been derived that, when solved, predicted errors in Monte Carlo calculations in nonmultiplying media. The present work allows error prediction in nonanalog Monte Carlo calculations of multiplying systems, even when supercritical. Nonanalog techniques such as biased kernels, particle splitting, and Russian Roulette are incorporated. Equations derived here allow prediction of how much a specific variance reduction technique reduces the number of histories required, to be weighed against the change in time required for calculation of each history. 1 figure, 1 table

Neutron flux calculation by means of Monte Carlo methods

International Nuclear Information System (INIS)

Barz, H.U.; Eichhorn, M.

1988-01-01

In this report a survey of modern neutron flux calculation procedures by means of Monte Carlo methods is given. Due to the progress in the development of variance reduction techniques and the improvements of computational techniques this method is of increasing importance. The basic ideas in application of Monte Carlo methods are briefly outlined. In more detail various possibilities of non-analog games and estimation procedures are presented, problems in the field of optimizing the variance reduction techniques are discussed. In the last part some important international Monte Carlo codes and own codes of the authors are listed and special applications are described. (author)

PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code

International Nuclear Information System (INIS)

Iandola, F.N.; O'Brien, M.J.; Procassini, R.J.

2010-01-01

Monte Carlo particle transport applications are often written in low-level languages (C/C++) for optimal performance on clusters and supercomputers. However, this development approach often sacrifices straightforward usability and testing in the interest of fast application performance. To improve usability, some high-performance computing applications employ mixed-language programming with high-level and low-level languages. In this study, we consider the benefits of incorporating an interactive Python interface into a Monte Carlo application. With PyMercury, a new Python extension to the Mercury general-purpose Monte Carlo particle transport code, we improve application usability without diminishing performance. In two case studies, we illustrate how PyMercury improves usability and simplifies testing and validation in a Monte Carlo application. In short, PyMercury demonstrates the value of interactive Python for Monte Carlo particle transport applications. In the future, we expect interactive Python to play an increasingly significant role in Monte Carlo usage and testing.

RMCgui: a new interface for the workflow associated with running Reverse Monte Carlo simulations

International Nuclear Information System (INIS)

Dove, Martin T; Rigg, Gary

2013-01-01

The Reverse Monte Carlo method enables construction and refinement of large atomic models of materials that are tuned to give best agreement with experimental data such as neutron and x-ray total scattering data, capturing both the average structure and fluctuations. The practical drawback with the current implementations of this approach is the relatively complex workflow required, from setting up the configuration and simulation details through to checking the final outputs and analysing the resultant configurations. In order to make this workflow more accessible to users, we have developed an end-to-end workflow wrapped within a graphical user interface—RMCgui—designed to make the Reverse Monte Carlo more widely accessible. (paper)

Transport methods: general. 1. The Analytical Monte Carlo Method for Radiation Transport Calculations

International Nuclear Information System (INIS)

Martin, William R.; Brown, Forrest B.

2001-01-01

We present an alternative Monte Carlo method for solving the coupled equations of radiation transport and material energy. This method is based on incorporating the analytical solution to the material energy equation directly into the Monte Carlo simulation for the radiation intensity. This method, which we call the Analytical Monte Carlo (AMC) method, differs from the well known Implicit Monte Carlo (IMC) method of Fleck and Cummings because there is no discretization of the material energy equation since it is solved as a by-product of the Monte Carlo simulation of the transport equation. Our method also differs from the method recently proposed by Ahrens and Larsen since they use Monte Carlo to solve both equations, while we are solving only the radiation transport equation with Monte Carlo, albeit with effective sources and cross sections to represent the emission sources. Our method bears some similarity to a method developed and implemented by Carter and Forest nearly three decades ago, but there are substantive differences. We have implemented our method in a simple zero-dimensional Monte Carlo code to test the feasibility of the method, and the preliminary results are very promising, justifying further extension to more realistic geometries. (authors)

Markov Chain Monte Carlo

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 7; Issue 3. Markov Chain Monte Carlo - Examples. Arnab Chakraborty. General Article Volume 7 Issue 3 March 2002 pp 25-34. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/007/03/0025-0034. Keywords.

Monte Carlo studies of high-transverse-energy hadronic interactions

International Nuclear Information System (INIS)

Corcoran, M.D.

