Monte Carlo-based tail exponent estimator
Barunik, Jozef; Vacha, Lukas
2010-11-01
In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations, we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the international world stock market indices. On the two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent.
Efficient sampling algorithms for Monte Carlo based treatment planning
International Nuclear Information System (INIS)
DeMarco, J.J.; Solberg, T.D.; Chetty, I.; Smathers, J.B.
1998-01-01
Efficient sampling algorithms are necessary for producing a fast Monte Carlo based treatment planning code. This study evaluates several aspects of a photon-based tracking scheme and the effect of optimal sampling algorithms on the efficiency of the code. Four areas were tested: pseudo-random number generation, generalized sampling of a discrete distribution, sampling from the exponential distribution, and delta scattering as applied to photon transport through a heterogeneous simulation geometry. Generalized sampling of a discrete distribution using the cutpoint method can produce speedup gains of one order of magnitude versus conventional sequential sampling. Photon transport modifications based upon the delta scattering method were implemented and compared with a conventional boundary and collision checking algorithm. The delta scattering algorithm is faster by a factor of six versus the conventional algorithm for a boundary size of 5 mm within a heterogeneous geometry. A comparison of portable pseudo-random number algorithms and exponential sampling techniques is also discussed
GPU-Monte Carlo based fast IMRT plan optimization
Directory of Open Access Journals (Sweden)
Yongbao Li
2014-03-01
, Shi F, Jiang S, Jia X. GPU-Monte Carlo based fast IMRT plan optimization. Int J Cancer Ther Oncol 2014; 2(2:020244. DOI: 10.14319/ijcto.0202.44
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)
Implementation of a Monte Carlo based inverse planning model for clinical IMRT with MCNP code
International Nuclear Information System (INIS)
He, Tongming Tony
2003-01-01
Inaccurate dose calculations and limitations of optimization algorithms in inverse planning introduce systematic and convergence errors to treatment plans. This work was to implement a Monte Carlo based inverse planning model for clinical IMRT aiming to minimize the aforementioned errors. The strategy was to precalculate the dose matrices of beamlets in a Monte Carlo based method followed by the optimization of beamlet intensities. The MCNP 4B (Monte Carlo N-Particle version 4B) code was modified to implement selective particle transport and dose tallying in voxels and efficient estimation of statistical uncertainties. The resulting performance gain was over eleven thousand times. Due to concurrent calculation of multiple beamlets of individual ports, hundreds of beamlets in an IMRT plan could be calculated within a practical length of time. A finite-sized point source model provided a simple and accurate modeling of treatment beams. The dose matrix calculations were validated through measurements in phantoms. Agreements were better than 1.5% or 0.2 cm. The beamlet intensities were optimized using a parallel platform based optimization algorithm that was capable of escape from local minima and preventing premature convergence. The Monte Carlo based inverse planning model was applied to clinical cases. The feasibility and capability of Monte Carlo based inverse planning for clinical IMRT was demonstrated. Systematic errors in treatment plans of a commercial inverse planning system were assessed in comparison with the Monte Carlo based calculations. Discrepancies in tumor doses and critical structure doses were up to 12% and 17%, respectively. The clinical importance of Monte Carlo based inverse planning for IMRT was demonstrated
Monte Carlo Based Framework to Support HAZOP Study
DEFF Research Database (Denmark)
Danko, Matej; Frutiger, Jerome; Jelemenský, Ľudovít
2017-01-01
deviations in process parameters simultaneously, thereby bringing an improvement to the Hazard and Operability study (HAZOP), which normally considers only one at a time deviation in process parameters. Furthermore, Monte Carlo filtering was then used to identify operability and hazard issues including...
Monte Carlo based radial shield design of typical PWR reactor
Energy Technology Data Exchange (ETDEWEB)
Gul, Anas; Khan, Rustam; Qureshi, M. Ayub; Azeem, Muhammad Waqar; Raza, S.A. [Pakistan Institute of Engineering and Applied Sciences, Islamabad (Pakistan). Dept. of Nuclear Engineering; Stummer, Thomas [Technische Univ. Wien (Austria). Atominst.
2017-04-15
This paper presents the radiation shielding model of a typical PWR (CNPP-II) at Chashma, Pakistan. The model was developed using Monte Carlo N Particle code [2], equipped with ENDF/B-VI continuous energy cross section libraries. This model was applied to calculate the neutron and gamma flux and dose rates in the radial direction at core mid plane. The simulated results were compared with the reference results of Shanghai Nuclear Engineering Research and Design Institute (SNERDI).
Monte Carlo based radial shield design of typical PWR reactor
Energy Technology Data Exchange (ETDEWEB)
Gul, Anas; Khan, Rustam; Qureshi, M. Ayub; Azeem, Muhammad Waqar; Raza, S.A. [Pakistan Institute of Engineering and Applied Sciences, Islamabad (Pakistan). Dept. of Nuclear Engineering; Stummer, Thomas [Technische Univ. Wien (Austria). Atominst.
2016-11-15
Neutron and gamma flux and dose equivalent rate distribution are analysed in radial and shields of a typical PWR type reactor based on the Monte Carlo radiation transport computer code MCNP5. The ENDF/B-VI continuous energy cross-section library has been employed for the criticality and shielding analysis. The computed results are in good agreement with the reference results (maximum difference is less than 56 %). It implies that MCNP5 a good tool for accurate prediction of neutron and gamma flux and dose rates in radial shield around the core of PWR type reactors.
Clinical dosimetry in photon radiotherapy. A Monte Carlo based investigation
International Nuclear Information System (INIS)
Wulff, Joerg
2010-01-01
Practical clinical dosimetry is a fundamental step within the radiation therapy process and aims at quantifying the absorbed radiation dose within a 1-2% uncertainty. To achieve this level of accuracy, corrections are needed for calibrated and air-filled ionization chambers, which are used for dose measurement. The procedures of correction are based on cavity theory of Spencer-Attix and are defined in current dosimetry protocols. Energy dependent corrections for deviations from calibration beams account for changed ionization chamber response in the treatment beam. The corrections applied are usually based on semi-analytical models or measurements and are generally hard to determine due to their magnitude of only a few percents or even less. Furthermore the corrections are defined for fixed geometrical reference-conditions and do not apply to non-reference conditions in modern radiotherapy applications. The stochastic Monte Carlo method for the simulation of radiation transport is becoming a valuable tool in the field of Medical Physics. As a suitable tool for calculation of these corrections with high accuracy the simulations enable the investigation of ionization chambers under various conditions. The aim of this work is the consistent investigation of ionization chamber dosimetry in photon radiation therapy with the use of Monte Carlo methods. Nowadays Monte Carlo systems exist, which enable the accurate calculation of ionization chamber response in principle. Still, their bare use for studies of this type is limited due to the long calculation times needed for a meaningful result with a small statistical uncertainty, inherent to every result of a Monte Carlo simulation. Besides heavy use of computer hardware, techniques methods of variance reduction to reduce the needed calculation time can be applied. Methods for increasing the efficiency in the results of simulation were developed and incorporated in a modern and established Monte Carlo simulation environment
Monte Carlo-based simulation of dynamic jaws tomotherapy
Energy Technology Data Exchange (ETDEWEB)
Sterpin, E.; Chen, Y.; Chen, Q.; Lu, W.; Mackie, T. R.; Vynckier, S. [Department of Molecular Imaging, Radiotherapy and Oncology, Universite Catholique de Louvain, 54 Avenue Hippocrate, 1200 Brussels, Belgium and Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States); TomoTherapy Inc., 1240 Deming Way, Madison, Wisconsin 53717 (United States); 21 Century Oncology., 1240 D' onofrio, Madison, Wisconsin 53719 (United States); TomoTherapy Inc., 1240 Deming Way, Madison, Wisconsin 53717 and Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States); Department of Radiotherapy and Oncology, Universite Catholique de Louvain, St-Luc University Hospital, 10 Avenue Hippocrate, 1200 Brussels (Belgium)
2011-09-15
Purpose: Original TomoTherapy systems may involve a trade-off between conformity and treatment speed, the user being limited to three slice widths (1.0, 2.5, and 5.0 cm). This could be overcome by allowing the jaws to define arbitrary fields, including very small slice widths (<1 cm), which are challenging for a beam model. The aim of this work was to incorporate the dynamic jaws feature into a Monte Carlo (MC) model called TomoPen, based on the MC code PENELOPE, previously validated for the original TomoTherapy system. Methods: To keep the general structure of TomoPen and its efficiency, the simulation strategy introduces several techniques: (1) weight modifiers to account for any jaw settings using only the 5 cm phase-space file; (2) a simplified MC based model called FastStatic to compute the modifiers faster than pure MC; (3) actual simulation of dynamic jaws. Weight modifiers computed with both FastStatic and pure MC were compared. Dynamic jaws simulations were compared with the convolution/superposition (C/S) of TomoTherapy in the ''cheese'' phantom for a plan with two targets longitudinally separated by a gap of 3 cm. Optimization was performed in two modes: asymmetric jaws-constant couch speed (''running start stop,'' RSS) and symmetric jaws-variable couch speed (''symmetric running start stop,'' SRSS). Measurements with EDR2 films were also performed for RSS for the formal validation of TomoPen with dynamic jaws. Results: Weight modifiers computed with FastStatic were equivalent to pure MC within statistical uncertainties (0.5% for three standard deviations). Excellent agreement was achieved between TomoPen and C/S for both asymmetric jaw opening/constant couch speed and symmetric jaw opening/variable couch speed, with deviations well within 2%/2 mm. For RSS procedure, agreement between C/S and measurements was within 2%/2 mm for 95% of the points and 3%/3 mm for 98% of the points, where dose is
Monte Carlo-based simulation of dynamic jaws tomotherapy
International Nuclear Information System (INIS)
Sterpin, E.; Chen, Y.; Chen, Q.; Lu, W.; Mackie, T. R.; Vynckier, S.
2011-01-01
Purpose: Original TomoTherapy systems may involve a trade-off between conformity and treatment speed, the user being limited to three slice widths (1.0, 2.5, and 5.0 cm). This could be overcome by allowing the jaws to define arbitrary fields, including very small slice widths (<1 cm), which are challenging for a beam model. The aim of this work was to incorporate the dynamic jaws feature into a Monte Carlo (MC) model called TomoPen, based on the MC code PENELOPE, previously validated for the original TomoTherapy system. Methods: To keep the general structure of TomoPen and its efficiency, the simulation strategy introduces several techniques: (1) weight modifiers to account for any jaw settings using only the 5 cm phase-space file; (2) a simplified MC based model called FastStatic to compute the modifiers faster than pure MC; (3) actual simulation of dynamic jaws. Weight modifiers computed with both FastStatic and pure MC were compared. Dynamic jaws simulations were compared with the convolution/superposition (C/S) of TomoTherapy in the ''cheese'' phantom for a plan with two targets longitudinally separated by a gap of 3 cm. Optimization was performed in two modes: asymmetric jaws-constant couch speed (''running start stop,'' RSS) and symmetric jaws-variable couch speed (''symmetric running start stop,'' SRSS). Measurements with EDR2 films were also performed for RSS for the formal validation of TomoPen with dynamic jaws. Results: Weight modifiers computed with FastStatic were equivalent to pure MC within statistical uncertainties (0.5% for three standard deviations). Excellent agreement was achieved between TomoPen and C/S for both asymmetric jaw opening/constant couch speed and symmetric jaw opening/variable couch speed, with deviations well within 2%/2 mm. For RSS procedure, agreement between C/S and measurements was within 2%/2 mm for 95% of the points and 3%/3 mm for 98% of the points, where dose is greater than 30% of the prescription dose (gamma analysis
Directory of Open Access Journals (Sweden)
Lin Wang
2018-01-01
Full Text Available Monte Carlo simulation of light propagation in turbid medium has been studied for years. A number of software packages have been developed to handle with such issue. However, it is hard to compare these simulation packages, especially for tissues with complex heterogeneous structures. Here, we first designed a group of mesh datasets generated by Iso2Mesh software, and used them to cross-validate the accuracy and to evaluate the performance of four Monte Carlo-based simulation packages, including Monte Carlo model of steady-state light transport in multi-layered tissues (MCML, tetrahedron-based inhomogeneous Monte Carlo optical simulator (TIMOS, Molecular Optical Simulation Environment (MOSE, and Mesh-based Monte Carlo (MMC. The performance of each package was evaluated based on the designed mesh datasets. The merits and demerits of each package were also discussed. Comparative results showed that the TIMOS package provided the best performance, which proved to be a reliable, efficient, and stable MC simulation package for users.
An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
Directory of Open Access Journals (Sweden)
S. Razmyan
2012-01-01
Full Text Available Discriminant analysis (DA is used for the measurement of estimates of a discriminant function by minimizing their group misclassifications to predict group membership of newly sampled data. A major source of misclassification in DA is due to the overlapping of groups. The uncertainty in the input variables and model parameters needs to be properly characterized in decision making. This study combines DEA-DA with a sensitivity analysis approach to an assessment of the influence of banks’ variables on the overall variance in overlap in a DA in order to determine which variables are most significant. A Monte-Carlo-based sensitivity analysis is considered for computing the set of first-order sensitivity indices of the variables to estimate the contribution of each uncertain variable. The results show that the uncertainties in the loans granted and different deposit variables are more significant than uncertainties in other banks’ variables in decision making.
Monte Carlo-based investigation of water-equivalence of solid phantoms at 137Cs energy
International Nuclear Information System (INIS)
Vishwakarma, Ramkrushna S.; Palani Selvam, T.; Sahoo, Sridhar; Mishra, Subhalaxmi; Chourasiya, Ghanshyam
2013-01-01
Investigation of solid phantom materials such as solid water, virtual water, plastic water, RW1, polystyrene, and polymethylmethacrylate (PMMA) for their equivalence to liquid water at 137 Cs energy (photon energy of 662 keV) under full scatter conditions is carried out using the EGSnrc Monte Carlo code system. Monte Carlo-based EGSnrc code system was used in the work to calculate distance-dependent phantom scatter corrections. The study also includes separation of primary and scattered dose components. Monte Carlo simulations are carried out using primary particle histories up to 5 x 10 9 to attain less than 0.3% statistical uncertainties in the estimation of dose. Water equivalence of various solid phantoms such as solid water, virtual water, RW1, PMMA, polystyrene, and plastic water materials are investigated at 137 Cs energy under full scatter conditions. The investigation reveals that solid water, virtual water, and RW1 phantoms are water equivalent up to 15 cm from the source. Phantom materials such as plastic water, PMMA, and polystyrene phantom materials are water equivalent up to 10 cm. At 15 cm from the source, the phantom scatter corrections are 1.035, 1.050, and 0.949 for the phantoms PMMA, plastic water, and polystyrene, respectively. (author)
Development of Monte Carlo-based pebble bed reactor fuel management code
International Nuclear Information System (INIS)
Setiadipura, Topan; Obara, Toru
2014-01-01
Highlights: • A new Monte Carlo-based fuel management code for OTTO cycle pebble bed reactor was developed. • The double-heterogeneity was modeled using statistical method in MVP-BURN code. • The code can perform analysis of equilibrium and non-equilibrium phase. • Code-to-code comparisons for Once-Through-Then-Out case were investigated. • Ability of the code to accommodate the void cavity was confirmed. - Abstract: A fuel management code for pebble bed reactors (PBRs) based on the Monte Carlo method has been developed in this study. The code, named Monte Carlo burnup analysis code for PBR (MCPBR), enables a simulation of the Once-Through-Then-Out (OTTO) cycle of a PBR from the running-in phase to the equilibrium condition. In MCPBR, a burnup calculation based on a continuous-energy Monte Carlo code, MVP-BURN, is coupled with an additional utility code to be able to simulate the OTTO cycle of PBR. MCPBR has several advantages in modeling PBRs, namely its Monte Carlo neutron transport modeling, its capability of explicitly modeling the double heterogeneity of the PBR core, and its ability to model different axial fuel speeds in the PBR core. Analysis at the equilibrium condition of the simplified PBR was used as the validation test of MCPBR. The calculation results of the code were compared with the results of diffusion-based fuel management PBR codes, namely the VSOP and PEBBED codes. Using JENDL-4.0 nuclide library, MCPBR gave a 4.15% and 3.32% lower k eff value compared to VSOP and PEBBED, respectively. While using JENDL-3.3, MCPBR gave a 2.22% and 3.11% higher k eff value compared to VSOP and PEBBED, respectively. The ability of MCPBR to analyze neutron transport in the top void of the PBR core and its effects was also confirmed
Monte Carlo based dosimetry and treatment planning for neutron capture therapy of brain tumors
International Nuclear Information System (INIS)
Zamenhof, R.G.; Brenner, J.F.; Wazer, D.E.; Madoc-Jones, H.; Clement, S.D.; Harling, O.K.; Yanch, J.C.
1990-01-01
Monte Carlo based dosimetry and computer-aided treatment planning for neutron capture therapy have been developed to provide the necessary link between physical dosimetric measurements performed on the MITR-II epithermal-neutron beams and the need of the radiation oncologist to synthesize large amounts of dosimetric data into a clinically meaningful treatment plan for each individual patient. Monte Carlo simulation has been employed to characterize the spatial dose distributions within a skull/brain model irradiated by an epithermal-neutron beam designed for neutron capture therapy applications. The geometry and elemental composition employed for the mathematical skull/brain model and the neutron and photon fluence-to-dose conversion formalism are presented. A treatment planning program, NCTPLAN, developed specifically for neutron capture therapy, is described. Examples are presented illustrating both one and two-dimensional dose distributions obtainable within the brain with an experimental epithermal-neutron beam, together with beam quality and treatment plan efficacy criteria which have been formulated for neutron capture therapy. The incorporation of three-dimensional computed tomographic image data into the treatment planning procedure is illustrated
Monte Carlo based treatment planning for modulated electron beam radiation therapy
Energy Technology Data Exchange (ETDEWEB)
Lee, Michael C. [Radiation Physics Division, Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States)]. E-mail: mclee@reyes.stanford.edu; Deng Jun; Li Jinsheng; Jiang, Steve B.; Ma, C.-M. [Radiation Physics Division, Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States)
2001-08-01
A Monte Carlo based treatment planning system for modulated electron radiation therapy (MERT) is presented. This new variation of intensity modulated radiation therapy (IMRT) utilizes an electron multileaf collimator (eMLC) to deliver non-uniform intensity maps at several electron energies. In this way, conformal dose distributions are delivered to irregular targets located a few centimetres below the surface while sparing deeper-lying normal anatomy. Planning for MERT begins with Monte Carlo generation of electron beamlets. Electrons are transported with proper in-air scattering and the dose is tallied in the phantom for each beamlet. An optimized beamlet plan may be calculated using inverse-planning methods. Step-and-shoot leaf sequences are generated for the intensity maps and dose distributions recalculated using Monte Carlo simulations. Here, scatter and leakage from the leaves are properly accounted for by transporting electrons through the eMLC geometry. The weights for the segments of the plan are re-optimized with the leaf positions fixed and bremsstrahlung leakage and electron scatter doses included. This optimization gives the final optimized plan. It is shown that a significant portion of the calculation time is spent transporting particles in the leaves. However, this is necessary since optimizing segment weights based on a model in which leaf transport is ignored results in an improperly optimized plan with overdosing of target and critical structures. A method of rapidly calculating the bremsstrahlung contribution is presented and shown to be an efficient solution to this problem. A homogeneous model target and a 2D breast plan are presented. The potential use of this tool in clinical planning is discussed. (author)
Energy Technology Data Exchange (ETDEWEB)
Anusionwu, Princess [Medical Physics, CancerCare Manitoba, Winnipeg Canada (Canada); Department of Physics & Astronomy, University of Manitoba, Winnipeg Canada (Canada); Alpuche Aviles, Jorge E. [Medical Physics, CancerCare Manitoba, Winnipeg Canada (Canada); Pistorius, Stephen [Medical Physics, CancerCare Manitoba, Winnipeg Canada (Canada); Department of Physics & Astronomy, University of Manitoba, Winnipeg Canada (Canada); Department of Radiology, University of Manitoba, Winnipeg (Canada)
2016-08-15
Objective: Commissioning of a Monte Carlo based electron dose calculation algorithm requires percentage depth doses (PDDs) and beam profiles which can be measured with multiple detectors. Electron dosimetry is commonly performed with cylindrical chambers but parallel plate chambers and diodes can also be used. The purpose of this study was to determine the most appropriate detector to perform the commissioning measurements. Methods: PDDs and beam profiles were measured for beams with energies ranging from 6 MeV to 15 MeV and field sizes ranging from 6 cm × 6 cm to 40 cm × 40 cm. Detectors used included diodes, cylindrical and parallel plate ionization chambers. Beam profiles were measured in water (100 cm source to surface distance) and in air (95 cm source to detector distance). Results: PDDs for the cylindrical chambers were shallower (1.3 mm averaged over all energies and field sizes) than those measured with the parallel plate chambers and diodes. Surface doses measured with the diode and cylindrical chamber were on average larger by 1.6 % and 3% respectively than those of the parallel plate chamber. Profiles measured with a diode resulted in penumbra values smaller than those measured with the cylindrical chamber by 2 mm. Conclusion: The diode was selected as the most appropriate detector since PDDs agreed with those measured with parallel plate chambers (typically recommended for low energies) and results in sharper profiles. Unlike ion chambers, no corrections are needed to measure PDDs, making it more convenient to use.
Energy Technology Data Exchange (ETDEWEB)
Ma, X.B., E-mail: maxb@ncepu.edu.cn; Qiu, R.M.; Chen, Y.X.
2017-02-15
Uncertainties regarding fission fractions are essential in understanding antineutrino flux predictions in reactor antineutrino experiments. A new Monte Carlo-based method to evaluate the covariance coefficients between isotopes is proposed. The covariance coefficients are found to vary with reactor burnup and may change from positive to negative because of balance effects in fissioning. For example, between {sup 235}U and {sup 239}Pu, the covariance coefficient changes from 0.15 to −0.13. Using the equation relating fission fraction and atomic density, consistent uncertainties in the fission fraction and covariance matrix were obtained. The antineutrino flux uncertainty is 0.55%, which does not vary with reactor burnup. The new value is about 8.3% smaller. - Highlights: • The covariance coefficients between isotopes vs reactor burnup may change its sign because of two opposite effects. • The relation between fission fraction uncertainty and atomic density are first studied. • A new MC-based method of evaluating the covariance coefficients between isotopes was proposed.
Monte Carlo based dosimetry and treatment planning for neutron capture therapy of brain tumors
International Nuclear Information System (INIS)
Zamenhof, R.G.; Clement, S.D.; Harling, O.K.; Brenner, J.F.; Wazer, D.E.; Madoc-Jones, H.; Yanch, J.C.
1990-01-01
Monte Carlo based dosimetry and computer-aided treatment planning for neutron capture therapy have been developed to provide the necessary link between physical dosimetric measurements performed on the MITR-II epithermal-neutron beams and the need of the radiation oncologist to synthesize large amounts of dosimetric data into a clinically meaningful treatment plan for each individual patient. Monte Carlo simulation has been employed to characterize the spatial dose distributions within a skull/brain model irradiated by an epithermal-neutron beam designed for neutron capture therapy applications. The geometry and elemental composition employed for the mathematical skull/brain model and the neutron and photon fluence-to-dose conversion formalism are presented. A treatment planning program, NCTPLAN, developed specifically for neutron capture therapy, is described. Examples are presented illustrating both one and two-dimensional dose distributions obtainable within the brain with an experimental epithermal-neutron beam, together with beam quality and treatment plan efficacy criteria which have been formulated for neutron capture therapy. The incorporation of three-dimensional computed tomographic image data into the treatment planning procedure is illustrated. The experimental epithermal-neutron beam has a maximum usable circular diameter of 20 cm, and with 30 ppm of B-10 in tumor and 3 ppm of B-10 in blood, it produces a beam-axis advantage depth of 7.4 cm, a beam-axis advantage ratio of 1.83, a global advantage ratio of 1.70, and an advantage depth RBE-dose rate to tumor of 20.6 RBE-cGy/min (cJ/kg-min). These characteristics make this beam well suited for clinical applications, enabling an RBE-dose of 2,000 RBE-cGy/min (cJ/kg-min) to be delivered to tumor at brain midline in six fractions with a treatment time of approximately 16 minutes per fraction
A Monte Carlo-based model for simulation of digital chest tomo-synthesis
International Nuclear Information System (INIS)
Ullman, G.; Dance, D. R.; Sandborg, M.; Carlsson, G. A.; Svalkvist, A.; Baath, M.
2010-01-01
The aim of this work was to calculate synthetic digital chest tomo-synthesis projections using a computer simulation model based on the Monte Carlo method. An anthropomorphic chest phantom was scanned in a computed tomography scanner, segmented and included in the computer model to allow for simulation of realistic high-resolution X-ray images. The input parameters to the model were adapted to correspond to the VolumeRAD chest tomo-synthesis system from GE Healthcare. Sixty tomo-synthesis projections were calculated with projection angles ranging from + 15 to -15 deg. The images from primary photons were calculated using an analytical model of the anti-scatter grid and a pre-calculated detector response function. The contributions from scattered photons were calculated using an in-house Monte Carlo-based model employing a number of variance reduction techniques such as the collision density estimator. Tomographic section images were reconstructed by transferring the simulated projections into the VolumeRAD system. The reconstruction was performed for three types of images using: (i) noise-free primary projections, (ii) primary projections including contributions from scattered photons and (iii) projections as in (ii) with added correlated noise. The simulated section images were compared with corresponding section images from projections taken with the real, anthropomorphic phantom from which the digital voxel phantom was originally created. The present article describes a work in progress aiming towards developing a model intended for optimisation of chest tomo-synthesis, allowing for simulation of both existing and future chest tomo-synthesis systems. (authors)
Response matrix Monte Carlo based on a general geometry local calculation for electron transport
International Nuclear Information System (INIS)
Ballinger, C.T.; Rathkopf, J.A.; Martin, W.R.
1991-01-01
A Response Matrix Monte Carlo (RMMC) method has been developed for solving electron transport problems. This method was born of the need to have a reliable, computationally efficient transport method for low energy electrons (below a few hundred keV) in all materials. Today, condensed history methods are used which reduce the computation time by modeling the combined effect of many collisions but fail at low energy because of the assumptions required to characterize the electron scattering. Analog Monte Carlo simulations are prohibitively expensive since electrons undergo coulombic scattering with little state change after a collision. The RMMC method attempts to combine the accuracy of an analog Monte Carlo simulation with the speed of the condensed history methods. Like condensed history, the RMMC method uses probability distributions functions (PDFs) to describe the energy and direction of the electron after several collisions. However, unlike the condensed history method the PDFs are based on an analog Monte Carlo simulation over a small region. Condensed history theories require assumptions about the electron scattering to derive the PDFs for direction and energy. Thus the RMMC method samples from PDFs which more accurately represent the electron random walk. Results show good agreement between the RMMC method and analog Monte Carlo. 13 refs., 8 figs
Directory of Open Access Journals (Sweden)
N Heidarloo
2017-08-01
Full Text Available Intraoperative electron radiotherapy is one of the radiotherapy methods that delivers a high single fraction of radiation dose to the patient in one session during the surgery. Beam shaper applicator is one of the applicators that is recently employed with this radiotherapy method. This applicator has a considerable application in treatment of large tumors. In this study, the dosimetric characteristics of the electron beam produced by LIAC intraoperative radiotherapy accelerator in conjunction with this applicator have been evaluated through Monte Carlo simulation by MCNP code. The results showed that the electron beam produced by the beam shaper applicator would have the desirable dosimetric characteristics, so that the mentioned applicator can be considered for clinical purposes. Furthermore, the good agreement between the results of simulation and practical dosimetry, confirms the applicability of Monte Carlo method in determining the dosimetric parameters of electron beam intraoperative radiotherapy
Design and evaluation of a Monte Carlo based model of an orthovoltage treatment system
International Nuclear Information System (INIS)
Penchev, Petar; Maeder, Ulf; Fiebich, Martin; Zink, Klemens; University Hospital Marburg
2015-01-01
The aim of this study was to develop a flexible framework of an orthovoltage treatment system capable of calculating and visualizing dose distributions in different phantoms and CT datasets. The framework provides a complete set of various filters, applicators and X-ray energies and therefore can be adapted to varying studies or be used for educational purposes. A dedicated user friendly graphical interface was developed allowing for easy setup of the simulation parameters and visualization of the results. For the Monte Carlo simulations the EGSnrc Monte Carlo code package was used. Building the geometry was accomplished with the help of the EGSnrc C++ class library. The deposited dose was calculated according to the KERMA approximation using the track-length estimator. The validation against measurements showed a good agreement within 4-5% deviation, down to depths of 20% of the depth dose maximum. Furthermore, to show its capabilities, the validated model was used to calculate the dose distribution on two CT datasets. Typical Monte Carlo calculation time for these simulations was about 10 minutes achieving an average statistical uncertainty of 2% on a standard PC. However, this calculation time depends strongly on the used CT dataset, tube potential, filter material/thickness and applicator size.
CARMEN: a system Monte Carlo based on linear programming from direct openings
International Nuclear Information System (INIS)
Ureba, A.; Pereira-Barbeiro, A. R.; Jimenez-Ortega, E.; Baeza, J. A.; Salguero, F. J.; Leal, A.
2013-01-01
The use of Monte Carlo (MC) has shown an improvement in the accuracy of the calculation of the dose compared to other analytics algorithms installed on the systems of business planning, especially in the case of non-standard situations typical of complex techniques such as IMRT and VMAT. Our treatment planning system called CARMEN, is based on the complete simulation, both the beam transport in the head of the accelerator and the patient, and simulation designed for efficient operation in terms of the accuracy of the estimate and the required computation times. (Author)
Determination of the spatial response of neutron based analysers using a Monte Carlo based method
International Nuclear Information System (INIS)
Tickner, James
2000-01-01
One of the principal advantages of using thermal neutron capture (TNC, also called prompt gamma neutron activation analysis or PGNAA) or neutron inelastic scattering (NIS) techniques for measuring elemental composition is the high penetrating power of both the incident neutrons and the resultant gamma-rays, which means that large sample volumes can be interrogated. Gauges based on these techniques are widely used in the mineral industry for on-line determination of the composition of bulk samples. However, attenuation of both neutrons and gamma-rays in the sample and geometric (source/detector distance) effects typically result in certain parts of the sample contributing more to the measured composition than others. In turn, this introduces errors in the determination of the composition of inhomogeneous samples. This paper discusses a combined Monte Carlo/analytical method for estimating the spatial response of a neutron gauge. Neutron propagation is handled using a Monte Carlo technique which allows an arbitrarily complex neutron source and gauge geometry to be specified. Gamma-ray production and detection is calculated analytically which leads to a dramatic increase in the efficiency of the method. As an example, the method is used to study ways of reducing the spatial sensitivity of on-belt composition measurements of cement raw meal
Monte-Carlo-based uncertainty propagation with hierarchical models—a case study in dynamic torque
Klaus, Leonard; Eichstädt, Sascha
2018-04-01
For a dynamic calibration, a torque transducer is described by a mechanical model, and the corresponding model parameters are to be identified from measurement data. A measuring device for the primary calibration of dynamic torque, and a corresponding model-based calibration approach, have recently been developed at PTB. The complete mechanical model of the calibration set-up is very complex, and involves several calibration steps—making a straightforward implementation of a Monte Carlo uncertainty evaluation tedious. With this in mind, we here propose to separate the complete model into sub-models, with each sub-model being treated with individual experiments and analysis. The uncertainty evaluation for the overall model then has to combine the information from the sub-models in line with Supplement 2 of the Guide to the Expression of Uncertainty in Measurement. In this contribution, we demonstrate how to carry this out using the Monte Carlo method. The uncertainty evaluation involves various input quantities of different origin and the solution of a numerical optimisation problem.
Monte Carlo based electron treatment planning and cutout output factor calculations
Mitrou, Ellis
Electron radiotherapy (RT) offers a number of advantages over photons. The high surface dose, combined with a rapid dose fall-off beyond the target volume presents a net increase in tumor control probability and decreases the normal tissue complication for superficial tumors. Electron treatments are normally delivered clinically without previously calculated dose distributions due to the complexity of the electron transport involved and greater error in planning accuracy. This research uses Monte Carlo (MC) methods to model clinical electron beams in order to accurately calculate electron beam dose distributions in patients as well as calculate cutout output factors, reducing the need for a clinical measurement. The present work is incorporated into a research MC calculation system: McGill Monte Carlo Treatment Planning (MMCTP) system. Measurements of PDDs, profiles and output factors in addition to 2D GAFCHROMICRTM EBT2 film measurements in heterogeneous phantoms were obtained to commission the electron beam model. The use of MC for electron TP will provide more accurate treatments and yield greater knowledge of the electron dose distribution within the patient. The calculation of output factors could invoke a clinical time saving of up to 1 hour per patient.
The specific bias in dynamic Monte Carlo simulations of nuclear reactors
International Nuclear Information System (INIS)
Yamamoto, T.; Endo, H.; Ishizu, T.; Tatewaki, I.
2013-01-01
During the development of Monte-Carlo-based dynamic code system, we have encountered two major Monte-Carlo-specific problems. One is the break down due to 'false super-criticality' which is caused by an accidentally large eigenvalue due to statistical error in spite of the fact that the reactor is actually not critical. The other problem, which is the main topic in this paper, is that the statistical error in power level using the reactivity calculated with Monte Carlo code is not symmetric about its mean but always positively biased. This signifies that the bias is accumulated as the calculation proceeds and consequently results in an over-estimation of the final power level. It should be noted that the bias will not be eliminated by refining the time step as long as the variance is not zero. A preliminary investigation on this matter using the one-group-precursor point kinetic equations was made and it was concluded that the bias in power level is approximately proportional to the product of variance in Monte Carlo calculation and elapsed time. This conclusion was verified with some numerical experiments. This outcome is important in quantifying the required precision of the Monte-Carlo-based reactivity calculations. (authors)
PELE: Protein Energy Landscape Exploration. A Novel Monte Carlo Based Technique.
Borrelli, Kenneth W; Vitalis, Andreas; Alcantara, Raul; Guallar, Victor
2005-11-01
Combining protein structure prediction algorithms and Metropolis Monte Carlo techniques, we provide a novel method to explore all-atom energy landscapes. The core of the technique is based on a steered localized perturbation followed by side-chain sampling as well as minimization cycles. The algorithm and its application to ligand diffusion are presented here. Ligand exit pathways are successfully modeled for different systems containing ligands of various sizes: carbon monoxide in myoglobin, camphor in cytochrome P450cam, and palmitic acid in the intestinal fatty-acid-binding protein. These initial applications reveal the potential of this new technique in mapping millisecond-time-scale processes. The computational cost associated with the exploration is significantly less than that of conventional MD simulations.
Monte Carlo based statistical power analysis for mediation models: methods and software.
Zhang, Zhiyong
2014-12-01
The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.
Monte Carlo based geometrical model for efficiency calculation of an n-type HPGe detector
Energy Technology Data Exchange (ETDEWEB)
Padilla Cabal, Fatima, E-mail: fpadilla@instec.c [Instituto Superior de Tecnologias y Ciencias Aplicadas, ' Quinta de los Molinos' Ave. Salvador Allende, esq. Luaces, Plaza de la Revolucion, Ciudad de la Habana, CP 10400 (Cuba); Lopez-Pino, Neivy; Luis Bernal-Castillo, Jose; Martinez-Palenzuela, Yisel; Aguilar-Mena, Jimmy; D' Alessandro, Katia; Arbelo, Yuniesky; Corrales, Yasser; Diaz, Oscar [Instituto Superior de Tecnologias y Ciencias Aplicadas, ' Quinta de los Molinos' Ave. Salvador Allende, esq. Luaces, Plaza de la Revolucion, Ciudad de la Habana, CP 10400 (Cuba)
2010-12-15
A procedure to optimize the geometrical model of an n-type detector is described. Sixteen lines from seven point sources ({sup 241}Am, {sup 133}Ba, {sup 22}Na, {sup 60}Co, {sup 57}Co, {sup 137}Cs and {sup 152}Eu) placed at three different source-to-detector distances (10, 20 and 30 cm) were used to calibrate a low-background gamma spectrometer between 26 and 1408 keV. Direct Monte Carlo techniques using the MCNPX 2.6 and GEANT 4 9.2 codes, and a semi-empirical procedure were performed to obtain theoretical efficiency curves. Since discrepancies were found between experimental and calculated data using the manufacturer parameters of the detector, a detail study of the crystal dimensions and the geometrical configuration is carried out. The relative deviation with experimental data decreases from a mean value of 18-4%, after the parameters were optimized.
A Monte Carlo-based treatment-planning tool for ion beam therapy
Böhlen, T T; Dosanjh, M; Ferrari, A; Haberer, T; Parodi, K; Patera, V; Mairan, A
2013-01-01
Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), theMCTP tool is able to perform TP studies u...
Experimental validation of a rapid Monte Carlo based micro-CT simulator
International Nuclear Information System (INIS)
Colijn, A P; Zbijewski, W; Sasov, A; Beekman, F J
2004-01-01
We describe a newly developed, accelerated Monte Carlo simulator of a small animal micro-CT scanner. Transmission measurements using aluminium slabs are employed to estimate the spectrum of the x-ray source. The simulator incorporating this spectrum is validated with micro-CT scans of physical water phantoms of various diameters, some containing stainless steel and Teflon rods. Good agreement is found between simulated and real data: normalized error of simulated projections, as compared to the real ones, is typically smaller than 0.05. Also the reconstructions obtained from simulated and real data are found to be similar. Thereafter, effects of scatter are studied using a voxelized software phantom representing a rat body. It is shown that the scatter fraction can reach tens of per cents in specific areas of the body and therefore scatter can significantly affect quantitative accuracy in small animal CT imaging
Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator
Bol, G. H.; Hissoiny, S.; Lagendijk, J. J. W.; Raaymakers, B. W.
2012-03-01
The MRI accelerator, a combination of a 6 MV linear accelerator with a 1.5 T MRI, facilitates continuous patient anatomy updates regarding translations, rotations and deformations of targets and organs at risk. Accounting for these demands high speed, online intensity-modulated radiotherapy (IMRT) re-optimization. In this paper, a fast IMRT optimization system is described which combines a GPU-based Monte Carlo dose calculation engine for online beamlet generation and a fast inverse dose optimization algorithm. Tightly conformal IMRT plans are generated for four phantom cases and two clinical cases (cervix and kidney) in the presence of the magnetic fields of 0 and 1.5 T. We show that for the presented cases the beamlet generation and optimization routines are fast enough for online IMRT planning. Furthermore, there is no influence of the magnetic field on plan quality and complexity, and equal optimization constraints at 0 and 1.5 T lead to almost identical dose distributions.
Accuracy assessment of a new Monte Carlo based burnup computer code
International Nuclear Information System (INIS)
El Bakkari, B.; ElBardouni, T.; Nacir, B.; ElYounoussi, C.; Boulaich, Y.; Meroun, O.; Zoubair, M.; Chakir, E.
2012-01-01
Highlights: ► A new burnup code called BUCAL1 was developed. ► BUCAL1 uses the MCNP tallies directly in the calculation of the isotopic inventories. ► Validation of BUCAL1 was done by code to code comparison using VVER-1000 LEU Benchmark Assembly. ► Differences from BM value were found to be ± 600 pcm for k ∞ and ±6% for the isotopic compositions. ► The effect on reactivity due to the burnup of Gd isotopes is well reproduced by BUCAL1. - Abstract: This study aims to test for the suitability and accuracy of a new home-made Monte Carlo burnup code, called BUCAL1, by investigating and predicting the neutronic behavior of a “VVER-1000 LEU Assembly Computational Benchmark”, at lattice level. BUCAL1 uses MCNP tally information directly in the computation; this approach allows performing straightforward and accurate calculation without having to use the calculated group fluxes to perform transmutation analysis in a separate code. ENDF/B-VII evaluated nuclear data library was used in these calculations. Processing of the data library is performed using recent updates of NJOY99 system. Code to code comparisons with the reported Nuclear OECD/NEA results are presented and analyzed.
Energy Technology Data Exchange (ETDEWEB)
Saha, Krishnendu [Ohio Medical Physics Consulting, Dublin, Ohio 43017 (United States); Straus, Kenneth J.; Glick, Stephen J. [Department of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655 (United States); Chen, Yu. [Department of Radiation Oncology, Columbia University, New York, New York 10032 (United States)
2014-08-28
To maximize sensitivity, it is desirable that ring Positron Emission Tomography (PET) systems dedicated for imaging the breast have a small bore. Unfortunately, due to parallax error this causes substantial degradation in spatial resolution for objects near the periphery of the breast. In this work, a framework for computing and incorporating an accurate system matrix into iterative reconstruction is presented in an effort to reduce spatial resolution degradation towards the periphery of the breast. The GATE Monte Carlo Simulation software was utilized to accurately model the system matrix for a breast PET system. A strategy for increasing the count statistics in the system matrix computation and for reducing the system element storage space was used by calculating only a subset of matrix elements and then estimating the rest of the elements by using the geometric symmetry of the cylindrical scanner. To implement this strategy, polar voxel basis functions were used to represent the object, resulting in a block-circulant system matrix. Simulation studies using a breast PET scanner model with ring geometry demonstrated improved contrast at 45% reduced noise level and 1.5 to 3 times resolution performance improvement when compared to MLEM reconstruction using a simple line-integral model. The GATE based system matrix reconstruction technique promises to improve resolution and noise performance and reduce image distortion at FOV periphery compared to line-integral based system matrix reconstruction.
Monte Carlo based water/medium stopping-power ratios for various ICRP and ICRU tissues
International Nuclear Information System (INIS)
Fernandez-Varea, Jose M; Carrasco, Pablo; Panettieri, Vanessa; Brualla, Lorenzo
2007-01-01
Water/medium stopping-power ratios, s w,m , have been calculated for several ICRP and ICRU tissues, namely adipose tissue, brain, cortical bone, liver, lung (deflated and inflated) and spongiosa. The considered clinical beams were 6 and 18 MV x-rays and the field size was 10 x 10 cm 2 . Fluence distributions were scored at a depth of 10 cm using the Monte Carlo code PENELOPE. The collision stopping powers for the studied tissues were evaluated employing the formalism of ICRU Report 37 (1984 Stopping Powers for Electrons and Positrons (Bethesda, MD: ICRU)). The Bragg-Gray values of s w,m calculated with these ingredients range from about 0.98 (adipose tissue) to nearly 1.14 (cortical bone), displaying a rather small variation with beam quality. Excellent agreement, to within 0.1%, is found with stopping-power ratios reported by Siebers et al (2000a Phys. Med. Biol. 45 983-95) for cortical bone, inflated lung and spongiosa. In the case of cortical bone, s w,m changes approximately 2% when either ICRP or ICRU compositions are adopted, whereas the stopping-power ratios of lung, brain and adipose tissue are less sensitive to the selected composition. The mass density of lung also influences the calculated values of s w,m , reducing them by around 1% (6 MV) and 2% (18 MV) when going from deflated to inflated lung
Cost-effectiveness of targeted screening for abdominal aortic aneurysm. Monte Carlo-based estimates.
