a New Method for Neutron Capture Therapy (nct) and Related Simulation by MCNP4C Code
NASA Astrophysics Data System (ADS)
Shirazi, Mousavi; Alireza, Seyed; Ali, Taheri
2010-01-01
Neutron capture therapy (NCT) is enumerated as one of the most important methods for treatment of some strong maladies among cancers in medical science thus is unavoidable controlling and protecting instances in use of this science. Among of treatment instances of this maladies with use of nuclear medical science is use of neutron therapy that is one of the most important and effective methods in treatment of cancers. But whereas fast neutrons have too destroyer effects and also sake of protection against additional absorbed energy (absorbed dose) by tissue during neutron therapy and also naught damaging to rest of healthy tissues, should be measured absorbed energy by tissue accurately, because destroyer effects of fast neutrons is almost quintuple more than gamma photons. In this article for neutron therapy act of male's liver has been simulated a system by the Monte Carlo method (MCNP4C code) and also with use of analytical method, thus absorbed dose by this tissue has been obtained for sources with different energies accurately and has been compared results of this two methods together.
Monte carlo simulation of x-ray spectra in diagnostic radiology and mammography using MCNP4C.
Ay, M R; Shahriari, M; Sarkar, S; Adib, M; Zaidi, H
2004-11-01
The general purpose Monte Carlo N-particle radiation transport computer code (MCNP4C) was used for the simulation of x-ray spectra in diagnostic radiology and mammography. The electrons were transported until they slow down and stop in the target. Both bremsstrahlung and characteristic x-ray production were considered in this work. We focus on the simulation of various target/filter combinations to investigate the effect of tube voltage, target material and filter thickness on x-ray spectra in the diagnostic radiology and mammography energy ranges. The simulated x-ray spectra were compared with experimental measurements and spectra calculated by IPEM report number 78. In addition, the anode heel effect and off-axis x-ray spectra were assessed for different anode angles and target materials and the results were compared with EGS4-based Monte Carlo simulations and measured data. Quantitative evaluation of the differences between our Monte Carlo simulated and comparison spectra was performed using student's t-test statistical analysis. Generally, there is a good agreement between the simulated x-ray and comparison spectra, although there are systematic differences between the simulated and reference spectra especially in the K-characteristic x-rays intensity. Nevertheless, no statistically significant differences have been observed between IPEM spectra and the simulated spectra. It has been shown that the difference between MCNP simulated spectra and IPEM spectra in the low energy range is the result of the overestimation of characteristic photons following the normalization procedure. The transmission curves produced by MCNP4C have good agreement with the IPEM report especially for tube voltages of 50 kV and 80 kV. The systematic discrepancy for higher tube voltages is the result of systematic differences between the corresponding spectra. PMID:15584526
NEPHTIS: 2D/3D validation elements using MCNP4c and TRIPOLI4 Monte-Carlo codes
Courau, T.; Girardi, E. [EDF R and D/SINETICS, 1av du General de Gaulle, F92141 Clamart CEDEX (France); Damian, F.; Moiron-Groizard, M. [DEN/DM2S/SERMA/LCA, CEA Saclay, F91191 Gif-sur-Yvette CEDEX (France)
2006-07-01
High Temperature Reactors (HTRs) appear as a promising concept for the next generation of nuclear power applications. The CEA, in collaboration with AREVA-NP and EDF, is developing a core modeling tool dedicated to the prismatic block-type reactor. NEPHTIS (Neutronics Process for HTR Innovating System) is a deterministic codes system based on a standard two-steps Transport-Diffusion approach (APOLLO2/CRONOS2). Validation of such deterministic schemes usually relies on Monte-Carlo (MC) codes used as a reference. However, when dealing with large HTR cores the fission source stabilization is rather poor with MC codes. In spite of this, it is shown in this paper that MC simulations may be used as a reference for a wide range of configurations. The first part of the paper is devoted to 2D and 3D MC calculations of a HTR core with control devices. Comparisons between MCNP4c and TRIPOLI4 MC codes are performed and show very consistent results. Finally, the last part of the paper is devoted to the code to code validation of the NEPHTIS deterministic scheme. (authors)
Development and validation of MCNP4C-based Monte Carlo simulator for fan- and cone-beam x-ray CT
NASA Astrophysics Data System (ADS)
Ay, Mohammad Reza; Zaidi, Habib
2005-10-01
An x-ray computed tomography (CT) simulator based on the Monte Carlo N-particle radiation transport computer code (MCNP4C) was developed for simulation of both fan- and cone-beam CT scanners. A user-friendly interface running under Matlab 6.5.1 creates the scanner geometry at different views as MCNP4C's input file. The full simulation of x-ray tube, phantom and detectors with single-slice, multi-slice and flat detector configurations was considered. The simulator was validated through comparison with experimental measurements of different nonuniform phantoms with varying sizes on both a clinical and a small-animal CT scanner. There is good agreement between the simulated and measured projections and reconstructed images. Thereafter, the effects of bow-tie filter, phantom size and septa length on scatter distribution in fan-beam CT were studied in detail. The relative difference between detected total, primary and scatter photons for septa length varying between 0 and 95 mm is 11.2%, 1.9% and 84.1%, respectively, whereas the scatter-to-primary ratio decreases by 83.8%. The developed simulator is a powerful tool for evaluating the effect of physical, geometrical and other design parameters on scanner performance and image quality in addition to offering a versatile tool for investigating potential artefacts and correction schemes when using CT-based attenuation correction on dual-modality PET/CT units.
Reniers, B; Verhaegen, F; Vynckier, S
2004-04-21
The use of low-energy photon emitters for brachytherapy applications, as in the treatment of the prostate or of eye tumours, has drastically increased in the last few years. New seed models for 103Pd and 125I have recently been introduced. The American Association of Physicists in Medicine recommends that measurements are made to obtain the dose rate constant, the radial dose function and the anisotropy function. These results must then be compared with Monte Carlo calculations to finally obtain the dosimetric parameters in liquid water. We have used the results obtained during the characterization of the new InterSource (furnished by IBt, Seneffe, Belgium) palladium and iodine sources to compare two Monte Carlo codes against experiment for these low energies. The measurements have been performed in three different media: two solid water plastics, WT1 and RW1, and polymethylmetacrylate. The Monte Carlo calculations were made using two different codes: MCNP4C and EGSnrc. These codes use photon cross-section data of a different origin. Differences were observed between both sets of input data below 100 keV, especially for the photoelectric effect. We obtained differences in the radial dose functions calculated with each code, which can be explained by the difference between the input data. New cross-section data were then tested for both codes. The agreement between the calculations using these new libraries is excellent. The differences are within the statistical uncertainties of the calculations. These results were compared with the experimental data. A good agreement is reached for both isotopes and in the three phantoms when the measured values are corrected for the presence of the TLDs in the phantom. PMID:15152693
Calculation of the store house worker dose in a lost wax foundry using MCNP-4C.
Alegría, Natalia; Legarda, Fernando; Herranz, Margarita; Idoeta, Raquel
2005-01-01
Lost wax casting is an industrial process which permits the transmutation into metal of models made in wax. The wax model is covered with a silicaceous shell of the required thickness and once this shell is built the set is heated and wax melted. Liquid metal is then cast into the shell replacing the wax. When the metal is cool, the shell is broken away in order to recover the metallic piece. In this process zircon sands are used for the preparation of the silicaceous shell. These sands have varying concentrations of natural radionuclides: 238U, 232Th and 235U together with their progenics. The zircon sand is distributed in bags of 50 kg, and 30 bags are on a pallet, weighing 1,500 kg. The pallets with the bags have dimensions 80 cm x 120 cm x 80 cm, and constitute the radiation source in this case. The only pathway of exposure to workers in the store house is external radiation. In this case there is no dust because the bags are closed and covered by plastic, the store house has a good ventilation rate and so radon accumulation is not possible. The workers do not touch with their hands the bags and consequently skin contamination will not take place. In this study all situations of external irradiation to the workers have been considered; transportation of the pallets from vehicle to store house, lifting the pallets to the shelf, resting of the stock on the shelf, getting down the pallets, and carrying the pallets to production area. Using MCNP-4C exposure situations have been simulated, considering that the source has a homogeneous composition, the minimum stock in the store house is constituted by 7 pallets, and the several distances between pallets and workers when they are at work. The photons flux obtained by MCNP-4C is multiplied by the conversion factor of Flux to Kerma for air by conversion factor to Effective Dose by Kerma unit, and by the number of emitted photons. Those conversion factors are obtained of ICRP 74 table 1 and table 17 respectively. This is the way to obtain a function giving dose rate around the source. PMID:16604600
NASA Astrophysics Data System (ADS)
Zamani, M.; Kasesaz, Y.; Khalafi, H.; Pooya, S. M. Hosseini
Boron Neutron Capture Therapy (BNCT) is used for treatment of many diseases, including brain tumors, in many medical centers. In this method, a target area (e.g., head of patient) is irradiated by some optimized and suitable neutron fields such as research nuclear reactors. Aiming at protection of healthy tissues which are located in the vicinity of irradiated tissue, and based on the ALARA principle, it is required to prevent unnecessary exposure of these vital organs. In this study, by using numerical simulation method (MCNP4C Code), the absorbed dose in target tissue and the equiavalent dose in different sensitive tissues of a patiant treated by BNCT, are calculated. For this purpose, we have used the parameters of MIRD Standard Phantom. Equiavelent dose in 11 sensitive organs, located in the vicinity of target, and total equivalent dose in whole body, have been calculated. The results show that the absorbed dose in tumor and normal tissue of brain equal to 30.35?Gy and 0.19?Gy, respectively. Also, total equivalent dose in 11 sensitive organs, other than tumor and normal tissue of brain, is equal to 14?mGy. The maximum equivalent doses in organs, other than brain and tumor, appear to the tissues of lungs and thyroid and are equal to 7.35?mSv and 3.00?mSv, respectively.
SECOND-ORDER CROSS TERMS IN MONTE CARLO DIFFERENTIAL OPERATOR PERTURBATION ESTIMATES
J. A. FAVORITE; D. K. PARSONS
2001-01-01
Given some initial, unperturbed problem and a desired perturbation, a second-order accurate Taylor series perturbation estimate for a Monte Carlo tally that is a function of two or more perturbed variables can be obtained using an implementation of the differential operator method that ignores cross terms, such as in MCNP4C{trademark}. This requires running a base case defined to be halfway
Determination of {beta}{sub eff} using MCNP-4C2 and application to the CROCUS and PROTEUS reactors
Vollaire, J. [European Organization for Nuclear Research CERN, CH-1211 Geneve 23 (Switzerland); Plaschy, M.; Jatuff, F. [Paul Scherrer Institut PSI, CH-5232 Villigen PSI (Switzerland); Chawla, R. [Paul Scherrer Institut PSI, CH-5232 Villigen PSI (Switzerland); Ecole Polytechnique Federale de Lausanne EPFL, CH-1015 Lausanne (Switzerland)
2006-07-01
A new Monte Carlo method for the determination of {beta}{sub eff} has been recently developed and tested using appropriate models of the experimental reactors CROCUS and PROTEUS. The current paper describes the applied methodology and highlights the resulting improvements compared to the simplest MCNP approach, i.e. the 'prompt method' technique. In addition, the flexibility advantages of the developed method are presented. Specifically, the possibility to obtain the effective delayed neutron fraction {beta}{sub eff} per delayed neutron group, per fissioning nuclide and per reactor region is illustrated. Finally, the MCNP predictions of {beta}{sub eff} are compared to the results of deterministic calculations. (authors)
Dawahra, S; Khattab, K; Saba, G
2015-10-01
A comparative study for fuel conversion from the HEU to LEU in the Miniature Neutron Source Reactor (MNSR) has been performed in this paper using the MCNP4C code. The neutron energy and lethargy flux spectra in the first inner and outer irradiation sites of the MNSR reactor for the existing HEU fuel (UAl4-Al, 90% enriched) and the potential LEU fuels (U3Si2-Al, U3Si-Al, U9Mo-Al, 19.75% enriched and UO2, 12.6% enriched) were investigated using the MCNP4C code. The neutron energy flux spectra for each group was calculated by dividing the neutron flux by the width of each energy group. The neutron flux spectra per unit lethargy was calculated by multiplying the neutron energy flux spectra for each energy group by the average energy of each group. The thermal neutron flux was calculated by summing the neutron fluxes from 0.0 to 0.625eV, the fast neutron flux was calculated by summing the neutron fluxes from 0.5MeV to 10MeV for the existing HEU and potential LEU fuels. Good agreements have been noticed between the flux spectra for the potential LEU fuels and the existing HEU fuels with maximum relative differences less than 10% and 8% in the inner and outer irradiation sites. PMID:26142805
Bagheri, Reza; Afarideh, Hossein; Maragheh, Mohammad Ghannadi; Shirmardi, Seyed Pezhman; Samani, Ali Bahrami
2015-05-01
Bone metastases are major clinical concern that can cause severe problems for patients. Currently, various beta emitters are used for bone pain palliation. This study, describes the process for absorbed dose prediction of selected bone surface and volume-seeking beta emitter radiopharmaceuticals such as (32)P, (89)SrCl2,(90)Y-EDTMP,(153)Sm-EDTMP, (166)Ho-DOTMP, (177)Lu-EDTMP,(186)Re-HEDP, and (188)Re-HEDP in human bone, using MCNP code. Three coaxial sub-cylinders 5?cm in height and 1.2, 2.6, and 7.6?cm in diameter were used for bone marrow, bone, and muscle simulation respectively. The *F8 tally was employed to calculate absorbed dose in the MCNP4C simulations. Results show that with injection of 1?MBq of these radiopharmaceuticals given to a 70?kg adult man, (32)P, (89)SrCl2, and (90)Y-EDTMP radiopharmaceuticals will have the highest amount of bone surface absorbed dose, where beta particles will have the greatest proportion in absorbed dose of bone surface in comparison with gamma radiation. These results demonstrate moderate agreement with available experimental data. PMID:25775234
Markov Chain Monte Carlo Methods Markov Chain Monte Carlo Methods
Robert, Christian P.
Markov Chain Monte Carlo Methods Markov Chain Monte Carlo Methods Christian P. Robert Universit´e Paris-Dauphine, IuF, & CRESt http://www.ceremade.dauphine.fr/~xian October 16, 2013 #12;Markov Chain 2011] #12;Markov Chain Monte Carlo Methods Outline Motivations, Random Variable Generation Chapters 1
Markov Chain Monte Carlo Methods Markov Chain Monte Carlo Methods
Robert, Christian P.
Markov Chain Monte Carlo Methods Markov Chain Monte Carlo Methods Christian P. Robert Universit´e Paris Dauphine and CREST-INSEE http://www.ceremade.dauphine.fr/~xian 3-6 Mayo 2005 #12;Markov Chain Integration Notions on Markov Chains The Metropolis-Hastings Algorithm The Gibbs Sampler MCMC tools
1 Simulation Monte Carlo methods
Verschelde, Jan
Outline 1 Simulation Monte Carlo methods random numbers 2 Repeat Until binary expansion break Intro to Computer Science (MCS 260) running simulations L-12 9 February 2015 1 / 30 #12;Simulation Monte. Simulation consists in the repeated drawing of samples according to a probability distribution. We count
Semistochastic Projector Monte Carlo Method
NASA Astrophysics Data System (ADS)
Petruzielo, F. R.; Holmes, A. A.; Changlani, Hitesh J.; Nightingale, M. P.; Umrigar, C. J.
2012-12-01
We introduce a semistochastic implementation of the power method to compute, for very large matrices, the dominant eigenvalue and expectation values involving the corresponding eigenvector. The method is semistochastic in that the matrix multiplication is partially implemented numerically exactly and partially stochastically with respect to expectation values only. Compared to a fully stochastic method, the semistochastic approach significantly reduces the computational time required to obtain the eigenvalue to a specified statistical uncertainty. This is demonstrated by the application of the semistochastic quantum Monte Carlo method to systems with a sign problem: the fermion Hubbard model and the carbon dimer.
Zimmerman, G.B.
1997-06-24
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ion 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 burns nd 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.
Optimizing Efficiency of Perturbative Monte Carlo Method
Truong, Thanh N.
-- --Method TOM J. EVANS, THANH N. TRUONG 1998 ABSTRACT: We introduce error weighting functions into the perturbative Monte Carlo method for use andror MM regions. 1998 John Wiley & Sons, Inc. J Comput Chem 19: 1632 1638, 1998 Keywords: Monte Carlo
NASA Astrophysics Data System (ADS)
Pauzi, A. M.
2013-06-01
The neutron transport code, Monte Carlo N-Particle (MCNP) which was wellkown as the gold standard in predicting nuclear reaction was used to model the small nuclear reactor core called "U-batteryTM", which was develop by the University of Manchester and Delft Institute of Technology. The paper introduces on the concept of modeling the small reactor core, a high temperature reactor (HTR) type with small coated TRISO fuel particle in graphite matrix using the MCNPv4C software. The criticality of the core were calculated using the software and analysed by changing key parameters such coolant type, fuel type and enrichment levels, cladding materials, and control rod type. The criticality results from the simulation were validated using the SCALE 5.1 software by [1] M Ding and J L Kloosterman, 2010. The data produced from these analyses would be used as part of the process of proposing initial core layout and a provisional list of materials for newly design reactor core. In the future, the criticality study would be continued with different core configurations and geometries.
Monte Carlo methods on advanced computer architectures
Martin, W.R. [Univ. of Michigan, Ann Arbor, MI (United States)
1991-12-31
Monte Carlo methods describe a wide class of computational methods that utilize random numbers to perform a statistical simulation of a physical problem, which itself need not be a stochastic process. For example, Monte Carlo can be used to evaluate definite integrals, which are not stochastic processes, or may be used to simulate the transport of electrons in a space vehicle, which is a stochastic process. The name Monte Carlo came about during the Manhattan Project to describe the new mathematical methods being developed which had some similarity to the games of chance played in the casinos of Monte Carlo. Particle transport Monte Carlo is just one application of Monte Carlo methods, and will be the subject of this review paper. Other applications of Monte Carlo, such as reliability studies, classical queueing theory, molecular structure, the study of phase transitions, or quantum chromodynamics calculations for basic research in particle physics, are not included in this review. The reference by Kalos is an introduction to general Monte Carlo methods and references to other applications of Monte Carlo can be found in this excellent book. For the remainder of this paper, the term Monte Carlo will be synonymous to particle transport Monte Carlo, unless otherwise noted. 60 refs., 14 figs., 4 tabs.
Quantum speedup of Monte Carlo methods
Ashley Montanaro
2015-07-29
Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomised or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.
Exploring Probability and the Monte Carlo Method
NSDL National Science Digital Library
2012-08-02
This multimedia mathematics resource examines probability. A video illustrates how math is used to evaluate the danger of avalanches in the mountains of Alberta. An interactive component allows students to compare theoretical and experimental probabilities, as well as explore the Monte Carlo method. A probability print activity is also included.
An enhanced Monte Carlo outlier detection method.
Zhang, Liangxiao; Li, Peiwu; Mao, Jin; Ma, Fei; Ding, Xiaoxia; Zhang, Qi
2015-09-30
Outlier detection is crucial in building a highly predictive model. In this study, we proposed an enhanced Monte Carlo outlier detection method by establishing cross-prediction models based on determinate normal samples and analyzing the distribution of prediction errors individually for dubious samples. One simulated and three real datasets were used to illustrate and validate the performance of our method, and the results indicated that this method outperformed Monte Carlo outlier detection in outlier diagnosis. After these outliers were removed, the value of validation by Kovats retention indices and the root mean square error of prediction decreased from 3.195 to 1.655, and the average cross-validation prediction error decreased from 2.0341 to 1.2780. This method helps establish a good model by eliminating outliers. © 2015 Wiley Periodicals, Inc. PMID:26226927
Monte Carlo Methods for the Linearized Poisson-Boltzmann Equation
Mascagni, Michael
the LPBE by a Monte Carlo method is to randomize a finite-difference algorithm. When applied to the LPBE algo- rithm, another, related, Monte Carlo algorithm is presented. This modified Monte Carlo method probability. It is then shown that this method is mathematically equivalent to the previous modified WOS
An introduction to Monte Carlo methods
NASA Astrophysics Data System (ADS)
Walter, J.-C.; Barkema, G. T.
2015-01-01
Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform an exact enumeration. The main principles of Monte Carlo simulations are ergodicity and detailed balance. The Ising model is a lattice spin system with nearest neighbor interactions that is appropriate to illustrate different examples of Monte Carlo simulations. It displays a second order phase transition between disordered (high temperature) and ordered (low temperature) phases, leading to different strategies of simulations. The Metropolis algorithm and the Glauber dynamics are efficient at high temperature. Close to the critical temperature, where the spins display long range correlations, cluster algorithms are more efficient. We introduce the rejection free (or continuous time) algorithm and describe in details an interesting alternative representation of the Ising model using graphs instead of spins with the so-called Worm algorithm. We conclude with an important discussion of the dynamical effects such as thermalization and correlation time.
A local superbasin kinetic Monte Carlo method.
Fichthorn, Kristen A; Lin, Yangzheng
2013-04-28
We present a local superbasin kinetic Monte Carlo (LSKMC) method that efficiently treats multiple-time-scale problems in kinetic Monte Carlo (KMC). The method is designed to solve the small-barrier problem created by groups of recurrent free-energy minima connected by low free-energy barriers and separated from the full phase space of the system by high barriers. We propose an algorithm to detect, on the fly, groups of recurrent free-energy minima connected by low free-energy barriers and to consolidate them into "superbasins," which we treat with rate equations and/or absorbing Markov chains. We discuss various issues involved with implementing LSKMC simulations that contain local superbasins and non-superbasin events concurrently. These issues include the time distribution of superbasin escapes and interactions between superbasin and non-superbasin states. The LSKMC method is exact, as it introduces no new approximations into conventional KMC simulations. We demonstrate various aspects of LSKMC in several examples, which indicate that significant increases in computational efficiency can be achieved using this method. PMID:23635108
Density-matrix quantum Monte Carlo method
NASA Astrophysics Data System (ADS)
Blunt, N. S.; Rogers, T. W.; Spencer, J. S.; Foulkes, W. M. C.
2014-06-01
We present a quantum Monte Carlo method capable of sampling the full density matrix of a many-particle system at finite temperature. This allows arbitrary reduced density matrix elements and expectation values of complicated nonlocal observables to be evaluated easily. The method resembles full configuration interaction quantum Monte Carlo but works in the space of many-particle operators instead of the space of many-particle wave functions. One simulation provides the density matrix at all temperatures simultaneously, from T =? to T =0, allowing the temperature dependence of expectation values to be studied. The direct sampling of the density matrix also allows the calculation of some previously inaccessible entanglement measures. We explain the theory underlying the method, describe the algorithm, and introduce an importance-sampling procedure to improve the stochastic efficiency. To demonstrate the potential of our approach, the energy and staggered magnetization of the isotropic antiferromagnetic Heisenberg model on small lattices, the concurrence of one-dimensional spin rings, and the Renyi S2 entanglement entropy of various sublattices of the 6×6 Heisenberg model are calculated. The nature of the sign problem in the method is also investigated.
Improvement of a quantum monte carlo method
NASA Astrophysics Data System (ADS)
Marcu, Mihail; Müller, Jürgen; Schmatzer, Franz-Karl
1986-07-01
Quantum Monte Carlo simulations based on the Trotter formula exp(- ?H)= lim M?? [exp(- gbA/ M)exp(- gbB/ M)] M, H= A+ B, involve extrapolating the finite M results to the M=? limit. New ways to perform this extrapolation are discussed. Data from an older simulation are reanalysed with the new method. For the one-dimensional isotropic ferromagnet our results now agree with other results in the literature. For the one-dimensional isotropic antiferromagnet, the critical exponent of the staggered susceptibility is consistent with 1.
Discrete range clustering using Monte Carlo methods
NASA Technical Reports Server (NTRS)
Chatterji, G. B.; Sridhar, B.
1993-01-01
For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.
Quantum Monte Carlo methods for nuclear physics
Carlson, Joseph A.; Gandolfi, Stefano; Pederiva, Francesco; Pieper, Steven C.; Schiavilla, Rocco; Schmidt, K. E,; Wiringa, Robert B.
2014-10-19
Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-bodymore »interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less
Quantum Monte Carlo methods for nuclear physics
NASA Astrophysics Data System (ADS)
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-07-01
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Calculating Pi Using the Monte Carlo Method
NASA Astrophysics Data System (ADS)
Williamson, Timothy
2013-11-01
During the summer of 2012, I had the opportunity to participate in a research experience for teachers at the center for sustainable energy at Notre Dame University (RET @ cSEND) working with Professor John LoSecco on the problem of using antineutrino detection to accurately determine the fuel makeup and operating power of nuclear reactors. During full power operation, a reactor may produce 1021 antineutrinos per second with approximately 100 per day being detected. While becoming familiar with the design and operation of the detectors, and how total antineutrino flux could be obtained from such a small sample, I read about a simulation program called Monte Carlo. Further investigation led me to the Monte Carlo method page of Wikipedia2 where I saw an example of approximating pi using this simulation. Other examples where this method was applied were typically done with computer simulations2 or purely mathematical.3 It is my belief that this method may be easily related to the students by performing the simple activity of sprinkling rice on an arc drawn in a square. The activity that follows was inspired by those simulations and was used by my AP Physics class last year with very good results.
Quantum Monte Carlo methods for nuclear physics
J. Carlson; S. Gandolfi; F. Pederiva; Steven C. Pieper; R. Schiavilla; K. E. Schmidt; R. B. Wiringa
2015-04-29
Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Methods for Monte Carlo simulations of biomacromolecules
Vitalis, Andreas; Pappu, Rohit V.
2010-01-01
The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies. PMID:20428473
Improved method for implicit Monte Carlo
Brown, F. B. (Forrest B.); Martin, W. R. (William R.)
2001-01-01
The Implicit Monte Carlo (IMC) method has been used for over 30 years to analyze radiative transfer problems, such as those encountered in stellar atmospheres or inertial confinement fusion. Reference [2] provided an exact error analysis of IMC for 0-D problems and demonstrated that IMC can exhibit substantial errors when timesteps are large. These temporal errors are inherent in the method and are in addition to spatial discretization errors and approximations that address nonlinearities (due to variation of physical constants). In Reference [3], IMC and four other methods were analyzed in detail and compared on both theoretical grounds and the accuracy of numerical tests. As discussed in, two alternative schemes for solving the radiative transfer equations, the Carter-Forest (C-F) method and the Ahrens-Larsen (A-L) method, do not exhibit the errors found in IMC; for 0-D, both of these methods are exact for all time, while for 3-D, A-L is exact for all time and C-F is exact within a timestep. These methods can yield substantially superior results to IMC.
Bilinear diffusion quantum Monte Carlo methods
NASA Astrophysics Data System (ADS)
Arias de Saavedra, F.; Kalos, M. H.
2003-02-01
The standard method of quantum Monte Carlo for the solution of the Schrödinger equation in configuration space can be described quite generally as devising a random walk that generates—at least asymptotically—populations of random walkers whose probability density is proportional to the wave function of the system being studied. While, in principle, the energy eigenvalue of the Hamiltonian can be calculated with high accuracy, estimators of operators that do not commute the Hamiltonian cannot. Bilinear quantum Monte Carlo (BQMC) is an alternative in which the square of the wave function is sampled in a somewhat indirect way. More specifically, one uses a pair of walkers at positions x and y and introduces stochastic dynamics to sample ?i(x)t(x,y)?j(y), where ?i(x) and ?j(y) are eigenfunctions of (possibly different) Hamiltonians, and t(x,y) is a kernel that correlates positions x and y. Using different Hamiltonians permits the accurate computation of small energy differences. We review the conceptual basis of BQMC, discuss qualitatively and analytically the problem of the fluctuations in the branching, and present partial solutions to that problem. Finally we exhibit numerical results for some model systems including harmonic oscillators and the hydrogen and helium atoms. Further research will be necessary to make this a practical and generally applicable scheme.
Accelerated Monte Carlo Methods for Coulomb Collisions
NASA Astrophysics Data System (ADS)
Rosin, Mark; Ricketson, Lee; Dimits, Andris; Caflisch, Russel; Cohen, Bruce
2014-03-01
We present a new highly efficient multi-level Monte Carlo (MLMC) simulation algorithm for Coulomb collisions in a plasma. The scheme, initially developed and used successfully for applications in financial mathematics, is applied here to kinetic plasmas for the first time. The method is based on a Langevin treatment of the Landau-Fokker-Planck equation and has a rich history derived from the works of Einstein and Chandrasekhar. The MLMC scheme successfully reduces the computational cost of achieving an RMS error ? in the numerical solution to collisional plasma problems from (?-3) - for the standard state-of-the-art Langevin and binary collision algorithms - to a theoretically optimal (?-2) scaling, when used in conjunction with an underlying Milstein discretization to the Langevin equation. In the test case presented here, the method accelerates simulations by factors of up to 100. We summarize the scheme, present some tricks for improving its efficiency yet further, and discuss the method's range of applicability. Work performed for US DOE by LLNL under contract DE-AC52- 07NA27344 and by UCLA under grant DE-FG02-05ER25710.
SECOND-ORDER CROSS TERMS IN MONTE CARLO DIFFERENTIAL OPERATOR PERTURBATION ESTIMATES
J. A. FAVORITE; D. K. PARSONS
2001-03-01
Given some initial, unperturbed problem and a desired perturbation, a second-order accurate Taylor series perturbation estimate for a Monte Carlo tally that is a function of two or more perturbed variables can be obtained using an implementation of the differential operator method that ignores cross terms, such as in MCNP4C{trademark}. This requires running a base case defined to be halfway between the perturbed and unperturbed states of all of the perturbed variables and doubling the first-order estimate of the effect of perturbing from the ''midpoint'' base case to the desired perturbed case. The difference between such a midpoint perturbation estimate and the standard perturbation estimate (using the endpoints) is a second-order estimate of the sum of the second-order cross terms of the Taylor series expansion. This technique is demonstrated on an analytic fixed-source problem, a Godiva k{sub eff} eigenvalue problem, and a concrete shielding problem. The effect of ignoring the cross terms in all three problems is significant.
MCMs: Early History and The Basics Monte Carlo Methods
Mascagni, Michael
The Problems The People The Technology Monte Carlo Methods The Birth General Concepts of the Monte Carlo Method. The Technology: Massive human computers using hand calculators, the Fermiac, access to early digital computers Simulation of neutron histories (neutronics) 1. Given neutron positions/momenta, geometry 2. Compute flux
Simulated Annealing: A Monte Carlo Method for GPS Surveying
Fidanova, Stefka
Simulated Annealing: A Monte Carlo Method for GPS Surveying Stefka Fidanova IPP -- BAS, Acad. G annealing technique,which is a Monte Carlo method, to analyze and improve the e#ciency of the de sign which can be coupled with the simulated annealing technique. 1 Introduction The GPS is a satellite
Mehranian, A.; Ay, M. R.; Alam, N. Riyahi; Zaidi, H. [Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, P.O. Box 14155-6447, Tehran (Iran, Islamic Republic of) and Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, P.O. Box 14185-615, Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, P.O. Box 14155-6447, Tehran (Iran, Islamic Republic of); Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, P.O. Box 14185-615, Tehran (Iran, Islamic Republic of) and Research Institute for Nuclear Medicine, Tehran University of Medical Sciences, P.O. Box 14155-6447, Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, P.O. Box 14155-6447, Tehran (Iran, Islamic Republic of); Division of Nuclear Medicine, Geneva University Hospital, CH-1211 Geneva (Switzerland) and Geneva Neuroscience Center, Geneva University, CH-1205 Geneva (Switzerland)
2010-02-15
Purpose: The accurate prediction of x-ray spectra under typical conditions encountered in clinical x-ray examination procedures and the assessment of factors influencing them has been a long-standing goal of the diagnostic radiology and medical physics communities. In this work, the influence of anode surface roughness on diagnostic x-ray spectra is evaluated using MCNP4C-based Monte Carlo simulations. Methods: An image-based modeling method was used to create realistic models from surface-cracked anodes. An in-house computer program was written to model the geometric pattern of cracks and irregularities from digital images of focal track surface in order to define the modeled anodes into MCNP input file. To consider average roughness and mean crack depth into the models, the surface of anodes was characterized by scanning electron microscopy and surface profilometry. It was found that the average roughness (R{sub a}) in the most aged tube studied is about 50 {mu}m. The correctness of MCNP4C in simulating diagnostic x-ray spectra was thoroughly verified by calling its Gaussian energy broadening card and comparing the simulated spectra with experimentally measured ones. The assessment of anode roughness involved the comparison of simulated spectra in deteriorated anodes with those simulated in perfectly plain anodes considered as reference. From these comparisons, the variations in output intensity, half value layer (HVL), heel effect, and patient dose were studied. Results: An intensity loss of 4.5% and 16.8% was predicted for anodes aged by 5 and 50 {mu}m deep cracks (50 kVp, 6 deg. target angle, and 2.5 mm Al total filtration). The variations in HVL were not significant as the spectra were not hardened by more than 2.5%; however, the trend for this variation was to increase with roughness. By deploying several point detector tallies along the anode-cathode direction and averaging exposure over them, it was found that for a 6 deg. anode, roughened by 50 {mu}m deep cracks, the reduction in exposure is 14.9% and 13.1% for 70 and 120 kVp tube voltages, respectively. For the evaluation of patient dose, entrance skin radiation dose was calculated for typical chest x-ray examinations. It was shown that as anode roughness increases, patient entrance skin dose decreases averagely by a factor of 15%. Conclusions: It was concluded that the anode surface roughness can have a non-negligible effect on output spectra in aged x-ray imaging tubes and its impact should be carefully considered in diagnostic x-ray imaging modalities.
COMPARISON OF MONTE CARLO METHODS FOR NONLINEAR RADIATION TRANSPORT
W. R. MARTIN; F. B. BROWN
2001-03-01
Five Monte Carlo methods for solving the nonlinear thermal radiation transport equations are compared. The methods include the well-known Implicit Monte Carlo method (IMC) developed by Fleck and Cummings, an alternative to IMC developed by Carter and Forest, an ''exact'' method recently developed by Ahrens and Larsen, and two methods recently proposed by Martin and Brown. The five Monte Carlo methods are developed and applied to the radiation transport equation in a medium assuming local thermodynamic equilibrium. Conservation of energy is derived and used to define appropriate material energy update equations for each of the methods. Details of the Monte Carlo implementation are presented, both for the random walk simulation and the material energy update. Simulation results for all five methods are obtained for two infinite medium test problems and a 1-D test problem, all of which have analytical solutions. Conclusions regarding the relative merits of the various schemes are presented.
A Particle Population Control Method for Dynamic Monte Carlo
NASA Astrophysics Data System (ADS)
Sweezy, Jeremy; Nolen, Steve; Adams, Terry; Zukaitis, Anthony
2014-06-01
A general particle population control method has been derived from splitting and Russian Roulette for dynamic Monte Carlo particle transport. A well-known particle population control method, known as the particle population comb, has been shown to be a special case of this general method. This general method has been incorporated in Los Alamos National Laboratory's Monte Carlo Application Toolkit (MCATK) and examples of it's use are shown for both super-critical and sub-critical systems.
Vectorized Monte Carlo methods for reactor lattice analysis
Brown, F.B.
1984-03-01
Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-energy Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.
Vectorized Monte Carlo methods for reactor lattice analysis
Brown, F.B.
1982-11-01
This report details some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-energy Monte Carlo code for use on the CYBER-205 computer. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. for background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.
Moradi, Farhad; Mahdavi, Seyed Rabi; Mostaar, Ahmad; Motamedi, Mohsen
2012-01-01
In this study the commissioning of a dose calculation algorithm in a currently used treatment planning system was performed and the calculation accuracy of two available methods in the treatment planning system i.e., collapsed cone convolution (CCC) and equivalent tissue air ratio (ETAR) was verified in tissue heterogeneities. For this purpose an inhomogeneous phantom (IMRT thorax phantom) was used and dose curves obtained by the TPS (treatment planning system) were compared with experimental measurements and Monte Carlo (MCNP code) simulation. Dose measurements were performed by using EDR2 radiographic films within the phantom. Dose difference (DD) between experimental results and two calculation methods was obtained. Results indicate maximum difference of 12% in the lung and 3% in the bone tissue of the phantom between two methods and the CCC algorithm shows more accurate depth dose curves in tissue heterogeneities. Simulation results show the accurate dose estimation by MCNP4C in soft tissue region of the phantom and also better results than ETAR method in bone and lung tissues. PMID:22973081
The Monte Carlo method improves physician practice valuation.
Grayson, James M; Rutsohn, Phil; Jackson, Pamela Z
2006-01-01
This article demonstrates the use of the Monte Carlo simulation method in physician practice valuation. The Monte Carlo method allows the valuator to incorporate probability ranges into the discounted cash flow model and obtain an output indicating the probability for specified ranges of practice valuation. Given the high level of uncertainty in projected cash flows associated with physician practices, the value of this kind of information in a practice valuation decision would quite obviously be superior to any single point estimate generated by a traditional discounted cash flow model. It is postulated that virtually all hospitals support an information system that can easily accommodate a Monte Carlo simulation. PMID:16906001
Monte Carlo methods and applications in nuclear physics
Carlson, J.
1990-01-01
Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs.
Methods for calculating forces within quantum Monte Carlo simulations.
Badinski, A; Haynes, P D; Trail, J R; Needs, R J
2010-02-24
Atomic force calculations within the variational and diffusion quantum Monte Carlo methods are described. The advantages of calculating diffusion quantum Monte Carlo forces with the 'pure' rather than the 'mixed' probability distribution are discussed. An accurate and practical method for calculating forces using the pure distribution is presented and tested for the SiH molecule. The statistics of force estimators are explored and violations of the central limit theorem are found in some cases. PMID:21386380
An improved method for treating Monte Carlo-diffusion interfaces
Densmore, J. D. (Jeffery D.)
2004-01-01
Discrete Diffusion Monte Carlo (DDMC) has been suggested as a technique for increasing the efficiency of Monte Carlo simulations in diffusive media. In this technique, Monte Carlo particles travel discrete steps between spatial cells according to a discretized diffusion equation. An important part of the DDMC method is the treatment of the interface between a transport region, where standard Monte Carlo is used, and a diffusive region, where DDMC is employed. Previously developed DDMC methods use the Marshak boundary condition at transport diffusion-interfaces, and thus produce incorrect results if the Monte Carlo-calculated angular flux incident on the interface surface is anisotropic. In this summary we present a new interface method based on the asymptotic diffusion-limit boundary condition, which is able to produce accurate solutions if the incident angular flux is anisotropic. We show that this new interface technique has a simple Monte Carlo interpretation, and can be used in conjunction with the existing DDMC method. With a set of numerical simulations, we demonstrate that this asymptotic interface method is much more accurate than the previously developed Marshak interface method.
Perturbation Monte Carlo methods for tissue structure alterations.
Nguyen, Jennifer; Hayakawa, Carole K; Mourant, Judith R; Spanier, Jerome
2013-01-01
This paper describes an extension of the perturbation Monte Carlo method to model light transport when the phase function is arbitrarily perturbed. Current perturbation Monte Carlo methods allow perturbation of both the scattering and absorption coefficients, however, the phase function can not be varied. The more complex method we develop and test here is not limited in this way. We derive a rigorous perturbation Monte Carlo extension that can be applied to a large family of important biomedical light transport problems and demonstrate its greater computational efficiency compared with using conventional Monte Carlo simulations to produce forward transport problem solutions. The gains of the perturbation method occur because only a single baseline Monte Carlo simulation is needed to obtain forward solutions to other closely related problems whose input is described by perturbing one or more parameters from the input of the baseline problem. The new perturbation Monte Carlo methods are tested using tissue light scattering parameters relevant to epithelia where many tumors originate. The tissue model has parameters for the number density and average size of three classes of scatterers; whole nuclei, organelles such as lysosomes and mitochondria, and small particles such as ribosomes or large protein complexes. When these parameters or the wavelength is varied the scattering coefficient and the phase function vary. Perturbation calculations give accurate results over variations of ?15-25% of the scattering parameters. PMID:24156056
Krylov-Projected Quantum Monte Carlo Method
NASA Astrophysics Data System (ADS)
Blunt, N. S.; Alavi, Ali; Booth, George H.
2015-07-01
We present an approach to the calculation of arbitrary spectral, thermal, and excited state properties within the full configuration interaction quzantum Monte Carlo framework. This is achieved via an unbiased projection of the Hamiltonian eigenvalue problem into a space of stochastically sampled Krylov vectors, thus, enabling the calculation of real-frequency spectral and thermal properties and avoiding explicit analytic continuation. We use this approach to calculate temperature-dependent properties and one- and two-body spectral functions for various Hubbard models, as well as isolated excited states in ab initio systems.
A hybrid Monte Carlo and response matrix Monte Carlo method in criticality calculation
Li, Z.; Wang, K.
2012-07-01
Full core calculations are very useful and important in reactor physics analysis, especially in computing the full core power distributions, optimizing the refueling strategies and analyzing the depletion of fuels. To reduce the computing time and accelerate the convergence, a method named Response Matrix Monte Carlo (RMMC) method based on analog Monte Carlo simulation was used to calculate the fixed source neutron transport problems in repeated structures. To make more accurate calculations, we put forward the RMMC method based on non-analog Monte Carlo simulation and investigate the way to use RMMC method in criticality calculations. Then a new hybrid RMMC and MC (RMMC+MC) method is put forward to solve the criticality problems with combined repeated and flexible geometries. This new RMMC+MC method, having the advantages of both MC method and RMMC method, can not only increase the efficiency of calculations, also simulate more complex geometries rather than repeated structures. Several 1-D numerical problems are constructed to test the new RMMC and RMMC+MC method. The results show that RMMC method and RMMC+MC method can efficiently reduce the computing time and variations in the calculations. Finally, the future research directions are mentioned and discussed at the end of this paper to make RMMC method and RMMC+MC method more powerful. (authors)
Study of the Transition Flow Regime using Monte Carlo Methods
NASA Technical Reports Server (NTRS)
Hassan, H. A.
1999-01-01
This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.
Successful combination of the stochastic linearization and Monte Carlo methods
NASA Technical Reports Server (NTRS)
Elishakoff, I.; Colombi, P.
1993-01-01
A combination of a stochastic linearization and Monte Carlo techniques is presented for the first time in literature. A system with separable nonlinear damping and nonlinear restoring force is considered. The proposed combination of the energy-wise linearization with the Monte Carlo method yields an error under 5 percent, which corresponds to the error reduction associated with the conventional stochastic linearization by a factor of 4.6.
Mosleh-Shirazi, M A; Hadad, K; Faghihi, R; Baradaran-Ghahfarokhi, M; Naghshnezhad, Z; Meigooni, A S
2012-08-01
This study primarily aimed to obtain the dosimetric characteristics of the Model 6733 (125)I seed (EchoSeed) with improved precision and accuracy using a more up-to-date Monte-Carlo code and data (MCNP5) compared to previously published results, including an uncertainty analysis. Its secondary aim was to compare the results obtained using the MCNP5, MCNP4c2, and PTRAN codes for simulation of this low-energy photon-emitting source. The EchoSeed geometry and chemical compositions together with a published (125)I spectrum were used to perform dosimetric characterization of this source as per the updated AAPM TG-43 protocol. These simulations were performed in liquid water material in order to obtain the clinically applicable dosimetric parameters for this source model. Dose rate constants in liquid water, derived from MCNP4c2 and MCNP5 simulations, were found to be 0.993 cGyh(-1)?U(-1) (±1.73%) and 0.965 cGyh(-1)?U(-1) (±1.68%), respectively. Overall, the MCNP5 derived radial dose and 2D anisotropy functions results were generally closer to the measured data (within ±4%) than MCNP4c and the published data for PTRAN code (Version 7.43), while the opposite was seen for dose rate constant. The generally improved MCNP5 Monte Carlo simulation may be attributed to a more recent and accurate cross-section library. However, some of the data points in the results obtained from the above-mentioned Monte Carlo codes showed no statistically significant differences. Derived dosimetric characteristics in liquid water are provided for clinical applications of this source model. PMID:22894389
Mosleh-Shirazi, M. A.; Hadad, K.; Faghihi, R.; Baradaran-Ghahfarokhi, M.; Naghshnezhad, Z.; Meigooni, A. S.
2012-08-15
This study primarily aimed to obtain the dosimetric characteristics of the Model 6733 {sup 125}I seed (EchoSeed) with improved precision and accuracy using a more up-to-date Monte-Carlo code and data (MCNP5) compared to previously published results, including an uncertainty analysis. Its secondary aim was to compare the results obtained using the MCNP5, MCNP4c2, and PTRAN codes for simulation of this low-energy photon-emitting source. The EchoSeed geometry and chemical compositions together with a published {sup 125}I spectrum were used to perform dosimetric characterization of this source as per the updated AAPM TG-43 protocol. These simulations were performed in liquid water material in order to obtain the clinically applicable dosimetric parameters for this source model. Dose rate constants in liquid water, derived from MCNP4c2 and MCNP5 simulations, were found to be 0.993 cGyh{sup -1} U{sup -1} ({+-}1.73%) and 0.965 cGyh{sup -1} U{sup -1} ({+-}1.68%), respectively. Overall, the MCNP5 derived radial dose and 2D anisotropy functions results were generally closer to the measured data (within {+-}4%) than MCNP4c and the published data for PTRAN code (Version 7.43), while the opposite was seen for dose rate constant. The generally improved MCNP5 Monte Carlo simulation may be attributed to a more recent and accurate cross-section library. However, some of the data points in the results obtained from the above-mentioned Monte Carlo codes showed no statistically significant differences. Derived dosimetric characteristics in liquid water are provided for clinical applications of this source model.
Quasicontinuum Monte Carlo: A method for surface growth simulations
G. Russo; L. M. Sander; P. Smereka
2004-01-01
We introduce an algorithm for treating growth on surfaces which combines important features of continuum methods (such as the level-set method) and kinetic Monte Carlo (KMC) simulations. We treat the motion of adatoms in continuum theory, but attach them to islands one atom at a time. The technique is borrowed from the dielectric breakdown model. Our method allows us to
A Monte Carlo method for combined segregation and linkage analysis
Guo, S.W. (Univ. of Michigan, Ann Arbor, MI (United States)); Thompson, E.A. (Univ. of Washington, Seattle, WA (United States))
1992-11-01
The authors introduce a Monte Carlo approach to combined segregation and linkage analysis of a quantitative trait observed in an extended pedigree. In conjunction with the Monte Carlo method of likelihood-ratio evaluation proposed by Thompson and Guo, the method provides for estimation and hypothesis testing. The greatest attraction of this approach is its ability to handle complex genetic models and large pedigrees. Two examples illustrate the practicality of the method. One is of simulated data on a large pedigree; the other is a reanalysis of published data previously analyzed by other methods. 40 refs, 5 figs., 5 tabs.
Monte Carlo Methods for Tempo Tracking and Rhythm Quantization
Cemgil, A T; 10.1613/jair.1121
2011-01-01
We present a probabilistic generative model for timing deviations in expressive music performance. The structure of the proposed model is equivalent to a switching state space model. The switch variables correspond to discrete note locations as in a musical score. The continuous hidden variables denote the tempo. We formulate two well known music recognition problems, namely tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. Exact computation of posterior features such as the MAP state is intractable in this model class, so we introduce Monte Carlo methods for integration and optimization. We compare Markov Chain Monte Carlo (MCMC) methods (such as Gibbs sampling, simulated annealing and iterative improvement) and sequential Monte Carlo methods (particle filters). Our simulation results suggest better results with sequential methods. The methods can be applied in both online and batch scenarios such as tempo tracking and transcr...
The Monte Carlo method in quantum field theory
Colin Morningstar
2007-02-20
This series of six lectures is an introduction to using the Monte Carlo method to carry out nonperturbative studies in quantum field theories. Path integrals in quantum field theory are reviewed, and their evaluation by the Monte Carlo method with Markov-chain based importance sampling is presented. Properties of Markov chains are discussed in detail and several proofs are presented, culminating in the fundamental limit theorem for irreducible Markov chains. The example of a real scalar field theory is used to illustrate the Metropolis-Hastings method and to demonstrate the effectiveness of an action-preserving (microcanonical) local updating algorithm in reducing autocorrelations. The goal of these lectures is to provide the beginner with the basic skills needed to start carrying out Monte Carlo studies in quantum field theories, as well as to present the underlying theoretical foundations of the method.
Zeinali-Rafsanjani, B; Mosleh-Shirazi, M A; Faghihi, R; Karbasi, S; Mosalaei, A
2015-01-01
To accurately recompute dose distributions in chest-wall radiotherapy with 120 kVp kilovoltage X-rays, an MCNP4C Monte Carlo model is presented using a fast method that obviates the need to fully model the tube components. To validate the model, half-value layer (HVL), percentage depth doses (PDDs) and beam profiles were measured. Dose measurements were performed for a more complex situation using thermoluminescence dosimeters (TLDs) placed within a Rando phantom. The measured and computed first and second HVLs were 3.8, 10.3 mm Al and 3.8, 10.6 mm Al, respectively. The differences between measured and calculated PDDs and beam profiles in water were within 2 mm/2% for all data points. In the Rando phantom, differences for majority of data points were within 2%. The proposed model offered an approximately 9500-fold reduced run time compared to the conventional full simulation. The acceptable agreement, based on international criteria, between the simulations and the measurements validates the accuracy of the model for its use in treatment planning and radiobiological modeling studies of superficial therapies including chest-wall irradiation using kilovoltage beam. PMID:26170553
Quasi-Newton Methods for Markov Chain Monte Carlo
Kaski, Samuel
Quasi-Newton Methods for Markov Chain Monte Carlo Yichuan Zhang and Charles Sutton School or infeasible. In this paper we propose MCMC samplers that make use of quasi- Newton approximations, which not valid. We address this problem by using limited memory quasi-Newton methods, which depend only
Heermann, Dieter W.
Contents 1. Stochastic Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 #12;#12;1. Stochastic Methods This chapter is concerned with methods which use stochastic elements. However, there are also inherently stochastic methods, such as the Monte-Carlo technique. An application
Multiple-time-stepping generalized hybrid Monte Carlo methods
NASA Astrophysics Data System (ADS)
Escribano, Bruno; Akhmatskaya, Elena; Reich, Sebastian; Azpiroz, Jon M.
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2-4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Multiple-time-stepping generalized hybrid Monte Carlo methods
Escribano, Bruno; Akhmatskaya, Elena; Reich, Sebastian; Azpiroz, Jon M.
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Introduction to the variational and diffusion Monte Carlo methods
Toulouse, Julien; Umrigar, C J
2015-01-01
We provide a pedagogical introduction to the two main variants of real-space quantum Monte Carlo methods for electronic-structure calculations: variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC). Assuming no prior knowledge on the subject, we review in depth the Metropolis-Hastings algorithm used in VMC for sampling the square of an approximate wave function, discussing details important for applications to electronic systems. We also review in detail the more sophisticated DMC algorithm within the fixed-node approximation, introduced to avoid the infamous Fermionic sign problem, which allows one to sample a more accurate approximation to the ground-state wave function. Throughout this review, we discuss the statistical methods used for evaluating expectation values and statistical uncertainties. In particular, we show how to estimate nonlinear functions of expectation values and their statistical uncertainties.
A Hybrid Monte Carlo Method for Surface Growth Simulations
G. Russo; P. Smereka
2003-01-01
We introduce an algorithm for treating growth on surfaces which combines\\u000aimportant features of continuum methods (such as the level-set method) and\\u000aKinetic Monte Carlo (KMC) simulations. We treat the motion of adatoms in\\u000acontinuum theory, but attach them to islands one atom at a time. The technique\\u000ais borrowed from the Dielectric Breakdown Model. Our method allows us to
Monte Carlo method for magnetic impurities in metals
NASA Technical Reports Server (NTRS)
Hirsch, J. E.; Fye, R. M.
1986-01-01
The paper discusses a Monte Carlo algorithm to study properties of dilute magnetic alloys; the method can treat a small number of magnetic impurities interacting wiith the conduction electrons in a metal. Results for the susceptibility of a single Anderson impurity in the symmetric case show the expected universal behavior at low temperatures. Some results for two Anderson impurities are also discussed.
Monte Carlo method of solving heat conduction problems
S. K. Fraley; T. J. Hoffman; P. N. Stevens
1977-01-01
An innovative approach in the use of Monte Carlo to solve heat conduction problems was developed using a transport equation approximation to the heat conduction equation. The method was shown to be applicable to the solution of multimedia problems in complex geometries with no inherent limitations as to the geometric complexity of problems which can be solved. Nuclear radiation transport
Cool Walking: A New Markov Chain Monte Carlo Sampling Method
Head-Gordon, Teresa L.
Cool Walking: A New Markov Chain Monte Carlo Sampling Method SCOTT BROWN, TERESA HEAD for overcoming quasi-ergodicity problems such as Jump Walking (J-Walking), Smart Walking (S-Walking), Smart Darting, and Parallel Tempering. We present an alternative to these approaches that we call Cool Walking
On the Gap-Tooth direct simulation Monte Carlo method
Armour, Jessica D
2012-01-01
This thesis develops and evaluates Gap-tooth DSMC (GT-DSMC), a direct Monte Carlo simulation procedure for dilute gases combined with the Gap-tooth method of Gear, Li, and Kevrekidis. The latter was proposed as a means of ...