1985-01-01

A four-jet Monte Carlo calculation has been used to simulate hadron-hadron interactions which deposit high transverse energy into a large-solid-angle calorimeter and limited solid-angle regions of the calorimeter. The calculation uses first-order QCD cross sections to generate two scattered jets and also produces beam and target jets. Field-Feynman fragmentation has been used in the hadronization. The sensitivity of the results to a few features of the Monte Carlo program has been studied. The results are found to be very sensitive to the method used to ensure overall energy conservation after the fragmentation of the four jets is complete. Results are also sensitive to the minimum momentum transfer in the QCD subprocesses and to the distribution of p/sub T/ to the jet axis and the multiplicities in the fragmentation. With reasonable choices of these features of the Monte Carlo program, good agreement with data at Fermilab/CERN SPS energies is obtained, comparable to the agreement achieved with more sophisticated parton-shower models. With other choices, however, the calculation gives qualitatively different results which are in strong disagreement with the data. These results have important implications for extracting physics conclusions from Monte Carlo calculations. It is not possible to test the validity of a particular model or distinguish between different models unless the Monte Carlo results are unambiguous and different models exhibit clearly different behavior

Monte Carlo calculations for doses in organs and tissues to oral radiography; Calculo de Monte Carlo para doses em orgaos e tecidos para radiologia oral

Energy Technology Data Exchange (ETDEWEB)

Sampaio, E V.M.

1986-12-31

Using the MIRD 5 phantom and Monte Carlo technique, organ doses in patients undergoing external dental examination were calculated taking into account the different x-ray beam geometries and the various possible positions of x-ray source with regard to the head of the patient. It was necessary to introduce in the original computer program a new source description specific for dental examinations. To have a realistic evaluation of organ doses during dental examination it was necessary to introduce a new region in the phantom heat which characterizes the teeth and salivary glands. The attenuation of the x-ray beam by the lead shield of the radiographic film was also introduced in the calculation. (author).

Monte Carlo methods and applications in nuclear physics

International Nuclear Information System (INIS)

Carlson, J.

1990-01-01

Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs

Acceptance and implementation of a system of planning computerized based on Monte Carlo

International Nuclear Information System (INIS)

Lopez-Tarjuelo, J.; Garcia-Molla, R.; Suan-Senabre, X. J.; Quiros-Higueras, J. Q.; Santos-Serra, A.; Marco-Blancas, N.; Calzada-Feliu, S.

2013-01-01

It has been done the acceptance for use clinical Monaco computerized planning system, based on an on a virtual model of the energy yield of the head of the linear electron Accelerator and that performs the calculation of the dose with an algorithm of x-rays (XVMC) based on Monte Carlo algorithm. (Author)

Microcanonical Monte Carlo

International Nuclear Information System (INIS)

Creutz, M.

1986-01-01

The author discusses a recently developed algorithm for simulating statistical systems. The procedure interpolates between molecular dynamics methods and canonical Monte Carlo. The primary advantages are extremely fast simulations of discrete systems such as the Ising model and a relative insensitivity to random number quality. A variation of the algorithm gives rise to a deterministic dynamics for Ising spins. This model may be useful for high speed simulation of non-equilibrium phenomena

Monte Carlo simulation applied to alpha spectrometry

International Nuclear Information System (INIS)

Baccouche, S.; Gharbi, F.; Trabelsi, A.

2007-01-01

Alpha particle spectrometry is a widely-used analytical method, in particular when we deal with pure alpha emitting radionuclides. Monte Carlo simulation is an adequate tool to investigate the influence of various phenomena on this analytical method. We performed an investigation of those phenomena using the simulation code GEANT of CERN. The results concerning the geometrical detection efficiency in different measurement geometries agree with analytical calculations. This work confirms that Monte Carlo simulation of solid angle of detection is a very useful tool to determine with very good accuracy the detection efficiency.

Monte Carlo simulation of neutron scattering instruments

International Nuclear Information System (INIS)

Seeger, P.A.

1995-01-01

A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width

Simulation of transport equations with Monte Carlo

International Nuclear Information System (INIS)

Matthes, W.

1975-09-01

The main purpose of the report is to explain the relation between the transport equation and the Monte Carlo game used for its solution. The introduction of artificial particles carrying a weight provides one with high flexibility in constructing many different games for the solution of the same equation. This flexibility opens a way to construct a Monte Carlo game for the solution of the adjoint transport equation. Emphasis is laid mostly on giving a clear understanding of what to do and not on the details of how to do a specific game

High-efficiency wavefunction updates for large scale Quantum Monte Carlo

Science.gov (United States)

Kent, Paul; McDaniel, Tyler; Li, Ying Wai; D'Azevedo, Ed

Within ab intio Quantum Monte Carlo (QMC) simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunctions. The evaluation of each Monte Carlo move requires finding the determinant of a dense matrix, which is traditionally iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. For calculations with thousands of electrons, this operation dominates the execution profile. We propose a novel rank- k delayed update scheme. This strategy enables probability evaluation for multiple successive Monte Carlo moves, with application of accepted moves to the matrices delayed until after a predetermined number of moves, k. Accepted events grouped in this manner are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency. This procedure does not change the underlying Monte Carlo sampling or the sampling efficiency. For large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude speedups can be obtained on both multi-core CPU and on GPUs, making this algorithm highly advantageous for current petascale and future exascale computations.