Pentikäinen, T J; Sipilä, T; Rissanen, P; Soisalon-Soininen, S; Salo, J
2000-01-01
This article reports a cost-effectiveness analysis of targeted screening for abdominal aortic aneurysm (AAA). A major emphasis was on the estimation of distributions of costs and effectiveness. We performed a Monte Carlo simulation using C programming language in a PC environment. Data on survival and costs, and a majority of screening probabilities, were from our own empirical studies. Natural history data were based on the literature. Each screened male gained 0.07 life-years at an incremental cost of FIM 3,300. The expected values differed from zero very significantly. For females, expected gains were 0.02 life-years at an incremental cost of FIM 1,100, which was not statistically significant. Cost-effectiveness ratios and their 95% confidence intervals were FIM 48,000 (27,000-121,000) and 54,000 (22,000-infinity) for males and females, respectively. Sensitivity analysis revealed that the results for males were stable. Individual variation in life-year gains was high. Males seemed to benefit from targeted AAA screening, and the results were stable. As far as the cost-effectiveness ratio is considered acceptable, screening for males seemed to be justified. However, our assumptions about growth and rupture behavior of AAAs might be improved with further clinical and epidemiological studies. As a point estimate, females benefited in a similar manner, but the results were not statistically significant. The evidence of this study did not justify screening of females.
Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning
International Nuclear Information System (INIS)
Chetty, Indrin J.; Rosu, Mihaela; Kessler, Marc L.; Fraass, Benedick A.; Haken, Randall K. ten; Kong, Feng-Ming; McShan, Daniel L.
2006-01-01
Purpose: To investigate methods of reporting and analyzing statistical uncertainties in doses to targets and normal tissues in Monte Carlo (MC)-based treatment planning. Methods and Materials: Methods for quantifying statistical uncertainties in dose, such as uncertainty specification to specific dose points, or to volume-based regions, were analyzed in MC-based treatment planning for 5 lung cancer patients. The effect of statistical uncertainties on target and normal tissue dose indices was evaluated. The concept of uncertainty volume histograms for targets and organs at risk was examined, along with its utility, in conjunction with dose volume histograms, in assessing the acceptability of the statistical precision in dose distributions. The uncertainty evaluation tools were extended to four-dimensional planning for application on multiple instances of the patient geometry. All calculations were performed using the Dose Planning Method MC code. Results: For targets, generalized equivalent uniform doses and mean target doses converged at 150 million simulated histories, corresponding to relative uncertainties of less than 2% in the mean target doses. For the normal lung tissue (a volume-effect organ), mean lung dose and normal tissue complication probability converged at 150 million histories despite the large range in the relative organ uncertainty volume histograms. For 'serial' normal tissues such as the spinal cord, large fluctuations exist in point dose relative uncertainties. Conclusions: The tools presented here provide useful means for evaluating statistical precision in MC-based dose distributions. Tradeoffs between uncertainties in doses to targets, volume-effect organs, and 'serial' normal tissues must be considered carefully in determining acceptable levels of statistical precision in MC-computed dose distributions
TH-E-BRE-08: GPU-Monte Carlo Based Fast IMRT Plan Optimization
Energy Technology Data Exchange (ETDEWEB)
Li, Y; Tian, Z; Shi, F; Jiang, S; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)
2014-06-15
Purpose: Intensity-modulated radiation treatment (IMRT) plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC) methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow. Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, rough beamlet dose calculations is conducted with only a small number of particles per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final Result. Results: For a lung case with 5317 beamlets, 10{sup 5} particles per beamlet in the first round, and 10{sup 8} particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec. Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.
Kirkby, Charles; Ghasroddashti, Esmaeel; Kovalchuk, Anna; Kolb, Bryan; Kovalchuk, Olga
2013-09-01
In radiation biology, rats are often irradiated, but the precise dose distributions are often lacking, particularly in areas that receive scatter radiation. We used a non-dedicated set of resources to calculate detailed dose distributions, including doses to peripheral organs well outside of the primary field, in common rat exposure settings. We conducted a detailed dose reconstruction in a rat through an analog to the conventional human treatment planning process. The process consisted of: (i) Characterizing source properties of an X-ray irradiator system, (ii) acquiring a computed tomography (CT) scan of a rat model, and (iii) using a Monte Carlo (MC) dose calculation engine to generate the dose distribution within the rat model. We considered cranial and liver irradiation scenarios where the rest of the body was protected by a lead shield. Organs of interest were the brain, liver and gonads. The study also included paired scenarios where the dose to adjacent, shielded rats was determined as a potential control for analysis of bystander effects. We established the precise doses and dose distributions delivered to the peripheral organs in single and paired rats. Mean doses to non-targeted organs in irradiated rats ranged from 0.03-0.1% of the reference platform dose. Mean doses to the adjacent rat peripheral organs were consistent to within 10% those of the directly irradiated rat. This work provided details of dose distributions in rat models under common irradiation conditions and established an effective scenario for delivering only scattered radiation consistent with that in a directly irradiated rat.
International Nuclear Information System (INIS)
Weathers, J.B.; Luck, R.; Weathers, J.W.
2009-01-01
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
Energy Technology Data Exchange (ETDEWEB)
Weathers, J.B. [Shock, Noise, and Vibration Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: James.Weathers@ngc.com; Luck, R. [Department of Mechanical Engineering, Mississippi State University, 210 Carpenter Engineering Building, P.O. Box ME, Mississippi State, MS 39762-5925 (United States)], E-mail: Luck@me.msstate.edu; Weathers, J.W. [Structural Analysis Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: Jeffrey.Weathers@ngc.com
2009-11-15
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun
2015-04-07
Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation
Monte Carlo-based development of a shield and total background estimation for the COBRA experiment
International Nuclear Information System (INIS)
Heidrich, Nadine
2014-11-01
The COBRA experiment aims for the measurement of the neutrinoless double beta decay and thus for the determination the effective Majorana mass of the neutrino. To be competitive with other next-generation experiments the background rate has to be in the order of 10 -3 counts/kg/keV/yr, which is a challenging criterion. This thesis deals with the development of a shield design and the calculation of the expected total background rate for the large scale COBRA experiment containing 13824 6 cm 3 CdZnTe detectors. For the development of a shield single-layer and multi-layer shields were investigated and a shield design was optimized concerning high-energy muon-induced neutrons. As the best design the combination of 10 cm boron doped polyethylene as outermost layer, 20 cm lead and 10 cm copper as innermost layer were determined. It showed the best performance regarding neutron attenuation as well as (n, γ) self-shielding effects leading to a negligible background rate of less than 2.10 -6 counts/kg/keV/yr. Additionally. the shield with a thickness of 40 cm is compact and costeffective. In the next step the expected total background rate was computed taking into account individual setup parts and various background sources including natural and man-made radioactivity, cosmic ray-induced background and thermal neutrons. Furthermore, a comparison of measured data from the COBRA demonstrator setup with Monte Carlo data was used to calculate reliable contamination levels of the single setup parts. The calculation was performed conservatively to prevent an underestimation. In addition, the contribution to the total background rate regarding the individual detector parts and background sources was investigated. The main portion arise from the Delrin support structure, the Glyptal lacquer followed by the circuit board of the high voltage supply. Most background events originate from particles with a quantity of 99 % in total. Regarding surface events a contribution of 26
Monte Carlo-based development of a shield and total background estimation for the COBRA experiment
Energy Technology Data Exchange (ETDEWEB)
Heidrich, Nadine
2014-11-15
The COBRA experiment aims for the measurement of the neutrinoless double beta decay and thus for the determination the effective Majorana mass of the neutrino. To be competitive with other next-generation experiments the background rate has to be in the order of 10{sup -3} counts/kg/keV/yr, which is a challenging criterion. This thesis deals with the development of a shield design and the calculation of the expected total background rate for the large scale COBRA experiment containing 13824 6 cm{sup 3} CdZnTe detectors. For the development of a shield single-layer and multi-layer shields were investigated and a shield design was optimized concerning high-energy muon-induced neutrons. As the best design the combination of 10 cm boron doped polyethylene as outermost layer, 20 cm lead and 10 cm copper as innermost layer were determined. It showed the best performance regarding neutron attenuation as well as (n, γ) self-shielding effects leading to a negligible background rate of less than 2.10{sup -6} counts/kg/keV/yr. Additionally. the shield with a thickness of 40 cm is compact and costeffective. In the next step the expected total background rate was computed taking into account individual setup parts and various background sources including natural and man-made radioactivity, cosmic ray-induced background and thermal neutrons. Furthermore, a comparison of measured data from the COBRA demonstrator setup with Monte Carlo data was used to calculate reliable contamination levels of the single setup parts. The calculation was performed conservatively to prevent an underestimation. In addition, the contribution to the total background rate regarding the individual detector parts and background sources was investigated. The main portion arise from the Delrin support structure, the Glyptal lacquer followed by the circuit board of the high voltage supply. Most background events originate from particles with a quantity of 99 % in total. Regarding surface events a
A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system.
Ma, Jiasen; Beltran, Chris; Seum Wan Chan Tseung, Hok; Herman, Michael G
2014-12-01
Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. For relatively large and complex three-field head and neck cases, i.e., >100,000 spots with a target volume of ∼ 1000 cm(3) and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45,000 dollars. The fast calculation and
A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system
Energy Technology Data Exchange (ETDEWEB)
Ma, Jiasen, E-mail: ma.jiasen@mayo.edu; Beltran, Chris; Seum Wan Chan Tseung, Hok; Herman, Michael G. [Department of Radiation Oncology, Division of Medical Physics, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States)
2014-12-15
Purpose: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. Methods: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. Results: For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm{sup 3} and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. Conclusions: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45
Monte Carlo-based QA for IMRT of head and neck cancers
Tang, F.; Sham, J.; Ma, C.-M.; Li, J.-S.
2007-06-01
It is well-known that the presence of large air cavity in a dense medium (or patient) introduces significant electronic disequilibrium when irradiated with megavoltage X-ray field. This condition may worsen by the possible use of tiny beamlets in intensity-modulated radiation therapy (IMRT). Commercial treatment planning systems (TPSs), in particular those based on the pencil-beam method, do not provide accurate dose computation for the lungs and other cavity-laden body sites such as the head and neck. In this paper we present the use of Monte Carlo (MC) technique for dose re-calculation of IMRT of head and neck cancers. In our clinic, a turn-key software system is set up for MC calculation and comparison with TPS-calculated treatment plans as part of the quality assurance (QA) programme for IMRT delivery. A set of 10 off-the-self PCs is employed as the MC calculation engine with treatment plan parameters imported from the TPS via a graphical user interface (GUI) which also provides a platform for launching remote MC simulation and subsequent dose comparison with the TPS. The TPS-segmented intensity maps are used as input for the simulation hence skipping the time-consuming simulation of the multi-leaf collimator (MLC). The primary objective of this approach is to assess the accuracy of the TPS calculations in the presence of air cavities in the head and neck whereas the accuracy of leaf segmentation is verified by fluence measurement using a fluoroscopic camera-based imaging device. This measurement can also validate the correct transfer of intensity maps to the record and verify system. Comparisons between TPS and MC calculations of 6 MV IMRT for typical head and neck treatments review regional consistency in dose distribution except at and around the sinuses where our pencil-beam-based TPS sometimes over-predicts the dose by up to 10%, depending on the size of the cavities. In addition, dose re-buildup of up to 4% is observed at the posterior nasopharyngeal
Development of a hybrid multi-scale phantom for Monte-Carlo based internal dosimetry
International Nuclear Information System (INIS)
Marcatili, S.; Villoing, D.; Bardies, M.
2015-01-01
Full text of publication follows. Aim: in recent years several phantoms were developed for radiopharmaceutical dosimetry in clinical and preclinical settings. Voxel-based models (Zubal, Max/Fax, ICRP110) were developed to reach a level of realism that could not be achieved by mathematical models. In turn, 'hybrid' models (XCAT, MOBY/ROBY, Mash/Fash) allow a further degree of versatility by offering the possibility to finely tune each model according to various parameters. However, even 'hybrid' models require the generation of a voxel version for Monte-Carlo modeling of radiation transport. Since absorbed dose simulation time is strictly related to geometry spatial sampling, a compromise should be made between phantom realism and simulation speed. This trade-off leads on one side in an overestimation of the size of small radiosensitive structures such as the skin or hollow organs' walls, and on the other hand to unnecessarily detailed voxellization of large, homogeneous structures. The Aim of this work is to develop a hybrid multi-resolution phantom model for Geant4 and Gate, to better characterize energy deposition in small structures while preserving reasonable computation times. Materials and Methods: we have developed a pipeline for the conversion of preexisting phantoms into a multi-scale Geant4 model. Meshes of each organ are created from raw binary images of a phantom and then voxellized to the smallest spatial sampling required by the user. The user can then decide to re-sample the internal part of each organ, while leaving a layer of smallest voxels at the edge of the organ. In this way, the realistic shape of the organ is maintained while reducing the voxel number in the inner part. For hollow organs, the wall is always modeled using the smallest voxel sampling. This approach allows choosing different voxel resolutions for each organ according to a specific application. Results: preliminary results show that it is possible to
Monte Carlo-based treatment planning system calculation engine for microbeam radiation therapy.
Martinez-Rovira, I; Sempau, J; Prezado, Y
2012-05-01
Microbeam radiation therapy (MRT) is a synchrotron radiotherapy technique that explores the limits of the dose-volume effect. Preclinical studies have shown that MRT irradiations (arrays of 25-75-μm-wide microbeams spaced by 200-400 μm) are able to eradicate highly aggressive animal tumor models while healthy tissue is preserved. These promising results have provided the basis for the forthcoming clinical trials at the ID17 Biomedical Beamline of the European Synchrotron Radiation Facility (ESRF). The first step includes irradiation of pets (cats and dogs) as a milestone before treatment of human patients. Within this context, accurate dose calculations are required. The distinct features of both beam generation and irradiation geometry in MRT with respect to conventional techniques require the development of a specific MRT treatment planning system (TPS). In particular, a Monte Carlo (MC)-based calculation engine for the MRT TPS has been developed in this work. Experimental verification in heterogeneous phantoms and optimization of the computation time have also been performed. The penelope/penEasy MC code was used to compute dose distributions from a realistic beam source model. Experimental verification was carried out by means of radiochromic films placed within heterogeneous slab-phantoms. Once validation was completed, dose computations in a virtual model of a patient, reconstructed from computed tomography (CT) images, were performed. To this end, decoupling of the CT image voxel grid (a few cubic millimeter volume) to the dose bin grid, which has micrometer dimensions in the transversal direction of the microbeams, was performed. Optimization of the simulation parameters, the use of variance-reduction (VR) techniques, and other methods, such as the parallelization of the simulations, were applied in order to speed up the dose computation. Good agreement between MC simulations and experimental results was achieved, even at the interfaces between two
Monte Carlo-based treatment planning system calculation engine for microbeam radiation therapy
Energy Technology Data Exchange (ETDEWEB)
Martinez-Rovira, I.; Sempau, J.; Prezado, Y. [Institut de Tecniques Energetiques, Universitat Politecnica de Catalunya, Diagonal 647, Barcelona E-08028 (Spain) and ID17 Biomedical Beamline, European Synchrotron Radiation Facility (ESRF), 6 rue Jules Horowitz B.P. 220, F-38043 Grenoble Cedex (France); Institut de Tecniques Energetiques, Universitat Politecnica de Catalunya, Diagonal 647, Barcelona E-08028 (Spain); Laboratoire Imagerie et modelisation en neurobiologie et cancerologie, UMR8165, Centre National de la Recherche Scientifique (CNRS), Universites Paris 7 et Paris 11, Bat 440., 15 rue Georges Clemenceau, F-91406 Orsay Cedex (France)
2012-05-15
Purpose: Microbeam radiation therapy (MRT) is a synchrotron radiotherapy technique that explores the limits of the dose-volume effect. Preclinical studies have shown that MRT irradiations (arrays of 25-75-{mu}m-wide microbeams spaced by 200-400 {mu}m) are able to eradicate highly aggressive animal tumor models while healthy tissue is preserved. These promising results have provided the basis for the forthcoming clinical trials at the ID17 Biomedical Beamline of the European Synchrotron Radiation Facility (ESRF). The first step includes irradiation of pets (cats and dogs) as a milestone before treatment of human patients. Within this context, accurate dose calculations are required. The distinct features of both beam generation and irradiation geometry in MRT with respect to conventional techniques require the development of a specific MRT treatment planning system (TPS). In particular, a Monte Carlo (MC)-based calculation engine for the MRT TPS has been developed in this work. Experimental verification in heterogeneous phantoms and optimization of the computation time have also been performed. Methods: The penelope/penEasy MC code was used to compute dose distributions from a realistic beam source model. Experimental verification was carried out by means of radiochromic films placed within heterogeneous slab-phantoms. Once validation was completed, dose computations in a virtual model of a patient, reconstructed from computed tomography (CT) images, were performed. To this end, decoupling of the CT image voxel grid (a few cubic millimeter volume) to the dose bin grid, which has micrometer dimensions in the transversal direction of the microbeams, was performed. Optimization of the simulation parameters, the use of variance-reduction (VR) techniques, and other methods, such as the parallelization of the simulations, were applied in order to speed up the dose computation. Results: Good agreement between MC simulations and experimental results was achieved, even at
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
Mastrogiuseppe, M.; Hayes, A. G.; Poggiali, V.; Lunine, J. I.; Lorenz, R. D.; Seu, R.; Le Gall, A.; Notarnicola, C.; Mitchell, K. L.; Malaska, M.; Birch, S. P. D.
2018-01-01
Recently, the Cassini RADAR was used to sound hydrocarbon lakes and seas on Saturn's moon Titan. Since the initial discovery of echoes from the seabed of Ligeia Mare, the second largest liquid body on Titan, a dedicated radar processing chain has been developed to retrieve liquid depth and microwave absorptivity information from RADAR altimetry of Titan's lakes and seas. Herein, we apply this processing chain to altimetry data acquired over southern Ontario Lacus during Titan fly-by T49 in December 2008. The new signal processing chain adopts super resolution techniques and dedicated taper functions to reveal the presence of reflection from Ontario's lakebed. Unfortunately, the extracted waveforms from T49 are often distorted due to signal saturation, owing to the extraordinarily strong specular reflections from the smooth lake surface. This distortion is a function of the saturation level and can introduce artifacts, such as signal precursors, which complicate data interpretation. We use a radar altimetry simulator to retrieve information from the saturated bursts and determine the liquid depth and loss tangent of Ontario Lacus. Received waveforms are represented using a two-layer model, where Cassini raw radar data are simulated in order to reproduce the effects of receiver saturation. A Monte Carlo based approach along with a simulated waveform look-up table is used to retrieve parameters that are given as inputs to a parametric model which constrains radio absorption of Ontario Lacus and retrieves information about the dielectric properties of the liquid. We retrieve a maximum depth of 50 m along the radar transect and a best-fit specific attenuation of the liquid equal to 0.2 ± 0.09 dB m-1 that, when converted into loss tangent, gives tanδ = 7 ± 3 × 10-5. When combined with laboratory measured cryogenic liquid alkane dielectric properties and the variable solubility of nitrogen in ethane-methane mixtures, the best-fit loss tangent is consistent with a
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
Angular biasing in implicit Monte-Carlo
International Nuclear Information System (INIS)
Zimmerman, G.B.
1994-01-01
Calculations of indirect drive Inertial Confinement Fusion target experiments require an integrated approach in which laser irradiation and radiation transport in the hohlraum are solved simultaneously with the symmetry, implosion and burn of the fuel capsule. The Implicit Monte Carlo method has proved to be a valuable tool for the two dimensional radiation transport within the hohlraum, but the impact of statistical noise on the symmetric implosion of the small fuel capsule is difficult to overcome. We present an angular biasing technique in which an increased number of low weight photons are directed at the imploding capsule. For typical parameters this reduces the required computer time for an integrated calculation by a factor of 10. An additional factor of 5 can also be achieved by directing even smaller weight photons at the polar regions of the capsule where small mass zones are most sensitive to statistical noise
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
International Nuclear Information System (INIS)
Ding, Y.; Arai, K.
2007-01-01
A method for estimation of forest parameters, species, tree shape, distance between canopies by means of Monte-Carlo based radiative transfer model with forestry surface model is proposed. The model is verified through experiments with the miniature model of forest, tree array of relatively small size of trees. Two types of miniature trees, ellipse-looking and cone-looking canopy are examined in the experiments. It is found that the proposed model and experimental results show a coincidence so that the proposed method is validated. It is also found that estimation of tree shape, trunk tree distance as well as distinction between deciduous or coniferous trees can be done with the proposed model. Furthermore, influences due to multiple reflections between trees and interaction between trees and under-laying grass are clarified with the proposed method
International Nuclear Information System (INIS)
Tippayakul, Chanatip; Ivanov, Kostadin; Frederick Sears, C.
2008-01-01
A practical fuel management system for the he Pennsylvania State University Breazeale Research Reactor (PSBR) based on the advanced Monte Carlo methodology was developed from the existing fuel management tool in this research. Several modeling improvements were implemented to the old system. The improved fuel management system can now utilize the burnup dependent cross section libraries generated specifically for PSBR fuel and it is also able to update the cross sections of these libraries by the Monte Carlo calculation automatically. Considerations were given to balance the computation time and the accuracy of the cross section update. Thus, certain types of a limited number of isotopes, which are considered 'important', are calculated and updated by the scheme. Moreover, the depletion algorithm of the existing fuel management tool was replaced from the predictor only to the predictor-corrector depletion scheme to account for burnup spectrum changes during the burnup step more accurately. An intermediate verification of the fuel management system was performed to assess the correctness of the newly implemented schemes against HELIOS. It was found that the agreement of both codes is good when the same energy released per fission (Q values) is used. Furthermore, to be able to model the reactor at various temperatures, the fuel management tool is able to utilize automatically the continuous cross sections generated at different temperatures. Other additional useful capabilities were also added to the fuel management tool to make it easy to use and be practical. As part of the development, a hybrid nodal diffusion/Monte Carlo calculation was devised to speed up the Monte Carlo calculation by providing more converged initial source distribution for the Monte Carlo calculation from the nodal diffusion calculation. Finally, the fuel management system was validated against the measured data using several actual PSBR core loadings. The agreement of the predicted core
International Nuclear Information System (INIS)
Mobit, P.
2002-01-01
Recent Monte Carlo simulations have shown that the assumption in the small cavity theory (and the extension of the small cavity theory by Spencer-Attix) that the cavity does not perturb the electron fluence is seriously flawed. For depths beyond d max not only is there a significant difference between the energy spectra in the medium and in the solid cavity materials but there is also a significant difference in the number of low-energy electrons which cannot travel across the solid cavity and hence deposit their dose in it (i.e. stopper electrons whose residual range is less than the cavity thickness). The number of these low-energy electrons that are not able to travel across the solid state cavity increases with depth and effective thickness of the detector. This also invalidates the assumption in the small cavity theory that most of the dose deposited in a small cavity is delivered by crossers. Based on Monte Carlo simulations, a new cavity theory for solid state detectors irradiated in electron beams has been proposed as: D med (p)=D det (p) x s S-A med.det x gamma(p) e x S T , where D med (p) is the dose to the medium at point, p, D det (p) is the average detector dose to the same point, s S-A med.det is the Spencer-Attix mass collision stopping power ratio of the medium to the detector material, gamma(p) e is the electron fluence perturbation correction factor and S T is a stopper-to-crosser correction factor to correct for the dependence of the stopper-to-crosser ratio on depth and the effective cavity size. Monte Carlo simulations have been computed for all the terms in this equation. The new cavity theory has been tested against the Spencer-Attix cavity equation as the small cavity limiting case and also Monte Carlo simulations. The agreement between this new cavity theory and Monte Carlo simulations is within 0.3%. (author)
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Fujita, Y [Tokai University School of Medicine, Isehara, Kanagawa (Japan)
2015-06-15
Purpose: Intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) are techniques that are widely used for treating cancer due to better target coverage and critical structure sparing. The increasing complexity of IMRT and VMAT plans leads to decreases in dose calculation accuracy. Monte Carlo simulations are the most accurate method for the determination of dose distributions in patients. However, the simulation settings for modeling an accurate treatment head are very complex and time consuming. The purpose of this work is to report our implementation of a simple Monte Carlo simulation system in a cloud-computing environment for dosimetric verification of IMRT and VMAT plans. Methods: Monte Carlo simulations of a Varian Clinac linear accelerator were performed using the BEAMnrc code, and dose distributions were calculated using the DOSXYZnrc code. Input files for the simulations were automatically generated from DICOM RT files by the developed web application. We therefore must only upload the DICOM RT files through the web interface, and the simulations are run in the cloud. The calculated dose distributions were exported to RT Dose files that can be downloaded through the web interface. The accuracy of the calculated dose distribution was verified by dose measurements. Results: IMRT and VMAT simulations were performed and good agreement results were observed for measured and MC dose comparison. Gamma analysis with a 3% dose and 3 mm DTA criteria shows a mean gamma index value of 95% for the studied cases. Conclusion: A Monte Carlo-based dose calculation system has been successfully implemented in a cloud environment. The developed system can be used for independent dose verification of IMRT and VMAT plans in routine clinical practice. The system will also be helpful for improving accuracy in beam modeling and dose calculation in treatment planning systems. This work was supported by JSPS KAKENHI Grant Number 25861057.
International Nuclear Information System (INIS)
Fujita, Y
2015-01-01
Purpose: Intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) are techniques that are widely used for treating cancer due to better target coverage and critical structure sparing. The increasing complexity of IMRT and VMAT plans leads to decreases in dose calculation accuracy. Monte Carlo simulations are the most accurate method for the determination of dose distributions in patients. However, the simulation settings for modeling an accurate treatment head are very complex and time consuming. The purpose of this work is to report our implementation of a simple Monte Carlo simulation system in a cloud-computing environment for dosimetric verification of IMRT and VMAT plans. Methods: Monte Carlo simulations of a Varian Clinac linear accelerator were performed using the BEAMnrc code, and dose distributions were calculated using the DOSXYZnrc code. Input files for the simulations were automatically generated from DICOM RT files by the developed web application. We therefore must only upload the DICOM RT files through the web interface, and the simulations are run in the cloud. The calculated dose distributions were exported to RT Dose files that can be downloaded through the web interface. The accuracy of the calculated dose distribution was verified by dose measurements. Results: IMRT and VMAT simulations were performed and good agreement results were observed for measured and MC dose comparison. Gamma analysis with a 3% dose and 3 mm DTA criteria shows a mean gamma index value of 95% for the studied cases. Conclusion: A Monte Carlo-based dose calculation system has been successfully implemented in a cloud environment. The developed system can be used for independent dose verification of IMRT and VMAT plans in routine clinical practice. The system will also be helpful for improving accuracy in beam modeling and dose calculation in treatment planning systems. This work was supported by JSPS KAKENHI Grant Number 25861057
TH-A-19A-06: Site-Specific Comparison of Analytical and Monte Carlo Based Dose Calculations
International Nuclear Information System (INIS)
Schuemann, J; Grassberger, C; Paganetti, H; Dowdell, S
2014-01-01
Purpose: To investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict dose distributions and to verify currently used uncertainty margins in proton therapy. Methods: Dose distributions predicted by an analytical pencilbeam algorithm were compared with Monte Carlo simulations (MCS) using TOPAS. 79 complete patient treatment plans were investigated for 7 disease sites (liver, prostate, breast, medulloblastoma spine and whole brain, lung and head and neck). A total of 508 individual passively scattered treatment fields were analyzed for field specific properties. Comparisons based on target coverage indices (EUD, D95, D90 and D50) were performed. Range differences were estimated for the distal position of the 90% dose level (R90) and the 50% dose level (R50). Two-dimensional distal dose surfaces were calculated and the root mean square differences (RMSD), average range difference (ARD) and average distal dose degradation (ADD), the distance between the distal position of the 80% and 20% dose levels (R80- R20), were analyzed. Results: We found target coverage indices calculated by TOPAS to generally be around 1–2% lower than predicted by the analytical algorithm. Differences in R90 predicted by TOPAS and the planning system can be larger than currently applied range margins in proton therapy for small regions distal to the target volume. We estimate new site-specific range margins (R90) for analytical dose calculations considering total range uncertainties and uncertainties from dose calculation alone based on the RMSD. Our results demonstrate that a reduction of currently used uncertainty margins is feasible for liver, prostate and whole brain fields even without introducing MC dose calculations. Conclusion: Analytical dose calculation algorithms predict dose distributions within clinical limits for more homogeneous patients sites (liver, prostate, whole brain). However, we recommend
TH-A-19A-06: Site-Specific Comparison of Analytical and Monte Carlo Based Dose Calculations
Energy Technology Data Exchange (ETDEWEB)
Schuemann, J; Grassberger, C; Paganetti, H [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States); Dowdell, S [Illawarra Shoalhaven Local Health District, Wollongong (Australia)
2014-06-15
Purpose: To investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict dose distributions and to verify currently used uncertainty margins in proton therapy. Methods: Dose distributions predicted by an analytical pencilbeam algorithm were compared with Monte Carlo simulations (MCS) using TOPAS. 79 complete patient treatment plans were investigated for 7 disease sites (liver, prostate, breast, medulloblastoma spine and whole brain, lung and head and neck). A total of 508 individual passively scattered treatment fields were analyzed for field specific properties. Comparisons based on target coverage indices (EUD, D95, D90 and D50) were performed. Range differences were estimated for the distal position of the 90% dose level (R90) and the 50% dose level (R50). Two-dimensional distal dose surfaces were calculated and the root mean square differences (RMSD), average range difference (ARD) and average distal dose degradation (ADD), the distance between the distal position of the 80% and 20% dose levels (R80- R20), were analyzed. Results: We found target coverage indices calculated by TOPAS to generally be around 1–2% lower than predicted by the analytical algorithm. Differences in R90 predicted by TOPAS and the planning system can be larger than currently applied range margins in proton therapy for small regions distal to the target volume. We estimate new site-specific range margins (R90) for analytical dose calculations considering total range uncertainties and uncertainties from dose calculation alone based on the RMSD. Our results demonstrate that a reduction of currently used uncertainty margins is feasible for liver, prostate and whole brain fields even without introducing MC dose calculations. Conclusion: Analytical dose calculation algorithms predict dose distributions within clinical limits for more homogeneous patients sites (liver, prostate, whole brain). However, we recommend
Energy Technology Data Exchange (ETDEWEB)
Hansen, J; Culberson, W; DeWerd, L [University of Wisconsin Medical Radiation Research Center, Madison, WI (United States); Soares, C [NIST (retired), Gaithersburg, MD (United States)
2016-06-15
Purpose: To test the validity of a windowless extrapolation chamber used to measure surface dose rate from planar ophthalmic applicators and to compare different Monte Carlo based codes for deriving correction factors. Methods: Dose rate measurements were performed using a windowless, planar extrapolation chamber with a {sup 90}Sr/{sup 90}Y Tracerlab RA-1 ophthalmic applicator previously calibrated at the National Institute of Standards and Technology (NIST). Capacitance measurements were performed to estimate the initial air gap width between the source face and collecting electrode. Current was measured as a function of air gap, and Bragg-Gray cavity theory was used to calculate the absorbed dose rate to water. To determine correction factors for backscatter, divergence, and attenuation from the Mylar entrance window found in the NIST extrapolation chamber, both EGSnrc Monte Carlo user code and Monte Carlo N-Particle Transport Code (MCNP) were utilized. Simulation results were compared with experimental current readings from the windowless extrapolation chamber as a function of air gap. Additionally, measured dose rate values were compared with the expected result from the NIST source calibration to test the validity of the windowless chamber design. Results: Better agreement was seen between EGSnrc simulated dose results and experimental current readings at very small air gaps (<100 µm) for the windowless extrapolation chamber, while MCNP results demonstrated divergence at these small gap widths. Three separate dose rate measurements were performed with the RA-1 applicator. The average observed difference from the expected result based on the NIST calibration was −1.88% with a statistical standard deviation of 0.39% (k=1). Conclusion: EGSnrc user code will be used during future work to derive correction factors for extrapolation chamber measurements. Additionally, experiment results suggest that an entrance window is not needed in order for an extrapolation
Optimum biasing of integral equations in Monte Carlo calculations
International Nuclear Information System (INIS)
Hoogenboom, J.E.
1979-01-01
In solving integral equations and estimating average values with the Monte Carlo method, biasing functions may be used to reduce the variancee of the estimates. A simple derivation was used to prove the existence of a zero-variance collision estimator if a specific biasing function and survival probability are applied. This optimum biasing function is the same as that used for the well known zero-variance last-event estimator
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.)
Energy Technology Data Exchange (ETDEWEB)
Oborn, B. M., E-mail: brad.oborn@gmail.com [Illawarra Cancer Care Centre (ICCC), Wollongong, NSW 2500, Australia and Centre for Medical Radiation Physics (CMRP), University of Wollongong, Wollongong, NSW 2500 (Australia); Ge, Y. [Sydney Medical School, University of Sydney, NSW 2006 (Australia); Hardcastle, N. [Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, NSW 2065 (Australia); Metcalfe, P. E. [Centre for Medical Radiation Physics (CMRP), University of Wollongong, Wollongong NSW 2500, Australia and Ingham Institute for Applied Medical Research, Liverpool, NSW 2170 (Australia); Keall, P. J. [Sydney Medical School, University of Sydney, NSW 2006, Australia and Ingham Institute for Applied Medical Research, Liverpool, NSW 2170 (Australia)
2016-01-15
Purpose: To report on significant dose enhancement effects caused by magnetic fields aligned parallel to 6 MV photon beam radiotherapy of small lung tumors. Findings are applicable to future inline MRI-guided radiotherapy systems. Methods: A total of eight clinical lung tumor cases were recalculated using Monte Carlo methods, and external magnetic fields of 0.5, 1.0, and 3 T were included to observe the impact on dose to the planning target volume (PTV) and gross tumor volume (GTV). Three plans were 6 MV 3D-CRT plans while 6 were 6 MV IMRT. The GTV’s ranged from 0.8 to 16 cm{sup 3}, while the PTV’s ranged from 1 to 59 cm{sup 3}. In addition, the dose changes in a 30 cm diameter cylindrical water phantom were investigated for small beams. The central 20 cm of this phantom contained either water or lung density insert. Results: For single beams, an inline magnetic field of 1 T has a small impact in lung dose distributions by reducing the lateral scatter of secondary electrons, resulting in a small dose increase along the beam. Superposition of multiple small beams leads to significant dose enhancements. Clinically, this process occurs in the lung tissue typically surrounding the GTV, resulting in increases to the D{sub 98%} (PTV). Two isolated tumors with very small PTVs (3 and 6 cm{sup 3}) showed increases in D{sub 98%} of 23% and 22%. Larger PTVs of 13, 26, and 59 cm{sup 3} had increases of 9%, 6%, and 4%, describing a natural fall-off in enhancement with increasing PTV size. However, three PTVs bounded to the lung wall showed no significant increase, due to lack of dose enhancement in the denser PTV volume. In general, at 0.5 T, the GTV mean dose enhancement is around 60% lower than that at 1 T, while at 3 T, it is 5%–60% higher than 1 T. Conclusions: Monte Carlo methods have described significant and predictable dose enhancement effects in small lung tumor plans for 6 MV radiotherapy when an external inline magnetic field is included. Results of this study
International Nuclear Information System (INIS)
Kuenzler, Thomas; Fotina, Irina; Stock, Markus; Georg, Dietmar
2009-01-01
The dosimetric performance of a Monte Carlo algorithm as implemented in a commercial treatment planning system (iPlan, BrainLAB) was investigated. After commissioning and basic beam data tests in homogenous phantoms, a variety of single regular beams and clinical field arrangements were tested in heterogeneous conditions (conformal therapy, arc therapy and intensity-modulated radiotherapy including simultaneous integrated boosts). More specifically, a cork phantom containing a concave-shaped target was designed to challenge the Monte Carlo algorithm in more complex treatment cases. All test irradiations were performed on an Elekta linac providing 6, 10 and 18 MV photon beams. Absolute and relative dose measurements were performed with ion chambers and near tissue equivalent radiochromic films which were placed within a transverse plane of the cork phantom. For simple fields, a 1D gamma (γ) procedure with a 2% dose difference and a 2 mm distance to agreement (DTA) was applied to depth dose curves, as well as to inplane and crossplane profiles. The average gamma value was 0.21 for all energies of simple test cases. For depth dose curves in asymmetric beams similar gamma results as for symmetric beams were obtained. Simple regular fields showed excellent absolute dosimetric agreement to measurement values with a dose difference of 0.1% ± 0.9% (1 standard deviation) at the dose prescription point. A more detailed analysis at tissue interfaces revealed dose discrepancies of 2.9% for an 18 MV energy 10 x 10 cm 2 field at the first density interface from tissue to lung equivalent material. Small fields (2 x 2 cm 2 ) have their largest discrepancy in the re-build-up at the second interface (from lung to tissue equivalent material), with a local dose difference of about 9% and a DTA of 1.1 mm for 18 MV. Conformal field arrangements, arc therapy, as well as IMRT beams and simultaneous integrated boosts were in good agreement with absolute dose measurements in the
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
International Nuclear Information System (INIS)
Larraga-Gutierrez, J. M.; Garcia-Garduno, O. A.; Hernandez-Bojorquez, M.; Galvan de la Cruz, O. O.; Ballesteros-Zebadua, P.
2010-01-01
This work presents the beam data commissioning and dose calculation validation of the first Monte Carlo (MC) based treatment planning system (TPS) installed in Mexico. According to the manufacturer specifications, the beam data commissioning needed for this model includes: several in-air and water profiles, depth dose curves, head-scatter factors and output factors (6x6, 12x12, 18x18, 24x24, 42x42, 60x60, 80x80 and 100x100 mm 2 ). Radiographic and radiochromic films, diode and ionization chambers were used for data acquisition. MC dose calculations in a water phantom were used to validate the MC simulations using comparisons with measured data. Gamma index criteria 2%/2 mm were used to evaluate the accuracy of MC calculations. MC calculated data show an excellent agreement for field sizes from 18x18 to 100x100 mm 2 . Gamma analysis shows that in average, 95% and 100% of the data passes the gamma index criteria for these fields, respectively. For smaller fields (12x12 and 6x6 mm 2 ) only 92% of the data meet the criteria. Total scatter factors show a good agreement ( 2 ) that show a error of 4.7%. MC dose calculations are accurate and precise for clinical treatment planning up to a field size of 18x18 mm 2 . Special care must be taken for smaller fields.
Directory of Open Access Journals (Sweden)
J. Tonttila
2013-08-01
Full Text Available A new method for parameterizing the subgrid variations of vertical velocity and cloud droplet number concentration (CDNC is presented for general circulation models (GCMs. These parameterizations build on top of existing parameterizations that create stochastic subgrid cloud columns inside the GCM grid cells, which can be employed by the Monte Carlo independent column approximation approach for radiative transfer. The new model version adds a description for vertical velocity in individual subgrid columns, which can be used to compute cloud activation and the subgrid distribution of the number of cloud droplets explicitly. Autoconversion is also treated explicitly in the subcolumn space. This provides a consistent way of simulating the cloud radiative effects with two-moment cloud microphysical properties defined at subgrid scale. The primary impact of the new parameterizations is to decrease the CDNC over polluted continents, while over the oceans the impact is smaller. Moreover, the lower CDNC induces a stronger autoconversion of cloud water to rain. The strongest reduction in CDNC and cloud water content over the continental areas promotes weaker shortwave cloud radiative effects (SW CREs even after retuning the model. However, compared to the reference simulation, a slightly stronger SW CRE is seen e.g. over mid-latitude oceans, where CDNC remains similar to the reference simulation, and the in-cloud liquid water content is slightly increased after retuning the model.
International Nuclear Information System (INIS)
Atitoaie, Alexandru; Tanasa, Radu; Enachescu, Cristian
2012-01-01
Spin crossover compounds are photo-magnetic bistable molecular magnets with two states in thermodynamic competition: the diamagnetic low-spin state and paramagnetic high-spin state. The thermal transition between the two states is often accompanied by a wide hysteresis, premise for possible application of these materials as recording media. In this paper we study the influence of the system's size on the thermal hysteresis loops using Monte Carlo simulations based on an Arrhenius dynamics applied for an Ising like model with long- and short-range interactions. We show that using appropriate boundary conditions it is possible to reproduce both the drop of hysteresis width with decreasing particle size, the hysteresis shift towards lower temperatures and the incomplete transition, as in the available experimental data. The case of larger systems composed by several sublattices is equally treated reproducing the shrinkage of the hysteresis loop's width experimentally observed. - Highlights: ► A study concerning size effects in spin crossover nanoparticles hysteresis is presented. ► An Ising like model with short- and long-range interactions and Arrhenius dynamics is employed. ► In open boundary system the hysteresis width decreases with particle size. ► With appropriate environment, hysteresis loop is shifted towards lower temperature and transition is incomplete.
International Nuclear Information System (INIS)
Li, Y; Tian, Z; Jiang, S; Jia, X; Song, T; Wu, Z; Liu, Y
2015-01-01
Purpose: Intensity-modulated proton therapy (IMPT) is increasingly used in proton therapy. For IMPT optimization, Monte Carlo (MC) is desired for spots dose calculations because of its high accuracy, especially in cases with a high level of heterogeneity. It is also preferred in biological optimization problems due to the capability of computing quantities related to biological effects. However, MC simulation is typically too slow to be used for this purpose. Although GPU-based MC engines have become available, the achieved efficiency is still not ideal. The purpose of this work is to develop a new optimization scheme to include GPU-based MC into IMPT. Methods: A conventional approach using MC in IMPT simply calls the MC dose engine repeatedly for each spot dose calculations. However, this is not the optimal approach, because of the unnecessary computations on some spots that turned out to have very small weights after solving the optimization problem. GPU-memory writing conflict occurring at a small beam size also reduces computational efficiency. To solve these problems, we developed a new framework that iteratively performs MC dose calculations and plan optimizations. At each dose calculation step, the particles were sampled from different spots altogether with Metropolis algorithm, such that the particle number is proportional to the latest optimized spot intensity. Simultaneously transporting particles from multiple spots also mitigated the memory writing conflict problem. Results: We have validated the proposed MC-based optimization schemes in one prostate case. The total computation time of our method was ∼5–6 min on one NVIDIA GPU card, including both spot dose calculation and plan optimization, whereas a conventional method naively using the same GPU-based MC engine were ∼3 times slower. Conclusion: A fast GPU-based MC dose calculation method along with a novel optimization workflow is developed. The high efficiency makes it attractive for clinical
Energy Technology Data Exchange (ETDEWEB)
Chi, Y; Li, Y; Tian, Z; Gu, X; Jiang, S; Jia, X [UT Southwestern Medical Center, Dallas, TX (United States)
2015-06-15
Purpose: Pencil-beam or superposition-convolution type dose calculation algorithms are routinely used in inverse plan optimization for intensity modulated radiation therapy (IMRT). However, due to their limited accuracy in some challenging cases, e.g. lung, the resulting dose may lose its optimality after being recomputed using an accurate algorithm, e.g. Monte Carlo (MC). It is the objective of this study to evaluate the feasibility and advantages of a new method to include MC in the treatment planning process. Methods: We developed a scheme to iteratively perform MC-based beamlet dose calculations and plan optimization. In the MC stage, a GPU-based dose engine was used and the particle number sampled from a beamlet was proportional to its optimized fluence from the previous step. We tested this scheme in four lung cancer IMRT cases. For each case, the original plan dose, plan dose re-computed by MC, and dose optimized by our scheme were obtained. Clinically relevant dosimetric quantities in these three plans were compared. Results: Although the original plan achieved a satisfactory PDV dose coverage, after re-computing doses using MC method, it was found that the PTV D95% were reduced by 4.60%–6.67%. After re-optimizing these cases with our scheme, the PTV coverage was improved to the same level as in the original plan, while the critical OAR coverages were maintained to clinically acceptable levels. Regarding the computation time, it took on average 144 sec per case using only one GPU card, including both MC-based beamlet dose calculation and treatment plan optimization. Conclusion: The achieved dosimetric gains and high computational efficiency indicate the feasibility and advantages of the proposed MC-based IMRT optimization method. Comprehensive validations in more patient cases are in progress.