A multilayer Monte Carlo method with free phase function choice
NASA Astrophysics Data System (ADS)
Watté, R.; Aernouts, B.; Saeys, W.
2012-06-01
This paper presents an adaptation of the widely accepted Monte Carlo method for Multi-layered media (MCML). Its original Henyey-Greenstein phase function is an interesting approach for describing how light scattering inside biological tissues occurs. It has the important advantage of generating deflection angles in an efficient - and therefore computationally fast- manner. However, in order to allow the fast generation of the phase function, the MCML code generates a distribution for the cosine of the deflection angle instead of generating a distribution for the deflection angle, causing a bias in the phase function. Moreover, other, more elaborate phase functions are not available in the MCML code. To overcome these limitations of MCML, it was adapted to allow the use of any discretized phase function. An additional tool allows generating a numerical approximation for the phase function for every layer. This could either be a discretized version of (1) the Henyey-Greenstein phase function, (2) a modified Henyey-Greenstein phase function or (3) a phase function generated from the Mie theory. These discretized phase functions are then stored in a look-up table, which can be used by the adapted Monte Carlo code. The Monte Carlo code with flexible phase function choice (fpf-MC) was compared and validated with the original MCML code. The novelty of the developed program is the generation of a user-friendly algorithm, which allows several types of phase functions to be generated and applied into a Monte Carlo method, without compromising the computational performance.
A separable shadow Hamiltonian hybrid Monte Carlo method
NASA Astrophysics Data System (ADS)
Sweet, Christopher R.; Hampton, Scott S.; Skeel, Robert D.; Izaguirre, Jesús A.
2009-11-01
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).
A separable shadow Hamiltonian hybrid Monte Carlo method
Sweet, Christopher R.; Hampton, Scott S.; Skeel, Robert D.; Izaguirre, Jesús A.
2009-01-01
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC’s performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog?Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http:??mdlab.sourceforge.net?s2hmc). PMID:19894997
Monte Carlo N-particle simulation of neutron-based sterilisation of anthrax contamination
Liu, B; Xu, J; Liu, T; Ouyang, X
2012-01-01
Objective To simulate the neutron-based sterilisation of anthrax contamination by Monte Carlo N-particle (MCNP) 4C code. Methods Neutrons are elementary particles that have no charge. They are 20 times more effective than electrons or ?-rays in killing anthrax spores on surfaces and inside closed containers. Neutrons emitted from a 252Cf neutron source are in the 100 keV to 2 MeV energy range. A 2.5 MeV D–D neutron generator can create neutrons at up to 1013 n s?1 with current technology. All these enable an effective and low-cost method of killing anthrax spores. Results There is no effect on neutron energy deposition on the anthrax sample when using a reflector that is thicker than its saturation thickness. Among all three reflecting materials tested in the MCNP simulation, paraffin is the best because it has the thinnest saturation thickness and is easy to machine. The MCNP radiation dose and fluence simulation calculation also showed that the MCNP-simulated neutron fluence that is needed to kill the anthrax spores agrees with previous analytical estimations very well. Conclusion The MCNP simulation indicates that a 10 min neutron irradiation from a 0.5 g 252Cf neutron source or a 1 min neutron irradiation from a 2.5 MeV D–D neutron generator may kill all anthrax spores in a sample. This is a promising result because a 2.5 MeV D–D neutron generator output >1013 n s?1 should be attainable in the near future. This indicates that we could use a D–D neutron generator to sterilise anthrax contamination within several seconds. PMID:22573293
Fixed-node diffusion Monte Carlo method for lithium systems
NASA Astrophysics Data System (ADS)
Rasch, K. M.; Mitas, L.
2015-07-01
We study lithium systems over a range of a number of atoms, specifically atomic anion, dimer, metallic cluster, and body-centered-cubic crystal, using the fixed-node diffusion Monte Carlo method. The focus is on analysis of the fixed-node errors of each system, and for that purpose we test several orbital sets in order to provide the most accurate nodal hypersurfaces. The calculations include both core and valence electrons in order to avoid any possible impact by pseudopotentials. To quantify the fixed-node errors, we compare our results to other highly accurate calculations, and wherever available, to experimental observations. The results for these Li systems show that the fixed-node diffusion Monte Carlo method achieves accurate total energies, recovers 96 -99 % of the correlation energy, and estimates binding energies with errors bounded by 0.1 eV /at .
Monte Carlo simulations of fermion systems: the determinant method
Gubernatis, J.E.
1985-01-01
Described are the details for performing Monte Carlo simulations on systems of fermions at finite temperatures by use of a technique called the Determinant Method. This method is based on a functional integral formulation of the fermion problem (Blankenbecler et al., Phys. Rev D 24, 2278 (1981)) in which the quartic fermion-fermion interactions that exist for certain models are transformed into bilinear ones by the introduction (J. Hirsch, Phys. Rev. B 28, 4059 (1983)) of Ising-like variables and an additional finite dimension. It is on the transformed problem the Monte Carlo simulations are performed. A brief summary of research on two such model problems, the spinless fermion lattice gas and the Anderson impurity problem, is also given.
NASA Astrophysics Data System (ADS)
Khrushcheva, O.; Zhurkin, E. E.; Malerba, L.; Becquart, C. S.; Domain, C.; Hou, M.
2003-04-01
Several variants are possible in the suite of programs forming multiscale predictive tools to estimate the yield strength increase caused by irradiation in RPV steels. For instance, at the atomic scale, both the Metropolis and the lattice kinetic Monte Carlo methods (MMC and LKMC respectively) allow predicting copper precipitation under irradiation conditions. Since these methods are based on different physical models, the present contribution discusses their consistency on the basis of a realistic case study. A cascade debris in iron containing 0.2% of copper was modelled by molecular dynamics with the DYMOKA code, which is part of the REVE suite. We use this debris as input for both the MMC and the LKMC simulations. Thermal motion and lattice relaxation can be avoided in the MMC, making the model closer to the LKMC (LMMC method). The predictions and the complementarity of the three methods for modelling the same phenomenon are then discussed.
Applications of Monte Carlo methods to statistical physics
K. Binder
1997-01-01
An introductory review of the Monte Carlo method for the statistical mechanics of condensed matter systems is given. Basic principles (random number generation, simple sampling versus importance sampling, Markov chains and master equations, etc) are explained and some classical applications (self-avoiding walks, percolation, the Ising model) are sketched. The finite-size scaling analysis of both second- and first-order phase transitions is
Monte Carlo Methods and Applications for the Nuclear Shell Model
Dean, D.J.; White, J.A.
1998-08-10
The shell-model Monte Carlo (SMMC) technique transforms the traditional nuclear shell-model problem into a path-integral over auxiliary fields. We describe below the method and its applications to four physics issues: calculations of sd-pf-shell nuclei, a discussion of electron-capture rates in pf-shell nuclei, exploration of pairing correlations in unstable nuclei, and level densities in rare earth systems.
Comparison of deterministic and Monte Carlo methods in shielding design.
Oliveira, A D; Oliveira, C
2005-01-01
In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions. PMID:16381723
Novel Extrapolation Method in the Monte Carlo Shell Model
Noritaka Shimizu; Yutaka Utsuno; Takahiro Mizusaki; Takaharu Otsuka; Takashi Abe; Michio Honma
2010-12-06
We propose an extrapolation method utilizing energy variance in the Monte Carlo shell model in order to estimate the energy eigenvalue and observables accurately. We derive a formula for the energy variance with deformed Slater determinants, which enables us to calculate the energy variance efficiently. The feasibility of the method is demonstrated for the full $pf$-shell calculation of $^{56}$Ni, and the applicability of the method to a system beyond current limit of exact diagonalization is shown for the $pf$+$g_{9/2}$-shell calculation of $^{64}$Ge.
Solving the many body pairing problem through Monte Carlo methods
NASA Astrophysics Data System (ADS)
Lingle, Mark; Volya, Alexander
2012-03-01
Nuclear superconductivity is a central part of quantum many-body dynamics. In mesoscopic systems such as atomic nuclei, this phenomenon is influenced by shell effects, mean-field deformation, particle decay, and by other collective and chaotic components of nucleon motion. The ability to find an exact solution to these pairing correlations is of particular importance. In this presentation we develop and investigate the effectiveness of different methods of attacking the nucleon pairing problem in nuclei. In particular, we concentrate on the Monte Carlo approach. We review the configuration space Monte Carlo techniques, the Suzuki-Trotter breakup of the time evolution operator, and treatment of the pairing problem with non-constant matrix elements. The quasi-spin symmetry allows for a mapping of the pairing problem onto a problem of interacting spins which in turn can be solved using a Monte Carlo approach. The algorithms are investigated for convergence to the true ground state of model systems and calculated ground state energies are compared to those found by an exact diagonalization method. The possibility to include other non-pairing interaction components of the Hamiltonian is also investigated.
A multi-scale Monte Carlo method for electrolytes
NASA Astrophysics Data System (ADS)
Liang, Yihao; Xu, Zhenli; Xing, Xiangjun
2015-08-01
Artifacts arise in the simulations of electrolytes using periodic boundary conditions (PBCs). We show the origin of these artifacts are the periodic image charges and the constraint of charge neutrality inside the simulation box, both of which are unphysical from the view point of real systems. To cure these problems, we introduce a multi-scale Monte Carlo (MC) method, where ions inside a spherical cavity are simulated explicitly, while ions outside are treated implicitly using a continuum theory. Using the method of Debye charging, we explicitly derive the effective interactions between ions inside the cavity, arising due to the fluctuations of ions outside. We find that these effective interactions consist of two types: (1) a constant cavity potential due to the asymmetry of the electrolyte, and (2) a reaction potential that depends on the positions of all ions inside. Combining the grand canonical Monte Carlo (GCMC) with a recently developed fast algorithm based on image charge method, we perform a multi-scale MC simulation of symmetric electrolytes, and compare it with other simulation methods, including PBC + GCMC method, as well as large scale MC simulation. We demonstrate that our multi-scale MC method is capable of capturing the correct physics of a large system using a small scale simulation.
Stabilized multilevel Monte Carlo method for stiff stochastic differential equations
Abdulle, Assyr, E-mail: assyr.abdulle@epfl.ch; Blumenthal, Adrian, E-mail: adrian.blumenthal@epfl.ch
2013-10-15
A multilevel Monte Carlo (MLMC) method for mean square stable stochastic differential equations with multiple scales is proposed. For such problems, that we call stiff, the performance of MLMC methods based on classical explicit methods deteriorates because of the time step restriction to resolve the fastest scales that prevents to exploit all the levels of the MLMC approach. We show that by switching to explicit stabilized stochastic methods and balancing the stabilization procedure simultaneously with the hierarchical sampling strategy of MLMC methods, the computational cost for stiff systems is significantly reduced, while keeping the computational algorithm fully explicit and easy to implement. Numerical experiments on linear and nonlinear stochastic differential equations and on a stochastic partial differential equation illustrate the performance of the stabilized MLMC method and corroborate our theoretical findings.
Variational Monte Carlo method for electron-phonon coupled systems
NASA Astrophysics Data System (ADS)
Ohgoe, Takahiro; Imada, Masatoshi
2014-05-01
We develop a variational Monte Carlo (VMC) method for electron-phonon coupled systems. The VMC method has been extensively used for investigating strongly correlated electrons over the last decades. However, its applications to electron-phonon coupled systems have been severely restricted because of its large Hilbert space. Here, we propose a variational wave function with a large number of variational parameters, which is suitable and tractable for systems with electron-phonon coupling. In the proposed wave function, we implement an unexplored electron-phonon correlation factor, which takes into account the effect of the entanglement between electrons and phonons. The method is applied to systems with diagonal electron-phonon interactions, i.e., interactions between charge densities and lattice displacements (phonons). As benchmarks, we compare VMC results with previous results obtained by the exact diagonalization, the Green function Monte Carlo method and the density matrix renormalization group for the Holstein and Holstein-Hubbard model. From these benchmarks, we show that the present method offers an efficient way to treat strongly coupled electron-phonon systems.
Analysis of real-time networks with monte carlo methods
NASA Astrophysics Data System (ADS)
Mauclair, C.; Durrieu, G.
2013-12-01
Communication networks in embedded systems are ever more large and complex. A better understanding of the dynamics of these networks is necessary to use them at best and lower costs. Todays tools are able to compute upper bounds of end-to-end delays that a packet being sent through the network could suffer. However, in the case of asynchronous networks, those worst end-to-end delay (WEED) cases are rarely observed in practice or through simulations due to the scarce situations that lead to worst case scenarios. A novel approach based on Monte Carlo methods is suggested to study the effects of the asynchrony on the performances.
Kasesaz, Y; Khalafi, H; Rahmani, F
2013-12-01
Optimization of the Beam Shaping Assembly (BSA) has been performed using the MCNP4C Monte Carlo code to shape the 2.45 MeV neutrons that are produced in the D-D neutron generator. Optimal design of the BSA has been chosen by considering in-air figures of merit (FOM) which consists of 70 cm Fluental as a moderator, 30 cm Pb as a reflector, 2mm (6)Li as a thermal neutron filter and 2mm Pb as a gamma filter. The neutron beam can be evaluated by in-phantom parameters, from which therapeutic gain can be derived. Direct evaluation of both set of FOMs (in-air and in-phantom) is very time consuming. In this paper a Response Matrix (RM) method has been suggested to reduce the computing time. This method is based on considering the neutron spectrum at the beam exit and calculating contribution of various dose components in phantom to calculate the Response Matrix. Results show good agreement between direct calculation and the RM method. PMID:23954283
Application of Monte Carlo methods in tomotherapy and radiation biophysics
NASA Astrophysics Data System (ADS)
Hsiao, Ya-Yun
Helical tomotherapy is an attractive treatment for cancer therapy because highly conformal dose distributions can be achieved while the on-board megavoltage CT provides simultaneous images for accurate patient positioning. The convolution/superposition (C/S) dose calculation methods typically used for Tomotherapy treatment planning may overestimate skin (superficial) doses by 3-13%. Although more accurate than C/S methods, Monte Carlo (MC) simulations are too slow for routine clinical treatment planning. However, the computational requirements of MC can be reduced by developing a source model for the parts of the accelerator that do not change from patient to patient. This source model then becomes the starting point for additional simulations of the penetration of radiation through patient. In the first section of this dissertation, a source model for a helical tomotherapy is constructed by condensing information from MC simulations into series of analytical formulas. The MC calculated percentage depth dose and beam profiles computed using the source model agree within 2% of measurements for a wide range of field sizes, which suggests that the proposed source model provides an adequate representation of the tomotherapy head for dose calculations. Monte Carlo methods are a versatile technique for simulating many physical, chemical and biological processes. In the second major of this thesis, a new methodology is developed to simulate of the induction of DNA damage by low-energy photons. First, the PENELOPE Monte Carlo radiation transport code is used to estimate the spectrum of initial electrons produced by photons. The initial spectrum of electrons are then combined with DNA damage yields for monoenergetic electrons from the fast Monte Carlo damage simulation (MCDS) developed earlier by Semenenko and Stewart (Purdue University). Single- and double-strand break yields predicted by the proposed methodology are in good agreement (1%) with the results of published experimental and theoretical studies for 60Co gamma-rays and low-energy x-rays. The reported studies provide new information about the potential biological consequences of diagnostic x-rays and selected gamma-emitting radioisotopes used in brachytherapy for the treatment of cancer. The proposed methodology is computationally efficient and may also be useful in proton therapy, space applications or internal dosimetry.
Markov-Chain Monte Carlo Methods for Simulations of Biomolecules
Bernd A. Berg
2007-09-04
The computer revolution has been driven by a sustained increase of computational speed of approximately one order of magnitude (a factor of ten) every five years since about 1950. In natural sciences this has led to a continuous increase of the importance of computer simulations. Major enabling techniques are Markov Chain Monte Carlo (MCMC) and Molecular Dynamics (MD) simulations. This article deals with the MCMC approach. First basic simulation techniques, as well as methods for their statistical analysis are reviewed. Afterwards the focus is on generalized ensembles and biased updating, two advanced techniques, which are of relevance for simulations of biomolecules, or are expected to become relevant with that respect. In particular we consider the multicanonical ensemble and the replica exchange method (also known as parallel tempering or method of multiple Markov chains).
Advanced Monte Carlo methods for thermal radiation transport
NASA Astrophysics Data System (ADS)
Wollaber, Allan B.
During the past 35 years, the Implicit Monte Carlo (IMC) method proposed by Fleck and Cummings has been the standard Monte Carlo approach to solving the thermal radiative transfer (TRT) equations. However, the IMC equations are known to have accuracy limitations that can produce unphysical solutions. In this thesis, we explicitly provide the IMC equations with a Monte Carlo interpretation by including particle weight as one of its arguments. We also develop and test a stability theory for the 1-D, gray IMC equations applied to a nonlinear problem. We demonstrate that the worst case occurs for 0-D problems, and we extend the results to a stability algorithm that may be used for general linearizations of the TRT equations. We derive gray, Quasidiffusion equations that may be deterministically solved in conjunction with IMC to obtain an inexpensive, accurate estimate of the temperature at the end of the time step. We then define an average temperature T* to evaluate the temperature-dependent problem data in IMC, and we demonstrate that using T* is more accurate than using the (traditional) beginning-of-time-step temperature. We also propose an accuracy enhancement to the IMC equations: the use of a time-dependent "Fleck factor". This Fleck factor can be considered an automatic tuning of the traditionally defined user parameter alpha, which generally provides more accurate solutions at an increased cost relative to traditional IMC. We also introduce a global weight window that is proportional to the forward scalar intensity calculated by the Quasidiffusion method. This weight window improves the efficiency of the IMC calculation while conserving energy. All of the proposed enhancements are tested in 1-D gray and frequency-dependent problems. These enhancements do not unconditionally eliminate the unphysical behavior that can be seen in the IMC calculations. However, for fixed spatial and temporal grids, they suppress them and clearly work to make the solution more accurate. Overall, the work presented represents first steps along several paths that can be taken to improve the Monte Carlo simulations of TRT problems.
ITER Neutronics Modeling Using Hybrid Monte Carlo/Deterministic and CAD-Based Monte Carlo Methods
Ibrahim, A.; Mosher, Scott W; Evans, Thomas M; Peplow, Douglas E.; Sawan, M.; Wilson, P.; Wagner, John C; Heltemes, Thad
2011-01-01
The immense size and complex geometry of the ITER experimental fusion reactor require the development of special techniques that can accurately and efficiently perform neutronics simulations with minimal human effort. This paper shows the effect of the hybrid Monte Carlo (MC)/deterministic techniques - Consistent Adjoint Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) - in enhancing the efficiency of the neutronics modeling of ITER and demonstrates the applicability of coupling these methods with computer-aided-design-based MC. Three quantities were calculated in this analysis: the total nuclear heating in the inboard leg of the toroidal field coils (TFCs), the prompt dose outside the biological shield, and the total neutron and gamma fluxes over a mesh tally covering the entire reactor. The use of FW-CADIS in estimating the nuclear heating in the inboard TFCs resulted in a factor of ~ 275 increase in the MC figure of merit (FOM) compared with analog MC and a factor of ~ 9 compared with the traditional methods of variance reduction. By providing a factor of ~ 21 000 increase in the MC FOM, the radiation dose calculation showed how the CADIS method can be effectively used in the simulation of problems that are practically impossible using analog MC. The total flux calculation demonstrated the ability of FW-CADIS to simultaneously enhance the MC statistical precision throughout the entire ITER geometry. Collectively, these calculations demonstrate the ability of the hybrid techniques to accurately model very challenging shielding problems in reasonable execution times.
Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods
NASA Astrophysics Data System (ADS)
Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.
2014-12-01
Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.
Applications of the Fixed-Node Quantum Monte Carlo Method
NASA Astrophysics Data System (ADS)
Kulahlioglu, Adem Halil
Quantum Monte Carlo (QMC) is a highly sophisticated quantum many-body method. Diffusion Monte Carlo (DMC), a projected QMC method, is a stochastic solution of the stationary Schrodinger's equation. It is, in principle, an exact method. However, in dealing with fermions, since trial wave functions meet the antisymmetric condition of the many-body fermionic systems, it inevitably encounters the fermion sign problem. One of the ways to circumvent the sign problem is by imposing the so-called fixed-node approximation. The fixed-node DMC (FN-DMC), a highly promising method, is emerging as the method of choice for correlated treatment of many-body electronic structure problems since it is much more accurate than Khon-Sham DFT and has a competitive accuracy with CCSD(T) but scales better with system size than CCSD(T). An important drawback in FN-DMC is the fixed-node bias introduced by the approximate nature of the trial wave function nodes. In this dissertation, we examine the fixed-node bias and its restrictive impact on the accuracy of FN-DMC. Also, electron density dependence of the fixed-node bias is discussed by taking a relatively small atomic system. In our dissertation, we also applied FN-DMC in a relatively large molecular system with a transition metal, Zinc-porphyrin, to calculate the excitation energy in an adiabatic limit (vertical excitation). We found that FN-DMC results agree well with experimental values as well as with results obtained by some other correlated ab initio methods such as CCSD. In addition, we used FN-DMC to study a transition metal dimer, Mo 2, which is a challenging system for theoretical studies since there is large amount of many-body correlation effects. We constructed the antisymmetric part (Slater part) of the trial wave function by means of the Selected-CI method. Moreover, we carried out CCSD(T) calculations in order to be able to compare FN-DMC energies with another correlated method energies. FN-DMC and CCSD(T) calculations in Mo2, which is dominant with d-d bondings, enabled us to make comparisons between these two competitive methods and investigate the limitations impairing FN-DMC accuracy.
A new effective Monte Carlo Midway coupling method in MCNP applied to a well logging problem
I. V. Serov; T. M. John; J. E. Hoogenboom
1998-01-01
The background of the Midway forward–adjoint coupling method including the black absorber technique for efficient Monte Carlo determination of radiation detector responses is described. The method is implemented in the general purpose MCNP Monte Carlo code. The utilization of the method is fairly straightforward and does not require any substantial extra expertise. The method was applied to a standard neutron
Diagrammatic Monte Carlo method for many-polaron problems.
Mishchenko, Andrey S; Nagaosa, Naoto; Prokof'ev, Nikolay
2014-10-17
We introduce the first bold diagrammatic Monte Carlo approach to deal with polaron problems at a finite electron density nonperturbatively, i.e., by including vertex corrections to high orders. Using the Holstein model on a square lattice as a prototypical example, we demonstrate that our method is capable of providing accurate results in the thermodynamic limit in all regimes from a renormalized Fermi liquid to a single polaron, across the nonadiabatic region where Fermi and Debye energies are of the same order of magnitude. By accounting for vertex corrections, the accuracy of the theoretical description is increased by orders of magnitude relative to the lowest-order self-consistent Born approximation employed in most studies. We also find that for the electron-phonon coupling typical for real materials, the quasiparticle effective mass increases and the quasiparticle residue decreases with increasing the electron density at constant electron-phonon coupling strength. PMID:25361271
Diagrammatic Monte Carlo Method for Many-Polaron Problems
NASA Astrophysics Data System (ADS)
Mishchenko, Andrey S.; Nagaosa, Naoto; Prokof'ev, Nikolay
2014-10-01
We introduce the first bold diagrammatic Monte Carlo approach to deal with polaron problems at a finite electron density nonperturbatively, i.e., by including vertex corrections to high orders. Using the Holstein model on a square lattice as a prototypical example, we demonstrate that our method is capable of providing accurate results in the thermodynamic limit in all regimes from a renormalized Fermi liquid to a single polaron, across the nonadiabatic region where Fermi and Debye energies are of the same order of magnitude. By accounting for vertex corrections, the accuracy of the theoretical description is increased by orders of magnitude relative to the lowest-order self-consistent Born approximation employed in most studies. We also find that for the electron-phonon coupling typical for real materials, the quasiparticle effective mass increases and the quasiparticle residue decreases with increasing the electron density at constant electron-phonon coupling strength.
A modified Monte Carlo 'local importance function transform' method
Keady, K. P.; Larsen, E. W.
2013-07-01
The Local Importance Function Transform (LIFT) method uses an approximation of the contribution transport problem to bias a forward Monte-Carlo (MC) source-detector simulation [1-3]. Local (cell-based) biasing parameters are calculated from an inexpensive deterministic adjoint solution and used to modify the physics of the forward transport simulation. In this research, we have developed a new expression for the LIFT biasing parameter, which depends on a cell-average adjoint current to scalar flux (J{sup *}/{phi}{sup *}) ratio. This biasing parameter differs significantly from the original expression, which uses adjoint cell-edge scalar fluxes to construct a finite difference estimate of the flux derivative; the resulting biasing parameters exhibit spikes in magnitude at material discontinuities, causing the original LIFT method to lose efficiency in problems with high spatial heterogeneity. The new J{sup *}/{phi}{sup *} expression, while more expensive to obtain, generates biasing parameters that vary smoothly across the spatial domain. The result is an improvement in simulation efficiency. A representative test problem has been developed and analyzed to demonstrate the advantage of the updated biasing parameter expression with regards to solution figure of merit (FOM). For reference, the two variants of the LIFT method are compared to a similar variance reduction method developed by Depinay [4, 5], as well as MC with deterministic adjoint weight windows (WW). (authors)
Underwater Optical Wireless Channel Modeling Using Monte-Carlo Method
NASA Astrophysics Data System (ADS)
Saini, P. Sri; Prince, Shanthi
2011-10-01
At present, there is a lot of interest in the functioning of the marine environment. Unmanned or Autonomous Underwater Vehicles (UUVs or AUVs) are used in the exploration of the underwater resources, pollution monitoring, disaster prevention etc. Underwater, where radio waves do not propagate, acoustic communication is being used. But, underwater communication is moving towards Optical Communication which has higher bandwidth when compared to Acoustic Communication but has shorter range comparatively. Underwater Optical Wireless Communication (OWC) is mainly affected by the absorption and scattering of the optical signal. In coastal waters, both inherent and apparent optical properties (IOPs and AOPs) are influenced by a wide array of physical, biological and chemical processes leading to optical variability. The scattering effect has two effects: the attenuation of the signal and the Inter-Symbol Interference (ISI) of the signal. However, the Inter-Symbol Interference is ignored in the present paper. Therefore, in order to have an efficient underwater OWC link it is necessary to model the channel efficiently. In this paper, the underwater optical channel is modeled using Monte-Carlo method. The Monte Carlo approach provides the most general and most flexible technique for numerically solving the equations of Radiative transfer. The attenuation co-efficient of the light signal is studied as a function of the absorption (a) and scattering (b) coefficients. It has been observed that for pure sea water and for less chlorophyll conditions blue wavelength is less absorbed whereas for chlorophyll rich environment red wavelength signal is absorbed less comparative to blue and green wavelength.
The direct Monte Carlo method for calculating alloy phases
Faulkner, J.S.; Horvath, E.A.; Wang, Yang [Florida Atlantic Univ., Boca Raton, FL (United States); Stocks, G.M. [Oak Ridge National Lab., TN (United States)
1992-11-01
Theories exist for predicting the structure of an alloy on the assumption that the energy of the alloy can be obtained from an Ising model Hamiltonian. It is not necessary to introduce interatomic potentials if the Monte Carlo method is used for thermodynamics. {delta}H is calculated directly from the electronic structure of the alloy using the embedded cluster method (ECM) of alloy theory. ECM is based on the coherent potential approximation (CPA) for the electronic states of random substitutional alloys. A version of the theory was developed within the context of the tight-binding model. Cray ymp calculations were made for a 50 - 50 Pd - Rh fcc alloy; electronic energies were obtained using an ECM based on KKR-CPA programs. The top of the miscibility gap is predicted to be at 1415 K. The order parameter vs T graph shows a critical temperature just above 1200 K. Calculations in the grand canonical mode are underway. The calculations are for the fcc lattice, but the bcc lattice is also considered. There are other methods, such as the Harris approximation, that will improve the energy calculations. 4 figs, 15 refs. (DLC)
Neutronic analysis code for fuel assembly using a vectorized Monte Carlo method
Morimoto, Y.; Maruyama, H.; Ishii, K.; Aoyama, M. (Hitachi Ltd., Ibaraki (Japan). Energy Research Lab.)
1989-12-01
A fuel assembly analysis code, VMONT, in which a multigroup neutron transport calculation is combined with a burnup calculation, has been developed for comprehensive design work use. The neutron transport calculation is performed with a vectorized Monte Carlo method that can realize speeds {gt}10 times faster than those of a scalar Monte Carlo method. The validity of the VMONT code is shown through test calculations against continuous energy Monte Carlo calculations and the proteus tight lattice experiment.
An automated variance reduction method for global Monte Carlo neutral particle transport problems
NASA Astrophysics Data System (ADS)
Cooper, Marc Andrew
A method to automatically reduce the variance in global neutral particle Monte Carlo problems by using a weight window derived from a deterministic forward solution is presented. This method reduces a global measure of the variance of desired tallies and increases its associated figure of merit. Global deep penetration neutron transport problems present difficulties for analog Monte Carlo. When the scalar flux decreases by many orders of magnitude, so does the number of Monte Carlo particles. This can result in large statistical errors. In conjunction with survival biasing, a weight window is employed which uses splitting and Russian roulette to restrict the symbolic weights of Monte Carlo particles. By establishing a connection between the scalar flux and the weight window, two important concepts are demonstrated. First, such a weight window can be constructed from a deterministic solution of a forward transport problem. Also, the weight window will distribute Monte Carlo particles in such a way to minimize a measure of the global variance. For Implicit Monte Carlo solutions of radiative transfer problems, an inefficient distribution of Monte Carlo particles can result in large statistical errors in front of the Marshak wave and at its leading edge. Again, the global Monte Carlo method is used, which employs a time-dependent weight window derived from a forward deterministic solution. Here, the algorithm is modified to enhance the number of Monte Carlo particles in the wavefront. Simulations show that use of this time-dependent weight window significantly improves the Monte Carlo calculation.
MARKOV CHAIN MONTE CARLO POSTERIOR SAMPLING WITH THE HAMILTONIAN METHOD
K. HANSON
2001-02-01
The Markov Chain Monte Carlo technique provides a means for drawing random samples from a target probability density function (pdf). MCMC allows one to assess the uncertainties in a Bayesian analysis described by a numerically calculated posterior distribution. This paper describes the Hamiltonian MCMC technique in which a momentum variable is introduced for each parameter of the target pdf. In analogy to a physical system, a Hamiltonian H is defined as a kinetic energy involving the momenta plus a potential energy {var_phi}, where {var_phi} is minus the logarithm of the target pdf. Hamiltonian dynamics allows one to move along trajectories of constant H, taking large jumps in the parameter space with relatively few evaluations of {var_phi} and its gradient. The Hamiltonian algorithm alternates between picking a new momentum vector and following such trajectories. The efficiency of the Hamiltonian method for multidimensional isotropic Gaussian pdfs is shown to remain constant at around 7% for up to several hundred dimensions. The Hamiltonian method handles correlations among the variables much better than the standard Metropolis algorithm. A new test, based on the gradient of {var_phi}, is proposed to measure the convergence of the MCMC sequence.
LISA data analysis using Markov chain Monte Carlo methods
Cornish, Neil J.; Crowder, Jeff [Department of Physics, Montana State University, Bozeman, Montana 59717 (United States)
2005-08-15
The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low-frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50 000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analysis, and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we supercool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions.
Kolbun, N.; Leveque, Ph.; Abboud, F.; Bol, A.; Vynckier, S.; Gallez, B. [Biomedical Magnetic Resonance Unit, Louvain Drug Research Institute, Universite catholique de Louvain, Avenue Mounier 73.40, B-1200 Brussels (Belgium); Molecular Imaging and Experimental Radiotherapy Unit, Institute of Experimental and Clinical Research, Universite catholique de Louvain, Avenue Hippocrate 55, B-1200 Brussels (Belgium); Biomedical Magnetic Resonance Unit, Louvain Drug Research Institute, Universite catholique de Louvain, Avenue Mounier 73.40, B-1200 Brussels (Belgium)
2010-10-15
Purpose: The experimental determination of doses at proximal distances from radioactive sources is difficult because of the steepness of the dose gradient. The goal of this study was to determine the relative radial dose distribution for a low dose rate {sup 192}Ir wire source using electron paramagnetic resonance imaging (EPRI) and to compare the results to those obtained using Gafchromic EBT film dosimetry and Monte Carlo (MC) simulations. Methods: Lithium formate and ammonium formate were chosen as the EPR dosimetric materials and were used to form cylindrical phantoms. The dose distribution of the stable radiation-induced free radicals in the lithium formate and ammonium formate phantoms was assessed by EPRI. EBT films were also inserted inside in ammonium formate phantoms for comparison. MC simulation was performed using the MCNP4C2 software code. Results: The radical signal in irradiated ammonium formate is contained in a single narrow EPR line, with an EPR peak-to-peak linewidth narrower than that of lithium formate ({approx}0.64 and 1.4 mT, respectively). The spatial resolution of EPR images was enhanced by a factor of 2.3 using ammonium formate compared to lithium formate because its linewidth is about 0.75 mT narrower than that of lithium formate. The EPRI results were consistent to within 1% with those of Gafchromic EBT films and MC simulations at distances from 1.0 to 2.9 mm. The radial dose values obtained by EPRI were about 4% lower at distances from 2.9 to 4.0 mm than those determined by MC simulation and EBT film dosimetry. Conclusions: Ammonium formate is a suitable material under certain conditions for use in brachytherapy dosimetry using EPRI. In this study, the authors demonstrated that the EPRI technique allows the estimation of the relative radial dose distribution at short distances for a {sup 192}Ir wire source.
Convolution/superposition using the Monte Carlo method.
Naqvi, Shahid A; Earl, Matthew A; Shepard, David M
2003-07-21
The convolution/superposition calculations for radiotherapy dose distributions are traditionally performed by convolving polyenergetic energy deposition kernels with TERMA (total energy released per unit mass) precomputed in each voxel of the irradiated phantom. We propose an alternative method in which the TERMA calculation is replaced by random sampling of photon energy, direction and interaction point. Then, a direction is randomly sampled from the angular distribution of the monoenergetic kernel corresponding to the photon energy. The kernel ray is propagated across the phantom, and energy is deposited in each voxel traversed. An important advantage of the explicit sampling of energy is that spectral changes with depth are automatically accounted for. No spectral or kernel hardening corrections are needed. Furthermore, the continuous sampling of photon direction allows us to model sharp changes in fluence, such as those due to collimator tongue-and-groove. The use of explicit photon direction also facilitates modelling of situations where a given voxel is traversed by photons from many directions. Extra-focal radiation, for instance, can therefore be modelled accurately. Our method also allows efficient calculation of a multi-segment/multi-beam IMRT plan by sampling of beam angles and field segments according to their relative weights. For instance, an IMRT plan consisting of seven 14 x 12 cm2 beams with a total of 300 field segments can be computed in 15 min on a single CPU, with 2% statistical fluctuations at the isocentre of the patient's CT phantom divided into 4 x 4 x 4 mm3 voxels. The calculation contains all aperture-specific effects, such as tongue and groove, leaf curvature and head scatter. This contrasts with deterministic methods in which each segment is given equal importance, and the time taken scales with the number of segments. Thus, the Monte Carlo superposition provides a simple, accurate and efficient method for complex radiotherapy dose calculations. PMID:12894973
Linearly scalable hybrid Monte Carlo method for conformational sampling of large biomolecules
Izaguirre, JesÃºs A.
multiple time scales that both limit the small time step of molecular dynamics (MD) and require the performance of either method separately. 2.1 Molecular Dynamics and Monte Carlo Molecular dynamicsLinearly scalable hybrid Monte Carlo method for conformational sampling of large biomolecules Scott
Specialising Simulator Generators for High-Performance Monte-Carlo Methods
Chakravarty, Manuel
in computationally intensive software, such as scientific and financial simulations. Software designers usually aim a computational chemistry simulation, using a Monte- Carlo method, that in its innermost loop repeatedly selectsSpecialising Simulator Generators for High-Performance Monte-Carlo Methods Gabriele Keller1 , Hugh
Author's personal copy Monte Carlo methods for design and analysis of radiation detectors
Shultis, J. Kenneth
Author's personal copy Monte Carlo methods for design and analysis of radiation detectors William L Radiation detectors Inverse problems Detector design a b s t r a c t An overview of Monte Carlo as a practical method for designing and analyzing radiation detectors is provided. The emphasis is on detectors
Quantum Monte Carlo methods and lithium cluster properties. [Atomic clusters
Owen, R.K.
1990-12-01
Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) (0.1981), 0.1895(9) (0.1874(4)), 0.1530(34) (0.1599(73)), 0.1664(37) (0.1724(110)), 0.1613(43) (0.1675(110)) Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) (0.0203(12)), 0.0188(10) (0.0220(21)), 0.0247(8) (0.0310(12)), 0.0253(8) (0.0351(8)) Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.
Quantum Monte Carlo methods and lithium cluster properties
Owen, R.K.
1990-12-01
Properties of small lithium clusters with sizes ranging from n = 1 to 5 atoms were investigated using quantum Monte Carlo (QMC) methods. Cluster geometries were found from complete active space self consistent field (CASSCF) calculations. A detailed development of the QMC method leading to the variational QMC (V-QMC) and diffusion QMC (D-QMC) methods is shown. The many-body aspect of electron correlation is introduced into the QMC importance sampling electron-electron correlation functions by using density dependent parameters, and are shown to increase the amount of correlation energy obtained in V-QMC calculations. A detailed analysis of D-QMC time-step bias is made and is found to be at least linear with respect to the time-step. The D-QMC calculations determined the lithium cluster ionization potentials to be 0.1982(14) [0.1981], 0.1895(9) [0.1874(4)], 0.1530(34) [0.1599(73)], 0.1664(37) [0.1724(110)], 0.1613(43) [0.1675(110)] Hartrees for lithium clusters n = 1 through 5, respectively; in good agreement with experimental results shown in the brackets. Also, the binding energies per atom was computed to be 0.0177(8) [0.0203(12)], 0.0188(10) [0.0220(21)], 0.0247(8) [0.0310(12)], 0.0253(8) [0.0351(8)] Hartrees for lithium clusters n = 2 through 5, respectively. The lithium cluster one-electron density is shown to have charge concentrations corresponding to nonnuclear attractors. The overall shape of the electronic charge density also bears a remarkable similarity with the anisotropic harmonic oscillator model shape for the given number of valence electrons.
Spike inference from calcium imaging using sequential Monte Carlo methods.
Vogelstein, Joshua T; Watson, Brendon O; Packer, Adam M; Yuste, Rafael; Jedynak, Bruno; Paninski, Liam
2009-07-22
As recent advances in calcium sensing technologies facilitate simultaneously imaging action potentials in neuronal populations, complementary analytical tools must also be developed to maximize the utility of this experimental paradigm. Although the observations here are fluorescence movies, the signals of interest--spike trains and/or time varying intracellular calcium concentrations--are hidden. Inferring these hidden signals is often problematic due to noise, nonlinearities, slow imaging rate, and unknown biophysical parameters. We overcome these difficulties by developing sequential Monte Carlo methods (particle filters) based on biophysical models of spiking, calcium dynamics, and fluorescence. We show that even in simple cases, the particle filters outperform the optimal linear (i.e., Wiener) filter, both by obtaining better estimates and by providing error bars. We then relax a number of our model assumptions to incorporate nonlinear saturation of the fluorescence signal, as well external stimulus and spike history dependence (e.g., refractoriness) of the spike trains. Using both simulations and in vitro fluorescence observations, we demonstrate temporal superresolution by inferring when within a frame each spike occurs. Furthermore, the model parameters may be estimated using expectation maximization with only a very limited amount of data (e.g., approximately 5-10 s or 5-40 spikes), without the requirement of any simultaneous electrophysiology or imaging experiments. PMID:19619479
Treatment planning aspects and Monte Carlo methods in proton therapy
NASA Astrophysics Data System (ADS)
Fix, Michael K.; Manser, Peter
2015-05-01
Over the last years, the interest in proton radiotherapy is rapidly increasing. Protons provide superior physical properties compared with conventional radiotherapy using photons. These properties result in depth dose curves with a large dose peak at the end of the proton track and the finite proton range allows sparing the distally located healthy tissue. These properties offer an increased flexibility in proton radiotherapy, but also increase the demand in accurate dose estimations. To carry out accurate dose calculations, first an accurate and detailed characterization of the physical proton beam exiting the treatment head is necessary for both currently available delivery techniques: scattered and scanned proton beams. Since Monte Carlo (MC) methods follow the particle track simulating the interactions from first principles, this technique is perfectly suited to accurately model the treatment head. Nevertheless, careful validation of these MC models is necessary. While for the dose estimation pencil beam algorithms provide the advantage of fast computations, they are limited in accuracy. In contrast, MC dose calculation algorithms overcome these limitations and due to recent improvements in efficiency, these algorithms are expected to improve the accuracy of the calculated dose distributions and to be introduced in clinical routine in the near future.
Spike Inference from Calcium Imaging Using Sequential Monte Carlo Methods
Vogelstein, Joshua T.; Watson, Brendon O.; Packer, Adam M.; Yuste, Rafael; Jedynak, Bruno; Paninski, Liam
2009-01-01
Abstract As recent advances in calcium sensing technologies facilitate simultaneously imaging action potentials in neuronal populations, complementary analytical tools must also be developed to maximize the utility of this experimental paradigm. Although the observations here are fluorescence movies, the signals of interest—spike trains and/or time varying intracellular calcium concentrations—are hidden. Inferring these hidden signals is often problematic due to noise, nonlinearities, slow imaging rate, and unknown biophysical parameters. We overcome these difficulties by developing sequential Monte Carlo methods (particle filters) based on biophysical models of spiking, calcium dynamics, and fluorescence. We show that even in simple cases, the particle filters outperform the optimal linear (i.e., Wiener) filter, both by obtaining better estimates and by providing error bars. We then relax a number of our model assumptions to incorporate nonlinear saturation of the fluorescence signal, as well external stimulus and spike history dependence (e.g., refractoriness) of the spike trains. Using both simulations and in vitro fluorescence observations, we demonstrate temporal superresolution by inferring when within a frame each spike occurs. Furthermore, the model parameters may be estimated using expectation maximization with only a very limited amount of data (e.g., ?5–10 s or 5–40 spikes), without the requirement of any simultaneous electrophysiology or imaging experiments. PMID:19619479
Monte Carlo methods for parallel processing of diffusion equations
Vafadari, Cyrus
2013-01-01
A Monte Carlo algorithm for solving simple linear systems using a random walk is demonstrated and analyzed. The described algorithm solves for each element in the solution vector independently. Furthermore, it is demonstrated ...
Integration of the Lippmann-Schwinger equation with the Monte Carlo method
Salomon, M.
1983-12-01
A Monte Carlo method to integrate the Lippmann-Schwinger equation for elastic scattering is presented. Advantages and limitations of this algorithm are compared with traditional methods of computation.
Franke, B. C.; Prinja, A. K.
2013-07-01
The stochastic Galerkin method (SGM) is an intrusive technique for propagating data uncertainty in physical models. The method reduces the random model to a system of coupled deterministic equations for the moments of stochastic spectral expansions of result quantities. We investigate solving these equations using the Monte Carlo technique. We compare the efficiency with brute-force Monte Carlo evaluation of uncertainty, the non-intrusive stochastic collocation method (SCM), and an intrusive Monte Carlo implementation of the stochastic collocation method. We also describe the stability limitations of our SGM implementation. (authors)
Perfetti, Christopher M; Rearden, Bradley T
2014-01-01
This work introduces a new approach for calculating sensitivity coefficients for generalized neutronic responses to nuclear data uncertainties using continuous-energy Monte Carlo methods. The approach presented in this paper, known as the GEAR-MC method, allows for the calculation of generalized sensitivity coefficients for multiple responses in a single Monte Carlo calculation with no nuclear data perturbations or knowledge of nuclear covariance data. The theory behind the GEAR-MC method is presented here, and proof of principle is demonstrated by using the GEAR-MC method to calculate sensitivity coefficients for responses in several 3D, continuous-energy Monte Carlo applications.
Article type: Opinion Article Why the Monte Carlo Method is so important
Kroese, Dirk P.
Article type: Opinion Article Why the Monte Carlo Method is so important today Article ID Dirk P, estimation, randomized optimization Abstract Since the beginning of electronic computing, people have been interested in carrying out random experiments on a computer. Such Monte Carlo tech- niques are now
Review of quantum Monte Carlo methods and results for Coulombic systems
Ceperley, D.
1983-01-27
The various Monte Carlo methods for calculating ground state energies are briefly reviewed. Then a summary of the charged systems that have been studied with Monte Carlo is given. These include the electron gas, small molecules, a metal slab and many-body hydrogen.
Widom, Michael
2011-01-01
PHYSICAL REVIEW E 84, 061912 (2011) Kinetic Monte Carlo method applied to nucleic acid hairpin December 2011) Kinetic Monte Carlo on coarse-grained systems, such as nucleic acid secondary structure states. Secondary structure models of nucleic acids, which record the pairings of complementary
Markov chain Monte Carlo posterior sampling with the Hamiltonian method.
Hanson, Kenneth M.
2001-01-01
A major advantage of Bayesian data analysis is that provides a characterization of the uncertainty in the model parameters estimated from a given set of measurements in the form of a posterior probability distribution. When the analysis involves a complicated physical phenomenon, the posterior may not be available in analytic form, but only calculable by means of a simulation code. In such cases, the uncertainty in inferred model parameters requires characterization of a calculated functional. An appealing way to explore the posterior, and hence characterize the uncertainty, is to employ the Markov Chain Monte Carlo technique. The goal of MCMC is to generate a sequence random of parameter x samples from a target pdf (probability density function), {pi}(x). In Bayesian analysis, this sequence corresponds to a set of model realizations that follow the posterior distribution. There are two basic MCMC techniques. In Gibbs sampling, typically one parameter is drawn from the conditional pdf at a time, holding all others fixed. In the Metropolis algorithm, all the parameters can be varied at once. The parameter vector is perturbed from the current sequence point by adding a trial step drawn randomly from a symmetric pdf. The trial position is either accepted or rejected on the basis of the probability at the trial position relative to the current one. The Metropolis algorithm is often employed because of its simplicity. The aim of this work is to develop MCMC methods that are useful for large numbers of parameters, n, say hundreds or more. In this regime the Metropolis algorithm can be unsuitable, because its efficiency drops as 0.3/n. The efficiency is defined as the reciprocal of the number of steps in the sequence needed to effectively provide a statistically independent sample from {pi}.
Hydrologic Model Selection using Markov chain Monte Carlo methods
NASA Astrophysics Data System (ADS)
Marshall, L.; Sharma, A.; Nott, D.
2002-12-01
Estimation of parameter uncertainty (and in turn model uncertainty) allows assessment of the risk in likely applications of hydrological models. Bayesian statistical inference provides an ideal means of assessing parameter uncertainty whereby prior knowledge about the parameter is combined with information from the available data to produce a probability distribution (the posterior distribution) that describes uncertainty about the parameter and serves as a basis for selecting appropriate values for use in modelling applications. Widespread use of Bayesian techniques in hydrology has been hindered by difficulties in summarizing and exploring the posterior distribution. These difficulties have been largely overcome by recent advances in Markov chain Monte Carlo (MCMC) methods that involve random sampling of the posterior distribution. This study presents an adaptive MCMC sampling algorithm which has characteristics that are well suited to model parameters with a high degree of correlation and interdependence, as is often evident in hydrological models. The MCMC sampling technique is used to compare six alternative configurations of a commonly used conceptual rainfall-runoff model, the Australian Water Balance Model (AWBM), using 11 years of daily rainfall runoff data from the Bass river catchment in Australia. The alternative configurations considered fall into two classes - those that consider model errors to be independent of prior values, and those that model the errors as an autoregressive process. Each such class consists of three formulations that represent increasing levels of complexity (and parameterisation) of the original model structure. The results from this study point both to the importance of using Bayesian approaches in evaluating model performance, as well as the simplicity of the MCMC sampling framework that has the ability to bring such approaches within the reach of the applied hydrological community.
Tracking multiple interacting subcellular structure by sequential Monte Carlo method.
Wen, Quan; Luby-Phelps, Kate; Gao, Jean
2009-01-01
With the wide application of Green Fluorescent Proteins (GFP) in the study of live cells, there is a surging need for computer-aided analysis on the huge amount of image sequence data acquired by the advanced microscopy devices. In this paper, a framework based on Sequential Monte Carlo (SMC) is proposed for multiple interacting object tracking. The distribution of the dimension varying joint state is sampled efficiently by a Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm with a novel height swap move. Experimental results were performed on synthetic and real confocal microscopy image sequences. PMID:19623773
Modeling granular phosphor screens by Monte Carlo methods
Panagiotis F. Liaparinos; Ioannis S. Kandarakis; Dionisis A. Cavouras; Harry B. Delis; George S. Panayiotakisa
2006-01-01
The intrinsic phosphor properties are of significant importance for the performance of phosphor screens used in medical imaging systems. In previous analytical-theoretical and Monte Carlo studies on granular phosphor materials, values of optical properties, and light interaction cross sections were found by fitting to experimental data. These values were then employed for the assessment of phosphor screen imaging performance. However,
I. QUANTUM MONTE CARLO METHODS: INTRODUCTION AND BASICS Markus Holzmann
, 2012) I will provide a rough overview of zero temperature Quantum Monte Carlo calculations in electronic structure or chemical physics. Ideally, one would like to know the eigen values parameters which are then optimized to lower the energy. However, already the evaluation of the wavefunction
A Monte Carlo method for exponential hedging of contingent claims
Hurd, Thomas R.
of Black, Scholes, Merton and others, #12;- nancial assets in complete markets can be priced uniquely theoretically con- sistent approach to pricing and hedging of securities in incomplete #12;nancial markets on simulated Monte Carlo data. It shares with the LS framework intuitivity, simplicity and ex- ibility. #3
A Monte Carlo method for calculating orbits of comets
J. Q. Zheng; M. J. Valtonen; S. Mikkola; J. J. Matese; P. G. Whitman; H. Rickman
1994-01-01
The present work is divided into two stages: 1. By using large numbers (several millions) of accurate orbit integrations with the K-S regularization, probability distributions for changes in the orbital elements of comets during encounters with planets are evaluated. 2. These distributions are used in a Monte Carlo simulation scheme which follows the evolution of orbits under repeated close encounters.
Walsh, Jonathan A. (Jonathan Alan)
2014-01-01
This thesis presents the development and analysis of computational methods for efficiently accessing and utilizing nuclear data in Monte Carlo neutron transport code simulations. Using the OpenMC code, profiling studies ...
Multivariate Population Balances via Moment and Monte Carlo Simulation Methods: An Important Sol with a population balance equation governing evolution of the "dispersed" (suspended) particle population. Early, hopefully, motivate a broader attack on important multivariate population balance problems, including those
A Monte Carlo method for the PDF equations of turbulent flow
Pope, S. B.
1980-01-01
A Monte Carlo method is presented which simulates the transport equations of joint probability density functions (pdf's) in turbulent flows. (Finite-difference solutions of the equations are impracticable, mainly because ...
Carlo Jacoboni; Lino Reggiani
1983-01-01
This review presents in a comprehensive and tutorial form the basic principles of the Monte Carlo method, as applied to the solution of transport problems in semiconductors. Sufficient details of a typical Monte Carlo simulation have been given to allow the interested reader to create his own Monte Carlo program, and the method has been briefly compared with alternative theoretical
Hunter, David
Batch means standard errors for MCMC Batch means is one method used to compute Monte Carlo standard errors. There is a vast literature on sophisticated methods for computing Monte Carlo standard errors Carlo standard error is ^ N . How do we pick b (and hence a) ? b (batch size) should be large enough so
Hunter, David
Batch means standard errors for MCMC Batch means is one method used to compute Monte Carlo standard errors. There is a vast literature on sophisticated methods for computing Monte Carlo standard errors of the Monte Carlo standard error is ^ N . How do we pick b (and hence a) ? The batch size b should be large
APR1400 LBLOCA uncertainty quantification by Monte Carlo method and comparison with Wilks' formula
Hwang, M.; Bae, S.; Chung, B. D. [Korea Atomic Energy Research Inst., 150 Dukjin-dong, Yuseong-gu, Daejeon (Korea, Republic of)
2012-07-01
An analysis of the uncertainty quantification for the PWR LBLOCA by the Monte Carlo calculation has been performed and compared with the tolerance level determined by Wilks' formula. The uncertainty range and distribution of each input parameter associated with the LBLOCA accident were determined by the PIRT results from the BEMUSE project. The Monte-Carlo method shows that the 95. percentile PCT value can be obtained reliably with a 95% confidence level using the Wilks' formula. The extra margin by the Wilks' formula over the true 95. percentile PCT by the Monte-Carlo method was rather large. Even using the 3 rd order formula, the calculated value using the Wilks' formula is nearly 100 K over the true value. It is shown that, with the ever increasing computational capability, the Monte-Carlo method is accessible for the nuclear power plant safety analysis within a realistic time frame. (authors)
Advanced computational methods for nodal diffusion, Monte Carlo, and S[sub N] problems
Martin, W.R.