The Monte Carlo Simulation Method for System Reliability and Risk Analysis

CERN Document Server

Zio, Enrico

2013-01-01

Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling.   Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques.   This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergra...

A contribution Monte Carlo method

International Nuclear Information System (INIS)

Aboughantous, C.H.

1994-01-01

A Contribution Monte Carlo method is developed and successfully applied to a sample deep-penetration shielding problem. The random walk is simulated in most of its parts as in conventional Monte Carlo methods. The probability density functions (pdf's) are expressed in terms of spherical harmonics and are continuous functions in direction cosine and azimuthal angle variables as well as in position coordinates; the energy is discretized in the multigroup approximation. The transport pdf is an unusual exponential kernel strongly dependent on the incident and emergent directions and energies and on the position of the collision site. The method produces the same results obtained with the deterministic method with a very small standard deviation, with as little as 1,000 Contribution particles in both analog and nonabsorption biasing modes and with only a few minutes CPU time

Evaluation and characterization of X-ray scattering in tissues and mammographic simulators using Monte Carlo simulation

International Nuclear Information System (INIS)

Oliveira, Monica G. Nunes; Braz, Delson; Silva, Regina Cely B. da S.

2005-01-01

The computer simulation has been widely used in physical researches by both the viability of the codes and the growth of the power of computers in the last decades. The Monte Carlo simulation program, EGS4 code is a simulation program used in the area of radiation transport. The simulators, surrogate tissues, phantoms are objects used to perform studies on dosimetric quantities and quality testing of images. The simulators have characteristics of scattering and absorption of radiation similar to tissues that make up the body. The aim of this work is to translate the effects of radiation interactions in a real healthy breast tissues, sick and on simulators using the EGS4 Monte Carlo simulation code

Exact Monte Carlo for molecules

International Nuclear Information System (INIS)

Lester, W.A. Jr.; Reynolds, P.J.

1985-03-01

A brief summary of the fixed-node quantum Monte Carlo method is presented. Results obtained for binding energies, the classical barrier height for H + H 2 , and the singlet-triplet splitting in methylene are presented and discussed. 17 refs

The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature

CERN Document Server

Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V

2010-01-01

A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications.

Application of the Monte Carlo method to diagnostic radiology

International Nuclear Information System (INIS)

Persliden, J.

1986-01-01

A Monte Carlo program for photon transport is developed. The program is used to investigate the energy imparted to water slabs (simulating patients), and the related backscattered and transmitted energies as functions of primary photon energy and water slab thickness. The accuracy of the results depends on the cross-section data for the probabilities of the various interactions in the slab and on the physical quantity calculated. Backscattered energy fractions can vary by as much as 10-20 %, using different sets of published data for the photoelectric cross section while imparted fractions are only slightly affected. The results are used to calculate improved conversion factors for determining the energy imparted to the patient in X-ray diagnostic examinations from measurements of the air collision kerma integrated over beam area. The small angle distribution of scattered photons transmitted through a water slab, relevant to problems of image quality, is calculated taking into account the diffraction phenomena of liquid water. The calculations are performed with a collision density estimator. This estimator makes it possible to calculate important physical quantities which are virtually impracticable to assess with the Monte Carlo codes commonly used in medical physics or in experiments. With the collision density estimator, the influence of air gaps on the reduction of scattered radiation is investigated for different detectors, field areas and primary X-ray spectra. Contrast degradation and contrast improvement factors are given as functions of field area for various air gaps. (With 105 refs.) (author)

No-compromise reptation quantum Monte Carlo

International Nuclear Information System (INIS)

Yuen, W K; Farrar, Thomas J; Rothstein, Stuart M

2007-01-01

Since its publication, the reptation quantum Monte Carlo algorithm of Baroni and Moroni (1999 Phys. Rev. Lett. 82 4745) has been applied to several important problems in physics, but its mathematical foundations are not well understood. We show that their algorithm is not of typical Metropolis-Hastings type, and we specify conditions required for the generated Markov chain to be stationary and to converge to the intended distribution. The time-step bias may add up, and in many applications it is only the middle of a reptile that is the most important. Therefore, we propose an alternative, 'no-compromise reptation quantum Monte Carlo' to stabilize the middle of the reptile. (fast track communication)

Exploring cluster Monte Carlo updates with Boltzmann machines.

Science.gov (United States)

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

Science.gov (United States)

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.