International Nuclear Information System (INIS)
Vithayasrichareon, Peerapat; MacGill, Iain F.
2012-01-01
This paper presents a novel decision-support tool for assessing future generation portfolios in an increasingly uncertain electricity industry. The tool combines optimal generation mix concepts with Monte Carlo simulation and portfolio analysis techniques to determine expected overall industry costs, associated cost uncertainty, and expected CO 2 emissions for different generation portfolio mixes. The tool can incorporate complex and correlated probability distributions for estimated future fossil-fuel costs, carbon prices, plant investment costs, and demand, including price elasticity impacts. The intent of this tool is to facilitate risk-weighted generation investment and associated policy decision-making given uncertainties facing the electricity industry. Applications of this tool are demonstrated through a case study of an electricity industry with coal, CCGT, and OCGT facing future uncertainties. Results highlight some significant generation investment challenges, including the impacts of uncertain and correlated carbon and fossil-fuel prices, the role of future demand changes in response to electricity prices, and the impact of construction cost uncertainties on capital intensive generation. The tool can incorporate virtually any type of input probability distribution, and support sophisticated risk assessments of different portfolios, including downside economic risks. It can also assess portfolios against multi-criterion objectives such as greenhouse emissions as well as overall industry costs. - Highlights: ► Present a decision support tool to assist generation investment and policy making under uncertainty. ► Generation portfolios are assessed based on their expected costs, risks, and CO 2 emissions. ► There is tradeoff among expected cost, risks, and CO 2 emissions of generation portfolios. ► Investment challenges include economic impact of uncertainties and the effect of price elasticity. ► CO 2 emissions reduction depends on the mix of
Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun
2018-01-01
One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Li, Y [Tsinghua University, Beijing, Beijing (China); UT Southwestern Medical Center, Dallas, TX (United States); Tian, Z; Jiang, S; Jia, X [UT Southwestern Medical Center, Dallas, TX (United States); Song, T [Southern Medical University, Guangzhou, Guangdong (China); UT Southwestern Medical Center, Dallas, TX (United States); Wu, Z; Liu, Y [Tsinghua University, Beijing, Beijing (China)
2015-06-15
Purpose: Intensity-modulated proton therapy (IMPT) is increasingly used in proton therapy. For IMPT optimization, Monte Carlo (MC) is desired for spots dose calculations because of its high accuracy, especially in cases with a high level of heterogeneity. It is also preferred in biological optimization problems due to the capability of computing quantities related to biological effects. However, MC simulation is typically too slow to be used for this purpose. Although GPU-based MC engines have become available, the achieved efficiency is still not ideal. The purpose of this work is to develop a new optimization scheme to include GPU-based MC into IMPT. Methods: A conventional approach using MC in IMPT simply calls the MC dose engine repeatedly for each spot dose calculations. However, this is not the optimal approach, because of the unnecessary computations on some spots that turned out to have very small weights after solving the optimization problem. GPU-memory writing conflict occurring at a small beam size also reduces computational efficiency. To solve these problems, we developed a new framework that iteratively performs MC dose calculations and plan optimizations. At each dose calculation step, the particles were sampled from different spots altogether with Metropolis algorithm, such that the particle number is proportional to the latest optimized spot intensity. Simultaneously transporting particles from multiple spots also mitigated the memory writing conflict problem. Results: We have validated the proposed MC-based optimization schemes in one prostate case. The total computation time of our method was ∼5–6 min on one NVIDIA GPU card, including both spot dose calculation and plan optimization, whereas a conventional method naively using the same GPU-based MC engine were ∼3 times slower. Conclusion: A fast GPU-based MC dose calculation method along with a novel optimization workflow is developed. The high efficiency makes it attractive for clinical
Cassola, V. F.; Kramer, R.; Brayner, C.; Khoury, H. J.
2010-08-01
Does the posture of a patient have an effect on the organ and tissue absorbed doses caused by x-ray examinations? This study aims to find the answer to this question, based on Monte Carlo (MC) simulations of commonly performed x-ray examinations using adult phantoms modelled to represent humans in standing as well as in the supine posture. The recently published FASH (female adult mesh) and MASH (male adult mesh) phantoms have the standing posture. In a first step, both phantoms were updated with respect to their anatomy: glandular tissue was separated from adipose tissue in the breasts, visceral fat was separated from subcutaneous fat, cartilage was segmented in ears, nose and around the thyroid, and the mass of the right lung is now 15% greater than the left lung. The updated versions are called FASH2_sta and MASH2_sta (sta = standing). Taking into account the gravitational effects on organ position and fat distribution, supine versions of the FASH2 and the MASH2 phantoms have been developed in this study and called FASH2_sup and MASH2_sup. MC simulations of external whole-body exposure to monoenergetic photons and partial-body exposure to x-rays have been made with the standing and supine FASH2 and MASH2 phantoms. For external whole-body exposure for AP and PA projection with photon energies above 30 keV, the effective dose did not change by more than 5% when the posture changed from standing to supine or vice versa. Apart from that, the supine posture is quite rare in occupational radiation protection from whole-body exposure. However, in the x-ray diagnosis supine posture is frequently used for patients submitted to examinations. Changes of organ absorbed doses up to 60% were found for simulations of chest and abdomen radiographs if the posture changed from standing to supine or vice versa. A further increase of differences between posture-specific organ and tissue absorbed doses with increasing whole-body mass is to be expected.
Ngaile, J. E.; Msaki, P. K.; Kazema, R. R.
2018-04-01
Contrast investigations of hysterosalpingography (HSG) and retrograde urethrography (RUG) fluoroscopy procedures remain the dominant diagnostic tools for the investigation of infertility in females and urethral strictures in males, respectively, owing to the scarcity and high cost of services of alternative diagnostic technologies. In light of the radiological risks associated with contrast based investigations of the genitourinary tract systems, there is a need to assess the magnitude of radiation burden imparted to patients undergoing HSG and RUG fluoroscopy procedures in Tanzania. The air kerma area product (KAP), fluoroscopy time, number of images, organ dose and effective dose to patients undergoing HSG and RUG procedures were obtained from four hospitals. The KAP was measured using a flat transmission ionization chamber, while the organ and effective doses were estimated using the knowledge of the patient characteristics, patient related exposure parameters, geometry of examination, KAP and Monte Carlo calculations (PCXMC). The median values of KAP for the HSG and RUG were 2.2 Gy cm2 and 3.3 Gy cm2, respectively. The median organ doses in the present study for the ovaries, urinary bladder and uterus for the HSG procedures, were 1.0 mGy, 4.0 mGy and 1.6 mGy, respectively, while for urinary bladder and testes of the RUG were 3.4 mGy and 5.9 mGy, respectively. The median values of effective doses for the HSG and RUG procedures were 0.65 mSv and 0.59 mSv, respectively. The median values of effective dose per hospital for the HSG and RUG procedures had a range of 1.6-2.8 mSv and 1.9-5.6 mSv, respectively, while the overall differences between individual effective doses across the four hospitals varied by factors of up to 22.0 and 46.7, respectively for the HSG and RUG procedures. The proposed diagnostic reference levels (DRLs) for the HSG and RUG were for KAP 2.8 Gy cm2 and 3.9 Gy cm2, for fluoroscopy time 0.8 min and 0.9 min, and for number of images 5 and 4
Energy Technology Data Exchange (ETDEWEB)
Petrizzi, L.; Batistoni, P.; Migliori, S. [Associazione EURATOM ENEA sulla Fusione, Frascati (Roma) (Italy); Chen, Y.; Fischer, U.; Pereslavtsev, P. [Association FZK-EURATOM Forschungszentrum Karlsruhe (Germany); Loughlin, M. [EURATOM/UKAEA Fusion Association, Culham Science Centre, Abingdon, Oxfordshire, OX (United Kingdom); Secco, A. [Nice Srl Via Serra 33 Camerano Casasco AT (Italy)
2003-07-01
In deuterium-deuterium (D-D) and deuterium-tritium (D-T) fusion plasmas neutrons are produced causing activation of JET machine components. For safe operation and maintenance it is important to be able to predict the induced activation and the resulting shut down dose rates. This requires a suitable system of codes which is capable of simulating both the neutron induced material activation during operation and the decay gamma radiation transport after shut-down in the proper 3-D geometry. Two methodologies to calculate the dose rate in fusion devices have been developed recently and applied to fusion machines, both using the MCNP Monte Carlo code. FZK has developed a more classical approach, the rigorous 2-step (R2S) system in which MCNP is coupled to the FISPACT inventory code with an automated routing. ENEA, in collaboration with the ITER Team, has developed an alternative approach, the direct 1 step method (D1S). Neutron and decay gamma transport are handled in one single MCNP run, using an ad hoc cross section library. The intention was to tightly couple the neutron induced production of a radio-isotope and the emission of its decay gammas for an accurate spatial distribution and a reliable calculated statistical error. The two methods have been used by the two Associations to calculate the dose rate in five positions of JET machine, two inside the vacuum chamber and three outside, at cooling times between 1 second and 1 year after shutdown. The same MCNP model and irradiation conditions have been assumed. The exercise has been proposed and financed in the frame of the Fusion Technological Program of the JET machine. The scope is to supply the designers with the most reliable tool and data to calculate the dose rate on fusion machines. Results showed that there is a good agreement: the differences range between 5-35%. The next step to be considered in 2003 will be an exercise in which the comparison will be done with dose-rate data from JET taken during and
International Nuclear Information System (INIS)
Petrizzi, L.; Batistoni, P.; Migliori, S.; Chen, Y.; Fischer, U.; Pereslavtsev, P.; Loughlin, M.; Secco, A.
2003-01-01
In deuterium-deuterium (D-D) and deuterium-tritium (D-T) fusion plasmas neutrons are produced causing activation of JET machine components. For safe operation and maintenance it is important to be able to predict the induced activation and the resulting shut down dose rates. This requires a suitable system of codes which is capable of simulating both the neutron induced material activation during operation and the decay gamma radiation transport after shut-down in the proper 3-D geometry. Two methodologies to calculate the dose rate in fusion devices have been developed recently and applied to fusion machines, both using the MCNP Monte Carlo code. FZK has developed a more classical approach, the rigorous 2-step (R2S) system in which MCNP is coupled to the FISPACT inventory code with an automated routing. ENEA, in collaboration with the ITER Team, has developed an alternative approach, the direct 1 step method (D1S). Neutron and decay gamma transport are handled in one single MCNP run, using an ad hoc cross section library. The intention was to tightly couple the neutron induced production of a radio-isotope and the emission of its decay gammas for an accurate spatial distribution and a reliable calculated statistical error. The two methods have been used by the two Associations to calculate the dose rate in five positions of JET machine, two inside the vacuum chamber and three outside, at cooling times between 1 second and 1 year after shutdown. The same MCNP model and irradiation conditions have been assumed. The exercise has been proposed and financed in the frame of the Fusion Technological Program of the JET machine. The scope is to supply the designers with the most reliable tool and data to calculate the dose rate on fusion machines. Results showed that there is a good agreement: the differences range between 5-35%. The next step to be considered in 2003 will be an exercise in which the comparison will be done with dose-rate data from JET taken during and
Energy Technology Data Exchange (ETDEWEB)
Tian, Z; Shi, F; Gu, X; Tan, J; Hassan-Rezaeian, N; Jiang, S; Jia, X [UT Southwestern Medical Center, Dallas, TX (United States); Graves, Y [University of California, San Diego, La Jolla, CA (United States)
2016-06-15
Purpose: This proof-of-concept study is to develop a real-time Monte Carlo (MC) based treatment-dose reconstruction and monitoring system for radiotherapy, especially for the treatments with complicated delivery, to catch treatment delivery errors at the earliest possible opportunity and interrupt the treatment only when an unacceptable dosimetric deviation from our expectation occurs. Methods: First an offline scheme is launched to pre-calculate the expected dose from the treatment plan, used as ground truth for real-time monitoring later. Then an online scheme with three concurrent threads is launched while treatment delivering, to reconstruct and monitor the patient dose in a temporally resolved fashion in real-time. Thread T1 acquires machine status every 20 ms to calculate and accumulate fluence map (FM). Once our accumulation threshold is reached, T1 transfers the FM to T2 for dose reconstruction ad starts to accumulate a new FM. A GPU-based MC dose calculation is performed on T2 when MC dose engine is ready and a new FM is available. The reconstructed instantaneous dose is directed to T3 for dose accumulation and real-time visualization. Multiple dose metrics (e.g. maximum and mean dose for targets and organs) are calculated from the current accumulated dose and compared with the pre-calculated expected values. Once the discrepancies go beyond our tolerance, an error message will be send to interrupt the treatment delivery. Results: A VMAT Head-and-neck patient case was used to test the performance of our system. Real-time machine status acquisition was simulated here. The differences between the actual dose metrics and the expected ones were 0.06%–0.36%, indicating an accurate delivery. ∼10Hz frequency of dose reconstruction and monitoring was achieved, with 287.94s online computation time compared to 287.84s treatment delivery time. Conclusion: Our study has demonstrated the feasibility of computing a dose distribution in a temporally resolved fashion
Energy Technology Data Exchange (ETDEWEB)
Ureba, A.; Pereira-Barbeiro, A. R.; Jimenez-Ortega, E.; Baeza, J. A.; Salguero, F. J.; Leal, A.
2013-07-01
The use of Monte Carlo (MC) has shown an improvement in the accuracy of the calculation of the dose compared to other analytics algorithms installed on the systems of business planning, especially in the case of non-standard situations typical of complex techniques such as IMRT and VMAT. Our treatment planning system called CARMEN, is based on the complete simulation, both the beam transport in the head of the accelerator and the patient, and simulation designed for efficient operation in terms of the accuracy of the estimate and the required computation times. (Author)
International Nuclear Information System (INIS)
EMAM, M; Eldib, A; Lin, M; Li, J; Chibani, O; Ma, C
2014-01-01
Purpose: An in-house Monte Carlo based treatment planning system (MC TPS) has been developed for modulated electron radiation therapy (MERT). Our preliminary MERT planning experience called for a more user friendly graphical user interface. The current work aimed to design graphical windows and tools to facilitate the contouring and planning process. Methods: Our In-house GUI MC TPS is built on a set of EGS4 user codes namely MCPLAN and MCBEAM in addition to an in-house optimization code, which was named as MCOPTIM. Patient virtual phantom is constructed using the tomographic images in DICOM format exported from clinical treatment planning systems (TPS). Treatment target volumes and critical structures were usually contoured on clinical TPS and then sent as a structure set file. In our GUI program we developed a visualization tool to allow the planner to visualize the DICOM images and delineate the various structures. We implemented an option in our code for automatic contouring of the patient body and lungs. We also created an interface window displaying a three dimensional representation of the target and also showing a graphical representation of the treatment beams. Results: The new GUI features helped streamline the planning process. The implemented contouring option eliminated the need for performing this step on clinical TPS. The auto detection option for contouring the outer patient body and lungs was tested on patient CTs and it was shown to be accurate as compared to that of clinical TPS. The three dimensional representation of the target and the beams allows better selection of the gantry, collimator and couch angles. Conclusion: An in-house GUI program has been developed for more efficient MERT planning. The application of aiding tools implemented in the program is time saving and gives better control of the planning process
Adinehvand, Karim; Rahatabad, Fereidoun Nowshiravan
2018-06-01
Calculation of 3D dose distribution during radiotherapy and nuclear medicine helps us for better treatment of sensitive organs such as ovaries and uterus. In this research, we investigate two groups of normoxic dosimeters based on meta-acrylic acid (MAGIC and MAGICAUG) and polyacrylamide (PAGATUG and PAGATAUG) for brachytherapy, nuclear medicine and Tele-therapy in their sensitive and critical role as organ dosimeters. These polymer gel dosimeters are compared with soft tissue while irradiated by different energy photons in therapeutic applications. This comparison has been simulated by Monte-Carlo based MCNPX code. ORNL phantom-Female has been used to model the critical organs of kidneys, ovaries and uterus. Right kidney is proposed to be the source of irradiation and another two organs are exposed to this irradiation. Effective atomic numbers of soft tissue, MAGIC, MAGICAUG, PAGATUG and PAGATAUG are 6.86, 7.07, 6.95, 7.28, and 7.07 respectively. Results show the polymer gel dosimeters are comparable to soft tissue for using in nuclear medicine and Tele-therapy. Differences between gel dosimeters and soft tissue are defined as the dose responses. This difference is less than 4.1%, 22.6% and 71.9% for Tele-therapy, nuclear medicine and brachytherapy respectively. The results approved that gel dosimeters are the best choice for ovaries and uterus in nuclear medicine and Tele-therapy respectively. Due to the slight difference between the effective atomic numbers of these polymer gel dosimeters and soft tissue, these polymer gels are not suitable for brachytherapy since the dependence of photon interaction to atomic number, for low energy brachytherapy, had been so effective. Also this dependence to atomic number, decrease for photoelectric and increase for Compton. Therefore polymer gel dosimeters are not a good alternative to soft tissue replacement in brachytherapy. Copyright © 2018 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Barrera, C A; Moran, M J
2007-08-21
The Neutron Imaging System (NIS) is one of seven ignition target diagnostics under development for the National Ignition Facility. The NIS is required to record hot-spot (13-15 MeV) and downscattered (6-10 MeV) images with a resolution of 10 microns and a signal-to-noise ratio (SNR) of 10 at the 20% contour. The NIS is a valuable diagnostic since the downscattered neutrons reveal the spatial distribution of the cold fuel during an ignition attempt, providing important information in the case of a failed implosion. The present study explores the parameter space of several line-of-sight (LOS) configurations that could serve as the basis for the final design. Six commercially available organic scintillators were experimentally characterized for their light emission decay profile and neutron sensitivity. The samples showed a long lived decay component that makes direct recording of a downscattered image impossible. The two best candidates for the NIS detector material are: EJ232 (BC422) plastic fibers or capillaries filled with EJ399B. A Monte Carlo-based end-to-end model of the NIS was developed to study the imaging capabilities of several LOS configurations and verify that the recovered sources meet the design requirements. The model includes accurate neutron source distributions, aperture geometries (square pinhole, triangular wedge, mini-penumbral, annular and penumbral), their point spread functions, and a pixelated scintillator detector. The modeling results show that a useful downscattered image can be obtained by recording the primary peak and the downscattered images, and then subtracting a decayed version of the former from the latter. The difference images need to be deconvolved in order to obtain accurate source distributions. The images are processed using a frequency-space modified-regularization algorithm and low-pass filtering. The resolution and SNR of these sources are quantified by using two surrogate sources. The simulations show that all LOS
International Nuclear Information System (INIS)
Borg, M.; Badr, I.; Royle, G. J.
2013-01-01
Modern full-field digital mammography (FFDM) units display the mean glandular dose (MGD) and the entrance or incident air kerma (K) to the breast following each exposure. Information on how these values are calculated is limited and knowing how displayed MGD values compare and correlate to conventional Monte-Carlo-based methods is useful. From measurements done on polymethyl methacrylate (PMMA) phantoms, it has been shown that displayed and calculated MGD values are similar for thin to medium thicknesses and appear to differ with larger PMMA thicknesses. As a result, a multiple linear regression analysis on the data was performed to generate models by which displayed MGD values on the two FFDM units included in the study may be converted to the Monte-Carlo values calculated by conventional methods. These models should be a useful tool for medical physicists requiring MGD data from FFDM units included in this paper and should reduce the survey time spent on dose calculations. (authors)
Development and application of the automated Monte Carlo biasing procedure in SAS4
International Nuclear Information System (INIS)
Tang, J.S.; Broadhead, B.L.
1995-01-01
An 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 three-dimensional Monte Carlo calculation. The automated procedure consisting of cross-section processing, adjoint flux determination, biasing parameter generation, and the initiation of a MORSE-SGC/S Monte Carlo calculation has been implemented in the SAS4 module of the SCALE computer code system. (author)
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.
Development and application of the automated Monte Carlo biasing procedure in SAS4
International Nuclear Information System (INIS)
Tang, J.S.; Broadhead, B.L.
1993-01-01
An 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 three-dimensional Monte Carlo calculation. The automated procedure consisting of cross-section processing, adjoint flux determination, biasing parameter generation, and the initiation of a MORSE-SGC/S Monte Carlo calculation has been implemented in the SAS4 module of the SCALE computer code system. The automated procedure has been used extensively in the investigation of both computational and experimental benchmarks for the NEACRP working group on shielding assessment of transportation packages. The results of these studies 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. The systematic biasing approach described in this paper can also be applied to other similar shielding problems
Czarnecki, Damian; Poppe, Björn; Zink, Klemens
2017-06-01
The impact of removing the flattening filter in clinical electron accelerators on the relationship between dosimetric quantities such as beam quality specifiers and the mean photon and electron energies of the photon radiation field was investigated by Monte Carlo simulations. The purpose of this work was to determine the uncertainties when using the well-known beam quality specifiers or energy-based beam specifiers as predictors of dosimetric photon field properties when removing the flattening filter. Monte Carlo simulations applying eight different linear accelerator head models with and without flattening filter were performed in order to generate realistic radiation sources and calculate field properties such as restricted mass collision stopping power ratios (L¯/ρ)airwater, mean photon and secondary electron energies. To study the impact of removing the flattening filter on the beam quality correction factors k Q , this factor for detailed ionization chamber models was calculated by Monte Carlo simulations. Stopping power ratios (L¯/ρ)airwater and k Q values for different ionization chambers as a function of TPR1020 and %dd(10) x were calculated. Moreover, mean photon energies in air and at the point of measurement in water as well as mean secondary electron energies at the point of measurement were calculated. The results revealed that removing the flattening filter led to a change within 0.3% in the relationship between %dd(10) x and (L¯/ρ)airwater, whereby the relationship between TPR1020 and (L¯/ρ)airwater changed up to 0.8% for high energy photon beams. However, TPR1020 was a good predictor of (L¯/ρ)airwater for both types of linear accelerator with energies filter within 1.1% and 1.6% was observed for TPR1020 and %dd(10) x respectively. The results of this study have shown that removing the flattening filter led to a change in the relationship between the well-known beam quality specifiers and dosimetric quantities at the point of measurement
Energy Technology Data Exchange (ETDEWEB)
Jin, L; Fan, J; Eldib, A; Price, R; Ma, C [Fox Chase Cancer Center, Philadelphia, PA (United States)
2016-06-15
Purpose: Treating nose skin with an electron beam is of a substantial challenge due to uneven nose surfaces and tissue heterogeneity, and consequently could have a great uncertainty of dose accuracy on the target. This work explored the method using Monte Carlo (MC)-based energy and intensity modulated electron radiotherapy (MERT), which would be delivered with a photon MLC in a standard medical linac (Artiste). Methods: The traditional treatment on the nose skin involves the usage of a bolus, often with a single energy electron beam. This work avoided using the bolus, and utilized mixed energies of electron beams. An in-house developed Monte Carlo (MC)-based dose calculation/optimization planning system was employed for treatment planning. Phase space data (6, 9, 12 and 15 MeV) were used as an input source for MC dose calculations for the linac. To reduce the scatter-caused penumbra, a short SSD (61 cm) was used. A clinical case of the nose skin, which was previously treated with a single 9 MeV electron beam, was replanned with the MERT method. The resultant dose distributions were compared with the plan previously clinically used. The dose volume histogram of the MERT plan is calculated to examine the coverage of the planning target volume (PTV) and critical structure doses. Results: The target coverage and conformality in the MERT plan are improved as compared to the conventional plan. The MERT can provide more sufficient target coverage and less normal tissue dose underneath the nose skin. Conclusion: Compared to the conventional treatment technique, using MERT for the nose skin treatment has shown the dosimetric advantages in the PTV coverage and conformality. In addition, this technique eliminates the necessity of the cutout and bolus, which makes the treatment more efficient and accurate.
International Nuclear Information System (INIS)
Jarry, G; De Marco, J J; Beifuss, U; Cagnon, C H; McNitt-Gray, M F
2003-01-01
The purpose of this work is to develop and test a method to estimate the relative and absolute absorbed radiation dose from axial and spiral CT scans using a Monte Carlo approach. Initial testing was done in phantoms and preliminary results were obtained from a standard mathematical anthropomorphic model (MIRD V) and voxelized patient data. To accomplish this we have modified a general purpose Monte Carlo transport code (MCNP4B) to simulate the CT x-ray source and movement, and then to calculate absorbed radiation dose in desired objects. The movement of the source in either axial or spiral modes was modelled explicitly while the CT system components were modelled using published information about x-ray spectra as well as information provided by the manufacturer. Simulations were performed for single axial scans using the head and body computed tomography dose index (CTDI) polymethylmethacrylate phantoms at both central and peripheral positions for all available beam energies and slice thicknesses. For comparison, corresponding physical measurements of CTDI in phantom were made with an ion chamber. To obtain absolute dose values, simulations and measurements were performed in air at the scanner isocentre for each beam energy. To extend the verification, the CT scanner model was applied to the MIRD V model and compared with published results using similar technical factors. After verification of the model, the generalized source was simulated and applied to voxelized models of patient anatomy. The simulated and measured absolute dose data in phantom agreed to within 2% for the head phantom and within 4% for the body phantom at 120 and 140 kVp; this extends to 8% for the head and 9% for the body phantom across all available beam energies and positions. For the head phantom, the simulated and measured absolute dose data agree to within 2% across all slice thicknesses at 120 kVp. Our results in the MIRD phantom agree within 11% of all the different organ dose values
International Nuclear Information System (INIS)
Pierre, J.R.M.
1996-01-01
Following the commissioning of the Low Enrichment Uranium (LEU) Fuelled SLOWPOKE-2 research reactor at the Royal Military College-College Militaire Royal (RMC-CMR), excess reactivity measurements were conducted over a range of temperature and power. The results showed a maximum excess reactivity of 3.37 mk at 33 o C. Several deterministic models using computer codes like WIMS-CRNL, CITATION, TRIVAC and DRAGON have been used to try to reproduce the excess reactivity and temperature trend of both the LEU and HEU SLOWPOKE-2 reactors. The best simulations had been obtained at Ecole Polytechnique de Montreal. They were able to reproduce the temperature trend of their HEU-fuelled reactor using TRIVAC calculations, but this model over-estimated the absolute value of the excess reactivity by 119 mk. Although calculations using DRAGON did not reproduce the temperature trend as well as TRIVAC, these calculations represented a significant improvement on the absolute value at 20 o C reducing the discrepancy to 13 mk. Given the advance in computer technology, a probabilistic approach was tried in this work, using the Monte-Carlo N-Particle Transport Code System MCNP 4A, to model the RMC-CMR SLOWPOKE-2 reactor.
Jagtap, A S; Palani Selvam, T; Patil, B J; Chavan, S T; Pethe, S N; Kulkarni, Gauri; Dahiwale, S S; Bhoraskar, V N; Dhole, S D
2016-12-01
A Telecobalt unit has wide range of applications in cancer treatments and is used widely in many countries all around the world. Estimation of surface dose in Cobalt-60 teletherapy machine becomes important since clinically useful photon beam consist of contaminated electrons during the patient treatment. EGSnrc along with the BEAMnrc user code was used to model the Theratron 780E telecobalt unit. Central axis depth dose profiles including surface doses have been estimated for the field sizes of 0×0, 6×6, 10×10, 15×15, 20×20, 25×25, 30×30cm 2 and at Source-to-surface distance (SSD) of 60 and 80cm. Surface dose was measured experimentally by the Gafchromic RTQA2 films and are in good agreement with the simulation results. The central axis depth dose data are compared with the data available from the British Journal of Radiology report no. 25. Contribution of contaminated electrons has also been calculated using Monte Carlo simulation by the different parts of the Cobalt-60 head for different field size and SSD's. Moreover, depth dose curve in zero area field size is calculated by extrapolation method and compared with the already published data. They are found in good agreement. Copyright © 2016 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Eleftheria Psarrou
2018-02-01
Full Text Available Pressures on water resources, which have increased significantly nowadays mainly due to rapid urbanization, population growth and climate change impacts, necessitate the development of innovative wastewater treatment and reuse technologies. In this context, a mid-scale decentralized technology concerning wastewater reuse is that of sewer mining. It is based on extracting wastewater from a wastewater system, treating it on-site and producing recycled water applicable for non-potable uses. Despite the technology’s considerable benefits, several challenges hinder its implementation. Sewer mining disturbs biochemical processes inside sewers and affects hydrogen sulfide build-up, resulting in odor, corrosion and health-related problems. In this study, a tool for optimal sewer mining unit placement aiming to minimize hydrogen sulfide production is presented. The Monte-Carlo method coupled with the Environmental Protection Agency’s Storm Water Management Model (SWMM is used to conduct multiple simulations of the network. The network’s response when sewage is extracted from it is also examined. Additionally, the study deals with optimal pumping scheduling. The overall methodology is applied in a sewer network in Greece providing useful results. It can therefore assist in selecting appropriate locations for sewer mining implementation, with the focus on eliminating hydrogen sulfide-associated problems while simultaneously ensuring that higher water needs are satisfied.
International Nuclear Information System (INIS)
Murthy, K.P.N.; Indira, R.
1986-01-01
An analytical formulation is presented for calculating the mean and variance of transmission for a model deep-penetration problem. With this formulation, the variance reduction characteristics of two biased Monte Carlo schemes are studied. The first is the usual exponential biasing wherein it is shown that the optimal biasing parameter depends sensitively on the scattering properties of the shielding medium. The second is a scheme that couples exponential biasing to the scattering angle biasing proposed recently. It is demonstrated that the coupled scheme performs better than exponential biasing
International Nuclear Information System (INIS)
Jin, L; Eldib, A; Li, J; Price, R; Ma, C
2015-01-01
Purpose: Uneven nose surfaces and air cavities underneath and the use of bolus present complexity and dose uncertainty when using a single electron energy beam to plan treatments of nose skin with a pencil beam-based planning system. This work demonstrates more accurate dose calculation and more optimal planning using energy and intensity modulated electron radiotherapy (MERT) delivered with a pMLC. Methods: An in-house developed Monte Carlo (MC)-based dose calculation/optimization planning system was employed for treatment planning. Phase space data (6, 9, 12 and 15 MeV) were used as an input source for MC dose calculations for the linac. To reduce the scatter-caused penumbra, a short SSD (61 cm) was used. Our previous work demonstrates good agreement in percentage depth dose and off-axis dose between calculations and film measurement for various field sizes. A MERT plan was generated for treating the nose skin using a patient geometry and a dose volume histogram (DVH) was obtained. The work also shows the comparison of 2D dose distributions between a clinically used conventional single electron energy plan and the MERT plan. Results: The MERT plan resulted in improved target dose coverage as compared to the conventional plan, which demonstrated a target dose deficit at the field edge. The conventional plan showed higher dose normal tissue irradiation underneath the nose skin while the MERT plan resulted in improved conformity and thus reduces normal tissue dose. Conclusion: This preliminary work illustrates that MC-based MERT planning is a promising technique in treating nose skin, not only providing more accurate dose calculation, but also offering an improved target dose coverage and conformity. In addition, this technique may eliminate the necessity of bolus, which often produces dose delivery uncertainty due to the air gaps that may exist between the bolus and skin
Energy Technology Data Exchange (ETDEWEB)
Ma, J; Wan Chan Tseung, H; Beltran, C [Mayo Clinic, Rochester, MN (United States)
2014-06-15
Purpose: To develop a clinically applicable intensity modulated proton therapy (IMPT) optimization system that utilizes more accurate Monte Carlo (MC) dose calculation, rather than analytical dose calculation. Methods: A very fast in-house graphics processing unit (GPU) based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified gradient based optimization method was used to achieve the desired dose volume histograms (DVH). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve the spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that Result from maintaining the intrinsic CT resolution and large number of proton spots. The dose effects were studied particularly in cases with heterogeneous materials in comparison with the commercial treatment planning system (TPS). Results: For a relatively large and complex three-field bi-lateral head and neck case (i.e. >100K spots with a target volume of ∼1000 cc and multiple surrounding critical structures), the optimization together with the initial MC dose influence map calculation can be done in a clinically viable time frame (i.e. less than 15 minutes) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The DVHs of the MC TPS plan compare favorably with those of a commercial treatment planning system. Conclusion: A GPU accelerated and MC-based IMPT optimization system was developed. The dose calculation and plan optimization can be performed in less than 15 minutes on a hardware system costing less than 45,000 dollars. The fast calculation and optimization makes the system easily expandable to robust and multi-criteria optimization. This work was funded in part by a grant from Varian Medical Systems, Inc.
International Nuclear Information System (INIS)
Ma, J; Wan Chan Tseung, H; Beltran, C
2014-01-01
Purpose: To develop a clinically applicable intensity modulated proton therapy (IMPT) optimization system that utilizes more accurate Monte Carlo (MC) dose calculation, rather than analytical dose calculation. Methods: A very fast in-house graphics processing unit (GPU) based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified gradient based optimization method was used to achieve the desired dose volume histograms (DVH). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve the spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that Result from maintaining the intrinsic CT resolution and large number of proton spots. The dose effects were studied particularly in cases with heterogeneous materials in comparison with the commercial treatment planning system (TPS). Results: For a relatively large and complex three-field bi-lateral head and neck case (i.e. >100K spots with a target volume of ∼1000 cc and multiple surrounding critical structures), the optimization together with the initial MC dose influence map calculation can be done in a clinically viable time frame (i.e. less than 15 minutes) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The DVHs of the MC TPS plan compare favorably with those of a commercial treatment planning system. Conclusion: A GPU accelerated and MC-based IMPT optimization system was developed. The dose calculation and plan optimization can be performed in less than 15 minutes on a hardware system costing less than 45,000 dollars. The fast calculation and optimization makes the system easily expandable to robust and multi-criteria optimization. This work was funded in part by a grant from Varian Medical Systems, Inc
Sikora, M; Dohm, O; Alber, M
2007-08-07
A dedicated, efficient Monte Carlo (MC) accelerator head model for intensity modulated stereotactic radiosurgery treatment planning is needed to afford a highly accurate simulation of tiny IMRT fields. A virtual source model (VSM) of a mini multi-leaf collimator (MLC) (the Elekta Beam Modulator (EBM)) is presented, allowing efficient generation of particles even for small fields. The VSM of the EBM is based on a previously published virtual photon energy fluence model (VEF) (Fippel et al 2003 Med. Phys. 30 301) commissioned with large field measurements in air and in water. The original commissioning procedure of the VEF, based on large field measurements only, leads to inaccuracies for small fields. In order to improve the VSM, it was necessary to change the VEF model by developing (1) a method to determine the primary photon source diameter, relevant for output factor calculations, (2) a model of the influence of the flattening filter on the secondary photon spectrum and (3) a more realistic primary photon spectrum. The VSM model is used to generate the source phase space data above the mini-MLC. Later the particles are transmitted through the mini-MLC by a passive filter function which significantly speeds up the time of generation of the phase space data after the mini-MLC, used for calculation of the dose distribution in the patient. The improved VSM model was commissioned for 6 and 15 MV beams. The results of MC simulation are in very good agreement with measurements. Less than 2% of local difference between the MC simulation and the diamond detector measurement of the output factors in water was achieved. The X, Y and Z profiles measured in water with an ion chamber (V = 0.125 cm(3)) and a diamond detector were used to validate the models. An overall agreement of 2%/2 mm for high dose regions and 3%/2 mm in low dose regions between measurement and MC simulation for field sizes from 0.8 x 0.8 cm(2) to 16 x 21 cm(2) was achieved. An IMRT plan film verification
International Nuclear Information System (INIS)
Chetty, Indrin J.; Curran, Bruce; Cygler, Joanna E.; DeMarco, John J.; Ezzell, Gary; Faddegon, Bruce A.; Kawrakow, Iwan; Keall, Paul J.; Liu, Helen; Ma, C.-M. Charlie; Rogers, D. W. O.; Seuntjens, Jan; Sheikh-Bagheri, Daryoush; Siebers, Jeffrey V.
2007-01-01
The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, the ability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and
International Nuclear Information System (INIS)
Satoh, Daiki; Sato, Tatsuhiko; Shigyo, Nobuhiro; Ishibashi, Kenji
2006-11-01
The Monte Carlo based computer code SCINFUL-QMD has been developed to evaluate response function and detection efficiency of a liquid organic scintillator for neutrons from 0.1 MeV to 3 GeV. This code is a modified version of SCINFUL that was developed at Oak Ridge National Laboratory in 1988, to provide a calculated full response anticipated for neutron interactions in a scintillator. The upper limit of the applicable energy was extended from 80 MeV to 3 GeV by introducing the quantum molecular dynamics incorporated with the statistical decay model (QMD+SDM) in the high-energy nuclear reaction part. The particles generated in QMD+SDM are neutron, proton, deuteron, triton, 3 He nucleus, alpha particle, and charged pion. Secondary reactions by neutron, proton, and pion inside the scintillator are also taken into account. With the extension of the applicable energy, the database of total cross sections for hydrogen and carbon nuclei were upgraded. This report describes the physical model, computational flow and how to use the code. (author)
International Nuclear Information System (INIS)
Badkul, R; Pokhrel, D; Jiang, H; Lominska, C; Wang, F; Ramanjappa, T
2016-01-01
Purpose: Intra-fractional tumor motion due to respiration may potentially compromise dose delivery for SBRT of lung tumors. Even sufficient margins are used to ensure there is no geometric miss of target volume, there is potential dose blurring effect may present due to motion and could impact the tumor coverage if motions are larger. In this study we investigated dose blurring effect of open fields as well as Lung SBRT patients planned using 2 non-coplanar dynamic conformal arcs(NCDCA) and few conformal beams(CB) calculated with Monte Carlo (MC) based algorithm utilizing phantom with 2D-diode array(MapCheck) and ion-chamber. Methods: SBRT lung patients were planned on Brainlab-iPlan system using 4D-CT scan and ITV were contoured on MIP image set and verified on all breathing phase image sets to account for breathing motion and then 5mm margin was applied to generate PTV. Plans were created using two NCDCA and 4-5 CB 6MV photon calculated using XVMC MC-algorithm. 3 SBRT patients plans were transferred to phantom with MapCheck and 0.125cc ion-chamber inserted in the middle of phantom to calculate dose. Also open field 3×3, 5×5 and 10×10 were calculated on this phantom. Phantom was placed on motion platform with varying motion from 5, 10, 20 and 30 mm with duty cycle of 4 second. Measurements were carried out for open fields as well 3 patients plans at static and various degree of motions. MapCheck planar dose and ion-chamber reading were collected and compared with static measurements and computed values to evaluate the dosimetric effect on tumor coverage due to motion. Results: To eliminate complexity of patients plan 3 simple open fields were also measured to see the dose blurring effect with the introduction of motion. All motion measured ionchamber values were normalized to corresponding static value. For open fields 5×5 and 10×10 normalized central axis ion-chamber values were 1.00 for all motions but for 3×3 they were 1 up to 10mm motion and 0.97 and 0
International Nuclear Information System (INIS)
Both, J.P.; Nimal, J.C.; Vergnaud, T.
1990-01-01
We discuss an automated biasing procedure for generating the parameters necessary to achieve efficient Monte Carlo biasing shielding calculations. The biasing techniques considered here are exponential transform and collision biasing deriving from the concept of the biased game based on the importance function. We use a simple model of the importance function with exponential attenuation as the distance to the detector increases. This importance function is generated on a three-dimensional mesh including geometry and with graph theory algorithms. This scheme is currently being implemented in the third version of the neutron and gamma ray transport code TRIPOLI-3. (author)
Monte Carlo-Based Tail Exponent Estimator
Czech Academy of Sciences Publication Activity Database
Baruník, Jozef; Vácha, Lukáš
2010-01-01
Roč. 2010, č. 6 (2010), s. 1-26 R&D Projects: GA ČR GA402/09/0965; GA ČR GD402/09/H045; GA ČR GP402/08/P207 Institutional research plan: CEZ:AV0Z10750506 Keywords : Hill estimator * α-stable distributions * tail exponent estimation Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2010/E/barunik-0342493.pdf
Automated-biasing approach to Monte Carlo shipping-cask calculations
International Nuclear Information System (INIS)
Hoffman, T.J.; Tang, J.S.; Parks, C.V.; Childs, R.L.
1982-01-01
Computer Sciences at Oak Ridge National Laboratory, under a contract with the Nuclear Regulatory Commission, has developed the SCALE system for performing standardized criticality, shielding, and heat transfer analyses of nuclear systems. During the early phase of shielding development in SCALE, it was established that Monte Carlo calculations of radiation levels exterior to a spent fuel shipping cask would be extremely expensive. This cost can be substantially reduced by proper biasing of the Monte Carlo histories. The purpose of this study is to develop and test an automated biasing procedure for the MORSE-SGC/S module of the SCALE system
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
A kinetic theory for nonanalog Monte Carlo algorithms: Exponential transform with angular biasing
International Nuclear Information System (INIS)
Ueki, T.; Larsen, E.W.
1998-01-01
A new Boltzmann Monte Carlo (BMC) equation is proposed to describe the transport of Monte Carlo particles governed by a set of nonanalog rules for the transition of space, velocity, and weight. The BMC equation is a kinetic equation that includes weight as an extra independent variable. The solution of the BMC equation is the pointwise distribution of velocity and weight throughout the physical system. The BMC equation is derived for the simulation of a transmitted current, utilizing the exponential transform with angular biasing. The weight moments of the solution of the BMC equation are used to predict the score moments of the transmission current. (Also, it is shown that an adjoint BMC equation can be used for this purpose.) Integrating the solution of the forward BMC equation over space, velocity, and weight, the mean number of flights per history is obtained. This is used to determine theoretically the figure of merit for any choice of biasing parameters. Also, a maximum safe value of the exponential transform parameter is proposed, which ensure the finite variance of variance estimate (sample variance) for any penetration distance. Finally, numerical results that validate the new theory are provided
International Nuclear Information System (INIS)
Hyung, Jin Shim; Beom, Seok Han; Chang, Hyo Kim
2003-01-01
Monte Carlo (MC) power method based on the fixed number of fission sites at the beginning of each cycle is known to cause biases in the variances of the k-eigenvalue (keff) and the fission reaction rate estimates. Because of the biases, the apparent variances of keff and the fission reaction rate estimates from a single MC run tend to be smaller or larger than the real variances of the corresponding quantities, depending on the degree of the inter-generational correlation of the sample. We demonstrate this through a numerical experiment involving 100 independent MC runs for the neutronics analysis of a 17 x 17 fuel assembly of a pressurized water reactor (PWR). We also demonstrate through the numerical experiment that Gelbard and Prael's batch method and Ueki et al's covariance estimation method enable one to estimate the approximate real variances of keff and the fission reaction rate estimates from a single MC run. We then show that the use of the approximate real variances from the two-bias predicting methods instead of the apparent variances provides an efficient MC power iteration scheme that is required in the MC neutronics analysis of a real system to determine the pin power distribution consistent with the thermal hydraulic (TH) conditions of individual pins of the system. (authors)
Guenole, Nigel
2018-01-01
The test for item level cluster bias examines the improvement in model fit that results from freeing an item's between level residual variance from a baseline model with equal within and between level factor loadings and between level residual variances fixed at zero. A potential problem is that this approach may include a misspecified unrestricted model if any non-invariance is present, but the log-likelihood difference test requires that the unrestricted model is correctly specified. A free baseline approach where the unrestricted model includes only the restrictions needed for model identification should lead to better decision accuracy, but no studies have examined this yet. We ran a Monte Carlo study to investigate this issue. When the referent item is unbiased, compared to the free baseline approach, the constrained baseline approach led to similar true positive (power) rates but much higher false positive (Type I error) rates. The free baseline approach should be preferred when the referent indicator is unbiased. When the referent assumption is violated, the false positive rate was unacceptably high for both free and constrained baseline approaches, and the true positive rate was poor regardless of whether the free or constrained baseline approach was used. Neither the free or constrained baseline approach can be recommended when the referent indicator is biased. We recommend paying close attention to ensuring the referent indicator is unbiased in tests of cluster bias. All Mplus input and output files, R, and short Python scripts used to execute this simulation study are uploaded to an open access repository.