1993-01-01
This document describes progress on five efforts for improving effectiveness of computational methods for particle diffusion and transport problems in nuclear engineering: (1) Multigrid methods for obtaining rapidly converging solutions of nodal diffusion problems. A alternative line relaxation scheme is being implemented into a nodal diffusion code. Simplified P2 has been implemented into this code. (2) Local Exponential Transform method for variance reduction in Monte Carlo neutron transport calculations. This work yielded predictions for both 1-D and 2-D x-y geometry better than conventional Monte Carlo with splitting and Russian Roulette. (3) Asymptotic Diffusion Synthetic Acceleration methods for obtaining accurate, rapidly converging solutions of multidimensional SN problems. New transport differencing schemes have been obtained that allow solution by the conjugate gradient method, and the convergence of this approach is rapid. (4) Quasidiffusion (QD) methods for obtaining accurate, rapidly converging solutions of multidimensional SN Problems on irregular spatial grids. A symmetrized QD method has been developed in a form that results in a system of two self-adjoint equations that are readily discretized and efficiently solved. (5) Response history method for speeding up the Monte Carlo calculation of electron transport problems. This method was implemented into the MCNP Monte Carlo code. In addition, we have developed and implemented a parallel time-dependent Monte Carlo code on two massively parallel processors.
Markov Chain Monte Carlo Method without Detailed Balance
Hidemaro Suwa; Synge Todo
2010-10-13
We present a specific algorithm that generally satisfies the balance condition without imposing the detailed balance in the Markov chain Monte Carlo. In our algorithm, the average rejection rate is minimized, and even reduced to zero in many relevant cases. The absence of the detailed balance also introduces a net stochastic flow in a configuration space, which further boosts up the convergence. We demonstrate that the autocorrelation time of the Potts model becomes more than 6 times shorter than that by the conventional Metropolis algorithm. Based on the same concept, a bounce-free worm algorithm for generic quantum spin models is formulated as well.
Densmore, Jeffery D., E-mail: jdd@lanl.gov [Computational Physics and Methods Group, Los Alamos National Laboratory, P.O. Box 1663, MS D409, Los Alamos, NM 87545 (United States); Thompson, Kelly G., E-mail: kgt@lanl.gov [Computational Physics and Methods Group, Los Alamos National Laboratory, P.O. Box 1663, MS D409, Los Alamos, NM 87545 (United States); Urbatsch, Todd J., E-mail: tmonster@lanl.gov [Computational Physics and Methods Group, Los Alamos National Laboratory, P.O. Box 1663, MS D409, Los Alamos, NM 87545 (United States)
2012-08-15
Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations in optically thick media. In DDMC, particles take discrete steps between spatial cells according to a discretized diffusion equation. Each discrete step replaces many smaller Monte Carlo steps, thus improving the efficiency of the simulation. In this paper, we present an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency-integrated diffusion equation for frequencies below a specified threshold, as optical thickness is typically a decreasing function of frequency. Above this threshold we employ standard Monte Carlo, which results in a hybrid transport-diffusion scheme. With a set of frequency-dependent test problems, we confirm the accuracy and increased efficiency of our new DDMC method.
Digitally reconstructed radiograph generation by an adaptive Monte Carlo method.
Li, Xiaoliang; Yang, Jie; Zhu, Yuemin
2006-06-01
Digitally reconstructed radiograph (DRR) generation is an important step in several medical imaging applications such as 2D-3D image registration, where the generation of DRR is a rate-limiting step. We present a novel DRR generation technique, called the adaptive Monte Carlo volume rendering (AMCVR) algorithm. It is based on the conventional Monte Carlo volume rendering (MCVR) technique that is very efficient for rendering large medical datasets. In contrast to the MCVR, the AMCVR does not produce sample points by sampling directly in the entire volume domain. Instead, it adaptively divides the entire volume domain into sub-domains using importance separation and then performs sampling in these sub-domains. As a result, the AMCVR produces almost the same image quality as that obtained with the MCVR while only using half samples, and increases projection speed by a factor of 2. Moreover, the AMCVR is suitable for fast memory addressing, which further improves processing speed. Independent of the size of medical datasets, the AMCVR allows for achieving a frame rate of about 15 Hz on a 2.8 GHz Pentium 4 PC while generating reasonably good quality DRR. PMID:16723763
Bahreyni Toossi, Mohammad Taghi; Ghorbani, Mahdi; Mowlavi, Ali Asghar; Meigooni, Ali Soleimani
2012-01-01
Background Dosimetric characteristics of a high dose rate (HDR) GZP6 Co-60 brachytherapy source have been evaluated following American Association of Physicists in MedicineTask Group 43U1 (AAPM TG-43U1) recommendations for their clinical applications. Materials and methods MCNP-4C and MCNPX Monte Carlo codes were utilized to calculate dose rate constant, two dimensional (2D) dose distribution, radial dose function and 2D anisotropy function of the source. These parameters of this source are compared with the available data for Ralstron 60Co and microSelectron192Ir sources. Besides, a superimposition method was developed to extend the obtained results for the GZP6 source No. 3 to other GZP6 sources. Results The simulated value for dose rate constant for GZP6 source was 1.104±0.03 cGyh-1U-1. The graphical and tabulated radial dose function and 2D anisotropy function of this source are presented here. The results of these investigations show that the dosimetric parameters of GZP6 source are comparable to those for the Ralstron source. While dose rate constant for the two 60Co sources are similar to that for the microSelectron192Ir source, there are differences between radial dose function and anisotropy functions. Radial dose function of the 192Ir source is less steep than both 60Co source models. In addition, the 60Co sources are showing more isotropic dose distribution than the 192Ir source. Conclusions The superimposition method is applicable to produce dose distributions for other source arrangements from the dose distribution of a single source. The calculated dosimetric quantities of this new source can be introduced as input data to the GZP6 treatment planning system (TPS) and to validate the performance of the TPS. PMID:23077455
Order N cluster Monte Carlo method for spin systems with long-range interactions
Kouki Fukui; Synge Todo
2009-01-01
An efficient O(N) cluster Monte Carlo method for Ising models with long-range interactions is presented. Our novel algorithm does not introduce any cutoff for interaction range and thus it strictly fulfills the detailed balance. The realized stochastic dynamics is equivalent to that of the conventional Swendsen–Wang algorithm, which requires O(N2) operations per Monte Carlo sweep if applied to long-range interacting
Time-step limits for a Monte Carlo Compton-scattering method
Densmore, Jeffery D; Warsa, James S; Lowrie, Robert B
2009-01-01
We perform a stability analysis of a Monte Carlo method for simulating the Compton scattering of photons by free electron in high energy density applications and develop time-step limits that avoid unstable and oscillatory solutions. Implementing this Monte Carlo technique in multi physics problems typically requires evaluating the material temperature at its beginning-of-time-step value, which can lead to this undesirable behavior. With a set of numerical examples, we demonstrate the efficacy of our time-step limits.
Kubic, W.L. Jr.; White, A.M. (Los Alamos National Lab., NM (USA); Westinghouse Savannah River Co., Aiken, SC (USA))
1989-01-01
Thermal-hydraulic computer codes represent non-linear functions that may contain discontinuities. Monte Carlo methods are an effective means of accurately evaluating the effect of uncertainty on a nonlinear function with discontinuities, but the computational requirements of standard Monte Carlo methods may be prohibitive. The linear variate Monte Carlo method is a means of reducing the computational requirements. The linear variate method combines the linear response surface method with Monte Carlo analysis to obtain an efficient and accurate method of nonlinear uncertainty analysis. The method is applied to the power limit analysis for the Savannah River Site reactors. 7 refs., 2 figs., 3 tabs.
The S/sub N//Monte Carlo response matrix hybrid method
Filippone, W.L.; Alcouffe, R.E.
1987-01-01
A hybrid method has been developed to iteratively couple S/sub N/ and Monte Carlo regions of the same problem. This technique avoids many of the restrictions and limitations of previous attempts to do the coupling and results in a general and relatively efficient method. We demonstrate the method with some simple examples.
Favorite; Jeffrey A
2002-01-01
The standard implementation of the differential operator (Taylor series) perturbation method for Monte Carlo criticality problems has previously been shown to have a wide range of applicability. In this method, the unperturbed fission distribution is used as a fixed source to estimate the change in the k{sub eff} eigenvalue of a system due to a perturbation. A new method, based
A Monte Carlo Synthetic-Acceleration Method for Solving the Thermal Radiation Diffusion Equation
Evans, Thomas M; Mosher, Scott W; Slattery, Stuart
2014-01-01
We present a novel synthetic-acceleration based Monte Carlo method for solving the equilibrium thermal radiation diusion equation in three dimensions. The algorithm performance is compared against traditional solution techniques using a Marshak benchmark problem and a more complex multiple material problem. Our results show that not only can our Monte Carlo method be an eective solver for sparse matrix systems, but also that it performs competitively with deterministic methods including preconditioned Conjugate Gradient while producing numerically identical results. We also discuss various aspects of preconditioning the method and its general applicability to broader classes of problems.
A Monte Carlo synthetic-acceleration method for solving the thermal radiation diffusion equation
Evans, Thomas M.; Mosher, Scott W.; Slattery, Stuart R.; Hamilton, Steven P.
2014-02-01
We present a novel synthetic-acceleration-based Monte Carlo method for solving the equilibrium thermal radiation diffusion equation in three spatial dimensions. The algorithm performance is compared against traditional solution techniques using a Marshak benchmark problem and a more complex multiple material problem. Our results show that our Monte Carlo method is an effective solver for sparse matrix systems. For solutions converged to the same tolerance, it performs competitively with deterministic methods including preconditioned conjugate gradient and GMRES. We also discuss various aspects of preconditioning the method and its general applicability to broader classes of problems.
Neutron matter at zero temperature with an auxiliary field diffusion Monte Carlo method
NASA Astrophysics Data System (ADS)
Sarsa, A.; Fantoni, S.; Schmidt, K. E.; Pederiva, F.
2003-08-01
The recently developed auxiliary field diffusion Monte Carlo method is applied to compute the equation of state and the compressibility of neutron matter. By combining diffusion Monte Carlo method for the spatial degrees of freedom and auxiliary field Monte Carlo method to separate the spin-isospin operators, quantum Monte Carlo can be used to simulate the ground state of many-nucleon systems (A?100). We use a path constraint to control the fermion sign problem. We have made simulations for realistic interactions, which include tensor and spin-orbit two-body potentials as well as three-nucleon forces. The Argonne v'8 and v'6 two-nucleon potentials plus the Urbana or Illinois three-nucleon potentials have been used in our calculations. We compare with fermion hypernetted chain results. We report on the results of a periodic box fermi hypernetted chain calculation, which is also used to estimate the finite size corrections to our quantum Monte Carlo simulations. Our auxiliary field diffusion Monte Carlo (AFDMC) results for v6 models of pure neutron matter are in reasonably good agreement with equivalent correlated basis function (CBF) calculations, providing energies per particle which are slightly lower than the CBF ones. However, the inclusion of the spin-orbit force leads to quite different results particularly at relatively high densities. The resulting equation of state from AFDMC calculations is harder than the one from previous Fermi hypernetted chain studies commonly used to determine the neutron star structure.
Monte Carlo Methods to Model Radiation Interactions and Induced Damage
NASA Astrophysics Data System (ADS)
Muñoz, Antonio; Fuss, Martina C.; Cortés-Giraldo, M. A.; Incerti, Sébastien; Ivanchenko, Vladimir; Ivanchenko, Anton; Quesada, J. M.; Salvat, Francesc; Champion, Christophe; Gómez-Tejedor, Gustavo García
This review is devoted to the analysis of some Monte Carlo (MC) simulation programmes which have been developed to describe radiation interaction with biologically relevant materials. Current versions of the MC codes Geant4 (GEometry ANd Tracking 4), PENELOPE (PENetration and Energy Loss of Positrons and Electrons), EPOTRAN (Electron and POsitron TRANsport), and LEPTS (Low-Energy Particle Track Simulation) are described. Mean features of each model, as the type of radiation to consider, the energy range covered by primary and secondary particles, the type of interactions included in the simulation and the considered target geometries are discussed. Special emphasis lies on recent developments that, together with (still emerging) new databases that include adequate data for biologically relevant materials, bring us continuously closer to a realistic, physically meaningful description of radiation damage in biological tissues.
Bold diagrammatic Monte Carlo method applied to fermionized frustrated spins.
Kulagin, S A; Prokof'ev, N; Starykh, O A; Svistunov, B; Varney, C N
2013-02-15
We demonstrate, by considering the triangular lattice spin-1/2 Heisenberg model, that Monte Carlo sampling of skeleton Feynman diagrams within the fermionization framework offers a universal first-principles tool for strongly correlated lattice quantum systems. We observe the fermionic sign blessing--cancellation of higher order diagrams leading to a finite convergence radius of the series. We calculate the magnetic susceptibility of the triangular-lattice quantum antiferromagnet in the correlated paramagnet regime and reveal a surprisingly accurate microscopic correspondence with its classical counterpart at all accessible temperatures. The extrapolation of the observed relation to zero temperature suggests the absence of the magnetic order in the ground state. We critically examine the implications of this unusual scenario. PMID:25166359
Monte Carlo Collision method for low temperature plasma simulation
NASA Astrophysics Data System (ADS)
Taccogna, Francesco
2015-01-01
This work shows the basic foundation of the particle-based representation of low temperature plasma description. In particular, the Monte Carlo Collision (MCC) recipe has been described for the case of electron-atom and ion-atom collisions. The model has been applied to the problem of plasma plume expansion from an electric Hall-effect type thruster. The presence of low energy secondary electrons from electron-atom ionization on the electron energy distribution function (EEDF) have been identified in the first 3 mm from the exit plane where, due to the azimuthal heating the ionization continues to play an important role. In addition, low energy charge-exchange ions from ion-atom electron transfer collisions are evident in the ion energy distribution functions (IEDF) 1 m from the exit plane.
Bold Diagrammatic Monte Carlo Method Applied to Fermionized Frustrated Spins
NASA Astrophysics Data System (ADS)
Kulagin, S. A.; Prokof'ev, N.; Starykh, O. A.; Svistunov, B.; Varney, C. N.
2013-02-01
We demonstrate, by considering the triangular lattice spin-1/2 Heisenberg model, that Monte Carlo sampling of skeleton Feynman diagrams within the fermionization framework offers a universal first-principles tool for strongly correlated lattice quantum systems. We observe the fermionic sign blessing—cancellation of higher order diagrams leading to a finite convergence radius of the series. We calculate the magnetic susceptibility of the triangular-lattice quantum antiferromagnet in the correlated paramagnet regime and reveal a surprisingly accurate microscopic correspondence with its classical counterpart at all accessible temperatures. The extrapolation of the observed relation to zero temperature suggests the absence of the magnetic order in the ground state. We critically examine the implications of this unusual scenario.
Perfetti, Christopher M; Martin, William R; Rearden, Bradley T; Williams, Mark L
2012-01-01
Three methods for calculating continuous-energy eigenvalue sensitivity coefficients were developed and implemented into the SHIFT Monte Carlo code within the Scale code package. The methods were used for several simple test problems and were evaluated in terms of speed, accuracy, efficiency, and memory requirements. A promising new method for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was developed and produced accurate sensitivity coefficients with figures of merit that were several orders of magnitude larger than those from existing methods.
Kharrati, Hedi; Agrebi, Amel; Karaoui, Mohamed-Karim [Ecole Superieure des Sciences et Techniques de la Sante de Monastir, Avenue Avicenne 5000 Monastir (Tunisia); Faculte des Sciences de Monastir (Tunisia)
2007-04-15
X-ray buildup factors of lead in broad beam geometry for energies from 15 to 150 keV are determined using the general purpose Monte Carlo N-particle radiation transport computer code (MCNP4C). The obtained buildup factors data are fitted to a modified three parameter Archer et al. model for ease in calculating the broad beam transmission with computer at any tube potentials/filters combinations in diagnostic energies range. An example for their use to compute the broad beam transmission at 70, 100, 120, and 140 kVp is given. The calculated broad beam transmission is compared to data derived from literature, presenting good agreement. Therefore, the combination of the buildup factors data as determined and a mathematical model to generate x-ray spectra provide a computationally based solution to broad beam transmission for lead barriers in shielding x-ray facilities.
Particle Monte Carlo methods in statistical learning and rare event simulation
Del Moral , Pierre
Particle Monte Carlo methods in statistical learning and rare event simulation P. Del Moral (INRIA Some hyper-refs Feynman-Kac formulae, Genealogical & Interacting Particle Systems with appl., Springer/delmoral/index.html [+ Links] #12;Stochastic particle sampling methods Interacting jumps models Genetic type interacting
Improved methods of handling massive tallies in reactor Monte Carlo Code RMC
She, D.; Wang, K.; Sun, J.; Qiu, Y.
2013-07-01
Monte Carlo simulations containing a large number of tallies generally suffer severe performance penalties due to a significant amount of run time spent in searching for and scoring individual tally bins. This paper describes the improved methods of handling large numbers of tallies, which have been implemented in the RMC Monte Carlo code. The calculation results demonstrate that the proposed methods can considerably improve the tally performance when massive tallies are treated. In the calculated case with 6 million of tally regions, only 10% of run time is increased in each active cycle against each inactive cycle. (authors)
Advantages of Analytical Transformations in Monte Carlo Methods for Radiation Transport
McKinley, M S; Brooks III, E D; Daffin, F
2004-12-13
Monte Carlo methods for radiation transport typically attempt to solve an integral by directly sampling analog or weighted particles, which are treated as physical entities. Improvements to the methods involve better sampling, probability games or physical intuition about the problem. We show that significant improvements can be achieved by recasting the equations with an analytical transform to solve for new, non-physical entities or fields. This paper looks at one such transform, the difference formulation for thermal photon transport, showing a significant advantage for Monte Carlo solution of the equations for time dependent transport. Other related areas are discussed that may also realize significant benefits from similar analytical transformations.
High-order path-integral Monte Carlo methods for solving quantum dot problems
NASA Astrophysics Data System (ADS)
Chin, Siu A.
2015-03-01
The conventional second-order path-integral Monte Carlo method is plagued with the sign problem in solving many-fermion systems. This is due to the large number of antisymmetric free-fermion propagators that are needed to extract the ground state wave function at large imaginary time. In this work we show that optimized fourth-order path-integral Monte Carlo methods, which use no more than five free-fermion propagators, can yield accurate quantum dot energies for up to 20 polarized electrons with the use of the Hamiltonian energy estimator.
Quasi-Monte Carlo methods for elliptic PDEs with random coefficients and applications
NASA Astrophysics Data System (ADS)
Graham, I. G.; Kuo, F. Y.; Nuyens, D.; Scheichl, R.; Sloan, I. H.
2011-05-01
We devise and implement quasi-Monte Carlo methods for computing the expectations of nonlinear functionals of solutions of a class of elliptic partial differential equations with random coefficients. Our motivation comes from fluid flow in random porous media, where relevant functionals include the fluid pressure/velocity at any point in space or the breakthrough time of a pollution plume being transported by the velocity field. Our emphasis is on situations where a very large number of random variables is needed to model the coefficient field. As an alternative to classical Monte Carlo, we here employ quasi-Monte Carlo methods, which use deterministically chosen sample points in an appropriate (usually high-dimensional) parameter space. Each realization of the PDE solution requires a finite element (FE) approximation in space, and this is done using a realization of the coefficient field restricted to a suitable regular spatial grid (not necessarily the same as the FE grid). In the statistically homogeneous case the corresponding covariance matrix can be diagonalized and the required coefficient realizations can be computed efficiently using FFT. In this way we avoid the use of a truncated Karhunen-Loève expansion, but introduce high nominal dimension in parameter space. Numerical experiments with 2-dimensional rough random fields, high variance and small length scale are reported, showing that the quasi-Monte Carlo method consistently outperforms the Monte Carlo method, with a smaller error and a noticeably better than O(N) convergence rate, where N is the number of samples. Moreover, the rate of convergence of the quasi-Monte Carlo method does not appear to degrade as the nominal dimension increases. Examples with dimension as high as 10 6 are reported.
Alcouffe, R.E.
1985-01-01
A difficult class of problems for the discrete-ordinates neutral particle transport method is to accurately compute the flux due to a spatially localized source. Because the transport equation is solved for discrete directions, the so-called ray effect causes the flux at space points far from the source to be inaccurate. Thus, in general, discrete ordinates would not be the method of choice to solve such problems. It is better suited for calculating problems with significant scattering. The Monte Carlo method is suited to localized source problems, particularly if the amount of collisional interactions in minimal. However, if there are many scattering collisions and the flux at all space points is desired, then the Monte Carlo method becomes expensive. To take advantage of the attributes of both approaches, we have devised a first collision source method to combine the Monte Carlo and discrete-ordinates solutions. That is, particles are tracked from the source to their first scattering collision and tallied to produce a source for the discrete-ordinates calculation. A scattered flux is then computed by discrete ordinates, and the total flux is the sum of the Monte Carlo and discrete ordinates calculated fluxes. In this paper, we present calculational results using the MCNP and TWODANT codes for selected two-dimensional problems that show the effectiveness of this method.
Markov Chain Mote Carlo solution of BK equation through Newton-Kantorovich method
Krzysztof Bozek; Krzysztof Kutak; Wieslaw Placzek
2013-06-28
We propose a new method for Monte Carlo solution of non-linear integral equations by combining the Newton-Kantorovich method for solving non-linear equations with the Markov Chain Monte Carlo (MCMC) method for solving linear equations. The Newton-Kantorovich method allows to express the non-linear equation as a system of the linear equations which then can be treated by the MCMC (random walk) algorithm. We apply this method to the Balitsky-Kovchegov (BK) equation describing evolution of gluon density at low x. Results of numerical computations show that the MCMC method is both precise and efficient. The presented algorithm may be particularly suited for solving more complicated and higher-dimensional non-linear integral equation, for which traditional methods become unfeasible.
Revised methods for few-group cross sections generation in the Serpent Monte Carlo code
Fridman, E. [Reactor Safety Div., Helmholz-Zentrum Dresden-Rossendorf, POB 51 01 19, Dresden, 01314 (Germany); Leppaenen, J. [VTT Technical Research Centre of Finland, POB 1000, FI-02044 VTT (Finland)
2012-07-01
This paper presents new calculation methods, recently implemented in the Serpent Monte Carlo code, and related to the production of homogenized few-group constants for deterministic 3D core analysis. The new methods fall under three topics: 1) Improved treatment of neutron-multiplying scattering reactions, 2) Group constant generation in reflectors and other non-fissile regions and 3) Homogenization in leakage-corrected criticality spectrum. The methodology is demonstrated by a numerical example, comparing a deterministic nodal diffusion calculation using Serpent-generated cross sections to a reference full-core Monte Carlo simulation. It is concluded that the new methodology improves the results of the deterministic calculation, and paves the way for Monte Carlo based group constant generation. (authors)
NASA Astrophysics Data System (ADS)
Clark, M. M.; Scott, H. L.
1996-03-01
Because of steric overlap, conventional Monte Carlo methods are very inefficient for the simulation of lipid interactions at fluid lipid bilayer densities. However, the configurational bias Monte Carlo (CBMC) sampling algorithm(J. Siepmann and D. Frenkel, Molecular Physics 75), 59, 1992. can potentially accelerate convergence of Monte Carlo simulations by many orders of magnitude. As an intermediate step in the process of extending a statistical mechanical model for the gel-to-ripple phase of a lipid bilayer(W. S. McCullough, J. H. H. Perk, and H. L. Scott, J. Chem. Phys. 93), 6070, 1990. to include the ripple-to-fluid phase transition, we calculate interaction energies between disordered lipid molecule pairs utilizing the CBMC method to sample chain configurations. We present the calculated order parameters, gauche bond distribution, and other structural data. These results are compared to results from other simulations and experiment.
Smith, Leon E.; Gesh, Christopher J.; Pagh, Richard T.; Miller, Erin A.; Shaver, Mark W.; Ashbaker, Eric D.; Batdorf, Michael T.; Ellis, J. E.; Kaye, William R.; McConn, Ronald J.; Meriwether, George H.; Ressler, Jennifer J.; Valsan, Andrei B.; Wareing, Todd A.
2008-10-31
Radiation transport modeling methods used in the radiation detection community fall into one of two broad categories: stochastic (Monte Carlo) and deterministic. Monte Carlo methods are typically the tool of choice for simulating gamma-ray spectrometers operating in homeland and national security settings (e.g. portal monitoring of vehicles or isotope identification using handheld devices), but deterministic codes that discretize the linear Boltzmann transport equation in space, angle, and energy offer potential advantages in computational efficiency for many complex radiation detection problems. This paper describes the development of a scenario simulation framework based on deterministic algorithms. Key challenges include: formulating methods to automatically define an energy group structure that can support modeling of gamma-ray spectrometers ranging from low to high resolution; combining deterministic transport algorithms (e.g. ray-tracing and discrete ordinates) to mitigate ray effects for a wide range of problem types; and developing efficient and accurate methods to calculate gamma-ray spectrometer response functions from the deterministic angular flux solutions. The software framework aimed at addressing these challenges is described and results from test problems that compare coupled deterministic-Monte Carlo methods and purely Monte Carlo approaches are provided.
Stabilizing canonical-ensemble calculations in the auxiliary-field Monte Carlo method
NASA Astrophysics Data System (ADS)
Gilbreth, C. N.; Alhassid, Y.
2015-03-01
Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the auxiliary-field Monte Carlo (AFMC) method, low-temperature or large-model-space calculations require numerically stabilized matrix multiplication. When adapting methods used in the grand-canonical ensemble to the canonical ensemble of fixed particle number, the numerical stabilization increases the number of required floating-point operations for computing observables by a factor of the size of the single-particle model space, and thus can greatly limit the systems that can be studied. We describe an improved method for stabilizing canonical-ensemble calculations in AFMC that exhibits better scaling, and present numerical tests that demonstrate the accuracy and improved performance of the method.
Advanced Monte Carlo Methods for Eigenvalue Sensitivity Coefficient Calculations
NASA Astrophysics Data System (ADS)
Perfetti, Christopher Michael
The need to perform eigenvalue sensitivity and uncertainty analysis with greater fidelity for more complex systems has motivated the extension of the current multigroup sensitivity coefficient methodologies to continuous-energy applications. This research presents a survey of existing eigenvalue sensitivity coefficient methods, and develops two new approaches for sensitivity coefficient calculations. The newly-developed CLUTCH sensitivity method has demonstrated the ability to accurately and efficiently calculate sensitivity coefficients for a set of multigroup test problems, and has shown potential for future continuous-energy calculations. The accuracy, speed, efficiency, and memory requirements of the different sensitivity methods are quantified for a set of well-known criticality safety test problems, and the strengths and weaknesses of each method are assessed. The CLUTCH method requires a weighting function to tally the importance of neutronic reactions, and this research quantifies the level of accuracy needed by this weighting function to successfully calculate sensitivity coefficients. Lastly, general recommendations on the applicability of each sensitivity coefficient are given, and future approaches to improve the performance and of the methods are offered.
Application of quantum Monte Carlo methods to excitonic and electronic systems
Lee, Robert
2011-07-12
The work in this thesis is concerned with the application and development of quantum Monte Carlo (QMC) methods. We begin by proposing a technique to maximise the efficiency of the extrapolation of DMC results to zero time step, finding that a...
Uncertainty Analysis in Upscaling Well Log data By Markov Chain Monte Carlo Method
Hwang, Kyubum
2010-01-16
. . . . . . . . . . 2 1.2.1 Fundamentals . . . . . . . . . . . . . . . . . . . . 2 1.2.2 Previous Works . . . . . . . . . . . . . . . . . . . 5 1.3 Uncertainty Problem in Upscaling . . . . . . . . . . . . 7 1.3.1 Cause and Classification . . . . . . . . . . . . . . 7 1.3... MARKOV CHAIN MONTE CARLO (MCMC) METHOD . . . 12 2.1 Concept . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3 The Acceptance Probability . . . . . . . . . . . . . . . 15 2.4 Main...
Monte Carlo Methods for Equilibrium and Nonequilibrium Problems in Interfacial Electrochemistry
Gregory Brown; Per Arne Rikvold; S. J. Mitchell; M. A. Novotny
1998-05-11
We present a tutorial discussion of Monte Carlo methods for equilibrium and nonequilibrium problems in interfacial electrochemistry. The discussion is illustrated with results from simulations of three specific systems: bromine adsorption on silver (100), underpotential deposition of copper on gold (111), and electrodeposition of urea on platinum (100).
ERIC Educational Resources Information Center
Dumenci, Levent; Windle, Michael
2001-01-01
Used Monte Carlo methods to evaluate the adequacy of cluster analysis to recover group membership based on simulated latent growth curve (LCG) models. Cluster analysis failed to recover growth subtypes adequately when the difference between growth curves was shape only. Discusses circumstances under which it was more successful. (SLD)
ERIC Educational Resources Information Center
Kim, Jee-Seon; Bolt, Daniel M.
2007-01-01
The purpose of this ITEMS module is to provide an introduction to Markov chain Monte Carlo (MCMC) estimation for item response models. A brief description of Bayesian inference is followed by an overview of the various facets of MCMC algorithms, including discussion of prior specification, sampling procedures, and methods for evaluating chain…
Bayesian Phylogenetic Inference Using DNA Sequences: A Markov Chain Monte Carlo Method
Ziheng Yang; Bruce Rannala
An improved Bayesian method is presented for estimating phylogenetic trees using DNA sequence data. The birth- death process with species sampling is used to specify the prior distribution of phylogenies and ancestral speciation times, and the posterior probabilities of phylogenies are used to estimate the maximum posterior probability (MAP) tree. Monte Carlo integration is used to integrate over the ancestral
A hybrid multiscale kinetic Monte Carlo method for simulation of copper electrodeposition q
for speeding up the simulation of copper electrodeposit- ion is presented. The fast diffusion eventsA hybrid multiscale kinetic Monte Carlo method for simulation of copper electrodeposition q Zheming are simulated deterministically with a heterogeneous diffusion model which con- siders site-blocking effects
Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains
Columbia University
Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains Yashar Ahmadian1 , Jonathan W. Pillow2 and Liam Paninski3 1 Department of Statistics, Columbia University 2 Departments of Psychology and Neurobiology, University of Texas at Austin 3 Department of Statistics and Center
Investigating the Limits of Monte Carlo Tree Search Methods in Computer Go
Müller, Martin
Investigating the Limits of Monte Carlo Tree Search Methods in Computer Go Shih-Chieh Huang1 progress in Com- puter Go. Still, program performance is uneven - most current Go pro- grams are much techniques, several conjectures regard- ing the behavior of MCTS-based Go programs in specific types of Go
Novel approach to modeling spectral-domain optical coherence tomography with Monte Carlo method
NASA Astrophysics Data System (ADS)
Kraszewski, Maciej; Trojanowski, Michal; Strakowski, Marcin; Pluci?ski, Jerzy; Kosmowski, Bogdan B.
2014-05-01
Numerical modeling Optical Coherence Tomography (OCT) systems is needed for optical setup optimization, development of new signal processing methods and assessment of impact of different physical phenomena inside the sample on OCT signal. The Monte Carlo method has been often used for modeling Optical Coherence Tomography, as it is a well established tool for simulating light propagation in scattering media. However, in this method light is modeled as a set of energy packets traveling along straight lines. This reduces accuracy of Monte Carlo calculations in case of simulating propagation of dopeds. Since such beams are commonly used in OCT systems, classical Monte Carlo algorithm need to be modified. In presented research, we have developed model of SD-OCT systems using combination of Monte Carlo and analytical methods. Our model includes properties of optical setup of OCT system, which is often omitted in other research. We present applied algorithms and comparison of simulation results with SD-OCT scans of optical phantoms. We have found that our model can be used for determination of level of OCT signal coming from scattering particles inside turbid media placed in different positions relatively to focal point of incident light beam. It may improve accuracy of simulating OCT systems.
Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water
ERIC Educational Resources Information Center
Gergely, John Robert
2009-01-01
Obtaining an accurate microscopic description of water structure and dynamics is of great interest to molecular biology researchers and in the physics and quantum chemistry simulation communities. This dissertation describes efforts to apply quantum Monte Carlo methods to this problem with the goal of making progress toward a fully "ab initio"…
Comparison of Eulerian and Lagrangian Monte Carlo PDF methods for turbulent diffusion flames
H. Möbus; P. Gerlinger; D. Brüggemann
2001-01-01
Methods based on Monte Carlo solutions of the transport equation for the joint probability density function (pdf) of scalars are considered to be among the most promising approaches for modeling turbulent reactive flows. For the treatment of convection and diffusion two approaches are well established, either from Eulerian or Lagrangian point of view. Simply speaking, the former is computationally less
NASA Astrophysics Data System (ADS)
Ballone, P.; Umrigar, C. J.; Delaly, P.
1992-03-01
By the variational Monte Carlo technique, we determine accurate wave functions for N electrons (N<=20) confined by the electrostatic potential of positively charged jellium spheres. The quality of the wave functions is tested by the diffusion Monte Carlo method. This shows that 90% of the fixed-node correlation energy is recovered by the variational computation. We analyze the electron-electron correlation functions and we compare the density, the total, exchange, and correlation energies, and ionization potentials to the predictions of the local-density approximation to density-functional theory.
Power Analysis for Complex Mediational Designs Using Monte Carlo Methods
ERIC Educational Resources Information Center
Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.
2010-01-01
Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex…
On Performance Measures for Infinite Swapping Monte Carlo Methods
J. D. Doll; Paul Dupuis
2014-10-14
We introduce and illustrate a number of performance measures for rare-event sampling methods. These measures are designed to be of use in a variety of expanded ensemble techniques including parallel tempering as well as infinite and partial infinite swapping approaches. Using a variety of selected applications we address questions concerning the variation of sampling performance with respect to key computational ensemble parameters.
Monte Carlo Methods for Maximum Margin Supervised Topic Models
Xing, Eric P.
of Intelligent Tech. & Sys., Tsinghua University, Beijing 100084, China School of Computer Science, Carnegie- vex dual formulation. We report thorough experimental results that compare our approach favorably constraints have been exclusively on the variational methods [7] usually with a strict mean-field assumption
On performance measures for infinite swapping Monte Carlo methods
NASA Astrophysics Data System (ADS)
Doll, J. D.; Dupuis, Paul
2015-01-01
We introduce and illustrate a number of performance measures for rare-event sampling methods. These measures are designed to be of use in a variety of expanded ensemble techniques including parallel tempering as well as infinite and partial infinite swapping approaches. Using a variety of selected applications, we address questions concerning the variation of sampling performance with respect to key computational ensemble parameters.
NASA Astrophysics Data System (ADS)
Nakamoto, Takamichi
Our group has studied an odor sensing system using an array of Quartz Crystal Microbalance (QCM) gas sensors and neural-network pattern recognition. In this odor sensing system, it is important to know the properties of sensing films coated on Quartz Crystal Microbalance electrodes. These sensing films have not been experimentally characterized well enough to predict the sensor response. We have investigated the predictions of sensor responses using a computational chemistry method, Grand Canonical Monte Carlo (GCMC) simulations. We have successfully predicted the amount of sorption using this method. The GCMC method requires no empirical parameters, unlike many other prediction methods used for QCM based sensor response modeling. In this chapter, the Grand Canonical Monte Carlo method is reviewed to predict the response of QCM gas sensor, and the modeling results are compared with experiments.
Wenner, Michael T.; Haghighat, Alireza; Gardner, Shane
2001-06-17
A methodology to use the solution of a deterministic multigroup S{sub n} transport code as the source distribution for a Monte Carlo criticality calculation is discussed. This methodology is referred to as the S{sub n} Source Initialization method. The effectiveness of this methodology is measured by simulating a loosely coupled benchmark, where standard Monte Carlo codes have shown a bias. The Monte Carlo N-Particle transport code MCNP and PENTRAN (three-dimensional parallel, multigroup, S{sub n}) transport code system were used. The PENTRAN code solution is used as a starting source distribution in the MCNP code, thereby decreasing the necessary active cycle length. The methodology was verified on the basis of a sample benchmark problem of a lattice of 5x5x1 highly enriched uranium metal spheres surrounded by air.
A Monte Carlo method for calculating Bayesian uncertainties in internal dosimetry.
Puncher, M; Birchall, A
2008-01-01
This paper presents a novel Monte Carlo method (WeLMoS, Weighted Likelihood Monte-Carlo sampling method) that has been developed to perform Bayesian analyses of monitoring data. The WeLMoS method randomly samples parameters from continuous prior probability distributions and then weights each vector by its likelihood (i.e. its goodness of fit to the measurement data). Furthermore, in order to quality assure the method, and assess its strengths and weaknesses, a second method (MCMC, Markov chain Monte Carlo) has also been developed. The MCMC method uses the Metropolis algorithm to sample directly from the posterior distribution of parameters. The methods are evaluated and compared using an artificially generated case involving an exposure to a plutonium nitrate aerosol. In addition to calculating the uncertainty on internal dose, the methods can also calculate the probability distribution of model parameter values given the observed data. In other words, the techniques provide a powerful tool to obtain the estimates of parameter values that best fit the data and the associated uncertainty on these estimates. Current applications of the methodology, including the determination of lung solubility parameters, from volunteer and cohort data, are also discussed. PMID:18806256
Reducing uncertainty in site characterization using Bayes Monte Carlo methods
Sohn, Michael D.; Small, Mitchell J.; Pantazidou, Marina
2004-04-28
A Bayesian uncertainty analysis approach is developed as a tool for assessing and reducing uncertainty in ground-water flow and chemical transport predictions. The method is illustrated for a site contaminated with chlorinated hydrocarbons. Uncertainty in source characterization, in chemical transport parameters, and in the assumed hydrogeologic structure was evaluated using engineering judgment and updated using observed field data. The updating approach using observed hydraulic head data was able to differentiate between reasonable and unreasonable hydraulic conductivity fields but could not differentiate between alternative conceptual models for the geological structure of the subsurface at the site. Updating using observed chemical concentration data reduced the uncertainty in most parameters and reduced uncertainty in alternative conceptual models describing the geological structure at the site, source locations, and the chemicals released at these sources. Thirty-year transport projections for no-action and source containment scenarios demonstrate a typical application of the methods.
On performance measures for infinite swapping Monte Carlo methods.
Doll, J D; Dupuis, Paul
2015-01-14
We introduce and illustrate a number of performance measures for rare-event sampling methods. These measures are designed to be of use in a variety of expanded ensemble techniques including parallel tempering as well as infinite and partial infinite swapping approaches. Using a variety of selected applications, we address questions concerning the variation of sampling performance with respect to key computational ensemble parameters. PMID:25591342
A Monte Carlo implementation of the predictor-corrector Quasi-Static method
Hackemack, M. W.; Ragusa, J. C.; Griesheimer, D. P.; Pounders, J. M.
2013-07-01
The Quasi-Static method (QS) is a useful tool for solving reactor transients since it allows for larger time steps when updating neutron distributions. Because of the beneficial attributes of Monte Carlo (MC) methods (exact geometries and continuous energy treatment), it is desirable to develop a MC implementation for the QS method. In this work, the latest version of the QS method known as the Predictor-Corrector Quasi-Static method is implemented. Experiments utilizing two energy-groups provide results that show good agreement with analytical and reference solutions. The method as presented can easily be implemented in any continuous energy, arbitrary geometry, MC code. (authors)
NASA Astrophysics Data System (ADS)
Kim, Minho; Lee, Hyounggun; Kim, Hyosim; Park, Hongmin; Lee, Wonho; Park, Sungho
2014-03-01
This study evaluated the Monte Carlo method for determining the dose calculation in fluoroscopy by using a realistic human phantom. The dose was calculated by using Monte Carlo N-particle extended (MCNPX) in simulations and was measured by using Korean Typical Man-2 (KTMAN-2) phantom in the experiments. MCNPX is a widely-used simulation tool based on the Monte-Carlo method and uses random sampling. KTMAN-2 is a virtual phantom written in MCNPX language and is based on the typical Korean man. This study was divided into two parts: simulations and experiments. In the former, the spectrum generation program (SRS-78) was used to obtain the output energy spectrum for fluoroscopy; then, each dose to the target organ was calculated using KTMAN-2 with MCNPX. In the latter part, the output of the fluoroscope was calibrated first and TLDs (Thermoluminescent dosimeter) were inserted in the ART (Alderson Radiation Therapy) phantom at the same places as in the simulation. Thus, the phantom was exposed to radiation, and the simulated and the experimental doses were compared. In order to change the simulation unit to the dose unit, we set the normalization factor (NF) for unit conversion. Comparing the simulated with the experimental results, we found most of the values to be similar, which proved the effectiveness of the Monte Carlo method in fluoroscopic dose evaluation. The equipment used in this study included a TLD, a TLD reader, an ART phantom, an ionization chamber and a fluoroscope.
Chung, Kiwhan
1996-01-01
While the use of Monte Carlo method has been prevalent in nuclear engineering, it has yet to fully blossom in the study of solute transport in porous media. By using an etched-glass micromodel, an attempt is made to apply Monte Carlo method...
Neutron-Gamma-ray-coupled albedo Monte Carlo method streaming analysis
Yamauchi, M.; Kawai, M.; Seki, Y.
1986-11-01
The neutron-gamma-ray-coupled albedo Monte Carlo (AMC) method has been developed and implemented in MORSE-I. The energy- and angle-dependent differential albedo data, which include secondary gamma rays, are calculated for a slab layer with one dimensional transport theory. Fundamental formulas for this method are described. The applicability to shielding design of fusion reactors is confirmed by analyzing the radiation streaming experiment conducted at the Fusion Neutronics Source facility, Japan Atomic Energy Research Institute. The AMC method has reproduced well the experimental data of radiation dose rates and spectra with an accuracy of approximately 10%. It is shown that the AMC method is several times more efficient than the ordinary Monte Carlo calculation in obtaining data necessary for the design with expected accuracy.
A high-order photon Monte Carlo method for radiative transfer in direct numerical simulation
Wu, Y.; Modest, M.F.; Haworth, D.C. . E-mail: dch12@psu.edu
2007-05-01
A high-order photon Monte Carlo method is developed to solve the radiative transfer equation. The statistical and discretization errors of the computed radiative heat flux and radiation source term are isolated and quantified. Up to sixth-order spatial accuracy is demonstrated for the radiative heat flux, and up to fourth-order accuracy for the radiation source term. This demonstrates the compatibility of the method with high-fidelity direct numerical simulation (DNS) for chemically reacting flows. The method is applied to address radiative heat transfer in a one-dimensional laminar premixed flame and a statistically one-dimensional turbulent premixed flame. Modifications of the flame structure with radiation are noted in both cases, and the effects of turbulence/radiation interactions on the local reaction zone structure are revealed for the turbulent flame. Computational issues in using a photon Monte Carlo method for DNS of turbulent reacting flows are discussed.
Linear scaling electronic structure Monte Carlo method for metals
NASA Astrophysics Data System (ADS)
Krajewski, Florian R.; Parrinello, Michele
2007-06-01
We present a method for sampling the Boltzmann distribution of a system in which the interionic interactions are derived from empirical or semiempirical electronic structure calculations within the Born-Oppenheimer approximation. We considerably improve on a scheme presented earlier [F. R. Krajewski and M. Parrinello, Phys. Rev. B 73, 041105(R) (2006)]. To this effect, we use an expression for the partition function in which electronic and ionic degrees of freedom are treated on the same footing. In addition, we introduce an auxiliary set of fields in such a way that the sampling of the partition function scales linearly with system size. We demonstrate the validity of this approach on tight-binding models of carbon nanotubes and silicon in its liquid and crystalline phases.
Searching therapeutic agents for treatment of Alzheimer disease using the Monte Carlo method.
Toropova, Mariya A; Toropov, Andrey A; Raška, Ivan; Rašková, Mária
2015-09-01
Quantitative structure - activity relationships (QSARs) for the pIC50 (binding affinity) of gamma-secretase inhibitors can be constructed with the Monte Carlo method using CORAL software (http://www.insilico.eu/coral). The considerable influence of the presence of rings of various types with respect to the above endpoint has been detected. The mechanistic interpretation and the domain of applicability of the QSARs are discussed. Methods to select new potential gamma-secretase inhibitors are suggested. PMID:26164035
Perfetti, C.; Martin, W.; Rearden, B.; Williams, M.
2012-07-01
Three methods for calculating continuous-energy eigenvalue sensitivity coefficients were developed and implemented into the Shift Monte Carlo code within the SCALE code package. The methods were used for two small-scale test problems and were evaluated in terms of speed, accuracy, efficiency, and memory requirements. A promising new method for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was developed and produced accurate sensitivity coefficients with figures of merit that were several orders of magnitude larger than those from existing methods. (authors)
NASA Astrophysics Data System (ADS)
Zhang, Xiaofeng
2012-03-01
Image formation in fluorescence diffuse optical tomography is critically dependent on construction of the Jacobian matrix. For clinical and preclinical applications, because of the highly heterogeneous characteristics of the medium, Monte Carlo methods are frequently adopted to construct the Jacobian. Conventional adjoint Monte Carlo method typically compute the Jacobian by multiplying the photon density fields radiated from the source at the excitation wavelength and from the detector at the emission wavelength. Nonetheless, this approach assumes that the source and the detector in Green's function are reciprocal, which is invalid in general. This assumption is particularly questionable in small animal imaging, where the mean free path length of photons is typically only one order of magnitude smaller than the representative dimension of the medium. We propose a new method that does not rely on the reciprocity of the source and the detector by tracing photon propagation entirely from the source to the detector. This method relies on the perturbation Monte Carlo theory to account for the differences in optical properties of the medium at the excitation and the emission wavelengths. Compared to the adjoint methods, the proposed method is more valid in reflecting the physical process of photon transport in diffusive media and is more efficient in constructing the Jacobian matrix for densely sampled configurations.
Frequency-domain Monte Carlo method for linear oscillatory gas flows
NASA Astrophysics Data System (ADS)
Ladiges, Daniel R.; Sader, John E.
2015-03-01
Gas flows generated by resonating nanoscale devices inherently occur in the non-continuum, low Mach number regime. Numerical simulations of such flows using the standard direct simulation Monte Carlo (DSMC) method are hindered by high statistical noise, which has motivated the development of several alternate Monte Carlo methods for low Mach number flows. Here, we present a frequency-domain low Mach number Monte Carlo method based on the Boltzmann-BGK equation, for the simulation of oscillatory gas flows. This circumvents the need for temporal simulations, as is currently required, and provides direct access to both amplitude and phase information using a pseudo-steady algorithm. The proposed method is validated for oscillatory Couette flow and the flow generated by an oscillating sphere. Good agreement is found with an existing time-domain method and accurate numerical solutions of the Boltzmann-BGK equation. Analysis of these simulations using a rigorous statistical approach shows that the frequency-domain method provides a significant improvement in computational speed.
On a Monte Carlo method for measurement uncertainty evaluation and its implementation
NASA Astrophysics Data System (ADS)
Harris, P. M.; Cox, M. G.
2014-08-01
The ‘Guide to the Expression of Uncertainty in Measurement’ (GUM) provides a framework and procedure for evaluating and expressing measurement uncertainty. The procedure has two main limitations. Firstly, the way a coverage interval is constructed to contain values of the measurand with a stipulated coverage probability is approximate. Secondly, insufficient guidance is given for the multivariate case in which there is more than one measurand. In order to address these limitations, two specific guidance documents (or ‘Supplements to the GUM’) on, respectively, a Monte Carlo method for uncertainty evaluation (Supplement 1) and extensions to any number of measurands (Supplement 2) have been published. A further document on developing and using measurement models in the context of uncertainty evaluation (Supplement 3) is also planned, but not considered in this paper. An overview is given of these guidance documents. In particular, a Monte Carlo method, which is the focus of Supplements 1 and 2, is described as a numerical approach to implement the ‘propagation of distributions’ formulated using the ‘change of variables formula’. Although applying a Monte Carlo method is conceptually straightforward, some of the practical aspects of using the method are considered, such as the choice of the number of trials and ensuring an implementation is memory-efficient. General comments about the implications of using the method in measurement and calibration services, such as the need to achieve transferability of measurement results, are made.
NASA Astrophysics Data System (ADS)
Aggarwal, Ashwani; Vasu, Ram M.
2003-07-01
Noninvasive diagnosis in medicine has shown considerable attention in recent years. Several methods are already available for imaging the biological tissue like X-ray computerized tomography, magentic resonance imaging and ultrasound imaging et c. But each of these methods has its own disadvantages. Optical tomography which uses NIR light is one of the emerging methods in teh field of medical imaging because it is non-invasive in nature. The only problem that occurs in using light for imaging the tissue is that it is highly scattered inside tissue, so the propagation of light in tissue is not confined to straight lines as is the case with X-ray tomography. Therefore the need arises to understand the behaviour of propagation of light in tissue. There are several methods for light interaction with tissue. Monte Carlo method is one of these methods which is a simple technique for simulation of light through tissue. The only problem faced with Monte Carlo simulation is its high computational time. Once the data is obtained using Monte Carlo simulation, it need to be inverted to obtain the reconstruction of tissue image. There are standard methods of reconstruction like algebraic reconstruction method, filtered backprojection method etc. But these methods can not be used as such in the case when light is used as probing radiations because it is highly scattered inside the tissue. The standard filtered backprojection method has been modified so that the zigzag path of photons is taken into consideration while back projecting the data. This is achieved by dividing the tissue domain in a square grid and storing the average path traversed in each grid element. It has been observed that the reconstruction obtained using this modification is much better than the result in case of standard filtered backprojection method.
Time-step limits for a Monte Carlo Compton-scattering method
Densmore, Jeffery D [Los Alamos National Laboratory; Warsa, James S [Los Alamos National Laboratory; Lowrie, Robert B [Los Alamos National Laboratory
2008-01-01
Compton scattering is an important aspect of radiative transfer in high energy density applications. In this process, the frequency and direction of a photon are altered by colliding with a free electron. The change in frequency of a scattered photon results in an energy exchange between the photon and target electron and energy coupling between radiation and matter. Canfield, Howard, and Liang have presented a Monte Carlo method for simulating Compton scattering that models the photon-electron collision kinematics exactly. However, implementing their technique in multiphysics problems that include the effects of radiation-matter energy coupling typically requires evaluating the material temperature at its beginning-of-time-step value. This explicit evaluation can lead to unstable and oscillatory solutions. In this paper, we perform a stability analysis of this Monte Carlo method and present time-step limits that avoid instabilities and nonphysical oscillations by considering a spatially independent, purely scattering radiative-transfer problem. Examining a simplified problem is justified because it isolates the effects of Compton scattering, and existing Monte Carlo techniques can robustly model other physics (such as absorption, emission, sources, and photon streaming). Our analysis begins by simplifying the equations that are solved via Monte Carlo within each time step using the Fokker-Planck approximation. Next, we linearize these approximate equations about an equilibrium solution such that the resulting linearized equations describe perturbations about this equilibrium. We then solve these linearized equations over a time step and determine the corresponding eigenvalues, quantities that can predict the behavior of solutions generated by a Monte Carlo simulation as a function of time-step size and other physical parameters. With these results, we develop our time-step limits. This approach is similar to our recent investigation of time discretizations for the Compton-scattering Fokker-Planck equation.
NASA Astrophysics Data System (ADS)
Mizusaki, Takahiro; Shimizu, Noritaka
2012-02-01
We propose a new variational Monte Carlo (VMC) method with an energy variance extrapolation for large-scale shell-model calculations. This variational Monte Carlo is a stochastic optimization method with a projected correlated condensed pair state as a trial wave function, and is formulated with the M-scheme representation of projection operators, the Pfaffian and the Markov-chain Monte Carlo. Using this method, we can stochastically calculate approximated yrast energies and electromagnetic transition strengths. Furthermore, by combining this VMC method with energy variance extrapolation, we can estimate exact shell-model energies.
Monte Carlo method for photon heating using temperature-dependent optical properties.
Slade, Adam Broadbent; Aguilar, Guillermo
2015-02-01
The Monte Carlo method for photon transport is often used to predict the volumetric heating that an optical source will induce inside a tissue or material. This method relies on constant (with respect to temperature) optical properties, specifically the coefficients of scattering and absorption. In reality, optical coefficients are typically temperature-dependent, leading to error in simulation results. The purpose of this study is to develop a method that can incorporate variable properties and accurately simulate systems where the temperature will greatly vary, such as in the case of laser-thawing of frozen tissues. A numerical simulation was developed that utilizes the Monte Carlo method for photon transport to simulate the thermal response of a system that allows temperature-dependent optical and thermal properties. This was done by combining traditional Monte Carlo photon transport with a heat transfer simulation to provide a feedback loop that selects local properties based on current temperatures, for each moment in time. Additionally, photon steps are segmented to accurately obtain path lengths within a homogenous (but not isothermal) material. Validation of the simulation was done using comparisons to established Monte Carlo simulations using constant properties, and a comparison to the Beer-Lambert law for temperature-variable properties. The simulation is able to accurately predict the thermal response of a system whose properties can vary with temperature. The difference in results between variable-property and constant property methods for the representative system of laser-heated silicon can become larger than 100K. This simulation will return more accurate results of optical irradiation absorption in a material which undergoes a large change in temperature. This increased accuracy in simulated results leads to better thermal predictions in living tissues and can provide enhanced planning and improved experimental and procedural outcomes. PMID:25488656
Monte Carlo Method for Predicting a Physically Based Drop Size Distribution Evolution of a Spray
NASA Astrophysics Data System (ADS)
Tembely, Moussa; Lécot, Christian; Soucemarianadin, Arthur
2010-03-01
We report in this paper a method for predicting the evolution of a physically based drop size distribution of a spray, by coupling the Maximum Entropy Formalism and the Monte Carlo scheme. Using the discrete or continuous population balance equation, a Mass Flow Algorithm is formulated taking into account interactions between droplets via coalescence. After deriving a kernel for coalescence, we solve the time dependent drop size distribution equation using a Monte Carlo method. We apply the method to the spray of a new print-head known as a Spray On Demand (SOD) device; the process exploits ultrasonic spray generation via a Faraday instability where the fluid/structure interaction causing the instability is described by a modified Hamilton's principle. This has led to a physically-based approach for predicting the initial drop size distribution within the framework of the Maximum Entropy Formalism (MEF): a three-parameter generalized Gamma distribution is chosen by using conservation of mass and energy. The calculation of the drop size distribution evolution by Monte Carlo method shows the effect of spray droplets coalescence both on the number-based or volume-based drop size distributions.