International Nuclear Information System (INIS)
Khuat, Quang Huy; Kim, Song Hyun; Kim, Do Hyun; Shin, Chang Ho
2015-01-01
This technique is known as Consistent Adjoint Driven Importance Sampling (CADIS) method and it is implemented in SCALE code system. In the CADIS method, adjoint transport equation has to be solved to determine deterministic importance functions. Using the CADIS method, a problem was noted that the biased adjoint flux estimated by deterministic methods can affect the calculation efficiency and error. The biases of adjoint function are caused by the methodology, calculation strategy, tolerance of result calculated by the deterministic method and inaccurate multi-group cross section libraries. In this paper, a study to analyze the influence of the biased adjoint functions into Monte Carlo computational efficiency is pursued. In this study, a method to estimate the calculation efficiency was proposed for applying the biased adjoint fluxes in the CADIS approach. For a benchmark problem, the responses and FOMs using SCALE code system were evaluated as applying the adjoint fluxes. The results show that the biased adjoint fluxes significantly affects the calculation efficiencies
International Nuclear Information System (INIS)
Dumonteil, E.; Diop, C.M.
2011-01-01
External linking scripts between Monte Carlo transport codes and burnup codes, and complete integration of burnup capability into Monte Carlo transport codes, have been or are currently being developed. Monte Carlo linked burnup methodologies may serve as an excellent benchmark for new deterministic burnup codes used for advanced systems; however, there are some instances where deterministic methodologies break down (i.e., heavily angularly biased systems containing exotic materials without proper group structure) and Monte Carlo burn up may serve as an actual design tool. Therefore, researchers are also developing these capabilities in order to examine complex, three-dimensional exotic material systems that do not contain benchmark data. Providing a reference scheme implies being able to associate statistical errors to any neutronic value of interest like k(eff), reaction rates, fluxes, etc. Usually in Monte Carlo, standard deviations are associated with a particular value by performing different independent and identical simulations (also referred to as 'cycles', 'batches', or 'replicas'), but this is only valid if the calculation itself is not biased. And, as will be shown in this paper, there is a bias in the methodology that consists of coupling transport and depletion codes because Bateman equations are not linear functions of the fluxes or of the reaction rates (those quantities being always measured with an uncertainty). Therefore, we have to quantify and correct this bias. This will be achieved by deriving an unbiased minimum variance estimator of a matrix exponential function of a normal mean. The result is then used to propose a reference scheme to solve Boltzmann/Bateman coupled equations, thanks to Monte Carlo transport codes. Numerical tests will be performed with an ad hoc Monte Carlo code on a very simple depletion case and will be compared to the theoretical results obtained with the reference scheme. Finally, the statistical error propagation
Detecting rater bias using a person-fit statistic: a Monte Carlo simulation study.
Aubin, André-Sébastien; St-Onge, Christina; Renaud, Jean-Sébastien
2018-04-01
With the Standards voicing concern for the appropriateness of response processes, we need to explore strategies that would allow us to identify inappropriate rater response processes. Although certain statistics can be used to help detect rater bias, their use is complicated by either a lack of data about their actual power to detect rater bias or the difficulty related to their application in the context of health professions education. This exploratory study aimed to establish the worthiness of pursuing the use of l z to detect rater bias. We conducted a Monte Carlo simulation study to investigate the power of a specific detection statistic, that is: the standardized likelihood l z person-fit statistics (PFS). Our primary outcome was the detection rate of biased raters, namely: raters whom we manipulated into being either stringent (giving lower scores) or lenient (giving higher scores), using the l z statistic while controlling for the number of biased raters in a sample (6 levels) and the rate of bias per rater (6 levels). Overall, stringent raters (M = 0.84, SD = 0.23) were easier to detect than lenient raters (M = 0.31, SD = 0.28). More biased raters were easier to detect then less biased raters (60% bias: 62, SD = 0.37; 10% bias: 43, SD = 0.36). The PFS l z seems to offer an interesting potential to identify biased raters. We observed detection rates as high as 90% for stringent raters, for whom we manipulated more than half their checklist. Although we observed very interesting results, we cannot generalize these results to the use of PFS with estimated item/station parameters or real data. Such studies should be conducted to assess the feasibility of using PFS to identify rater bias.
Energy Technology Data Exchange (ETDEWEB)
Dickens, J.K.
1988-04-01
This document provides a discussion of the development of the FORTRAN Monte Carlo program SCINFUL (for scintillator full response), a program designed to provide a calculated full response anticipated for either an NE-213 (liquid) scintillator or an NE-110 (solid) scintillator. The program may also be used to compute angle-integrated spectra of charged particles (p, d, t, /sup 3/He, and ..cap alpha..) following neutron interactions with /sup 12/C. Extensive comparisons with a variety of experimental data are given. There is generally overall good agreement (<10% differences) of results from SCINFUL calculations with measured detector responses, i.e., N(E/sub r/) vs E/sub r/ where E/sub r/ is the response pulse height, reproduce measured detector responses with an accuracy which, at least partly, depends upon how well the experimental configuration is known. For E/sub n/ < 16 MeV and for E/sub r/ > 15% of the maximum pulse height response, calculated spectra are within +-5% of experiment on the average. For E/sub n/ up to 50 MeV similar good agreement is obtained with experiment for E/sub r/ > 30% of maximum response. For E/sub n/ up to 75 MeV the calculated shape of the response agrees with measurements, but the calculations underpredicts the measured response by up to 30%. 65 refs., 64 figs., 3 tabs.
Modeling a secular trend by Monte Carlo simulation of height biased migration in a spatial network.
Groth, Detlef
2017-04-01
Background: In a recent Monte Carlo simulation, the clustering of body height of Swiss military conscripts within a spatial network with characteristic features of the natural Swiss geography was investigated. In this study I examined the effect of migration of tall individuals into network hubs on the dynamics of body height within the whole spatial network. The aim of this study was to simulate height trends. Material and methods: Three networks were used for modeling, a regular rectangular fishing net like network, a real world example based on the geographic map of Switzerland, and a random network. All networks contained between 144 and 148 districts and between 265-307 road connections. Around 100,000 agents were initially released with average height of 170 cm, and height standard deviation of 6.5 cm. The simulation was started with the a priori assumption that height variation within a district is limited and also depends on height of neighboring districts (community effect on height). In addition to a neighborhood influence factor, which simulates a community effect, body height dependent migration of conscripts between adjacent districts in each Monte Carlo simulation was used to re-calculate next generation body heights. In order to determine the direction of migration for taller individuals, various centrality measures for the evaluation of district importance within the spatial network were applied. Taller individuals were favored to migrate more into network hubs, backward migration using the same number of individuals was random, not biased towards body height. Network hubs were defined by the importance of a district within the spatial network. The importance of a district was evaluated by various centrality measures. In the null model there were no road connections, height information could not be delivered between the districts. Results: Due to the favored migration of tall individuals into network hubs, average body height of the hubs, and later
Monte Carlo based toy model for fission process
International Nuclear Information System (INIS)
Kurniadi, R.; Waris, A.; Viridi, S.
2014-01-01
There are many models and calculation techniques to obtain visible image of fission yield process. In particular, fission yield can be calculated by using two calculations approach, namely macroscopic approach and microscopic approach. This work proposes another calculation approach in which the nucleus is treated as a toy model. Hence, the fission process does not represent real fission process in nature completely. The toy model is formed by Gaussian distribution of random number that randomizes distance like the distance between particle and central point. The scission process is started by smashing compound nucleus central point into two parts that are left central and right central points. These three points have different Gaussian distribution parameters such as mean (μ CN , μ L , μ R ), and standard deviation (σ CN , σ L , σ R ). By overlaying of three distributions, the number of particles (N L , N R ) that are trapped by central points can be obtained. This process is iterated until (N L , N R ) become constant numbers. Smashing process is repeated by changing σ L and σ R , randomly
A Monte Carlo based spent fuel analysis safeguards strategy assessment
International Nuclear Information System (INIS)
Fensin, Michael L.; Tobin, Stephen J.; Swinhoe, Martyn T.; Menlove, Howard O.; Sandoval, Nathan P.
2009-01-01
Safeguarding nuclear material involves the detection of diversions of significant quantities of nuclear materials, and the deterrence of such diversions by the risk of early detection. There are a variety of motivations for quantifying plutonium in spent fuel assemblies by means of nondestructive assay (NDA) including the following: strengthening the capabilities of the International Atomic Energy Agencies ability to safeguards nuclear facilities, shipper/receiver difference, input accountability at reprocessing facilities and burnup credit at repositories. Many NDA techniques exist for measuring signatures from spent fuel; however, no single NDA technique can, in isolation, quantify elemental plutonium and other actinides of interest in spent fuel. A study has been undertaken to determine the best integrated combination of cost effective techniques for quantifying plutonium mass in spent fuel for nuclear safeguards. A standardized assessment process was developed to compare the effective merits and faults of 12 different detection techniques in order to integrate a few techniques and to down-select among the techniques in preparation for experiments. The process involves generating a basis burnup/enrichment/cooling time dependent spent fuel assembly library, creating diversion scenarios, developing detector models and quantifying the capability of each NDA technique. Because hundreds of input and output files must be managed in the couplings of data transitions for the different facets of the assessment process, a graphical user interface (GUI) was development that automates the process. This GUI allows users to visually create diversion scenarios with varied replacement materials, and generate a MCNPX fixed source detector assessment input file. The end result of the assembly library assessment is to select a set of common source terms and diversion scenarios for quantifying the capability of each of the 12 NDA techniques. We present here the generalized assessment process, the techniques employed to automate the coupled facets of the assessment process, and the standard burnup/enrichment/cooling time dependent spent fuel assembly library. We also clearly define the diversion scenarios that will be analyzed during the standardized assessments. Though this study is currently limited to generic PWR assemblies, it is expected that the results of the assessment will yield an adequate spent fuel analysis strategy knowledge that will help the down-select process for other reactor types
A Monte Carlo Based Spent Fuel Analysis Safeguards Strategy Assessment
Energy Technology Data Exchange (ETDEWEB)
Fensin, Michael L.; Tobin, Stephen J.; Swinhoe, Martyn T.; Menlove, Howard O.; Sandoval, Nathan P. [Los Alamos National Laboratory, E540, Los Alamos, NM 87545 (United States)
2009-06-15
Safeguarding nuclear material involves the detection of diversions of significant quantities of nuclear materials, and the deterrence of such diversions by the risk of early detection. There are a variety of motivations for quantifying plutonium in spent fuel assemblies by means of nondestructive assay (NDA) including the following: strengthening the capabilities of the International Atomic Energy Agencies ability to safeguards nuclear facilities, shipper/receiver difference, input accountability at reprocessing facilities and burnup credit at repositories. Many NDA techniques exist for measuring signatures from spent fuel; however, no single NDA technique can, in isolation, quantify elemental plutonium and other actinides of interest in spent fuel. A study has been undertaken to determine the best integrated combination of cost effective techniques for characterizing Pu mass in spent fuel for nuclear safeguards. A standardized assessment process was developed to compare the effective merits and faults of 12 different detection techniques in order to integrate a few techniques and to down-select among the techniques in preparation for experiments. The process involves generating a basis burnup/enrichment/cooling time dependent spent fuel assembly library, determining and identifying limiting diversion scenarios, developing detector models and quantifying the capability of each NDA technique. Because hundreds of input and output files must be managed in the couplings of data transitions for the different facets of the assessment process, a graphical user interface (GUI) was development that automates the process. This GUI allows users to visually create diversion scenarios with varied replacement materials, and generate a MCNPX fixed source detector assessment input file. The end result of the assembly library assessment is to select a set of common source terms and diversion scenarios for quantifying the capability of each of the 12 NDA techniques. We present here the generalized assessment process, the techniques employed to automate the coupled facets of the assessment process, and the standard burnup/enrichment/cooling time dependent spent fuel assembly library. We also clearly define the diversion scenarios that will be analyzed during the standardized assessments. Though this study is currently limited to generic PWR assemblies, it is expected that the results of the assessment will yield an adequate spent fuel analysis strategy knowledge that will help the down-select process for other reactor types. (authors)
Energy Technology Data Exchange (ETDEWEB)
Mendenhall, Marcus H., E-mail: marcus.h.mendenhall@vanderbilt.edu [Vanderbilt University, Department of Electrical Engineering, P.O. Box 351824B, Nashville, TN 37235 (United States); Weller, Robert A., E-mail: robert.a.weller@vanderbilt.edu [Vanderbilt University, Department of Electrical Engineering, P.O. Box 351824B, Nashville, TN 37235 (United States)
2012-03-01
In Monte Carlo particle transport codes, it is often important to adjust reaction cross-sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analog Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross-section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross-section change. This makes it possible to increase the cross-section of nuclear reactions by factors exceeding 10{sup 4} (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful in problems that involve the computation of particle penetration deep into a target (e.g. atmospheric showers or shielding studies).
International Nuclear Information System (INIS)
Mendenhall, Marcus H.; Weller, Robert A.
2012-01-01
In Monte Carlo particle transport codes, it is often important to adjust reaction cross-sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analog Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross-section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross-section change. This makes it possible to increase the cross-section of nuclear reactions by factors exceeding 10 4 (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful in problems that involve the computation of particle penetration deep into a target (e.g. atmospheric showers or shielding studies).
An importance biasing for 1-D deep-penetration problem by Monte Carlo
International Nuclear Information System (INIS)
Gupta, H.C.; Dwivedi, S.R.
1988-01-01
Using the itegral equations for the first and second moments of the 'total score' in an analogue and non-analogue simulations zero-variance biasing schemes have been obtained for all the commonly used reaction rate estimators. For partial score estimators a new zero-variance biasing scheme has been obtained as a special case. The new zero-variance scheme developed for partial score estimators has been used to develop an importance biasing scheme for use with expectation estimator in one dimensional deep-penetration problems with isotropic scattering. The importance biasing scheme has been studied for variance reduction in shields with anisotropic scattering. It is observed that the scheme not only results into a significant reduction in variance over the exponential biasing but also simplifies the complicated sampling procedure for the particle's outgoing direction at collision point. (author). 27 tables, 79 refs
International Nuclear Information System (INIS)
Dumonteil, E.
2009-01-01
Various variance-reduction techniques are used in Monte Carlo particle transport. Most of them rely either on a hypothesis made by the user (parameters of the exponential biasing, mesh and weight bounds for weight windows, etc.) or on a previous calculation of the system with, for example, a deterministic solver. This paper deals with a new acceleration technique, namely, auto-adaptative neural network biasing. Indeed, instead of using any a priori knowledge of the system, it is possible, at a given point in a simulation, to use the Monte Carlo histories previously simulated to train a neural network, which, in return, should be able to provide an estimation of the adjoint flux, used then for biasing the simulation. We will describe this method, detail its implementation in the Monte Carlo code Tripoli4, and discuss its results on two test cases. (author)
Monte Carlo simulations of microchannel plate detectors I: steady-state voltage bias results
Energy Technology Data Exchange (ETDEWEB)
Ming Wu, Craig Kruschwitz, Dane Morgan, Jiaming Morgan
2008-07-01
X-ray detectors based on straight-channel microchannel plates (MCPs) are a powerful diagnostic tool for two-dimensional, time-resolved imaging and timeresolved x-ray spectroscopy in the fields of laser-driven inertial confinement fusion and fast z-pinch experiments. Understanding the behavior of microchannel plates as used in such detectors is critical to understanding the data obtained. The subject of this paper is a Monte Carlo computer code we have developed to simulate the electron cascade in a microchannel plate under a static applied voltage. Also included in the simulation is elastic reflection of low-energy electrons from the channel wall, which is important at lower voltages. When model results were compared to measured microchannel plate sensitivities, good agreement was found. Spatial resolution simulations of MCP-based detectors were also presented and found to agree with experimental measurements.
International Nuclear Information System (INIS)
Ueki, T.; Larsen, E.W.
1998-01-01
The authors show that Monte Carlo simulations of neutral particle transport in planargeometry anisotropically scattering media, using the exponential transform with angular biasing as a variance reduction device, are governed by a new Boltzman Monte Carlo (BMC) equation, which includes particle weight as an extra independent variable. The weight moments of the solution of the BMC equation determine the moments of the score and the mean number of collisions per history in the nonanalog Monte Carlo simulations. Therefore, the solution of the BMC equation predicts the variance of the score and the figure of merit in the simulation. Also, by (1) using an angular biasing function that is closely related to the ''asymptotic'' solution of the linear Boltzman equation and (2) requiring isotropic weight changes as collisions, they derive a new angular biasing scheme. Using the BMC equation, they propose a universal ''safe'' upper limit of the transform parameter, valid for any type of exponential transform. In numerical calculations, they demonstrate that the behavior of the Monte Carlo simulations and the performance predicted by deterministically solving the BMC equation agree well, and that the new angular biasing scheme is always advantageous
International Nuclear Information System (INIS)
Richet, Y.; Jacquet, O.; Bay, X.
2005-01-01
The accuracy of an Iterative Monte Carlo calculation requires the convergence of the simulation output process. The present paper deals with a post processing algorithm to suppress the transient due to initialization applied on criticality calculations. It should be noticed that this initial transient suppression aims only at obtaining a stationary output series, then the convergence of the calculation needs to be guaranteed independently. The transient suppression algorithm consists in a repeated truncation of the first observations of the output process. The truncation of the first observations is performed as long as a steadiness test based on Brownian bridge theory is negative. This transient suppression method was previously tuned for a simplified model of criticality calculations, although this paper focuses on the efficiency on real criticality calculations. The efficiency test is based on four benchmarks with strong source convergence problems: 1) a checkerboard storage of fuel assemblies, 2) a pin cell array with irradiated fuel, 3) 3 one-dimensional thick slabs, and 4) an array of interacting fuel spheres. It appears that the transient suppression method needs to be more widely validated on real criticality calculations before any blind using as a post processing in criticality codes
Directory of Open Access Journals (Sweden)
Francesco Sarracino
2017-04-01
Full Text Available Recent studies documented that survey data contain duplicate records. We assess how duplicate records affect regression estimates, and we evaluate the effectiveness of solutions to deal with duplicate records. Results show that the chances of obtaining unbiased estimates when data contain 40 doublets (about 5% of the sample range between 3.5% and 11.5% depending on the distribution of duplicates. If 7 quintuplets are present in the data (2% of the sample, then the probability of obtaining biased estimates ranges between 11% and 20%. Weighting the duplicate records by the inverse of their multiplicity, or dropping superfluous duplicates outperform other solutions in all considered scenarios. Our results illustrate the risk of using data in presence of duplicate records and call for further research on strategies to analyze affected data.
Automatic Monte-Carlo tuning for minimum bias events at the LHC
Energy Technology Data Exchange (ETDEWEB)
Kama, Sami
2010-06-22
The Large Hadron Collider near Geneva Switzerland will ultimately collide protons at a center-of-mass energy of 14 TeV and 40 MHz bunch crossing rate with a luminosity of L=10{sup 34} cm{sup -2}s{sup -1}. At each bunch crossing about 20 soft proton-proton interactions are expected to happen. In order to study new phenomena and improve our current knowledge of the physics these events must be understood. However, the physics of soft interactions are not completely known at such high energies. Different phenomenological models, trying to explain these interactions, are implemented in several Monte-Carlo (MC) programs such as PYTHIA, PHOJET and EPOS. Some parameters in such MC programs can be tuned to improve the agreement with the data. In this thesis a new method for tuning the MC programs, based on Genetic Algorithms and distributed analysis techniques have been presented. This method represents the first and fully automated MC tuning technique that is based on true MC distributions. It is an alternative to parametrization-based automatic tuning. This new method is used in finding new tunes for PYTHIA 6 and 8. These tunes are compared to the tunes found by alternative methods, such as the PROFESSOR framework and manual tuning, and found to be equivalent or better. Charged particle multiplicity, dN{sub ch}/d{eta}, Lorentz-invariant yield, transverse momentum and mean transverse momentum distributions at various center-of-mass energies are generated using default tunes of EPOS, PHOJET and the Genetic Algorithm tunes of PYTHIA 6 and 8. These distributions are compared to measurements from UA5, CDF, CMS and ATLAS in order to investigate the best model available. Their predictions for the ATLAS detector at LHC energies have been investigated both with generator level and full detector simulation studies. Comparison with the data did not favor any model implemented in the generators, but EPOS is found to describe investigated distributions better. New data from ATLAS and
Automatic Monte-Carlo tuning for minimum bias events at the LHC
International Nuclear Information System (INIS)
Kama, Sami
2010-01-01
The Large Hadron Collider near Geneva Switzerland will ultimately collide protons at a center-of-mass energy of 14 TeV and 40 MHz bunch crossing rate with a luminosity of L=10 34 cm -2 s -1 . At each bunch crossing about 20 soft proton-proton interactions are expected to happen. In order to study new phenomena and improve our current knowledge of the physics these events must be understood. However, the physics of soft interactions are not completely known at such high energies. Different phenomenological models, trying to explain these interactions, are implemented in several Monte-Carlo (MC) programs such as PYTHIA, PHOJET and EPOS. Some parameters in such MC programs can be tuned to improve the agreement with the data. In this thesis a new method for tuning the MC programs, based on Genetic Algorithms and distributed analysis techniques have been presented. This method represents the first and fully automated MC tuning technique that is based on true MC distributions. It is an alternative to parametrization-based automatic tuning. This new method is used in finding new tunes for PYTHIA 6 and 8. These tunes are compared to the tunes found by alternative methods, such as the PROFESSOR framework and manual tuning, and found to be equivalent or better. Charged particle multiplicity, dN ch /dη, Lorentz-invariant yield, transverse momentum and mean transverse momentum distributions at various center-of-mass energies are generated using default tunes of EPOS, PHOJET and the Genetic Algorithm tunes of PYTHIA 6 and 8. These distributions are compared to measurements from UA5, CDF, CMS and ATLAS in order to investigate the best model available. Their predictions for the ATLAS detector at LHC energies have been investigated both with generator level and full detector simulation studies. Comparison with the data did not favor any model implemented in the generators, but EPOS is found to describe investigated distributions better. New data from ATLAS and CMS show higher
Yüksel, Yusuf; Akıncı, Ümit
2016-12-07
Using Monte Carlo simulations, we have investigated the dynamic phase transition properties of magnetic nanoparticles with ferromagnetic core coated by an antiferromagnetic shell structure. Effects of field amplitude and frequency on the thermal dependence of magnetizations, magnetization reversal mechanisms during hysteresis cycles, as well as on the exchange bias and coercive fields have been examined, and the feasibility of applying dynamic magnetic fields on the particle have been discussed for technological and biomedical purposes.
Mendenhall, Marcus H.; Weller, Robert A.
2011-01-01
In Monte Carlo particle transport codes, it is often important to adjust reaction cross sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analogous Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross section change. This makes it possible t...
International Nuclear Information System (INIS)
Yang Jinan; Mihara, Takatsugu
1998-12-01
This report presents a variance reduction technique to estimate the reliability and availability of highly complex systems during phased mission time using the Monte Carlo simulation. In this study, we introduced the variance reduction technique with a concept of distance between the present system state and the cut set configurations. Using this technique, it becomes possible to bias the transition from the operating states to the failed states of components towards the closest cut set. Therefore a component failure can drive the system towards a cut set configuration more effectively. JNC developed the PHAMMON (Phased Mission Analysis Program with Monte Carlo Method) code which involved the two kinds of variance reduction techniques: (1) forced transition, and (2) failure biasing. However, these techniques did not guarantee an effective reduction in variance. For further improvement, a variance reduction technique incorporating the distance concept was introduced to the PHAMMON code and the numerical calculation was carried out for the different design cases of decay heat removal system in a large fast breeder reactor. Our results indicate that the technique addition of this incorporating distance concept is an effective means of further reducing the variance. (author)
Energy Technology Data Exchange (ETDEWEB)
Sharma, D; Badano, A [Division of Imaging, Diagnostics and Software Reliability, OSEL/CDRH, Food & Drug Administration, MD (United States); Sempau, J [Technical University of Catalonia, Barcelona (Spain)
2016-06-15
Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. The weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.
Monte Carlo techniques in radiation therapy
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...
International Nuclear Information System (INIS)
Dickens, J.K.
1988-04-01
This document provides a discussion of the development of the FORTRAN Monte Carlo program SCINFUL (for scintillator full response), a program designed to provide a calculated full response anticipated for either an NE-213 (liquid) scintillator or an NE-110 (solid) scintillator. The program may also be used to compute angle-integrated spectra of charged particles (p, d, t, 3 He, and α) following neutron interactions with 12 C. Extensive comparisons with a variety of experimental data are given. There is generally overall good agreement ( 15% of the maximum pulse height response, calculated spectra are within +-5% of experiment on the average. For E/sub n/ up to 50 MeV similar good agreement is obtained with experiment for E/sub r/ > 30% of maximum response. For E/sub n/ up to 75 MeV the calculated shape of the response agrees with measurements, but the calculations underpredicts the measured response by up to 30%. 65 refs., 64 figs., 3 tabs
Kinetic-Monte-Carlo-Based Parallel Evolution Simulation Algorithm of Dust Particles
Directory of Open Access Journals (Sweden)
Xiaomei Hu
2014-01-01
Full Text Available The evolution simulation of dust particles provides an important way to analyze the impact of dust on the environment. KMC-based parallel algorithm is proposed to simulate the evolution of dust particles. In the parallel evolution simulation algorithm of dust particles, data distribution way and communication optimizing strategy are raised to balance the load of every process and reduce the communication expense among processes. The experimental results show that the simulation of diffusion, sediment, and resuspension of dust particles in virtual campus is realized and the simulation time is shortened by parallel algorithm, which makes up for the shortage of serial computing and makes the simulation of large-scale virtual environment possible.
Discrete Spin Vector Approach for Monte Carlo-based Magnetic Nanoparticle Simulations
Senkov, Alexander; Peralta, Juan; Sahay, Rahul
The study of magnetic nanoparticles has gained significant popularity due to the potential uses in many fields such as modern medicine, electronics, and engineering. To study the magnetic behavior of these particles in depth, it is important to be able to model and simulate their magnetic properties efficiently. Here we utilize the Metropolis-Hastings algorithm with a discrete spin vector model (in contrast to the standard continuous model) to model the magnetic hysteresis of a set of protected pure iron nanoparticles. We compare our simulations with the experimental hysteresis curves and discuss the efficiency of our algorithm.
An automated Monte-Carlo based method for the calculation of cascade summing factors
Energy Technology Data Exchange (ETDEWEB)
Jackson, M.J., E-mail: mark.j.jackson@awe.co.uk; Britton, R.; Davies, A.V.; McLarty, J.L.; Goodwin, M.
2016-10-21
A versatile method has been developed to calculate cascade summing factors for use in quantitative gamma-spectrometry analysis procedures. The proposed method is based solely on Evaluated Nuclear Structure Data File (ENSDF) nuclear data, an X-ray energy library, and accurate efficiency characterisations for single detector counting geometries. The algorithm, which accounts for γ–γ, γ–X, γ–511 and γ–e{sup −} coincidences, can be applied to any design of gamma spectrometer and can be expanded to incorporate any number of nuclides. Efficiency characterisations can be derived from measured or mathematically modelled functions, and can accommodate both point and volumetric source types. The calculated results are shown to be consistent with an industry standard gamma-spectrometry software package. Additional benefits including calculation of cascade summing factors for all gamma and X-ray emissions, not just the major emission lines, are also highlighted. - Highlights: • Versatile method to calculate coincidence summing factors for gamma-spectrometry analysis. • Based solely on ENSDF format nuclear data and detector efficiency characterisations. • Enables generation of a CSF library for any detector, geometry and radionuclide. • Improves measurement accuracy and reduces acquisition times required to meet MDA.
Monte Carlo; based validation of the ENDF/MC2-II/SDX cell homogenization path
International Nuclear Information System (INIS)
Wade, D.C.
1978-11-01
The results are summarized of a program of validation of the unit cell homogenization prescriptions and codes used for the analysis of Zero Power Reactor (ZPR) fast breeder reactor critical experiments. The ZPR drawer loading patterns comprise both plate type and pin-calandria type unit cells. A prescription is used to convert the three dimensional physical geometry of the drawer loadings into one dimensional calculational models. The ETOE-II/MC 2 -II/SDX code sequence is used to transform ENDF/B basic nuclear data into unit cell average broad group cross sections based on the 1D models. Cell average, broad group anisotropic diffusion coefficients are generated using the methods of Benoist or of Gelbard. The resulting broad (approx. 10 to 30) group parameters are used in multigroup diffusion and S/sub n/ transport calculations of full core XY or RZ models which employ smeared atom densities to represent the contents of the unit cells
Markov models for digraph panel data : Monte Carlo-based derivative estimation
Schweinberger, Michael; Snijders, Tom A. B.
2007-01-01
A parametric, continuous-time Markov model for digraph panel data is considered. The parameter is estimated by the method of moments. A convenient method for estimating the variance-covariance matrix of the moment estimator relies on the delta method, requiring the Jacobian matrix-that is, the
Development of a Monte-Carlo based method for calculating the effect of stationary fluctuations
DEFF Research Database (Denmark)
Pettersen, E. E.; Demazire, C.; Jareteg, K.
2015-01-01
equivalent problems nevertheless requires the possibility to modify the macroscopic cross-sections, and we use the work of Kuijper, van der Marck and Hogenbirk to define group-wise macroscopic cross-sections in MCNP [1]. The method is illustrated in this paper at a frequency of 1 Hz, for which only the real...
International Nuclear Information System (INIS)
Visvikis, D.; Lefevre, T.; Lamare, F.; Kontaxakis, G.; Santos, A.; Darambara, D.
2006-01-01
The majority of present position emission tomography (PET) animal systems are based on the coupling of high-density scintillators and light detectors. A disadvantage of these detector configurations is the compromise between image resolution, sensitivity and energy resolution. In addition, current combined imaging devices are based on simply placing back-to-back and in axial alignment different apparatus without any significant level of software or hardware integration. The use of semiconductor CdZnTe (CZT) detectors is a promising alternative to scintillators for gamma-ray imaging systems. At the same time CZT detectors have the potential properties necessary for the construction of a truly integrated imaging device (PET/SPECT/CT). The aims of this study was to assess the performance of different small animal PET scanner architectures based on CZT pixellated detectors and compare their performance with that of state of the art existing PET animal scanners. Different scanner architectures were modelled using GATE (Geant4 Application for Tomographic Emission). Particular scanner design characteristics included an overall cylindrical scanner format of 8 and 24 cm in axial and transaxial field of view, respectively, and a temporal coincidence window of 8 ns. Different individual detector modules were investigated, considering pixel pitch down to 0.625 mm and detector thickness from 1 to 5 mm. Modified NEMA NU2-2001 protocols were used in order to simulate performance based on mouse, rat and monkey imaging conditions. These protocols allowed us to directly compare the performance of the proposed geometries with the latest generation of current small animal systems. Results attained demonstrate the potential for higher NECR with CZT based scanners in comparison to scintillator based animal systems
Monte Carlo based demonstration of sufficiently dimensioned shielding for a Co-60 testing facility
International Nuclear Information System (INIS)
Wind, Michael; Beck, Peter; Latocha, Marcin
2015-01-01
The electrical properties of electronic equipment can be changed in an ionized radiation field. The knowledge of these changes is necessary for applications in space, in air traffic and nuclear medicine. Experimental tests will be performed in Co-60 radiation fields in the irradiation facility (TEC facility) of the Seibersdorf Labor GmbH that is in construction. The contribution deals with a simulation that is aimed to calculate the local dose rate within and outside the building for demonstration of sufficient dimensioning of the shielding in compliance with the legal dose rate limits.
An automated Monte-Carlo based method for the calculation of cascade summing factors
Jackson, M. J.; Britton, R.; Davies, A. V.; McLarty, J. L.; Goodwin, M.
2016-10-01
A versatile method has been developed to calculate cascade summing factors for use in quantitative gamma-spectrometry analysis procedures. The proposed method is based solely on Evaluated Nuclear Structure Data File (ENSDF) nuclear data, an X-ray energy library, and accurate efficiency characterisations for single detector counting geometries. The algorithm, which accounts for γ-γ, γ-X, γ-511 and γ-e- coincidences, can be applied to any design of gamma spectrometer and can be expanded to incorporate any number of nuclides. Efficiency characterisations can be derived from measured or mathematically modelled functions, and can accommodate both point and volumetric source types. The calculated results are shown to be consistent with an industry standard gamma-spectrometry software package. Additional benefits including calculation of cascade summing factors for all gamma and X-ray emissions, not just the major emission lines, are also highlighted.
Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy
Sharma, Sanjib
2017-08-01
Markov Chain Monte Carlo based Bayesian data analysis has now become the method of choice for analyzing and interpreting data in almost all disciplines of science. In astronomy, over the last decade, we have also seen a steady increase in the number of papers that employ Monte Carlo based Bayesian analysis. New, efficient Monte Carlo based methods are continuously being developed and explored. In this review, we first explain the basics of Bayesian theory and discuss how to set up data analysis problems within this framework. Next, we provide an overview of various Monte Carlo based methods for performing Bayesian data analysis. Finally, we discuss advanced ideas that enable us to tackle complex problems and thus hold great promise for the future. We also distribute downloadable computer software (available at https://github.com/sanjibs/bmcmc/ ) that implements some of the algorithms and examples discussed here.
Markov chain Monte Carlo methods in radiotherapy treatment planning
International Nuclear Information System (INIS)
Hugtenburg, R.P.
2001-01-01
The Markov chain method can be used to incorporate measured data in Monte Carlo based radiotherapy treatment planning. This paper shows that convergence to the measured data, within the target precision, is achievable. Relative output factors for blocked fields and oblique beams are shown to compare well with independent measurements according to the same criterion. (orig.)
Clinical considerations of Monte Carlo for electron radiotherapy treatment planning
International Nuclear Information System (INIS)
Faddegon, Bruce; Balogh, Judith; Mackenzie, Robert; Scora, Daryl
1998-01-01
Technical requirements for Monte Carlo based electron radiotherapy treatment planning are outlined. The targeted overall accuracy for estimate of the delivered dose is the least restrictive of 5% in dose, 5 mm in isodose position. A system based on EGS4 and capable of achieving this accuracy is described. Experience gained in system design and commissioning is summarized. The key obstacle to widespread clinical use of Monte Carlo is lack of clinically acceptable measurement based methodology for accurate commissioning
International Nuclear Information System (INIS)
Wilson, Brandon M; Smith, Barton L
2013-01-01
Uncertainties are typically assumed to be constant or a linear function of the measured value; however, this is generally not true. Particle image velocimetry (PIV) is one example of a measurement technique that has highly nonlinear, time varying local uncertainties. Traditional uncertainty methods are not adequate for the estimation of the uncertainty of measurement statistics (mean and variance) in the presence of nonlinear, time varying errors. Propagation of instantaneous uncertainty estimates into measured statistics is performed allowing accurate uncertainty quantification of time-mean and statistics of measurements such as PIV. It is shown that random errors will always elevate the measured variance, and thus turbulent statistics such as u'u'-bar. Within this paper, nonlinear, time varying errors are propagated from instantaneous measurements into the measured mean and variance using the Taylor-series method. With these results and knowledge of the systematic and random uncertainty of each measurement, the uncertainty of the time-mean, the variance and covariance can be found. Applicability of the Taylor-series uncertainty equations to time varying systematic and random errors and asymmetric error distributions are demonstrated with Monte-Carlo simulations. The Taylor-series uncertainty estimates are always accurate for uncertainties on the mean quantity. The Taylor-series variance uncertainty is similar to the Monte-Carlo results for cases in which asymmetric random errors exist or the magnitude of the instantaneous variations in the random and systematic errors is near the ‘true’ variance. However, the Taylor-series method overpredicts the uncertainty in the variance as the instantaneous variations of systematic errors are large or are on the same order of magnitude as the ‘true’ variance. (paper)
Directory of Open Access Journals (Sweden)
Grant B. Morgan
2015-02-01
Full Text Available Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.
Monte Carlo-based validation of the ENDF/MC2-II/SDX cell homogenization path
International Nuclear Information System (INIS)
Wade, D.C.
1979-04-01
The results are presented of a program of validation of the unit cell homogenization prescriptions and codes used for the analysis of Zero Power Reactor (ZPR) fast breeder reactor critical experiments. The ZPR drawer loading patterns comprise both plate type and pin-calandria type unit cells. A prescription is used to convert the three dimensional physical geometry of the drawer loadings into one dimensional calculational models. The ETOE-II/MC 2 -II/SDX code sequence is used to transform ENDF/B basic nuclear data into unit cell average broad group cross sections based on the 1D models. Cell average, broad group anisotropic diffusion coefficients are generated using the methods of Benoist or of Gelbard. The resulting broad (approx. 10 to 30) group parameters are used in multigroup diffusion and S/sub n/ transport calculations of full core XY or RZ models which employ smeared atom densities to represent the contents of the unit cells
Advanced Multilevel Monte Carlo Methods
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.
Advanced Multilevel Monte Carlo Methods
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.
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
Nievaart, V.A.; Legrady, D.; Moss, R.L.; Kloosterman, J.L.; Van der Hagen, T.H.; Van Dam, H.
2007-01-01
This paper deals with the application of the adjoint transport theory in order to optimize Monte Carlo based radiotherapy treatment planning. The technique is applied to Boron Neutron Capture Therapy where most often mixed beams of neutrons and gammas are involved. In normal forward Monte Carlo
Biased Monte Carlo algorithms on unitary groups
International Nuclear Information System (INIS)
Creutz, M.; Gausterer, H.; Sanielevici, S.
1989-01-01
We introduce a general updating scheme for the simulation of physical systems defined on unitary groups, which eliminates the systematic errors due to inexact exponentiation of algebra elements. The essence is to work directly with group elements for the stochastic noise. Particular cases of the scheme include the algorithm of Metropolis et al., overrelaxation algorithms, and globally corrected Langevin and hybrid algorithms. The latter are studied numerically for the case of SU(3) theory
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)
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.)
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
DEFF Research Database (Denmark)
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
The measurement issue is the key issue in the literature on trade policy-induced agri-cultural price incentive bias. This paper introduces a general equilibrium effective rate of protection (GE-ERP) measure, which extends and generalizes earlier partial equilibrium nominal protection measures...... shares and intersectoral linkages - are crucial for determining the sign and magnitude of trade policy bias. The GE-ERP measure is therefore uniquely suited to capture the full impact of trade policies on agricultural price incentives. A Monte Carlo procedure confirms that the results are robust....... For the 15 sample countries, the results indicate that the agricultural price incentive bias, which was generally perceived to exist during the 1980s, was largely eliminated during the 1990s. The results also demonstrate that general equilibrium effects and country-specific characteristics - including trade...
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.
International Nuclear Information System (INIS)
Cornelius, I.M.; Rosenfeld, A.B.
2003-01-01
Microdosimetry is used to predict the biological effects of the densely ionizing radiation environments of hadron therapy and space. The creation of a solid state microdosimeter to replace the conventional Tissue Equivalent Proportional Counter (TEPC) is a topic of ongoing research. The Centre for Medical Radiation Physics has been investigating a technique using microscopic arrays of reverse biased PN junctions. A prototype silicon-on-insulator (SOI) microdosimeter was developed and preliminary measurements have been conducted at several hadron therapy facilities. Several factors impede the application of silicon microdosimeters to hadron therapy. One of the major limitations is that of tissue equivalence, ideally the silicon microdosimeter should provide a microdosimetry distribution identical to that of a microscopic volume of tissue. For microdosimetry in neutron fields, such as Fast Neutron Therapy, it is important that products resulting from neutron interactions in the non tissue equivalent sensitive volume do not contribute significantly to the spectrum. Experimental measurements have been conducted at the Gershenson Radiation Oncology Center, Harper Hospital, Detroit by Bradley et al. The aim was to provide a comparison with measurements performed with a TEPC under identical experimental conditions. Monte Carlo based calculations of these measurements were made using the GEANT4 Monte Carlo toolkit. Agreement between experimental and theoretical results was observed. The model illustrated the importance of neutron interactions in the non tissue equivalent sensitive volume and showed this effect to decrease with sensitive volume size as expected. Simulations were also performed for 1 micron cubic silicon sensitive volumes embedded in tissue equivalent material to predict the best case scenario for silicon microdosimetry in Fast Neutron Therapy
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
Levy, David M; Peart, Sandra J
2008-06-01
We wish to deal with investigator bias in a statistical context. We sketch how a textbook solution to the problem of "outliers" which avoids one sort of investigator bias, creates the temptation for another sort. We write down a model of the approbation seeking statistician who is tempted by sympathy for client to violate the disciplinary standards. We give a simple account of one context in which we might expect investigator bias to flourish. Finally, we offer tentative suggestions to deal with the problem of investigator bias which follow from our account. As we have given a very sparse and stylized account of investigator bias, we ask what might be done to overcome this limitation.
Multiple histogram method and static Monte Carlo sampling
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
Zimmerman, George B.
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.
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
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
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
Continuous energy Monte Carlo method based homogenization multi-group constants calculation
International Nuclear Information System (INIS)
Li Mancang; Wang Kan; Yao Dong
2012-01-01
The efficiency of the standard two-step reactor physics calculation relies on the accuracy of multi-group constants from the assembly-level homogenization process. In contrast to the traditional deterministic methods, generating the homogenization cross sections 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 bank can be used for a wide range of applications, resulting in the versatility using Monte Carlo codes for homogenization. As the first stage to realize Monte Carlo based lattice homogenization, the track length scheme is used as the foundation of cross section generation, which is straight forward. The scattering matrix and Legendre components, however, require special techniques. The Scattering Event method was proposed to solve the problem. There are no continuous energy counterparts in the Monte Carlo calculation for neutron diffusion coefficients. P 1 cross sections were used to calculate the diffusion coefficients for diffusion reactor simulator codes. B N theory is applied to take the leakage effect into account when the infinite lattice of identical symmetric motives is assumed. The MCMC code was developed and the code was applied in four assembly configurations to assess the accuracy and the applicability. At core-level, A PWR prototype core is examined. The results show that the Monte Carlo based multi-group constants behave well in average. The method could be applied to complicated configuration nuclear reactor core to gain higher accuracy. (authors)
Harris, Ian
2016-01-01
I read with interest the comment by Mark Wilson in the Indian Journal of Medical Ethics regarding bias and conflicts of interest in medical journals. Wilson targets one journal (the New England Journal of Medicine: NEJM) and one particular "scandal" to make his point that journals' decisions on publication are biased by commercial conflicts of interest (CoIs). It is interesting that he chooses the NEJM which, by his own admission, had one of the strictest CoI policies and had published widely on this topic. The feeling is that if the NEJM can be guilty, they can all be guilty.
Josse Delfgaauw; Michiel Souverijn
2014-01-01
markdownabstract__Abstract__ When verifiable performance measures are imperfect, organizations often resort to subjective performance pay. This may give supervisors the power to direct employees towards tasks that mainly benefit the supervisor rather than the organization. We cast a principal-supervisor-agent model in a multitask setting, where the supervisor has an intrinsic preference towards specific tasks. We show that subjective performance pay based on evaluation by a biased supervisor ...
Automatic generation of biasing parameters for MORSE shielding problems
International Nuclear Information System (INIS)
Hoogenboom, J.E.
1995-01-01
It would be favourable if the biasing functions could be obtained from the Monte Carlo calculation itself. This is discussed in this paper as well as the way to obtain biasing parameters from it for splitting, Russian roulette and path length stretching. The method is demonstrated for a shielding problem solved with the MORSE-SGC/S Monte Carlo code of the SCALE-system. (K.A.)
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
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)
Eilert, Tobias; Beckers, Maximilian; Drechsler, Florian; Michaelis, Jens
2017-10-01
The analysis tool and software package Fast-NPS can be used to analyse smFRET data to obtain quantitative structural information about macromolecules in their natural environment. In the algorithm a Bayesian model gives rise to a multivariate probability distribution describing the uncertainty of the structure determination. Since Fast-NPS aims to be an easy-to-use general-purpose analysis tool for a large variety of smFRET networks, we established an MCMC based sampling engine that approximates the target distribution and requires no parameter specification by the user at all. For an efficient local exploration we automatically adapt the multivariate proposal kernel according to the shape of the target distribution. In order to handle multimodality, the sampler is equipped with a parallel tempering scheme that is fully adaptive with respect to temperature spacing and number of chains. Since the molecular surrounding of a dye molecule affects its spatial mobility and thus the smFRET efficiency, we introduce dye models which can be selected for every dye molecule individually. These models allow the user to represent the smFRET network in great detail leading to an increased localisation precision. Finally, a tool to validate the chosen model combination is provided. Programme Files doi:http://dx.doi.org/10.17632/7ztzj63r68.1 Licencing provisions: Apache-2.0 Programming language: GUI in MATLAB (The MathWorks) and the core sampling engine in C++ Nature of problem: Sampling of highly diverse multivariate probability distributions in order to solve for macromolecular structures from smFRET data. Solution method: MCMC algorithm with fully adaptive proposal kernel and parallel tempering scheme.
Energy Technology Data Exchange (ETDEWEB)
Suarez, Hector Sauri; Becker, Franz; Metz, Volker [Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen (Germany). Inst. for Nuclear Waste Disposal (INE); Pang, Bo [Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen (Germany). Inst. for Nuclear Waste Disposal (INE); Shenzhen Univ. (China). College of Physics and Energy
2017-06-15
In the operational phase of a deep geological disposal facility for high-level nuclear waste, the radiation field in the vicinity of a waste cask is influenced by the backscattered radiation of the surrounding walls of the emplacement drift. For a comparison of disposal of spent nuclear fuel in various host rocks, it is of interest to investigate the influence of the surrounding materials on the radiation field and the personal radiation exposure. In this generic study individual dosimetry of personnel involved in emplacement of casks with spent nuclear fuel in drifts in rock salt and in a clay formation was modelled.
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
Minimum variance Monte Carlo importance sampling with parametric dependence
International Nuclear Information System (INIS)
Ragheb, M.M.H.; Halton, J.; Maynard, C.W.
1981-01-01
An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de
Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo
Schön, Thomas B.; Svensson, Andreas; Murray, Lawrence; Lindsten, Fredrik
2018-05-01
Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space models. There is no closed-form solution available for this problem, implying that we are forced to use approximations. In this tutorial we will provide a self-contained introduction to one of the state-of-the-art methods-the particle Metropolis-Hastings algorithm-which has proven to offer a practical approximation. This is a Monte Carlo based method, where the particle filter is used to guide a Markov chain Monte Carlo method through the parameter space. One of the key merits of the particle Metropolis-Hastings algorithm is that it is guaranteed to converge to the "true solution" under mild assumptions, despite being based on a particle filter with only a finite number of particles. We will also provide a motivating numerical example illustrating the method using a modeling language tailored for sequential Monte Carlo methods. The intention of modeling languages of this kind is to open up the power of sophisticated Monte Carlo methods-including particle Metropolis-Hastings-to a large group of users without requiring them to know all the underlying mathematical details.
Monte Carlo method in radiation transport problems
International Nuclear Information System (INIS)
Dejonghe, G.; Nimal, J.C.; Vergnaud, T.
1986-11-01
In neutral radiation transport problems (neutrons, photons), two values are important: the flux in the phase space and the density of particles. To solve the problem with Monte Carlo method leads to, among other things, build a statistical process (called the play) and to provide a numerical value to a variable x (this attribution is called score). Sampling techniques are presented. Play biasing necessity is proved. A biased simulation is made. At last, the current developments (rewriting of programs for instance) are presented due to several reasons: two of them are the vectorial calculation apparition and the photon and neutron transport in vacancy media [fr
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.
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.)
Monte Carlo method for neutron transport problems
International Nuclear Information System (INIS)
Asaoka, Takumi
1977-01-01
Some methods for decreasing variances in Monte Carlo neutron transport calculations are presented together with the results of sample calculations. A general purpose neutron transport Monte Carlo code ''MORSE'' was used for the purpose. The first method discussed in this report is the method of statistical estimation. As an example of this method, the application of the coarse-mesh rebalance acceleration method to the criticality calculation of a cylindrical fast reactor is presented. Effective multiplication factor and its standard deviation are presented as a function of the number of histories and comparisons are made between the coarse-mesh rebalance method and the standard method. Five-group neutron fluxes at core center are also compared with the result of S4 calculation. The second method is the method of correlated sampling. This method was applied to the perturbation calculation of control rod worths in a fast critical assembly (FCA-V-3) Two methods of sampling (similar flight paths and identical flight paths) are tested and compared with experimental results. For every cases the experimental value lies within the standard deviation of the Monte Carlo calculations. The third method is the importance sampling. In this report a biased selection of particle flight directions discussed. This method was applied to the flux calculation in a spherical fast neutron system surrounded by a 10.16 cm iron reflector. Result-direction biasing, path-length stretching, and no biasing are compared with S8 calculation. (Aoki, K.)
Metrics for Diagnosing Undersampling in Monte Carlo Tally Estimates
International Nuclear Information System (INIS)
Perfetti, Christopher M.; Rearden, Bradley T.
2015-01-01
This study explored the potential of using Markov chain convergence diagnostics to predict the prevalence and magnitude of biases due to undersampling in Monte Carlo eigenvalue and flux tally estimates. Five metrics were applied to two models of pressurized water reactor fuel assemblies and their potential for identifying undersampling biases was evaluated by comparing the calculated test metrics with known biases in the tallies. Three of the five undersampling metrics showed the potential to accurately predict the behavior of undersampling biases in the responses examined in this study.
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
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.
Development of a space radiation Monte Carlo computer simulation based on the FLUKA and ROOT codes
Pinsky, L; Ferrari, A; Sala, P; Carminati, F; Brun, R
2001-01-01
This NASA funded project is proceeding to develop a Monte Carlo-based computer simulation of the radiation environment in space. With actual funding only initially in place at the end of May 2000, the study is still in the early stage of development. The general tasks have been identified and personnel have been selected. The code to be assembled will be based upon two major existing software packages. The radiation transport simulation will be accomplished by updating the FLUKA Monte Carlo program, and the user interface will employ the ROOT software being developed at CERN. The end-product will be a Monte Carlo-based code which will complement the existing analytic codes such as BRYNTRN/HZETRN presently used by NASA to evaluate the effects of radiation shielding in space. The planned code will possess the ability to evaluate the radiation environment for spacecraft and habitats in Earth orbit, in interplanetary space, on the lunar surface, or on a planetary surface such as Mars. Furthermore, it will be usef...
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...
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.
Bias against research on gender bias.
Cislak, Aleksandra; Formanowicz, Magdalena; Saguy, Tamar
2018-01-01
The bias against women in academia is a documented phenomenon that has had detrimental consequences, not only for women, but also for the quality of science. First, gender bias in academia affects female scientists, resulting in their underrepresentation in academic institutions, particularly in higher ranks. The second type of gender bias in science relates to some findings applying only to male participants, which produces biased knowledge. Here, we identify a third potentially powerful source of gender bias in academia: the bias against research on gender bias. In a bibliometric investigation covering a broad range of social sciences, we analyzed published articles on gender bias and race bias and established that articles on gender bias are funded less often and published in journals with a lower Impact Factor than articles on comparable instances of social discrimination. This result suggests the possibility of an underappreciation of the phenomenon of gender bias and related research within the academic community. Addressing this meta-bias is crucial for the further examination of gender inequality, which severely affects many women across the world.
A Monte Carlo technique for signal level detection in implanted intracranial pressure monitoring.
Avent, R K; Charlton, J D; Nagle, H T; Johnson, R N
1987-01-01
Statistical monitoring techniques like CUSUM, Trigg's tracking signal and EMP filtering have a major advantage over more recent techniques, such as Kalman filtering, because of their inherent simplicity. In many biomedical applications, such as electronic implantable devices, these simpler techniques have greater utility because of the reduced requirements on power, logic complexity and sampling speed. The determination of signal means using some of the earlier techniques are reviewed in this paper, and a new Monte Carlo based method with greater capability to sparsely sample a waveform and obtain an accurate mean value is presented. This technique may find widespread use as a trend detection method when reduced power consumption is a requirement.
Weight window/importance generator for Monte Carlo streaming problems
International Nuclear Information System (INIS)
Booth, T.E.
1983-01-01
A Monte Carlo method for solving highly angle dependent streaming problems is described. The method uses a DXTRAN-like angle biasing scheme, a space-angle weight window to reduce weight fluctuations introduced by the angle biasing, and a space-angle importance generator to set parameters for the space-angle weight window. Particle leakage through a doubly-bent duct is calculated to demonstrate the method's use
XSDRNPM-S biasing of MORSE-SGC/S shipping-cask calculations
International Nuclear Information System (INIS)
Hoffman, T.J.; Tang, J.S.
1982-06-01
This report describes implementation of a systematic approach for biasing a Monte Carlo radiation transport calculation. In particular, the adjoint fluxes from a one-dimensional discrete ordinates calculation with the XSDRNPM-S code are used to generate biasing parameters for the multigroup Monte Carlo code, MORSE-SGC/S. Application of this biasing procedure to several deep penetration spent fuel shipping cask problems is also reported. The results obtained for neutron and gamma-ray transport indicate that relatively inexpensive Monte Carlo calculations are possible for dry and water filled shipping cask problems using these procedures. 5 tables
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
MCOR - Monte Carlo depletion code for reference LWR calculations
Energy Technology Data Exchange (ETDEWEB)
Puente Espel, Federico, E-mail: fup104@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Tippayakul, Chanatip, E-mail: cut110@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Ivanov, Kostadin, E-mail: kni1@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Misu, Stefan, E-mail: Stefan.Misu@areva.com [AREVA, AREVA NP GmbH, Erlangen (Germany)
2011-04-15
Research highlights: > Introduction of a reference Monte Carlo based depletion code with extended capabilities. > Verification and validation results for MCOR. > Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations. Additionally
MCOR - Monte Carlo depletion code for reference LWR calculations
International Nuclear Information System (INIS)
Puente Espel, Federico; Tippayakul, Chanatip; Ivanov, Kostadin; Misu, Stefan
2011-01-01
Research highlights: → Introduction of a reference Monte Carlo based depletion code with extended capabilities. → Verification and validation results for MCOR. → Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations
Significant biases affecting abundance determinations
Wesson, Roger
2015-08-01
I have developed two highly efficient codes to automate analyses of emission line nebulae. The tools place particular emphasis on the propagation of uncertainties. The first tool, ALFA, uses a genetic algorithm to rapidly optimise the parameters of gaussian fits to line profiles. It can fit emission line spectra of arbitrary resolution, wavelength range and depth, with no user input at all. It is well suited to highly multiplexed spectroscopy such as that now being carried out with instruments such as MUSE at the VLT. The second tool, NEAT, carries out a full analysis of emission line fluxes, robustly propagating uncertainties using a Monte Carlo technique.Using these tools, I have found that considerable biases can be introduced into abundance determinations if the uncertainty distribution of emission lines is not well characterised. For weak lines, normally distributed uncertainties are generally assumed, though it is incorrect to do so, and significant biases can result. I discuss observational evidence of these biases. The two new codes contain routines to correctly characterise the probability distributions, giving more reliable results in analyses of emission line nebulae.
Energy Technology Data Exchange (ETDEWEB)
Wind, Michael; Beck, Peter; Latocha, Marcin [Seibersdorf Labor GmbH, Radiation Protection Dosimetry, Seibersdorf (Austria)
2015-07-01
The electrical properties of electronic equipment can be changed in an ionized radiation field. The knowledge of these changes is necessary for applications in space, in air traffic and nuclear medicine. Experimental tests will be performed in Co-60 radiation fields in the irradiation facility (TEC facility) of the Seibersdorf Labor GmbH that is in construction. The contribution deals with a simulation that is aimed to calculate the local dose rate within and outside the building for demonstration of sufficient dimensioning of the shielding in compliance with the legal dose rate limits.
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 ...
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)
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
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
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)
Einstein, Gnanatheepam; Udayakumar, Kanniyappan; Aruna, Prakasarao; Ganesan, Singaravelu
2017-03-01
Fluorescence of Protein has been widely used in diagnostic oncology for characterizing cellular metabolism. However, the intensity of fluorescence emission is affected due to the absorbers and scatterers in tissue, which may lead to error in estimating exact protein content in tissue. Extraction of intrinsic fluorescence from measured fluorescence has been achieved by different methods. Among them, Monte Carlo based method yields the highest accuracy for extracting intrinsic fluorescence. In this work, we have attempted to generate a lookup table for Monte Carlo simulation of fluorescence emission by protein. Furthermore, we fitted the generated lookup table using an empirical relation. The empirical relation between measured and intrinsic fluorescence is validated using tissue phantom experiments. The proposed relation can be used for estimating intrinsic fluorescence of protein for real-time diagnostic applications and thereby improving the clinical interpretation of fluorescence spectroscopic data.
Monte Carlo codes and Monte Carlo simulator program
International Nuclear Information System (INIS)
Higuchi, Kenji; Asai, Kiyoshi; Suganuma, Masayuki.
1990-03-01
Four typical Monte Carlo codes KENO-IV, MORSE, MCNP and VIM have been vectorized on VP-100 at Computing Center, JAERI. The problems in vector processing of Monte Carlo codes on vector processors have become clear through the work. As the result, it is recognized that these are difficulties to obtain good performance in vector processing of Monte Carlo codes. A Monte Carlo computing machine, which processes the Monte Carlo codes with high performances is being developed at our Computing Center since 1987. The concept of Monte Carlo computing machine and its performance have been investigated and estimated by using a software simulator. In this report the problems in vectorization of Monte Carlo codes, Monte Carlo pipelines proposed to mitigate these difficulties and the results of the performance estimation of the Monte Carlo computing machine by the simulator are described. (author)
Combination of biased forecasts: Bias correction or bias based weights?
Wenzel, Thomas
1999-01-01
Most of the literature on combination of forecasts deals with the assumption of unbiased individual forecasts. Here, we consider the case of biased forecasts and discuss two different combination techniques resulting in an unbiased forecast. On the one hand we correct the individual forecasts, and on the other we calculate bias based weights. A simulation study gives some insight in the situations where we should use the different methods.
Systematic approach to establishing criticality biases
International Nuclear Information System (INIS)
Larson, S.L.
1995-09-01
A systematic approach has been developed to determine benchmark biases and apply those biases to code results to meet the requirements of DOE Order 5480.24 regarding documenting criticality safety margins. Previously, validation of the code against experimental benchmarks to prove reasonable agreement was sufficient. However, DOE Order 5480.24 requires contractors to adhere to the requirements of ANSI/ANS-8.1 and establish subcritical margins. A method was developed to incorporate biases and uncertainties from benchmark calculations into a k eff value with quantifiable uncertainty. The method produces a 95% confidence level in both the k eff value of the scenario modeled and the distribution of the k eff S calculated by the Monte Carlo code. Application of the method to a group of benchmarks modeled using the KENO-Va code and the SCALE 27 group cross sections is also presented
Suppression of the initial transient in Monte Carlo criticality simulations
International Nuclear Information System (INIS)
Richet, Y.
2006-12-01
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)
Hybrid biasing approaches for global variance reduction
International Nuclear Information System (INIS)
Wu, Zeyun; Abdel-Khalik, Hany S.
2013-01-01
A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.
ATLAS Monte Carlo tunes for MC09
The ATLAS collaboration
2010-01-01
This note describes the ATLAS tunes of underlying event and minimum bias description for the main Monte Carlo generators used in the MC09 production. For the main shower generators, pythia and herwig (with jimmy), the MRST LO* parton distribution functions (PDFs) were used for the first time in ATLAS. Special studies on the performance of these, conceptually new, PDFs for high pt physics processes at LHC energies are presented. In addition, a tune of jimmy for CTEQ6.6 is presented, for use with MC@NLO.
MBR Monte Carlo Simulation in PYTHIA8
Ciesielski, R.
We present the MBR (Minimum Bias Rockefeller) Monte Carlo simulation of (anti)proton-proton interactions and its implementation in the PYTHIA8 event generator. We discuss the total, elastic, and total-inelastic cross sections, and three contributions from diffraction dissociation processes that contribute to the latter: single diffraction, double diffraction, and central diffraction or double-Pomeron exchange. The event generation follows a renormalized-Regge-theory model, successfully tested using CDF data. Based on the MBR-enhanced PYTHIA8 simulation, we present cross-section predictions for the LHC and beyond, up to collision energies of 50 TeV.
Importance biasing quality criterion based on contribution response theory
International Nuclear Information System (INIS)
Borisov, N.M.; Panin, M.P.
2001-01-01
The report proposes a visual criterion of importance biasing both of forward and adjoint simulation. The similarity of contribution Monte Carlo and importance biasing random collision event distribution is proved. The conservation of total number of random trajectory crossings of surfaces, which separate the source and the detector is proposed as importance biasing quality criterion. The use of this criterion is demonstrated on the example of forward vs. adjoint importance biasing in gamma ray deep penetration problem. The larger amount of published data on forward field characteristics than on adjoint leads to the more accurate approximation of adjoint importance function in comparison to forward, for it adjoint importance simulation is more effective than forward. The proposed criterion indicates it visually, showing the most uniform distribution of random trajectory crossing events for the most effective importance biasing parameters and pointing to the direction of tuning importance biasing parameters. (orig.)
Monte Carlo work at Argonne National Laboratory
International Nuclear Information System (INIS)
Gelbard, E.M.; Prael, R.E.
1974-01-01
A simple model of the Monte Carlo process is described and a (nonlinear) recursion relation between fission sources in successive generations is developed. From the linearized form of these recursion relations, it is possible to derive expressions for the mean square coefficients of error modes in the iterates and for correlation coefficients between fluctuations in successive generations. First-order nonlinear terms in the recursion relation are analyzed. From these nonlinear terms an expression for the bias in the eigenvalue estimator is derived, and prescriptions for measuring the bias are formulated. Plans for the development of the VIM code are reviewed, and the proposed treatment of small sample perturbations in VIM is described. 6 references. (U.S.)
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
Indian Academy of Sciences (India)
Administrator
Journal of Genetics, Vol. 83, No. 2, August 2004. Keywords. codon bias; alcohol dehydrogenase; Darwinian ... RESEARCH COMMENTARY. Benefits of being biased! SUTIRTH DEY*. Evolutionary Biology Laboratory, Evolutionary & Organismal Biology Unit,. Jawaharlal Nehru Centre for Advanced Scientific Research,.
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.
Doronin, Alexander; Rushmeier, Holly E.; Meglinski, Igor; Bykov, Alexander V.
2016-03-01
We present a new Monte Carlo based approach for the modelling of Bidirectional Scattering-Surface Reflectance Distribution Function (BSSRDF) for accurate rendering of human skin appearance. The variations of both skin tissues structure and the major chromophores are taken into account correspondingly to the different ethnic and age groups. The computational solution utilizes HTML5, accelerated by the graphics processing units (GPUs), and therefore is convenient for the practical use at the most of modern computer-based devices and operating systems. The results of imitation of human skin reflectance spectra, corresponding skin colours and examples of 3D faces rendering are presented and compared with the results of phantom studies.
Monte Carlo and Quasi-Monte Carlo Sampling
Lemieux, Christiane
2009-01-01
Presents essential tools for using quasi-Monte Carlo sampling in practice. This book focuses on issues related to Monte Carlo methods - uniform and non-uniform random number generation, variance reduction techniques. It covers several aspects of quasi-Monte Carlo methods.
BIASED BEARINGS-ONIKY PARAMETER ESTIMATION FOR BISTATIC SYSTEM
Institute of Scientific and Technical Information of China (English)
Xu Benlian; Wang Zhiquan
2007-01-01
According to the biased angles provided by the bistatic sensors,the necessary condition of observability and Cramer-Rao low bounds for the bistatic system are derived and analyzed,respectively.Additionally,a dual Kalman filter method is presented with the purpose of eliminating the effect of biased angles on the state variable estimation.Finally,Monte-Carlo simulations are conducted in the observable scenario.Simulation results show that the proposed theory holds true,and the dual Kalman filter method can estimate state variable and biased angles simultaneously.Furthermore,the estimated results can achieve their Cramer-Rao low bounds.
Scouting the feasibility of Monte Carlo reactor dynamics simulations
International Nuclear Information System (INIS)
Legrady, David; Hoogenboom, J. Eduard
2008-01-01
In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)
Scouting the feasibility of Monte Carlo reactor dynamics simulations
Energy Technology Data Exchange (ETDEWEB)
Legrady, David [Forschungszentrum Dresden-Rossendorf, Dresden (Germany); Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)
2008-07-01
In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (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.
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.
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
International Nuclear Information System (INIS)
Wollaber, Allan Benton
2016-01-01
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating @@), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
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
Energy Technology Data Exchange (ETDEWEB)
Wollaber, Allan Benton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-06-16
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
A New Bias Corrected Version of Heteroscedasticity Consistent Covariance Estimator
Directory of Open Access Journals (Sweden)
Munir Ahmed
2016-06-01
Full Text Available In the presence of heteroscedasticity, different available flavours of the heteroscedasticity consistent covariance estimator (HCCME are used. However, the available literature shows that these estimators can be considerably biased in small samples. Cribari–Neto et al. (2000 introduce a bias adjustment mechanism and give the modified White estimator that becomes almost bias-free even in small samples. Extending these results, Cribari-Neto and Galvão (2003 present a similar bias adjustment mechanism that can be applied to a wide class of HCCMEs’. In the present article, we follow the same mechanism as proposed by Cribari-Neto and Galvão to give bias-correction version of HCCME but we use adaptive HCCME rather than the conventional HCCME. The Monte Carlo study is used to evaluate the performance of our proposed estimators.
Directory of Open Access Journals (Sweden)
Chul Chung
2007-12-01
Full Text Available We estimate the CPI bias in Korea by employing the approach of Engel’s Law as suggested by Hamilton (2001. This paper is the first attempt to estimate the bias using Korean panel data, Korean Labor and Income Panel Study(KLIPS. Following Hamilton’s model with nonlinear specification correction, our estimation result shows that the cumulative CPI bias over the sample period (2000-2005 was 0.7 percent annually. This CPI bias implies that about 21 percent of the inflation rate during the period can be attributed to the bias. In light of purchasing power parity, we provide an interpretation of the estimated bias.
Neutron spectrum unfolding using genetic algorithm in a Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Suman, Vitisha [Health Physics Division, Bhabha Atomic Research Centre, Mumbai 400085 (India); Sarkar, P.K., E-mail: pksarkar02@gmail.com [Manipal Centre for Natural Sciences, Manipal University, Manipal 576104 (India)
2014-02-11
A spectrum unfolding technique GAMCD (Genetic Algorithm and Monte Carlo based spectrum Deconvolution) has been developed using the genetic algorithm methodology within the framework of Monte Carlo simulations. Each Monte Carlo history starts with initial solution vectors (population) as randomly generated points in the hyper dimensional solution space that are related to the measured data by the response matrix of the detection system. The transition of the solution points in the solution space from one generation to another are governed by the genetic algorithm methodology using the techniques of cross-over (mating) and mutation in a probabilistic manner adding new solution points to the population. The population size is kept constant by discarding solutions having lesser fitness values (larger differences between measured and calculated results). Solutions having the highest fitness value at the end of each Monte Carlo history are averaged over all histories to obtain the final spectral solution. The present method shows promising results in neutron spectrum unfolding for both under-determined and over-determined problems with simulated test data as well as measured data when compared with some existing unfolding codes. An attractive advantage of the present method is the independence of the final spectra from the initial guess spectra.
ARCHER, a new Monte Carlo software tool for emerging heterogeneous computing environments
International Nuclear Information System (INIS)
Xu, X. George; Liu, Tianyu; Su, Lin; Du, Xining; Riblett, Matthew; Ji, Wei; Gu, Deyang; Carothers, Christopher D.; Shephard, Mark S.; Brown, Forrest B.; Kalra, Mannudeep K.; Liu, Bob
2015-01-01
Highlights: • A fast Monte Carlo based radiation transport code ARCHER was developed. • ARCHER supports different hardware including CPU, GPU and Intel Xeon Phi coprocessor. • Code is benchmarked again MCNP for medical applications. • A typical CT scan dose simulation only takes 6.8 s on an NVIDIA M2090 GPU. • GPU and coprocessor-based codes are 5–8 times faster than the CPU-based codes. - Abstract: The Monte Carlo radiation transport community faces a number of challenges associated with peta- and exa-scale computing systems that rely increasingly on heterogeneous architectures involving hardware accelerators such as GPUs and Xeon Phi coprocessors. Existing Monte Carlo codes and methods must be strategically upgraded to meet emerging hardware and software needs. In this paper, we describe the development of a software, called ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments), which is designed as a versatile testbed for future Monte Carlo codes. Preliminary results from five projects in nuclear engineering and medical physics are presented
Neutron spectrum unfolding using genetic algorithm in a Monte Carlo simulation
International Nuclear Information System (INIS)
Suman, Vitisha; Sarkar, P.K.
2014-01-01
A spectrum unfolding technique GAMCD (Genetic Algorithm and Monte Carlo based spectrum Deconvolution) has been developed using the genetic algorithm methodology within the framework of Monte Carlo simulations. Each Monte Carlo history starts with initial solution vectors (population) as randomly generated points in the hyper dimensional solution space that are related to the measured data by the response matrix of the detection system. The transition of the solution points in the solution space from one generation to another are governed by the genetic algorithm methodology using the techniques of cross-over (mating) and mutation in a probabilistic manner adding new solution points to the population. The population size is kept constant by discarding solutions having lesser fitness values (larger differences between measured and calculated results). Solutions having the highest fitness value at the end of each Monte Carlo history are averaged over all histories to obtain the final spectral solution. The present method shows promising results in neutron spectrum unfolding for both under-determined and over-determined problems with simulated test data as well as measured data when compared with some existing unfolding codes. An attractive advantage of the present method is the independence of the final spectra from the initial guess spectra
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 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
International Nuclear Information System (INIS)
Blanchard, R.J.
1995-01-01
This documents Phase 1 determinations on sampler induced bias for four sampler types used in tank characterization. Each sampler, grab sampler or bottle-on-a-string, auger sampler, sludge sampler and universal sampler, is briefly discussed and their physical limits noted. Phase 2 of this document will define additional testing and analysis to further define Sampler Bias
2018-02-01
Department of the Army position unless so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an... Interior view of the photovoltaic bias generator showing wrapped-wire side of circuit board...3 Fig. 4 Interior view of the photovoltaic bias generator showing component side of circuit board
Das-Smaal, E.A.
1990-01-01
On what grounds can we conclude that an act of categorization is biased? In this chapter, it is contended that in the absence of objective norms of what categories actually are, biases in categorization can only be specified in relation to theoretical understandings of categorization. Therefore, the
Jazz Club
2012-01-01
The 5th edition of the "Monts Jura Jazz Festival" that will take place on September 21st and 22nd 2012 at the Esplanade du Lac in Divonne-les-Bains. This festival is organized by the "CERN Jazz Club" with the support of the "CERN Staff Association". This festival is a major musical event in the French/Swiss area and proposes a world class program with jazz artists such as D.Lockwood and D.Reinhardt. More information on http://www.jurajazz.com.
2012-01-01
The 5th edition of the "Monts Jura Jazz Festival" will take place at the Esplanade du Lac in Divonne-les-Bains, France on September 21 and 22. This festival organized by the CERN Jazz Club and supported by the CERN Staff Association is becoming a major musical event in the Geneva region. International Jazz artists like Didier Lockwood and David Reinhardt are part of this year outstanding program. Full program and e-tickets are available on the festival website. Don't miss this great festival!
Approximate Bias Correction in Econometrics
James G. MacKinnon; Anthony A. Smith Jr.
1995-01-01
This paper discusses ways to reduce the bias of consistent estimators that are biased in finite samples. It is necessary that the bias function, which relates parameter values to bias, should be estimable by computer simulation or by some other method. If so, bias can be reduced or, in some cases that may not be unrealistic, even eliminated. In general, several evaluations of the bias function will be required to do this. Unfortunately, reducing bias may increase the variance, or even the mea...
Energy Technology Data Exchange (ETDEWEB)
Galloway, Jack D.; Tobin, Stephen J.; Trellue, Holly R.; Fensin, Michael L. [Los Alamos National Laboratory, Los Alamos, (United States)
2011-12-15
The Next Generation Safeguards Initiate (NGSI) of the United States Department of Energy has funded a multi-laboratory/university collaboration to quantify plutonium content in spent fuel (SF) with non-destructive assay (NDA) techniques and quantify the capability of these NDA techniques to detect pin diversions from SF assemblies. The first Monte Carlo based spent fuel library (SFL) developed for the NGSI program contained information for 64 different types of SF assemblies (four initial enrichments, burnups, and cooling times). The maximum amount of fission products allowed to still model a 17x17 Westinghouse pressurized water reactor (PWR) fuel assembly with four regions per fuel pin was modelled. The number of fission products tracked was limited by the available memory. Studies have since indicated that additional fission product inclusion and asymmetric burning of the assembly is desired. Thus, an updated SFL has been developed using an enhanced version of MCNPX, more powerful computing resources, and the Monte Carlo-based burnup code Monteburns, which links MCNPX to a depletion code and models a representative 1 Division-Slash 8 core geometry containing one region per fuel pin in the assemblies of interest, including a majority of the fission products with available cross sections. Often in safeguards, the limiting factor in the accuracy of NDA instruments is the quality of the working standard used in calibration. In the case of SF this is anticipated to also be true, particularly for several of the neutron techniques. The fissile isotopes of interest are co-mingled with neutron absorbers that alter the measured count rate. This paper will quantify how well working standards can be generated for PWR spent fuel assemblies and also describe the spatial plutonium distribution across an assembly. More specifically we will demonstrate how Monte Carlo gamma measurement simulations and a Monte Carlo burnup code can be used to characterize the emitted gamma
International Nuclear Information System (INIS)
Xiao Gang; Li Zhizhong
2004-01-01
Based on integral equaiton describing the life-history of Markov system, six types of estimators of the current unavailability of Markov system with dependent repair are propounded. Combining with the biased sampling of state transition time of system, six types of Monte Carlo for estimating the current unavailability are given. Two numerical examples are given to deal with the variances and efficiencies of the six types of Monte Carlo methods. (authors)
Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy
Bonenfant, Éric; Magnoux, Vincent; Hissoiny, Sami; Ozell, Benoît; Beaulieu, Luc; Després, Philippe
2015-07-01
The aim of this study was to evaluate the potential of bGPUMCD, a Monte Carlo algorithm executed on Graphics Processing Units (GPUs), for fast dose calculations in permanent prostate implant dosimetry. It also aimed to validate a low dose rate brachytherapy source in terms of TG-43 metrics and to use this source to compute dose distributions for permanent prostate implant in very short times. The physics of bGPUMCD was reviewed and extended to include Rayleigh scattering and fluorescence from photoelectric interactions for all materials involved. The radial and anisotropy functions were obtained for the Nucletron SelectSeed in TG-43 conditions. These functions were compared to those found in the MD Anderson Imaging and Radiation Oncology Core brachytherapy source registry which are considered the TG-43 reference values. After appropriate calibration of the source, permanent prostate implant dose distributions were calculated for four patients and compared to an already validated Geant4 algorithm. The radial function calculated from bGPUMCD showed excellent agreement (differences within 1.3%) with TG-43 accepted values. The anisotropy functions at r = 1 cm and r = 4 cm were within 2% of TG-43 values for angles over 17.5°. For permanent prostate implants, Monte Carlo-based dose distributions with a statistical uncertainty of 1% or less for the target volume were obtained in 30 s or less for 1 × 1 × 1 mm3 calculation grids. Dosimetric indices were very similar (within 2.7%) to those obtained with a validated, independent Monte Carlo code (Geant4) performing the calculations for the same cases in a much longer time (tens of minutes to more than a hour). bGPUMCD is a promising code that lets envision the use of Monte Carlo techniques in a clinical environment, with sub-minute execution times on a standard workstation. Future work will explore the use of this code with an inverse planning method to provide a complete Monte Carlo-based planning solution.
Data analytics using canonical correlation analysis and Monte Carlo simulation
Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles
2017-07-01
A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.
Exchange bias in nearly perpendicularly coupled ferromagnetic/ferromagnetic system
International Nuclear Information System (INIS)
Bu, K.M.; Kwon, H.Y.; Oh, S.W.; Won, C.
2012-01-01
Exchange bias phenomena appear not only in ferromagnetic/antiferromagnetic systems but also in ferromagnetic/ferromagnetic systems in which two layers are nearly perpendicularly coupled. We investigated the origin of the symmetry-breaking mechanism and the relationship between the exchange bias and the system's energy parameters. We compared the results of computational Monte Carlo simulations with those of theoretical model calculation. We found that the exchange bias exhibited nonlinear behaviors, including sign reversal and singularities. These complicated behaviors were caused by two distinct magnetization processes depending on the interlayer coupling strength. The exchange bias reached a maximum at the transition between the two magnetization processes. - Highlights: ► Exchange bias phenomena are found in perpendicularly coupled F/F systems. ► Exchange bias exhibits nonlinear behaviors, including sign reversal and singularities. ► These complicated behaviors were caused by two distinct magnetization processes. ► Exchange bias reached a maximum at the transition between the two magnetization processes. ► We established an equation to maximize the exchange bias in perpendicularly coupled F/F system.
DEFF Research Database (Denmark)
Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan
2006-01-01
This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....
Directory of Open Access Journals (Sweden)
James Sundali
2006-07-01
Full Text Available We examine two departures of individual perceptions of randomness from probability theory: the hot hand and the gambler's fallacy, and their respective opposites. This paper's first contribution is to use data from the field (individuals playing roulette in a casino to demonstrate the existence and impact of these biases that have been previously documented in the lab. Decisions in the field are consistent with biased beliefs, although we observe significant individual heterogeneity in the population. A second contribution is to separately identify these biases within a given individual, then to examine their within-person correlation. We find a positive and significant correlation across individuals between hot hand and gambler's fallacy biases, suggesting a common (root cause of the two related errors. We speculate as to the source of this correlation (locus of control, and suggest future research which could test this speculation.
Introduction to Unconscious Bias
Schmelz, Joan T.
2010-05-01
We all have biases, and we are (for the most part) unaware of them. In general, men and women BOTH unconsciously devalue the contributions of women. This can have a detrimental effect on grant proposals, job applications, and performance reviews. Sociology is way ahead of astronomy in these studies. When evaluating identical application packages, male and female University psychology professors preferred 2:1 to hire "Brian” over "Karen” as an assistant professor. When evaluating a more experienced record (at the point of promotion to tenure), reservations were expressed four times more often when the name was female. This unconscious bias has a repeated negative effect on Karen's career. This talk will introduce the concept of unconscious bias and also give recommendations on how to address it using an example for a faculty search committee. The process of eliminating unconscious bias begins with awareness, then moves to policy and practice, and ends with accountability.
Anil V. Mishra; Umaru B. Conteh
2014-01-01
This paper constructs the float adjusted measure of home bias and explores the determinants of bond home bias by employing the International Monetary Fund's high quality dataset (2001 to 2009) on cross-border bond investment. The paper finds that Australian investors' prefer investing in countries with higher economic development and more developed bond markets. Exchange rate volatility appears to be an impediment for cross-border bond investment. Investors prefer investing in countries with ...
Uncertainty analysis using Monte Carlo method in the measurement of phase by ESPI
International Nuclear Information System (INIS)
Anguiano Morales, Marcelino; Martinez, Amalia; Rayas, J. A.; Cordero, Raul R.
2008-01-01
A method for simultaneously measuring whole field in-plane displacements by using optical fiber and based on the dual-beam illumination principle electronic speckle pattern interferometry (ESPI) is presented in this paper. A set of single mode optical fibers and beamsplitter are employed to split the laser beam into four beams of equal intensity.One pair of fibers is utilized to illuminate the sample in the horizontal plane so it is sensitive only to horizontal in-plane displacement. Another pair of optical fibers is set to be sensitive only to vertical in-plane displacement. Each pair of optical fibers differs in longitude to avoid unwanted interference. By means of a Fourier-transform method of fringe-pattern analysis (Takeda method), we can obtain the quantitative data of whole field displacements. We found the uncertainty associated with the phases by mean of Monte Carlo-based technique
International Nuclear Information System (INIS)
Lupton, L.R.; Keller, N.A.
1982-09-01
The design of a positron emission tomography (PET) ring camera involves trade-offs between such things as sensitivity, resolution and cost. As a design aid, a Monte Carlo simulation of a single-ring camera system has been developed. The model includes a source-filled phantom, collimators, detectors, and optional shadow shields and inter-crystal septa. Individual gamma rays are tracked within the system materials until they escape, are absorbed, or are detected. Compton and photelectric interactions are modelled. All system dimensions are variable within the computation. Coincidence and singles data are recorded according to type (true or scattered), annihilation origin, and detected energy. Photon fluxes at various points of interest, such as the edge of the phantom and the collimator, are available. This report reviews the basics of PET, describes the physics involved in the simulation, and provides detailed outlines of the routines
2003-01-01
MGS MOC Release No. MOC2-387, 10 June 2003This is a Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) wide angle view of the Charitum Montes, south of Argyre Planitia, in early June 2003. The seasonal south polar frost cap, composed of carbon dioxide, has been retreating southward through this area since spring began a month ago. The bright features toward the bottom of this picture are surfaces covered by frost. The picture is located near 57oS, 43oW. North is at the top, south is at the bottom. Sunlight illuminates the scene from the upper left. The area shown is about 217 km (135 miles) wide.
Monte Carlo criticality calculations accelerated by a growing neutron population
International Nuclear Information System (INIS)
Dufek, Jan; Tuttelberg, Kaur
2016-01-01
Highlights: • Efficiency is significantly improved when population size grows over cycles. • The bias in the fission source is balanced to other errors in the source. • The bias in the fission source decays over the cycle as the population grows. - Abstract: We propose a fission source convergence acceleration method for Monte Carlo criticality simulation. As the efficiency of Monte Carlo criticality simulations is sensitive to the selected neutron population size, the method attempts to achieve the acceleration via on-the-fly control of the neutron population size. The neutron population size is gradually increased over successive criticality cycles so that the fission source bias amounts to a specific fraction of the total error in the cumulative fission source. An optimal setting then gives a reasonably small neutron population size, allowing for an efficient source iteration; at the same time the neutron population size is chosen large enough to ensure a sufficiently small source bias, such that does not limit accuracy of the simulation.
Energy Technology Data Exchange (ETDEWEB)
Morillon, B.
1996-12-31
With most of the traditional and contemporary techniques, it is still impossible to solve the transport equation if one takes into account a fully detailed geometry and if one studies precisely the interactions between particles and matters. Only the Monte Carlo method offers such a possibility. However with significant attenuation, the natural simulation remains inefficient: it becomes necessary to use biasing techniques where the solution of the adjoint transport equation is essential. The Monte Carlo code Tripoli has been using such techniques successfully for a long time with different approximate adjoint solutions: these methods require from the user to find out some parameters. If this parameters are not optimal or nearly optimal, the biases simulations may bring about small figures of merit. This paper presents a description of the most important biasing techniques of the Monte Carlo code Tripoli ; then we show how to calculate the importance function for general geometry with multigroup cases. We present a completely automatic biasing technique where the parameters of the biased simulation are deduced from the solution of the adjoint transport equation calculated by collision probabilities. In this study we shall estimate the importance function through collision probabilities method and we shall evaluate its possibilities thanks to a Monte Carlo calculation. We compare different biased simulations with the importance function calculated by collision probabilities for one-group and multigroup problems. We have run simulations with new biasing method for one-group transport problems with isotropic shocks and for multigroup problems with anisotropic shocks. The results show that for the one-group and homogeneous geometry transport problems the method is quite optimal without splitting and russian roulette technique but for the multigroup and heterogeneous X-Y geometry ones the figures of merit are higher if we add splitting and russian roulette technique.
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
Bias-corrected estimation in potentially mildly explosive autoregressive models
DEFF Research Database (Denmark)
Haufmann, Hendrik; Kruse, Robinson
This paper provides a comprehensive Monte Carlo comparison of different finite-sample bias-correction methods for autoregressive processes. We consider classic situations where the process is either stationary or exhibits a unit root. Importantly, the case of mildly explosive behaviour is studied...... that the indirect inference approach oers a valuable alternative to other existing techniques. Its performance (measured by its bias and root mean squared error) is balanced and highly competitive across many different settings. A clear advantage is its applicability for mildly explosive processes. In an empirical...
Exchange bias of patterned systems: Model and numerical simulation
International Nuclear Information System (INIS)
Garcia, Griselda; Kiwi, Miguel; Mejia-Lopez, Jose; Ramirez, Ricardo
2010-01-01
The magnitude of the exchange bias field of patterned systems exhibits a notable increase in relation to the usual bilayer systems, where a continuous ferromagnetic film is deposited on an antiferromagnet insulator. Here we develop a model, and implement a Monte Carlo calculation, to interpret the experimental observations which is consistent with experimental results, on the basis of assuming a small fraction of spins pinned ferromagnetically in the antiferromagnetic interface layer.
DEFF Research Database (Denmark)
Paldam, Martin
is censoring: selection by the size of estimate; SR3 selects the optimal combination of fit and size; and SR4 selects the first satisficing result. The last four SRs are steered by priors and result in bias. The MST and the FAT-PET have been developed for detection and correction of such bias. The simulations......Economic research typically runs J regressions for each selected for publication – it is often selected as the ‘best’ of the regressions. The paper examines five possible meanings of the word ‘best’: SR0 is ideal selection with no bias; SR1 is polishing: selection by statistical fit; SR2...... are made by data variation, while the model is the same. It appears that SR0 generates narrow funnels much at odds with observed funnels, while the other four funnels look more realistic. SR1 to SR4 give the mean a substantial bias that confirms the prior causing the bias. The FAT-PET MRA works well...
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)
Lectures on Monte Carlo methods
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 sampling of fission multiplicity.
Energy Technology Data Exchange (ETDEWEB)
Hendricks, J. S. (John S.)