Order-N cluster Monte Carlo method for spin systems with long-range interactions
Fukui, Kouki [Department of Applied Physics, University of Tokyo, 7-3-1 Hongo, Tokyo 113-8656 (Japan); Todo, Synge [Department of Applied Physics, University of Tokyo, 7-3-1 Hongo, Tokyo 113-8656 (Japan); CREST, Japan Science and Technology Agency, Kawaguchi 332-0012 (Japan)], E-mail: wistaria@ap.t.u-tokyo.ac.jp
2009-04-20
An efficient O(N) cluster Monte Carlo method for Ising models with long-range interactions is presented. Our novel algorithm does not introduce any cutoff for interaction range and thus it strictly fulfills the detailed balance. The realized stochastic dynamics is equivalent to that of the conventional Swendsen-Wang algorithm, which requires O(N{sup 2}) operations per Monte Carlo sweep if applied to long-range interacting models. In addition, it is shown that the total energy and the specific heat can also be measured in O(N) time. We demonstrate the efficiency of our algorithm over the conventional method and the O(NlogN) algorithm by Luijten and Bloete. We also apply our algorithm to the classical and quantum Ising chains with inverse-square ferromagnetic interactions, and confirm in a high accuracy that a Kosterlitz-Thouless phase transition, associated with a universal jump in the magnetization, occurs in both cases.
A Monte Carlo wavefunction method for semiclassical simulations of spin-position entanglement
Billington, C J; Anderson, R P; Turner, L D
2015-01-01
We present a Monte Carlo wavefunction method for semiclassically modeling spin-$\\frac12$ systems in a magnetic field gradient in one dimension. Our model resolves the conflict of determining what classical force an atom should be subjected to when it is in an arbitrary superposition of internal states. Spatial degrees of freedom are considered to be an environment, entanglement with which decoheres the internal states. Atoms follow classical trajectories through space, punctuated by probabilistic jumps between spin states. We modify the conventional Monte Carlo wavefunction method to jump between states when population transfer occurs, rather than when population is later discarded via exponential decay. This results in a spinor wavefunction that is continuous in time, and allows us to model the classical particle trajectories (evolution of the environment variables) more accurately. The model is not computationally demanding and it agrees well with simulations of the full spatial wavefunction of an atom.
Chen, Jin; Venugopal, Vivek; Intes, Xavier
2011-01-01
Time-resolved fluorescence optical tomography allows 3-dimensional localization of multiple fluorophores based on lifetime contrast while providing a unique data set for improved resolution. However, to employ the full fluorescence time measurements, a light propagation model that accurately simulates weakly diffused and multiple scattered photons is required. In this article, we derive a computationally efficient Monte Carlo based method to compute time-gated fluorescence Jacobians for the simultaneous imaging of two fluorophores with lifetime contrast. The Monte Carlo based formulation is validated on a synthetic murine model simulating the uptake in the kidneys of two distinct fluorophores with lifetime contrast. Experimentally, the method is validated using capillaries filled with 2.5nmol of ICG and IRDye™800CW respectively embedded in a diffuse media mimicking the average optical properties of mice. Combining multiple time gates in one inverse problem allows the simultaneous reconstruction of multiple fluorophores with increased resolution and minimal crosstalk using the proposed formulation. PMID:21483610
High-order Path Integral Monte Carlo methods for solving strongly correlated fermion problems
NASA Astrophysics Data System (ADS)
Chin, Siu A.
2015-03-01
In solving for the ground state of a strongly correlated many-fermion system, the conventional second-order Path Integral Monte Carlo method is plagued with the sign problem. This is due to the large number of anti-symmetric free fermion propagators that are needed to extract the square of the ground state wave function at large imaginary time. In this work, I show that optimized fourth-order Path Integral Monte Carlo methods, which uses no more than 5 free-fermion propagators, in conjunction with the use of the Hamiltonian energy estimator, can yield accurate ground state energies for quantum dots with up to 20 polarized electrons. The correlations are directly built-in and no explicit wave functions are needed. This work is supported by the Qatar National Research Fund NPRP GRANT #5-674-1-114.
Application of the vector Monte-Carlo method in polarisation optical coherence tomography
Churmakov, D Yu [Cranfield Health, Cranfield University, Silsoe (United Kingdom); Kuz'min, V L [Saint Petersburg Institute of Commerce and Economics (Russian Federation); Meglinskii, I V [Department of Physics, N G Chernyshevskii Saratov State University, Saratov (Russian Federation)
2006-11-30
The vector Monte-Carlo method is developed and applied to polarisation optical coherence tomography. The basic principles of simulation of the propagation of polarised electromagnetic radiation with a small coherence length are considered under conditions of multiple scattering. The results of numerical simulations for Rayleigh scattering well agree with the Milne solution generalised to the case of an electromagnetic field and with theoretical calculations in the diffusion approximation. (special issue devoted to multiple radiation scattering in random media)
A Modified Monte Carlo Method for Carrier Transport in Germanium, Free of Isotropic Rates
NASA Astrophysics Data System (ADS)
Sundqvist, Kyle
2010-03-01
We present a new method for carrier transport simulation, relevant for high-purity germanium < 100 > at a temperature of 40 mK. In this system, the scattering of electrons and holes is dominated by spontaneous phonon emission. Free carriers are always out of equilibrium with the lattice. We must also properly account for directional effects due to band structure, but there are many cautions in the literature about treating germanium in particular. These objections arise because the germanium electron system is anisotropic to an extreme degree, while standard Monte Carlo algorithms maintain a reliance on isotropic, integrated rates. We re-examine Fermi's Golden Rule to produce a Monte Carlo method free of isotropic rates. Traditional Monte Carlo codes implement particle scattering based on an isotropically averaged rate, followed by a separate selection of the particle's final state via a momentum-dependent probability. In our method, the kernel of Fermi's Golden Rule produces analytical, bivariate rates which allow for the simultaneous choice of scatter and final state selection. Energy and momentum are automatically conserved. We compare our results to experimental data.
Methods for Monte Carlo simulation of the exospheres of the moon and Mercury
NASA Astrophysics Data System (ADS)
Hodges, R. R.
1980-01-01
A general form of the integral equation of exospheric transport on moon-like bodies is derived in a form that permits arbitrary specification of time varying physical processes affecting atom creation and annihilation, atom-regolith collisions, adsorption and desorption, and nonplanetocentric acceleration. Because these processes usually defy analytic representation, the Monte Carlo method of solution of the transport equation, the only viable alternative, is described in detail, with separate discussions of the methods of specification of physical processes as probabalistic functions. Proof of the validity of the Monte Carlo exosphere simulation method is provided in the form of a comparison of analytic and Monte Carlo solutions to three classical, and analytically tractable, exosphere problems. One of the key phenomena in moonlike exosphere simulations, the distribution of velocities of the atoms leaving a regolith, depends mainly on the nature of collisions of free atoms with rocks. It is shown that on the moon and Mercury, elastic collisions of helium atoms with a Maxwellian distribution of vibrating, bound atoms produce a nearly Maxwellian distribution of helium velocities, despite the absence of speeds in excess of escape in the impinging helium velocity distribution.
NASA Astrophysics Data System (ADS)
Ebru Ermis, Elif; Celiktas, Cuneyt
2015-07-01
Calculations of gamma-ray mass attenuation coefficients of various detector materials (crystals) were carried out by means of FLUKA Monte Carlo (MC) method at different gamma-ray energies. NaI, PVT, GSO, GaAs and CdWO4 detector materials were chosen in the calculations. Calculated coefficients were also compared with the National Institute of Standards and Technology (NIST) values. Obtained results through this method were highly in accordance with those of the NIST values. It was concluded from the study that FLUKA MC method can be an alternative way to calculate the gamma-ray mass attenuation coefficients of the detector materials.
Lattice-switching Monte Carlo method for crystals of flexible molecules.
Bridgwater, Sally; Quigley, David
2014-12-01
We discuss implementation of the lattice-switching Monte Carlo method (LSMC) as a binary sampling between two synchronized Markov chains exploring separated minima in the potential energy landscape. When expressed in this fashion, the generalization to more complex crystals is straightforward. We extend the LSMC method to a flexible model of linear alkanes, incorporating bond length and angle constraints. Within this model, we accurately locate a transition between two polymorphs of n-butane with increasing density, and suggest this as a benchmark problem for other free-energy methods. PMID:25615228
Level Densities of Heavy Nuclei by the Shell Model Monte Carlo Method
Y. Alhassid; C. Özen; H. Nakada
2013-05-24
The microscopic calculation of nuclear level densities in the presence of correlations is a difficult many-body problem. The shell model Monte Carlo method provides a powerful technique to carry out such calculations using the framework of the configuration-interaction shell model in spaces that are many orders of magnitude larger than spaces that can be treated by conventional methods. We present recent applications of the method to the calculation of level densities and their collective enhancement factors in heavy nuclei. The calculated level densities are in close agreement with experimental data.
A Hybrid Monte Carlo-Deterministic Method for Global Binary Stochastic Medium Transport Problems
Keady, K P; Brantley, P
2010-03-04
Global deep-penetration transport problems are difficult to solve using traditional Monte Carlo techniques. In these problems, the scalar flux distribution is desired at all points in the spatial domain (global nature), and the scalar flux typically drops by several orders of magnitude across the problem (deep-penetration nature). As a result, few particle histories may reach certain regions of the domain, producing a relatively large variance in tallies in those regions. Implicit capture (also known as survival biasing or absorption suppression) can be used to increase the efficiency of the Monte Carlo transport algorithm to some degree. A hybrid Monte Carlo-deterministic technique has previously been developed by Cooper and Larsen to reduce variance in global problems by distributing particles more evenly throughout the spatial domain. This hybrid method uses an approximate deterministic estimate of the forward scalar flux distribution to automatically generate weight windows for the Monte Carlo transport simulation, avoiding the necessity for the code user to specify the weight window parameters. In a binary stochastic medium, the material properties at a given spatial location are known only statistically. The most common approach to solving particle transport problems involving binary stochastic media is to use the atomic mix (AM) approximation in which the transport problem is solved using ensemble-averaged material properties. The most ubiquitous deterministic model developed specifically for solving binary stochastic media transport problems is the Levermore-Pomraning (L-P) model. Zimmerman and Adams proposed a Monte Carlo algorithm (Algorithm A) that solves the Levermore-Pomraning equations and another Monte Carlo algorithm (Algorithm B) that is more accurate as a result of improved local material realization modeling. Recent benchmark studies have shown that Algorithm B is often significantly more accurate than Algorithm A (and therefore the L-P model) for deep penetration problems such as examined in this paper. In this research, we investigate the application of a variant of the hybrid Monte Carlo-deterministic method proposed by Cooper and Larsen to global deep penetration problems involving binary stochastic media. To our knowledge, hybrid Monte Carlo-deterministic methods have not previously been applied to problems involving a stochastic medium. We investigate two approaches for computing the approximate deterministic estimate of the forward scalar flux distribution used to automatically generate the weight windows. The first approach uses the atomic mix approximation to the binary stochastic medium transport problem and a low-order discrete ordinates angular approximation. The second approach uses the Levermore-Pomraning model for the binary stochastic medium transport problem and a low-order discrete ordinates angular approximation. In both cases, we use Monte Carlo Algorithm B with weight windows automatically generated from the approximate forward scalar flux distribution to obtain the solution of the transport problem.
Wagner, J.C.; Haghighat, A.; Petrovic, B.G.; Hanshaw, H.L.
1995-12-31
Monte Carlo calculations of pressure vessel (PV) neutron fluence have been performed to benchmark discrete ordinates (S{sub N}) transport methods. These calculations, along with measured data at the ex-vessel cavity dosimeter, provide a means to examine various uncertainties associated with the S{sub N} transport calculations. For the purpose of the PV fluence calculations, synthesized 3-D deterministic models are shown to produce results that are quite comparable to results from Monte Carlo methods, provided the two methods utilize the same multigroup cross section libraries. Differences between continuous energy Monte Carlo and multigroup S{sub N} calculations are analyzed and discussed.
Quasi-Monte Carlo methods for lattice systems: A first look
NASA Astrophysics Data System (ADS)
Jansen, K.; Leovey, H.; Ammon, A.; Griewank, A.; Müller-Preussker, M.
2014-03-01
We investigate the applicability of quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable calculated by averaging over random observations generated from an ordinary Markov chain Monte Carlo simulation behaves like N, where N is the number of observations. By means of quasi-Monte Carlo methods it is possible to improve this behavior for certain problems to N-1, or even further if the problems are regular enough. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling. Catalogue identifier: AERJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERJ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence version 3 No. of lines in distributed program, including test data, etc.: 67759 No. of bytes in distributed program, including test data, etc.: 2165365 Distribution format: tar.gz Programming language: C and C++. Computer: PC. Operating system: Tested on GNU/Linux, should be portable to other operating systems with minimal efforts. Has the code been vectorized or parallelized?: No RAM: The memory usage directly scales with the number of samples and dimensions: Bytes used = “number of samples” × “number of dimensions” × 8 Bytes (double precision). Classification: 4.13, 11.5, 23. External routines: FFTW 3 library (http://www.fftw.org) Nature of problem: Certain physical models formulated as a quantum field theory through the Feynman path integral, such as quantum chromodynamics, require a non-perturbative treatment of the path integral. The only known approach that achieves this is the lattice regularization. In this formulation the path integral is discretized to a finite, but very high dimensional integral. So far only Monte Carlo, and especially Markov chain-Monte Carlo methods like the Metropolis or the hybrid Monte Carlo algorithm have been used to calculate approximate solutions of the path integral. These algorithms often lead to the undesired effect of autocorrelation in the samples of observables and suffer in any case from the slow asymptotic error behavior proportional to N, if N is the number of samples. Solution method: This program applies the quasi-Monte Carlo approach and the reweighting technique (respectively the weighted uniform sampling method) to generate uncorrelated samples of observables of the anharmonic oscillator with an improved asymptotic error behavior. Unusual features: The application of the quasi-Monte Carlo approach is quite revolutionary in the field of lattice field theories. Running time: The running time depends directly on the number of samples N and dimensions d. On modern computers a run with up to N=216=65536 (including 9 replica runs) and d=100 should not take much longer than one minute.
Generalized Moment Method for Gap Estimation and Quantum Monte Carlo Level Spectroscopy
NASA Astrophysics Data System (ADS)
Suwa, Hidemaro; Todo, Synge
2015-08-01
We formulate a convergent sequence for the energy gap estimation in the worldline quantum Monte Carlo method. The ambiguity left in the conventional gap calculation for quantum systems is eliminated. Our estimation will be unbiased in the low-temperature limit, and also the error bar is reliably estimated. The level spectroscopy from quantum Monte Carlo data is developed as an application of the unbiased gap estimation. From the spectral analysis, we precisely determine the Kosterlitz-Thouless quantum phase-transition point of the spin-Peierls model. It is established that the quantum phonon with a finite frequency is essential to the critical theory governed by the antiadiabatic limit, i.e., the k =1 SU(2) Wess-Zumino-Witten model.
Visual improvement for bad handwriting based on Monte-Carlo method
NASA Astrophysics Data System (ADS)
Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua
2014-03-01
A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.
Beyond the Born-Oppenheimer approximation with quantum Monte Carlo methods
NASA Astrophysics Data System (ADS)
Tubman, Norm M.; Kylänpää, Ilkka; Hammes-Schiffer, Sharon; Ceperley, David M.
2014-10-01
In this work we develop tools that enable the study of nonadiabatic effects with variational and diffusion Monte Carlo methods. We introduce a highly accurate wave-function ansatz for electron-ion systems that can involve a combination of both clamped ions and quantum nuclei. We explicitly calculate the ground-state energies of H2, LiH, H2O, and FHF- using fixed-node quantum Monte Carlo with wave-function nodes that explicitly depend on the ion positions. The obtained energies implicitly include the effects arising from quantum nuclei and electron-nucleus coupling. We compare our results to the best theoretical and experimental results available and find excellent agreement.
Comparison of dose calculation algorithms with Monte Carlo methods for photon arcs.
Chow, James C L; Wong, Eugene; Chen, Jeff Z; Van Dyk, Jake
2003-10-01
The objective of this study is to seek an accurate and efficient method to calculate the dose distribution of a photon arc. The algorithms tested include Monte Carlo, pencil beam kernel (PK), and collapsed cone convolution (CCC). For the Monte Carlo dose calculation, EGS4/DOSXYZ was used. The SRCXYZ source code associated with the DOSXYZ was modified so that the gantry angle of a photon beam would be sampled uniformly within the arc range about an isocenter to simulate a photon arc. Specifically, photon beams (6/18 MV, 4 x 4 and 10 x 10 cm2) described by a phase space file generated by BEAM (MCPHS), or by two point sources with different photon energy spectra (MCDIV) were used. These methods were used to calculate three-dimensional (3-D) distributions in a PMMA phantom, a cylindrical water phantom, and a phantom with lung inhomogeneity. A commercial treatment planning system was also used to calculate dose distributions in these phantoms using equivalent tissue air ratio (ETAR), PK and CCC algorithms for inhomogeneity corrections. Dose distributions for a photon arc in these phantoms were measured using a RK ion chamber and radiographic films. For homogeneous phantoms, the measured results agreed well (approximately 2% error) with predictions by the Monte Carlo simulations (MCPHS and MCDIV) and the treatment planning system for the 180 degrees and 360 degrees photon arcs. For the dose distribution in the phantom with lung inhomogeneity with a 90 degrees photon arc, the Monte Carlo calculations agreed with the measurements within 2%, while the treatment planning system using ETAR, PK and CCC underestimated or overestimated the dose inside the lung inhomogeneity from 6% to 12%. PMID:14596305
A high order method for orbital conjunctions analysis: Monte Carlo collision probability computation
NASA Astrophysics Data System (ADS)
Morselli, Alessandro; Armellin, Roberto; Di Lizia, Pierluigi; Bernelli Zazzera, Franco
2015-01-01
Three methods for the computation of the probability of collision between two space objects are presented. These methods are based on the high order Taylor expansion of the time of closest approach (TCA) and distance of closest approach (DCA) of the two orbiting objects with respect to their initial conditions. The identification of close approaches is first addressed using the nominal objects states. When a close approach is identified, the dependence of the TCA and DCA on the uncertainties in the initial states is efficiently computed with differential algebra (DA) techniques. In the first method the collision probability is estimated via fast DA-based Monte Carlo simulation, in which, for each pair of virtual objects, the DCA is obtained via the fast evaluation of its Taylor expansion. The second and the third methods are the DA version of Line Sampling and Subset Simulation algorithms, respectively. These are introduced to further improve the efficiency and accuracy of Monte Carlo collision probability computation, in particular for cases of very low collision probabilities. The performances of the methods are assessed on orbital conjunctions occurring in different orbital regimes and dynamical models. The probabilities obtained and the associated computational times are compared against standard (i.e. not DA-based) version of the algorithms and analytical methods. The dependence of the collision probability on the initial orbital state covariance is investigated as well.
NASA Astrophysics Data System (ADS)
Sharma, Anupam; Long, Lyle N.
2004-10-01
A particle approach using the Direct Simulation Monte Carlo (DSMC) method is used to solve the problem of blast impact with structures. A novel approach to model the solid boundary condition for particle methods is presented. The solver is validated against an analytical solution of the Riemann shocktube problem and against experiments on interaction of a planar shock with a square cavity. Blast impact simulations are performed for two model shapes, a box and an I-shaped beam, assuming that the solid body does not deform. The solver uses domain decomposition technique to run in parallel. The parallel performance of the solver on two Beowulf clusters is also presented.
Hybrid method for modeling epitaxial growth: Kinetic Monte Carlo plus molecular dynamics
NASA Astrophysics Data System (ADS)
Zoontjens, P.; Schulze, T. P.; Hendy, S. C.
2007-12-01
We propose a concurrently coupled hybrid molecular dynamics (MD) and kinetic Monte Carlo (KMC) algorithm to simulate the motion of grain boundaries between fcc and hcp islands during epitaxial growth on a fcc (111) surface. The method combines MD and KMC in an adaptive spatial domain decomposition, so that near the grain boundary, atoms are treated using MD but away from the boundary atoms are simulated by KMC. The method allows the grain boundary to interact with structures that form on spatial scales significantly larger than that of the MD domain but with a negligible increase in computational cost.
Lecchini-Visintini, A; Maciejowski, J
2009-01-01
We introduce bounds on the finite-time performance of random searches based on Markov chain Monte Carlo methods for approaching the global solution of stochastic optimization problems defined on continuous domains. In contrast to existing results these bounds can be used in practice as rigorous stopping criteria. Our results are inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory. A comparison with other state-of-the art methods having finite-time guarantees for solving stochastic programming problems is included.
NASA Astrophysics Data System (ADS)
Munz, Claus-Dieter; Auweter-Kurtz, Monika; Fasoulas, Stefanos; Mirza, Asim; Ortwein, Philip; Pfeiffer, Marcel; Stindl, Torsten
2014-10-01
Plasma flows with high Knudsen numbers cannot be treated with classic continuum methods, as represented for example by the Navier-Stokes or the magnetohydrodynamic equations. Instead, the more fundamental Boltzmann equation has to be solved, which is done here approximately by particle based methods that also allow for thermal and chemical non-equilibrium. The Particle-In-Cell method is used to treat the collisionless Vlasov-Maxwell system, while neutral reactive flows are treated by the Direct Simulation Monte Carlo method. In this article, a combined approach is presented that allows the simulation of reactive, partially or fully ionized plasma flows. Both particle methods are briefly outlined and the coupling and parallelization strategies are described. As an example, the results of a streamer discharge simulation are presented and discussed in order to demonstrate the capabilities of the coupled method.
NASA Astrophysics Data System (ADS)
Bruscaglioni, P.; Ismaelli, A.; Zaccanti, G.; Pantani, L.
A Monte Carlo method applicable to the evaluation of the contribution of different order of scattering to the power transmitted through a turbid atmosphere is presented, together with the results of numerical calculations performed by means of scalar scattering functions. The Monte Carlo method has shortened the calculation time required for determining the contribution of orders of scattering to the power transmitted from a collimated laser source to a receiver placed at a certain optical distance.
Monte Carlo methods and their analysis for Coulomb collisions in multicomponent plasmas
Bobylev, A.V.; Potapenko, I.F.
2013-08-01
Highlights: •A general approach to Monte Carlo methods for multicomponent plasmas is proposed. •We show numerical tests for the two-component (electrons and ions) case. •An optimal choice of parameters for speeding up the computations is discussed. •A rigorous estimate of the error of approximation is proved. -- Abstract: A general approach to Monte Carlo methods for Coulomb collisions is proposed. Its key idea is an approximation of Landau–Fokker–Planck equations by Boltzmann equations of quasi-Maxwellian kind. It means that the total collision frequency for the corresponding Boltzmann equation does not depend on the velocities. This allows to make the simulation process very simple since the collision pairs can be chosen arbitrarily, without restriction. It is shown that this approach includes the well-known methods of Takizuka and Abe (1977) [12] and Nanbu (1997) as particular cases, and generalizes the approach of Bobylev and Nanbu (2000). The numerical scheme of this paper is simpler than the schemes by Takizuka and Abe [12] and by Nanbu. We derive it for the general case of multicomponent plasmas and show some numerical tests for the two-component (electrons and ions) case. An optimal choice of parameters for speeding up the computations is also discussed. It is also proved that the order of approximation is not worse than O(?(?)), where ? is a parameter of approximation being equivalent to the time step ?t in earlier methods. A similar estimate is obtained for the methods of Takizuka and Abe and Nanbu.
An implicit Monte Carlo method for simulation of impurity transport in divertor plasma
Suzuki, Akiko; Hayashi, Nobuhiko; Hatayama, Akiyoshi
1997-02-01
A new {open_quotes}implicit{close_quotes} Monte Carlo (IMC) method has been developed to simulate ionization and recombination processes of impurity ions in divertor plasmas. The IMC method takes into account many ionization and recombination processes during a time step {Delta}t. The time step is not limited by a condition, {Delta}t {much_lt} {tau}{sub min} ({tau}{sub min}; the minimum characteristic time of atomic processes), which is forced to be adopted in conventional Monte Carlo methods. We incorporate this method into a one-dimensional impurity transport model. In this transport calculation, impurity ions are followed with the time step about 10 times larger than that used in conventional methods. The average charge state of impurities, (Z), and the radiative cooling rate, L(T{sub e}), are calculated at the electron temperature T{sub e} in divertor plasmas. These results are compared with those obtained from the simple noncoronal model. 10 refs., 7 figs.
NASA Astrophysics Data System (ADS)
Zhang, G.; Lu, D.; Webster, C.
2014-12-01
The rational management of oil and gas reservoir requires an understanding of its response to existing and planned schemes of exploitation and operation. Such understanding requires analyzing and quantifying the influence of the subsurface uncertainties on predictions of oil and gas production. As the subsurface properties are typically heterogeneous causing a large number of model parameters, the dimension independent Monte Carlo (MC) method is usually used for uncertainty quantification (UQ). Recently, multilevel Monte Carlo (MLMC) methods were proposed, as a variance reduction technique, in order to improve computational efficiency of MC methods in UQ. In this effort, we propose a new acceleration approach for MLMC method to further reduce the total computational cost by exploiting model hierarchies. Specifically, for each model simulation on a new added level of MLMC, we take advantage of the approximation of the model outputs constructed based on simulations on previous levels to provide better initial states of new simulations, which will help improve efficiency by, e.g. reducing the number of iterations in linear system solving or the number of needed time-steps. This is achieved by using mesh-free interpolation methods, such as Shepard interpolation and radial basis approximation. Our approach is applied to a highly heterogeneous reservoir model from the tenth SPE project. The results indicate that the accelerated MLMC can achieve the same accuracy as standard MLMC with a significantly reduced cost.
Mcclarren, Ryan G; Urbatsch, Todd J
2008-01-01
In this note we develop a robust implicit Monte Carlo (IMC) algorithm based on more accurately updating the linearized equilibrium radiation energy density. The method does not introduce oscillations in the solution and has the same limit as {Delta}t{yields}{infinity} as the standard Fleck and Cummings IMC method. Moreover, the approach we introduce can be trivially added to current implementations of IMC by changing the definition of the Fleck factor. Using this new method we develop an adaptive scheme that uses either standard IMC or the modified method basing the adaptation on a zero-dimensional problem solved in each cell. Numerical results demonstrate that the new method alleviates both the nonphysical overheating that occurs in standard IMC when the time step is large and significantly diminishes the statistical noise in the solution.
Adaptive and Recursive Time Relaxed Monte Carlo methods for rarefied gas dynamics
L. Pareschi; S. Trazzi; B. Wennberg
2010-09-14
Recently a new class of Monte Carlo methods, called Time Relaxed Monte Carlo (TRMC), designed for the simulation of the Boltzmann equation close to fluid regimes have been introduced. A generalized Wild sum expansion of the solution is at the basis of the simulation schemes. After a splitting of the equation the time discretization of the collision step is obtained from the Wild sum expansion of the solution by replacing high order terms in the expansion with the equilibrium Maxwellian distribution; in this way speed up of the methods close to fluid regimes is obtained by efficiently thermalizing particles close to the equilibrium state. In this work we present an improvement of such methods which allows to obtain an effective uniform accuracy in time without any restriction on the time step and subsequent increase of the computational cost. The main ingredient of the new algorithms is recursivity. Several techniques can be used to truncate the recursive trees generated by the schemes without deteriorating the accuracy of the numerical solution. Techniques based on adaptive strategies are presented. Numerical results emphasize the gain of efficiency of the present simulation schemes with respect to standard DSMC methods.
Parsons, Tom
2008-01-01
Paleoearthquake observations often lack enough events at a given site to directly define a probability density function (PDF) for earthquake recurrence. Sites with fewer than 10-15 intervals do not provide enough information to reliably determine the shape of the PDF using standard maximum-likelihood techniques [e.g., Ellsworth et al., 1999]. In this paper I present a method that attempts to fit wide ranges of distribution parameters to short paleoseismic series. From repeated Monte Carlo draws, it becomes possible to quantitatively estimate most likely recurrence PDF parameters, and a ranked distribution of parameters is returned that can be used to assess uncertainties in hazard calculations. In tests on short synthetic earthquake series, the method gives results that cluster around the mean of the input distribution, whereas maximum likelihood methods return the sample means [e.g., NIST/SEMATECH, 2006]. For short series (fewer than 10 intervals), sample means tend to reflect the median of an asymmetric recurrence distribution, possibly leading to an overestimate of the hazard should they be used in probability calculations. Therefore a Monte Carlo approach may be useful for assessing recurrence from limited paleoearthquake records. Further, the degree of functional dependence among parameters like mean recurrence interval and coefficient of variation can be established. The method is described for use with time-independent and time-dependent PDF?s, and results from 19 paleoseismic sequences on strike-slip faults throughout the state of California are given.
Parsons, T.
2008-01-01
Paleoearthquake observations often lack enough events at a given site to directly define a probability density function (PDF) for earthquake recurrence. Sites with fewer than 10-15 intervals do not provide enough information to reliably determine the shape of the PDF using standard maximum-likelihood techniques (e.g., Ellsworth et al., 1999). In this paper I present a method that attempts to fit wide ranges of distribution parameters to short paleoseismic series. From repeated Monte Carlo draws, it becomes possible to quantitatively estimate most likely recurrence PDF parameters, and a ranked distribution of parameters is returned that can be used to assess uncertainties in hazard calculations. In tests on short synthetic earthquake series, the method gives results that cluster around the mean of the input distribution, whereas maximum likelihood methods return the sample means (e.g., NIST/SEMATECH, 2006). For short series (fewer than 10 intervals), sample means tend to reflect the median of an asymmetric recurrence distribution, possibly leading to an overestimate of the hazard should they be used in probability calculations. Therefore a Monte Carlo approach may be useful for assessing recurrence from limited paleoearthquake records. Further, the degree of functional dependence among parameters like mean recurrence interval and coefficient of variation can be established. The method is described for use with time-independent and time-dependent PDFs, and results from 19 paleoseismic sequences on strike-slip faults throughout the state of California are given.
NASA Astrophysics Data System (ADS)
Iakovidis, S.; Apostolidis, C.; Samaras, T.
2015-04-01
The objective of the present work is the application of the Monte Carlo method (GUMS1) for evaluating uncertainty in electromagnetic field measurements and the comparison of the results with the ones obtained using the 'standard' method (GUM). In particular, the two methods are applied in order to evaluate the field measurement uncertainty using a frequency selective radiation meter and the Total Exposure Quotient (TEQ) uncertainty. Comparative results are presented in order to highlight cases where GUMS1 results deviate significantly from the ones obtained using GUM, such as the presence of a non-linear mathematical model connecting the inputs with the output quantity (case of the TEQ model) or the presence of a dominant nonnormal distribution of an input quantity (case of U-shaped mismatch uncertainty). The deviation of the results obtained from the two methods can even lead to different decisions regarding the conformance with the exposure reference levels.
Hunter, J. L. [Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., 24-107, Cambridge, MA 02139 (United States); Sutton, T. M. [Knolls Atomic Power Laboratory, Bechtel Marine Propulsion Corporation, P. O. Box 1072, Schenectady, NY 12301-1072 (United States)
2013-07-01
In Monte Carlo iterated-fission-source calculations relative uncertainties on local tallies tend to be larger in lower-power regions and smaller in higher-power regions. Reducing the largest uncertainties to an acceptable level simply by running a larger number of neutron histories is often prohibitively expensive. The uniform fission site method has been developed to yield a more spatially-uniform distribution of relative uncertainties. This is accomplished by biasing the density of fission neutron source sites while not biasing the solution. The method is integrated into the source iteration process, and does not require any auxiliary forward or adjoint calculations. For a given amount of computational effort, the use of the method results in a reduction of the largest uncertainties relative to the standard algorithm. Two variants of the method have been implemented and tested. Both have been shown to be effective. (authors)
Figueira, C; Di Maria, S; Baptista, M; Mendes, M; Madeira, P; Vaz, P
2015-07-01
Computed tomography (CT) is one of the most used techniques in medical diagnosis, and its use has become one of the main sources of exposure of the population to ionising radiation. This work concentrates on the paediatric patients, since children exhibit higher radiosensitivity than adults. Nowadays, patient doses are estimated through two standard CT dose index (CTDI) phantoms as a reference to calculate CTDI volume (CTDIvol) values. This study aims at improving the knowledge about the radiation exposure to children and to better assess the accuracy of the CTDIvol method. The effectiveness of the CTDIvol method for patient dose estimation was then investigated through a sensitive study, taking into account the doses obtained by three methods: CTDIvol measured, CTDIvol values simulated with Monte Carlo (MC) code MCNPX and the recent proposed method Size-Specific Dose Estimate (SSDE). In order to assess organ doses, MC simulations were executed with paediatric voxel phantoms. PMID:25883302
Chen, I.J.; Gelbard, E.M.
1988-07-01
The narrow resonance (NR) approximation has, in the past, been applied to regular lattices with fairly simple unit cells. Attempts to use the NR approximation to deal with fine details of the lattice structure, or with complicated lattice cells, have generally been based on assumptions and approximations that are rather difficult to evaluate. A benchmark method is developed in which slowing down is still treated in the NR approximation, but spatial neutron transport is handled by Monte Carlo. This benchmark method is used to evaluate older methods for analyzing the double-heterogeneity effect in fast reactors, and for computing resonance integrals in the PROTEUS lattices. New methods for treating the PROTEUS lattices are proposed.
Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks
Yang, Jin; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.
2009-01-01
We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena. PMID:18851068
Green, P L; Worden, K
2015-09-28
In this paper, the authors outline the general principles behind an approach to Bayesian system identification and highlight the benefits of adopting a Bayesian framework when attempting to identify models of nonlinear dynamical systems in the presence of uncertainty. It is then described how, through a summary of some key algorithms, many of the potential difficulties associated with a Bayesian approach can be overcome through the use of Markov chain Monte Carlo (MCMC) methods. The paper concludes with a case study, where an MCMC algorithm is used to facilitate the Bayesian system identification of a nonlinear dynamical system from experimentally observed acceleration time histories. PMID:26303916
Modeling of electron scattering in thin manganese films on silicon by Monte Carlo methods
NASA Astrophysics Data System (ADS)
Tökési, K.; Némethy, A.; Kövér, L.; Varga, D.; Mukoyama, T.
1996-04-01
The electron energy distribution of the backscattered electrons from manganese and manganese films deposited on a silicon substrate was studied. The Monte Carlo technique was used to simulate the backscattered electron energy distributions and these were compared with the measured reflected electron spectra. A good agreement was found in general between our calculations and the experimental results. In addition, the applicability of Tougaard's method for the determination of the energy loss function from reflected electron energy loss spectroscopy and simulated backscattered electron spectra of manganese films deposited on a silicon substrate were investigated.
Three-dimensional hypersonic rarefied flow calculations using direct simulation Monte Carlo method
NASA Technical Reports Server (NTRS)
Celenligil, M. Cevdet; Moss, James N.
1993-01-01
A summary of three-dimensional simulations on the hypersonic rarefied flows in an effort to understand the highly nonequilibrium flows about space vehicles entering the Earth's atmosphere for a realistic estimation of the aerothermal loads is presented. Calculations are performed using the direct simulation Monte Carlo method with a five-species reacting gas model, which accounts for rotational and vibrational internal energies. Results are obtained for the external flows about various bodies in the transitional flow regime. For the cases considered, convective heating, flowfield structure and overall aerodynamic coefficients are presented and comparisons are made with the available experimental data. The agreement between the calculated and measured results are very good.
NASA Astrophysics Data System (ADS)
Shimizu, Keiichi; Genji, Takamu
The situation in which the plan of a new distribution network system should be examined as an electric power company approaches by the multi-machine interconnection of the distributed generators that will be expected in the near future. Then, the authors assumed applying the distribution system which may be adopted as the near future to a system and equipment of the Kansai Electric Power Company, and executed the reliability evaluation concerning the outage energy and voltage sag power that used the real scale model of distribution system by the stochastic reliability evaluation that used the Monte Carlo method.
Refinement of overlapping local/global iteration method based on Monte Carlo/p-CMFD calculations
Jo, Y.; Yun, S.; Cho, N. Z.
2013-07-01
In this paper, the overlapping local/global (OLG) iteration method based on Monte Carlo/p-CMFD calculations is refined in two aspects. One is the consistent use of estimators to generate homogenized scattering cross sections. Another is that the incident or exiting angular interval is divided into multi-angular bins to modulate albedo boundary conditions for local problems. Numerical tests show that, compared to the one angle bin case in a previous study, the four angle bin case shows significantly improved results. (authors)
Green, P. L.; Worden, K.
2015-01-01
In this paper, the authors outline the general principles behind an approach to Bayesian system identification and highlight the benefits of adopting a Bayesian framework when attempting to identify models of nonlinear dynamical systems in the presence of uncertainty. It is then described how, through a summary of some key algorithms, many of the potential difficulties associated with a Bayesian approach can be overcome through the use of Markov chain Monte Carlo (MCMC) methods. The paper concludes with a case study, where an MCMC algorithm is used to facilitate the Bayesian system identification of a nonlinear dynamical system from experimentally observed acceleration time histories. PMID:26303916
Determination of the spatial response of neutron based analysers using a Monte Carlo based method
Tickner
2000-10-01
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. PMID:11003485
A new Monte Carlo method for dynamical evolution of non-spherical stellar systems
NASA Astrophysics Data System (ADS)
Vasiliev, Eugene
2015-01-01
We have developed a novel Monte Carlo method for simulating the dynamical evolution of stellar systems in arbitrary geometry. The orbits of stars are followed in a smooth potential represented by a basis-set expansion and perturbed after each timestep using local velocity diffusion coefficients from the standard two-body relaxation theory. The potential and diffusion coefficients are updated after an interval of time that is a small fraction of the relaxation time, but may be longer than the dynamical time. Thus, our approach is a bridge between the Spitzer's formulation of the Monte Carlo method and the temporally smoothed self-consistent field method. The primary advantages are the ability to follow the secular evolution of shape of the stellar system, and the possibility of scaling the amount of two-body relaxation to the necessary value, unrelated to the actual number of particles in the simulation. Possible future applications of this approach in galaxy dynamics include the problem of consumption of stars by a massive black hole in a non-spherical galactic nucleus, evolution of binary supermassive black holes, and the influence of chaos on the shape of galaxies, while for globular clusters it may be used for studying the influence of rotation.
NASA Astrophysics Data System (ADS)
Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Kim, S.
2011-10-01
Data assimilation techniques have received growing attention due to their capability to improve prediction. Among various data assimilation techniques, sequential Monte Carlo (SMC) methods, known as "particle filters", are a Bayesian learning process that has the capability to handle non-linear and non-Gaussian state-space models. In this paper, we propose an improved particle filtering approach to consider different response times of internal state variables in a hydrologic model. The proposed method adopts a lagged filtering approach to aggregate model response until the uncertainty of each hydrologic process is propagated. The regularization with an additional move step based on the Markov chain Monte Carlo (MCMC) methods is also implemented to preserve sample diversity under the lagged filtering approach. A distributed hydrologic model, water and energy transfer processes (WEP), is implemented for the sequential data assimilation through the updating of state variables. The lagged regularized particle filter (LRPF) and the sequential importance resampling (SIR) particle filter are implemented for hindcasting of streamflow at the Katsura catchment, Japan. Control state variables for filtering are soil moisture content and overland flow. Streamflow measurements are used for data assimilation. LRPF shows consistent forecasts regardless of the process noise assumption, while SIR has different values of optimal process noise and shows sensitive variation of confidential intervals, depending on the process noise. Improvement of LRPF forecasts compared to SIR is particularly found for rapidly varied high flows due to preservation of sample diversity from the kernel, even if particle impoverishment takes place.
Dynamic load balancing for petascale quantum Monte Carlo applications: The Alias method
NASA Astrophysics Data System (ADS)
Sudheer, C. D.; Krishnan, S.; Srinivasan, A.; Kent, P. R. C.
2013-02-01
Diffusion Monte Carlo is a highly accurate Quantum Monte Carlo method for electronic structure calculations of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency on parallel machines. This step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receiving at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm: a simple renumbering of the MPI ranks based on proximity and a space filling curve significantly improves the MPI Allgather performance. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL show up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that require load balancing.
Dynamic Load Balancing for Petascale Quantum Monte Carlo Applications: The Alias Method
Sudheer, C. D.; Krishnan, S.; Srinivasan, Ashok; Kent, Paul R
2013-01-01
Diffusion Monte Carlo is the most accurate widely used Quantum Monte Carlo method for the electronic structure of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency and avoid accumulation of systematic errors on parallel machines. The load balancing step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receiving at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL showing up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that requires load balancing.
The applicability of certain Monte Carlo methods to the analysis of interacting polymers
Krapp, D.M. Jr. [Univ. of California, Berkeley, CA (United States)
1998-05-01
The authors consider polymers, modeled as self-avoiding walks with interactions on a hexagonal lattice, and examine the applicability of certain Monte Carlo methods for estimating their mean properties at equilibrium. Specifically, the authors use the pivoting algorithm of Madras and Sokal and Metroplis rejection to locate the phase transition, which is known to occur at {beta}{sub crit} {approx} 0.99, and to recalculate the known value of the critical exponent {nu} {approx} 0.58 of the system for {beta} = {beta}{sub crit}. Although the pivoting-Metropolis algorithm works well for short walks (N < 300), for larger N the Metropolis criterion combined with the self-avoidance constraint lead to an unacceptably small acceptance fraction. In addition, the algorithm becomes effectively non-ergodic, getting trapped in valleys whose centers are local energy minima in phase space, leading to convergence towards different values of {nu}. The authors use a variety of tools, e.g. entropy estimation and histograms, to improve the results for large N, but they are only of limited effectiveness. Their estimate of {beta}{sub crit} using smaller values of N is 1.01 {+-} 0.01, and the estimate for {nu} at this value of {beta} is 0.59 {+-} 0.005. They conclude that even a seemingly simple system and a Monte Carlo algorithm which satisfies, in principle, ergodicity and detailed balance conditions, can in practice fail to sample phase space accurately and thus not allow accurate estimations of thermal averages. This should serve as a warning to people who use Monte Carlo methods in complicated polymer folding calculations. The structure of the phase space combined with the algorithm itself can lead to surprising behavior, and simply increasing the number of samples in the calculation does not necessarily lead to more accurate results.
Monte Carlo 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. PMID:24338601
A Monte Carlo simulation based inverse propagation method for stochastic model updating
NASA Astrophysics Data System (ADS)
Bao, Nuo; Wang, Chunjie
2015-08-01
This paper presents an efficient stochastic model updating method based on statistical theory. Significant parameters have been selected implementing the F-test evaluation and design of experiments, and then the incomplete fourth-order polynomial response surface model (RSM) has been developed. Exploiting of the RSM combined with Monte Carlo simulation (MCS), reduces the calculation amount and the rapid random sampling becomes possible. The inverse uncertainty propagation is given by the equally weighted sum of mean and covariance matrix objective functions. The mean and covariance of parameters are estimated synchronously by minimizing the weighted objective function through hybrid of particle-swarm and Nelder-Mead simplex optimization method, thus the better correlation between simulation and test is achieved. Numerical examples of a three degree-of-freedom mass-spring system under different conditions and GARTEUR assembly structure validated the feasibility and effectiveness of the proposed method.
Efficient Markov chain Monte Carlo methods for decoding neural spike trains.
Ahmadian, Yashar; Pillow, Jonathan W; Paninski, Liam
2011-01-01
Stimulus reconstruction or decoding methods provide an important tool for understanding how sensory and motor information is represented in neural activity. We discuss Bayesian decoding methods based on an encoding generalized linear model (GLM) that accurately describes how stimuli are transformed into the spike trains of a group of neurons. The form of the GLM likelihood ensures that the posterior distribution over the stimuli that caused an observed set of spike trains is log concave so long as the prior is. This allows the maximum a posteriori (MAP) stimulus estimate to be obtained using efficient optimization algorithms. Unfortunately, the MAP estimate can have a relatively large average error when the posterior is highly nongaussian. Here we compare several Markov chain Monte Carlo (MCMC) algorithms that allow for the calculation of general Bayesian estimators involving posterior expectations (conditional on model parameters). An efficient version of the hybrid Monte Carlo (HMC) algorithm was significantly superior to other MCMC methods for gaussian priors. When the prior distribution has sharp edges and corners, on the other hand, the "hit-and-run" algorithm performed better than other MCMC methods. Using these algorithms, we show that for this latter class of priors, the posterior mean estimate can have a considerably lower average error than MAP, whereas for gaussian priors, the two estimators have roughly equal efficiency. We also address the application of MCMC methods for extracting nonmarginal properties of the posterior distribution. For example, by using MCMC to calculate the mutual information between the stimulus and response, we verify the validity of a computationally efficient Laplace approximation to this quantity for gaussian priors in a wide range of model parameters; this makes direct model-based computation of the mutual information tractable even in the case of large observed neural populations, where methods based on binning the spike train fail. Finally, we consider the effect of uncertainty in the GLM parameters on the posterior estimators. PMID:20964539
Favorite, Jeffrey A. [Los Alamos National Laboratory (United States)
2002-11-15
The standard implementation of the differential operator (Taylor series) perturbation method for Monte Carlo criticality problems has previously been shown to have a wide range of applicability. In this method, the unperturbed fission distribution is used as a fixed source to estimate the change in the k{sub eff} eigenvalue of a system due to a perturbation. A new method, based on the deterministic perturbation theory assumption that the flux distribution (rather than the fission source distribution) is unchanged after a perturbation, is proposed in this paper. Dubbed the F-A method, the new method is implemented within the framework of the standard differential operator method by making tallies only in perturbed fissionable regions and combining the standard differential operator estimate of their perturbations according to the deterministic first-order perturbation formula. The F-A method, developed to extend the range of applicability of the differential operator method rather than as a replacement, was more accurate than the standard implementation for positive and negative density perturbations in a thin shell at the exterior of a computational Godiva model. The F-A method was also more accurate than the standard implementation at estimating reactivity worth profiles of samples with a very small positive reactivity worth (compared to actual measurements) in the Zeus critical assembly, but it was less accurate for a sample with a small negative reactivity worth.
KERR, REX A.; BARTOL, THOMAS M.; KAMINSKY, BORIS; DITTRICH, MARKUS; CHANG, JEN-CHIEN JACK; BADEN, SCOTT B.; SEJNOWSKI, TERRENCE J.; STILES, JOEL R.
2010-01-01
Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum methods may best represent finite numbers of molecules interacting in complex cellular spaces. We describe and validate new tools and algorithms developed for a new version of the MCell simulation program (MCell3), which supports generalized Monte Carlo modeling of diffusion and chemical reaction in solution, on surfaces representing membranes, and combinations thereof. A new syntax for describing the spatial directionality of surface reactions is introduced, along with optimizations and algorithms that can substantially reduce computational costs (e.g., event scheduling, variable time and space steps). Examples for simple reactions in simple spaces are validated by comparison to analytic solutions. Thus we show how spatially realistic Monte Carlo simulations of biological systems can be far more cost-effective than often is assumed, and provide a level of accuracy and insight beyond that of continuum methods. PMID:20151023
Unpolarized Fermi gas in squeezed anisotropic harmonic trap by Quantum Monte Carlo methods
NASA Astrophysics Data System (ADS)
Li, Xin; Mitas, Lubos
2012-02-01
Using diffusion Monte Carlo (DMC) method, we calculate the ground state properties of unpolarized Fermi gas at unitarity regime in both isotropic and anisotropic harmonic potentials. We study the effects of anisotropy by increasing the frequency in z direction ?z of the harmonic potential while keeping the frequency in x and y direction unchanged. The true unitarity regime is obtained by extrapolating the interaction range to zero and the calculations are done using the fixed-node diffusion Monte Carlo method. The trial function is of the BCS form with the pairing function expanded in appropriate linear combinations of the anisotropic oscillator eigenstates. We evaluate the binding energies for varying particle numbers and we estimate its behavior in the limit of large number of atoms. We estimate dependence of projected density profile and momentum distribution on the X-Y plane with respect to ?z. Our results can be readily used as a benchmark for the cold atom experiment with similar experimental set-up. Supported by ARO and NSF.
A Deterministic-Monte Carlo Hybrid Method for Time-Dependent Neutron Transport Problems
Justin Pounders; Farzad Rahnema
2001-10-01
A new deterministic-Monte Carlo hybrid solution technique is derived for the time-dependent transport equation. This new approach is based on dividing the time domain into a number of coarse intervals and expanding the transport solution in a series of polynomials within each interval. The solutions within each interval can be represented in terms of arbitrary source terms by using precomputed response functions. In the current work, the time-dependent response function computations are performed using the Monte Carlo method, while the global time-step march is performed deterministically. This work extends previous work by coupling the time-dependent expansions to space- and angle-dependent expansions to fully characterize the 1D transport response/solution. More generally, this approach represents and incremental extension of the steady-state coarse-mesh transport method that is based on global-local decompositions of large neutron transport problems. An example of a homogeneous slab is discussed as an example of the new developments.
Efficient continuous-time quantum Monte Carlo method for the ground state of correlated fermions
NASA Astrophysics Data System (ADS)
Wang, Lei; Iazzi, Mauro; Corboz, Philippe; Troyer, Matthias
2015-06-01
We present the ground state extension of the efficient continuous-time quantum Monte Carlo algorithm for lattice fermions of M. Iazzi and M. Troyer, Phys. Rev. B 91, 241118 (2015), 10.1103/PhysRevB.91.241118. Based on continuous-time expansion of an imaginary-time projection operator, the algorithm is free of systematic error and scales linearly with projection time and interaction strength. Compared to the conventional quantum Monte Carlo methods for lattice fermions, this approach has greater flexibility and is easier to combine with powerful machinery such as histogram reweighting and extended ensemble simulation techniques. We discuss the implementation of the continuous-time projection in detail using the spinless t -V model as an example and compare the numerical results with exact diagonalization, density matrix renormalization group, and infinite projected entangled-pair states calculations. Finally we use the method to study the fermionic quantum critical point of spinless fermions on a honeycomb lattice and confirm previous results concerning its critical exponents.
Kerr, Rex A; Bartol, Thomas M; Kaminsky, Boris; Dittrich, Markus; Chang, Jen-Chien Jack; Baden, Scott B; Sejnowski, Terrence J; Stiles, Joel R
2008-10-13
Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum methods may best represent finite numbers of molecules interacting in complex cellular spaces. We describe and validate new tools and algorithms developed for a new version of the MCell simulation program (MCell3), which supports generalized Monte Carlo modeling of diffusion and chemical reaction in solution, on surfaces representing membranes, and combinations thereof. A new syntax for describing the spatial directionality of surface reactions is introduced, along with optimizations and algorithms that can substantially reduce computational costs (e.g., event scheduling, variable time and space steps). Examples for simple reactions in simple spaces are validated by comparison to analytic solutions. Thus we show how spatially realistic Monte Carlo simulations of biological systems can be far more cost-effective than often is assumed, and provide a level of accuracy and insight beyond that of continuum methods. PMID:20151023
Comparison of the Batho, ETAR and Monte Carlo dose calculation methods in CT based patient models.
du Plessis, F C; Willemse, C A; Lötter, M G; Goedhals, L
2001-04-01
This paper shows the contribution that Monte Carlo methods make in regard to dose distribution calculations in CT based patient models and the role it plays as a gold standard to evaluate other dose calculation algorithms. The EGS4 based BEAM code was used to construct a generic 8 MV accelerator to obtain a series of x-ray field sources. These were used in the EGS4 based DOSXYZ code to generate beam data in a mathematical water phantom to set up a beam model in a commercial treatment planning system (TPS), CADPLAN V.2.7.9. Dose distributions were calculated with the Batho and ETAR inhomogeneity correction algorithms in head/sinus, lung, and prostate patient models for 2 x 2, 5 x 5, and 10 X 10 cm2 open x-ray beams. Corresponding dose distributions were calculated with DOSXYZ that were used as a benchmark. The dose comparisons are expressed in terms of 2D isodose distributions, percentage depth dose data, and dose difference volume histograms (DDVH's). Results indicated that the Batho and ETAR methods contained inaccuracies of 20%-70% in the maxillary sinus region in the head model. Large lung inhomogeneities irradiated with small fields gave rise to absorbed dose deviations of 10%-20%. It is shown for a 10 x 10 cm2 field that DOSXYZ models lateral scatter in lung that is not present in the Batho and ETAR methods. The ETAR and Batho methods are accurate within 3% in a prostate model. We showed how the performance of these inhomogeneity correction methods can be understood in realistic patient models using validated Monte Carlo codes such as BEAM and DOSXYZ. PMID:11339755
Electron-Phonon Scattering in Planar MOSFETs: NEGF and Monte Carlo Methods
Himadri S. Pal; Dmitri E. Nikonov; Raseong Kim; Mark S. Lundstrom
2012-09-21
A formalism for incorporating electron-phonon scattering into the nonequilibrium Green's function (NEGF) framework that is applicable to planar MOSFETs is presented. Restructuring the NEGF equations in terms of approximate summation of transverse momentum modes leads to a rigorous and efficient method of solution. This helps to drastically reduce the computational complexity, allowing treatment of both quantum mechanics and dissipative electron-phonon scattering processes for device sizes from nanometers to microns. The formalism is systematically benchmarked against Monte Carlo solutions of the classical Boltzmann transport for model potential profiles. Results show a remarkably close agreement between the two methods for variety of channel lengths and bias conditions, both for elastic and inelastic scattering processes.