2004-01-01
Two new methods have been developed for fission multiplicity modeling in Monte Carlo calculations. The traditional method of sampling neutron multiplicity from fission is to sample the number of neutrons above or below the average. For example, if there are 2.7 neutrons per fission, three would be chosen 70% of the time and two would be chosen 30% of the time. For many applications, particularly {sup 3}He coincidence counting, a better estimate of the true number of neutrons per fission is required. Generally, this number is estimated by sampling a Gaussian distribution about the average. However, because the tail of the Gaussian distribution is negative and negative neutrons cannot be produced, a slight positive bias can be found in the average value. For criticality calculations, the result of rejecting the negative neutrons is an increase in k{sub eff} of 0.1% in some cases. For spontaneous fission, where the average number of neutrons emitted from fission is low, the error also can be unacceptably large. If the Gaussian width approaches the average number of fissions, 10% too many fission neutrons are produced by not treating the negative Gaussian tail adequately. The first method to treat the Gaussian tail is to determine a correction offset, which then is subtracted from all sampled values of the number of neutrons produced. This offset depends on the average value for any given fission at any energy and must be computed efficiently at each fission from the non-integrable error function. The second method is to determine a corrected zero point so that all neutrons sampled between zero and the corrected zero point are killed to compensate for the negative Gaussian tail bias. Again, the zero point must be computed efficiently at each fission. Both methods give excellent results with a negligible computing time penalty. It is now possible to include the full effects of fission multiplicity without the negative Gaussian tail bias.
EGS4, Electron Photon Shower Simulation by Monte-Carlo
International Nuclear Information System (INIS)
1998-01-01
1 - Description of program or function: The EGS code system is one of a chain of three codes designed to solve the electromagnetic shower problem by Monte Carlo simulation. This chain makes possible simulation of almost any electron-photon transport problem conceivable. The structure of the system, with its global features, modular form, and structured programming, is readily adaptable to virtually any interfacing scheme that is desired on the part of the user. EGS4 is a package of subroutines plus block data with a flexible user interface. This allows for greater flexibility without requiring the user to be overly familiar with the internal details of the code. Combining this with the macro facility capabilities of the Mortran3 language, this reduces the likelihood that user edits will introduce bugs into the code. EGS4 uses material cross section and branching ratio data created and fit by the companion code, PEGS4. EGS4 allows for the implementation of importance sampling and other variance reduction techniques such as leading particle biasing, splitting, path length biasing, Russian roulette, etc. 2 - Method of solution: EGS employs the Monte Carlo method of solution. It allows all of the fundamental processes to be included and arbitrary geometries can be treated, also. Other minor processes, such as photoneutron production, can be added as a further generalization. Since showers develop randomly according to the quantum laws of probability, each shower is different. We again are led to the Monte Carlo method. 3 - Restrictions on the complexity of the problem: None noted
Automatic fission source convergence criteria for Monte Carlo criticality calculations
International Nuclear Information System (INIS)
Shim, Hyung Jin; Kim, Chang Hyo
2005-01-01
The Monte Carlo criticality calculations for the multiplication factor and the power distribution in a nuclear system require knowledge of stationary or fundamental-mode fission source distribution (FSD) in the system. Because it is a priori unknown, so-called inactive cycle Monte Carlo (MC) runs are performed to determine it. The inactive cycle MC runs should be continued until the FSD converges to the stationary FSD. Obviously, if one stops them prematurely, the MC calculation results may have biases because the followup active cycles may be run with the non-stationary FSD. Conversely, if one performs the inactive cycle MC runs more than necessary, one is apt to waste computing time because inactive cycle MC runs are used to elicit the fundamental-mode FSD only. In the absence of suitable criteria for terminating the inactive cycle MC runs, one cannot but rely on empiricism in deciding how many inactive cycles one should conduct for a given problem. Depending on the problem, this may introduce biases into Monte Carlo estimates of the parameters one tries to calculate. The purpose of this paper is to present new fission source convergence criteria designed for the automatic termination of inactive cycle MC runs
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
Geology of Maxwell Montes, Venus
Head, J. W.; Campbell, D. B.; Peterfreund, A. R.; Zisk, S. A.
1984-01-01
Maxwell Montes represent the most distinctive topography on the surface of Venus, rising some 11 km above mean planetary radius. The multiple data sets of the Pioneer missing and Earth based radar observations to characterize Maxwell Montes are analyzed. Maxwell Montes is a porkchop shaped feature located at the eastern end of Lakshmi Planum. The main massif trends about North 20 deg West for approximately 1000 km and the narrow handle extends several hundred km West South-West WSW from the north end of the main massif, descending down toward Lakshmi Planum. The main massif is rectilinear and approximately 500 km wide. The southern and northern edges of Maxwell Montes coincide with major topographic boundaries defining the edge of Ishtar Terra.
Measuring agricultural policy bias
DEFF Research Database (Denmark)
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
2010-01-01
Measurement is a key issue in the literature on price incentive bias induced by trade policy. We introduce a general equilibrium measure of the relative effective rate of protection, which generalizes earlier protection measures. For our fifteen sample countries, results indicate that the agricul...
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
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
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)
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)
van Erp, T.S.; Dubbeldam, D.; Caremans, T.P.; Calero, S.; Martens, J.A.
2010-01-01
We devise an efficient Monte Carlo scheme to study the adsorption of a multicomponent gas in a nanoporous material. The configurational bias move is extended by a novel replica exchange procedure where the configurations of the different simulations describing one particular gas content are being
Monte Carlo Methods in ICF (LIRPP Vol. 13)
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.
Monte Carlo simulations of plutonium gamma-ray spectra
International Nuclear Information System (INIS)
Koenig, Z.M.; Carlson, J.B.; Wang, Tzu-Fang; Ruhter, W.D.
1993-01-01
Monte Carlo calculations were investigated as a means of simulating the gamma-ray spectra of Pu. These simulated spectra will be used to develop and evaluate gamma-ray analysis techniques for various nondestructive measurements. Simulated spectra of calculational standards can be used for code intercomparisons, to understand systematic biases and to estimate minimum detection levels of existing and proposed nondestructive analysis instruments. The capability to simulate gamma-ray spectra from HPGe detectors could significantly reduce the costs of preparing large numbers of real reference materials. MCNP was used for the Monte Carlo transport of the photons. Results from the MCNP calculations were folded in with a detector response function for a realistic spectrum. Plutonium spectrum peaks were produced with Lorentzian shapes, for the x-rays, and Gaussian distributions. The MGA code determined the Pu isotopes and specific power of this calculated spectrum and compared it to a similar analysis on a measured spectrum
Measurement bias of fluid velocity in molecular simulations
International Nuclear Information System (INIS)
Tysanner, Martin W.; Garcia, Alejandro L.
2004-01-01
In molecular simulations of fluid flow, the measurement of mean fluid velocity is considered to be a straightforward computation, yet there is some ambiguity in its definition. We show that in systems far from equilibrium, such as those with large temperature or velocity gradients, two commonly used definitions give slightly different results. Specifically, a bias can arise when computing the mean fluid velocity by measuring the mean particle velocity in a cell and averaging this mean over samples. We show that this bias comes from the correlation of momentum and density fluctuations in non-equilibrium fluids, obtain an analytical expression for predicting it, and discuss what system characteristics (e.g., number of particles per cell, temperature gradients) reduce or magnify the error. The bias has a physical origin so although we demonstrate it by direct simulation Monte Carlo (DSMC) computations, the same effect will be observed with other particle-based simulation methods, such as molecular dynamics and lattice gases
Efficient bias correction for magnetic resonance image denoising.
Mukherjee, Partha Sarathi; Qiu, Peihua
2013-05-30
Magnetic resonance imaging (MRI) is a popular radiology technique that is used for visualizing detailed internal structure of the body. Observed MRI images are generated by the inverse Fourier transformation from received frequency signals of a magnetic resonance scanner system. Previous research has demonstrated that random noise involved in the observed MRI images can be described adequately by the so-called Rician noise model. Under that model, the observed image intensity at a given pixel is a nonlinear function of the true image intensity and of two independent zero-mean random variables with the same normal distribution. Because of such a complicated noise structure in the observed MRI images, denoised images by conventional denoising methods are usually biased, and the bias could reduce image contrast and negatively affect subsequent image analysis. Therefore, it is important to address the bias issue properly. To this end, several bias-correction procedures have been proposed in the literature. In this paper, we study the Rician noise model and the corresponding bias-correction problem systematically and propose a new and more effective bias-correction formula based on the regression analysis and Monte Carlo simulation. Numerical studies show that our proposed method works well in various applications. Copyright © 2012 John Wiley & Sons, Ltd.
Estimation bias and bias correction in reduced rank autoregressions
DEFF Research Database (Denmark)
Nielsen, Heino Bohn
2017-01-01
This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...
Multilevel sequential Monte Carlo samplers
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 . âˆž>h0>h1â‹¯>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. Â© 2016 Elsevier B.V.
Multilevel sequential Monte Carlo samplers
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 . âˆž>h0>h1â‹¯>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. Â© 2016 Elsevier B.V.
Directory of Open Access Journals (Sweden)
Hector Barco-Ríos
2011-06-01
Full Text Available The manganites have been widely studied because of their important properties as colossal magnetoresistance and exchange bias that are important phenomena used in many technological applications. For this reason, in this work, a study of the exchange bias effect present in La2/3Ca1/3MnO3/La1/3Ca2/3MnO3. This study was carried out by using the Monte Carlo method and the Metropolis Algorithm. In order to make easy this study, a graphic user interface was built alloying a friendly interaction. The interface permits to control the thickness of Ferromagnetic and Antiferromagnetic layer, temperatures the magnetic field, the number of Monte Carlo steps and the exchange parameters. Results obtained reflected the influence of all of these parameters on the exchange bias and coercive fields.
Selection of important Monte Carlo histories
International Nuclear Information System (INIS)
Egbert, Stephen D.
1987-01-01
The 1986 Dosimetry System (DS86) for Japanese A-bomb survivors uses information describing the behavior of individual radiation particles, simulated by Monte Carlo methods, to calculate the transmission of radiation into structures and, thence, into humans. However, there are practical constraints on the number of such particle 'histories' that may be used. First, the number must be sufficiently high to provide adequate statistical precision fir any calculated quantity of interest. For integral quantities, such as dose or kerma, statistical precision of approximately 5% (standard deviation) is required to ensure that statistical uncertainties are not a major contributor to the overall uncertainty of the transmitted value. For differential quantities, such as scalar fluence spectra, 10 to 15% standard deviation on individual energy groups is adequate. Second, the number of histories cannot be so large as to require an unacceptably large amount of computer time to process the entire survivor data base. Given that there are approx. 30,000 survivors, each having 13 or 14 organs of interest, the number of histories per organ must be constrained to less than several ten's of thousands at the very most. Selection and use of the most important Monte Carlo leakage histories from among all those calculated allows the creation of an efficient house and organ radiation transmission system for use at RERF. While attempts have been made during the adjoint Monte Carlo calculation to bias the histories toward an efficient dose estimate, this effort has been far from satisfactory. Many of the adjoint histories on a typical leakage tape are either starting in an energy group in which there is very little kerma or dose or leaking into an energy group with very little free-field couple with. By knowing the typical free-field fluence and the fluence-to-dose factors with which the leaking histories will be used, one can select histories rom a leakage tape that will contribute to dose
Monte Carlo simulation of experiments
International Nuclear Information System (INIS)
Opat, G.I.
1977-07-01
An outline of the technique of computer simulation of particle physics experiments by the Monte Carlo method is presented. Useful special purpose subprograms are listed and described. At each stage the discussion is made concrete by direct reference to the programs SIMUL8 and its variant MONTE-PION, written to assist in the analysis of the radiative decay experiments μ + → e + ν sub(e) antiνγ and π + → e + ν sub(e)γ, respectively. These experiments were based on the use of two large sodium iodide crystals, TINA and MINA, as e and γ detectors. Instructions for the use of SIMUL8 and MONTE-PION are given. (author)
A Monte Carlo model for 3D grain evolution during welding
Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena
2017-09-01
Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bézier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. The model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.
Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz Ram model
Morin, Mario A.; Ficarazzo, Francesco
2006-04-01
Rock fragmentation is considered the most important aspect of production blasting because of its direct effects on the costs of drilling and blasting and on the economics of the subsequent operations of loading, hauling and crushing. Over the past three decades, significant progress has been made in the development of new technologies for blasting applications. These technologies include increasingly sophisticated computer models for blast design and blast performance prediction. Rock fragmentation depends on many variables such as rock mass properties, site geology, in situ fracturing and blasting parameters and as such has no complete theoretical solution for its prediction. However, empirical models for the estimation of size distribution of rock fragments have been developed. In this study, a blast fragmentation Monte Carlo-based simulator, based on the Kuz-Ram fragmentation model, has been developed to predict the entire fragmentation size distribution, taking into account intact and joints rock properties, the type and properties of explosives and the drilling pattern. Results produced by this simulator were quite favorable when compared with real fragmentation data obtained from a blast quarry. It is anticipated that the use of Monte Carlo simulation will increase our understanding of the effects of rock mass and explosive properties on the rock fragmentation by blasting, as well as increase our confidence in these empirical models. This understanding will translate into improvements in blasting operations, its corresponding costs and the overall economics of open pit mines and rock quarries.
Gamma streaming experiments for validation of Monte Carlo code
International Nuclear Information System (INIS)
Thilagam, L.; Mohapatra, D.K.; Subbaiah, K.V.; Iliyas Lone, M.; Balasubramaniyan, V.
2012-01-01
In-homogeneities in shield structures lead to considerable amount of leakage radiation (streaming) increasing the radiation levels in accessible areas. Development works on experimental as well as computational methods for quantifying this streaming radiation are still continuing. Monte Carlo based radiation transport code, MCNP is usually a tool for modeling and analyzing such problems involving complex geometries. In order to validate this computational method for streaming analysis, it is necessary to carry out some experimental measurements simulating these inhomogeneities like ducts and voids present in the bulk shields for typical cases. The data thus generated will be analysed by simulating the experimental set up employing MCNP code and optimized input parameters for the code in finding solutions for similar radiation streaming problems will be formulated. Comparison of experimental data obtained from radiation streaming experiments through ducts will give a set of thumb rules and analytical fits for total radiation dose rates within and outside the duct. The present study highlights the validation of MCNP code through the gamma streaming experiments carried out with the ducts of various shapes and dimensions. Over all, the present study throws light on suitability of MCNP code for the analysis of gamma radiation streaming problems for all duct configurations considered. In the present study, only dose rate comparisons have been made. Studies on spectral comparison of streaming radiation are in process. Also, it is planned to repeat the experiments with various shield materials. Since the penetrations and ducts through bulk shields are unavoidable in an operating nuclear facility the results on this kind of radiation streaming simulations and experiments will be very useful in the shield structure optimization without compromising the radiation safety
Latent degradation indicators estimation and prediction: A Monte Carlo approach
Zhou, Yifan; Sun, Yong; Mathew, Joseph; Wolff, Rodney; Ma, Lin
2011-01-01
Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.
Monte Carlo modelling of Schottky diode for rectenna simulation
Bernuchon, E.; Aniel, F.; Zerounian, N.; Grimault-Jacquin, A. S.
2017-09-01
Before designing a detector circuit, the electrical parameters extraction of the Schottky diode is a critical step. This article is based on a Monte-Carlo (MC) solver of the Boltzmann Transport Equation (BTE) including different transport mechanisms at the metal-semiconductor contact such as image force effect or tunneling. The weight of tunneling and thermionic current is quantified according to different degrees of tunneling modelling. The I-V characteristic highlights the dependence of the ideality factor and the current saturation with bias. Harmonic Balance (HB) simulation on a rectifier circuit within Advanced Design System (ADS) software shows that considering non-linear ideality factor and saturation current for the electrical model of the Schottky diode does not seem essential. Indeed, bias independent values extracted in forward regime on I-V curve are sufficient. However, the non-linear series resistance extracted from a small signal analysis (SSA) strongly influences the conversion efficiency at low input powers.
Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations
Directory of Open Access Journals (Sweden)
Roberto S. Flowers-Cano
2018-02-01
Full Text Available Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP, bias-corrected bootstrap (BC, accelerated bias-corrected bootstrap (BCA and a modified version of the standard bootstrap (MSB. Different simulation scenarios were analyzed. In some cases, the mother distribution function was fit to the random samples that were generated. In other cases, a distribution function different to the mother distribution was fit to the samples. When the fitted distribution had three parameters, and was the same as the mother distribution, the intervals constructed with the four techniques had acceptable coverage. However, the bootstrap techniques failed in several of the cases in which the fitted distribution had two parameters.
Strategije drevesnega preiskovanja Monte Carlo
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...
Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality
Bishara, Anthony J.; Hittner, James B.
2015-01-01
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
An Efficient Monte Carlo Approach to Compute PageRank for Large Graphs on a Single PC
Directory of Open Access Journals (Sweden)
Sonobe Tomohiro
2016-03-01
Full Text Available This paper describes a novel Monte Carlo based random walk to compute PageRanks of nodes in a large graph on a single PC. The target graphs of this paper are ones whose size is larger than the physical memory. In such an environment, memory management is a difficult task for simulating the random walk among the nodes. We propose a novel method that partitions the graph into subgraphs in order to make them fit into the physical memory, and conducts the random walk for each subgraph. By evaluating the walks lazily, we can conduct the walks only in a subgraph and approximate the random walk by rotating the subgraphs. In computational experiments, the proposed method exhibits good performance for existing large graphs with several passes of the graph data.
Directory of Open Access Journals (Sweden)
Anna Russo
Full Text Available Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders.
International Nuclear Information System (INIS)
Roy, Arup Singha; Palani Selvam, T.; Raman, Anand; Raja, V.; Chaudhury, Probal
2014-01-01
Over the years, various types of tritium-in-air monitors have been designed and developed based on different principles. Ionization chamber, proportional counter and scintillation detector systems are few among them. A plastic scintillator based, flow-cell type online tritium-in-air monitoring system was developed for online monitoring of tritium in air. The value of the scintillator mass inside the cell-volume, which maximizes the response of the detector system, should be obtained to get maximum efficiency. The present study is aimed to optimize the amount of mass of the plastic scintillator film for the flow-cell based tritium monitoring instrument so that maximum efficiency is achieved. The Monte Carlo based EGSnrc code system has been used for this purpose
Stepanek, J; Laissue, J A; Lyubimova, N; Di Michiel, F; Slatkin, D N
2000-01-01
Microbeam radiation therapy (MRT) is a currently experimental method of radiotherapy which is mediated by an array of parallel microbeams of synchrotron-wiggler-generated X-rays. Suitably selected, nominally supralethal doses of X-rays delivered to parallel microslices of tumor-bearing tissues in rats can be either palliative or curative while causing little or no serious damage to contiguous normal tissues. Although the pathogenesis of MRT-mediated tumor regression is not understood, as in all radiotherapy such understanding will be based ultimately on our understanding of the relationships among the following three factors: (1) microdosimetry, (2) damage to normal tissues, and (3) therapeutic efficacy. Although physical microdosimetry is feasible, published information on MRT microdosimetry to date is computational. This report describes Monte Carlo-based computational MRT microdosimetry using photon and/or electron scattering and photoionization cross-section data in the 1 e V through 100 GeV range distrib...
A continuation multilevel Monte Carlo algorithm
Collier, Nathan
2014-09-05
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. The actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients. © 2014, Springer Science+Business Media Dordrecht.
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)
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
International Nuclear Information System (INIS)
Cruz, C. M.; Pinera, I; Abreu, Y.; Leyva, A.
2007-01-01
Present work concerns with the implementation of a Monte Carlo based calculation algorithm describing particularly the occurrence of Atom Displacements induced by the Gamma Radiation interactions at a given target material. The Atom Displacement processes were considered only on the basis of single elastic scattering interactions among fast secondary electrons with matrix atoms, which are ejected from their crystalline sites at recoil energies higher than a given threshold energy. The secondary electron transport was described assuming typical approaches on this matter, where consecutive small angle scattering and very low energy transfer events behave as a continuously cuasi-classical electron state changes along a given path length delimited by two discrete high scattering angle and electron energy losses events happening on a random way. A limiting scattering angle was introduced and calculated according Moliere-Bethe-Goudsmit-Saunderson Electron Multiple Scattering, which allows splitting away secondary electrons single scattering processes from multiple one, according which a modified McKinley-Feshbach electron elastic scattering cross section arises. This distribution was statistically sampled and simulated in the framework of the Monte Carlo Method to perform discrete single electron scattering processes, particularly those leading to Atom Displacement events. The possibility of adding this algorithm to present existing open Monte Carlo code systems is analyze, in order to improve their capabilities. (Author)
International Nuclear Information System (INIS)
Wagner, J.C.; Haghighat, A.
1998-01-01
Although the Monte Carlo method is considered to be the most accurate method available for solving radiation transport problems, its applicability is limited by its computational expense. Thus, biasing techniques, which require intuition, guesswork, and iterations involving manual adjustments, are employed to make reactor shielding calculations feasible. To overcome this difficulty, the authors have developed a method for using the S N adjoint function for automated variance reduction of Monte Carlo calculations through source biasing and consistent transport biasing with the weight window technique. They describe the implementation of this method into the standard production Monte Carlo code MCNP and its application to a realistic calculation, namely, the reactor cavity dosimetry calculation. The computational effectiveness of the method, as demonstrated through the increase in calculational efficiency, is demonstrated and quantified. Important issues associated with this method and its efficient use are addressed and analyzed. Additional benefits in terms of the reduction in time and effort required of the user are difficult to quantify but are possibly as important as the computational efficiency. In general, the automated variance reduction method presented is capable of increases in computational performance on the order of thousands, while at the same time significantly reducing the current requirements for user experience, time, and effort. Therefore, this method can substantially increase the applicability and reliability of Monte Carlo for large, real-world shielding applications
Spatial Bias in Field-Estimated Unsaturated Hydraulic Properties
Energy Technology Data Exchange (ETDEWEB)
HOLT,ROBERT M.; WILSON,JOHN L.; GLASS JR.,ROBERT J.
2000-12-21
Hydraulic property measurements often rely on non-linear inversion models whose errors vary between samples. In non-linear physical measurement systems, bias can be directly quantified and removed using calibration standards. In hydrologic systems, field calibration is often infeasible and bias must be quantified indirectly. We use a Monte Carlo error analysis to indirectly quantify spatial bias in the saturated hydraulic conductivity, K{sub s}, and the exponential relative permeability parameter, {alpha}, estimated using a tension infiltrometer. Two types of observation error are considered, along with one inversion-model error resulting from poor contact between the instrument and the medium. Estimates of spatial statistics, including the mean, variance, and variogram-model parameters, show significant bias across a parameter space representative of poorly- to well-sorted silty sand to very coarse sand. When only observation errors are present, spatial statistics for both parameters are best estimated in materials with high hydraulic conductivity, like very coarse sand. When simple contact errors are included, the nature of the bias changes dramatically. Spatial statistics are poorly estimated, even in highly conductive materials. Conditions that permit accurate estimation of the statistics for one of the parameters prevent accurate estimation for the other; accurate regions for the two parameters do not overlap in parameter space. False cross-correlation between estimated parameters is created because estimates of K{sub s} also depend on estimates of {alpha} and both parameters are estimated from the same data.
International Nuclear Information System (INIS)
Kiwi, Miguel
2001-01-01
Research on the exchange bias (EB) phenomenon has witnessed a flurry of activity during recent years, which stems from its use in magnetic sensors and as stabilizers in magnetic reading heads. EB was discovered in 1956 but it attracted only limited attention until these applications, closely related to giant magnetoresistance, were developed during the last decade. In this review, I initially give a short introduction, listing the most salient experimental results and what is required from an EB theory. Next, I indicate some of the obstacles in the road towards a satisfactory understanding of the phenomenon. The main body of the text reviews and critically discusses the activity that has flourished, mainly during the last 5 years, in the theoretical front. Finally, an evaluation of the progress made, and a critical assessment as to where we stand nowadays along the road to a satisfactory theory, is presented
Bias modification training can alter approach bias and chocolate consumption.
Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika
2016-01-01
Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.
Development of fast and accurate Monte Carlo code MVP
International Nuclear Information System (INIS)
Mori, Takamasa
2001-01-01
The development work of fast and accurate Monte Carlo code MVP has started at JAERI in late 80s. From the beginning, the code was designed to utilize vector supercomputers and achieved higher computation speed by a factor of 10 or more compared with conventional codes. In 1994, the first version of MVP was released together with cross section libraries based on JENDL-3.1 and JENDL-3.2. In 1996, minor revision was made by adding several functions such as treatments of ENDF-B6 file 6 data, time dependent problem, and so on. Since 1996, several works have been carried out for the next version of MVP. The main works are (1) the development of continuous energy Monte Carlo burn-up calculation code MVP-BURN, (2) the development of a system to generate cross section libraries at arbitrary temperature, and (3) the study on error estimations and their biases in Monte Carlo eigenvalue calculations. This paper summarizes the main features of MVP, results of recent studies and future plans for MVP. (author)
(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.
Monte Carlo applications to core-following of the National Research Universal reactor (NRU)
International Nuclear Information System (INIS)
Nguyen, T.S.; Wang, X.; Leung, T.
2014-01-01
Reactor code TRIAD, relying on a two-group neutron diffusion model, is currently used for core-following of NRU - to track reactor assembly locations and burnups. The Monte Carlo (MCNP or SERPENT) full-reactor models of NRU can be used to provide the core power distribution for calculating fuel burnups, with WIMS-AECL providing fuel depletion calculations. The MCNP/WIMS core-following results were in good agreement with the measured data, within the expected biases. The Monte Carlo methods, still very time-consuming, need to be able to run faster before they can replace TRIAD for timely support of NRU operations. (author)
Religious Attitudes and Home Bias
C. Reggiani; G. Rossini
2008-01-01
Home bias affects trade in goods, services and financial assets. It is mostly generated by "natural" trade barriers. Among these dividers we may list many behavioral and sociological factors, such as status quo biases and a few kind of ‘embeddedness’. Unfortunately these factors are difficult to measure. An important part of ‘embeddedness’ may be related to religious attitudes. Is there any relation between economic home bias and religious attitudes at the individual tier? Our aim is to provi...
Bias in clinical intervention research
DEFF Research Database (Denmark)
Gluud, Lise Lotte
2006-01-01
Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical...... evidence is needed to evaluate their effects on the extent and direction of bias. This narrative review summarizes the findings of methodological studies on the influence of bias in clinical trials. A number of methodological studies suggest that lack of adequate randomization in published trial reports...
Importance biasing scheme implemented in the PRIZMA code
International Nuclear Information System (INIS)
Kandiev, I.Z.; Malyshkin, G.N.
1997-01-01
PRIZMA code is intended for Monte Carlo calculations of linear radiation transport problems. The code has wide capabilities to describe geometry, sources, material composition, and to obtain parameters specified by user. There is a capability to calculate path of particle cascade (including neutrons, photons, electrons, positrons and heavy charged particles) taking into account possible transmutations. Importance biasing scheme was implemented to solve the problems which require calculation of functionals related to small probabilities (for example, problems of protection against radiation, problems of detection, etc.). The scheme enables to adapt trajectory building algorithm to problem peculiarities
Selection bias and the Rubin-Ford effect
International Nuclear Information System (INIS)
James, P.A.; Joseph, R.D.; Collins, C.A.
1991-01-01
We have re-examined the 'Rubin-Ford effect', and more recent claims of galaxy streaming from the same galaxy sample, to investigate the impact of selection effects on these results. A 'Monte Carlo'-type analysis was applied to simulate the selection procedure used to obtain this sample, and a strong bias was identified, resulting in apparent velocity flows at 600-800 km s -1 . Thus the 'Rubin-Ford effect' and the associated galaxy streaming are spurious effects resulting from the method of sample selection. (author)
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
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.; Dean, D.J.; Langanke, K.
1997-01-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; the resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo (SMMC) methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, the thermal and rotational behavior of rare-earth and γ-soft nuclei, and the calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. (orig.)
Shell model Monte Carlo methods
International Nuclear Information System (INIS)
Koonin, S.E.
1996-01-01
We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of γ-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs
Information environment, behavioral biases, and home bias in analysts’ recommendations
DEFF Research Database (Denmark)
Farooq, Omar; Taouss, Mohammed
2012-01-01
Can information environment of a firm explain home bias in analysts’ recommendations? Can the extent of agency problems explain optimism difference between foreign and local analysts? This paper answers these questions by documenting the effect of information environment on home bias in analysts’...
Threat bias, not negativity bias, underpins differences in political ideology.
Lilienfeld, Scott O; Latzman, Robert D
2014-06-01
Although disparities in political ideology are rooted partly in dispositional differences, Hibbing et al.'s analysis paints with an overly broad brush. Research on the personality correlates of liberal-conservative differences points not to global differences in negativity bias, but to differences in threat bias, probably emanating from differences in fearfulness. This distinction bears implications for etiological research and persuasion efforts.
Parallel Monte Carlo reactor neutronics
International Nuclear Information System (INIS)
Blomquist, R.N.; Brown, F.B.
1994-01-01
The issues affecting implementation of parallel algorithms for large-scale engineering Monte Carlo neutron transport simulations are discussed. For nuclear reactor calculations, these include load balancing, recoding effort, reproducibility, domain decomposition techniques, I/O minimization, and strategies for different parallel architectures. Two codes were parallelized and tested for performance. The architectures employed include SIMD, MIMD-distributed memory, and workstation network with uneven interactive load. Speedups linear with the number of nodes were achieved
Elements of Monte Carlo techniques
International Nuclear Information System (INIS)
Nagarajan, P.S.
2000-01-01
The Monte Carlo method is essentially mimicking the real world physical processes at the microscopic level. With the incredible increase in computing speeds and ever decreasing computing costs, there is widespread use of the method for practical problems. The method is used in calculating algorithm-generated sequences known as pseudo random sequence (prs)., probability density function (pdf), test for randomness, extension to multidimensional integration etc
Adaptive Multilevel Monte Carlo Simulation
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).
Geometrical splitting in Monte Carlo
International Nuclear Information System (INIS)
Dubi, A.; Elperin, T.; Dudziak, D.J.
1982-01-01
A statistical model is presented by which a direct statistical approach yielded an analytic expression for the second moment, the variance ratio, and the benefit function in a model of an n surface-splitting Monte Carlo game. In addition to the insight into the dependence of the second moment on the splitting parameters the main importance of the expressions developed lies in their potential to become a basis for in-code optimization of splitting through a general algorithm. Refs
Extending canonical Monte Carlo methods
International Nuclear Information System (INIS)
Velazquez, L; Curilef, S
2010-01-01
In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C α with α≈0.2 for the particular case of the 2D ten-state Potts model
Hansen, T. M.; Cordua, K. S.
2017-12-01
Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.
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
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
Heuristic Biases in Mathematical Reasoning
Inglis, Matthew; Simpson, Adrian
2005-01-01
In this paper we briefly describe the dual process account of reasoning, and explain the role of heuristic biases in human thought. Concentrating on the so-called matching bias effect, we describe a piece of research that indicates a correlation between success at advanced level mathematics and an ability to override innate and misleading…
Gender bias affects forests worldwide
Marlène Elias; Susan S Hummel; Bimbika S Basnett; Carol J.P. Colfer
2017-01-01
Gender biases persist in forestry research and practice. These biases result in reduced scientific rigor and inequitable, ineffective, and less efficient policies, programs, and interventions. Drawing from a two-volume collection of current and classic analyses on gender in forests, we outline five persistent and inter-related themes: gendered governance, tree tenure,...
Anti-Bias Education: Reflections
Derman-Sparks, Louise
2011-01-01
It is 30 years since NAEYC published "Anti-Bias Curriculum Tools for Empowering Young Children" (Derman-Sparks & ABC Task Force, 1989). Since then, anti-bias education concepts have become part of the early childhood education (ECE) narrative in the United States and many other countries. It has brought a fresh way of thinking about…
Hong-Ghi Min
2011-01-01
Using Monte Carlo simulation of the Portfolio-balance model of the exchange rates, we report finite sample properties of the GMM estimator for testing over-identifying restrictions in the simultaneous equations model. F-form of Sargans statistic performs better than its chi-squared form while Hansens GMM statistic has the smallest bias.
Neel, John H.; Stallings, William M.
An influential statistics test recommends a Levene text for homogeneity of variance. A recent note suggests that Levene's test is upwardly biased for small samples. Another report shows inflated Alpha estimates and low power. Neither study utilized more than two sample sizes. This Monte Carlo study involved sampling from a normal population for…
Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian
2018-02-01
This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.
Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian
2018-01-01
Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.
Smart darting diffusion Monte Carlo: Applications to lithium ion-Stockmayer clusters
Christensen, H. M.; Jake, L. C.; Curotto, E.
2016-05-01
In a recent investigation [K. Roberts et al., J. Chem. Phys. 136, 074104 (2012)], we have shown that, for a sufficiently complex potential, the Diffusion Monte Carlo (DMC) random walk can become quasiergodic, and we have introduced smart darting-like moves to improve the sampling. In this article, we systematically characterize the bias that smart darting moves introduce in the estimate of the ground state energy of a bosonic system. We then test a simple approach to eliminate completely such bias from the results. The approach is applied for the determination of the ground state of lithium ion-n-dipoles clusters in the n = 8-20 range. For these, the smart darting diffusion Monte Carlo simulations find the same ground state energy and mixed-distribution as the traditional approach for n simulations may produce a more reliable ground state mixed-distribution.
Study of Monte Carlo approach to experimental uncertainty propagation with MSTW 2008 PDFs
Watt, G.
2012-01-01
We investigate the Monte Carlo approach to propagation of experimental uncertainties within the context of the established 'MSTW 2008' global analysis of parton distribution functions (PDFs) of the proton at next-to-leading order in the strong coupling. We show that the Monte Carlo approach using replicas of the original data gives PDF uncertainties in good agreement with the usual Hessian approach using the standard Delta(chi^2) = 1 criterion, then we explore potential parameterisation bias by increasing the number of free parameters, concluding that any parameterisation bias is likely to be small, with the exception of the valence-quark distributions at low momentum fractions x. We motivate the need for a larger tolerance, Delta(chi^2) > 1, by making fits to restricted data sets and idealised consistent or inconsistent pseudodata. Instead of using data replicas, we alternatively produce PDF sets randomly distributed according to the covariance matrix of fit parameters including appropriate tolerance values,...
Simultaneous Monte Carlo zero-variance estimates of several correlated means
International Nuclear Information System (INIS)
Booth, T.E.
1997-08-01
Zero variance procedures have been in existence since the dawn of Monte Carlo. Previous works all treat the problem of zero variance solutions for a single tally. One often wants to get low variance solutions to more than one tally. When the sets of random walks needed for two tallies are similar, it is more efficient to do zero variance biasing for both tallies in the same Monte Carlo run, instead of two separate runs. The theory presented here correlates the random walks of particles by the similarity of their tallies. Particles with dissimilar tallies rapidly become uncorrelated whereas particles with similar tallies will stay correlated through most of their random walk. The theory herein should allow practitioners to make efficient use of zero-variance biasing procedures in practical problems
Intergenerational Correlation in Monte Carlo k-Eigenvalue Calculation
International Nuclear Information System (INIS)
Ueki, Taro
2002-01-01
This paper investigates intergenerational correlation in the Monte Carlo k-eigenvalue calculation of a neutron effective multiplicative factor. To this end, the exponential transform for path stretching has been applied to large fissionable media with localized highly multiplying regions because in such media an exponentially decaying shape is a rough representation of the importance of source particles. The numerical results show that the difference between real and apparent variances virtually vanishes for an appropriate value of the exponential transform parameter. This indicates that the intergenerational correlation of k-eigenvalue samples could be eliminated by the adjoint biasing of particle transport. The relation between the biasing of particle transport and the intergenerational correlation is therefore investigated in the framework of collision estimators, and the following conclusion has been obtained: Within the leading order approximation with respect to the number of histories per generation, the intergenerational correlation vanishes when immediate importance is constant, and the immediate importance under simulation can be made constant by the biasing of particle transport with a function adjoint to the source neutron's distribution, i.e., the importance over all future generations
Application to risk analysis of Monte Carlo method
International Nuclear Information System (INIS)
Mihara, Takashi
2001-01-01
Phased mission analysis code, PHAMMON by means of monte carlo method is developed for reliability assessment of decay heat removal system in LMFBR. Success criteria and grace periods of the decay heat removal system which has long mission times (∼1 week or ∼1 month) change as a function of time. It is necessary to divide mission time into some phases. In probability safety assessment (PSA) of real systems, it usually happens that the mean time to component failure (MTTF) is considerably long (1000-10 6 hours) and the mean time to component repair (MTTR) is short (∼10 hours). The failure probability of the systems, therefore, is extremely small (10 -6 -10 -9 ). Suitable variance reduction techniques are needed. The PHAMMON code involved two kinds of variance reduction techniques: (1) forced time transitions, and (2) failure biasing. For further reducing the variance of the result from the PHAMMON code execution, a biasing method of the transitions towards the closest cut set incorporating a new distance concept is introduced to the PHAMMON code. Failure probability and it's fractional standard deviation for the decay heat removal system are calculated by the PHAMMON code under the conditions of various success criteria over 168hrs after reactor shutdown. The biasing of the transition towards the closet cut set is an effective means of reducing the variance. (M. Suetake)
QUANTIFYING THE BIASES OF SPECTROSCOPICALLY SELECTED GRAVITATIONAL LENSES
International Nuclear Information System (INIS)
Arneson, Ryan A.; Brownstein, Joel R.; Bolton, Adam S.
2012-01-01
Spectroscopic selection has been the most productive technique for the selection of galaxy-scale strong gravitational lens systems with known redshifts. Statistically significant samples of strong lenses provide a powerful method for measuring the mass-density parameters of the lensing population, but results can only be generalized to the parent population if the lensing selection biases are sufficiently understood. We perform controlled Monte Carlo simulations of spectroscopic lens surveys in order to quantify the bias of lenses relative to parent galaxies in velocity dispersion, mass axis ratio, and mass-density profile. For parameters typical of the SLACS and BELLS surveys, we find (1) no significant mass axis ratio detection bias of lenses relative to parent galaxies; (2) a very small detection bias toward shallow mass-density profiles, which is likely negligible compared to other sources of uncertainty in this parameter; (3) a detection bias toward smaller Einstein radius for systems drawn from parent populations with group- and cluster-scale lensing masses; and (4) a lens-modeling bias toward larger velocity dispersions for systems drawn from parent samples with sub-arcsecond mean Einstein radii. This last finding indicates that the incorporation of velocity-dispersion upper limits of non-lenses is an important ingredient for unbiased analyses of spectroscopically selected lens samples. In general, we find that the completeness of spectroscopic lens surveys in the plane of Einstein radius and mass-density profile power-law index is quite uniform, up to a sharp drop in the region of large Einstein radius and steep mass-density profile, and hence that such surveys are ideally suited to the study of massive field galaxies.
Cornelius, Iwan; Guatelli, Susanna; Fournier, Pauline; Crosbie, Jeffrey C; Sanchez Del Rio, Manuel; Bräuer-Krisch, Elke; Rosenfeld, Anatoly; Lerch, Michael
2014-05-01
Microbeam radiation therapy (MRT) is a synchrotron-based radiotherapy modality that uses high-intensity beams of spatially fractionated radiation to treat tumours. The rapid evolution of MRT towards clinical trials demands accurate treatment planning systems (TPS), as well as independent tools for the verification of TPS calculated dose distributions in order to ensure patient safety and treatment efficacy. Monte Carlo computer simulation represents the most accurate method of dose calculation in patient geometries and is best suited for the purpose of TPS verification. A Monte Carlo model of the ID17 biomedical beamline at the European Synchrotron Radiation Facility has been developed, including recent modifications, using the Geant4 Monte Carlo toolkit interfaced with the SHADOW X-ray optics and ray-tracing libraries. The code was benchmarked by simulating dose profiles in water-equivalent phantoms subject to irradiation by broad-beam (without spatial fractionation) and microbeam (with spatial fractionation) fields, and comparing against those calculated with a previous model of the beamline developed using the PENELOPE code. Validation against additional experimental dose profiles in water-equivalent phantoms subject to broad-beam irradiation was also performed. Good agreement between codes was observed, with the exception of out-of-field doses and toward the field edge for larger field sizes. Microbeam results showed good agreement between both codes and experimental results within uncertainties. Results of the experimental validation showed agreement for different beamline configurations. The asymmetry in the out-of-field dose profiles due to polarization effects was also investigated, yielding important information for the treatment planning process in MRT. This work represents an important step in the development of a Monte Carlo-based independent verification tool for treatment planning in MRT.
Mishra, Subhalaxmi; Dixit, P K; Selvam, T Palani; Yavalkar, Sanket S; Deshpande, D D
2018-01-01
A Monte Carlo model of a 6 MV medical linear accelerator (linac) unit built indigenously was developed using the BEAMnrc user code of the EGSnrc code system. The model was benchmarked against the measurements. Monte Carlo simulations were carried out for different incident electron beam parameters in the study. Simulation of indigenously developed linac unit has been carried out using the Monte Carlo based BEAMnrc user-code of the EGSnrc code system. Using the model, percentage depth dose (PDD), and lateral dose profiles were studied using the DOSXYZnrc user code. To identify appropriate electron parameters, three different distributions of electron beam intensity were investigated. For each case, the kinetic energy of the incident electron was varied from 6 to 6.5 MeV (0.1 MeV increment). The calculated dose data were compared against the measurements using the PTW, Germany make RFA dosimetric system (water tank MP3-M and 0.125 cm 3 ion chamber). The best fit of incident electron beam parameter was found for the combination of beam energy of 6.2 MeV and circular Gaussian distributed source in X and Y with FWHM of 1.0 mm. PDD and beam profiles (along both X and Y directions) were calculated for the field sizes from 5 cm × 5 cm to 25 cm × 25 cm. The dose difference between the calculated and measured PDD and profile values were under 1%, except for the penumbra region where the maximum deviation was found to be around 2%. A Monte Carlo model of indigenous linac (6 MV) has been developed and benchmarked against the measured data.
QCD Monte-Carlo model tuning studies with CMS data at 13 TeV
Sunar Cerci, Deniz
2018-01-01
New CMS PYTHIA 8 event tunes are presented. The new tunes are obtained using minimum bias and underlying event observables using Monte Carlo configurations with consistent parton distribution functions and strong coupling constant values in the matrix element and the parton shower. Validation and performance studies are presented by comparing the predictions of the new tune to various soft- and hard-QCD measurements at 7, 8 and 13 TeV with CMS.
Monte Carlo Particle Lists: MCPL
DEFF Research Database (Denmark)
Kittelmann, Thomas; Klinkby, Esben Bryndt; Bergbäck Knudsen, Erik
2017-01-01
A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular...... simulation packages. Program summary: Program Title: MCPL. Program Files doi: http://dx.doi.org/10.17632/cby92vsv5g.1 Licensing provisions: CC0 for core MCPL, see LICENSE file for details. Programming language: C and C++ External routines/libraries: Geant4, MCNP, McStas, McXtrace Nature of problem: Saving...
Cognitive Bias in Systems Verification
Larson, Steve
2012-01-01
Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.
Administrative bias in South Africa
Directory of Open Access Journals (Sweden)
E S Nwauche
2005-01-01
Full Text Available This article reviews the interpretation of section 6(2(aii of the Promotion of Administrative Justice Act which makes an administrator “biased or reasonably suspected of bias” a ground of judicial review. In this regard, the paper reviews the determination of administrative bias in South Africa especially highlighting the concept of institutional bias. The paper notes that inspite of the formulation of the bias ground of review the test for administrative bias is the reasonable apprehension test laid down in the case of President of South Africa v South African Rugby Football Union(2 which on close examination is not the same thing. Accordingly the paper urges an alternative interpretation that is based on the reasonable suspicion test enunciated in BTR Industries South Africa (Pty Ltd v Metal and Allied Workers Union and R v Roberts. Within this context, the paper constructs a model for interpreting the bias ground of review that combines the reasonable suspicion test as interpreted in BTR Industries and R v Roberts, the possibility of the waiver of administrative bias, the curative mechanism of administrative appeal as well as some level of judicial review exemplified by the jurisprudence of article 6(1 of the European Convention of Human Rights, especially in the light of the contemplation of the South African Magistrate Court as a jurisdictional route of judicial review.