DSMC calculations for the double ellipse. [direct simulation Monte Carlo method
NASA Technical Reports Server (NTRS)
Moss, James N.; Price, Joseph M.; Celenligil, M. Cevdet
1990-01-01
The direct simulation Monte Carlo (DSMC) method involves the simultaneous computation of the trajectories of thousands of simulated molecules in simulated physical space. Rarefied flow about the double ellipse for test case 6.4.1 has been calculated with the DSMC method of Bird. The gas is assumed to be nonreacting nitrogen flowing at a 30 degree incidence with respect to the body axis, and for the surface boundary conditions, the wall is assumed to be diffuse with full thermal accommodation and at a constant wall temperature of 620 K. A parametric study is presented that considers the effect of variations of computational domain, gas model, cell size, and freestream density on surface quantities.
Hybrid Monte Carlo/Deterministic Methods for Accelerating Active Interrogation Modeling
Peplow, Douglas E.; Miller, Thomas Martin; Patton, Bruce W; Wagner, John C
2013-01-01
The potential for smuggling special nuclear material (SNM) into the United States is a major concern to homeland security, so federal agencies are investigating a variety of preventive measures, including detection and interdiction of SNM during transport. One approach for SNM detection, called active interrogation, uses a radiation source, such as a beam of neutrons or photons, to scan cargo containers and detect the products of induced fissions. In realistic cargo transport scenarios, the process of inducing and detecting fissions in SNM is difficult due to the presence of various and potentially thick materials between the radiation source and the SNM, and the practical limitations on radiation source strength and detection capabilities. Therefore, computer simulations are being used, along with experimental measurements, in efforts to design effective active interrogation detection systems. The computer simulations mostly consist of simulating radiation transport from the source to the detector region(s). Although the Monte Carlo method is predominantly used for these simulations, difficulties persist related to calculating statistically meaningful detector responses in practical computing times, thereby limiting their usefulness for design and evaluation of practical active interrogation systems. In previous work, the benefits of hybrid methods that use the results of approximate deterministic transport calculations to accelerate high-fidelity Monte Carlo simulations have been demonstrated for source-detector type problems. In this work, the hybrid methods are applied and evaluated for three example active interrogation problems. Additionally, a new approach is presented that uses multiple goal-based importance functions depending on a particle s relevance to the ultimate goal of the simulation. Results from the examples demonstrate that the application of hybrid methods to active interrogation problems dramatically increases their calculational efficiency.
Quantum Monte Carlo method for the ground state of many-boson systems.
Purwanto, Wirawan; Zhang, Shiwei
2004-11-01
We formulate a quantum Monte Carlo (QMC) method for calculating the ground state of many-boson systems. The method is based on a field-theoretical approach, and is closely related to existing fermion auxiliary-field QMC methods which are applied in several fields of physics. The ground-state projection is implemented as a branching random walk in the space of permanents consisting of identical single-particle orbitals. Any single-particle basis can be used, and the method is in principle exact. We illustrate this method with a trapped atomic boson gas, where the atoms interact via an attractive or repulsive contact two-body potential. We choose as the single-particle basis a real-space grid. We compare with exact results in small systems and arbitrarily sized systems of untrapped bosons with attractive interactions in one dimension, where analytical solutions exist. We also compare with the corresponding Gross-Pitaevskii (GP) mean-field calculations for trapped atoms, and discuss the close formal relation between our method and the GP approach. Our method provides a way to systematically improve upon GP while using the same framework, capturing interaction and correlation effects with a stochastic, coherent ensemble of noninteracting solutions. We discuss various algorithmic issues, including importance sampling and the back-propagation technique for computing observables, and illustrate them with numerical studies. We show results for systems with up to N approximately 400 bosons. PMID:15600791
Risk assessment of water quality using Monte Carlo simulation and artificial neural network method.
Jiang, Yunchao; Nan, Zhongren; Yang, Sucai
2013-06-15
There is always uncertainty in any water quality risk assessment. A Monte Carlo simulation (MCS) is regarded as a flexible, efficient method for characterizing such uncertainties. However, the required computational effort for MCS-based risk assessment is great, particularly when the number of random variables is large and the complicated water quality models have to be calculated by a computationally expensive numerical method, such as the finite element method (FEM). To address this issue, this paper presents an improved method that incorporates an artificial neural network (ANN) into the MCS to enhance the computational efficiency of conventional risk assessment. The conventional risk assessment uses the FEM to create multiple water quality models, which can be time consuming or cumbersome. In this paper, an ANN model was used as a substitute for the iterative FEM runs, and thus, the number of water quality models that must be calculated can be dramatically reduced. A case study on the chemical oxygen demand (COD) pollution risks in the Lanzhou section of the Yellow River in China was taken as a reference. Compared with the conventional risk assessment method, the ANN-MCS-based method can save much computational effort without a loss of accuracy. The results show that the proposed method in this paper is more applicable to assess water quality risks. Because the characteristics of this ANN-MCS-based technique are quite general, it is hoped that the technique can also be applied to other MCS-based uncertainty analysis in the environmental field. PMID:23583753
NASA Astrophysics Data System (ADS)
Schütt, Johannes; Böhm, Michael C.
A Green's function quantum Monte Carlo (GF QMC) method is described which renders possible the determination of the exact ground state energy of any ? system in the computational framework of effective ? Hamiltonians. An instruction to evaluate the growth estimator in the simultaneous presence of positive and negative phases is suggested. Numerical results for five annulene molecules with 4-12 atomic centres as well as 10 further ? molecules with different topology (i.e., monocycles with methylene groups, bi- and polycycles) are given. Negative phases occur in 13 of the 15 ? networks considered. The statistical QMC results are compared with data derived by conventional (many-body) diagonalization techniques. The interaction-free Hückel Hamiltonian has been adopted as most simple setup to test the applicability of the Monte Carlo approach. Many-body results have been derived for the Hubbard and Pariser-Parr-Pople variants of the ?-electron Hamiltonian. It is demonstrated that GF QMC results can be derived whose accuracy does not depend on the presence of negative signs in the numerical simulation.
Bianchini, G.; Burgio, N.; Carta, M. [ENEA C.R. CASACCIA, via Anguillarese, 301, 00123 S. Maria di Galeria Roma (Italy); Peluso, V. [ENEA C.R. BOLOGNA, Via Martiri di Monte Sole, 4, 40129 Bologna (Italy); Fabrizio, V.; Ricci, L. [Univ. of Rome La Sapienza, C/o ENEA C.R. CASACCIA, via Anguillarese, 301, 00123 S. Maria di Galeria Roma (Italy)
2012-07-01
The GUINEVERE experiment (Generation of Uninterrupted Intense Neutrons at the lead Venus Reactor) is an experimental program in support of the ADS technology presently carried out at SCK-CEN in Mol (Belgium). In the experiment a modified lay-out of the original thermal VENUS critical facility is coupled to an accelerator, built by the French body CNRS in Grenoble, working in both continuous and pulsed mode and delivering 14 MeV neutrons by bombardment of deuterons on a tritium-target. The modified lay-out of the facility consists of a fast subcritical core made of 30% U-235 enriched metallic Uranium in a lead matrix. Several off-line and on-line reactivity measurement techniques will be investigated during the experimental campaign. This report is focused on the simulation by deterministic (ERANOS French code) and Monte Carlo (MCNPX US code) calculations of three reactivity measurement techniques, Slope ({alpha}-fitting), Area-ratio and Source-jerk, applied to a GUINEVERE subcritical configuration (namely SC1). The inferred reactivity, in dollar units, by the Area-ratio method shows an overall agreement between the two deterministic and Monte Carlo computational approaches, whereas the MCNPX Source-jerk results are affected by large uncertainties and allow only partial conclusions about the comparison. Finally, no particular spatial dependence of the results is observed in the case of the GUINEVERE SC1 subcritical configuration. (authors)
Monte Carlo Methods for Estimating Interfacial Free Energies and Line Tensions
NASA Astrophysics Data System (ADS)
Binder, Kurt; Block, Benjamin; Das, Subir K.; Virnau, Peter; Winter, David
2011-08-01
Excess contributions to the free energy due to interfaces occur for many problems encountered in the statistical physics of condensed matter when coexistence between different phases is possible (e.g. wetting phenomena, nucleation, crystal growth, etc.). This article reviews two methods to estimate both interfacial free energies and line tensions by Monte Carlo simulations of simple models, (e.g. the Ising model, a symmetrical binary Lennard-Jones fluid exhibiting a miscibility gap, and a simple Lennard-Jones fluid). One method is based on thermodynamic integration. This method is useful to study flat and inclined interfaces for Ising lattices, allowing also the estimation of line tensions of three-phase contact lines, when the interfaces meet walls (where "surface fields" may act). A generalization to off-lattice systems is described as well. The second method is based on the sampling of the order parameter distribution of the system throughout the two-phase coexistence region of the model. Both the interface free energies of flat interfaces and of (spherical or cylindrical) droplets (or bubbles) can be estimated, including also systems with walls, where sphere-cap shaped wall-attached droplets occur. The curvature-dependence of the interfacial free energy is discussed, and estimates for the line tensions are compared to results from the thermodynamic integration method. Basic limitations of all these methods are critically discussed, and an outlook on other approaches is given.
Nonequilibrium hypersonic flows simulations with asymptotic-preserving Monte Carlo methods
NASA Astrophysics Data System (ADS)
Ren, Wei; Liu, Hong; Jin, Shi
2014-12-01
In the rarefied gas dynamics, the DSMC method is one of the most popular numerical tools. It performs satisfactorily in simulating hypersonic flows surrounding re-entry vehicles and micro-/nano- flows. However, the computational cost is expensive, especially when Kn ? 0. Even for flows in the near-continuum regime, pure DSMC simulations require a number of computational efforts for most cases. Albeit several DSMC/NS hybrid methods are proposed to deal with this, those methods still suffer from the boundary treatment, which may cause nonphysical solutions. Filbet and Jin [1] proposed a framework of new numerical methods of Boltzmann equation, called asymptotic preserving schemes, whose computational costs are affordable as Kn ? 0. Recently, Ren et al. [2] realized the AP schemes with Monte Carlo methods (AP-DSMC), which have better performance than counterpart methods. In this paper, AP-DSMC is applied in simulating nonequilibrium hypersonic flows. Several numerical results are computed and analyzed to study the efficiency and capability of capturing complicated flow characteristics.
Radiation Transport for Explosive Outflows: A Multigroup Hybrid Monte Carlo Method
NASA Astrophysics Data System (ADS)
Wollaeger, Ryan T.; van Rossum, Daniel R.; Graziani, Carlo; Couch, Sean M.; Jordan, George C., IV; Lamb, Donald Q.; Moses, Gregory A.
2013-12-01
We explore Implicit Monte Carlo (IMC) and discrete diffusion Monte Carlo (DDMC) for radiation transport in high-velocity outflows with structured opacity. The IMC method is a stochastic computational technique for nonlinear radiation transport. IMC is partially implicit in time and may suffer in efficiency when tracking MC particles through optically thick materials. DDMC accelerates IMC in diffusive domains. Abdikamalov extended IMC and DDMC to multigroup, velocity-dependent transport with the intent of modeling neutrino dynamics in core-collapse supernovae. Densmore has also formulated a multifrequency extension to the originally gray DDMC method. We rigorously formulate IMC and DDMC over a high-velocity Lagrangian grid for possible application to photon transport in the post-explosion phase of Type Ia supernovae. This formulation includes an analysis that yields an additional factor in the standard IMC-to-DDMC spatial interface condition. To our knowledge the new boundary condition is distinct from others presented in prior DDMC literature. The method is suitable for a variety of opacity distributions and may be applied to semi-relativistic radiation transport in simple fluids and geometries. Additionally, we test the code, called SuperNu, using an analytic solution having static material, as well as with a manufactured solution for moving material with structured opacities. Finally, we demonstrate with a simple source and 10 group logarithmic wavelength grid that IMC-DDMC performs better than pure IMC in terms of accuracy and speed when there are large disparities between the magnitudes of opacities in adjacent groups. We also present and test our implementation of the new boundary condition.
A modular method to handle multiple time-dependent quantities in Monte Carlo simulations.
Shin, J; Perl, J; Schümann, J; Paganetti, H; Faddegon, B A
2012-06-01
A general method for handling time-dependent quantities in Monte Carlo simulations was developed to make such simulations more accessible to the medical community for a wide range of applications in radiotherapy, including fluence and dose calculation. To describe time-dependent changes in the most general way, we developed a grammar of functions that we call 'Time Features'. When a simulation quantity, such as the position of a geometrical object, an angle, a magnetic field, a current, etc, takes its value from a Time Feature, that quantity varies over time. The operation of time-dependent simulation was separated into distinct parts: the Sequence samples time values either sequentially at equal increments or randomly from a uniform distribution (allowing quantities to vary continuously in time), and then each time-dependent quantity is calculated according to its Time Feature. Due to this modular structure, time-dependent simulations, even in the presence of multiple time-dependent quantities, can be efficiently performed in a single simulation with any given time resolution. This approach has been implemented in TOPAS (TOol for PArticle Simulation), designed to make Monte Carlo simulations with Geant4 more accessible to both clinical and research physicists. To demonstrate the method, three clinical situations were simulated: a variable water column used to verify constancy of the Bragg peak of the Crocker Lab eye treatment facility of the University of California, the double-scattering treatment mode of the passive beam scattering system at Massachusetts General Hospital (MGH), where a spinning range modulator wheel accompanied by beam current modulation produces a spread-out Bragg peak, and the scanning mode at MGH, where time-dependent pulse shape, energy distribution and magnetic fields control Bragg peak positions. Results confirm the clinical applicability of the method. PMID:22572201
Zok, Frank
A Method for Coating Fibers in Oxide Composites Jared H. Weaver, James Yang, Carlos G. Levi Rockwell Scientific Corporation, Thousand Oaks, CA 91360-2362 A method for applying monazite coatings onto an intermediate fugitive coating, followed by impregnation and pyrolysis of a monazite precursor solution
Wagner, John C [ORNL; Mosher, Scott W [ORNL; Evans, Thomas M [ORNL; Peplow, Douglas E. [ORNL; Turner, John A [ORNL
2011-01-01
This paper describes code and methods development at the Oak Ridge National Laboratory focused on enabling high-fidelity, large-scale reactor analyses with Monte Carlo (MC). Current state-of-the-art tools and methods used to perform real commercial reactor analyses have several undesirable features, the most significant of which is the non-rigorous spatial decomposition scheme. Monte Carlo methods, which allow detailed and accurate modeling of the full geometry and are considered the gold standard for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the deterministic, multi-level spatial decomposition methodology in current practice. However, the prohibitive computational requirements associated with obtaining fully converged, system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. The goal of this research is to change this paradigm by enabling direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome are the slow, non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, our research has focused on the development and implementation of (1) a novel hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition (DD) algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The hybrid method development is based on an extension of the FW-CADIS method, which attempts to achieve uniform statistical uncertainty throughout a designated problem space. The MC DD development is being implemented in conjunction with the Denovo deterministic radiation transport package to have direct access to the 3-D, massively parallel discrete-ordinates solver (to support the hybrid method) and the associated parallel routines and structure. This paper describes the hybrid method, its implementation, and initial testing results for a realistic 2-D quarter core pressurized-water reactor model and also describes the MC DD algorithm and its implementation.
A First-Passage Kinetic Monte Carlo method for reaction–drift–diffusion processes
Mauro, Ava J.; Sigurdsson, Jon Karl; Shrake, Justin; Atzberger, Paul J.; Isaacson, Samuel A.
2014-02-15
Stochastic reaction–diffusion models are now a popular tool for studying physical systems in which both the explicit diffusion of molecules and noise in the chemical reaction process play important roles. The Smoluchowski diffusion-limited reaction model (SDLR) is one of several that have been used to study biological systems. Exact realizations of the underlying stochastic processes described by the SDLR model can be generated by the recently proposed First-Passage Kinetic Monte Carlo (FPKMC) method. This exactness relies on sampling analytical solutions to one and two-body diffusion equations in simplified protective domains. In this work we extend the FPKMC to allow for drift arising from fixed, background potentials. As the corresponding Fokker–Planck equations that describe the motion of each molecule can no longer be solved analytically, we develop a hybrid method that discretizes the protective domains. The discretization is chosen so that the drift–diffusion of each molecule within its protective domain is approximated by a continuous-time random walk on a lattice. New lattices are defined dynamically as the protective domains are updated, hence we will refer to our method as Dynamic Lattice FPKMC or DL-FPKMC. We focus primarily on the one-dimensional case in this manuscript, and demonstrate the numerical convergence and accuracy of our method in this case for both smooth and discontinuous potentials. We also present applications of our method, which illustrate the impact of drift on reaction kinetics.
A First-Passage Kinetic Monte Carlo method for reaction-drift-diffusion processes
NASA Astrophysics Data System (ADS)
Mauro, Ava J.; Sigurdsson, Jon Karl; Shrake, Justin; Atzberger, Paul J.; Isaacson, Samuel A.
2014-02-01
Stochastic reaction-diffusion models are now a popular tool for studying physical systems in which both the explicit diffusion of molecules and noise in the chemical reaction process play important roles. The Smoluchowski diffusion-limited reaction model (SDLR) is one of several that have been used to study biological systems. Exact realizations of the underlying stochastic processes described by the SDLR model can be generated by the recently proposed First-Passage Kinetic Monte Carlo (FPKMC) method. This exactness relies on sampling analytical solutions to one and two-body diffusion equations in simplified protective domains. In this work we extend the FPKMC to allow for drift arising from fixed, background potentials. As the corresponding Fokker-Planck equations that describe the motion of each molecule can no longer be solved analytically, we develop a hybrid method that discretizes the protective domains. The discretization is chosen so that the drift-diffusion of each molecule within its protective domain is approximated by a continuous-time random walk on a lattice. New lattices are defined dynamically as the protective domains are updated, hence we will refer to our method as Dynamic Lattice FPKMC or DL-FPKMC. We focus primarily on the one-dimensional case in this manuscript, and demonstrate the numerical convergence and accuracy of our method in this case for both smooth and discontinuous potentials. We also present applications of our method, which illustrate the impact of drift on reaction kinetics.
A particle-inspired Monte Carlo tree estimation method in Bayesian filtering
NASA Astrophysics Data System (ADS)
Wu, Hong; Li, Dehua; Li, Qingguang; Shen, Hui
2013-10-01
A particle-inspired Monte Carlo tree estimation method is proposed to avoid repeating similar simulation and handle the depletion problem in particle filter. Under the inspiration of particles, the method divides the state-space recursively in a top-down manner to form a tree structure that each node in the tree is corresponding to a sub-space. Particles are allocated to the corresponding terminal node during the procedure. Certain size of minimal sub-space or piece is specified to terminate the dividing. Each piece is corresponding to a leaf-node of the tree structure and the prediction probability density in it is approximated by the proportion of its particles in total particles. Instead of importance sampling for each particle, the method takes uniformly random measurements to compute the posterior probability density in each piece. As a result, the method is applied to growth model and has better performance in high SNR environments compared with the Sampling Importance Resampling method.
A Monte Carlo method for variance estimation for estimators based on induced smoothing.
Jin, Zhezhen; Shao, Yongzhao; Ying, Zhiliang
2015-01-01
An important issue in statistical inference for semiparametric models is how to provide reliable and consistent variance estimation. Brown and Wang (2005. Standard errors and covariance matrices for smoothed rank estimators. Biometrika 92: , 732-746) proposed a variance estimation procedure based on an induced smoothing for non-smooth estimating functions. Herein a Monte Carlo version is developed that does not require any explicit form for the estimating function itself, as long as numerical evaluation can be carried out. A general convergence theory is established, showing that any one-step iteration leads to a consistent variance estimator and continuation of the iterations converges at an exponential rate. The method is demonstrated through the Buckley-James estimator and the weighted log-rank estimators for censored linear regression, and rank estimation for multiple event times data. PMID:24812418
Electronic correlation effects in a fullerene molecule studied by the variational Monte Carlo method
Krivnov, V.Y. (Institute of Chemical Physics, Russian Academy of Sciences, Kosygina 4, 117 977 Moscow (Russian Federation)); Shamovsky, I.L. (Institute of Chemical Physics, Russian Academy of Sciences, Kosygina 4, 117 977 Moscow (Russian Federation) Chemistry Department, University of West Indies Mona Campus, St. Andrew, Kingston 7 (Jamaica)); Tornau, E.E. (Semiconductor Physics Institute, Gostauto 11, 2600, Vilnius (Lithuania)); Rosengren, A. (Department of Theoretical Physics, Royal Institute of Technology, S-100 44 Stockholm (Sweden))
1994-10-15
Electron-correlation effects in the fullerene molecule and its ions are investigated in the framework of the Hubbard model. The variational Monte Carlo method and the Gutzwiller wave function are used. Most attention is paid to the case of intermediate interactions, but also the strong coupling limit, where the Hubbard model reduces to the antiferromagnetic Heisenberg model, is considered for the fullerene molecule. In this case we obtain a very low variational ground state energy. Futher, we have calculated the main spin correlation functions in the ground state. Only short-range order is found. The pairing energy of two electrons added to a fullerene molecule or to a fullerene ion is also calculated. Contrary to the results obtained by second-order perturbation theory, pair binding is not found.
On Choosing Effective Elasticity Tensors Using a Monte-Carlo Method
NASA Astrophysics Data System (ADS)
Danek, Tomasz; Slawinski, Michael A.
2015-02-01
A generally anisotropic elasticity tensor can be related to its closest counterparts in various symmetry classes. We refer to these counterparts as effective tensors in these classes. In finding effective tensors, we do not assume a priori orientations of their symmetry planes and axes. Knowledge of orientations of Hookean solids allows us to infer properties of materials represented by these solids. Obtaining orientations and parameter values of effective tensors is a highly nonlinear process involving finding absolute minima for orthogonal projections under all three-dimensional rotations. Given the standard deviations of the components of a generally anisotropic tensor, we examine the influence of measurement errors on the properties of effective tensors. We use a global optimization method to generate thousands of realizations of a generally anisotropic tensor, subject to errors. Using this optimization, we perform a Monte Carlo analysis of distances between that tensor and its counterparts in different symmetry classes, as well as of their orientations and elasticity parameters
A spectral analysis of the domain decomposed Monte Carlo method for linear systems
Slattery, S. R.; Wilson, P. P. H.; Evans, T. M.
2013-07-01
The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)
Accelerating mesh-based Monte Carlo method on modern CPU architectures
Fang, Qianqian; Kaeli, David R.
2012-01-01
In this report, we discuss the use of contemporary ray-tracing techniques to accelerate 3D mesh-based Monte Carlo photon transport simulations. Single Instruction Multiple Data (SIMD) based computation and branch-less design are exploited to accelerate ray-tetrahedron intersection tests and yield a 2-fold speed-up for ray-tracing calculations on a multi-core CPU. As part of this work, we have also studied SIMD-accelerated random number generators and math functions. The combination of these techniques achieved an overall improvement of 22% in simulation speed as compared to using a non-SIMD implementation. We applied this new method to analyze a complex numerical phantom and both the phantom data and the improved code are available as open-source software at http://mcx.sourceforge.net/mmc/. PMID:23243572
A Monte Carlo Method for Projecting Uncertainty in 2D Lagrangian Trajectories
NASA Astrophysics Data System (ADS)
Robel, A.; Lozier, S.; Gary, S. F.
2009-12-01
In this study, a novel method is proposed for modeling the propagation of uncertainty due to subgrid-scale processes through a Lagrangian trajectory advected by ocean surface velocities. The primary motivation and application is differentiating between active and passive trajectories for sea turtles as observed through satellite telemetry. A spatiotemporal launch box is centered on the time and place of actual launch and populated with launch points. Synthetic drifters are launched at each of these locations, adding, at each time step along the trajectory, Monte Carlo perturbations in velocity scaled to the natural variability of the velocity field. The resulting trajectory cloud provides a dynamically evolving density field of synthetic drifter locations that represent the projection of subgrid-scale uncertainty out in time. Subsequently, by relaunching synthetic drifters at points along the trajectory, plots are generated in a daisy chain configuration of the “most likely passive pathways” for the drifter.
Ground State Calculations of Confined Hydrogen Molecule H_2 Using Variational Monte Carlo Method
Doma, S B; Amer, A A
2015-01-01
The variational Monte Carlo method is used to evaluate the ground-state energy of the confined hydrogen molecule, H_2. Accordingly, we considered the case of hydrogen molecule confined by a hard prolate spheroidal cavity when the nuclear positions are clamped at the foci (on-focus case). Also, the case of off-focus nuclei in which the two nuclei are not clamped to the foci is studied. This case provides flexibility for the treatment of the molecular properties by selecting an arbitrary size and shape of the confining spheroidal box. An accurate trial wave function depending on many variational parameters is used for this purpose. The obtained results are in good agreement with the most recent results.
Modelling of an obliquely deposited thin film in three dimensions by kinetic Monte Carlo method
NASA Astrophysics Data System (ADS)
Liu, Zu-Li; Zhang, Xue-Feng; Yao, Kai-Lun; Wei, He-Lin; Huang, Yun-Mi
2004-12-01
A simulation of the growth of an obliquely deposited thin film in a three-dimensional lattice was made using kinetic Monte Carlo method. Cu growth in three dimensions on a (001) substrate with high deposition rates has been simulated in this model. We mainly investigated the variation of three-dimensional morphology and microstructure of films with incidence angle of sputtered flux. The relation of roughness and densities of films with incidence angle was also investigated. The simulation results show that the surface roughness increases and the relative density of thin film decreases with increasing incidence angle, respectively; the columnar structures were separated by void regions for large incidence angle and high deposition rate. The simulation results are in good agreement with experimental results. However, the orientation angle of columns is not completely consistent with the classical tangent rule.
Pairing in Cold Atoms and other Applications for Quantum Monte Carlo methods
Bajdich, Michal; Kolorenc, Jindrich; Mitas, Lubos; Reynolds, P. J.
2010-01-01
We discuss the importance of the fermion nodes for the quantum Monte Carlo (QMC) methods and find two cases of the exact nodes. We describe the structure of the gen- eralized pairing wave functions in Pfaffian antisymmetric form and demonstrate their equivalency with certain class of configuration interaction wave functions. We present the QMC calculations of a model fermion system at unitary limit. We find the system to have the energy of E = 0.425Efree and the condensate fraction of = 0.48. Further we also perform the QMC calculations of the potential energy surface and the electric dipole moment along that surface of the LiSr molecule. We estimate the vibrationally averaged dipole moment to be D =0 = 0.4(2).
An analysis of the convergence of the direct simulation Monte Carlo method
NASA Astrophysics Data System (ADS)
Galitzine, Cyril; Boyd, Iain D.
2015-05-01
In this article, a rigorous framework for the analysis of the convergence of the direct simulation Monte Carlo (DSMC) method is presented. It is applied to the simulation of two test cases: an axisymmetric jet at a Knudsen number of 0.01 and Mach number of 1 and a two-dimensional cylinder flow at a Knudsen of 0.05 and Mach 10. The rate of convergence of sampled quantities is found to be well predicted by an extended form of the Central Limit Theorem that takes into account the correlation of samples but requires the calculation of correlation spectra. A simplified analytical model that does not require correlation spectra is then constructed to model the effect of sample correlation. It is then used to obtain an a priori estimate of the convergence error.
An Efficient Monte Carlo Method for Modeling Radiative Transfer in Protoplanetary Disks
NASA Technical Reports Server (NTRS)
Kim, Stacy
2011-01-01
Monte Carlo methods have been shown to be effective and versatile in modeling radiative transfer processes to calculate model temperature profiles for protoplanetary disks. Temperatures profiles are important for connecting physical structure to observation and for understanding the conditions for planet formation and migration. However, certain areas of the disk such as the optically thick disk interior are under-sampled, or are of particular interest such as the snow line (where water vapor condenses into ice) and the area surrounding a protoplanet. To improve the sampling, photon packets can be preferentially scattered and reemitted toward the preferred locations at the cost of weighting packet energies to conserve the average energy flux. Here I report on the weighting schemes developed, how they can be applied to various models, and how they affect simulation mechanics and results. We find that improvements in sampling do not always imply similar improvements in temperature accuracies and calculation speeds.
Investigation of a V{sub 15} magnetic molecular nanocluster by the Monte Carlo method
Khizriev, K. Sh.; Dzhamalutdinova, I. S.; Taaev, T. A.
2013-06-15
Exchange interactions in a V{sub 15} magnetic molecular nanocluster are considered, and the process of magnetization reversal for various values of the set of exchange constants is analyzed by the Monte Carlo method. It is shown that the best agreement between the field dependence of susceptibility and experimental results is observed for the following set of exchange interaction constants in a V{sub 15} magnetic molecular nanocluster: J = 500 K, J Prime = 150 K, J Double-Prime = 225 K, J{sub 1} = 50 K, and J{sub 2} = 50 K. It is observed for the first time that, in a strong magnetic field, for each of the three transitions from low-spin to high-spin states, the heat capacity exhibits two closely spaced maxima.
The many-body Wigner Monte Carlo method for time-dependent ab-initio quantum simulations
Sellier, J.M. Dimov, I.
2014-09-15
The aim of ab-initio approaches is the simulation of many-body quantum systems from the first principles of quantum mechanics. These methods are traditionally based on the many-body Schrödinger equation which represents an incredible mathematical challenge. In this paper, we introduce the many-body Wigner Monte Carlo method in the context of distinguishable particles and in the absence of spin-dependent effects. Despite these restrictions, the method has several advantages. First of all, the Wigner formalism is intuitive, as it is based on the concept of a quasi-distribution function. Secondly, the Monte Carlo numerical approach allows scalability on parallel machines that is practically unachievable by means of other techniques based on finite difference or finite element methods. Finally, this method allows time-dependent ab-initio simulations of strongly correlated quantum systems. In order to validate our many-body Wigner Monte Carlo method, as a case study we simulate a relatively simple system consisting of two particles in several different situations. We first start from two non-interacting free Gaussian wave packets. We, then, proceed with the inclusion of an external potential barrier, and we conclude by simulating two entangled (i.e. correlated) particles. The results show how, in the case of negligible spin-dependent effects, the many-body Wigner Monte Carlo method provides an efficient and reliable tool to study the time-dependent evolution of quantum systems composed of distinguishable particles.
Multi-Physics Markov Chain Monte Carlo Methods for Subsurface Flows
NASA Astrophysics Data System (ADS)
Rigelo, J.; Ginting, V.; Rahunanthan, A.; Pereira, F.
2014-12-01
For CO2 sequestration in deep saline aquifers, contaminant transport in subsurface, and oil or gas recovery, we often need to forecast flow patterns. Subsurface characterization is a critical and challenging step in flow forecasting. To characterize subsurface properties we establish a statistical description of the subsurface properties that are conditioned to existing dynamic and static data. A Markov Chain Monte Carlo (MCMC) algorithm is used in a Bayesian statistical description to reconstruct the spatial distribution of rock permeability and porosity. The MCMC algorithm requires repeatedly solving a set of nonlinear partial differential equations describing displacement of fluids in porous media for different values of permeability and porosity. The time needed for the generation of a reliable MCMC chain using the algorithm can be too long to be practical for flow forecasting. In this work we develop fast and effective computational methods for generating MCMC chains in the Bayesian framework for the subsurface characterization. Our strategy consists of constructing a family of computationally inexpensive preconditioners based on simpler physics as well as on surrogate models such that the number of fine-grid simulations is drastically reduced in the generated MCMC chains. In particular, we introduce a huff-puff technique as screening step in a three-stage multi-physics MCMC algorithm to reduce the number of expensive final stage simulations. The huff-puff technique in the algorithm enables a better characterization of subsurface near wells. We assess the quality of the proposed multi-physics MCMC methods by considering Monte Carlo simulations for forecasting oil production in an oil reservoir.
Wagner, John C; Peplow, Douglas E.; Mosher, Scott W
2014-01-01
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 an extension of the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for more than a decade 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 more uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented and demonstrated within the MAVRIC sequence of SCALE and the ADVANTG/MCNP framework. Application of the method to representative, real-world problems, including calculation of dose rate and energy dependent flux throughout the problem space, dose rates in specific areas, and energy spectra at multiple detectors, is presented and discussed. Results of the FW-CADIS method and other recently developed global variance reduction approaches are also compared, and the FW-CADIS method outperformed the other methods in all cases considered.
ATR WG-MOX Fuel Pellet Burnup Measurement by Monte Carlo - Mass Spectrometric Method
Chang, Gray Sen I
2002-10-01
This paper presents a new method for calculating the burnup of nuclear reactor fuel, the MCWO-MS method, and describes its application to an experiment currently in progress to assess the suitability for use in light-water reactors of Mixed-OXide (MOX) fuel that contains plutonium derived from excess nuclear weapons material. To demonstrate that the available experience base with Reactor-Grade Mixed uranium-plutonium OXide (RGMOX) can be applied to Weapons-Grade (WG)-MOX in light water reactors, and to support potential licensing of MOX fuel made from weapons-grade plutonium and depleted uranium for use in United States reactors, an experiment containing WG-MOX fuel is being irradiated in the Advanced Test Reactor (ATR) at the Idaho National Engineering and Environmental Laboratory. Fuel burnup is an important parameter needed for fuel performance evaluation. For the irradiated MOX fuel’s Post-Irradiation Examination, the 148Nd method is used to measure the burnup. The fission product 148Nd is an ideal burnup indicator, when appropriate correction factors are applied. In the ATR test environment, the spectrum-dependent and burnup-dependent correction factors (see Section 5 for detailed discussion) can be substantial in high fuel burnup. The validated Monte Carlo depletion tool (MCWO) used in this study can provide a burnup-dependent correction factor for the reactor parameters, such as capture-to-fission ratios, isotopic concentrations and compositions, fission power, and spectrum in a straightforward fashion. Furthermore, the correlation curve generated by MCWO can be coupled with the 239Pu/Pu ratio measured by a Mass Spectrometer (in the new MCWO-MS method) to obtain a best-estimate MOX fuel burnup. A Monte Carlo - MCWO method can eliminate the generation of few-group cross sections. The MCWO depletion tool can analyze the detailed spatial and spectral self-shielding effects in UO2, WG-MOX, and reactor-grade mixed oxide (RG-MOX) fuel pins. The MCWO-MS tool only needs the MS-measured 239Pu/Pu ratio, without the measured isotope 148Nd concentration data, to determine the burnup accurately. MCWO-MS not only provided linear heat generation rate, Pu isotopic composition versus burnup, and burnup distributions within the WG-MOX fuel capsules, but also correctly pointed out the inconsistency in the large difference in burnups obtained by the 148Nd method.
Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods
NASA Astrophysics Data System (ADS)
Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.
2011-12-01
Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion of random effects. However, in the biased case, only Method 3 correctly estimates all the unknown parameters, and both Methods 1 and 2 provide wrong values for the biased parameters. The synthetic case study demonstrates that if the covariance matrix for PCA analysis is inconsistent with true models, the PCA methods with geometric or MCMC sampling will provide incorrect estimates.
Implementation of unsteady sampling procedures for the parallel direct simulation Monte Carlo method
NASA Astrophysics Data System (ADS)
Cave, H. M.; Tseng, K.-C.; Wu, J.-S.; Jermy, M. C.; Huang, J.-C.; Krumdieck, S. P.
2008-06-01
An unsteady sampling routine for a general parallel direct simulation Monte Carlo method called PDSC is introduced, allowing the simulation of time-dependent flow problems in the near continuum range. A post-processing procedure called DSMC rapid ensemble averaging method (DREAM) is developed to improve the statistical scatter in the results while minimising both memory and simulation time. This method builds an ensemble average of repeated runs over small number of sampling intervals prior to the sampling point of interest by restarting the flow using either a Maxwellian distribution based on macroscopic properties for near equilibrium flows (DREAM-I) or output instantaneous particle data obtained by the original unsteady sampling of PDSC for strongly non-equilibrium flows (DREAM-II). The method is validated by simulating shock tube flow and the development of simple Couette flow. Unsteady PDSC is found to accurately predict the flow field in both cases with significantly reduced run-times over single processor code and DREAM greatly reduces the statistical scatter in the results while maintaining accurate particle velocity distributions. Simulations are then conducted of two applications involving the interaction of shocks over wedges. The results of these simulations are compared to experimental data and simulations from the literature where there these are available. In general, it was found that 10 ensembled runs of DREAM processing could reduce the statistical uncertainty in the raw PDSC data by 2.5-3.3 times, based on the limited number of cases in the present study.
Low-Density Nozzle Flow by the Direct Simulation Monte Carlo and Continuum Methods
NASA Technical Reports Server (NTRS)
Chung, Chang-Hong; Kim, Sku C.; Stubbs, Robert M.; Dewitt, Kenneth J.
1994-01-01
Two different approaches, the direct simulation Monte Carlo (DSMC) method based on molecular gasdynamics, and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gasdynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental data, in which density and rotational temperature variations along the centerline and at various locations inside a low-density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data, both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity-temperature exponent, have substantial effects on the results of the DSMC method.
Modeling diffusion and phase transitions by a uniform-acceptance force-bias Monte Carlo method
NASA Astrophysics Data System (ADS)
Timonova, Maria; Groenewegen, Jasper; Thijsse, Barend J.
2010-04-01
The uniform-acceptance force-bias Monte Carlo (UFMC) method [G. Dereli, Mol. Simul. 8, 351 (1992)] is a little-used atomistic simulation method that has strong potential as alternative or complementary technique to molecular dynamics (MD). We have applied UFMC to surface diffusion, amorphization, melting, glass transition, and crystallization, mainly of silicon. The purpose is to study the potential and the limitations of the method: to investigate its applicability, determine safe and effective values of the two UFMC parameters—a temperature and a maximum allowed atomic displacement per iteration step—that lead to reliable results for different types of simulations, assess the computational speed increase relative to MD, discover the microscopic mechanisms that make UFMC work, and show in what kind of simulations it can be useful and preferable over MD. It is found that in many simulations, UFMC can be a very efficient alternative to MD: it leads to analogous results in much fewer iteration steps. Due to the straightforward formalism of UFMC, it can be easily implemented in any MD code. Thus both methods can be combined and applied in turn, using UFMC for the acceleration of certain processes and MD for keeping precision and monitoring individual atom trajectories.
Accuracy of Monte Carlo Criticality Calculations During BR2 Operation
Kalcheva, Silva; Koonen, Edgar; Ponsard, Bernard [SCK-CEN (Belgium)
2005-08-15
The Belgian Material Test Reactor BR2 is a strongly heterogeneous high-flux engineering test reactor at SCK-CEN (Centre d'Etude de l'Energie Nucleaire) in Mol with a thermal power of 60 to 100 MW. It deploys highly enriched uranium, water-cooled concentric plate fuel elements, positioned inside a beryllium reflector with a complex hyperboloid arrangement of test holes. The objective of this paper is to validate the MCNP and ORIGEN-S three-dimensional (3-D) model for reactivity predictions of the entire BR2 core during reactor operation. We employ the Monte Carlo code MCNP-4C to evaluate the effective multiplication factor k{sub eff} and 3-D space-dependent specific power distribution. The one-dimensional code ORIGEN-S is used to calculate the isotopic fuel depletion versus burnup and to prepare a database with depleted fuel compositions. The approach taken is to evaluate the 3-D power distribution at each time step and along with the database to evaluate the 3-D isotopic fuel depletion at the next step and to deduce the corresponding shim rod positions of the reactor operation. The capabilities of both codes are fully exploited without constraints on the number of involved isotope depletion chains or an increase of the computational time. The reactor has a complex operation, with important shutdowns between cycles, and its reactivity is strongly influenced by poisons, mainly {sup 3}He and {sup 6}Li from the beryllium reflector, and the burnable absorbers {sup 149}Sm and {sup 10}B in the fresh UAl{sub x} fuel. The computational predictions for the shim rod positions at various restarts are within 0.5 $ ({beta}{sub eff} = 0.0072)
Exploration of the use of the kinetic Monte Carlo method in simulation of quantum dot growth
NASA Astrophysics Data System (ADS)
Ramsey, James J.
2011-12-01
The use of Kinetic Monte Carlo (KMC) simulations in modeling growth of quantum dots (QDs) on semiconductor surfaces is explored. The underlying theory of the KMC method and the algorithms used in KMC implementations are explained, and the merits and shortcomings of previous KMC simulations on QD growth are discussed. Exploratory research has determined that on the one hand, quantitative KMC simulation of InAs/GaAs QD growth would need to be off-lattice, but that on the other hand, the available empirical interatomic potentials needed to make such off-lattice simulation tractable are not reliable for modeling semiconductor surfaces. A qualitative Kinetic Monte Carlo model is then developed for QD growth on a (001) substrate of tetrahedrally coordinated semiconductor material. It takes into account three different kinds of anisotropy: elastic anisotropy of the substrate, anisotropy in diffusion of isolated particles deposited onto the substrate (or single-particle diffusional anisotropy), and anisotropy in the interactions amongst nearest-neighboring deposited particles. Elastic effects are taken into account through a phenomenological repulsive ring model. The results of the qualitative simulation are as follows: (1) Effects of elastic anisotropy appear more pronounced in some experiments than others, with an anisotropic model needed to reproduce the order seen in some experimental results, while an isotropic model better explains the results from other experiments. (2) The single-particle diffusional anisotropy appears to explain the disorder in arrangement of quantum dots that has been seen in several experiments. (3) Anisotropy in interactions among nearest-neighboring particles appears to explain the oblong shapes of quantum dots seen in experiments of growth of InGaAs dots on GaAs(001), and to partially explain the presence of chains of dots as well. It is concluded that while the prospects of quantitative KMC simulations of quantum dot growth face difficulties, qualitative KMC simulations can lend some physical insights and lead to new questions that may be addressed by future research.
Calculation of the entropy of random coil polymers with the hypothetical scanning Monte Carlo method
NASA Astrophysics Data System (ADS)
White, Ronald P.; Meirovitch, Hagai
2005-12-01
Hypothetical scanning Monte Carlo (HSMC) is a method for calculating the absolute entropy S and free energy F from a given MC trajectory developed recently and applied to liquid argon, TIP3P water, and peptides. In this paper HSMC is extended to random coil polymers by applying it to self-avoiding walks on a square lattice—a simple but difficult model due to strong excluded volume interactions. With HSMC the probability of a given chain is obtained as a product of transition probabilities calculated for each bond by MC simulations and a counting formula. This probability is exact in the sense that it is based on all the interactions of the system and the only approximation is due to finite sampling. The method provides rigorous upper and lower bounds for F, which can be obtained from a very small sample and even from a single chain conformation. HSMC is independent of existing techniques and thus constitutes an independent research tool. The HSMC results are compared to those obtained by other methods, and its application to complex lattice chain models is discussed; we emphasize its ability to treat any type of boundary conditions for which a reference state (with known free energy) might be difficult to define for a thermodynamic integration process. Finally, we stress that the capability of HSMC to extract the absolute entropy from a given sample is important for studying relaxation processes, such as protein folding.
Method using a Monte Carlo simulation database for optimizing x-ray fluoroscopic conditions
NASA Astrophysics Data System (ADS)
Ueki, Hironori; Okajima, Kenichi
2001-06-01
To improve image quality (IQ) and reduce dose in x-ray fluoroscopy, we have developed a new method for optimizing x-ray conditions such as x-ray tube voltage, tube current, and gain of the detector. This method uses a Monte Carlo (MC)-simulation database for analyzing the relations between IQ, x-ray dose, and x-ray conditions. The optimization consists of three steps. First, a permissible dose limit for each object thickness is preset. Then, the MC database is used to calculate the IQ of x-ray projections under all the available conditions that satisfy this presetting. Finally, the optimum conditions are determined as the ones that provide the highest IQ. The MC database contains projections of an estimation phantom simulated under emissions of single-energy photons with various energies. By composing these single-energy projections according to the bremsstrahlung energy distributions, the IQs under any x-ray conditions can be calculated in a very short time. These calculations show that the optimum conditions are determined by the relation between quantum noise and scattering. Moreover, the heat-capacity limit of the x-ray tube can also determine the optimum conditions. It is concluded that the developed optimization method can reduce the time and cost of designing x-ray fluoroscopic systems.
Bridging the gap between quantum Monte Carlo and F12-methods
NASA Astrophysics Data System (ADS)
Chinnamsetty, Sambasiva Rao; Luo, Hongjun; Hackbusch, Wolfgang; Flad, Heinz-Jürgen; Uschmajew, André
2012-06-01
Tensor product approximation of pair-correlation functions opens a new route from quantum Monte Carlo (QMC) to explicitly correlated F12 methods. Thereby one benefits from stochastic optimization techniques used in QMC to get optimal pair-correlation functions which typically recover more than 85% of the total correlation energy. Our approach incorporates, in particular, core and core-valence correlation which are poorly described by homogeneous and isotropic ansatz functions usually applied in F12 calculations. We demonstrate the performance of the tensor product approximation by applications to atoms and small molecules. It turns out that the canonical tensor format is especially suitable for the efficient computation of two- and three-electron integrals required by explicitly correlated methods. The algorithm uses a decomposition of three-electron integrals, originally introduced by Boys and Handy and further elaborated by Ten-no in his 3d numerical quadrature scheme, which enables efficient computations in the tensor format. Furthermore, our method includes the adaptive wavelet approximation of tensor components where convergence rates are given in the framework of best N-term approximation theory.
Yamamoto, K.; Hashizume, K.; Wada, T.; Ohta, M.; Suda, T. [Department of Physics, Konan University, 8-9-1 Okamoto, Kobe 653-8501 (Japan); Nishimura, T.; Fujimoto, M. Y.; Kato, K. [Division of Science, Hokkaido University, Sapporo 060-0810 (Japan); Meme Media Laboratory, Hokkaido University, Sapporo 060-0813 (Japan); Aikawa, M. [Institut d'Astronomie et d'Astrophysique, C.P.226, Universite Libre de Bruxelles, B-1050 Brussels (Belgium)
2006-07-12
We propose a Monte Carlo method to study the reaction paths in nucleosynthesis during stellar evolution. Determination of reaction paths is important to obtain the physical picture of stellar evolution. The combination of network calculation and our method gives us a better understanding of physical picture. We apply our method to the case of the helium shell flash model in the extremely metal poor star.
Bertsekas, Dimitri
and Singularity Issues Monte Carlo Linear Algebra: A Review and Recent Results Dimitri P. Bertsekas Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Caradache, France, 2012 #12;Motivating Framework: Low-Dimensional Approximation Sampling Issues Solution Methods and Singularity Issues
A Sequential Monte Carlo Method for Bayesian Analysis of Massive Datasets.
Ridgeway, Greg; Madigan, David
2003-07-01
Markov chain Monte Carlo (MCMC) techniques revolutionized statistical practice in the 1990s by providing an essential toolkit for making the rigor and flexibility of Bayesian analysis computationally practical. At the same time the increasing prevalence of massive datasets and the expansion of the field of data mining has created the need for statistically sound methods that scale to these large problems. Except for the most trivial examples, current MCMC methods require a complete scan of the dataset for each iteration eliminating their candidacy as feasible data mining techniques.In this article we present a method for making Bayesian analysis of massive datasets computationally feasible. The algorithm simulates from a posterior distribution that conditions on a smaller, more manageable portion of the dataset. The remainder of the dataset may be incorporated by reweighting the initial draws using importance sampling. Computation of the importance weights requires a single scan of the remaining observations. While importance sampling increases efficiency in data access, it comes at the expense of estimation efficiency. A simple modification, based on the "rejuvenation" step used in particle filters for dynamic systems models, sidesteps the loss of efficiency with only a slight increase in the number of data accesses.To show proof-of-concept, we demonstrate the method on two examples. The first is a mixture of transition models that has been used to model web traffic and robotics. For this example we show that estimation efficiency is not affected while offering a 99% reduction in data accesses. The second example applies the method to Bayesian logistic regression and yields a 98% reduction in data accesses. PMID:19789656
NASA Astrophysics Data System (ADS)
Farah, J.; Martinetti, F.; Sayah, R.; Lacoste, V.; Donadille, L.; Trompier, F.; Nauraye, C.; De Marzi, L.; Vabre, I.; Delacroix, S.; Hérault, J.; Clairand, I.
2014-06-01
Monte Carlo calculations are increasingly used to assess stray radiation dose to healthy organs of proton therapy patients and estimate the risk of secondary cancer. Among the secondary particles, neutrons are of primary concern due to their high relative biological effectiveness. The validation of Monte Carlo simulations for out-of-field neutron doses remains however a major challenge to the community. Therefore this work focused on developing a global experimental approach to test the reliability of the MCNPX models of two proton therapy installations operating at 75 and 178 MeV for ocular and intracranial tumor treatments, respectively. The method consists of comparing Monte Carlo calculations against experimental measurements of: (a) neutron spectrometry inside the treatment room, (b) neutron ambient dose equivalent at several points within the treatment room, (c) secondary organ-specific neutron doses inside the Rando-Alderson anthropomorphic phantom. Results have proven that Monte Carlo models correctly reproduce secondary neutrons within the two proton therapy treatment rooms. Sensitive differences between experimental measurements and simulations were nonetheless observed especially with the highest beam energy. The study demonstrated the need for improved measurement tools, especially at the high neutron energy range, and more accurate physical models and cross sections within the Monte Carlo code to correctly assess secondary neutron doses in proton therapy applications.
Application of Quantum Monte Carlo Methods to Describe the Properties of Manganese Oxide Polymorphs
NASA Astrophysics Data System (ADS)
Schiller, Joshua; Ertekin, Elif
2015-03-01
First-principles descriptions of the properties of correlated materials such as transition metal oxides has been a long-standing challenge. Manganese oxide is one such example: according to both conventional and hybrid functional density functional theory, the zinc blende polymorph is predicted to be lower in energy than the rock salt polymorph that occurs in nature. While the correct energy ordering can be obtained in density functional approaches by careful selection of modeling parameters, we present here an alternative approach based on quantum Monte Carlo methods, which are a suite of stochastic tools for solution of the many-body Schrodinger equation. Due to its direct treatment of electron correlation, the QMC method offers the possibility of parameter-free, high-accuracy, systematically improvable analysis. In manganese oxide, we find that the QMC methodology is able to accurately reproduce relative phase energies, lattice constants, and band gaps without the use of adjustable parameters. Additionally, statistical analysis of the many-body wave functions from QMC provides some diagnostic assessments to reveal the physics that may be missing from other modeling approaches.
Uncertainty quantification through the Monte Carlo method in a cloud computing setting
NASA Astrophysics Data System (ADS)
Cunha, Americo; Nasser, Rafael; Sampaio, Rubens; Lopes, Hélio; Breitman, Karin
2014-05-01
The Monte Carlo (MC) method is the most common technique used for uncertainty quantification, due to its simplicity and good statistical results. However, its computational cost is extremely high, and, in many cases, prohibitive. Fortunately, the MC algorithm is easily parallelizable, which allows its use in simulations where the computation of a single realization is very costly. This work presents a methodology for the parallelization of the MC method, in the context of cloud computing. This strategy is based on the MapReduce paradigm, and allows an efficient distribution of tasks in the cloud. This methodology is illustrated on a problem of structural dynamics that is subject to uncertainties. The results show that the technique is capable of producing good results concerning statistical moments of low order. It is shown that even a simple problem may require many realizations for convergence of histograms, which makes the cloud computing strategy very attractive (due to its high scalability capacity and low-cost). Additionally, the results regarding the time of processing and storage space usage allow one to qualify this new methodology as a solution for simulations that require a number of MC realizations beyond the standard.
NASA Astrophysics Data System (ADS)
Zhang, Jun; Guo, Fan
2015-08-01
Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system's dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error(DTE) fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system's dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.
Simulation of Watts Bar Unit 1 Initial Startup Tests with Continuous Energy Monte Carlo Methods
Godfrey, Andrew T; Gehin, Jess C; Bekar, Kursat B; Celik, Cihangir
2014-01-01
The Consortium for Advanced Simulation of Light Water Reactors* is developing a collection of methods and software products known as VERA, the Virtual Environment for Reactor Applications. One component of the testing and validation plan for VERA is comparison of neutronics results to a set of continuous energy Monte Carlo solutions for a range of pressurized water reactor geometries using the SCALE component KENO-VI developed by Oak Ridge National Laboratory. Recent improvements in data, methods, and parallelism have enabled KENO, previously utilized predominately as a criticality safety code, to demonstrate excellent capability and performance for reactor physics applications. The highly detailed and rigorous KENO solutions provide a reliable nu-meric reference for VERAneutronics and also demonstrate the most accurate predictions achievable by modeling and simulations tools for comparison to operating plant data. This paper demonstrates the performance of KENO-VI for the Watts Bar Unit 1 Cycle 1 zero power physics tests, including reactor criticality, control rod worths, and isothermal temperature coefficients.