Toward a Monte Carlo program for simulating vapor-liquid phase equilibria from first principles
Energy Technology Data Exchange (ETDEWEB)
McGrath, M; Siepmann, J I; Kuo, I W; Mundy, C J; Vandevondele, J; Sprik, M; Hutter, J; Mohamed, F; Krack, M; Parrinello, M
2004-10-20
Efficient Monte Carlo algorithms are combined with the Quickstep energy routines of CP2K to develop a program that allows for Monte Carlo simulations in the canonical, isobaric-isothermal, and Gibbs ensembles using a first principles description of the physical system. Configurational-bias Monte Carlo techniques and pre-biasing using an inexpensive approximate potential are employed to increase the sampling efficiency and to reduce the frequency of expensive ab initio energy evaluations. The new Monte Carlo program has been validated through extensive comparison with molecular dynamics simulations using the programs CPMD and CP2K. Preliminary results for the vapor-liquid coexistence properties (T = 473 K) of water using the Becke-Lee-Yang-Parr exchange and correlation energy functionals, a triple-zeta valence basis set augmented with two sets of d-type or p-type polarization functions, and Goedecker-Teter-Hutter pseudopotentials are presented. The preliminary results indicate that this description of water leads to an underestimation of the saturated liquid density and heat of vaporization and, correspondingly, an overestimation of the saturated vapor pressure.
Development of Monte Carlo decay gamma-ray transport calculation system
Energy Technology Data Exchange (ETDEWEB)
Sato, Satoshi [Japan Atomic Energy Research Inst., Naka, Ibaraki (Japan). Naka Fusion Research Establishment; Kawasaki, Nobuo [Fujitsu Ltd., Tokyo (Japan); Kume, Etsuo [Japan Atomic Energy Research Inst., Center for Promotion of Computational Science and Engineering, Tokai, Ibaraki (Japan)
2001-06-01
In the DT fusion reactor, it is critical concern to evaluate the decay gamma-ray biological dose rates after the reactor shutdown exactly. In order to evaluate the decay gamma-ray biological dose rates exactly, three dimensional Monte Carlo decay gamma-ray transport calculation system have been developed by connecting the three dimensional Monte Carlo particle transport calculation code and the induced activity calculation code. The developed calculation system consists of the following four functions. (1) The operational neutron flux distribution is calculated by the three dimensional Monte Carlo particle transport calculation code. (2) The induced activities are calculated by the induced activity calculation code. (3) The decay gamma-ray source distribution is obtained from the induced activities. (4) The decay gamma-rays are generated by using the decay gamma-ray source distribution, and the decay gamma-ray transport calculation is conducted by the three dimensional Monte Carlo particle transport calculation code. In order to reduce the calculation time drastically, a biasing system for the decay gamma-ray source distribution has been developed, and the function is also included in the present system. In this paper, the outline and the detail of the system, and the execution example are reported. The evaluation for the effect of the biasing system is also reported. (author)
Critical Thinking and Cognitive Bias
Directory of Open Access Journals (Sweden)
Jeffrey Maynes
2015-05-01
Full Text Available Teaching critical thinking skill is a central pedagogical aim in many courses. These skills, it is hoped, will be both portable (applicable in a wide range of contexts and durable (not forgotten quickly. Yet, both of these virtues are challenged by pervasive and potent cognitive biases, such as motivated reasoning, false consensus bias and hindsight bias. In this paper, I argue that a focus on the development of metacognitive skill shows promise as a means to inculcate debiasing habits in students. Such habits will help students become more critical reasoners. I close with suggestions for implementing this strategy.
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Larsen, Edward W.
2001-01-01
. We present results from a class of criticality calculations. These problems consist of alternating arrays of fuel and moderator regions, each region being 3.0 cm thick. Forward Monte Carlo calculations were run with (a) traditional Monte Carlo using a track-length estimate of k and survival biasing (SB); (b) the new VVR method without the linear spatial term (VVR1); (c) the new VVR method without the linear spatial term, but with SB (VVR1/SB); (d) the new VVR method with the linear spatial term (VVR2); and (e) the new VVR method with the linear spatial term and with SB (VVR2/SB). The traditional Monte Carlo calculation was performed with SB since this resulted in a higher FOM than using analog Monte Carlo. We performed the adjoint calculation using a finite difference diffusion code with a fine-mesh size of Δx = 0.1 cm. The time required to perform the deterministic adjoint calculation was much less than the time required for the Monte Carlo calculation and evaluation of the variational functional and is not included in the FOM. For each problem, the new VVR method outperforms the traditional Monte Carlo method, and the VVR method with the linear spatial term performs slightly better. For the largest problem, the two VVR methods without survival biasing (SB) outperformed the traditional Monte Carlo method by a factor of 36. We note that the use of SB decreases the efficiency of the VVR method. This decrease in FOM is due to the extra cost per history of the VVR method and the longer history length incurred by using SB. However, the new VVR method still outperforms the traditional Monte Carlo calculation even when (non-optimally) used with SB. In conclusion, we have developed a new VVR method for Monte Carlo criticality calculations. 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
Mean field simulation for Monte Carlo integration
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
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.)
Monte Carlo surface flux tallies
International Nuclear Information System (INIS)
Favorite, Jeffrey A.
2010-01-01
Particle fluxes on surfaces are difficult to calculate with Monte Carlo codes because the score requires a division by the surface-crossing angle cosine, and grazing angles lead to inaccuracies. We revisit the standard practice of dividing by half of a cosine 'cutoff' for particles whose surface-crossing cosines are below the cutoff. The theory behind this approximation is sound, but the application of the theory to all possible situations does not account for two implicit assumptions: (1) the grazing band must be symmetric about 0, and (2) a single linear expansion for the angular flux must be applied in the entire grazing band. These assumptions are violated in common circumstances; for example, for separate in-going and out-going flux tallies on internal surfaces, and for out-going flux tallies on external surfaces. In some situations, dividing by two-thirds of the cosine cutoff is more appropriate. If users were able to control both the cosine cutoff and the substitute value, they could use these parameters to make accurate surface flux tallies. The procedure is demonstrated in a test problem in which Monte Carlo surface fluxes in cosine bins are converted to angular fluxes and compared with the results of a discrete ordinates calculation.
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
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
International Nuclear Information System (INIS)
Sinha, Amar; Kashyap, Yogesh; Roy, Tushar; Agrawal, Ashish; Sarkar, P.S.; Shukla, Mayank
2009-01-01
The problem of illicit trafficking of explosives, narcotics or fissile materials represents a real challenge to civil security. Neutron based detection systems are being actively explored worldwide as a confirmatory tool for applications in the detection of explosives either hidden inside a vehicle or a cargo container or buried inside soil. The development of a system and its experimental testing is a tedious process and to develop such a system each experimental condition needs to be theoretically simulated. Monte Carlo based methods are used to find an optimized design for such detection system. In order to design such systems, it is necessary to optimize source and detector system for each specific application. The present paper deals with such optimization studies using Monte Carlo technique for tagged neutron based system for explosives and narcotics detection hidden in a cargo and landmine detection using backscatter neutrons. We will also discuss some simulation studies on detection of fissile material and photo-neutron source design for applications on cargo scanning. (author)
Preferences, country bias, and international trade
S. Roy (Santanu); J.M.A. Viaene (Jean-Marie)
1998-01-01
textabstractAnalyzes international trade where consumer preferences exhibit country bias. Why country biases arise; How trade can occur in the presence of country bias; Implication for the pattern of trade and specialization.
Uncertainties in s-process nucleosynthesis in massive stars determined by Monte Carlo variations
Nishimura, N.; Hirschi, R.; Rauscher, T.; St. J. Murphy, A.; Cescutti, G.
2017-08-01
The s-process in massive stars produces the weak component of the s-process (nuclei up to A ˜ 90), in amounts that match solar abundances. For heavier isotopes, such as barium, production through neutron capture is significantly enhanced in very metal-poor stars with fast rotation. However, detailed theoretical predictions for the resulting final s-process abundances have important uncertainties caused both by the underlying uncertainties in the nuclear physics (principally neutron-capture reaction and β-decay rates) as well as by the stellar evolution modelling. In this work, we investigated the impact of nuclear-physics uncertainties relevant to the s-process in massive stars. Using a Monte Carlo based approach, we performed extensive nuclear reaction network calculations that include newly evaluated upper and lower limits for the individual temperature-dependent reaction rates. We found that most of the uncertainty in the final abundances is caused by uncertainties in the neutron-capture rates, while β-decay rate uncertainties affect only a few nuclei near s-process branchings. The s-process in rotating metal-poor stars shows quantitatively different uncertainties and key reactions, although the qualitative characteristics are similar. We confirmed that our results do not significantly change at different metallicities for fast rotating massive stars in the very low metallicity regime. We highlight which of the identified key reactions are realistic candidates for improved measurement by future experiments.
Optimal mesh hierarchies in Multilevel Monte Carlo methods
Von Schwerin, Erik
2016-01-08
I will discuss how to choose optimal mesh hierarchies in Multilevel Monte Carlo (MLMC) simulations when computing the expected value of a quantity of interest depending on the solution of, for example, an Ito stochastic differential equation or a partial differential equation with stochastic data. I will consider numerical schemes based on uniform discretization methods with general approximation orders and computational costs. I will compare optimized geometric and non-geometric hierarchies and discuss how enforcing some domain constraints on parameters of MLMC hierarchies affects the optimality of these hierarchies. I will also discuss the optimal tolerance splitting between the bias and the statistical error contributions and its asymptotic behavior. This talk presents joint work with N.Collier, A.-L.Haji-Ali, F. Nobile, and R. Tempone.
Optimal mesh hierarchies in Multilevel Monte Carlo methods
Von Schwerin, Erik
2016-01-01
I will discuss how to choose optimal mesh hierarchies in Multilevel Monte Carlo (MLMC) simulations when computing the expected value of a quantity of interest depending on the solution of, for example, an Ito stochastic differential equation or a partial differential equation with stochastic data. I will consider numerical schemes based on uniform discretization methods with general approximation orders and computational costs. I will compare optimized geometric and non-geometric hierarchies and discuss how enforcing some domain constraints on parameters of MLMC hierarchies affects the optimality of these hierarchies. I will also discuss the optimal tolerance splitting between the bias and the statistical error contributions and its asymptotic behavior. This talk presents joint work with N.Collier, A.-L.Haji-Ali, F. Nobile, and R. Tempone.
The three-dimensional Monte-Carlo code TRIPOLI-02
International Nuclear Information System (INIS)
Baur, A.; Bourdet, L.; Dejonghe, G.; Gonnord, J.; Monnier, A.; Nimal, J.C.; Vergnaud, T.
1980-04-01
TRIPOLI-2 solves the transport equation for neutrons or gamma rays in tridimensional geometrical configurations. TRIPOLI uses the Monte Carlo method. This method allows to treat exactly the geometrical configurations, the energy losses and the scattering laws. TRIPOLI 2 allows to treat the following problems: gamma transport problems, neutrons transport problems with fixed source (the problems can be time dependent or not), critical problems without fixed source and research of multiplication factor due to fissions, subcritical problems with fixed source and with multiplication by fission. These problems can be separate in two types. First type: shielding problems essentially with deep penetration and streaming through voids. Biasing technics are used to reduce the computing time. Second type: core problems for cell calculations or for small core calculations. In this case, it is necessary to have a fine representation of the cross sections. The thermalization is also treated exactly [fr
Monte Carlo applications at Hanford Engineering Development Laboratory
International Nuclear Information System (INIS)
Carter, L.L.; Morford, R.J.; Wilcox, A.D.
1980-03-01
Twenty applications of neutron and photon transport with Monte Carlo have been described to give an overview of the current effort at HEDL. A satisfaction factor was defined which quantitatively assigns an overall return for each calculation relative to the investment in machine time and expenditure of manpower. Low satisfaction factors are frequently encountered in the calculations. Usually this is due to limitations in execution rates of present day computers, but sometimes a low satisfaction factor is due to computer code limitations, calendar time constraints, or inadequacy of the nuclear data base. Present day computer codes have taken some of the burden off of the user. Nevertheless, it is highly desirable for the engineer using the computer code to have an understanding of particle transport including some intuition for the problems being solved, to understand the construction of sources for the random walk, to understand the interpretation of tallies made by the code, and to have a basic understanding of elementary biasing techniques
Modelling of scintillator based flat-panel detectors with Monte-Carlo simulations
International Nuclear Information System (INIS)
Reims, N; Sukowski, F; Uhlmann, N
2011-01-01
Scintillator based flat panel detectors are state of the art in the field of industrial X-ray imaging applications. Choosing the proper system and setup parameters for the vast range of different applications can be a time consuming task, especially when developing new detector systems. Since the system behaviour cannot always be foreseen easily, Monte-Carlo (MC) simulations are keys to gain further knowledge of system components and their behaviour for different imaging conditions. In this work we used two Monte-Carlo based models to examine an indirect converting flat panel detector, specifically the Hamamatsu C9312SK. We focused on the signal generation in the scintillation layer and its influence on the spatial resolution of the whole system. The models differ significantly in their level of complexity. The first model gives a global description of the detector based on different parameters characterizing the spatial resolution. With relatively small effort a simulation model can be developed which equates the real detector regarding signal transfer. The second model allows a more detailed insight of the system. It is based on the well established cascade theory, i.e. describing the detector as a cascade of elemental gain and scattering stages, which represent the built in components and their signal transfer behaviour. In comparison to the first model the influence of single components especially the important light spread behaviour in the scintillator can be analysed in a more differentiated way. Although the implementation of the second model is more time consuming both models have in common that a relatively small amount of system manufacturer parameters are needed. The results of both models were in good agreement with the measured parameters of the real system.
Directory of Open Access Journals (Sweden)
K. Müller
2018-03-01
Full Text Available Fatigue load assessment of floating offshore wind turbines poses new challenges on the feasibility of numerical procedures. Due to the increased sensitivity of the considered system with respect to the environmental conditions from wind and ocean, the application of common procedures used for fixed-bottom structures results in either inaccurate simulation results or hard-to-quantify conservatism in the system design. Monte Carlo-based sampling procedures provide a more realistic approach to deal with the large variation in the environmental conditions, although basic randomization has shown slow convergence. Specialized sampling methods allow efficient coverage of the complete design space, resulting in faster convergence and hence a reduced number of required simulations. In this study, a quasi-random sampling approach based on Sobol sequences is applied to select representative events for the determination of the lifetime damage. This is calculated applying Monte Carlo integration, using subsets of a resulting total of 16 200 coupled time–domain simulations performed with the simulation code FAST. The considered system is the Danmarks Tekniske Universitet (DTU 10 MW reference turbine installed on the LIFES50+ OO-Star Wind Floater Semi 10 MW floating platform. Statistical properties of the considered environmental parameters (i.e., wind speed, wave height and wave period are determined based on the measurement data from the Gulf of Maine, USA. Convergence analyses show that it is sufficient to perform around 200 simulations in order to reach less than 10 % uncertainty of lifetime fatigue damage-equivalent loading. Complementary in-depth investigation is performed, focusing on the load sensitivity and the impact of outliers (i.e., values far away from the mean. Recommendations for the implementation of the proposed methodology in the design process are also provided.
Fringe biasing: A variance reduction technique for optically thick meshes
Energy Technology Data Exchange (ETDEWEB)
Smedley-Stevenson, R. P. [AWE PLC, Aldermaston Reading, Berkshire, RG7 4PR (United Kingdom)
2013-07-01
Fringe biasing is a stratified sampling scheme applicable to Monte Carlo thermal radiation transport codes. The thermal emission source in optically thick cells is partitioned into separate contributions from the cell interiors (where the likelihood of the particles escaping the cells is virtually zero) and the 'fringe' regions close to the cell boundaries. Thermal emission in the cell interiors can now be modelled with fewer particles, the remaining particles being concentrated in the fringes so that they are more likely to contribute to the energy exchange between cells. Unlike other techniques for improving the efficiency in optically thick regions (such as random walk and discrete diffusion treatments), fringe biasing has the benefit of simplicity, as the associated changes are restricted to the sourcing routines with the particle tracking routines being unaffected. This paper presents an analysis of the potential for variance reduction achieved from employing the fringe biasing technique. The aim of this analysis is to guide the implementation of this technique in Monte Carlo thermal radiation codes, specifically in order to aid the choice of the fringe width and the proportion of particles allocated to the fringe (which are interrelated) in multi-dimensional simulations, and to confirm that the significant levels of variance reduction achieved in simulations can be understood by studying the behaviour for simple test cases. The variance reduction properties are studied for a single cell in a slab geometry purely absorbing medium, investigating the accuracy of the scalar flux and current tallies on one of the interfaces with the surrounding medium. (authors)
Fringe biasing: A variance reduction technique for optically thick meshes
International Nuclear Information System (INIS)
Smedley-Stevenson, R. P.
2013-01-01
Fringe biasing is a stratified sampling scheme applicable to Monte Carlo thermal radiation transport codes. The thermal emission source in optically thick cells is partitioned into separate contributions from the cell interiors (where the likelihood of the particles escaping the cells is virtually zero) and the 'fringe' regions close to the cell boundaries. Thermal emission in the cell interiors can now be modelled with fewer particles, the remaining particles being concentrated in the fringes so that they are more likely to contribute to the energy exchange between cells. Unlike other techniques for improving the efficiency in optically thick regions (such as random walk and discrete diffusion treatments), fringe biasing has the benefit of simplicity, as the associated changes are restricted to the sourcing routines with the particle tracking routines being unaffected. This paper presents an analysis of the potential for variance reduction achieved from employing the fringe biasing technique. The aim of this analysis is to guide the implementation of this technique in Monte Carlo thermal radiation codes, specifically in order to aid the choice of the fringe width and the proportion of particles allocated to the fringe (which are interrelated) in multi-dimensional simulations, and to confirm that the significant levels of variance reduction achieved in simulations can be understood by studying the behaviour for simple test cases. The variance reduction properties are studied for a single cell in a slab geometry purely absorbing medium, investigating the accuracy of the scalar flux and current tallies on one of the interfaces with the surrounding medium. (authors)
International Nuclear Information System (INIS)
Moore, J.G.
1974-01-01
The Monte Carlo code MONK is a general program written to provide a high degree of flexibility to the user. MONK is distinguished by its detailed representation of nuclear data in point form i.e., the cross-section is tabulated at specific energies instead of the more usual group representation. The nuclear data are unadjusted in the point form but recently the code has been modified to accept adjusted group data as used in fast and thermal reactor applications. The various geometrical handling capabilities and importance sampling techniques are described. In addition to the nuclear data aspects, the following features are also described; geometrical handling routines, tracking cycles, neutron source and output facilities. 12 references. (U.S.)
Monte Carlo lattice program KIM
International Nuclear Information System (INIS)
Cupini, E.; De Matteis, A.; Simonini, R.
1980-01-01
The Monte Carlo program KIM solves the steady-state linear neutron transport equation for a fixed-source problem or, by successive fixed-source runs, for the eigenvalue problem, in a two-dimensional thermal reactor lattice. Fluxes and reaction rates are the main quantities computed by the program, from which power distribution and few-group averaged cross sections are derived. The simulation ranges from 10 MeV to zero and includes anisotropic and inelastic scattering in the fast energy region, the epithermal Doppler broadening of the resonances of some nuclides, and the thermalization phenomenon by taking into account the thermal velocity distribution of some molecules. Besides the well known combinatorial geometry, the program allows complex configurations to be represented by a discrete set of points, an approach greatly improving calculation speed
Implementation of an approximate zero-variance scheme in the TRIPOLI Monte Carlo code
Energy Technology Data Exchange (ETDEWEB)
Christoforou, S.; Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Dumonteil, E.; Petit, O.; Diop, C. [Commissariat a l' Energie Atomique CEA, Gif-sur-Yvette (France)
2006-07-01
In an accompanying paper it is shown that theoretically a zero-variance Monte Carlo scheme can be devised for criticality calculations if the space, energy and direction dependent adjoint function is exactly known. This requires biasing of the transition and collision kernels with the appropriate adjoint function. In this paper it is discussed how an existing general purpose Monte Carlo code like TRIPOLI can be modified to approach the zero-variance scheme. This requires modifications for reading in the adjoint function obtained from a separate deterministic calculation for a number of space intervals, energy groups and discrete directions. Furthermore, a function has to be added to supply the direction dependent and the averaged adjoint function at a specific position in the system by interpolation. The initial particle weights of a certain batch must be set inversely proportional to the averaged adjoint function and proper normalization of the initial weights must be secured. The sampling of the biased transition kernel requires cumulative integrals of the biased kernel along the flight path until a certain value, depending on a selected random number is reached to determine a new collision site. The weight of the particle must be adapted accordingly. The sampling of the biased collision kernel (in a multigroup treatment) is much more like the normal sampling procedure. A numerical example is given for a 3-group calculation with a simplified transport model (two-direction model), demonstrating that the zero-variance scheme can be approximated quite well for this simplified case. (authors)
Conditional Monte Carlo randomization tests for regression models.
Parhat, Parwen; Rosenberger, William F; Diao, Guoqing
2014-08-15
We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.
Monte Carlo parametric importance sampling with particle tracks scaling
International Nuclear Information System (INIS)
Ragheb, M.M.H.
1981-01-01
A method for Monte Carlo importance sampling with parametric dependence is proposed. It depends upon obtaining over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adopted and others rejected. The proposed method is applied to the finite slab penetration problem. When the exponential transformation is used, our method involves scaling of the generated particle tracks, and is a new application of Morton's method of similar trajectories. The method constitutes a generalization of Spanier's multistage importance sampling method, obtained by proper weighting over a single stage the curves he obtains over several stages, and preserves the statistical correlations between histories. It represents an extension of a theory by Frolov and Chentsov on Monte Carlo calculations of smooth curves to surfaces and to importance sampling calculations. By the proposed method, it seems possible to systematically arrive at minimum variance results and to avoid the infinite variances and effective biases sometimes observed in this type of calculation. (orig.) [de
Efficient Monte Carlo Simulations of Gas Molecules Inside Porous Materials.
Kim, Jihan; Smit, Berend
2012-07-10
Monte Carlo (MC) simulations are commonly used to obtain adsorption properties of gas molecules inside porous materials. In this work, we discuss various optimization strategies that lead to faster MC simulations with CO2 gas molecules inside host zeolite structures used as a test system. The reciprocal space contribution of the gas-gas Ewald summation and both the direct and the reciprocal gas-host potential energy interactions are stored inside energy grids to reduce the wall time in the MC simulations. Additional speedup can be obtained by selectively calling the routine that computes the gas-gas Ewald summation, which does not impact the accuracy of the zeolite's adsorption characteristics. We utilize two-level density-biased sampling technique in the grand canonical Monte Carlo (GCMC) algorithm to restrict CO2 insertion moves into low-energy regions within the zeolite materials to accelerate convergence. Finally, we make use of the graphics processing units (GPUs) hardware to conduct multiple MC simulations in parallel via judiciously mapping the GPU threads to available workload. As a result, we can obtain a CO2 adsorption isotherm curve with 14 pressure values (up to 10 atm) for a zeolite structure within a minute of total compute wall time.
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.
Nested Sampling with Constrained Hamiltonian Monte Carlo
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.
Negativity Bias in Dangerous Drivers.
Directory of Open Access Journals (Sweden)
Jing Chai
Full Text Available The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes.
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...
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 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)
Investigating the minimum achievable variance in a Monte Carlo criticality calculation
Energy Technology Data Exchange (ETDEWEB)
Christoforou, Stavros; Eduard Hoogenboom, J. [Delft University of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)
2008-07-01
The sources of variance in a Monte Carlo criticality calculation are identified and their contributions analyzed. A zero-variance configuration is initially simulated using analytically calculated adjoint functions for biasing. From there, the various sources are analyzed. It is shown that the minimum threshold comes from the fact that the fission source is approximated. In addition, the merits of a simple variance reduction method, such as implicit capture, are shown when compared to an analog simulation. Finally, it is shown that when non-exact adjoint functions are used for biasing, the variance reduction is rather insensitive to the quality of the adjoints, suggesting that the generation of the adjoints should have as low CPU cost as possible, in order to o et the CPU cost in the implementation of the biasing of a simulation. (authors)
Heavy Ion Induced Degradation in SiC Schottky Diodes: Bias and Energy Deposition Dependence
Javanainen, Arto; Galloway, Kenneth F.; Nicklaw, Christopher; Bosser, Alexandre L.; Ferlet-Cavrois, Veronique; Lauenstein, Jean-Marie; Pintacuda, Francesco; Reed, Robert A.; Schrimpf, Ronald D.; Weller, Robert A.;
2016-01-01
Experimental results on ion-induced leakage current increase in 4H-SiC Schottky power diodes are presented. Monte Carlo and TCAD simulations show that degradation is due to the synergy between applied bias and ion energy deposition. This degradation is possibly related to thermal spot annealing at the metal semiconductor interface. This thermal annealing leads to an inhomogeneity of the Schottky barrier that could be responsible for the increase leakage current as a function of fluence.
Numerical value biases sound localization.
Golob, Edward J; Lewald, Jörg; Getzmann, Stephan; Mock, Jeffrey R
2017-12-08
Speech recognition starts with representations of basic acoustic perceptual features and ends by categorizing the sound based on long-term memory for word meaning. However, little is known about whether the reverse pattern of lexical influences on basic perception can occur. We tested for a lexical influence on auditory spatial perception by having subjects make spatial judgments of number stimuli. Four experiments used pointing or left/right 2-alternative forced choice tasks to examine perceptual judgments of sound location as a function of digit magnitude (1-9). The main finding was that for stimuli presented near the median plane there was a linear left-to-right bias for localizing smaller-to-larger numbers. At lateral locations there was a central-eccentric location bias in the pointing task, and either a bias restricted to the smaller numbers (left side) or no significant number bias (right side). Prior number location also biased subsequent number judgments towards the opposite side. Findings support a lexical influence on auditory spatial perception, with a linear mapping near midline and more complex relations at lateral locations. Results may reflect coding of dedicated spatial channels, with two representing lateral positions in each hemispace, and the midline area represented by either their overlap or a separate third channel.
Automatic variance reduction for Monte Carlo simulations via the local importance function transform
International Nuclear Information System (INIS)
Turner, S.A.
1996-02-01
The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of ''real'' particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ''black box''. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases
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
Variance bias analysis for the Gelbard's batch method
Energy Technology Data Exchange (ETDEWEB)
Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)
2014-05-15
In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.
News Consumption and Media Bias
Yi Xiang; Miklos Sarvary
2007-01-01
Bias in the market for news is well-documented. Recent research in economics explains the phenomenon by assuming that consumers want to read (watch) news that is consistent with their tastes or prior beliefs rather than the truth. The present paper builds on this idea but recognizes that (i) besides “biased” consumers, there are also “conscientious” consumers whose sole interest is in discovering the truth, and (ii) consistent with reality, media bias is constrained by the truth. These two fa...
Biased limiter experiments on text
International Nuclear Information System (INIS)
Phillips, P.E.; Wootton, A.J.; Rowan, W.L.; Ritz, C.P.; Rhodes, T.L.; Bengtson, R.D.; Hodge, W.L.; Durst, R.D.; McCool, S.C.; Richards, B.; Gentle, K.W.; Schoch, P.; Forster, J.C.; Hickok, R.L.; Evans, T.E.
1987-01-01
Experiments using an electrically biased limiter have been performed on the Texas Experimental Tokamak (TEXT). A small movable limiter is inserted past the main poloidal ring limiter (which is electrically connected to the vacuum vessel) and biased at V Lim with respect to it. The floating potential, plasma potential and shear layer position can be controlled. With vertical strokeV Lim vertical stroke ≥ 50 V the plasma density increases. For V Lim Lim > 0 the results obtained are inconclusive. Variation of V Lim changes the electrostatic turbulence which may explain the observed total flux changes. (orig.)
The coalitional value theory of antigay bias
Winegard, Bo; Reynolds, Tania; Baumeister, Roy F.; Plant, E. Ashby
2016-01-01
Research indicates that antigay bias follows a specific pattern (and probably has throughout written history, at least in the West): (a) men evince more antigay bias than women; (b) men who belong to traditionally male coalitions evince more antigay bias than those who do not; (c) antigay bias is
TU-F-CAMPUS-T-05: A Cloud-Based Monte Carlo Dose Calculation for Electron Cutout Factors
Energy Technology Data Exchange (ETDEWEB)
Mitchell, T; Bush, K [Stanford School of Medicine, Stanford, CA (United States)
2015-06-15
Purpose: For electron cutouts of smaller sizes, it is necessary to verify electron cutout factors due to perturbations in electron scattering. Often, this requires a physical measurement using a small ion chamber, diode, or film. The purpose of this study is to develop a fast Monte Carlo based dose calculation framework that requires only a smart phone photograph of the cutout and specification of the SSD and energy to determine the electron cutout factor, with the ultimate goal of making this cloud-based calculation widely available to the medical physics community. Methods: The algorithm uses a pattern recognition technique to identify the corners of the cutout in the photograph as shown in Figure 1. It then corrects for variations in perspective, scaling, and translation of the photograph introduced by the user’s positioning of the camera. Blob detection is used to identify the portions of the cutout which comprise the aperture and the portions which are cutout material. This information is then used define physical densities of the voxels used in the Monte Carlo dose calculation algorithm as shown in Figure 2, and select a particle source from a pre-computed library of phase-spaces scored above the cutout. The electron cutout factor is obtained by taking a ratio of the maximum dose delivered with the cutout in place to the dose delivered under calibration/reference conditions. Results: The algorithm has been shown to successfully identify all necessary features of the electron cutout to perform the calculation. Subsequent testing will be performed to compare the Monte Carlo results with a physical measurement. Conclusion: A simple, cloud-based method of calculating electron cutout factors could eliminate the need for physical measurements and substantially reduce the time required to properly assure accurate dose delivery.
Biasing secondary particle interaction physics and production in MCNP6
International Nuclear Information System (INIS)
Fensin, M.L.; James, M.R.
2016-01-01
Highlights: • Biasing secondary production and interactions of charged particles in the tabular energy regime. • Examining lower weight window bounds for rare events when using Russian roulette. • The new biasing strategy can speedup calculations by a factor of 1 million or more. - Abstract: Though MCNP6 will transport elementary charged particles and light ions to low energies (i.e. less than 20 MeV), MCNP6 has historically relied on model physics with suggested minimum energies of ∼20 to 200 MeV. Use of library data for the low energy regime was developed for MCNP6 1.1.Beta to read and use light ion libraries. Thick target yields of neutron production for alphas on fluoride result in 1 production event per roughly million sampled alphas depending on the energy of the alpha (for other isotopes the yield can be even rarer). Calculation times to achieve statistically significant and converged thick target yields are quite laborious, needing over one hundred processor hours. The MUCEND code possess a biasing technique for improving the sampling of secondary particle production by forcing a nuclear interaction to occur per each alpha transported. We present here a different biasing strategy for secondary particle production from charged particles. During each substep, as the charged particle slows down, we bias both a nuclear collision event to occur at each substep and the production of secondary particles at the collision event, while still continuing to progress the charged particle until reaching a region of zero importance or an energy/time cutoff. This biasing strategy is capable of speeding up calculations by a factor of a million or more as compared to the unbiased calculation. Further presented here are both proof that the biasing strategy is capable of producing the same results as the unbiased calculation and the limitations to consider in order to achieve accurate results of secondary particle production. Though this strategy was developed for MCNP
A method for the quantification of biased signalling at constitutively active receptors.
Hall, David A; Giraldo, Jesús
2018-06-01
Biased agonism, the ability of an agonist to differentially activate one of several signal transduction pathways when acting at a given receptor, is an increasingly recognized phenomenon at many receptors. The Black and Leff operational model lacks a way to describe constitutive receptor activity and hence inverse agonism. Thus, it is impossible to analyse the biased signalling of inverse agonists using this model. In this theoretical work, we develop and illustrate methods for the analysis of biased inverse agonism. Methods were derived for quantifying biased signalling in systems that demonstrate constitutive activity using the modified operational model proposed by Slack and Hall. The methods were illustrated using Monte Carlo simulations. The Monte Carlo simulations demonstrated that, with an appropriate experimental design, the model parameters are 'identifiable'. The method is consistent with methods based on the measurement of intrinsic relative activity (RA i ) (ΔΔlogR or ΔΔlog(τ/K a )) proposed by Ehlert and Kenakin and their co-workers but has some advantages. In particular, it allows the quantification of ligand bias independently of 'system bias' removing the requirement to normalize to a standard ligand. In systems with constitutive activity, the Slack and Hall model provides methods for quantifying the absolute bias of agonists and inverse agonists. This provides an alternative to methods based on RA i and is complementary to the ΔΔlog(τ/K a ) method of Kenakin et al. in systems where use of that method is inappropriate due to the presence of constitutive activity. © 2018 The British Pharmacological Society.
Plane-parallel biases computed from inhomogeneous Arctic clouds and sea ice
Rozwadowska, Anna; Cahalan, Robert F.
2002-10-01
Monte Carlo simulations of the expected influence of nonuniformity in cloud structure and surface albedo on shortwave radiative fluxes in the Arctic atmosphere are presented. In particular, plane-parallel biases in cloud albedo and transmittance are studied for nonabsorbing, low-level, all-liquid stratus clouds over sea ice. The "absolute bias" is defined as the difference between the cloud albedo or transmittance for the uniform or plane-parallel case, and the albedo or transmittance for nonuniform conditions with the same mean cloud optical thickness and the same mean surface albedo, averaged over a given area (i.e., bias > 0 means plane-parallel overestimates). Ranges of means and standard deviations of input parameters typical of Arctic conditions are determined from the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment Artic Cloud Experiment (FIRE/ACE)/Surface Heat Budget of the Arctic Ocean (SHEBA)/Atmospheric Radiation Measurement Program (ARM) experiment, a cooperative effort of the Department of Energy, NASA, NSF, the National Oceanic and Atmospheric Administration, the Office of Naval Research, and the Atmospheric Environment Service. We determine the sensitivity of the bias with respect to the following: domain averaged means and spatial variances of cloud optical thickness and surface albedo, shape of the surface reflectance function, presence of a scattering layer under the clouds, and solar zenith angle. The simulations show that the biases in Arctic conditions are generally lower than in subtropical stratocumulus. The magnitudes of the absolute biases are unlikely to exceed 0.02 for albedo and 0.05 for transmittance. The "relative bias" expresses the absolute bias as a percentage of the actual cloud albedo or transmittance. The magnitude of the relative bias in albedo is typically below 2% over the reflective Arctic surface, while the magnitude of the relative bias in transmittance can exceed 10%.
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.
Monte carlo simulation for soot dynamics
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.
Energy Technology Data Exchange (ETDEWEB)
Makovicka, L.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J. [Universite de Franche-Comte, Equipe IRMA/ENISYS/FEMTO-ST, UMR6174 CNRS, 25 - Montbeliard (France); Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Salomon, M. [Universite de Franche-Comte, Equipe AND/LIFC, 90 - Belfort (France)
2009-01-15
Monte Carlo codes, precise but slow, are very important tools in the vast majority of specialities connected to Radiation Physics, Radiation Protection and Dosimetry. A discussion about some other computing solutions is carried out; solutions not only based on the enhancement of computer power, or on the 'biasing'used for relative acceleration of these codes (in the case of photons), but on more efficient methods (A.N.N. - artificial neural network, C.B.R. - case-based reasoning - or other computer science techniques) already and successfully used for a long time in other scientific or industrial applications and not only Radiation Protection or Medical Dosimetry. (authors)
Biased Brownian dynamics for rate constant calculation.
Zou, G; Skeel, R D; Subramaniam, S
2000-01-01
An enhanced sampling method-biased Brownian dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampl...
Monte Carlo Codes Invited Session
International Nuclear Information System (INIS)
Trama, J.C.; Malvagi, F.; Brown, F.
2013-01-01
This document lists 22 Monte Carlo codes used in radiation transport applications throughout the world. For each code the names of the organization and country and/or place are given. We have the following computer codes. 1) ARCHER, USA, RPI; 2) COG11, USA, LLNL; 3) DIANE, France, CEA/DAM Bruyeres; 4) FLUKA, Italy and CERN, INFN and CERN; 5) GEANT4, International GEANT4 collaboration; 6) KENO and MONACO (SCALE), USA, ORNL; 7) MC21, USA, KAPL and Bettis; 8) MCATK, USA, LANL; 9) MCCARD, South Korea, Seoul National University; 10) MCNP6, USA, LANL; 11) MCU, Russia, Kurchatov Institute; 12) MONK and MCBEND, United Kingdom, AMEC; 13) MORET5, France, IRSN Fontenay-aux-Roses; 14) MVP2, Japan, JAEA; 15) OPENMC, USA, MIT; 16) PENELOPE, Spain, Barcelona University; 17) PHITS, Japan, JAEA; 18) PRIZMA, Russia, VNIITF; 19) RMC, China, Tsinghua University; 20) SERPENT, Finland, VTT; 21) SUPERMONTECARLO, China, CAS INEST FDS Team Hefei; and 22) TRIPOLI-4, France, CEA Saclay
Advanced computers and Monte Carlo
International Nuclear Information System (INIS)
Jordan, T.L.
1979-01-01
High-performance parallelism that is currently available is synchronous in nature. It is manifested in such architectures as Burroughs ILLIAC-IV, CDC STAR-100, TI ASC, CRI CRAY-1, ICL DAP, and many special-purpose array processors designed for signal processing. This form of parallelism has apparently not been of significant value to many important Monte Carlo calculations. Nevertheless, there is much asynchronous parallelism in many of these calculations. A model of a production code that requires up to 20 hours per problem on a CDC 7600 is studied for suitability on some asynchronous architectures that are on the drawing board. The code is described and some of its properties and resource requirements ae identified to compare with corresponding properties and resource requirements are identified to compare with corresponding properties and resource requirements are identified to compare with corresponding properties and resources of some asynchronous multiprocessor architectures. Arguments are made for programer aids and special syntax to identify and support important asynchronous parallelism. 2 figures, 5 tables
Adaptive Markov Chain Monte Carlo
Jadoon, Khan
2016-08-08
A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In the MCMC simulations, posterior distribution was computed using Bayes rule. The electromagnetic forward model based on the full solution of Maxwell\\'s equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD mini-Explorer. The model parameters and uncertainty for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness are not well estimated as compared to layers electrical conductivity because layer thicknesses in the model exhibits a low sensitivity to the EMI measurements, and is hence difficult to resolve. Application of the proposed MCMC based inversion to the field measurements in a drip irrigation system demonstrate that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provide useful insight about parameter uncertainty for the assessment of the model outputs.
Exploring Attribution Theory and Bias
Robinson, Jessica A.
2017-01-01
Courses: This activity can be used in a wide range of classes, including interpersonal communication, introduction to communication, and small group communication. Objectives: After completing this activity, students should be able to: (1) define attribution theory, personality attribution, situational attribution, and attribution bias; (2)…
Ratio Bias and Policy Preferences
DEFF Research Database (Denmark)
Pedersen, Rasmus Tue
2016-01-01
Numbers permeate modern political communication. While current scholarship on framing effects has focused on the persuasive effects of words and arguments, this article shows that framing of numbers can also substantially affect policy preferences. Such effects are caused by ratio bias, which...
Bias in Peripheral Depression Biomarkers
DEFF Research Database (Denmark)
Carvalho, André F; Köhler, Cristiano A; Brunoni, André R
2016-01-01
BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect...
International Nuclear Information System (INIS)
Kwee, Regina
2010-01-01
Since the restart of the LHC in November 2009, ATLAS has collected inelastic pp collisions to perform first measurements on charged particle densities. These measurements will help to constrain various models describing phenomenologically soft parton interactions. Understanding the trigger efficiencies for different event types are therefore crucial to minimize any possible bias in the event selection. ATLAS uses two main minimum bias triggers, featuring complementary detector components and trigger levels. While a hardware based first trigger level situated in the forward regions with 2.2 < |η| < 3.8 has been proven to select pp-collisions very efficiently, the Inner Detector based minimum bias trigger uses a random seed on filled bunches and central tracking detectors for the event selection. Both triggers were essential for the analysis of kinematic spectra of charged particles. Their performance and trigger efficiency measurements as well as studies on possible bias sources will be presented. We also highlight the advantage of these triggers for particle correlation analyses. (author)
Gender bias in teaching evaluations
Mengel, Friederike; Sauermann, Jan; Zölitz, Ulf Zoelitz
2017-01-01
This paper provides new evidence on gender bias in teaching evaluations. We exploit a quasi-experimental dataset of 19,952 student evaluations of university faculty in a context where students are randomly allocated to female or male instructors. Despite the fact that neither students’ grades nor
Attentional Bias in Math Anxiety
Directory of Open Access Journals (Sweden)
Orly eRubinsten
2015-10-01
Full Text Available Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety as well (i.e., a persistent negative reaction to math. Twenty seven participants (14 with high levels of math anxiety and 13 with low levels of math anxiety were presented with a novel computerized numerical version of the well established dot probe task. One of 6 types of prime stimuli, either math related or typically neutral, were presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks. Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in math anxiety. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words. These findings suggest that attentional bias is linked to unduly intense math anxiety symptoms.
Attentional bias in math anxiety.
Rubinsten, Orly; Eidlin, Hili; Wohl, Hadas; Akibli, Orly
2015-01-01
Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety (MA) as well (i.e., a persistent negative reaction to math). Twenty seven participants (14 with high levels of MA and 13 with low levels of MA) were presented with a novel computerized numerical version of the well established dot probe task. One of six types of prime stimuli, either math related or typically neutral, was presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks) that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks). Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in MA. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words). These findings suggest that attentional bias is linked to unduly intense MA symptoms.
Perception bias in route choice
Vreeswijk, Jacob Dirk; Thomas, Tom; van Berkum, Eric C.; van Arem, Bart
2014-01-01
Travel time is probably one of the most studied attributes in route choice. Recently, perception of travel time received more attention as several studies have shown its importance in explaining route choice behavior. In particular, travel time estimates by travelers appear to be biased against
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
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.
Quantum Monte Carlo approaches for correlated systems
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 ...
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)
Frontiers of quantum Monte Carlo workshop: preface
International Nuclear Information System (INIS)
Gubernatis, J.E.
1985-01-01
The introductory remarks, table of contents, and list of attendees are presented from the proceedings of the conference, Frontiers of Quantum Monte Carlo, which appeared in the Journal of Statistical Physics
Avariide kiuste Monte Carlosse / Aare Arula
Arula, Aare
2007-01-01
Vt. ka Tehnika dlja Vsehh nr. 3, lk. 26-27. 26. jaanuaril 1937 Tallinnast Monte Carlo tähesõidule startinud Karl Siitanit ja tema meeskonda ootasid ees seiklused, mis oleksid neile peaaegu elu maksnud
Monte Carlo code development in Los Alamos
International Nuclear Information System (INIS)
Carter, L.L.; Cashwell, E.D.; Everett, C.J.; Forest, C.A.; Schrandt, R.G.; Taylor, W.M.; Thompson, W.L.; Turner, G.D.
1974-01-01
The present status of Monte Carlo code development at Los Alamos Scientific Laboratory is discussed. A brief summary is given of several of the most important neutron, photon, and electron transport codes. 17 references. (U.S.)
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 Transport for Electron Thermal Transport
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.