Adjoint-based deviational Monte Carlo methods for phonon transport calculations
NASA Astrophysics Data System (ADS)
Péraud, Jean-Philippe M.; Hadjiconstantinou, Nicolas G.
2015-06-01
In the field of linear transport, adjoint formulations exploit linearity to derive powerful reciprocity relations between a variety of quantities of interest. In this paper, we develop an adjoint formulation of the linearized Boltzmann transport equation for phonon transport. We use this formulation for accelerating deviational Monte Carlo simulations of complex, multiscale problems. Benefits include significant computational savings via direct variance reduction, or by enabling formulations which allow more efficient use of computational resources, such as formulations which provide high resolution in a particular phase-space dimension (e.g., spectral). We show that the proposed adjoint-based methods are particularly well suited to problems involving a wide range of length scales (e.g., nanometers to hundreds of microns) and lead to computational methods that can calculate quantities of interest with a cost that is independent of the system characteristic length scale, thus removing the traditional stiffness of kinetic descriptions. Applications to problems of current interest, such as simulation of transient thermoreflectance experiments or spectrally resolved calculation of the effective thermal conductivity of nanostructured materials, are presented and discussed in detail.
Quantifying uncertainties in pollutant mapping studies using the Monte Carlo method
NASA Astrophysics Data System (ADS)
Tan, Yi; Robinson, Allen L.; Presto, Albert A.
2014-12-01
Routine air monitoring provides accurate measurements of annual average concentrations of air pollutants, but the low density of monitoring sites limits its capability in capturing intra-urban variation. Pollutant mapping studies measure air pollutants at a large number of sites during short periods. However, their short duration can cause substantial uncertainty in reproducing annual mean concentrations. In order to quantify this uncertainty for existing sampling strategies and investigate methods to improve future studies, we conducted Monte Carlo experiments with nationwide monitoring data from the EPA Air Quality System. Typical fixed sampling designs have much larger uncertainties than previously assumed, and produce accurate estimates of annual average pollution concentrations approximately 80% of the time. Mobile sampling has difficulties in estimating long-term exposures for individual sites, but performs better for site groups. The accuracy and the precision of a given design decrease when data variation increases, indicating challenges in sites intermittently impact by local sources such as traffic. Correcting measurements with reference sites does not completely remove the uncertainty associated with short duration sampling. Using reference sites with the addition method can better account for temporal variations than the multiplication method. We propose feasible methods for future mapping studies to reduce uncertainties in estimating annual mean concentrations. Future fixed sampling studies should conduct two separate 1-week long sampling periods in all 4 seasons. Mobile sampling studies should estimate annual mean concentrations for exposure groups with five or more sites. Fixed and mobile sampling designs have comparable probabilities in ordering two sites, so they may have similar capabilities in predicting pollutant spatial variations. Simulated sampling designs have large uncertainties in reproducing seasonal and diurnal variations at individual sites, but are capable to predict these variations for exposure groups.
Statistical analysis of chemical transformation kinetics using Markov-Chain Monte Carlo methods.
Görlitz, Linus; Gao, Zhenglei; Schmitt, Walter
2011-05-15
For the risk assessment of chemicals intentionally released into the environment, as, e.g., pesticides, it is indispensable to investigate their environmental fate. Main characteristics in this context are transformation rates and partitioning behavior. In most cases the relevant parameters are not directly measurable but are determined indirectly from experimentally determined concentrations in various environmental compartments. Usually this is done by fitting mathematical models, which are usually nonlinear, to the observed data and such deriving estimates of the parameter values. Statistical analysis is then used to judge the uncertainty of the estimates. Of particular interest in this context is the question whether degradation rates are significantly different from zero. Standard procedure is to use nonlinear least-squares methods to fit the models and to estimate the standard errors of the estimated parameters from Fisher's Information matrix and estimated level of measurement noise. This, however, frequently leads to counterintuitive results as the estimated probability distributions of the parameters based on local linearization of the optimized models are often too wide or at least differ significantly in shape from the real distribution. In this paper we identify the shortcoming of this procedure and propose a statistically valid approach based on Markov-Chain Monte Carlo sampling that is appropriate to determine the real probability distribution of model parameters. The effectiveness of this method is demonstrated on three data sets. Although it is generally applicable to different problems where model parameters are to be inferred, in the present case for simplicity we restrict the discussion to the evaluation of metabolic degradation of chemicals in soil. It is shown that the method is successfully applicable to problems of different complexity. We applied it to kinetic data from compounds with one and five metabolites. Additionally, using simulated data, it is shown that the MCMC method estimates the real probability distributions of parameters well and much better than the standard optimization approach. PMID:21526818
Summarizing the output of a Monte Carlo method for uncertainty evaluation
NASA Astrophysics Data System (ADS)
Harris, P. M.; Matthews, C. E.; Cox, M. G.; Forbes, A. B.
2014-06-01
The ‘Guide to the Expression of Uncertainty in Measurement’ (GUM) requires that the way a measurement uncertainty is expressed should be transferable. It should be possible to use directly the uncertainty evaluated for one measurement as a component in evaluating the uncertainty for another measurement that depends on the first. Although the method for uncertainty evaluation described in the GUM meets this requirement of transferability, it is less clear how this requirement is to be achieved when GUM Supplement 1 is applied. That Supplement uses a Monte Carlo method to provide a sample composed of many values drawn randomly from the probability distribution for the measurand. Such a sample does not constitute a convenient way of communicating knowledge about the measurand. In this paper consideration is given to obtaining a more compact summary of such a sample that preserves information about the measurand contained in the sample and can be used in a subsequent uncertainty evaluation. In particular, a coverage interval for the measurand that corresponds to a given coverage probability is often required. If the measurand is characterized by a probability distribution that is not close to being Gaussian, sufficient information has to be conveyed to enable such a coverage interval to be computed reliably. A quantile function in the form of an extended lambda distribution can provide adequate approximations in a number of cases. This distribution is defined by a fixed number of adjustable parameters determined, for example, by matching the moments of the distribution to those calculated in terms of the sample of values. In this paper, alternative flexible models for the quantile function and methods for determining a quantile function from a sample of values are proposed for meeting the above needs.
Pazirandeh, Ali; Azizi, Maryam; Farhad Masoudi, S
2006-01-01
Among many conventional techniques, nuclear techniques have shown to be faster, more reliable, and more effective in detecting explosives. In the present work, neutrons from a 5 Ci Am-Be neutron source being in water tank are captured by elements of soil and landmine (TNT), namely (14)N, H, C, and O. The prompt capture gamma-ray spectrum taken by a NaI (Tl) scintillation detector indicates the characteristic photo peaks of the elements in soil and landmine. In the high-energy region of the gamma-ray spectrum, besides 10.829 MeV of (15)N, single escape (SE) and double escape (DE) peaks are unmistakable photo peaks, which make the detection of concealed explosive possible. The soil has the property of moderating neutrons as well as diffusing the thermal neutron flux. Among many elements in soil, silicon is more abundant and (29)Si emits 10.607 MeV prompt capture gamma-ray, which makes 10.829 MeV detection difficult. The Monte Carlo simulation was used to adjust source-target-detector distances and soil moisture content to yield the best result. Therefore, we applied MCNP4C for configuration very close to reality of a hidden landmine in soil. PMID:16081298
Analysis of probabilistic short run marginal cost using Monte Carlo method
Gutierrez-Alcaraz, G.; Navarrete, N.; Tovar-Hernandez, J.H.; Fuerte-Esquivel, C.R. [Inst. Tecnologico de Morelia, Michoacan (Mexico). Dept. de Ing. Electrica y Electronica; Mota-Palomino, R. [Inst. Politecnico Nacional (Mexico). Escuela Superior de Ingenieria Mecanica y Electrica
1999-11-01
The structure of the Electricity Supply Industry is undergoing dramatic changes to provide new services options. The main aim of this restructuring is allowing generating units the freedom of selling electricity to anybody they wish at a price determined by market forces. Several methodologies have been proposed in order to quantify different costs associated with those new services offered by electrical utilities operating under a deregulated market. The new wave of pricing is heavily influenced by economic principles designed to price products to elastic market segments on the basis of marginal costs. Hence, spot pricing provides the economic structure for many of new services. At the same time, the pricing is influenced by uncertainties associated to the electric system state variables which defined its operating point. In this paper, nodal probabilistic short run marginal costs are calculated, considering as random variables the load, the production cost and availability of generators. The effect of the electrical network is evaluated taking into account linearized models. A thermal economic dispatch is used to simulate each operational condition generated by Monte Carlo method on small fictitious power system in order to assess the effect of the random variables on the energy trading. First, this is carry out by introducing each random variable one by one, and finally considering the random interaction of all of them.
Burns, G.S.
1989-01-01
Monte Carlo simulation methods were used to investigate the absorbed dose distribution around several preliminary source configurations and the 3M Company models 6701, 6702, and 6711 I-125 seeds in water. Simulations for the preliminary sources, all of which were structurally simpler than the seeds, were conducted to demonstrate correct behavior of the computer software. The relative dose distribution of the three seed models were found to be anisotropic, and distinct. Observed differences in the relative dose distributions of the three models are attributable to differences in seed design and photon emission spectrum. Variations in end weld thicknesses and radioactivity distributions within the seeds were found to have substantial influence on the relative dose distributions. Dosimetry estimates along the longitudinal axis of the seeds are particularly uncertain due to such variation. Finally, perturbations of the single seed dose distribution created by neighboring seeds within the implant were determined. Such perturbations are strongly dependent on the seed model used and on the separation between seeds. Simple superposition of single seed dose distributions in multiple seed implants causes overestimation of dose within seed planes. Errors may be quite large for single plane implants with small seed separations.
Simulation of Statistical Neutron Capture Processes Using Monte Carlo Methods with TALYS
NASA Astrophysics Data System (ADS)
Dycus, Drew D.; Bertolli, Michael; Smith, Michael S.; Kozub, Raymond L.
2014-09-01
The rapid neutron capture process (r-process) is thought to be responsible for the synthesis of about half of the nuclear species heavier than Fe. Calculations for the r-process suggest the 130Sn(n , ?) 131Sn reaction rate plays a pivotal role in nucleosynthesis, engendering global effects on isotopic abundances over a wide mass range during the freeze-out epoch following (n , ?) ?2 (? , n) equilibrium. This is owing, in part, to the long ?-decay lifetime of 130Sn (162 s). Direct neutron capture (DC) is likely the dominant reaction at late times in the r-process near the N = 82 closed shell, but the reaction rate and nucleosynthesis calculations require (n , ?) cross sections for both DC and statistical capture. The latter depend heavily on the level density, and that is not yet well established for 131Sn. In order to acquire better estimates of the statistical contribution in the doubly magic 132Sn region, we have undertaken Monte Carlo methods of varying the nuclear reaction model parameters to calculate (n , ?) cross sections for a range of incident neutron energies using the code TALYS. Results will be presented. Research supported by the U. S. Department of Energy.
Živkovi?, Jelena V; Truti?, Nataša V; Veselinovi?, Jovana B; Nikoli?, Goran M; Veselinovi?, Aleksandar M
2015-09-01
The Monte Carlo method was used for QSAR modeling of maleimide derivatives as glycogen synthase kinase-3? inhibitors. The first QSAR model was developed for a series of 74 3-anilino-4-arylmaleimide derivatives. The second QSAR model was developed for a series of 177 maleimide derivatives. QSAR models were calculated with the representation of the molecular structure by the simplified molecular input-line entry system. Two splits have been examined: one split into the training and test set for the first QSAR model, and one split into the training, test and validation set for the second. The statistical quality of the developed model is very good. The calculated model for 3-anilino-4-arylmaleimide derivatives had following statistical parameters: r(2)=0.8617 for the training set; r(2)=0.8659, and rm(2)=0.7361 for the test set. The calculated model for maleimide derivatives had following statistical parameters: r(2)=0.9435, for the training, r(2)=0.9262 and rm(2)=0.8199 for the test and r(2)=0.8418, r(av)m(2)=0.7469 and ?rm(2)=0.1476 for the validation set. Structural indicators considered as molecular fragments responsible for the increase and decrease in the inhibition activity have been defined. The computer-aided design of new potential glycogen synthase kinase-3? inhibitors has been presented by using defined structural alerts. PMID:26257010
Monte Carlo Method For Simulating Gamma-Ray Interaction With Materials: A Case Study on Si
Gao, Fei; Campbell, Luke W.; Devanathan, Ram; Xie, YuLong; Corrales, L. Rene; Peurrung, Anthony J.; Weber, William J.
2007-08-21
In the present work, a Monte Carlo (MC) method has been developed to simulate various quantum mechanical processes for energy loss of photons and fast electrons. The MC model is demonstrated by application to the interaction of photons with silicon over the energy range from 50 eV to 2 MeV and the following subsequent electron cascades. The electron cascade process is commonly represented by two macroscopic parameters, the mean energy required to create an electron-hole pair, W, and the Fano factor, F, describing the electron yield and its variance. At energies lower than 5 keV, W generally decreases with increasing photon energy (from 3.96 to 3.58 eV), and it exhibits a sawtooth variation, as observed previously. However, discontinuities at the shell edges follow the photoionization cross section, in contrast to previous results. The function, F(Ep), initially increases with increasing photon energy, Ep, to a maximum value of 0.187 around 155 eV, and then decreases at higher energies. Above the K shell edge, F has a value of 0.135. These results are consistent with experimental observations. The simulated distribution indicates that the interband transition and plasmon excitation are the most important mechanisms of electron-hole pair creation, while core shell ionization appears to be significant only at high energies.
Absorbed Dose Calculations Using Mesh-based Human Phantoms And Monte Carlo Methods
NASA Astrophysics Data System (ADS)
Kramer, Richard
2011-08-01
Health risks attributable to the exposure to ionizing radiation are considered to be a function of the absorbed or equivalent dose to radiosensitive organs and tissues. However, as human tissue cannot express itself in terms of equivalent dose, exposure models have to be used to determine the distribution of equivalent dose throughout the human body. An exposure model, be it physical or computational, consists of a representation of the human body, called phantom, plus a method for transporting ionizing radiation through the phantom and measuring or calculating the equivalent dose to organ and tissues of interest. The FASH2 (Female Adult meSH) and the MASH2 (Male Adult meSH) computational phantoms have been developed at the University of Pernambuco in Recife/Brazil based on polygon mesh surfaces using open source software tools and anatomical atlases. Representing standing adults, FASH2 and MASH2 have organ and tissue masses, body height and body mass adjusted to the anatomical data published by the International Commission on Radiological Protection for the reference male and female adult. For the purposes of absorbed dose calculations the phantoms have been coupled to the EGSnrc Monte Carlo code, which can transport photons, electrons and positrons through arbitrary media. This paper reviews the development of the FASH2 and the MASH2 phantoms and presents dosimetric applications for X-ray diagnosis and for prostate brachytherapy.
NASA Astrophysics Data System (ADS)
Hantal, György; Picaud, Sylvain; Hoang, Paul N. M.; Voloshin, Vladimir P.; Medvedev, Nikolai N.; Jedlovszky, Pál
2010-10-01
The grand canonical Monte Carlo method is used to simulate the adsorption isotherms of water molecules on different types of model soot particles. These soot models are constructed by first removing atoms from onion-fullerene structures in order to create randomly distributed pores inside the soot, and then performing molecular dynamics simulations, based on the reactive adaptive intermolecular reactive empirical bond order (AIREBO) description of the interaction between carbon atoms, to optimize the resulting structures. The obtained results clearly show that the main driving force of water adsorption on soot is the possibility of the formation of new water-water hydrogen bonds with the already adsorbed water molecules. The shape of the calculated water adsorption isotherms at 298 K strongly depends on the possible confinement of the water molecules in pores of the carbonaceous structure. We found that there are two important factors influencing the adsorption ability of soot. The first of these factors, dominating at low pressures, is the ability of the soot of accommodating the first adsorbed water molecules at strongly hydrophilic sites. The second factor concerns the size and shape of the pores, which should be such that the hydrogen bonding network of the water molecules filling them should be optimal. This second factor determines the adsorption properties at higher pressures.
Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics
Hall, Howard L [ORNL
2012-01-01
Nuclear forensic science has become increasingly important for global nuclear security, and enhancing the timeliness of forensic analysis has been established as an important objective in the field. New, faster techniques must be developed to meet this objective. Current approaches for the analysis of minor actinides, fission products, and fuel-specific materials require time-consuming chemical separation coupled with measurement through either nuclear counting or mass spectrometry. These very sensitive measurement techniques can be hindered by impurities or incomplete separation in even the most painstaking chemical separations. High-temperature gas-phase separation or thermochromatography has been used in the past for the rapid separations in the study of newly created elements and as a basis for chemical classification of that element. This work examines the potential for rapid separation of gaseous species to be applied in nuclear forensic investigations. Monte Carlo modeling has been used to evaluate the potential utility of the thermochromatographic separation method, albeit this assessment is necessarily limited due to the lack of available experimental data for validation.
Applications of Monte Carlo methods for the analysis of MHTGR case of the VHTRC benchmark
Difilippo, F.C.
1994-03-01
Monte Carlo methods, as implemented in the MCNP code, have been used to analyze the neutronics characteristics of benchmarks related to Modular High Temperature Gas-Cooled Reactors. The benchmarks are idealized versions of the Japanese (VHTRC) and Swiss (PROTEUS) facilities and an actual configuration of the PROTEUS Configuration 1 experiment. The purpose of the unit cell benchmarks is to compare multiplication constants, critical bucklings, migration lengths, reaction rates and spectral indices. The purpose of the full reactors benchmarks is to compare multiplication constants, reaction rates, spectral indices, neutron balances, reaction rates profiles, temperature coefficients of reactivity and effective delayed neutron fractions. All of these parameters can be calculated by MCNP, which can provide a very detailed model of the geometry of the configurations, from fuel particles to entire fuel assemblies, using at the same time a continuous energy model. These characteristics make MCNP a very useful tool to analyze these MHTGR benchmarks. The author has used the MCNP latest version, 4.x, eld = 01/12/93 with an ENDF/B-V cross section library. This library does not yet contain temperature dependent resonance materials, so all calculations correspond to room temperature, T = 300{degrees}K. Two separate reports were made -- one for the VHTRC, the other for the PROTEUS benchmark.
Applications of Monte Carlo methods for the analysis of MHTGR case of the PROTEUS benchmark
Difilippo, F.C.
1994-04-01
Monte Carlo methods, as implemented in the MCNP code, have been used to analyze the neutronics characteristics of benchmarks related to Modular High Temperature Gas-Cooled Reactors. The benchmarks are idealized versions of the Japanes (VHTRC) and Swiss (PROTEUS) facilities and an actual configurations of the PROTEUS Configuration I experiment. The purpose of the unit cell benchmarks is to compare multiplication constants, critical bucklings, migration lengths, reaction rates and spectral indices. The purpose of the full reactors benchmarks is to compare multiplication constants, reaction rates, spectral indices, neutron balances, reaction rates profiles, temperature coefficients of reactivity and effective delayed neutron fractions. All of these parameters can be calculated by MCNP, which can provide a very detailed model of the geometry of the configurations, from fuel particles to entire fuel assemblies, using at the same time a continuous energy model. These characteristics make MCNP a very useful tool to analyze these MHTGR benchmarks. We have used the MCNP latest version, 4.x, eld = 01/12/93 with an ENDF/B-V cross section library. This library does not yet contain temperature dependent resonance materials, so all calculations correspond to room temperature, T = 300{degree}K. Two separate reports were made -- one for the VHTRC, the other for the PROTEUS benchmark.
Calculation of complete fusion cross sections of heavy ion reactions using the Monte Carlo method
Ghodsi, O. N.; Mahmoodi, M.; Ariai, J.
2007-03-15
The nucleus-nucleus potential for the fusion reactions {sup 40}Ca+{sup 48}Ca, {sup 16}O+{sup 208}Pb, and {sup 48}Ca+{sup 48}Ca has been calculated using the Monte Carlo method. The results obtained indicate that the technique employed for the calculation of the nucleus-nucleus potential is an efficient one. The effects of the spin and the isospin terms have also been studied using the same technique. The analysis of the results obtained for the {sup 48}Ca+{sup 48}Ca reaction reveal that the isospin-dependent term in the nucleon-nucleon potential causes the nuclear potential to drop by an amount of 0.5 MeV. The analytical calculations of the fusion cross section, particularly those at energies less than the fusion barrier, are in good agreement with the experimental data. In these calculations the effective nucleon-nucleon potential chosen is of the M3Y-Paris potential form and no adjustable parameter has been used.
NASA Astrophysics Data System (ADS)
Velazquez, L.; Castro-Palacio, J. C.
2015-03-01
Velazquez and Curilef [J. Stat. Mech. (2010) P02002, 10.1088/1742-5468/2010/02/P02002; J. Stat. Mech. (2010) P04026, 10.1088/1742-5468/2010/04/P04026] have proposed a methodology to extend Monte Carlo algorithms that are based on canonical ensemble. According to our previous study, their proposal allows us to overcome slow sampling problems in systems that undergo any type of temperature-driven phase transition. After a comprehensive review about ideas and connections of this framework, we discuss the application of a reweighting technique to improve the accuracy of microcanonical calculations, specifically, the well-known multihistograms method of Ferrenberg and Swendsen [Phys. Rev. Lett. 63, 1195 (1989), 10.1103/PhysRevLett.63.1195]. As an example of application, we reconsider the study of the four-state Potts model on the square lattice L ×L with periodic boundary conditions. This analysis allows us to detect the existence of a very small latent heat per site qL during the occurrence of temperature-driven phase transition of this model, whose size dependence seems to follow a power law qL(L ) ?(1/L ) z with exponent z ?0 .26 ±0 .02. Discussed is the compatibility of these results with the continuous character of temperature-driven phase transition when L ?+? .
Velazquez, L; Castro-Palacio, J C
2015-03-01
Velazquez and Curilef [J. Stat. Mech. (2010); J. Stat. Mech. (2010)] have proposed a methodology to extend Monte Carlo algorithms that are based on canonical ensemble. According to our previous study, their proposal allows us to overcome slow sampling problems in systems that undergo any type of temperature-driven phase transition. After a comprehensive review about ideas and connections of this framework, we discuss the application of a reweighting technique to improve the accuracy of microcanonical calculations, specifically, the well-known multihistograms method of Ferrenberg and Swendsen [Phys. Rev. Lett. 63, 1195 (1989)]. As an example of application, we reconsider the study of the four-state Potts model on the square lattice L×L with periodic boundary conditions. This analysis allows us to detect the existence of a very small latent heat per site qL during the occurrence of temperature-driven phase transition of this model, whose size dependence seems to follow a power law qL(L)?(1/L)z with exponent z?0.26±0.02. Discussed is the compatibility of these results with the continuous character of temperature-driven phase transition when L?+?. PMID:25871247
The simulation of Methane hydrate crystal growth by Monte-Carlo Method
NASA Astrophysics Data System (ADS)
Ikeda, H.; Miranda, C. R.; Matsuoka, T.
2007-12-01
Recently, methane hydrate has been expected as a new and promising energy resource, and it abundantly occurs under the deep-sea beds. However, there is still a considerable technical and economical problem for a practical exploration of methane hydrate as an energy resource. For example, it is considerable difficult to control the stability of the methane hydrate reservoirs. In this way, it is fundamental to know and predict the process that controls the methane hydrate formation in order to produce it safely and efficiently. In this study, we simulate the process of methane hydrate crystal growth with CO2 substitution. We have adopted the combination of cellular automata with Monte Carlo method in a similar way as suggested by Buenas, Kvamme and Svandal (J. of Crystal Growth - 2006). The effects of CO2 substitution on methane hydrate growth will be investigated by considering diffusion of both species (CO2 and methane) and using the free energy of the systems that has been obtained by molecular dynamics calculations and thermodynamic data. The growth process is investigated under the relevant thermodynamic conditions (temperature and pressure) of methane hydrate reservoirs and takes in account three main physical effects: solidification of the liquid hydrate, the diffusion of the molecular species (CO2 and CH4) and the heat transport.
Kinetic Monte Carlo method for dislocation migration in the presence of solute
Deo, Chaitanya S.; Srolovitz, David J.; Cai Wei; Bulatov, Vasily V. [Princeton Materials Institute, Princeton University, Princeton, New Jersey 08540 (United States); Department of Materials Science and Engineering, University of Michigan, Ann Arbor, Michigan 48105 (United States); Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544 (United States); Princeton Materials Institute, Princeton University, Princeton, New Jersey 08544 (United States); Chemistry and Materials Science Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550 (United States)
2005-01-01
We present a kinetic Monte Carlo method for simulating dislocation motion in alloys within the framework of the kink model. The model considers the glide of a dislocation in a static, three-dimensional solute atom atmosphere. It includes both a description of the short-range interaction between a dislocation core and the solute and long-range solute-dislocation interactions arising from the interplay of the solute misfit and the dislocation stress field. Double-kink nucleation rates are calculated using a first-passage-time analysis that accounts for the subcritical annihilation of embryonic double kinks as well as the presence of solutes. We explicitly consider the case of the motion of a <111>-oriented screw dislocation on a {l_brace}011{r_brace}-slip plane in body-centered-cubic Mo-based alloys. Simulations yield dislocation velocity as a function of stress, temperature, and solute concentration. The dislocation velocity results are shown to be consistent with existing experimental data and, in some cases, analytical models. Application of this model depends upon the validity of the kink model and the availability of fundamental properties (i.e., single-kink energy, Peierls stress, secondary Peierls barrier to kink migration, single-kink mobility, solute-kink interaction energies, solute misfit), which can be obtained from first-principles calculations and/or molecular-dynamics simulations.
Assessment of the Contrast to Noise Ratio in PET Scanners with Monte Carlo Methods
NASA Astrophysics Data System (ADS)
Michail, C. M.; Karpetas, G. E.; Fountos, G. P.; Valais, I. G.; Nikolopoulos, D.; Kandarakis, I. S.; Panayiotakis, G. S.
2015-09-01
The aim of the present study was to assess the contrast to noise ratio (CNR) of PET scanners through a thin layer chromatography (TLC) plane source. The source was simulated using a previously validated Monte Carlo model. The model was developed by using the GATE MC package and reconstructed images obtained with the STIR software for tomographic image reconstruction. The PET scanner simulated was the GE DiscoveryST. A plane source consisted of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrates, immersed in 18F-FDG bath solution. Image quality was assessed in terms of the CNR. CNR was estimated from coronal reconstructed images of the plane source. Images were reconstructed by the maximum likelihood estimation (MLE)-OSMAPOSL. OSMAPOSL reconstruction was assessed by using various subsets (3, 15 and 21) and various iterations (2 to 20). CNR values were found to decrease when both iterations and subsets increase. Two (2) iterations were found to be optimal. The simulated PET evaluation method, based on the TLC plane source, can be useful in image quality assessment of PET scanners.
Numerical simulation of pulsed neutron induced gamma log using Monte Carlo method
NASA Astrophysics Data System (ADS)
Byeongho, Byeongho; Hwang, Seho; Shin, Jehyun; Park, Chang Je; Kim, Jongman; Kim, Ki-Seog
2015-04-01
Recently the neutron induced gamma log is the key role in shale play. This study was performed for understanding an energy characteristics spectrum of neutron induced gamma log using Monte Carlo method. A neutron generator which emits 14 MeV neutron particles was used. Flux of thermal neutron and capture gamma was calculated from detectors arranged at 10 cm intervals from neutron generator. Sandstone, limestone, granite, and basalt were selected to estimate and simulate response characteristics using MCNP. Also, the design for reducing effects of natural gamma (K, Th U) and back scattering was also applied to the sonde model in MCNP. Through results of energy spectrum analysis of capture gamma which detected to the detector in numerical sonde model, we knew that atoms which have wide neutron cross-section and are abundant in formation such as calcium, iron, silicon, magnesium, aluminium, hydrogen, and so forth were detected. Those results can help to design the optimal array of neutron and capture gamma detectors.
Inverse Monte-Carlo and Demon Methods for Effective Polyakov Loop Models of SU(N)-YM
Christian Wozar; Tobias Kaestner; Bjoern H. Wellegehausen; Andreas Wipf; Thomas Heinzl
2008-08-29
We study effective Polyakov loop models for SU(N) Yang-Mills theories at finite temperature. In particular effective models for SU(3) YM with an additional adjoint Polyakov loop potential are considered. The rich phase structure including a center and anti-center directed phase is reproduced with an effective model utilizing the inverse Monte-Carlo method. The demon method as a possibility to obtain the effective models' couplings is compared to the method of Schwinger-Dyson equations. Thermalization effects of microcanonical and canonical demon method are analyzed. Finally the elaborate canonical demon method is applied to the finite temperature SU(4) YM phase transition.
HRMC_1.1: Hybrid Reverse Monte Carlo method with silicon and carbon potentials
NASA Astrophysics Data System (ADS)
Opletal, G.; Petersen, T. C.; O'Malley, B.; Snook, I. K.; McCulloch, D. G.; Yarovsky, I.
2011-02-01
The Hybrid Reverse Monte Carlo (HRMC) code models the atomic structure of materials via the use of a combination of constraints including experimental diffraction data and an empirical energy potential. This energy constraint is in the form of either the Environment Dependent Interatomic Potential (EDIP) for carbon and silicon and the original and modified Stillinger-Weber potentials applicable to silicon. In this version, an update is made to correct an error in the EDIP carbon energy calculation routine. New version program summaryProgram title: HRMC version 1.1 Catalogue identifier: AEAO_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAO_v1_1.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 36 991 No. of bytes in distributed program, including test data, etc.: 907 800 Distribution format: tar.gz Programming language: FORTRAN 77 Computer: Any computer capable of running executables produced by the g77 Fortran compiler. Operating system: Unix, Windows RAM: Depends on the type of empirical potential use, number of atoms and which constraints are employed. Classification: 7.7 Catalogue identifier of previous version: AEAO_v1_0 Journal reference of previous version: Comput. Phys. Comm. 178 (2008) 777 Does the new version supersede the previous version?: Yes Nature of problem: Atomic modelling using empirical potentials and experimental data. Solution method: Monte Carlo Reasons for new version: An error in a term associated with the calculation of energies using the EDIP carbon potential which results in incorrect energies. Summary of revisions: Fix to correct brackets in the two body part of the EDIP carbon potential routine. Additional comments: The code is not standard FORTRAN 77 but includes some additional features and therefore generates errors when compiled using the Nag95 compiler. It does compile successfully with the GNU g77 compiler ( http://www.gnu.org/software/fortran/fortran.html). Running time: Depends on the type of empirical potential use, number of atoms and which constraints are employed. The test included in the distribution took 37 minutes on a DEC Alpha PC.
Dosimetric validation of Acuros XB with Monte Carlo methods for photon dose calculations
Bush, K.; Gagne, I. M.; Zavgorodni, S.; Ansbacher, W.; Beckham, W. [Department of Medical Physics, British Columbia Cancer Agency-Vancouver Island Center, Victoria, British Columbia V8R 6V5 (Canada)
2011-04-15
Purpose: The dosimetric accuracy of the recently released Acuros XB advanced dose calculation algorithm (Varian Medical Systems, Palo Alto, CA) is investigated for single radiation fields incident on homogeneous and heterogeneous geometries, and a comparison is made to the analytical anisotropic algorithm (AAA). Methods: Ion chamber measurements for the 6 and 18 MV beams within a range of field sizes (from 4.0x4.0 to 30.0x30.0 cm{sup 2}) are used to validate Acuros XB dose calculations within a unit density phantom. The dosimetric accuracy of Acuros XB in the presence of lung, low-density lung, air, and bone is determined using BEAMnrc/DOSXYZnrc calculations as a benchmark. Calculations using the AAA are included for reference to a current superposition/convolution standard. Results: Basic open field tests in a homogeneous phantom reveal an Acuros XB agreement with measurement to within {+-}1.9% in the inner field region for all field sizes and energies. Calculations on a heterogeneous interface phantom were found to agree with Monte Carlo calculations to within {+-}2.0%({sigma}{sub MC}=0.8%) in lung ({rho}=0.24 g cm{sup -3}) and within {+-}2.9%({sigma}{sub MC}=0.8%) in low-density lung ({rho}=0.1 g cm{sup -3}). In comparison, differences of up to 10.2% and 17.5% in lung and low-density lung were observed in the equivalent AAA calculations. Acuros XB dose calculations performed on a phantom containing an air cavity ({rho}=0.001 g cm{sup -3}) were found to be within the range of {+-}1.5% to {+-}4.5% of the BEAMnrc/DOSXYZnrc calculated benchmark ({sigma}{sub MC}=0.8%) in the tissue above and below the air cavity. A comparison of Acuros XB dose calculations performed on a lung CT dataset with a BEAMnrc/DOSXYZnrc benchmark shows agreement within {+-}2%/2mm and indicates that the remaining differences are primarily a result of differences in physical material assignments within a CT dataset. Conclusions: By considering the fundamental particle interactions in matter based on theoretical interaction cross sections, the Acuros XB algorithm is capable of modeling radiotherapy dose deposition with accuracy only previously achievable with Monte Carlo techniques.
Parallel Markov Chain Monte Carlo Methods for Large Scale Statistical Inverse Problems
Wang, Kainan
2014-04-18
but also the uncertainty of these estimations. Markov chain Monte Carlo (MCMC) is a useful technique to sample the posterior distribution and information can be extracted from the sampled ensemble. However, MCMC is very expensive to compute, especially...
[Study of Determination of Oil Mixture Components Content Based on Quasi-Monte Carlo Method].
Wang, Yu-tian; Xu, Jing; Liu, Xiao-fei; Chen, Meng-han; Wang, Shi-tao
2015-05-01
Gasoline, kerosene, diesel is processed by crude oil with different distillation range. The boiling range of gasoline is 35 ~205 °C. The boiling range of kerosene is 140~250 °C. And the boiling range of diesel is 180~370 °C. At the same time, the carbon chain length of differentmineral oil is different. The carbon chain-length of gasoline is within the scope of C7 to C11. The carbon chain length of kerosene is within the scope of C12 to C15. And the carbon chain length of diesel is within the scope of C15 to C18. The recognition and quantitative measurement of three kinds of mineral oil is based on different fluorescence spectrum formed in their different carbon number distribution characteristics. Mineral oil pollution occurs frequently, so monitoring mineral oil content in the ocean is very important. A new method of components content determination of spectra overlapping mineral oil mixture is proposed, with calculation of characteristic peak power integrationof three-dimensional fluorescence spectrum by using Quasi-Monte Carlo Method, combined with optimal algorithm solving optimum number of characteristic peak and range of integral region, solving nonlinear equations by using BFGS(a rank to two update method named after its inventor surname first letter, Boyden, Fletcher, Goldfarb and Shanno) method. Peak power accumulation of determined points in selected area is sensitive to small changes of fluorescence spectral line, so the measurement of small changes of component content is sensitive. At the same time, compared with the single point measurement, measurement sensitivity is improved by the decrease influence of random error due to the selection of points. Three-dimensional fluorescence spectra and fluorescence contour spectra of single mineral oil and the mixture are measured by taking kerosene, diesel and gasoline as research objects, with a single mineral oil regarded whole, not considered each mineral oil components. Six characteristic peaks are selected for characteristic peak power integration to determine components content of mineral oil mixture of gasoline, kerosene and diesel by optimal algorithm. Compared with single point measurement of peak method and mean method, measurement sensitivity is improved about 50 times. The implementation of high precision measurement of mixture components content of gasoline, kerosene and diesel provides a practical algorithm for components content direct determination of spectra overlapping mixture without chemical separation. PMID:26415451
NASA Astrophysics Data System (ADS)
Sacadura, J.-F.; Al Abed, A.
1983-11-01
Problems concerning heat transfer occurring simultaneously by means of conduction and radiation have important applications related to reentry heating and the employment of fibers as insulators. The Monte Carlo method has been utilized by Howell and Perlmutter (1964) in the solution of the pure radiation problem, and by Howell et al. (1965) for the study of the coupled radiation-convection problem in the steady state. In the present investigation, the Monte Carlo method is coupled with the finite difference method to solve the problem of the energy transfer in a homogeneous gray solid for cases in which radiation is an important mode of heat transfer. Both the transient and steady-state solutions are obtained.
Adaptive {delta}f Monte Carlo Method for Simulation of RF-heating and Transport in Fusion Plasmas
Hoeoek, J.; Hellsten, T.
2009-11-26
Essential for modeling heating and transport of fusion plasma is determining the distribution function of the plasma species. Characteristic for RF-heating is creation of particle distributions with a high energy tail. In the high energy region the deviation from a Maxwellian distribution is large while in the low energy region the distribution is close to a Maxwellian due to the velocity dependency of the collision frequency. Because of geometry and orbit topology Monte Carlo methods are frequently used. To avoid simulating the thermal part, {delta}f methods are beneficial. Here we present a new {delta}f Monte Carlo method with an adaptive scheme for reducing the total variance and sources, suitable for calculating the distribution function for RF-heating.
Dynamical estimation of neuron and network properties II: Path integral Monte Carlo methods.
Kostuk, Mark; Toth, Bryan A; Meliza, C Daniel; Margoliash, Daniel; Abarbanel, Henry D I
2012-03-01
Hodgkin-Huxley (HH) models of neuronal membrane dynamics consist of a set of nonlinear differential equations that describe the time-varying conductance of various ion channels. Using observations of voltage alone we show how to estimate the unknown parameters and unobserved state variables of an HH model in the expected circumstance that the measurements are noisy, the model has errors, and the state of the neuron is not known when observations commence. The joint probability distribution of the observed membrane voltage and the unobserved state variables and parameters of these models is a path integral through the model state space. The solution to this integral allows estimation of the parameters and thus a characterization of many biological properties of interest, including channel complement and density, that give rise to a neuron's electrophysiological behavior. This paper describes a method for directly evaluating the path integral using a Monte Carlo numerical approach. This provides estimates not only of the expected values of model parameters but also of their posterior uncertainty. Using test data simulated from neuronal models comprising several common channels, we show that short (<50 ms) intracellular recordings from neurons stimulated with a complex time-varying current yield accurate and precise estimates of the model parameters as well as accurate predictions of the future behavior of the neuron. We also show that this method is robust to errors in model specification, supporting model development for biological preparations in which the channel expression and other biophysical properties of the neurons are not fully known. PMID:22526358
A Markov Chain Monte Carlo method for the groundwater inverse problem.
Lu, Z.; Higdon, D. M.; Zhang, D.
2004-01-01
In this study, we develop a Markov Chain Monte Carlo method (MCMC) to estimate the hydraulic conductivity field conditioned on the direct measurements of hydraulic conductivity and indirect measurements of dependent variables such as hydraulic head for saturated flow in randomly heterogeneous porous media. The log hydraulic conductivity field is represented (parameterized) by the combination of some basis kernels centered at fixed spatial locations. The prior distribution for the vector of coefficients {theta} are taken from a posterior distribution {pi}({theta}/d) that is proportional to the product of the likelihood function of measurements d given parameter vector {theta} and the prior distribution of {theta}. Starting from any initial setting, a partial realization of a Markov chain is generated by updating only one component of {theta} at a time according to Metropolis rules. This ensures that output from this chain has {pi}({theta}/d) as its stationary distribution. The posterior mean of the parameter {theta} (and thus the mean log hydraulic conductivity conditional to measurements on hydraulic conductivity, and hydraulic head) can be estimated from the Markov chain realizations (ignoring some early realizations). The uncertainty associated with the mean filed can also be assessed from these realizations. In addition, the MCMC approach provides an alternative for estimating conditional predictions of hydraulic head and concentration and their associated uncertainties. Numerical examples for flow in a hypothetic random porous medium show that estimated log hydraulic conductivity field from the MCMC approach is closer to the original hypothetical random field than those obtained using kriging or cokriging methods.
Range Verification Methods in Particle Therapy: Underlying Physics and Monte Carlo Modeling
Kraan, Aafke Christine
2015-01-01
Hadron therapy allows for highly conformal dose distributions and better sparing of organs-at-risk, thanks to the characteristic dose deposition as function of depth. However, the quality of hadron therapy treatments is closely connected with the ability to predict and achieve a given beam range in the patient. Currently, uncertainties in particle range lead to the employment of safety margins, at the expense of treatment quality. Much research in particle therapy is therefore aimed at developing methods to verify the particle range in patients. Non-invasive in vivo monitoring of the particle range can be performed by detecting secondary radiation, emitted from the patient as a result of nuclear interactions of charged hadrons with tissue, including ?+ emitters, prompt photons, and charged fragments. The correctness of the dose delivery can be verified by comparing measured and pre-calculated distributions of the secondary particles. The reliability of Monte Carlo (MC) predictions is a key issue. Correctly modeling the production of secondaries is a non-trivial task, because it involves nuclear physics interactions at energies, where no rigorous theories exist to describe them. The goal of this review is to provide a comprehensive overview of various aspects in modeling the physics processes for range verification with secondary particles produced in proton, carbon, and heavier ion irradiation. We discuss electromagnetic and nuclear interactions of charged hadrons in matter, which is followed by a summary of some widely used MC codes in hadron therapy. Then, we describe selected examples of how these codes have been validated and used in three range verification techniques: PET, prompt gamma, and charged particle detection. We include research studies and clinically applied methods. For each of the techniques, we point out advantages and disadvantages, as well as clinical challenges still to be addressed, focusing on MC simulation aspects. PMID:26217586
NASA Astrophysics Data System (ADS)
Harries, Tim J.
2015-04-01
We present a set of new numerical methods that are relevant to calculating radiation pressure terms in hydrodynamics calculations, with a particular focus on massive star formation. The radiation force is determined from a Monte Carlo estimator and enables a complete treatment of the detailed microphysics, including polychromatic radiation and anisotropic scattering, in both the free-streaming and optically thick limits. Since the new method is computationally demanding we have developed two new methods that speed up the algorithm. The first is a photon packet splitting algorithm that enables efficient treatment of the Monte Carlo process in very optically thick regions. The second is a parallelization method that distributes the Monte Carlo workload over many instances of the hydrodynamic domain, resulting in excellent scaling of the radiation step. We also describe the implementation of a sink particle method that enables us to follow the accretion on to, and the growth of, the protostars. We detail the results of extensive testing and benchmarking of the new algorithms.
Capote, Roberto [Nuclear Data Section, International Atomic Energy Agency, P.O. Box 100, Wagramer Strasse 5, A-1400 Vienna (Austria)], E-mail: Roberto.CapoteNoy@iaea.org; Smith, Donald L. [Argonne National Laboratory, 1710 Avenida del Mundo, Coronado, California 92118-3073 (United States)
2008-12-15
The Unified Monte Carlo method (UMC) has been suggested to avoid certain limitations and approximations inherent to the well-known Generalized Least Squares (GLS) method of nuclear data evaluation. This contribution reports on an investigation of the performance of the UMC method in comparison with the GLS method. This is accomplished by applying both methods to simple examples with few input values that were selected to explore various features of the evaluation process that impact upon the quality of an evaluation. Among the issues explored are: i) convergence of UMC results with the number of Monte Carlo histories and the ranges of sampled values; ii) a comparison of Monte Carlo sampling using the Metropolis scheme and a brute force approach; iii) the effects of large data discrepancies; iv) the effects of large data uncertainties; v) the effects of strong or weak model or experimental data correlations; and vi) the impact of ratio data and integral data. Comparisons are also made of the evaluated results for these examples when the input values are first transformed to comparable logarithmic values prior to performing the evaluation. Some general conclusions that are applicable to more realistic evaluation exercises are offered.
Simulating the proton transfer in gramicidin A by a sequential dynamical Monte Carlo method.
Till, Mirco S; Essigke, Timm; Becker, Torsten; Ullmann, G Matthias
2008-10-23
The large interest in long-range proton transfer in biomolecules is triggered by its importance for many biochemical processes such as biological energy transduction and drug detoxification. Since long-range proton transfer occurs on a microsecond time scale, simulating this process on a molecular level is still a challenging task and not possible with standard simulation methods. In general, the dynamics of a reactive system can be described by a master equation. A natural way to describe long-range charge transfer in biomolecules is to decompose the process into elementary steps which are transitions between microstates. Each microstate has a defined protonation pattern. Although such a master equation can in principle be solved analytically, it is often too demanding to solve this equation because of the large number of microstates. In this paper, we describe a new method which solves the master equation by a sequential dynamical Monte Carlo algorithm. Starting from one microstate, the evolution of the system is simulated as a stochastic process. The energetic parameters required for these simulations are determined by continuum electrostatic calculations. We apply this method to simulate the proton transfer through gramicidin A, a transmembrane proton channel, in dependence on the applied membrane potential and the pH value of the solution. As elementary steps in our reaction, we consider proton uptake and release, proton transfer along a hydrogen bond, and rotations of water molecules that constitute a proton wire through the channel. A simulation of 8 mus length took about 5 min on an Intel Pentium 4 CPU with 3.2 GHz. We obtained good agreement with experimental data for the proton flux through gramicidin A over a wide range of pH values and membrane potentials. We find that proton desolvation as well as water rotations are equally important for the proton transfer through gramicidin A at physiological membrane potentials. Our method allows to simulate long-range charge transfer in biological systems at time scales, which are not accessible by other methods. PMID:18826179
Forward treatment planning for modulated electron radiotherapy (MERT) employing Monte Carlo methods
Henzen, D., E-mail: henzen@ams.unibe.ch; Manser, P.; Frei, D.; Volken, W.; Born, E. J.; Lössl, K.; Aebersold, D. M.; Fix, M. K. [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010 Berne (Switzerland)] [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010 Berne (Switzerland); Neuenschwander, H. [Clinic for Radiation-Oncology, Lindenhofspital Bern, CH-3012 Berne (Switzerland)] [Clinic for Radiation-Oncology, Lindenhofspital Bern, CH-3012 Berne (Switzerland); Stampanoni, M. F. M. [Institute for Biomedical Engineering, ETH Zürich and Paul Scherrer Institut, CH-5234 Villigen (Switzerland)] [Institute for Biomedical Engineering, ETH Zürich and Paul Scherrer Institut, CH-5234 Villigen (Switzerland)
2014-03-15
Purpose: This paper describes the development of a forward planning process for modulated electron radiotherapy (MERT). The approach is based on a previously developed electron beam model used to calculate dose distributions of electron beams shaped by a photon multi leaf collimator (pMLC). Methods: As the electron beam model has already been implemented into the Swiss Monte Carlo Plan environment, the Eclipse treatment planning system (Varian Medical Systems, Palo Alto, CA) can be included in the planning process for MERT. In a first step, CT data are imported into Eclipse and a pMLC shaped electron beam is set up. This initial electron beam is then divided into segments, with the electron energy in each segment chosen according to the distal depth of the planning target volume (PTV) in beam direction. In order to improve the homogeneity of the dose distribution in the PTV, a feathering process (Gaussian edge feathering) is launched, which results in a number of feathered segments. For each of these segments a dose calculation is performed employing the in-house developed electron beam model along with the macro Monte Carlo dose calculation algorithm. Finally, an automated weight optimization of all segments is carried out and the total dose distribution is read back into Eclipse for display and evaluation. One academic and two clinical situations are investigated for possible benefits of MERT treatment compared to standard treatments performed in our clinics and treatment with a bolus electron conformal (BolusECT) method. Results: The MERT treatment plan of the academic case was superior to the standard single segment electron treatment plan in terms of organs at risk (OAR) sparing. Further, a comparison between an unfeathered and a feathered MERT plan showed better PTV coverage and homogeneity for the feathered plan, with V{sub 95%} increased from 90% to 96% and V{sub 107%} decreased from 8% to nearly 0%. For a clinical breast boost irradiation, the MERT plan led to a similar homogeneity in the PTV compared to the standard treatment plan while the mean body dose was lower for the MERT plan. Regarding the second clinical case, a whole breast treatment, MERT resulted in a reduction of the lung volume receiving more than 45% of the prescribed dose when compared to the standard plan. On the other hand, the MERT plan leads to a larger low-dose lung volume and a degraded dose homogeneity in the PTV. For the clinical cases evaluated in this work, treatment plans using the BolusECT technique resulted in a more homogenous PTV and CTV coverage but higher doses to the OARs than the MERT plans. Conclusions: MERT treatments were successfully planned for phantom and clinical cases, applying a newly developed intuitive and efficient forward planning strategy that employs a MC based electron beam model for pMLC shaped electron beams. It is shown that MERT can lead to a dose reduction in OARs compared to other methods. The process of feathering MERT segments results in an improvement of the dose homogeneity in the PTV.
NASA Astrophysics Data System (ADS)
Kannenberg, Keith Christopher
The impingement of gas plumes from small thrusters on spacecraft surfaces is modeled using the direct simulation Monte Carlo (DSMC) technique. Strategies for improving the efficiency and resolution of DSMC simulations are presented. These methods include variable scaling of simulation parameters and computational grid design. Computational cost of a simulation can be reduced by as much as two orders of magnitude using these methods. A parallel, three-dimensional implementation of the DSMC method is described. A flexible, cell-based grid methodology is employed which allows the use of structured, unstructured or hybrid grids. This provides the ability to handle complex geometric configurations. An efficient particle tracing scheme is used for particle movement which eliminates the need for an explicit sorting step. Strong numerical performance and high parallel efficiencies are obtained. Several impingement problems are investigated in order to test the accuracy and performance of the DSMC method and implementation for plume flows. The first problem is a nitrogen plume from a resistojet nozzle impinging on an axisymmetric body. The plume flow is started with exit plane data from a simulation of the diverging section of the nozzle. Good agreement is found with experimental data for surface pressure over a range of body locations. A free jet of nitrogen impacting on an inclined flat plate is examined as a three-dimensional test case. The three-dimensional code is validated through comparison with an axisymmetric simulation of the case where the plume axis is normal to the plate. Good agreement is found with experimental measurements of surface pressure, shear stress and heat transfer for several plate orientations. Free molecular analysis is found to over predict surface properties while providing good qualitative agreement. The plume of a hydrazine thruster mounted on a model satellite configuration is investigated to demonstrate the ability to compute complex configurations. Surface properties and integrated impingement effects are calculated on a solar array panel. The plume is shown to transfer a significant fraction of the thruster's momentum and energy to the array. Free molecular analysis is less accurate as a result of multi species and boundary layer effects.
Somasundaram, E.; Palmer, T. S. [Department of Nuclear Engineering and Radiation Health Physics, Oregon State University, 116 Radiation Center, Corvallis, OR 97332-5902 (United States)
2013-07-01
In this paper, the work that has been done to implement variance reduction techniques in a three dimensional, multi group Monte Carlo code - Tortilla, that works within the frame work of the commercial deterministic code - Attila, is presented. This project is aimed to develop an integrated Hybrid code that seamlessly takes advantage of the deterministic and Monte Carlo methods for deep shielding radiation detection problems. Tortilla takes advantage of Attila's features for generating the geometric mesh, cross section library and source definitions. Tortilla can also read importance functions (like adjoint scalar flux) generated from deterministic calculations performed in Attila and use them to employ variance reduction schemes in the Monte Carlo simulation. The variance reduction techniques that are implemented in Tortilla are based on the CADIS (Consistent Adjoint Driven Importance Sampling) method and the LIFT (Local Importance Function Transform) method. These methods make use of the results from an adjoint deterministic calculation to bias the particle transport using techniques like source biasing, survival biasing, transport biasing and weight windows. The results obtained so far and the challenges faced in implementing the variance reduction techniques are reported here. (authors)
Neoclassical electron transport calculation by using {delta}f Monte Carlo method
Matsuoka, Seikichi [Graduate University for Advanced Studies (SOKENDAI), Toki 509-5292 (Japan); Satake, Shinsuke; Yokoyama, Masayuki [Graduate University for Advanced Studies (SOKENDAI), Toki 509-5292 (Japan); National Institute for Fusion Science, Toki 509-5292 (Japan); Wakasa, Arimitsu; Murakami, Sadayoshi [Department of Nuclear Engineering, Kyoto University, Kyoto 606-8501 (Japan)
2011-03-15
High electron temperature plasmas with steep temperature gradient in the core are obtained in recent experiments in the Large Helical Device [A. Komori et al., Fusion Sci. Technol. 58, 1 (2010)]. Such plasmas are called core electron-root confinement (CERC) and have attracted much attention. In typical CERC plasmas, the radial electric field shows a transition phenomenon from a small negative value (ion root) to a large positive value (electron root) and the radial electric field in helical plasmas are determined dominantly by the ambipolar condition of neoclassical particle flux. To investigate such plasmas' neoclassical transport precisely, the numerical neoclassical transport code, FORTEC-3D [S. Satake et al., J. Plasma Fusion Res. 1, 002 (2006)], which solves drift kinetic equation based on {delta}f Monte Carlo method and has been applied for ion species so far, is extended to treat electron neoclassical transport. To check the validity of our new FORTEC-3D code, benchmark calculations are carried out with GSRAKE [C. D. Beidler et al., Plasma Phys. Controlled Fusion 43, 1131 (2001)] and DCOM/NNW [A. Wakasa et al., Jpn. J. Appl. Phys. 46, 1157 (2007)] codes which calculate neoclassical transport using certain approximations. The benchmark calculation shows a good agreement among FORTEC-3D, GSRAKE and DCOM/NNW codes for a low temperature (T{sub e}(0)=1.0 keV) plasma. It is also confirmed that finite orbit width effect included in FORTEC-3D affects little neoclassical transport even for the low collisionality plasma if the plasma is at the low temperature. However, for a higher temperature (5 keV at the core) plasma, significant difference arises among FORTEC-3D, GSRAKE, and DCOM/NNW. These results show an importance to evaluate electron neoclassical transport by solving the kinetic equation rigorously including effect of finite radial drift for high electron temperature plasmas.
Spray cooling simulation implementing time scale analysis and the Monte Carlo method
NASA Astrophysics Data System (ADS)
Kreitzer, Paul Joseph
Spray cooling research is advancing the field of heat transfer and heat rejection in high power electronics. Smaller and more capable electronics packages are producing higher amounts of waste heat, along with smaller external surface areas, and the use of active cooling is becoming a necessity. Spray cooling has shown extremely high levels of heat rejection, of up to 1000 W/cm 2 using water. Simulations of spray cooling are becoming more realistic, but this comes at a price. A previous researcher has used CFD to successfully model a single 3D droplet impact into a liquid film using the level set method. However, the complicated multiphysics occurring during spray impingement and surface interactions increases computation time to more than 30 days. Parallel processing on a 32 processor system has reduced this time tremendously, but still requires more than a day. The present work uses experimental and computational results in addition to numerical correlations representing the physics occurring on a heated impingement surface. The current model represents the spray behavior of a Spraying Systems FullJet 1/8-g spray nozzle. Typical spray characteristics are indicated as follows: flow rate of 1.05x10-5 m3/s, normal droplet velocity of 12 m/s, droplet Sauter mean diameter of 48 microm, and heat flux values ranging from approximately 50--100 W/cm2 . This produces non-dimensional numbers of: We 300--1350, Re 750--3500, Oh 0.01--0.025. Numerical and experimental correlations have been identified representing crater formation, splashing, film thickness, droplet size, and spatial flux distributions. A combination of these methods has resulted in a Monte Carlo spray impingement simulation model capable of simulating hundreds of thousands of droplet impingements or approximately one millisecond. A random sequence of droplet impingement locations and diameters is generated, with the proper radial spatial distribution and diameter distribution. Hence the impingement, lifetime and interactions of the droplet impact craters are tracked versus time within the limitations of the current model. A comparison of results from this code to experimental results shows similar trends in surface behavior and heat transfer values. Three methods have been used to directly compare the simulation results with published experimental data, including: contact line length estimates, empirical heat transfer equation calculations, and non-dimensional Nusselt numbers. A Nusselt number of 55.5 was calculated for experimental values, while a Nu of 16.0 was calculated from the simulation.
Monte-Carlo methods for chemical-mechanical planarization on multiple-layer and dual-material models
NASA Astrophysics Data System (ADS)
Chen, Yu; Kahng, Andrew B.; Robins, Gabriel; Zelikovsky, Alexander
2002-07-01
Chemical-mechanical planarization (CMP) and other manufacturing steps in very deep submicron VLSI have varying effects on device and interconnect features, depending on the local layout density. To improve manufacturability and performance predictability, we seek to make a layout uniform with respect to prescribed density criteria, by inserting area fill geometries in to the layout. We review previous research on single-layer fill for flat and hierarchical layout density control based on the Interlevel Dielectric CMP model. We also describe the recent combination of CMP physical modeling and linear programing for multiple-layer density control, as well as the Shallow Trench Isolation CMP model. Our work makes the following contributions for the Multiple-layer Interlevel Dielectric CMP model. First, we propose a new linear programming approach with a new objective for the multiple-layer fill problem. Second, we describe modified Monte-Carlo approaches for the multiple- layer fill problem. Comparisons with previous approaches show that the new linear programming method is more reasonable for manufacturability, and that the Monte-Carlo approach is efficient and yields more accurate results for large layouts. The CMP step in Shallow Trench Isolation (STI) is a dual-material polishing process, i.e., multiple materials are being polished simultaneously during the CMP process. Simple greedy methods were proposed for the non- linear problem with Min-Var and Min-Fill objectives, where the certain amount of dummy features are always added at a position with the smallest density. In this paper, we propose more efficient Monte-Carlo methods for the Min-Var objective, as well a improved Greedy and Monte-Carlo methods for the Min-Fill objective. Our experimental experience shows that they can get better solutions with respect to the objectives.
D'Angola, A.; Tuttafesta, M.; Guadagno, M.; Santangelo, P.; Laricchiuta, A.; Colonna, G.; Capitelli, M.
2012-11-27
Calculations of thermodynamic properties of Helium plasma by using the Reaction Ensemble Monte Carlo method (REMC) are presented. Non ideal effects at high pressure are observed. Calculations, performed by using Exp-6 or multi-potential curves in the case of neutral-charge interactions, show that in the thermodynamic conditions considered no significative differences are observed. Results have been obtained by using a Graphics Processing Unit (GPU)-CUDA C version of REMC.
Williams, M. L.; Gehin, J. C.; Clarno, K. T.
2006-07-01
The TSUNAMI computational sequences currently in the SCALE 5 code system provide an automated approach to performing sensitivity and uncertainty analysis for eigenvalue responses, using either one-dimensional discrete ordinates or three-dimensional Monte Carlo methods. This capability has recently been expanded to address eigenvalue-difference responses such as reactivity changes. This paper describes the methodology and presents results obtained for an example advanced CANDU reactor design. (authors)
Lawson, A B
The spatial modelling of small area health data has, for some time, included spatial autocorrelation as a random effect. This effect is non-specific and global and does not address the location of clusters of disease (a specific task). This paper addresses the need for specific and non-specific random effects within spatial epidemiology. In addition, individual frailty is also considered important and a computational algorithm based on reversible jump Markov chain Monte Carlo (RJMCMC) methods is described. PMID:10960859
NASA Astrophysics Data System (ADS)
Odorico, R.
1981-06-01
A Monte Carlo method is presented for the calculation of the QCD evolution of structure functions. Its application is discussed in detail in the framework of the LLA, but it can also be used with modified parton decay probability functions including higher-order effects. For heavy quark production, threshold constraints can be correctly taken into account, and one obtains results which at low Q2 are consistent with those of the photon-gluon fusion model.
NASA Astrophysics Data System (ADS)
Yesilyurt, Gokhan
Two of the primary challenges associated with the neutronic analysis of the Very High Temperature Reactor (VHTR) are accounting for resonance self-shielding in the particle fuel (contributing to the double heterogeneity) and accounting for temperature feedback due to Doppler broadening. The double heterogeneity challenge is addressed by defining a "double heterogeneity factor" (DHF) that allows conventional light water reactor (LWR) lattice physics codes to analyze VHTR configurations. The challenge of treating Doppler broadening is addressed by a new "on-the-fly" methodology that is applied during the random walk process with negligible impact on computational efficiency. Although this methodology was motivated by the need to treat temperature feedback in a VHTR, it is applicable to any reactor design. The on-the-fly Doppler methodology is based on a combination of Taylor and asymptotic series expansions. The type of series representation was determined by investigating the temperature dependence of U238 resonance cross sections in three regions: near the resonance peaks, mid-resonance, and the resonance wings. The coefficients for these series expansions were determined by regressions over the energy and temperature range of interest. The comparison of the broadened cross sections using this methodology with the NJOY cross sections was excellent. A Monte Carlo code was implemented to apply the combined regression model and used to estimate the additional computing cost which was found to be less than 1%. The DHF accounts for the effect of the particle heterogeneity on resonance absorption in particle fuel. The first level heterogeneity posed by the VHTR fuel particles is a unique characteristic that cannot be accounted for by conventional LWR lattice physics codes. On the other hand, Monte Carlo codes can take into account the detailed geometry of the VHTR including resolution of individual fuel particles without performing any type of resonance approximation. The DHF, basically a self shielding factor, was found to be weakly dependent on space and fuel depletion. The DHF only depends strongly on the packing fraction in a fuel compact. Therefore, it is proposed that DHFs be tabulated as a function of packing fraction to analyze the heterogeneous fuel in VHTR configuration with LWR lattice physics codes.
Alrefae, T
2014-12-01
A simple method of efficiency calibration for gamma spectrometry was performed. This method, which focused on measuring the radioactivity of (137)Cs in food samples, was based on Monte Carlo simulations available in the free-of-charge toolkit GEANT4. Experimentally, the efficiency values of a high-purity germanium detector were calculated for three reference materials representing three different food items. These efficiency values were compared with their counterparts produced by a computer code that simulated experimental conditions. Interestingly, the output of the simulation code was in acceptable agreement with the experimental findings, thus validating the proposed method. PMID:24214912
Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues
Harris, G.; Van Horn, R.
1996-06-01
The EPA is increasingly considering the use of probabilistic risk assessment techniques as an alternative or refinement of the current point estimate of risk. This report provides an overview of the probabilistic technique called Monte Carlo Analysis. Advantages and disadvantages of implementing a Monte Carlo analysis over a point estimate analysis for environmental risk assessment are discussed. The general methodology is provided along with an example of its implementation. A phased approach to risk analysis that allows iterative refinement of the risk estimates is recommended for use at the INEL.
Magnetic interpretation by the Monte Carlo method with application to the intrusion of the Crimea
NASA Astrophysics Data System (ADS)
Gryshchuk, Pavlo
2014-05-01
The study involves the application of geophysical methods for geological mapping. Magnetic and radiometric measurements were used to delineate the intrusive bodies in Bakhchysarai region of the Crimea. Proton magnetometers used to measure the total magnetic field in the area and variation station. Scintillation radiometer used to determine the radiation dose. Due to susceptimeter measured the magnetic susceptibility of rocks. It deal with the fact that in this area of research the rock mass appears on the surface. Anomalous values of the magnetic intensity were obtained as the difference between the observed measurements and values on variation station. Through geophysical data were given maps of the anomalous magnetic field, radiation dose, and magnetic susceptibility. Geology of area consisted from magmatic rocks and overlying sedimentary rocks. The main task of research was to study the geometry and the magnetization vector of igneous rocks. Intrusive body composed of diabase and had an average magnetic susceptibility, weak dose rate and negative magnetic field. Sedimentary rocks were represented by clays. They had a low value of the magnetic susceptibility and the average dose rate. Map of magnetic susceptibility gave information about the values and distribution of magnetized bodies close to the surface. These data were used to control and elaboration the data of the magnetic properties for magnetic modelling. Magnetic anomaly map shows the distribution of magnetization in depth. Interpretation profile was located perpendicular to the strike of the intrusive body. Modelling was performed for profile of the magnetic field. Used the approach for filling by rectangular blocks of geological media. The fitting implemented for value magnetization and its vector for ever block. Fitting was carried out using the Monte Carlo method in layers from the bottom to top. After passing through all the blocks were fixed magnetic parameters of the block with the best approximation between the theoretical and observed fields i.e. object function. It was first iteration. The next iteration begins with this block. If after next access through blocks was not reduce the objective function is carried out with the passage of the last block as in the first iteration. This technique worked well for separate synthetic models. As result was obtained the geometric boundaries of geological objects. Igneous rocks are nearly vertical magnetization with respect to the current field. Perhaps, this is because the Jurassic diabase at its formation frozen in time when the magnetic poles have opposite signs in comparison to the modern magnetic field. Due to the magnetic modelling obtained geological section that consistent with geological concept.
Evans, J. S.; Chan, S. I.; Goddard, W. A.
1995-01-01
Many interesting proteins possess defined sequence stretches containing negatively charged amino acids. At present, experimental methods (X-ray crystallography, NMR) have failed to provide structural data for many of these sequence domains. We have applied the dihedral probability grid-Monte Carlo (DPG-MC) conformational search algorithm to a series of N- and C-capped polyelectrolyte peptides, (Glu)20, (Asp)20, (PSer)20, and (PSer-Asp)10, that represent polyanionic regions in a number of important proteins, such as parathymosin, calsequestrin, the sodium channel protein, and the acidic biomineralization proteins. The atomic charges were estimated from charge equilibration and the valence and van der Waals parameters are from DREIDING. Solvation of the carboxylate and phosphate groups was treated using sodium counterions for each charged side chain (one Na+ for COO-; two Na for CO(PO3)-2) plus a distance-dependent (shielded) dielectric constant, epsilon = epsilon 0 R, to simulate solvent water. The structures of these polyelectrolyte polypeptides were obtained by the DPG-MC conformational search with epsilon 0 = 10, followed by calculation of solvation energies for the lowest energy conformers using the protein dipole-Langevin dipole method of Warshel. These calculations predict a correlation between amino acid sequence and global folded conformational minima: 1. Poly-L-Glu20, our structural benchmark, exhibited a preference for right-handed alpha-helix (47% helicity), which approximates experimental observations of 55-60% helicity in solution. 2. For Asp- and PSer-containing sequences, all conformers exhibited a low preference for right-handed alpha-helix formation (< or = 10%), but a significant percentage (approximately 20% or greater) of beta-strand and beta-turn dihedrals were found in all three sequence cases: (1) Aspn forms supercoil conformers, with a 2:1:1 ratio of beta-turn:beta-strand:alpha-helix dihedral angles; (2) PSer20 features a nearly 1:1 ratio of beta-turn:beta-sheet dihedral preferences, with very little preference for alpha-helical structure, and possesses short regions of strand and turn combinations that give rise to a collapsed bend or hairpin structure; (3) (PSer-Asp)10 features a 3:2:1 ratio of beta-sheet:beta-turn:alpha-helix and gives rise to a superturn or C-shaped structure. PMID:8535238
Kumar, Sudhir; Srinivasan, P; Sharma, S D; Saxena, Sanjay Kumar; Bakshi, A K; Dash, Ashutosh; Babu, D A R; Sharma, D N
2015-09-01
Isotope production and Application Division of Bhabha Atomic Research Center developed (32)P patch sources for treatment of superficial tumors. Surface dose rate of a newly developed (32)P patch source of nominal diameter 25mm was measured experimentally using standard extrapolation ionization chamber and Gafchromic EBT film. Monte Carlo model of the (32)P patch source along with the extrapolation chamber was also developed to estimate the surface dose rates from these sources. The surface dose rates to tissue (cGy/min) measured using extrapolation chamber and radiochromic films are 82.03±4.18 (k=2) and 79.13±2.53 (k=2) respectively. The two values of the surface dose rates measured using the two independent experimental methods are in good agreement to each other within a variation of 3.5%. The surface dose rate to tissue (cGy/min) estimated using the MCNP Monte Carlo code works out to be 77.78±1.16 (k=2). The maximum deviation between the surface dose rates to tissue obtained by Monte Carlo and the extrapolation chamber method is 5.2% whereas the difference between the surface dose rates obtained by radiochromic film measurement and the Monte Carlo simulation is 1.7%. The three values of the surface dose rates of the (32)P patch source obtained by three independent methods are in good agreement to one another within the uncertainties associated with their measurements and calculation. This work has demonstrated that MCNP based electron transport simulations are accurate enough for determining the dosimetry parameters of the indigenously developed (32)P patch sources for contact brachytherapy applications. PMID:26086681
A study of the XY model by the Monte Carlo method
NASA Technical Reports Server (NTRS)
Suranyi, Peter; Harten, Paul
1987-01-01
The massively parallel processor is used to perform Monte Carlo simulations for the two dimensional XY model on lattices of sizes up to 128 x 128. A parallel random number generator was constructed, finite size effects were studied, and run times were compared with those on a CRAY X-MP supercomputer.
Implementation of a Monte Carlo method to model photon conversion for solar cells
C. del Cañizo; I. Tobías; J. Perezbedmar; A. C. Pan; A. Luque
2008-01-01
A physical model describing different photon conversion mechanisms is presented in the context of photovoltaic applications. To solve the resulting system of equations, a Monte Carlo ray-tracing model is implemented, which takes into account the coupling of the photon transport phenomena to the non-linear rate equations describing luminescence. It also separates the generation of rays from the two very different
A Monte Carlo Method for Testing the Statistical Significance of a Regression Equation
Iver A. Lund
1970-01-01
A Monte Carlo technique for testing the statistical significance of an estimate by regression is described. It is illustrated on a medium-range prediction of precipitation. The purpose of the technique is to permit the use of all data available while developing a regression equation. This is especially important when the sample is small. The need for setting aside a fraction
A Bayesian Approach to Multiscale Inverse Problems Using Sequential Monte Carlo Method
Zabaras, Nicholas J.
;Motivation Methodology Case Studies Outline I 1 Outline 2 Motivation 3 Methodology Parameter Field Representation Sparse Grid Bayesian Model Sequential Monte Carlo 4 Case Studies Example 1 : Linear Log Permeability Example 2 : Gaussian Process Log-Permeability Example 3 : Variogram Model Example 4 : Channelized
Nanothermodynamics of large iron clusters by means of a flat histogram Monte Carlo method
Basire, M.; Soudan, J.-M.; Angelié, C.
2014-09-14
The thermodynamics of iron clusters of various sizes, from 76 to 2452 atoms, typical of the catalyst particles used for carbon nanotubes growth, has been explored by a flat histogram Monte Carlo (MC) algorithm (called the ?-mapping), developed by Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. This method provides the classical density of states, g{sub p}(E{sub p}) in the configurational space, in terms of the potential energy of the system, with good and well controlled convergence properties, particularly in the melting phase transition zone which is of interest in this work. To describe the system, an iron potential has been implemented, called “corrected EAM” (cEAM), which approximates the MEAM potential of Lee et al. [Phys. Rev. B 64, 184102 (2001)] with an accuracy better than 3 meV/at, and a five times larger computational speed. The main simplification concerns the angular dependence of the potential, with a small impact on accuracy, while the screening coefficients S{sub ij} are exactly computed with a fast algorithm. With this potential, ergodic explorations of the clusters can be performed efficiently in a reasonable computing time, at least in the upper half of the solid zone and above. Problems of ergodicity exist in the lower half of the solid zone but routes to overcome them are discussed. The solid-liquid (melting) phase transition temperature T{sub m} is plotted in terms of the cluster atom number N{sub at}. The standard N{sub at}{sup ?1/3} linear dependence (Pawlow law) is observed for N{sub at} >300, allowing an extrapolation up to the bulk metal at 1940 ±50 K. For N{sub at} <150, a strong divergence is observed compared to the Pawlow law. The melting transition, which begins at the surface, is stated by a Lindemann-Berry index and an atomic density analysis. Several new features are obtained for the thermodynamics of cEAM clusters, compared to the Rydberg pair potential clusters studied in Paper I.
Nanothermodynamics of large iron clusters by means of a flat histogram Monte Carlo method.
Basire, M; Soudan, J-M; Angelié, C
2014-09-14
The thermodynamics of iron clusters of various sizes, from 76 to 2452 atoms, typical of the catalyst particles used for carbon nanotubes growth, has been explored by a flat histogram Monte Carlo (MC) algorithm (called the ?-mapping), developed by Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. This method provides the classical density of states, gp(Ep) in the configurational space, in terms of the potential energy of the system, with good and well controlled convergence properties, particularly in the melting phase transition zone which is of interest in this work. To describe the system, an iron potential has been implemented, called "corrected EAM" (cEAM), which approximates the MEAM potential of Lee et al. [Phys. Rev. B 64, 184102 (2001)] with an accuracy better than 3 meV/at, and a five times larger computational speed. The main simplification concerns the angular dependence of the potential, with a small impact on accuracy, while the screening coefficients S(ij) are exactly computed with a fast algorithm. With this potential, ergodic explorations of the clusters can be performed efficiently in a reasonable computing time, at least in the upper half of the solid zone and above. Problems of ergodicity exist in the lower half of the solid zone but routes to overcome them are discussed. The solid-liquid (melting) phase transition temperature T(m) is plotted in terms of the cluster atom number N(at). The standard N(at)(-1/3) linear dependence (Pawlow law) is observed for N(at) >300, allowing an extrapolation up to the bulk metal at 1940 ±50 K. For N(at) <150, a strong divergence is observed compared to the Pawlow law. The melting transition, which begins at the surface, is stated by a Lindemann-Berry index and an atomic density analysis. Several new features are obtained for the thermodynamics of cEAM clusters, compared to the Rydberg pair potential clusters studied in Paper I. PMID:25217913
NASA Astrophysics Data System (ADS)
Hirvijoki, E.; Kurki-Suonio, T.; Äkäslompolo, S.; Varje, J.; Koskela, T.; Miettunen, J.
2015-06-01
This paper explains how to obtain the distribution function of minority ions in tokamak plasmas using the Monte Carlo method. Since the emphasis is on energetic ions, the guiding-center transformation is outlined, including also the transformation of the collision operator. Even within the guiding-center formalism, the fast particle simulations can still be very CPU intensive and, therefore, we introduce the reader also to the world of high-performance computing. The paper is concluded with a few examples where the presented method has been applied.
NASA Astrophysics Data System (ADS)
Doll, J. D.; Plattner, Nuria; Freeman, David L.; Liu, Yufei; Dupuis, Paul
2012-11-01
In the present paper we identify a rigorous property of a number of tempering-based Monte Carlo sampling methods, including parallel tempering as well as partial and infinite swapping. Based on this property we develop a variety of performance measures for such rare-event sampling methods that are broadly applicable, informative, and straightforward to implement. We illustrate the use of these performance measures with a series of applications involving the equilibrium properties of simple Lennard-Jones clusters, applications for which the performance levels of partial and infinite swapping approaches are found to be higher than those of conventional parallel tempering.
Wade, A. C. J.; Baillie, D.; Blakie, P. B.
2011-08-15
In this paper, we develop a direct simulation Monte Carlo method for simulating highly nonequilibrium dynamics of nondegenerate ultracold gases. We show that our method can simulate the high-energy collision of two thermal clouds in the regime observed in experiments [Thomas et al. Phys. Rev. Lett. 93, 173201 (2004)], which requires the inclusion of beyond s-wave scattering. We also consider the long-time dynamics of this system, demonstrating that this would be a practical experimental scenario for testing the Boltzmann equation and studying rethermalization.
Investigation of Collimator Influential Parameter on SPECT Image Quality: a Monte Carlo Study
Banari Bahnamiri, Sh.
2015-01-01
Background Obtaining high quality images in Single Photon Emission Tomography (SPECT) device is the most important goal in nuclear medicine. Because if image quality is low, the possibility of making a mistake in diagnosing and treating the patient will rise. Studying effective factors in spatial resolution of imaging systems is thus deemed to be vital. One of the most important factors in SPECT imaging in nuclear medicine is the use of an appropriate collimator for a certain radiopharmaceutical feature in order to create the best image as it can be effective in the quantity of Full Width at Half Maximum (FWHM) which is the main parameter in spatial resolution. Method In this research, the simulation of the detector and collimator of SPECT imaging device, Model HD3 made by Philips Co. and the investigation of important factors on the collimator were carried out using MCNP-4c code. Results The results of the experimental measurments and simulation calculations revealed a relative difference of less than 5% leading to the confirmation of the accuracy of conducted simulation MCNP code calculation. Conclusion This is the first essential step in the design and modelling of new collimators used for creating high quality images in nuclear medicine. PMID:25973410
NASA Astrophysics Data System (ADS)
Jin, Shengye; Tamura, Masayuki
2013-10-01
Monte Carlo Ray Tracing (MCRT) method is a versatile application for simulating radiative transfer regime of the Solar - Atmosphere - Landscape system. Moreover, it can be used to compute the radiation distribution over a complex landscape configuration, as an example like a forest area. Due to its robustness to the complexity of the 3-D scene altering, MCRT method is also employed for simulating canopy radiative transfer regime as the validation source of other radiative transfer models. In MCRT modeling within vegetation, one basic step is the canopy scene set up. 3-D scanning application was used for representing canopy structure as accurately as possible, but it is time consuming. Botanical growth function can be used to model the single tree growth, but cannot be used to express the impaction among trees. L-System is also a functional controlled tree growth simulation model, but it costs large computing memory. Additionally, it only models the current tree patterns rather than tree growth during we simulate the radiative transfer regime. Therefore, it is much more constructive to use regular solid pattern like ellipsoidal, cone, cylinder etc. to indicate single canopy. Considering the allelopathy phenomenon in some open forest optical images, each tree in its own `domain' repels other trees. According to this assumption a stochastic circle packing algorithm is developed to generate the 3-D canopy scene in this study. The canopy coverage (%) and the tree amount (N) of the 3-D scene are declared at first, similar to the random open forest image. Accordingly, we randomly generate each canopy radius (rc). Then we set the circle central coordinate on XY-plane as well as to keep circles separate from each other by the circle packing algorithm. To model the individual tree, we employ the Ishikawa's tree growth regressive model to set the tree parameters including DBH (dt), tree height (H). However, the relationship between canopy height (Hc) and trunk height (Ht) is unclear to us. We assume the proportion between Hc and Ht as a random number in the interval from 2.0 to 3.0. De Wit's sphere leaf angle distribution function was used within the canopy for acceleration. Finally, we simulate the open forest albedo using MCRT method. The MCRT algorithm of this study is summarized as follows (1) Initialize the photon with a position (r0), source direction (?0) and intensity (I0), respectively. (2) Simulate the free path (s) of a photon under the condition of (r', ?, I') in the canopy. (3) Calculate the new position of the photon r=r +s?'. (4) Determine the new scattering direction (?)after collision at, r and then calculate the new intensity I = ?L(?L,?'-->?)I'.(5) Accumulate the intensity I of a photon escaping from the top boundary of the 3-D Scene, otherwise redo from step (2), until I is smaller than a threshold. (6) Repeat from step (1), for each photon. We testify the model on four different simulated open forests and the effectiveness of the model is demonstrated in details.
Safigholi, Habib; Faghihi, Reza; Jashni, Somaye Karimi; Meigooni, Ali S. [Faculty of Engineering, Science and Research Branch, Islamic Azad University, Fars, 73481-13111, Persepolis (Iran, Islamic Republic of); Department of Nuclear Engineering and Radiation Research Center, Shiraz University, 71936-16548, Shiraz (Iran, Islamic Republic of); Shiraz University of Medical Sciences, 71348-14336, Shiraz (Iran, Islamic Republic of); Department of Radiation therapy, Comprehensive Cancer Center of Nevada, 3730 South Eastern Avenue, Las Vegas, Nevada 89169 (United States)
2012-04-15
Purpose: The goal of this study is to determine a method for Monte Carlo (MC) characterization of the miniature electronic brachytherapy x-ray sources (MEBXS) and to set dosimetric parameters according to TG-43U1 formalism. TG-43U1 parameters were used to get optimal designs of MEBXS. Parameters that affect the dose distribution such as anode shapes, target thickness, target angles, and electron beam source characteristics were evaluated. Optimized MEBXS designs were obtained and used to determine radial dose functions and 2D anisotropy functions in the electron energy range of 25-80 keV. Methods: Tungsten anode material was considered in two different geometries, hemispherical and conical-hemisphere. These configurations were analyzed by the 4C MC code with several different optimization techniques. The first optimization compared target thickness layers versus electron energy. These optimized thicknesses were compared with published results by Ihsan et al.[Nucl. Instrum. Methods Phys. Res. B 264, 371-377 (2007)]. The second optimization evaluated electron source characteristics by changing the cathode shapes and electron energies. Electron sources studied included; (1) point sources, (2) uniform cylinders, and (3) nonuniform cylindrical shell geometries. The third optimization was used to assess the apex angle of the conical-hemisphere target. The goal of these optimizations was to produce 2D-dose anisotropy functions closer to unity. An overall optimized MEBXS was developed from this analysis. The results obtained from this model were compared to known characteristics of HDR {sup 125}I, LDR {sup 103}Pd, and Xoft Axxent electronic brachytherapy source (XAEBS) [Med. Phys. 33, 4020-4032 (2006)]. Results: The optimized anode thicknesses as a function of electron energy is fitted by the linear equation Y ({mu}m) = 0.0459X (keV)-0.7342. The optimized electron source geometry is obtained for a disk-shaped parallel beam (uniform cylinder) with 0.9 mm radius. The TG-43 distribution is less sensitive to the shape of the conical-hemisphere anode than the hemispherical anode. However, the optimized apex angle of conical-hemisphere anode was determined to be 60 deg. For the hemispherical targets, calculated radial dose function values at a distance of 5 cm were 0.137, 0.191, 0.247, and 0.331 for 40, 50, 60, and 80 keV electrons, respectively. These values for the conical-hemisphere targets are 0.165, 0.239, 0.305, and 0.412, respectively. Calculated 2D anisotropy functions values for the hemispherical target shape were F(1 cm, 0 deg.) = 1.438 and F(1 cm, 0 deg.) = 1.465 for 30 and 80 keV electrons, respectively. The corresponding values for conical-hemisphere targets are 1.091 and 1.241, respectively. Conclusions: A method for the characterizations of MEBXS using TG-43U1 dosimetric data using the MC MCNP4C has been presented. The effects of target geometry, thicknesses, and electron source geometry have been investigated. The final choices of MEBXS design are conical-hemisphere target shapes having an apex angle of 60 deg. Tungsten material having an optimized thickness versus electron energy and a 0.9 mm radius of uniform cylinder as a cathode produces optimal electron source characteristics.
Stochastic method for accommodation of equilibrating basins in kinetic Monte Carlo simulations.
Siclen, Clinton Dew Van
2007-02-21
A computationally simple way to accommodate 'basins' of trapping states in standard kinetic Monte Carlo simulations is presented. By assuming that the system is effectively equilibrated in the basin, the residence time (time spent in the basin before escape) and the probabilities for transitions to states outside the basin may be calculated. This is demonstrated for point defect diffusion over a periodic grid of sites containing a complex basin. PMID:22251579
Stochastic method for accommodation of equilibrating basins in kinetic Monte Carlo simulations
Van Siclen, Clinton D
2007-02-01
A computationally simple way to accommodate "basins" of trapping states in standard kinetic Monte Carlo simulations is presented. By assuming the system is effectively equilibrated in the basin, the residence time (time spent in the basin before escape) and the probabilities for transition to states outside the basin may be calculated. This is demonstrated for point defect diffusion over a periodic grid of sites containing a complex basin.
NASA Astrophysics Data System (ADS)
Wu, Di M.; Zhao, S. S.; Lu, Jun Q.; Hu, Xin-Hua
2000-06-01
In Monte Carlo simulations of light propagating in biological tissues, photons propagating in the media are described as classic particles being scattered and absorbed randomly in the media, and their path are tracked individually. To obtain any statistically significant results, however, a large number of photons is needed in the simulations and the calculations are time consuming and sometime impossible with existing computing resource, especially when considering the inhomogeneous boundary conditions. To overcome this difficulty, we have implemented a parallel computing technique into our Monte Carlo simulations. And this moment is well justified due to the nature of the Monte Carlo simulation. Utilizing the PVM (Parallel Virtual Machine, a parallel computing software package), parallel codes in both C and Fortran have been developed on the massive parallel computer of Cray T3E and a local PC-network running Unix/Sun Solaris. Our results show that parallel computing can significantly reduce the running time and make efficient usage of low cost personal computers. In this report, we present a numerical study of light propagation in a slab phantom of skin tissue using the parallel computing technique.
Smith, William R; Lísal, Martin
2002-07-01
A Monte Carlo computer simulation method is presented for directly performing property predictions for fluid systems at fixed total internal energy, U, or enthalpy, H, using a molecular-level system model. The method is applicable to both nonreacting and reacting systems. Potential applications are to (1) adiabatic flash (Joule-Thomson expansion) calculations for nonreacting pure fluids and mixtures at fixed (H,P), where P is the pressure; and (2) adiabatic (flame-temperature) calculations at fixed (U,V) or (H,P), where V is the system volume. The details of the method are presented. The method is compared with existing related simulation methodologies for nonreacting systems, one of which addresses the problem involving fixing portions of U or of H, and one of which solves the problem at fixed H considered here by means of an indirect approach. We illustrate the method by an adiabatic calculation involving the ammonia synthesis reaction. PMID:12241338
Davis, Mitchell A; Dunn, Andrew K
2015-06-29
Few methods exist that can accurately handle dynamic light scattering in the regime between single and highly multiple scattering. We demonstrate dynamic light scattering Monte Carlo (DLS-MC), a numerical method by which the electric field autocorrelation function may be calculated for arbitrary geometries if the optical properties and particle motion are known or assumed. DLS-MC requires no assumptions regarding the number of scattering events, the final form of the autocorrelation function, or the degree of correlation between scattering events. Furthermore, the method is capable of rapidly determining the effect of particle motion changes on the autocorrelation function in heterogeneous samples. We experimentally validated the method and demonstrated that the simulations match both the expected form and the experimental results. We also demonstrate the perturbation capabilities of the method by calculating the autocorrelation function of flow in a representation of mouse microvasculature and determining the sensitivity to flow changes as a function of depth. PMID:26191723
NASA Astrophysics Data System (ADS)
Pereira, Pedro F.; Sherif, Sherif S.
2012-10-01
Numerical simulation of the interaction between light and tissue is important for the design and analysis of many optical imaging modalities. Most current simulations are based on the Transport Theory of light in a dielectric, and only calculate the intensity of light in a volume. These simulations do not provide phase information, which is important for many biomedical imaging systems. We are interested in obtaining the optical field, magnitude and phase, due to the interaction of light with tissue. Therefore, we need to solve the integral equation for scalar scattering in a volume of interest. Since the wavelength of light is in the order of nanometres, simulation of volumes of more than a few millimetres requires intensive computational resources. For large volumes, Monte Carlo methods are a suitable choice because their computational complexity is independent of the mathematical dimension of the problem. Also by a careful selection of the random sampling scheme the number of samples needed can be further reduced. In this paper we present an implementation of a method to solve Fredholm integral equations of the second kind using Reversible Jump Markov chain Monte Carlo (RJMCMC). This method could be used to simulate light in tissue with very large electrical size, meaning tissue whose physical dimensions are much larger than the wavelength of light, by solving the integral equation of scalar scattering over a large domain. We implemented this method based on RJMCMC and present in this paper the results of applying it to solve integral equations of one and two dimensions.
Clement, S D; Choi, J R; Zamenhof, R G; Yanch, J C; Harling, O K
1990-01-01
Monte Carlo methods of coupled neutron/photon transport are being used in the design of filtered beams for Neutron Capture Therapy (NCT). This method of beam analysis provides segregation of each individual dose component, and thereby facilitates beam optimization. The Monte Carlo method is discussed in some detail in relation to NCT epithermal beam design. Ideal neutron beams (i.e., plane-wave monoenergetic neutron beams with no primary gamma-ray contamination) have been modeled both for comparison and to establish target conditions for a practical NCT epithermal beam design. Detailed models of the 5 MWt Massachusetts Institute of Technology Research Reactor (MITR-II) together with a polyethylene head phantom have been used to characterize approximately 100 beam filter and moderator configurations. Using the Monte Carlo methodology of beam design and benchmarking/calibrating our computations with measurements, has resulted in an epithermal beam design which is useful for therapy of deep-seated brain tumors. This beam is predicted to be capable of delivering a dose of 2000 RBE-cGy (cJ/kg) to a therapeutic advantage depth of 5.7 cm in polyethylene assuming 30 micrograms/g 10B in tumor with a ten-to-one tumor-to-blood ratio, and a beam diameter of 18.4 cm. The advantage ratio (AR) is predicted to be 2.2 with a total irradiation time of approximately 80 minutes. Further optimization work on the MITR-II epithermal beams is expected to improve the available beams. PMID:2268248
Modeling of microscale gas flows using the direct simulation Monte Carlo method
NASA Astrophysics Data System (ADS)
Alexeenko, Alina A.
Microflows are defined as fluid flow phenomena associated with microscale mechanical devices. A great number of such devices have been manufactured over the last few decades using surface and bulk silicon micro-machining. Many of micro-electro-mechanical systems (MEMS) involve gaseous flows. Gas flows in MEMS with characteristic size on the order of microns differ from their larger counterparts. Three important flow parameters: Knudsen and Reynolds numbers and surface-to-volume ratio, are drastically different from those encountered in large scale flows. Accurate numerical modeling of microflows is indispensable for providing design capability for MEMS by predicting the flow field and performance characteristics. The main goal of the thesis research is the development, implementation and application of comprehensive direct simulation Monte Carlo approach to microscale gas flows. Flows in microthrusters and microchannels are commonly encountered in MEMS and are the focus of the study. The investigation of physical processes in three-dimensional micronozzles and the influence of Reynolds number, geometrical configuration and temperature regime have been carried out in the thesis. The impact of wall effects on thrust is examined for axisymmetric and two- and three-dimensional cold gas micronozzles. The flow in a flat micronozzle has a 3D structure and is strongly influenced by the end walls. The additional friction losses on the side walls cause a reduction in thrust of about 20% compared to the two-dimensional and axisymmetric nozzles. The work on coupled analysis of a microthruster is aimed at the developing a numerical simulation code capable of modeling the temporal variation of microthruster material temperature and performance characteristics. The application of the developed approach to two-dimensional and three-dimensional microthrusters gives several important insights into the dependence of performance characteristics on Reynolds number, thermal conditions and thruster geometry. The mass discharge of the microthruster have been found to decrease significantly in time due to increasing wall temperature. Such behavior of the mass discharge coefficient is obtained for both 2D and 3D models as well as for different stagnation pressures and geometrical shapes. Investigation of gas flows in microchannels with constriction have been carried out both analytically and numerically in order to understand the flow phenomena observed in experiments. An analytical model is developed to predict pressure drop and mass flow rate. The validation of the model is conducted by comparison with 2D DSMC calculations. The model accurately predicts the mass flow rate and pressure drop at the constriction section and compares well with the DSMC results. The DSMC simulations have shown that the flow separation may occur at the constriction. The presence of the separation zone does not influence the pressure distribution and the mass flow rate. The DSMC method have been applied for calibration of micro-Newton thrust stand and investigation of effects of the facility background. The DSMC calculations have been conducted for orifice flow for Kn = 0.01 to 40. It is found that for low Knudsen numbers the background gas contribution to the total force becomes significant. This is attributed to the jet shadowing effect, and, therefore, it must be included in modeling to permit a comparison with experiment.
NASA Astrophysics Data System (ADS)
Wang, Dong; Tse, Peter W.
2015-05-01
Slurry pumps are commonly used in oil-sand mining for pumping mixtures of abrasive liquids and solids. These operations cause constant wear of slurry pump impellers, which results in the breakdown of the slurry pumps. This paper develops a prognostic method for estimating remaining useful life of slurry pump impellers. First, a moving-average wear degradation index is proposed to assess the performance degradation of the slurry pump impeller. Secondly, the state space model of the proposed health index is constructed. A general sequential Monte Carlo method is employed to derive the parameters of the state space model. The remaining useful life of the slurry pump impeller is estimated by extrapolating the established state space model to a specified alert threshold. Data collected from an industrial oil sand pump were used to validate the developed method. The results show that the accuracy of the developed method improves as more data become available.
Martin, W.R.
1993-01-01
This document describes progress on five efforts for improving effectiveness of computational methods for particle diffusion and transport problems in nuclear engineering: (1) Multigrid methods for obtaining rapidly converging solutions of nodal diffusion problems. A alternative line relaxation scheme is being implemented into a nodal diffusion code. Simplified P2 has been implemented into this code. (2) Local Exponential Transform method for variance reduction in Monte Carlo neutron transport calculations. This work yielded predictions for both 1-D and 2-D x-y geometry better than conventional Monte Carlo with splitting and Russian Roulette. (3) Asymptotic Diffusion Synthetic Acceleration methods for obtaining accurate, rapidly converging solutions of multidimensional SN problems. New transport differencing schemes have been obtained that allow solution by the conjugate gradient method, and the convergence of this approach is rapid. (4) Quasidiffusion (QD) methods for obtaining accurate, rapidly converging solutions of multidimensional SN Problems on irregular spatial grids. A symmetrized QD method has been developed in a form that results in a system of two self-adjoint equations that are readily discretized and efficiently solved. (5) Response history method for speeding up the Monte Carlo calculation of electron transport problems. This method was implemented into the MCNP Monte Carlo code. In addition, we have developed and implemented a parallel time-dependent Monte Carlo code on two massively parallel processors.
Calculation of images from an anthropomorphic chest phantom using Monte Carlo methods
NASA Astrophysics Data System (ADS)
Ullman, Gustaf; Malusek, Alexandr; Sandborg, Michael; Dance, David R.; Alm Carlsson, Gudrun
2006-03-01
Monte Carlo (MC) computer simulation of chest x-ray imaging systems has hitherto been performed using anthropomorphic phantoms with too large (3 mm) voxel sizes. The aim for this work was to develop and use a Monte Carlo computer program to compute projection x-ray images of a high-resolution anthropomorphic voxel phantom for visual clinical image quality evaluation and dose-optimization. An Alderson anthropomorphic chest phantom was imaged in a CT-scanner and reconstructed with isotropic voxels of 0.7 mm. The phantom was segmented and included in a Monte Carlo computer program using the collision density estimator to derive the energies imparted to the detector per unit area of each pixel by scattered photons. The image due to primary photons was calculated analytically including a pre-calculated detector response function. Attenuation and scatter of x-rays in the phantom, grid and image detector was considered. Imaging conditions (tube voltage, anti-scatter device) were varied and the images compared to a real computed radiography (Fuji FCR 9501) image. Four imaging systems were simulated (two tube voltages 81 kV and 141 kV using either a grid with ratio 10 or a 30 cm air gap). The effect of scattered radiation on the visibility of thoracic vertebrae against the heart and lungs is demonstrated. The simplicity in changing the imaging conditions will allow us not only to produce images of existing imaging systems, but also of hypothetical, future imaging systems. We conclude that the calculated images of the high-resolution voxel phantom are suitable for human detection experiments of low-contrast lesions.
Nuclear Level Density of ${}^{161}$Dy in the Shell Model Monte Carlo Method
Cem Özen; Yoram Alhassid; Hitoshi Nakada
2012-06-27
We extend the shell-model Monte Carlo applications to the rare-earth region to include the odd-even nucleus ${}^{161}$Dy. The projection on an odd number of particles leads to a sign problem at low temperatures making it impractical to extract the ground-state energy in direct calculations. We use level counting data at low energies and neutron resonance data to extract the shell model ground-state energy to good precision. We then calculate the level density of ${}^{161}$Dy and find it in very good agreement with the level density extracted from experimental data.
Prediction of rocket plume radiative heating using backward Monte-Carlo method
NASA Technical Reports Server (NTRS)
Wang, K. C.
1993-01-01
A backward Monte-Carlo plume radiation code has been developed to predict rocket plume radiative heating to the rocket base region. This paper provides a description of this code and provides sample results. The code was used to predict radiative heating to various locations during test firings of 48-inch solid rocket motors at NASA Marshall Space Flight Center. Comparisons with test measurements are provided. Predictions of full scale sea level Redesigned Solid Rocket Motor (RSRM) and Advanced Solid Rocket Motor (ASRM) plume radiative heating to the Space Shuttle external tank (ET) dome center were also made. A comparison with the Development Flight Instrumentation (DFI) measurements is also provided.
Wagner, John C; Peplow, Douglas E.; Mosher, Scott W; Evans, Thomas M
2010-01-01
This paper provides a review of the hybrid (Monte Carlo/deterministic) radiation transport methods and codes used at the Oak Ridge National Laboratory and examples of their application for increasing the efficiency of real-world, fixed-source Monte Carlo analyses. The two principal hybrid methods are (1) Consistent Adjoint Driven Importance Sampling (CADIS) for optimization of a localized detector (tally) region (e.g., flux, dose, or reaction rate at a particular location) and (2) Forward Weighted CADIS (FW-CADIS) for optimizing distributions (e.g., mesh tallies over all or part of the problem space) or multiple localized detector regions (e.g., simultaneous optimization of two or more localized tally regions). The two methods have been implemented and automated in both the MAVRIC sequence of SCALE 6 and ADVANTG, a code that works with the MCNP code. As implemented, the methods utilize the results of approximate, fast-running 3-D discrete ordinates transport calculations (with the Denovo code) to generate consistent space- and energy-dependent source and transport (weight windows) biasing parameters. These methods and codes have been applied to many relevant and challenging problems, including calculations of PWR ex-core thermal detector response, dose rates throughout an entire PWR facility, site boundary dose from arrays of commercial spent fuel storage casks, radiation fields for criticality accident alarm system placement, and detector response for special nuclear material detection scenarios and nuclear well-logging tools. Substantial computational speed-ups, generally O(10{sup 2-4}), have been realized for all applications to date. This paper provides a brief review of the methods, their implementation, results of their application, and current development activities, as well as a considerable list of references for readers seeking more information about the methods and/or their applications.
A new method to calculate the response of the WENDI-II rem counter using the FLUKA Monte Carlo Code
NASA Astrophysics Data System (ADS)
Jägerhofer, Lukas; Feldbaumer, Eduard; Theis, Christian; Roesler, Stefan; Vincke, Helmut
2012-11-01
The FHT-762 WENDI-II is a commercially available wide range neutron rem counter which uses a 3He counter tube inside a polyethylene moderator. To increase the response above 10 MeV of kinetic neutron energy, a layer of tungsten powder is implemented into the moderator shell. For the purpose of the characterization of the response, a detailed model of the detector was developed and implemented for FLUKA Monte Carlo simulations. In common practice Monte Carlo simulations are used to calculate the neutron fluence inside the active volume of the detector. The resulting fluence is then folded offline with the reaction rate of the 3He(n,p)3H reaction to yield the proton-triton production rate. Consequently this approach does not consider geometrical effects like wall effects, where one or both reaction products leave the active volume of the detector without triggering a count. This work introduces a two-step simulation method which can be used to determine the detector's response, including geometrical effects, directly, using Monte Carlo simulations. A "first step" simulation identifies the 3He(n,p)3H reaction inside the active volume of the 3He counter tube and records its position. In the "second step" simulation the tritons and protons are started in accordance with the kinematics of the 3He(n,p)3H reaction from the previously recorded positions and a correction factor for geometrical effects is determined. The three dimensional Monte Carlo model of the detector as well as the two-step simulation method were evaluated and tested in the well-defined fields of an 241Am-Be(?,n) source as well as in the field of a 252Cf source. Results were compared with measurements performed by Gutermuth et al. [1] at GSI with an 241Am-Be(?,n) source as well as with measurements performed by the manufacturer in the field of a 252Cf source. Both simulation results show very good agreement with the respective measurements. After validating the method, the response values in terms of counts per unit fluence were calculated for 95 different incident neutron energies between 1 meV and 5 GeV.
Response of thermoluminescent dosimeters to photons simulated with the Monte Carlo method
NASA Astrophysics Data System (ADS)
Moralles, M.; Guimarães, C. C.; Okuno, E.
2005-06-01
Personal monitors composed of thermoluminescent dosimeters (TLDs) made of natural fluorite (CaF 2:NaCl) and lithium fluoride (Harshaw TLD-100) were exposed to gamma and X rays of different qualities. The GEANT4 radiation transport Monte Carlo toolkit was employed to calculate the energy depth deposition profile in the TLDs. X-ray spectra of the ISO/4037-1 narrow-spectrum series, with peak voltage (kVp) values in the range 20-300 kV, were obtained by simulating a X-ray Philips MG-450 tube associated with the recommended filters. A realistic photon distribution of a 60Co radiotherapy source was taken from results of Monte Carlo simulations found in the literature. Comparison between simulated and experimental results revealed that the attenuation of emitted light in the readout process of the fluorite dosimeter must be taken into account, while this effect is negligible for lithium fluoride. Differences between results obtained by heating the dosimeter from the irradiated side and from the opposite side allowed the determination of the light attenuation coefficient for CaF 2:NaCl (mass proportion 60:40) as 2.2 mm -1.
Comparative Dosimetric Estimates of a 25 keV Electron Micro-beam with three Monte Carlo Codes
Mainardi, Enrico; Donahue, Richard J.; Blakely, Eleanor A.
2002-09-11
The calculations presented compare the different performances of the three Monte Carlo codes PENELOPE-1999, MCNP-4C and PITS, for the evaluation of Dose profiles from a 25 keV electron micro-beam traversing individual cells. The overall model of a cell is a water cylinder equivalent for the three codes but with a different internal scoring geometry: hollow cylinders for PENELOPE and MCNP, whereas spheres are used for the PITS code. A cylindrical cell geometry with scoring volumes with the shape of hollow cylinders was initially selected for PENELOPE and MCNP because of its superior simulation of the actual shape and dimensions of a cell and for its improved computer-time efficiency if compared to spherical internal volumes. Some of the transfer points and energy transfer that constitute a radiation track may actually fall in the space between spheres, that would be outside the spherical scoring volume. This internal geometry, along with the PENELOPE algorithm, drastically reduced the computer time when using this code if comparing with event-by-event Monte Carlo codes like PITS. This preliminary work has been important to address dosimetric estimates at low electron energies. It demonstrates that codes like PENELOPE can be used for Dose evaluation, even with such small geometries and energies involved, which are far below the normal use for which the code was created. Further work (initiated in Summer 2002) is still needed however, to create a user-code for PENELOPE that allows uniform comparison of exact cell geometries, integral volumes and also microdosimetric scoring quantities, a field where track-structure codes like PITS, written for this purpose, are believed to be superior.
NASA Astrophysics Data System (ADS)
Shahrabi, Mohammad; Tavakoli-Anbaran, Hossien
2015-02-01
Calculation of dosimetry parameters by TG-60 approach for beta sources and TG-43 approach for gamma sources can help to design brachytherapy sources. In this work, TG-60 dosimetry parameters are calculated for the Sm-153 brachytherapy seed using the Monte Carlo simulation approach. The continuous beta spectrum of Sm-153 and probability density are applied to simulate the Sm-153 source. Sm-153 is produced by neutron capture during the 152Sm( n,)153Sm reaction in reactors. The Sm-153 radionuclide decays by beta rays followed by gamma-ray emissions with half-life of 1.928 days. Sm-153 source is simulated in a spherical water phantom to calculate the deposited energy and geometry function in the intended points. The Sm-153 seed consists of 20% samarium, 30% calcium and 50% silicon, in cylindrical shape with density 1.76gr/cm^3. The anisotropy function and radial dose function were calculated at 0-4mm radial distances relative to the seed center and polar angles of 0-90 degrees. The results of this research are compared with the results of Taghdiri et al. (Iran. J. Radiat. Res. 9, 103 (2011)). The final beta spectrum of Sm-153 is not considered in their work. Results show significant relative differences even up to 5 times for anisotropy functions at 0.6, 1 and 2mm distances and some angles. MCNP4C Monte Carlo code is applied in both in the present paper and in the above-mentioned one.
Remarkable Moments in the History of Neutron Transport Monte Carlo Methods
NASA Astrophysics Data System (ADS)
Lux, I.
Ladies and Gentlemen, Dear Colleagues, It is my utmost pleasure to talk to the acknowledged audience of this outstanding conference. Forgive me if I begin my talk with something personal. Quite a time ago, when I have made my first steps in the wonderland of Monte Carlo I have often dreamed about visiting the two capitals of this art: Novosibirsk in Russia and Los Alamos in the USA. I had the opportunity to see quite a few places in the World but somehow neither of these two. Now we all have gathered in Lisbon and you brought here in your head and in your papers all what is worth of knowing in this field of science, while strange enough, Lisbon is almost exactly in the midpoint between Novosibirsk and Los Alamos1. I would like to call to your attention the symbolic meaning of this.
Comparing methods and Monte Carlo algorithms at phase transition regimes: A general overview
NASA Astrophysics Data System (ADS)
Fiore, Carlos E.
2014-03-01
Although numerical simulations constitute one of the most important tools in statistical mechanics, in practice the things are not so simple. Standard commonly used algorithms lead to well known difficulties at phase transition regimes, hence avoiding the achievement of precise thermodynamic quantities. In the last years, several approaches have been proposed in order to circumvent such difficulties. With these concepts in mind, here we present a comparison among distinct Monte Carlo algorithms, analyzing their efficiency and reliability. We show that their difficulties are substantially reduced when proper approaches for phase transitions are used. We illustrate the main concepts and ideas in the Blume-Emery-Griffiths (BEG) model, that displays strong first-order transitions in and second-order transitions low and high temperatures, respectively.
A method to perform multi-scale Monte Carlo simulations in the clinical setting.
Lucido, Joseph John; Popescu, I Antoniu; Moiseenko, Vitali
2015-09-01
In order to model the track structure of clinical mega-voltage photon beams in a reasonable time, it is necessary to use a multi-scale approach incorporating a track-structure algorithm for the regions of interest and a condensed history algorithm for the rest of the geometry. This paper introduces a multi-scale Monte Carlo system, which is used to hand off particle trajectory information between the two algorithms. Since condensed history algorithms ignore electrons with energy below a fixed threshold and those electrons are important to the track structure on the micrometre scale, it is necessary to hand over all charged particles to the track-structure algorithm only in a volume that extends beyond the scoring volume. Additionally, the system is validated against experimental results for radio-isotope gamma spectra. PMID:26242976
Stoller, Roger E [ORNL; Golubov, Stanislav I [ORNL; Becquart, C. S. [Universite de Lille; Domain, C. [EDF R& D, Clamart, France
2007-08-01
The multiscale modeling scheme encompasses models from the atomistic to the continuum scale. Phenomena at the mesoscale are typically simulated using reaction rate theory, Monte Carlo, or phase field models. These mesoscale models are appropriate for application to problems that involve intermediate length scales, and timescales from those characteristic of diffusion to long-term microstructural evolution (~?s to years). Although the rate theory and Monte Carlo models can be used simulate the same phenomena, some of the details are handled quite differently in the two approaches. Models employing the rate theory have been extensively used to describe radiation-induced phenomena such as void swelling and irradiation creep. The primary approximations in such models are time- and spatial averaging of the radiation damage source term, and spatial averaging of the microstructure into an effective medium. Kinetic Monte Carlo models can account for these spatial and temporal correlations; their primary limitation is the computational burden which is related to the size of the simulation cell. A direct comparison of RT and object kinetic MC simulations has been made in the domain of point defect cluster dynamics modeling, which is relevant to the evolution (both nucleation and growth) of radiation-induced defect structures. The primary limitations of the OKMC model are related to computational issues. Even with modern computers, the maximum simulation cell size and the maximum dose (typically much less than 1 dpa) that can be simulated are limited. In contrast, even very detailed RT models can simulate microstructural evolution for doses up 100 dpa or greater in clock times that are relatively short. Within the context of the effective medium, essentially any defect density can be simulated. Overall, the agreement between the two methods is best for irradiation conditions which produce a high density of defects (lower temperature and higher displacement rate), and for materials that have a relatively high density of fixed sinks such as dislocations.