A continuation multilevel Monte Carlo algorithm
Collier, Nathan; Haji Ali, Abdul Lateef; Nobile, Fabio; von Schwerin, Erik; Tempone, Raul
2014-01-01
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error
Aasta film - joonisfilm "Mont Blanc" / Verni Leivak
Leivak, Verni, 1966-
2002-01-01
Eesti Filmiajakirjanike Ühing andis aasta 2001 parima filmi tiitli Priit Tenderi joonisfilmile "Mont Blanc" : Eesti Joonisfilm 2001.Ka filmikriitikute eelistused kinodes ja televisioonis 2001. aastal näidatud filmide osas
Simulation and the Monte Carlo method
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...
Hybrid Monte Carlo methods in computational finance
Leitao Rodriguez, A.
2017-01-01
Monte Carlo methods are highly appreciated and intensively employed in computational finance in the context of financial derivatives valuation or risk management. The method offers valuable advantages like flexibility, easy interpretation and straightforward implementation. Furthermore, the
Measurement of the $B^-$ lifetime using a simulation free approach for trigger bias correction
Energy Technology Data Exchange (ETDEWEB)
Aaltonen, T.; /Helsinki Inst. of Phys.; Adelman, J.; /Chicago U., EFI; Alvarez Gonzalez, B.; /Cantabria Inst. of Phys.; Amerio, S.; /INFN, Padua; Amidei, D.; /Michigan U.; Anastassov, A.; /Northwestern U.; Annovi, A.; /Frascati; Antos, J.; /Comenius U.; Apollinari, G.; /Fermilab; Appel, J.; /Fermilab; Apresyan, A.; /Purdue U. /Waseda U.
2010-04-01
The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. In this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B{sup -} using the mode B{sup -} {yields} D{sup 0}{pi}{sup -}. The B{sup -} lifetime is measured as {tau}{sub B{sup -}} = 1.663 {+-} 0.023 {+-} 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.
Measurement of the B- lifetime using a simulation free approach for trigger bias correction
International Nuclear Information System (INIS)
2010-01-01
The collection of a large number of B hadron decays to hadronic final states at the CDF II detector is possible due to the presence of a trigger that selects events based on track impact parameters. However, the nature of the selection requirements of the trigger introduces a large bias in the observed proper decay time distribution. A lifetime measurement must correct for this bias and the conventional approach has been to use a Monte Carlo simulation. The leading sources of systematic uncertainty in the conventional approach are due to differences between the data and the Monte Carlo simulation. In this paper they present an analytic method for bias correction without using simulation, thereby removing any uncertainty between data and simulation. This method is presented in the form of a measurement of the lifetime of the B - using the mode B - → D 0 π - . The B - lifetime is measured as τ B# sup -# = 1.663 ± 0.023 ± 0.015 ps, where the first uncertainty is statistical and the second systematic. This new method results in a smaller systematic uncertainty in comparison to methods that use simulation to correct for the trigger bias.
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.
Multilevel Monte Carlo in Approximate Bayesian Computation
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 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)
Selb, Juliette; Ogden, Tyler M.; Dubb, Jay; Fang, Qianqian; Boas, David A.
2013-03-01
Time-domain near-infrared spectroscopy (TD-NIRS) offers the ability to measure the absolute baseline optical properties of a tissue. Specifically, for brain imaging, the robust assessment of cerebral blood volume and oxygenation based on measurement of cerebral hemoglobin concentrations is essential for reliable cross-sectional and longitudinal studies. In adult heads, these baseline measurements are complicated by the presence of thick extra-cerebral tissue (scalp, skull, CSF). A simple semi-infinite homogeneous model of the head has proven to have limited use because of the large errors it introduces in the recovered brain absorption. Analytical solutions for layered media have shown improved performance on Monte-Carlo simulated data and layered phantom experiments, but their validity on real adult head data has never been demonstrated. With the advance of fast Monte Carlo approaches based on GPU computation, numerical methods to solve the radiative transfer equation become viable alternatives to analytical solutions of the diffusion equation. Monte Carlo approaches provide the additional advantage to be adaptable to any geometry, in particular more realistic head models. The goals of the present study were twofold: (1) to implement a fast and flexible Monte Carlo-based fitting routine to retrieve the brain optical properties; (2) to characterize the performances of this fitting method on realistic adult head data. We generated time-resolved data at various locations over the head, and fitted them with different models of light propagation: the homogeneous analytical model, and Monte Carlo simulations for three head models: a two-layer slab, the true subject's anatomy, and that of a generic atlas head. We found that the homogeneous model introduced a median 20 to 25% error on the recovered brain absorption, with large variations over the range of true optical properties. The two-layer slab model only improved moderately the results over the homogeneous one. On
Biasing transition rate method based on direct MC simulation for probabilistic safety assessment
Institute of Scientific and Technical Information of China (English)
Xiao-Lei Pan; Jia-Qun Wang; Run Yuan; Fang Wang; Han-Qing Lin; Li-Qin Hu; Jin Wang
2017-01-01
Direct Monte Carlo (MC) simulation is a powerful probabilistic safety assessment method for accounting dynamics of the system.But it is not efficient at simulating rare events.A biasing transition rate method based on direct MC simulation is proposed to solve the problem in this paper.This method biases transition rates of the components by adding virtual components to them in series to increase the occurrence probability of the rare event,hence the decrease in the variance of MC estimator.Several cases are used to benchmark this method.The results show that the method is effective at modeling system failure and is more efficient at collecting evidence of rare events than the direct MC simulation.The performance is greatly improved by the biasing transition rate method.
Underlying Event studies and Monte Carlo tunes for inelastic pp events with the ATLAS detector
Nurse, E; The ATLAS collaboration
2010-01-01
Studies of the momentum flow in inelastic collisions at 900 GeV and 7 TeV recorded with a minimum bias trigger strategy are reported. A single high pT track is selected, and the distribution of other tracks in the event is evaluated relative to this reference track. The evolution of the charged momentum flow in the rest of the event, as a function of the pT of the reference track, gives important information about the transition from minimum bias event structure to the full underlying event observed in high-pT collision events. Results are presented after correction and unfolding of detector effects to allow simpler comparison to Monte Carlo models. In addition, the PYTHIA Monte Carlo generator has been tuned to ATLAS measurements at 900 GeV and 7 TeV. Standard distributions from Minimum Bias events, as well as the Underlying Event studies are included in the first tunes to ATLAS measurements at the LHC. The tunes aim for one consistent description of the new measurements as well as data from the Tevatron and...
Energy Technology Data Exchange (ETDEWEB)
Christoforou, Stavros, E-mail: stavros.christoforou@gmail.com [Kirinthou 17, 34100, Chalkida (Greece); Hoogenboom, J. Eduard, E-mail: j.e.hoogenboom@tudelft.nl [Department of Applied Sciences, Delft University of Technology (Netherlands)
2011-07-01
A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k{sub eff} estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)
International Nuclear Information System (INIS)
Christoforou, Stavros; Hoogenboom, J. Eduard
2011-01-01
A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k_e_f_f estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)
International Nuclear Information System (INIS)
Colbeck, Roger; Kent, Adrian
2006-01-01
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Colbeck, Roger; Kent, Adrian
2006-03-01
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT.
Chowdhry, D P
1995-01-01
This article identifies gender bias against female children and youth in India. Gender bias is based on centuries-old religious beliefs and sayings from ancient times. Discrimination is reflected in denial or ignorance of female children's educational, health, nutrition, and recreational needs. Female infanticide and selective abortion of female fetuses are other forms of discrimination. The task of eliminating or reducing gender bias will involve legal, developmental, political, and administrative measures. Public awareness needs to be created. There is a need to reorient the education and health systems and to advocate for gender equality. The government of India set the following goals for the 1990s: to protect the survival of the girl child and practice safe motherhood; to develop the girl child in general; and to protect vulnerable girl children in different circumstances and in special groups. The Health Authorities should monitor the laws carefully to assure marriage after the minimum age, ban sex determination of the fetus, and monitor the health and nutrition of pre-school girls and nursing and pregnant mothers. Mothers need to be encouraged to breast feed, and to breast feed equally between genders. Every village and slum area needs a mini health center. Maternal mortality must decline. Primary health centers and hospitals need more women's wards. Education must be universally accessible. Enrollments should be increased by educating rural tribal and slum parents, reducing distances between home and school, making curriculum more relevant to girls, creating more female teachers, and providing facilities and incentives for meeting the needs of girl students. Supplementary income could be provided to families for sending girls to school. Recreational activities must be free of gender bias. Dowry, sati, and devdasi systems should be banned.
Competition and Commercial Media Bias
Blasco, Andrea; Sobbrio, Francesco
2011-01-01
This paper reviews the empirical evidence on commercial media bias (i.e., advertisers influence over media accuracy) and then introduces a simple model to summarize the main elements of the theoretical literature. The analysis provides three main policy insights for media regulators: i) Media regulators should target their monitoring efforts towards news contents upon which advertisers are likely to share similar preferences; ii) In advertising industries characterized by high correlation in ...
BEHAVIORAL BIASES IN TRADING SECURITIES
Directory of Open Access Journals (Sweden)
Turcan Ciprian Sebastian
2010-12-01
Full Text Available The main thesis of this paper represents the importance and the effects that human behavior has over capital markets. It is important to see the link between the asset valuation and investor sentiment that motivate to pay for an asset a certain prices over/below the intrinsic value. The main behavioral aspects discussed are emotional factors such as: fear of regret, overconfidence, perseverance, loss aversion ,heuristic biases, misinformation and thinking errors, herding and their consequences.
Galaxy formation and physical bias
Cen, Renyue; Ostriker, Jeremiah P.
1992-01-01
We have supplemented our code, which computes the evolution of the physical state of a representative piece of the universe to include, not only the dynamics of dark matter (with a standard PM code), and the hydrodynamics of the gaseous component (including detailed collisional and radiative processes), but also galaxy formation on a heuristic but plausible basis. If, within a cell the gas is Jeans' unstable, collapsing, and cooling rapidly, it is transformed to galaxy subunits, which are then followed with a collisionless code. After grouping them into galaxies, we estimate the relative distributions of galaxies and dark matter and the relative velocities of galaxies and dark matter. In a large scale CDM run of 80/h Mpc size with 8 x 10 exp 6 cells and dark matter particles, we find that physical bias b is on the 8/h Mpc scale is about 1.6 and increases towards smaller scales, and that velocity bias is about 0.8 on the same scale. The comparable HDM simulation is highly biased with b = 2.7 on the 8/h Mpc scale. Implications of these results are discussed in the light of the COBE observations which provide an accurate normalization for the initial power spectrum. CDM can be ruled out on the basis of too large a predicted small scale velocity dispersion at greater than 95 percent confidence level.
Opinion dynamics with confirmation bias.
Directory of Open Access Journals (Sweden)
Armen E Allahverdyan
Full Text Available Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical research of this phenomenon has mainly focused on its economic implications possibly missing its potential connections with broader notions of cognitive science.We formulate a (non-Bayesian model for revising subjective probabilistic opinion of a confirmationally-biased agent in the light of a persuasive opinion. The revision rule ensures that the agent does not react to persuasion that is either far from his current opinion or coincides with it. We demonstrate that the model accounts for the basic phenomenology of the social judgment theory, and allows to study various phenomena such as cognitive dissonance and boomerang effect. The model also displays the order of presentation effect-when consecutively exposed to two opinions, the preference is given to the last opinion (recency or the first opinion (primacy -and relates recency to confirmation bias. Finally, we study the model in the case of repeated persuasion and analyze its convergence properties.The standard Bayesian approach to probabilistic opinion revision is inadequate for describing the observed phenomenology of persuasion process. The simple non-Bayesian model proposed here does agree with this phenomenology and is capable of reproducing a spectrum of effects observed in psychology: primacy-recency phenomenon, boomerang effect and cognitive dissonance. We point out several limitations of the model that should motivate its future development.
Directory of Open Access Journals (Sweden)
Eric Dumonteil
2017-09-01
Full Text Available The Monte Carlo criticality simulation of decoupled systems, as for instance in large reactor cores, has been a challenging issue for a long time. In particular, due to limited computer time resources, the number of neutrons simulated per generation is still many order of magnitudes below realistic statistics, even during the start-up phases of reactors. This limited number of neutrons triggers a strong clustering effect of the neutron population that affects Monte Carlo tallies. Below a certain threshold, not only is the variance affected but also the estimation of the eigenvectors. In this paper we will build a time-dependent diffusion equation that takes into account both spatial correlations and population control (fixed number of neutrons along generations. We will show that its solution obeys a traveling wave dynamic, and we will discuss the mechanism that explains this biasing of local tallies whenever leakage boundary conditions are applied to the system.
Chain segmentation for the Monte Carlo solution of particle transport problems
International Nuclear Information System (INIS)
Ragheb, M.M.H.
1984-01-01
A Monte Carlo approach is proposed where the random walk chains generated in particle transport simulations are segmented. Forward and adjoint-mode estimators are then used in conjunction with the firstevent source density on the segmented chains to obtain multiple estimates of the individual terms of the Neumann series solution at each collision point. The solution is then constructed by summation of the series. The approach is compared to the exact analytical and to the Monte Carlo nonabsorption weighting method results for two representative slowing down and deep penetration problems. Application of the proposed approach leads to unbiased estimates for limited numbers of particle simulations and is useful in suppressing an effective bias problem observed in some cases of deep penetration particle transport problems
Tripoli-4, a three-dimensional poly-kinetic particle transport Monte-Carlo code
International Nuclear Information System (INIS)
Both, J.P.; Lee, Y.K.; Mazzolo, A.; Peneliau, Y.; Petit, O.; Roesslinger, B.; Soldevila, M.
2003-01-01
In this updated of the Monte-Carlo transport code Tripoli-4, we list and describe its current main features. The code computes coupled neutron-photon propagation as well as the electron-photon cascade shower. While providing the user with common biasing techniques, it also implements an automatic weighting scheme. Tripoli-4 enables the user to compute the following physical quantities: a flux, a multiplication factor, a current, a reaction rate, a dose equivalent rate as well as deposit of energy and recoil energies. For each interesting physical quantity, a Monte-Carlo simulation offers different types of estimators. Tripoli-4 has support for execution in parallel mode. Special features and applications are also presented
MUSiC - A general search for deviations from Monte Carlo predictions in CMS
Energy Technology Data Exchange (ETDEWEB)
Biallass, Philipp A, E-mail: biallass@cern.c [Physics Institute IIIA, RWTH Aachen, Physikzentrum, 52056 Aachen (Germany)
2009-06-01
A model independent analysis approach in CMS is presented, systematically scanning the data for deviations from the Monte Carlo expectation. Such an analysis can contribute to the understanding of the detector and the tuning of the event generators. Furthermore, due to the minimal theoretical bias this approach is sensitive to a variety of models of new physics, including those not yet thought of. Events are classified into event classes according to their particle content (muons, electrons, photons, jets and missing transverse energy). A broad scan of various distributions is performed, identifying significant deviations from the Monte Carlo simulation. The importance of systematic uncertainties is outlined, which are taken into account rigorously within the algorithm. Possible detector effects and generator issues, as well as models involving Supersymmetry and new heavy gauge bosons are used as an input to the search algorithm.
MUSIC -- An Automated Scan for Deviations between Data and Monte Carlo Simulation
CMS Collaboration
2008-01-01
We present a model independent analysis approach, systematically scanning the data for deviations from the Monte Carlo expectation. Such an analysis can contribute to the understanding of the detector and the tuning of the event generators. Due to the minimal theoretical bias this approach is sensitive to a variety of models, including those not yet thought of. Events are classified into event classes according to their particle content (muons, electrons, photons, jets and missing transverse energy). A broad scan of various distributions is performed, identifying significant deviations from the Monte Carlo simulation. We outline the importance of systematic uncertainties, which are taken into account rigorously within the algorithm. Possible detector effects and generator issues, as well as models involving supersymmetry and new heavy gauge bosons have been used as an input to the search algorithm. %Several models involving supersymmetry, new heavy gauge bosons and leptoquarks, as well as possible detector ef...
MUSiC A General Search for Deviations from Monte Carlo Predictions in CMS
Biallass, Philipp
2009-01-01
A model independent analysis approach in CMS is presented, systematically scanning the data for deviations from the Monte Carlo expectation. Such an analysis can contribute to the understanding of the detector and the tuning of the event generators. Furthermore, due to the minimal theoretical bias this approach is sensitive to a variety of models of new physics, including those not yet thought of. Events are classified into event classes according to their particle content (muons, electrons, photons, jets and missing transverse energy). A broad scan of various distributions is performed, identifying significant deviations from the Monte Carlo simulation. The importance of systematic uncertainties is outlined, which are taken into account rigorously within the algorithm. Possible detector effects and generator issues, as well as models involving Supersymmetry and new heavy gauge bosons are used as an input to the search algorithm.
MUSiC - A general search for deviations from Monte Carlo predictions in CMS
International Nuclear Information System (INIS)
Biallass, Philipp A
2009-01-01
A model independent analysis approach in CMS is presented, systematically scanning the data for deviations from the Monte Carlo expectation. Such an analysis can contribute to the understanding of the detector and the tuning of the event generators. Furthermore, due to the minimal theoretical bias this approach is sensitive to a variety of models of new physics, including those not yet thought of. Events are classified into event classes according to their particle content (muons, electrons, photons, jets and missing transverse energy). A broad scan of various distributions is performed, identifying significant deviations from the Monte Carlo simulation. The importance of systematic uncertainties is outlined, which are taken into account rigorously within the algorithm. Possible detector effects and generator issues, as well as models involving Supersymmetry and new heavy gauge bosons are used as an input to the search algorithm.
Tripoli-4, a three-dimensional poly-kinetic particle transport Monte-Carlo code
Energy Technology Data Exchange (ETDEWEB)
Both, J P; Lee, Y K; Mazzolo, A; Peneliau, Y; Petit, O; Roesslinger, B; Soldevila, M [CEA Saclay, Dir. de l' Energie Nucleaire (DEN/DM2S/SERMA/LEPP), 91 - Gif sur Yvette (France)
2003-07-01
In this updated of the Monte-Carlo transport code Tripoli-4, we list and describe its current main features. The code computes coupled neutron-photon propagation as well as the electron-photon cascade shower. While providing the user with common biasing techniques, it also implements an automatic weighting scheme. Tripoli-4 enables the user to compute the following physical quantities: a flux, a multiplication factor, a current, a reaction rate, a dose equivalent rate as well as deposit of energy and recoil energies. For each interesting physical quantity, a Monte-Carlo simulation offers different types of estimators. Tripoli-4 has support for execution in parallel mode. Special features and applications are also presented.
Matrilateral Bias in Human Grandmothering
Directory of Open Access Journals (Sweden)
Martin Daly
2017-09-01
Full Text Available Children receive more care and resources from their maternal grandmothers than from their paternal grandmothers. This asymmetry is the “matrilateral bias” in grandmaternal investment. Here, we synopsize the evolutionary theories that predict such a bias, and review evidence of its cross-cultural generality and magnitude. Evolutionists have long maintained that investing in a daughter’s child yields greater fitness returns, on average, than investing in a son’s child because of paternity uncertainty: the son’s putative progeny may have been sired by someone else. Recent theoretical work has identified an additional natural selective basis for the matrilateral bias that may be no less important: supporting grandchildren lightens the load on their mother, increasing her capacity to pursue her fitness in other ways, and if she invests those gains either in her natal relatives or in children of a former or future partner, fitness returns accrue to the maternal, but not the paternal, grandmother. In modern democracies, where kinship is reckoned bilaterally and no postmarital residence norms restrict grandmaternal access to grandchildren, many studies have found large matrilateral biases in contact, childcare, and emotional closeness. In other societies, patrilineal ideology and postmarital residence with the husband’s kin (virilocality might be expected to have produced a patrilateral bias instead, but the available evidence refutes this hypothesis. In hunter-gatherers, regardless of professed norms concerning kinship and residence, mothers get needed help at and after childbirth from their mothers, not their mothers-in-law. In traditional agricultural and pastoral societies, patrilineal and virilocal norms are common, but young mothers still turn to their natal families for crucial help, and several studies have documented benefits, including reduced child mortality, associated with access to maternal, but not paternal, grandmothers. Even
Bandyopadhyay, Pradipta
2008-04-07
The efficiency of the two-surface monte carlo (TSMC) method depends on the closeness of the actual potential and the biasing potential used to propagate the system of interest. In this work, it is shown that by combining the basin hopping method with TSMC, the efficiency of the method can be increased by several folds. TSMC with basin hopping is used to generate quantum mechanical trajectory and large number of stationary points of water clusters.
Bias-correction in vector autoregressive models
DEFF Research Database (Denmark)
Engsted, Tom; Pedersen, Thomas Quistgaard
2014-01-01
We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study......, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable...... improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find...
The Probability Distribution for a Biased Spinner
Foster, Colin
2012-01-01
This article advocates biased spinners as an engaging context for statistics students. Calculating the probability of a biased spinner landing on a particular side makes valuable connections between probability and other areas of mathematics. (Contains 2 figures and 1 table.)
Short Communication: Gender Bias and Stigmatization against ...
African Journals Online (AJOL)
Short Communication: Gender Bias and Stigmatization against Women Living with ... In Ethiopia, HIV/AIDS is highly stigmatized due to the fact that sexual ... bias, socio-economic situations and traditional beliefs contribute, individually and in ...
International Nuclear Information System (INIS)
Orkoulas, G.; Panagiotopoulos, A.Z.
1994-01-01
In this work, we investigate the liquid--vapor phase transition of the restricted primitive model of ionic fluids. We show that at the low temperatures where the phase transition occurs, the system cannot be studied by conventional molecular simulation methods because convergence to equilibrium is slow. To accelerate convergence, we propose cluster Monte Carlo moves capable of moving more than one particle at a time. We then address the issue of charged particle transfers in grand canonical and Gibbs ensemble Monte Carlo simulations, for which we propose a biased particle insertion/destruction scheme capable of sampling short interparticle distances. We compute the chemical potential for the restricted primitive model as a function of temperature and density from grand canonical Monte Carlo simulations and the phase envelope from Gibbs Monte Carlo simulations. Our calculated phase coexistence curve is in agreement with recent results of Caillol obtained on the four-dimensional hypersphere and our own earlier Gibbs ensemble simulations with single-ion transfers, with the exception of the critical temperature, which is lower in the current calculations. Our best estimates for the critical parameters are T * c =0.053, ρ * c =0.025. We conclude with possible future applications of the biased techniques developed here for phase equilibrium calculations for ionic fluids
Optimization of path length stretching in Monte Carlo calculations for non-leakage problems
Energy Technology Data Exchange (ETDEWEB)
Hoogenboom, J.E. [Delft Univ. of Technology (Netherlands)
2005-07-01
Path length stretching (or exponential biasing) is a well known variance reduction technique in Monte Carlo calculations. It can especially be useful in shielding problems where particles have to penetrate a lot of material before being tallied. Several authors sought for optimization of the path length stretching parameter for detection of the leakage of neutrons from a slab. Here the adjoint function behaves as a single exponential function and can well be used to determine the stretching parameter. In this paper optimization is sought for a detector embedded in the system, which changes the adjoint function in the detector drastically. From literature it is known that the combination of path length stretching and angular biasing can result in appreciable variance reduction. However, angular biasing is not generally available in general purpose Monte Carlo codes and therefore we want to restrict ourselves to the application of pure path length stretching and finding optimum parameters for that. Nonetheless, the starting point for our research is the zero-variance scheme. In order to study the solution in detail the simplified monoenergetic two-direction model is adopted, which allows analytical solutions and can still be used in a Monte Carlo simulation. Knowing the zero-variance solution analytically, it is shown how optimum path length stretching parameters can be derived from it. It results in path length shrinking in the detector. Results for the variance in the detector response are shown in comparison with other patterns for the stretching parameter. The effect of anisotropic scattering on the path length stretching parameter is taken into account. (author)
Is there bias in editorial choice? Yes
Moustafa, Khaled
2018-01-01
Nature has recently published a Correspondence claiming the absence of fame biases in the editorial choice. The topic is interesting and deserves a deeper analysis than it was presented because the reported brief analysis and its conclusion are somewhat biased for many reasons, some of them are discussed here. Since the editorial assessment is a form of peer-review, the biases reported on external peer-reviews would, thus, apply to the editorial assessment, too. The biases would be proportion...
Bias-field equalizer for bubble memories
Keefe, G. E.
1977-01-01
Magnetoresistive Perm-alloy sensor monitors bias field required to maintain bubble memory. Sensor provides error signal that, in turn, corrects magnitude of bias field. Error signal from sensor can be used to control magnitude of bias field in either auxiliary set of bias-field coils around permanent magnet field, or current in small coils used to remagnetize permanent magnet by infrequent, short, high-current pulse or short sequence of pulses.
Optimization of linear Monte Carlo calculations
International Nuclear Information System (INIS)
Troubetzkoy, E.S.
1991-01-01
The variance of the calculation is minimized on the basis of parameters generated by a learning technique. The optimum is obtained if sampling is biased proportionally to the expected root-mean-square score. In this paper, the method is compared with existing methods, which bias proportionally to the expected score
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.)
The Accuracy Enhancing Effect of Biasing Cues
W. Vanhouche (Wouter); S.M.J. van Osselaer (Stijn)
2009-01-01
textabstractExtrinsic cues such as price and irrelevant attributes have been shown to bias consumers’ product judgments. Results in this article replicate those findings in pretrial judgments but show that such biasing cues can improve quality judgments at a later point in time. Initially biasing
Biased managers, organizational design, and incentive provision
Moreira, Humberto Ataíde; Costa, Cristiano Machado; Ferreira, Daniel Bernardo Soares
2004-01-01
Rio de Janeiro We model the tradeoff between the balance and the strength of incentives implicit in the choice between hierarchical and matrix organizational structures. We show that managerial biases determine which structure is optimal: hierarchical forms are preferred when biases are low, while matrix structures are preferred when biases are high.
Minimum bias and underlying event studies at CDF
International Nuclear Information System (INIS)
Moggi, Niccolo
2010-01-01
Soft, non-perturbative, interactions are poorly understood from the theoretical point of view even though they form a large part of the hadronic cross section at the energies now available. We review the CDF studies on minimum-bias ad underlying event in p(bar p) collisions at 2 TeV. After proposing an operative definition of 'underlying event', we present part of a systematic set of measurements carried out by the CDF Collaboration with the goal to provide data to test and improve the QCD models of hadron collisions. Different analysis strategies of the underlying event and possible event topologies are discussed. Part of the CDF minimum-bias results are also presented: in this sample, that represent the full inelastic cross-section, we can test simultaneously our knowledge of all the components that concur to form hadronic interactions. Comparisons with MonteCarlo simulations are always shown along with the data. These measurements will also contribute to more precise estimates of the soft QCD background of high-p T observables.
International Nuclear Information System (INIS)
Hoogenboom, J.E.
1981-01-01
An adjoint Monte Carlo technique is described for the solution of neutron transport problems. The optimum biasing function for a zero-variance collision estimator is derived. The optimum treatment of an analog of a non-velocity thermal group has also been derived. The method is extended to multiplying systems, especially for eigenfunction problems to enable the estimate of averages over the unknown fundamental neutron flux distribution. A versatile computer code, FOCUS, has been written, based on the described theory. Numerical examples are given for a shielding problem and a critical assembly, illustrating the performance of the FOCUS code. 19 refs
PBMC: Pre-conditioned Backward Monte Carlo code for radiative transport in planetary atmospheres
García Muñoz, A.; Mills, F. P.
2017-08-01
PBMC (Pre-Conditioned Backward Monte Carlo) solves the vector Radiative Transport Equation (vRTE) and can be applied to planetary atmospheres irradiated from above. The code builds the solution by simulating the photon trajectories from the detector towards the radiation source, i.e. in the reverse order of the actual photon displacements. In accounting for the polarization in the sampling of photon propagation directions and pre-conditioning the scattering matrix with information from the scattering matrices of prior (in the BMC integration order) photon collisions, PBMC avoids the unstable and biased solutions of classical BMC algorithms for conservative, optically-thick, strongly-polarizing media such as Rayleigh atmospheres.
Mean-value identities as an opportunity for Monte Carlo error reduction.
Fernandez, L A; Martin-Mayor, V
2009-05-01
In the Monte Carlo simulation of both lattice field theories and of models of statistical mechanics, identities verified by exact mean values, such as Schwinger-Dyson equations, Guerra relations, Callen identities, etc., provide well-known and sensitive tests of thermalization bias as well as checks of pseudo-random-number generators. We point out that they can be further exploited as control variates to reduce statistical errors. The strategy is general, very simple, and almost costless in CPU time. The method is demonstrated in the two-dimensional Ising model at criticality, where the CPU gain factor lies between 2 and 4.
On the errors on Omega(0): Monte Carlo simulations of the EMSS cluster sample
DEFF Research Database (Denmark)
Oukbir, J.; Arnaud, M.
2001-01-01
We perform Monte Carlo simulations of synthetic EMSS cluster samples, to quantify the systematic errors and the statistical uncertainties on the estimate of Omega (0) derived from fits to the cluster number density evolution and to the X-ray temperature distribution up to z=0.83. We identify...... the scatter around the relation between cluster X-ray luminosity and temperature to be a source of systematic error, of the order of Delta (syst)Omega (0) = 0.09, if not properly taken into account in the modelling. After correcting for this bias, our best Omega (0) is 0.66. The uncertainties on the shape...
The future of new calculation concepts in dosimetry based on the Monte Carlo Methods
International Nuclear Information System (INIS)
Makovicka, L.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Vasseur, A.; Sauget, M.; Martin, E.; Gschwind, R.; Henriet, J.; Salomon, M.
2009-01-01
Monte Carlo codes, precise but slow, are very important tools in the vast majority of specialities connected to Radiation Physics, Radiation Protection and Dosimetry. A discussion about some other computing solutions is carried out; solutions not only based on the enhancement of computer power, or on the 'biasing'used for relative acceleration of these codes (in the case of photons), but on more efficient methods (A.N.N. - artificial neural network, C.B.R. - case-based reasoning - or other computer science techniques) already and successfully used for a long time in other scientific or industrial applications and not only Radiation Protection or Medical Dosimetry. (authors)
Monte Carlo simulations of a ferromagnetic-FeF2 system
International Nuclear Information System (INIS)
Billoni, Orlando V.; Tamarit, Francisco A.; Cannas, Sergio A.
2006-01-01
In this work, we perform Monte Carlo simulations to study the magnetization reversal mechanism in ferromagnetic thin films on FeF 2 . In particular, we emulate a bilayer AFM/FM structure, where the AFM interface corresponds to an uncompensated (100) plane. The magnetic moments are modeled by classical Heisenberg spin variables. Our analysis focus on the role of the exchange interaction J AF between the FM spins and the spins belonging to the AFM interface on the reversal mechanisms of the magnetization. By simulating hysteresis loops we study the effect of temperature on the bias field
Monte Carlo strategies in scientific computing
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...
Random Numbers and Monte Carlo Methods
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.
Off-diagonal expansion quantum Monte Carlo.
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.
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
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.
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
Directory of Open Access Journals (Sweden)
Vahid Moslemi
2011-03-01
Full Text Available Introduction: In brachytherapy, radioactive sources are placed close to the tumor, therefore, small changes in their positions can cause large changes in the dose distribution. This emphasizes the need for computerized treatment planning. The usual method for treatment planning of cervix brachytherapy uses conventional radiographs in the Manchester system. Nowadays, because of their advantages in locating the source positions and the surrounding tissues, CT and MRI images are replacing conventional radiographs. In this study, we used CT images in Monte Carlo based dose calculation for brachytherapy treatment planning, using an interface software to create the geometry file required in the MCNP code. The aim of using the interface software is to facilitate and speed up the geometry set-up for simulations based on the patient’s anatomy. This paper examines the feasibility of this method in cervix brachytherapy and assesses its accuracy and speed. Material and Methods: For dosimetric measurements regarding the treatment plan, a pelvic phantom was made from polyethylene in which the treatment applicators could be placed. For simulations using CT images, the phantom was scanned at 120 kVp. Using an interface software written in MATLAB, the CT images were converted into MCNP input file and the simulation was then performed. Results: Using the interface software, preparation time for the simulations of the applicator and surrounding structures was approximately 3 minutes; the corresponding time needed in the conventional MCNP geometry entry being approximately 1 hour. The discrepancy in the simulated and measured doses to point A was 1.7% of the prescribed dose. The corresponding dose differences between the two methods in rectum and bladder were 3.0% and 3.7% of the prescribed dose, respectively. Comparing the results of simulation using the interface software with those of simulation using the standard MCNP geometry entry showed a less than 1
An inclusive taxonomy of behavioral biases
Directory of Open Access Journals (Sweden)
David Peón
2017-07-01
Full Text Available This paper overviews the theoretical and empirical research on behavioral biases and their influence in the literature. To provide a systematic exposition, we present a unified framework that takes the reader through an original taxonomy, based on the reviews of relevant authors in the field. In particular, we establish three broad categories that may be distinguished: heuristics and biases; choices, values and frames; and social factors. We then describe the main biases within each category, and revise the main theoretical and empirical developments, linking each bias with other biases and anomalies that are related to them, according to the literature.
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
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
International Nuclear Information System (INIS)
Ho, Le Bin; Lan, Tran Nguyen; Hai, Tran Hoang
2013-01-01
In this work, we have used the Monte Carlo simulation to investigate the magnetic properties of an isolated composite magnetic nanoparticle with ferromagnetic (FM) core and antiferromagnetic (AFM) shell morphology. The defects were assumed to be randomly located at the AFM interface. The Néel anisotropy was used for the FM interface spins at where there are the lacks of crystal symmetry due to the vacancies at AFM interface. With a moderate defect concentration, the coercive field non-monotonously depends on the Néel anisotropy. We have examined the dependence of coercivity, exchange bias field, and vertical shift on defect concentration. We found that in addition to AFM shell, the disordered FM interface is another pining-source for exchange bias phenomenon. We discuss our simulated results in the relation to recent experimental findings
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.
Simplified monte carlo simulation for Beijing spectrometer
International Nuclear Information System (INIS)
Wang Taijie; Wang Shuqin; Yan Wuguang; Huang Yinzhi; Huang Deqiang; Lang Pengfei
1986-01-01
The Monte Carlo method based on the functionization of the performance of detectors and the transformation of values of kinematical variables into ''measured'' ones by means of smearing has been used to program the Monte Carlo simulation of the performance of the Beijing Spectrometer (BES) in FORTRAN language named BESMC. It can be used to investigate the multiplicity, the particle type, and the distribution of four-momentum of the final states of electron-positron collision, and also the response of the BES to these final states. Thus, it provides a measure to examine whether the overall design of the BES is reasonable and to decide the physical topics of the BES
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
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)
A keff calculation method by Monte Carlo
International Nuclear Information System (INIS)
Shen, H; Wang, K.
2008-01-01
The effective multiplication factor (k eff ) is defined as the ratio between the number of neutrons in successive generations, which definition is adopted by most Monte Carlo codes (e.g. MCNP). Also, it can be thought of as the ratio of the generation rate of neutrons by the sum of the leakage rate and the absorption rate, which should exclude the effect of the neutron reaction such as (n, 2n) and (n, 3n). This article discusses the Monte Carlo method for k eff calculation based on the second definition. A new code has been developed and the results are presented. (author)
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
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
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
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
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.)
Gender Bias Affects Forests Worldwide
Directory of Open Access Journals (Sweden)
Marlène Elias
2017-04-01
Full Text Available Gender biases persist in forestry research and practice. These biases result in reduced scientific rigor and inequitable, ineffective, and less efficient policies, programs, and interventions. Drawing from a two-volume collection of current and classic analyses on gender in forests, we outline five persistent and inter-related themes: gendered governance, tree tenure, forest spaces, division of labor, and ecological knowledge. Each emerges across geographic regions in the northern and southern hemisphere and reflects inequities in women’s and men’s ability to make decisions about and benefit from trees, forests, and their products. Women’s ability to participate in community-based forest governance is typically less than men’s, causing concern for social equity and forest stewardship. Women’s access to trees and their products is commonly more limited than men’s, and mediated by their relationship with their male counterparts. Spatial patterns of forest use reflect gender norms and taboos, and men’s greater access to transportation. The division of labor results in gender specialization in the collection of forest products, with variations in gender roles across regions. All these gender differences result in ecological knowledge that is distinct but also complementary and shifting across the genders. The ways gender plays out in relation to each theme may vary across cultures and contexts, but the influence of gender, which intersects with other factors of social differentiation in shaping forest landscapes, is global.
Workplace ageism: discovering hidden bias.
Malinen, Sanna; Johnston, Lucy
2013-01-01
BACKGROUND/STUDY CONTEXT: Research largely shows no performance differences between older and younger employees, or that older workers even outperform younger employees, yet negative attitudes towards older workers can underpin discrimination. Unfortunately, traditional "explicit" techniques for assessing attitudes (i.e., self-report measures) have serious drawbacks. Therefore, using an approach that is novel to organizational contexts, the authors supplemented explicit with implicit (indirect) measures of attitudes towards older workers, and examined the malleability of both. This research consists of two studies. The authors measured self-report (explicit) attitudes towards older and younger workers with a survey, and implicit attitudes with a reaction-time-based measure of implicit associations. In addition, to test whether attitudes were malleable, the authors measured attitudes before and after a mental imagery intervention, where the authors asked participants in the experimental group to imagine respected and valued older workers from their surroundings. Negative, stable implicit attitudes towards older workers emerged in two studies. Conversely, explicit attitudes showed no age bias and were more susceptible to change intervention, such that attitudes became more positive towards older workers following the experimental manipulation. This research demonstrates the unconscious nature of bias against older workers, and highlights the utility of implicit attitude measures in the context of the workplace. In the current era of aging workforce and skill shortages, implicit measures may be necessary to illuminate hidden workplace ageism.
Energy Technology Data Exchange (ETDEWEB)
Al-Subeihi, Ala' A.A., E-mail: subeihi@yahoo.com [Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen (Netherlands); BEN-HAYYAN-Aqaba International Laboratories, Aqaba Special Economic Zone Authority (ASEZA), P. O. Box 2565, Aqaba 77110 (Jordan); Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert [Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen (Netherlands); Bladeren, Peter J. van [Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen (Netherlands); Nestec S.A., Avenue Nestlé 55, 1800 Vevey (Switzerland); Rietjens, Ivonne M.C.M.; Punt, Ans [Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen (Netherlands)
2015-03-01
The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1′-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1′-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1′-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1′-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1′-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1′-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment. - Highlights: • Interindividual human differences in methyleugenol bioactivation were simulated. • This was done using in vitro incubations, PBK modeling
International Nuclear Information System (INIS)
Al-Subeihi, Ala' A.A.; Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert; Bladeren, Peter J. van; Rietjens, Ivonne M.C.M.; Punt, Ans
2015-01-01
The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1′-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1′-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1′-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1′-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1′-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1′-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment. - Highlights: • Interindividual human differences in methyleugenol bioactivation were simulated. • This was done using in vitro incubations, PBK modeling
International Nuclear Information System (INIS)
Wagner, J. C.; Blakeman, E. D.; Peplow, D. E.
2009-01-01
This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is a variation on the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for some time to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development of an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain approximately uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented in the ADVANTG/MCNP framework and has been fully automated within the MAVRIC sequence of SCALE 6. Results of the application of the method to enabling the calculation of dose rates throughout an entire full-scale pressurized-water reactor facility are presented and discussed. (authors)
Fast sequential Monte Carlo methods for counting and optimization
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
Energy Technology Data Exchange (ETDEWEB)
Türkmen, Mehmet, E-mail: tm@hacettepe.edu.tr [Nuclear Engineering Department, Hacettepe University, Beytepe Campus, Ankara (Turkey); Çolak, Üner [Energy Institute, Istanbul Technical University, Ayazağa Campus, Maslak, Istanbul (Turkey); Ergün, Şule [Nuclear Engineering Department, Hacettepe University, Beytepe Campus, Ankara (Turkey)
2015-12-15
Highlights: • Optimum core maps were generated for the ITU TRIGA Mark II Research Reactor. • Calculations were performed using a Monte Carlo based reactor physics code, MCNP. • Single-Objective and Multi-Objective Genetic Algorithms were used for the optimization. • k{sub eff} and ppf{sub max} were considered as the optimization objectives. • The generated core maps were compared with the fresh core map. - Abstract: The main purpose of this study is to present the results of Core Map (CM) generation calculations for the İstanbul Technical University TRIGA Mark II Research Reactor by using Genetic Algorithms (GA) coupled with a Monte Carlo (MC) based-particle transport code. Optimization problems under consideration are: (i) maximization of the core excess reactivity (ρ{sub ex}) using Single-Objective GA when the burned fuel elements with no fresh fuel elements are used, (ii) maximization of the ρ{sub ex} and minimization of maximum power peaking factor (ppf{sub max}) using Multi-Objective GA when the burned fuels with fresh fuels are used. The results were obtained when all the control rods are fully withdrawn. ρ{sub ex} and ppf{sub max} values of the produced best CMs were provided. Core-averaged neutron spectrum, and variation of neutron fluxes with respect to radial distance were presented for the best CMs. The results show that it is possible to find an optimum CM with an excess reactivity of 1.17 when the burned fuels are used. In the case of a mix of burned fuels and fresh fuels, the best pattern has an excess reactivity of 1.19 with a maximum peaking factor of 1.4843. In addition, when compared with the fresh CM, the thermal fluxes of the generated CMs decrease by about 2% while change in the fast fluxes is about 1%.Classification: J. Core physics.
International Nuclear Information System (INIS)
Krasa, A.; Krizek, F.; Wagner, V.; Kugler, A.; Henzl, V.; Henzlova, D.; Majerle, M.; Adam, J.; Caloun, P.; Bradnova, V.; Chultem, D.; Kalinnikov, V.G.; Krivopustov, M.I.; Solnyshkin, A.A.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.; Tumehndehlgehr, Ts.; Vasil'ev, S.I.
2005-01-01
This paper reports on two experiments performed at the Synchrophasotron/Nuclotron accelerator complex at JINR. Relativistic protons with energies 885 MeV and 1.5 GeV hit a massive cylindrical lead target. The spatial and energetic distributions of the neutron field produced by the spallation reactions were measured by the activation of Al, Au, Bi, Co, and Cu foils placed on the surface of the target and close to it. The yields of the radioactive nuclei produced by threshold reactions in these foils were determined by the analyses of their γ spectra. The comparison with Monte-Carlo based simulations was performed both with the LAHET+MCNP code and the MCNPX code
Krasa, A; Bradnova, V; Caloun, P; Chultem, D; Henzl, V; Henzlová, D; Kalinnikov, V G; Krivopustov, M I; Krízek, F; Kugler, A; Majerle, M; Solnyshkin, A A; Stegailov, V I; Tsoupko-Sitnikov, V M; Tumendelger, T; Vasilev, S I; Wagner, V; Nuclear Physics Institute of Academy of Sciences of Czech Republic, Rez, Czech Republic
2005-01-01
This paper reports on two experiments performed at the Synchrophasotron/Nuclotron accelerator complex at JINR. Relativistic protons with energies 885 MeV and 1.5 GeV hit a massive cylindrical lead target. The spatial and energetic distributions of the neutron field produced by the spallation reactions were measured by the activation of Al, Au, Bi, Co, and Cu foils placed on the surface of the target and close to it. The yields of the radioactive nuclei produced by threshold reactions in these foils were determined by the analyses of their $\\gamma$ spectra. The comparison with Monte-Carlo based simulations was performed both with the LAHET+MCNP code and the MCNPX code.
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)