A fast 3D image reconstruction method based on Monte-Carlo simulation for laminar optical tomography
NASA Astrophysics Data System (ADS)
Jia, Mengyu; Cui, Shanshan; Chen, Xueying; Zhao, Huijuan; Gao, Feng
2014-09-01
Laminar optical tomography (LOT) is a new mesoscopic functional optical imaging technique. Currently, the forward problem of LOT image reconstruction is generally solved on the basis of Monte-Carlo (MC) methods. However, considering the nonlinear nature of the image reconstruction in LOT, with the increasing number of source positions, methods based on MC takes too much computation time. Based on the scheme of trajectory translation and target voxel regression (TT&TVR) proposed by our group, this paper develops a fast 3D image reconstruction algorithm. The algorithm is applied to the absorption reconstruction of the layered inhomogeneous media. Results demonstrate that the reconstructing time is less than 15min with the X-Y-Z section of the sample subdivided into 50 × 50 × 10 voxels, and the target size and quantitativeness ratio can be obtained in a satisfying accuracy.
NASA Astrophysics Data System (ADS)
Cerjanic, Alexander M.
The development of a spectral domain method of moments code for the modeling of single layer microstrip patch antennas is presented in this thesis. The mixed potential integral equation formulation of Maxwell's equations is used as the theoretical basis for the work, and is solved via the method of moments. General-purpose graphics processing units are used for the computation of the impedance matrix by incorporation of quasi-Monte Carlo integration. The development of the various components of the code, including Green's function, impedance matrix, and excitation vector modules are discussed with individual test cases for the major code modules. The integrated code was tested by modeling a suite of four coaxially probe fed circularly polarized single layer microstrip patch antennas and the computed results are compared to those obtained by measurement. Finally, a study examining the relationship between design parameters and S11 performance was undertaken using the code.
New One-Flavor Hybrid Monte Carlo Simulation Method for Lattice Fermions with gamma-five Hermiticity
Kenji Ogawa
2011-04-12
We propose a new method for Hybrid Monte Carlo (HMC) simulations with odd numbers of dynamical fermions on the lattice. It employs a different approach from polynomial or rational HMC. In this method, gamma-five hermiticity of the lattice Dirac operators is crucial and it can be applied to Wilson, domain-wall, and overlap fermions. We compare HMC simulations with two degenerate flavors and (1 + 1) degenerate flavors using optimal domain-wall fermions. The ratio of the efficiency, (number of accepted trajectories) / (simulation time), is about 3:2. The relation between pseudofermion action of chirally symmetric lattice fermions in four-dimensional(overlap) and five-dimensional(domain-wall) representation are also analyzed.
Dupuis, Paul [Brown University] [Brown University
2014-03-14
This proposal is concerned with applications of Monte Carlo to problems in physics and chemistry where rare events degrade the performance of standard Monte Carlo. One class of problems is concerned with computation of various aspects of the equilibrium behavior of some Markov process via time averages. The problem to be overcome is that rare events interfere with the efficient sampling of all relevant parts of phase space. A second class concerns sampling transitions between two or more stable attractors. Here, rare events do not interfere with the sampling of all relevant parts of phase space, but make Monte Carlo inefficient because of the very large number of samples required to obtain variance comparable to the quantity estimated. The project uses large deviation methods for the mathematical analyses of various Monte Carlo techniques, and in particular for algorithmic analysis and design. This is done in the context of relevant application areas, mainly from chemistry and biology.
Dieudonne, C.; Dumonteil, E.; Malvagi, F.; Diop, C. M.
2013-07-01
For several years, Monte Carlo burnup/depletion codes have appeared, which couple a Monte Carlo code to simulate the neutron transport to a deterministic method that computes the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3 dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the time-expensive Monte Carlo solver called at each time step. Therefore, great improvements in term of calculation time could be expected if one could get rid of Monte Carlo transport sequences. For example, it may seem interesting to run an initial Monte Carlo simulation only once, for the first time/burnup step, and then to use the concentration perturbation capability of the Monte Carlo code to replace the other time/burnup steps (the different burnup steps are seen like perturbations of the concentrations of the initial burnup step). This paper presents some advantages and limitations of this technique and preliminary results in terms of speed up and figure of merit. Finally, we will detail different possible calculation scheme based on that method. (authors)
Bashkatov, A N; Genina, Elina A; Kochubei, V I; Tuchin, Valerii V [Department of Optics and Biomedical Physics, N.G.Chernyshevskii Saratov State University (Russian Federation)
2006-12-31
Based on the digital image analysis and inverse Monte-Carlo method, the proximate analysis method is deve-loped and the optical properties of hairs of different types are estimated in three spectral ranges corresponding to three colour components. The scattering and absorption properties of hairs are separated for the first time by using the inverse Monte-Carlo method. The content of different types of melanin in hairs is estimated from the absorption coefficient. It is shown that the dominating type of melanin in dark hairs is eumelanin, whereas in light hairs pheomelanin dominates. (special issue devoted to multiple radiation scattering in random media)
Debabrata Deb; Alexander Winkler; Mohammad Hossein Yamani; Martin Oettel; Peter Virnau; Kurt Binder
2011-04-29
Hard-sphere fluids confined between parallel plates a distance $D$ apart are studied for a wide range of packing fractions, including also the onset of crystallization, applying Monte Carlo simulation techniques and density functional theory. The walls repel the hard spheres (of diameter $\\sigma$) with a Weeks-Chandler-Andersen (WCA) potential $V_{WCA}(z) = 4 \\epsilon [(\\sigma_w/z)^{12}-(\\sigma_w/z)^6 + 1/4]$, with range $\\sigma_w = \\sigma/2$. We vary the strength $\\epsilon$ over a wide range and the case of simple hard walls is also treated for comparison. By the variation of $\\epsilon$ one can change both the surface excess packing fraction and the wall-fluid $(\\gamma_{wf})$ and wall-crystal $(\\gamma_{wc})$ surface free energies. Several different methods to extract $\\gamma_{wf}$ and $\\gamma_{wc}$ from Monte Carlo (MC) simulations are implemented, and their accuracy and efficiency is comparatively discussed. The density functional theory (DFT) using Fundamental Measure functionals is found to be quantitatively accurate over a wide range of packing fractions; small deviations between DFT and MC near the fluid to crystal transition need to be studied further. Our results on density profiles near soft walls could be useful to interpret corresponding experiments with suitable colloidal dispersions.
NASA Astrophysics Data System (ADS)
Srinivasan, P.; Priya, S.; Patel, Tarun; Gopalakrishnan, R. K.; Sharma, D. N.
2015-01-01
DD/DT fusion neutron generators are used as sources of 2.5 MeV/14.1 MeV neutrons in experimental laboratories for various applications. Detailed knowledge of the radiation dose rates around the neutron generators are essential for ensuring radiological protection of the personnel involved with the operation. This work describes the experimental and Monte Carlo studies carried out in the Purnima Neutron Generator facility of the Bhabha Atomic Research Center (BARC), Mumbai. Verification and validation of the shielding adequacy was carried out by measuring the neutron and gamma dose-rates at various locations inside and outside the neutron generator hall during different operational conditions both for 2.5-MeV and 14.1-MeV neutrons and comparing with theoretical simulations. The calculated and experimental dose rates were found to agree with a maximum deviation of 20% at certain locations. This study has served in benchmarking the Monte Carlo simulation methods adopted for shield design of such facilities. This has also helped in augmenting the existing shield thickness to reduce the neutron and associated gamma dose rates for radiological protection of personnel during operation of the generators at higher source neutron yields up to 1 × 1010 n/s.
Wang, Wenlong; Machta, Jonathan; Katzgraber, Helmut G
2015-07-01
Population annealing is a Monte Carlo algorithm that marries features from simulated-annealing and parallel-tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a Hamiltonian. Thus, population-annealing Monte Carlo can be used as a heuristic to solve combinatorial optimization problems. We illustrate the capabilities of population-annealing Monte Carlo by computing ground states of the three-dimensional Ising spin glass with Gaussian disorder, while comparing to simulated-annealing and parallel-tempering Monte Carlo. Our results suggest that population annealing Monte Carlo is significantly more efficient than simulated annealing but comparable to parallel-tempering Monte Carlo for finding spin-glass ground states. PMID:26274303
NASA Astrophysics Data System (ADS)
Wang, Wenlong; Machta, Jonathan; Katzgraber, Helmut G.
2015-07-01
Population annealing is a Monte Carlo algorithm that marries features from simulated-annealing and parallel-tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a Hamiltonian. Thus, population-annealing Monte Carlo can be used as a heuristic to solve combinatorial optimization problems. We illustrate the capabilities of population-annealing Monte Carlo by computing ground states of the three-dimensional Ising spin glass with Gaussian disorder, while comparing to simulated-annealing and parallel-tempering Monte Carlo. Our results suggest that population annealing Monte Carlo is significantly more efficient than simulated annealing but comparable to parallel-tempering Monte Carlo for finding spin-glass ground states.
NASA Technical Reports Server (NTRS)
Tsang, L.; Lou, S. H.; Chan, C. H.
1991-01-01
The extended boundary condition method is applied to Monte Carlo simulations of two-dimensional random rough surface scattering. The numerical results are compared with one-dimensional random rough surfaces obtained from the finite-element method. It is found that the mean scattered intensity from two-dimensional rough surfaces differs from that of one dimension for rough surfaces with large slopes.
Specific absorbed fractions of electrons and photons for Rad-HUMAN phantom using Monte Carlo method
NASA Astrophysics Data System (ADS)
Wang, Wen; Cheng, Meng-Yun; Long, Peng-Cheng; Hu, Li-Qin
2015-07-01
The specific absorbed fractions (SAF) for self- and cross-irradiation are effective tools for the internal dose estimation of inhalation and ingestion intakes of radionuclides. A set of SAFs of photons and electrons were calculated using the Rad-HUMAN phantom, which is a computational voxel phantom of a Chinese adult female that was created using the color photographic image of the Chinese Visible Human (CVH) data set by the FDS Team. The model can represent most Chinese adult female anatomical characteristics and can be taken as an individual phantom to investigate the difference of internal dose with Caucasians. In this study, the emission of mono-energetic photons and electrons of 10 keV to 4 MeV energy were calculated using the Monte Carlo particle transport calculation code MCNP. Results were compared with the values from ICRP reference and ORNL models. The results showed that SAF from the Rad-HUMAN have similar trends but are larger than those from the other two models. The differences were due to the racial and anatomical differences in organ mass and inter-organ distance. The SAFs based on the Rad-HUMAN phantom provide an accurate and reliable data for internal radiation dose calculations for Chinese females. Supported by Strategic Priority Research Program of Chinese Academy of Sciences (XDA03040000), National Natural Science Foundation of China (910266004, 11305205, 11305203) and National Special Program for ITER (2014GB112001)
Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange.
Hula, Andreas; Montague, P Read; Dayan, Peter
2015-06-01
Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agent's preference for equity with their partner, beliefs about the partner's appetite for equity, beliefs about the partner's model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP). However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference. PMID:26053429
Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange
Hula, Andreas; Montague, P. Read; Dayan, Peter
2015-01-01
Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agent’s preference for equity with their partner, beliefs about the partner’s appetite for equity, beliefs about the partner’s model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP). However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference. PMID:26053429
DSMC calculations for the delta wing. [Direct Simulation Monte Carlo method
NASA Technical Reports Server (NTRS)
Celenligil, M. Cevdet; Moss, James N.
1990-01-01
Results are reported from three-dimensional direct simulation Monte Carlo (DSMC) computations, using a variable-hard-sphere molecular model, of hypersonic flow on a delta wing. The body-fitted grid is made up of deformed hexahedral cells divided into six tetrahedral subcells with well defined triangular faces; the simulation is carried out for 9000 time steps using 150,000 molecules. The uniform freestream conditions include M = 20.2, T = 13.32 K, rho = 0.00001729 kg/cu m, and T(wall) = 620 K, corresponding to lambda = 0.00153 m and Re = 14,000. The results are presented in graphs and briefly discussed. It is found that, as the flow expands supersonically around the leading edge, an attached leeside flow develops around the wing, and the near-surface density distribution has a maximum downstream from the stagnation point. Coefficients calculated include C(H) = 0.067, C(DP) = 0.178, C(DF) = 0.110, C(L) = 0.714, and C(D) = 1.089. The calculations required 56 h of CPU time on the NASA Langley Voyager CRAY-2 supercomputer.
NASA Technical Reports Server (NTRS)
Jensen, K. A.; Ripoll, J.-F.; Wray, A. A.; Joseph, D.; ElHafi, M.
2004-01-01
Five computational methods for solution of the radiative transfer equation in an absorbing-emitting and non-scattering gray medium were compared on a 2 m JP-8 pool fire. The temperature and absorption coefficient fields were taken from a synthetic fire due to the lack of a complete set of experimental data for fires of this size. These quantities were generated by a code that has been shown to agree well with the limited quantity of relevant data in the literature. Reference solutions to the governing equation were determined using the Monte Carlo method and a ray tracing scheme with high angular resolution. Solutions using the discrete transfer method, the discrete ordinate method (DOM) with both S(sub 4) and LC(sub 11) quadratures, and moment model using the M(sub 1) closure were compared to the reference solutions in both isotropic and anisotropic regions of the computational domain. DOM LC(sub 11) is shown to be the more accurate than the commonly used S(sub 4) quadrature technique, especially in anisotropic regions of the fire domain. This represents the first study where the M(sub 1) method was applied to a combustion problem occurring in a complex three-dimensional geometry. The M(sub 1) results agree well with other solution techniques, which is encouraging for future applications to similar problems since it is computationally the least expensive solution technique. Moreover, M(sub 1) results are comparable to DOM S(sub 4).
Simulation of Mach-Effect Illusion Using Three-Layered Retinal Cell Model and Monte Carlo Method
NASA Astrophysics Data System (ADS)
Ueno, Akinori; Arai, Ken; Miyashita, Osamu
We proposed a novel retinal model capable of simulating Mach-effect, which is known as an optical illusion emphasizing edges of an object. The model was constructed by a rod cell layer, a bipolar cell layer, and a ganglion cell layer. Lateral inhibition and perceptive field networks were introduced between the layers, respectively. Photoelectric conversion for a single photon incidence at each rod cell was defined as an equation, and the input to the model was simulated as a distribution of transmitted photons through the input image for consecutive incidences by Monte Carlo method. Since this model successfully simulated not only Mach-effect illusion, but also DOG-like (Difference of Gaussian like) profile for a spot light incidence, the model was considered to form functionally the perceptive field of the retinal ganglion cell.
Ohgoe, Takahiro; Kawashima, Naoki [Institute for Solid State Physics, University of Tokyo, 5-1-5 Kashiwa-no-ha, Kashiwa, Chiba 277-8581 (Japan)
2011-02-15
We study the supercounterfluid (SCF) states in the two-component hard-core Bose-Hubbard model on a square lattice, using the quantum Monte Carlo method based on the worm (directed-loop) algorithm. Since the SCF state is a state of a pair condensation characterized by {ne}0,=0, and =0, where a and b are the order parameters of the two components, it is important to study behaviors of the pair-correlation function . For this purpose, we propose a choice of the worm head for calculating the pair-correlation function. From this pair correlation, we confirm the Kosterlitz-Thouless character of the SCF phase. The simulation efficiency is also improved in the SCF phase.
Quantum Monte Carlo method for pairing phenomena: Supercounterfluid of two-species Bose gases in optical lattices
NASA Astrophysics Data System (ADS)
Ohgoe, Takahiro; Kawashima, Naoki
2011-02-01
We study the supercounterfluid (SCF) states in the two-component hard-core Bose-Hubbard model on a square lattice, using the quantum Monte Carlo method based on the worm (directed-loop) algorithm. Since the SCF state is a state of a pair condensation characterized by ?0,=0, and =0, where a and b are the order parameters of the two components, it is important to study behaviors of the pair-correlation function
Monte Carlo and least-squares methods applied in unfolding of X-ray spectra measured with cadmium telluride detectors
NASA Astrophysics Data System (ADS)
Moralles, M.; Bonifácio, D. A. B.; Bottaro, M.; Pereira, M. A. G.
2007-09-01
Spectra of calibration sources and X-ray beams were measured with a cadmium telluride (CdTe) detector. The response function of the detector was simulated using the GEANT4 Monte Carlo toolkit. Trapping of charge carriers were taken into account using the Hecht equation in the active zone of the CdTe crystal associated with a continuous function to produce drop of charge collection efficiency near the metallic contacts and borders. The rise time discrimination is approximated by a cut in the depth of the interaction relative to cathode and corrections that depend on the pulse amplitude. The least-squares method with truncation was employed to unfold X-ray spectra typically used in medical diagnostics and the results were compared with reference data.
Nasser, Hassan; Cessac, Bruno
2012-01-01
Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In a first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have been focusing on modelling synchronous spike patterns, leaving aside the temporal dynamics of the neural activity. However, the maximum entropy principle can be generalized to the temporal case, leading to Markovian models where memory effects and time correlations in the dynamics are properly taken into account. In a second part, we present a new method based on Monte-Carlo sampling which is suited for the fitting of large-scale spatio-temporal MaxEnt models. The formalism and the tools presented here will be essential to fit MaxEnt spatio-temporal models to large neural ensembles.
NASA Astrophysics Data System (ADS)
Liu, Lang
2015-05-01
The unitary correlation operator method (UCOM) and the similarity renormalization group theory (SRG) are compared and discussed in the framework of the no-core Monte Carlo shell model (MCSM) calculations for 3H and 4He. The treatment of spurious center-of-mass motion by Lawson's prescription is performed in the MCSM calculations. These results with both transformed interactions show good suppression of spurious center-of-mass motion with proper Lawson's prescription parameter ?c.m. values. The UCOM potentials obtain faster convergence of total energy for the ground state than that of SRG potentials in the MCSM calculations, which differs from the cases in the no-core shell model calculations (NCSM). These differences are discussed and analyzed in terms of the truncation scheme in the MCSM and NCSM, as well as the properties of the potentials of SRG and UCOM. Supported by Fundamental Research Funds for the Central Universities (JUSRP1035), National Natural Science Foundation of China (11305077)
NASA Astrophysics Data System (ADS)
Wirawan, Rahadi; Waris, Abdul; Djamal, Mitra; Handayani, Gunawan
2015-04-01
The spectrum of gamma energy absorption in the NaI crystal (scintillation detector) is the interaction result of gamma photon with NaI crystal, and it's associated with the photon gamma energy incoming to the detector. Through a simulation approach, we can perform an early observation of gamma energy absorption spectrum in a scintillator crystal detector (NaI) before the experiment conducted. In this paper, we present a simulation model result of gamma energy absorption spectrum for energy 100-700 keV (i.e. 297 keV, 400 keV and 662 keV). This simulation developed based on the concept of photon beam point source distribution and photon cross section interaction with the Monte Carlo method. Our computational code has been successfully predicting the multiple energy peaks absorption spectrum, which derived from multiple photon energy sources.
NASA Astrophysics Data System (ADS)
Vozinaki, Anthi Eirini K.; Karatzas, George P.; Sibetheros, Ioannis A.; Varouchakis, Emmanouil A.
2014-05-01
Damage curves are the most significant component of the flood loss estimation models. Their development is quite complex. Two types of damage curves exist, historical and synthetic curves. Historical curves are developed from historical loss data from actual flood events. However, due to the scarcity of historical data, synthetic damage curves can be alternatively developed. Synthetic curves rely on the analysis of expected damage under certain hypothetical flooding conditions. A synthetic approach was developed and presented in this work for the development of damage curves, which are subsequently used as the basic input to a flood loss estimation model. A questionnaire-based survey took place among practicing and research agronomists, in order to generate rural loss data based on the responders' loss estimates, for several flood condition scenarios. In addition, a similar questionnaire-based survey took place among building experts, i.e. civil engineers and architects, in order to generate loss data for the urban sector. By answering the questionnaire, the experts were in essence expressing their opinion on how damage to various crop types or building types is related to a range of values of flood inundation parameters, such as floodwater depth and velocity. However, the loss data compiled from the completed questionnaires were not sufficient for the construction of workable damage curves; to overcome this problem, a Weighted Monte Carlo method was implemented, in order to generate extra synthetic datasets with statistical properties identical to those of the questionnaire-based data. The data generated by the Weighted Monte Carlo method were processed via Logistic Regression techniques in order to develop accurate logistic damage curves for the rural and the urban sectors. A Python-based code was developed, which combines the Weighted Monte Carlo method and the Logistic Regression analysis into a single code (WMCLR Python code). Each WMCLR code execution provided a flow velocity-depth damage curve for a specific land use. More specifically, each WMCLR code execution for the agricultural sector generated a damage curve for a specific crop and for every month of the year, thus relating the damage to any crop with floodwater depth, flow velocity and the growth phase of the crop at the time of flooding. Respectively, each WMCLR code execution for the urban sector developed a damage curve for a specific building type, relating structural damage with floodwater depth and velocity. Furthermore, two techno-economic models were developed in Python programming language, in order to estimate monetary values of flood damages to the rural and the urban sector, respectively. A new Monte Carlo simulation was performed, consisting of multiple executions of the techno-economic code, which generated multiple damage cost estimates. Each execution used the proper WMCLR simulated damage curve. The uncertainty analysis of the damage estimates established the accuracy and reliability of the proposed methodology for the synthetic damage curves' development.
NASA Astrophysics Data System (ADS)
Gallardo, Sergio; Pozuelo, Fausto; Querol, Andrea; Ródenas, José; Verdú, Gumersindo
2014-06-01
An accurate knowledge of the photon spectra emitted by X-ray tubes in radiodiagnostic is essential to better estimate the imparted dose to patients and to improve the quality image obtained with these devices. In this work, it is proposed the use of a flat panel detector together with a PMMA wedge to estimate the actual X-ray spectrum using the Monte Carlo method and unfolding techniques. The MCNP5 code has been used to model different flat panels (based on indirect and direct methods to produce charge carriers from absorbed X-rays) and to obtain the dose curves and system response functions. Most of the actual flat panel devices use scintillator materials that present K-edge discontinuities in the mass energy-absorption coefficient, which strongly affect the response matrix. In this paper, the applicability of different flat panels for reconstructing X-ray spectra is studied. The effect of the mass energy-absorption coefficient of the scintillator material has been studied on the response matrix and consequently, in the reconstructed spectra. Different unfolding methods are tested to reconstruct the actual X-ray spectrum knowing the dose curve and the response function. It has been concluded that the regularization method MTSVD is appropriate to unfold X-ray spectra in all the scintillators studied.
NASA Astrophysics Data System (ADS)
Li, J. S.; Ma, C.-M.
2008-02-01
The effects of high electron energy cutoff (ECUT) have been investigated and a method to reduce the dose statistical uncertainty caused by high ECUT was implemented in this work. In EGS4 Monte Carlo simulations, an electron is discarded and its energy is deposited locally when its total energy is lower than ECUT. The deposited energy can be significantly higher than the energy loss calculated using the CSDA model with the corresponding stopping powers in a low-density medium. This will create higher statistical uncertainties in the dose distributions, especially in air and lung tissues. In this work, a new method was implemented to continuously transport a discarded electron without considering multiple scattering or secondary particle generation. The energy loss is calculated based on the mass collision stopping powers in the local medium with an additional energy loss (70%) to account for the effect of approximations made in transporting the electron in a straight line rather than a curved path. The new method can significantly reduce the dose statistical uncertainty and thus improve the simulation efficiency even though the new method requires about 2% more CPU time. Our results showed that the statistical uncertainty of the dose in air cavities of a head-and-neck patient was reduced from 39% to about 2%. The dose distribution for the head and neck patient was significantly improved without losing dose accuracy and simulation efficiency.
Huang, Yinlun
Optimization Method Zheng Liu and Yinlun Huang* Department of Chemical Engineering and Materials Science Wayne a healthy development, for all entities, through synergistic collaboration and decision makers should
NASA Astrophysics Data System (ADS)
Benhdech, Yassine; Beaumont, Stéphane; Guédon, Jean-Pierre; Torfeh, Tarraf
2010-04-01
In this paper, we deepen the R&D program named DTO-DC (Digital Object Test and Dosimetric Console), which goal is to develop an efficient, accurate and full method to achieve dosimetric quality control (QC) of radiotherapy treatment planning system (TPS). This method is mainly based on Digital Test Objects (DTOs) and on Monte Carlo (MC) simulation using the PENELOPE code [1]. These benchmark simulations can advantageously replace experimental measures typically used as reference for comparison with TPS calculated dose. Indeed, the MC simulations rather than dosimetric measurements allow contemplating QC without tying treatment devices and offer in many situations (i.p. heterogeneous medium, lack of scattering volume...) better accuracy compared to dose measurements with classical dosimetry equipment of a radiation therapy department. Furthermore using MC simulations and DTOs, i.e. a totally numerical QC tools, will also simplify QC implementation, and enable process automation; this allows radiotherapy centers to have a more complete and thorough QC. The program DTO-DC was established primarily on ELEKTA accelerator (photons mode) using non-anatomical DTOs [2]. Today our aim is to complete and apply this program on VARIAN accelerator (photons and electrons mode) using anatomical DTOs. First, we developed, modeled and created three anatomical DTOs in DICOM format: 'Head and Neck', Thorax and Pelvis. We parallelized the PENELOPE code using MPI libraries to accelerate their calculation, we have modeled in PENELOPE geometry Clinac head of Varian Clinac 2100CD (photons mode). Then, to implement this method, we calculated the dose distributions in Pelvis DTO using PENELOPE and ECLIPSE TPS. Finally we compared simulated and calculated dose distributions employing the relative difference proposed by Venselaar [3]. The results of this work demonstrate the feasibility of this method that provides a more accurate and easily achievable QC. Nonetheless, this method, implemented on ECLIPSE TPS version 8.6.15, has revealed large discrepancies (11%) between Monte Carlo simulations and the AAA algorithm calculations especially in equivalent air and equivalent bone areas. Our work will be completed by dose measurement (with film) in the presence of heterogeneous environment to validate MC simulations.
NASA Technical Reports Server (NTRS)
Palmer, Grant; Prabhu, Dinesh; Cruden, Brett A.
2013-01-01
The 2013-2022 Decaedal survey for planetary exploration has identified probe missions to Uranus and Saturn as high priorities. This work endeavors to examine the uncertainty for determining aeroheating in such entry environments. Representative entry trajectories are constructed using the TRAJ software. Flowfields at selected points on the trajectories are then computed using the Data Parallel Line Relaxation (DPLR) Computational Fluid Dynamics Code. A Monte Carlo study is performed on the DPLR input parameters to determine the uncertainty in the predicted aeroheating, and correlation coefficients are examined to identify which input parameters show the most influence on the uncertainty. A review of the present best practices for input parameters (e.g. transport coefficient and vibrational relaxation time) is also conducted. It is found that the 2(sigma) - uncertainty for heating on Uranus entry is no more than 2.1%, assuming an equilibrium catalytic wall, with the uncertainty being determined primarily by diffusion and H(sub 2) recombination rate within the boundary layer. However, if the wall is assumed to be partially or non-catalytic, this uncertainty may increase to as large as 18%. The catalytic wall model can contribute over 3x change in heat flux and a 20% variation in film coefficient. Therefore, coupled material response/fluid dynamic models are recommended for this problem. It was also found that much of this variability is artificially suppressed when a constant Schmidt number approach is implemented. Because the boundary layer is reacting, it is necessary to employ self-consistent effective binary diffusion to obtain a correct thermal transport solution. For Saturn entries, the 2(sigma) - uncertainty for convective heating was less than 3.7%. The major uncertainty driver was dependent on shock temperature/velocity, changing from boundary layer thermal conductivity to diffusivity and then to shock layer ionization rate as velocity increases. While radiative heating for Uranus entry was negligible, the nominal solution for Saturn computed up to 20% radiative heating at the highest velocity examined. The radiative heating followed a non-normal distribution, with up to a 3x variation in magnitude. This uncertainty is driven by the H(sub 2) dissociation rate, as H(sub 2) that persists in the hot non-equilibrium zone contributes significantly to radiation.
DeMarco, J J; Cagnon, C H; Cody, D D; Stevens, D M; McCollough, C H; O'Daniel, J; McNitt-Gray, M F
2005-09-01
The purpose of this work was to extend the verification of Monte Carlo based methods for estimating radiation dose in computed tomography (CT) exams beyond a single CT scanner to a multidetector CT (MDCT) scanner, and from cylindrical CTDI phantom measurements to both cylindrical and physical anthropomorphic phantoms. Both cylindrical and physical anthropomorphic phantoms were scanned on an MDCT under the specified conditions. A pencil ionization chamber was used to record exposure for the cylindrical phantom, while MOSFET (metal oxide semiconductor field effect transistor) detectors were used to record exposure at the surface of the anthropomorphic phantom. Reference measurements were made in air at isocentre using the pencil ionization chamber under the specified conditions. Detailed Monte Carlo models were developed for the MDCT scanner to describe the x-ray source (spectra, bowtie filter, etc) and geometry factors (distance from focal spot to isocentre, source movement due to axial or helical scanning, etc). Models for the cylindrical (CTDI) phantoms were available from the previous work. For the anthropomorphic phantom, CT image data were used to create a detailed voxelized model of the phantom's geometry. Anthropomorphic phantom material compositions were provided by the manufacturer. A simulation of the physical scan was performed using the mathematical models of the scanner, phantom and specified scan parameters. Tallies were recorded at specific voxel locations corresponding to the MOSFET physical measurements. Simulations of air scans were performed to obtain normalization factors to convert results to absolute dose values. For the CTDI body (32 cm) phantom, measurements and simulation results agreed to within 3.5% across all conditions. For the anthropomorphic phantom, measured surface dose values from a contiguous axial scan showed significant variation and ranged from 8 mGy/100 mAs to 16 mGy/100 mAs. Results from helical scans of overlapping pitch (0.9375) and extended pitch (1.375) were also obtained. Comparisons between the MOSFET measurements and the absolute dose value derived from the Monte Carlo simulations demonstrate agreement in terms of absolute dose values as well as the spatially varying characteristics. This work demonstrates the ability to extend models from a single detector scanner using cylindrical phantoms to an MDCT scanner using both cylindrical and anthropomorphic phantoms. Future work will be extended to voxelized patient models of different sizes and to other MDCT scanners. PMID:16177525
ERIC Educational Resources Information Center
Carsey, Thomas M.; Harden, Jeffrey J.
2015-01-01
Graduate students in political science come to the discipline interested in exploring important political questions, such as "What causes war?" or "What policies promote economic growth?" However, they typically do not arrive prepared to address those questions using quantitative methods. Graduate methods instructors must…
D. D. Ferrante; J. Doll; G. S. Guralnik; D. Sabo
2002-09-04
Using a common technique for approximating distributions [generalized functions], we are able to use standard Monte Carlo methods to compute QFT quantities in Minkowski spacetime, under phase transitions, or when dealing with coalescing stationary points.
Sharma, Diksha; Badal, Andreu; Badano, Aldo
2012-04-21
The computational modeling of medical imaging systems often requires obtaining a large number of simulated images with low statistical uncertainty which translates into prohibitive computing times. We describe a novel hybrid approach for Monte Carlo simulations that maximizes utilization of CPUs and GPUs in modern workstations. We apply the method to the modeling of indirect x-ray detectors using a new and improved version of the code MANTIS, an open source software tool used for the Monte Carlo simulations of indirect x-ray imagers. We first describe a GPU implementation of the physics and geometry models in fastDETECT2 (the optical transport model) and a serial CPU version of the same code. We discuss its new features like on-the-fly column geometry and columnar crosstalk in relation to the MANTIS code, and point out areas where our model provides more flexibility for the modeling of realistic columnar structures in large area detectors. Second, we modify PENELOPE (the open source software package that handles the x-ray and electron transport in MANTIS) to allow direct output of location and energy deposited during x-ray and electron interactions occurring within the scintillator. This information is then handled by optical transport routines in fastDETECT2. A load balancer dynamically allocates optical transport showers to the GPU and CPU computing cores. Our hybridMANTIS approach achieves a significant speed-up factor of 627 when compared to MANTIS and of 35 when compared to the same code running only in a CPU instead of a GPU. Using hybridMANTIS, we successfully hide hours of optical transport time by running it in parallel with the x-ray and electron transport, thus shifting the computational bottleneck from optical tox-ray transport. The new code requires much less memory than MANTIS and, asa result, allows us to efficiently simulate large area detectors. PMID:22469917
Shi, C. Y.; Xu, X. George; Stabin, Michael G.
2008-07-15
Estimates of radiation absorbed doses from radionuclides internally deposited in a pregnant woman and her fetus are very important due to elevated fetal radiosensitivity. This paper reports a set of specific absorbed fractions (SAFs) for use with the dosimetry schema developed by the Society of Nuclear Medicine's Medical Internal Radiation Dose (MIRD) Committee. The calculations were based on three newly constructed pregnant female anatomic models, called RPI-P3, RPI-P6, and RPI-P9, that represent adult females at 3-, 6-, and 9-month gestational periods, respectively. Advanced Boundary REPresentation (BREP) surface-geometry modeling methods were used to create anatomically realistic geometries and organ volumes that were carefully adjusted to agree with the latest ICRP reference values. A Monte Carlo user code, EGS4-VLSI, was used to simulate internal photon emitters ranging from 10 keV to 4 MeV. SAF values were calculated and compared with previous data derived from stylized models of simplified geometries and with a model of a 7.5-month pregnant female developed previously from partial-body CT images. The results show considerable differences between these models for low energy photons, but generally good agreement at higher energies. These differences are caused mainly by different organ shapes and positions. Other factors, such as the organ mass, the source-to-target-organ centroid distance, and the Monte Carlo code used in each study, played lesser roles in the observed differences in these. Since the SAF values reported in this study are based on models that are anatomically more realistic than previous models, these data are recommended for future applications as standard reference values in internal dosimetry involving pregnant females.
NASA Astrophysics Data System (ADS)
Fox, Jane L.; Ha?, Aleksander B.
2009-12-01
The non-thermal escape of neutral O atoms from Mars at the current epoch is largely due to dissociative recombination of O2+: O2+(v,J)+e?O+O+?E. There are five energetically allowed channels of this reaction, with exothermicities, and thus O kinetic energies, that depend on the on electronic energies of the O atoms produced, on the vibrational and rotational state of the initial O2+ ions, and on the ion and electron velocities. We here construct high and low solar activity models of the martian thermosphere/ionosphere for a solar zenith angle of 60°. The background neutral atmosphere comprises 12 neutral species, whose density profiles range from 80 to 700 km. We calculate the density profiles for 14 ions from 80 to 400 km for both eroded and non-eroded ionospheric models. Using previously described methods, we model the vibrational distribution of the O2+( v) ions as a function of altitude and compute the nascent kinetic energy distribution of the hot O atoms. We then predict the photochemical escape rate of O atoms from Mars in two ways: first by employing the exobase approximation, and second, by using a spherical Monte Carlo code, which tracks the energetic O atoms as they collide with other species in their paths from their initial production altitudes, energies and angles. The O atoms are assumed to escape if they reach 700 km with energies greater than the escape energy. We carry out these Monte Carlo calculations using two different approximations for the distribution of scattering angles in the center-of-mass frame. We first assume that the scattering is isotropic, and then we do the same calculations for a more realistic forward-scattering distribution. We find that the calculated O escape rates for the isotropic model are comparable to those for the exobase approximation, but that the escape rates for the more realistic forward scattering model are an order of magnitude larger.
NASA Astrophysics Data System (ADS)
San Martini, F. M.; Dunlea, E.; Ortega, J. M.; McRae, G. J.; Molina, L. T.; Molina, M. J.; Dzepina, K.; Jimenez, J.; Shorter, J. H.; Canagaratna, M. R.; Herndon, S. C.; Onasch, T. B.; Jayne, J. T.; Wormhoudt, J. C.; Zahniser, M. S.; Worsnop, D. R.; Kolb, C. E.; Salcedo, D.; Marley, N. A.; Gaffney, J. S.; Grutter de La Mora, M.
2004-12-01
Significant effort has been devoted to collecting data on urban particulate matter (PM) concentrations, and advances in particle measurement technologies have allowed for an increasingly sophisticated picture to be developed. Relative to this, the dataset for the gas phase precursors to the inorganic PM is sparse, despite the necessity of these observations in determining effective control strategies. A Bayesian method has been implemented to exploit the asymmetry between the rich aerosol dataset and the relatively poor dataset on gas-phase precursors. A Markov Chain Monte Carlo algorithm was combined with the equilibrium inorganic aerosol model ISORROPIA to produce a powerful tool to analyze aerosol data and predict gas phase concentrations where these are unavailable. The method directly incorporates measurement uncertainty, prior knowledge, and provides for a formal framework to combine measurements of different quality. Applying the method to data from Mexico City, evidence for stable and metastable aerosols was found, and model predictions relative to the observations and their uncertainties are critically compared. Gas phase concentrations, where unavailable, were estimated including, for the first time in Mexico City, hydrochloric acid. The policy implications of these findings will be discussed, with a focus on the role of ammonia and chloride species on particle formation.
Novel phase-space Monte-Carlo method for quench dynamics in 1D and 2D spin models
NASA Astrophysics Data System (ADS)
Pikovski, Alexander; Schachenmayer, Johannes; Rey, Ana Maria
2015-05-01
An important outstanding problem is the effcient numerical computation of quench dynamics in large spin systems. We propose a semiclassical method to study many-body spin dynamics in generic spin lattice models. The method, named DTWA, is based on a novel type of discrete Monte-Carlo sampling in phase-space. We demonstare the power of the technique by comparisons with analytical and numerically exact calculations. It is shown that DTWA captures the dynamics of one- and two-point correlations 1D systems. We also use DTWA to study the dynamics of correlations in 2D systems with many spins and different types of long-range couplings, in regimes where other numerical methods are generally unreliable. Computing spatial and time-dependent correlations, we find a sharp change in the speed of propagation of correlations at a critical range of interactions determined by the system dimension. The investigations are relevant for a broad range of systems including solids, atom-photon systems and ultracold gases of polar molecules, trapped ions, Rydberg, and magnetic atoms. This work has been financially supported by JILA-NSF-PFC-1125844, NSF-PIF-1211914, ARO, AFOSR, AFOSR-MURI.
NASA Astrophysics Data System (ADS)
Díaz, N. Cornejo; Vargas, M. Jurado
2008-02-01
We present the new improved version of our Monte Carlo program DETEFF for detector efficiency calibration in gamma-ray spectrometry. It can be applied to a wide range of sample geometries commonly used for measurements with coaxial gamma-ray detectors: point, rectangular, disk, cylindrical, and Marinelli sources (the last being newly included in this version). The program is a dedicated code, designed specifically for computation of gamma-ray detector efficiency. Therefore, it is more user-friendly and less time consuming than most multi-purpose programs that are intended for a wide range of applications. The comparison of efficiency values obtained with DETEFF and MCNP4C for a typical HpGe detector and for energies between 40 and 1800 keV for point, cylindrical, and Marinelli geometries gave acceptable results, with relative deviations <2% for most energies. The validity of the program was also tested by comparing the DETEFF-calculated efficiency values with those obtained experimentally using a coaxial HpGe detector for different sources (point, disk, and 250 mL Marinelli beaker) which contain 241Am, 109Cd, 57Co, 139Ce, 85Sr, 137Cs, 88Y, and 60Co. The calculated values were in good agreement with the experimental efficiencies for the three geometries considered, with the relative deviations generally being below 3.0%. These results and those obtained during the application of the previous versions indicate the program's suitability as a tool for the efficiency calibration of coaxial gamma-ray detectors, especially in routine measurements such as environmental monitoring.
Monte Carlo Library Least Square (MCLLS) Method for Multiple Radioactive Particle Tracking in BPR
NASA Astrophysics Data System (ADS)
Wang, Zhijian; Lee, Kyoung; Gardner, Robin
2010-03-01
In This work, a new method of radioactive particles tracking is proposed. An accurate Detector Response Functions (DRF's) was developed from MCNP5 to generate library for NaI detectors with a significant speed-up factor of 200. This just make possible for the idea of MCLLS method which is used for locating and tracking the radioactive particle in a modular Pebble Bed Reactor (PBR) by searching minimum Chi-square values. The method was tested to work pretty good in our lab condition with a six 2" X 2" NaI detectors array only. This method was introduced in both forward and inverse ways. A single radioactive particle tracking system with three collimated 2" X 2" NaI detectors is used for benchmark purpose.
Biotic indices have been used ot assess biological condition by dividing index scores into condition categories. Historically the number of categories has been based on professional judgement. Alternatively, statistical methods such as power analysis can be used to determine the ...
ATR WG-MOX Fuel Pellet Burnup Measurement by Monte Carlo - Mass Spectrometric Method
G. S. Chang; Gray Sen I
2002-01-01
This paper presents a new method for calculating the burnup of nuclear reactor fuel, the MCWO-MS method, and describes its application to an experiment currently in progress to assess the suitability for use in light-water reactors of Mixed-OXide (MOX) fuel that contains plutonium derived from excess nuclear weapons material. To demonstrate that the available experience base with Reactor-Grade Mixed uranium-plutonium
NASA Astrophysics Data System (ADS)
Sabouri, P.; Bidaud, A.; Dabiran, S.; Lecarpentier, D.; Ferragut, F.
2014-04-01
The development of tools for nuclear data uncertainty propagation in lattice calculations are presented. The Total Monte Carlo method and the Generalized Perturbation Theory method are used with the code DRAGON to allow propagation of nuclear data uncertainties in transport calculations. Both methods begin the propagation of uncertainties at the most elementary level of the transport calculation - the Evaluated Nuclear Data File. The developed tools are applied to provide estimates for response uncertainties of a PWR cell as a function of burnup.
N. B. Zheleznov
2010-01-01
The probability of an asteroid colliding with a planet can be estimated by the Monte Carlo method, in particular, through the statistical simulation of the possible initial conditions for the motion of an asteroid based on the probability density distribution set by the respective covariance matrix to be further projected with the orbital model onto the supposed time point of
Lanconelli, Nico
2004-01-01
Nuclear Instruments and Methods in Physics Research A 527 (2004) 201205 A full Monte Carlo application of compression, and the integration with RX cameras. The positioning in the vicinity of the tumor tungsten sheet will be placed between the crystal matrix and the compressor to shield the background of low
Monniaux, David
such as nuclear power plants were sensors have a limited life time and cannot be expected to be reliable. Sound of Programming Languages An Abstract Monte-Carlo Method for the Analysis of Probabilistic Programs David Monniaux, for the analysis of programs featuring both probabilistic and non-probabilistic nondeter- minism. After introducing
Pázsit, Imre
2007-01-01
Nuclear Instruments and Methods in Physics Research A 582 (2007) 629637 Monte Carlo and analytical materials in applications such as nuclear nonproliferation, homeland security, and basic physics research unfolding, which have a variety of applications, including nuclear nonproliferation and homeland security
Budanec, M; Knezevi?, Z; Bokuli?, T; Mrcela, I; Vrtar, M; Veki?, B; Kusi?, Z
2008-12-01
This work studied the percent depth doses of (60)Co photon beams in the buildup region of a plastic phantom by LiF TLD measurements and by Monte Carlo calculations. An agreement within +/-1.5% was found between PDDs measured by TLD and calculated by the Monte Carlo method with the TLD in a plastic phantom. The dose in the plastic phantom was scored in voxels, with thickness scaled by physical and electron density. PDDs calculated by electron density scaling showed a better match with PDD(TLD)(MC); the difference is within +/-1.5% in the buildup region for square and rectangular field sizes. PMID:18541436
Bead-Fourier path integral Monte Carlo method applied to systems of identical particles
NASA Astrophysics Data System (ADS)
Vorontsov-Velyaminov, P. N.; Gorbunov, R. I.; Ivanov, S. D.
1999-09-01
To make the PIMC method more effective a combined, bead-Fourier (BF), PIMC simulation scheme was introduced with its extreme cases corresponding to the ordinary “bead” and Fourier PIMC methods. Optimal choice of the number of beads and of Fourier harmonics made it possible to reproduce well the ground state energy and electron density in the H-atom. While applying the BF method to systems of identical particles a procedure of simultaneous account for all classes of permutations suggested earlier was used with subsequent symmetrization of the exchange factor in the weight function. A procedure of random walk in the spin space allows to calculate also spin dependent averages. The exact expressions obtained for the partition function and canonical averages of a D-dimensional system of N noninteracting identical particles in a harmonic field gave a reliable test of the developed MC procedures performed for N=2,3,5 in a wide temperature range. We compared the analytically available exact result for the average of sign,
Inferring synaptic inputs given a noisy voltage trace via sequential Monte Carlo methods
Columbia University
intracellular voltage-clamp or current-clamp recordings from the postsynaptic cell. These methods are based) algorithms that con- sist of alternating iterations between these synaptic recovery and model estimation input conductances are large and distinct enough to be inferred via direct thresholding techniques
Xu, Yuan; Bai, Ti; Yan, Hao; Ouyang, Luo; Pompos, Arnold; Wang, Jing; Zhou, Linghong; Jiang, Steve B; Jia, Xun
2015-05-01
Cone-beam CT (CBCT) has become the standard image guidance tool for patient setup in image-guided radiation therapy. However, due to its large illumination field, scattered photons severely degrade its image quality. While kernel-based scatter correction methods have been used routinely in the clinic, it is still desirable to develop Monte Carlo (MC) simulation-based methods due to their accuracy. However, the high computational burden of the MC method has prevented routine clinical application. This paper reports our recent development of a practical method of MC-based scatter estimation and removal for CBCT. In contrast with conventional MC approaches that estimate scatter signals using a scatter-contaminated CBCT image, our method used a planning CT image for MC simulation, which has the advantages of accurate image intensity and absence of image truncation. In our method, the planning CT was first rigidly registered with the CBCT. Scatter signals were then estimated via MC simulation. After scatter signals were removed from the raw CBCT projections, a corrected CBCT image was reconstructed. The entire workflow was implemented on a GPU platform for high computational efficiency. Strategies such as projection denoising, CT image downsampling, and interpolation along the angular direction were employed to further enhance the calculation speed. We studied the impact of key parameters in the workflow on the resulting accuracy and efficiency, based on which the optimal parameter values were determined. Our method was evaluated in numerical simulation, phantom, and real patient cases. In the simulation cases, our method reduced mean HU errors from 44 to 3?HU and from 78 to 9?HU in the full-fan and the half-fan cases, respectively. In both the phantom and the patient cases, image artifacts caused by scatter, such as ring artifacts around the bowtie area, were reduced. With all the techniques employed, we achieved computation time of less than 30?s including the time for both the scatter estimation and CBCT reconstruction steps. The efficacy of our method and its high computational efficiency make our method attractive for clinical use. PMID:25860299
Park, H. J.; Shim, H. J.; Joo, H. G.; Kim, C. H.
2012-07-01
The purpose of this paper is to quantify uncertainties of fuel pin cell or fuel assembly (FA) homogenized few group diffusion theory constants generated from the B1 theory-augmented Monte Carlo (MC) method. A mathematical formulation of the first kind is presented to quantify uncertainties of the few group constants in terms of the two major sources of the MC method; statistical and nuclear cross section and nuclide number density input data uncertainties. The formulation is incorporated into the Seoul National Univ. MC code McCARD. It is then used to compute the uncertainties of the burnup-dependent homogenized two group constants of a low-enriched UO{sub 2} fuel pin cell and a PWR FA on the condition that nuclear cross section input data of U-235 and U-238 from JENDL 3.3 library and nuclide number densities from the solution to fuel depletion equations have uncertainties. The contribution of the MC input data uncertainties to the uncertainties of the two group constants of the two fuel systems is separated from that of the statistical uncertainties. The utilities of uncertainty quantifications are then discussed from the standpoints of safety analysis of existing power reactors, development of new fuel or reactor system design, and improvement of covariance files of the evaluated nuclear data libraries. (authors)
Song, Sangha; Elgezua, Inko; Kobayashi, Yo; Fujie, Masakatsu G
2013-01-01
In biomedical, Monte-carlo simulation is commonly used for simulation of light diffusion in tissue. But, most of previous studies did not consider a radial beam LED as light source. Therefore, we considered characteristics of a radial beam LED and applied them on MC simulation as light source. In this paper, we consider 3 characteristics of radial beam LED. The first is an initial launch area of photons. The second is an incident angle of a photon at an initial photon launching area. The third is the refraction effect according to contact area between LED and a turbid medium. For the verification of the MC simulation, we compared simulation and experimental results. The average of the correlation coefficient between simulation and experimental results is 0.9954. Through this study, we show an effective method to simulate light diffusion on tissue with characteristics for radial beam LED based on MC simulation. PMID:24109615
Assaraf, Roland
2014-12-01
We show that the recently proposed correlated sampling without reweighting procedure extends the locality (asymptotic independence of the system size) of a physical property to the statistical fluctuations of its estimator. This makes the approach potentially vastly more efficient for computing space-localized properties in large systems compared with standard correlated methods. A proof is given for a large collection of noninteracting fragments. Calculations on hydrogen chains suggest that this behavior holds not only for systems displaying short-range correlations, but also for systems with long-range correlations. PMID:25615231
Finch, W. Holmes; Bolin, Jocelyn H.; Kelley, Ken
2014-01-01
Classification using standard statistical methods such as linear discriminant analysis (LDA) or logistic regression (LR) presume knowledge of group membership prior to the development of an algorithm for prediction. However, in many real world applications members of the same nominal group, might in fact come from different subpopulations on the underlying construct. For example, individuals diagnosed with depression will not all have the same levels of this disorder, though for the purposes of LDA or LR they will be treated in the same manner. The goal of this simulation study was to examine the performance of several methods for group classification in the case where within group membership was not homogeneous. For example, suppose there are 3 known groups but within each group two unknown classes. Several approaches were compared, including LDA, LR, classification and regression trees (CART), generalized additive models (GAM), and mixture discriminant analysis (MIXDA). Results of the study indicated that CART and mixture discriminant analysis were the most effective tools for situations in which known groups were not homogeneous, whereas LDA, LR, and GAM had the highest rates of misclassification. Implications of these results for theory and practice are discussed. PMID:24904445
Error propagation in the computation of volumes in 3D city models with the Monte Carlo method
NASA Astrophysics Data System (ADS)
Biljecki, F.; Ledoux, H.; Stoter, J.
2014-11-01
This paper describes the analysis of the propagation of positional uncertainty in 3D city models to the uncertainty in the computation of their volumes. Current work related to error propagation in GIS is limited to 2D data and 2D GIS operations, especially of rasters. In this research we have (1) developed two engines, one that generates random 3D buildings in CityGML in multiple LODs, and one that simulates acquisition errors to the geometry; (2) performed an error propagation analysis on volume computation based on the Monte Carlo method; and (3) worked towards establishing a framework for investigating error propagation in 3D GIS. The results of the experiments show that a comparatively small error in the geometry of a 3D city model may cause significant discrepancies in the computation of its volume. This has consequences for several applications, such as in estimation of energy demand and property taxes. The contribution of this work is twofold: this is the first error propagation analysis in 3D city modelling, and the novel approach and the engines that we have created can be used for analysing most of 3D GIS operations, supporting related research efforts in the future.
NASA Astrophysics Data System (ADS)
Li, Xin; Koloren?, Jind?ich; Mitas, Lubos
2011-08-01
We calculate the ground-state properties of an unpolarized two-component Fermi gas with the aid of the diffusion quantum Monte Carlo (DMC) methods. Using an extrapolation to the zero effective range of the attractive two-particle interaction, we find E/Efree in the unitary limit to be 0.212(2), 0.407(2), 0.409(3), and 0.398(3) for 4, 14, 38, and 66 atoms, respectively. Our calculations indicate that the dependence of the total energy on the effective range of the interaction Reff is sizable and the extrapolation to Reff=0 is therefore important for reaching the true unitary limit. To test the quality of nodal surfaces and to estimate the impact of the fixed-node approximation, we perform released-node DMC calculations for 4 and 14 atoms. Analysis of the released-node and the fixed-node results suggests that the main sources of the fixed-node errors are long-range correlations, which are difficult to sample in the released-node approaches due to the fast growth of the bosonic noise. Besides energies, we evaluate the two-body density matrix and the condensate fraction. We find that the condensate fraction for the 66-atom system converges to 0.56(1) after the extrapolation to the zero interaction range.
NASA Astrophysics Data System (ADS)
Kohno, R.; Hotta, K.; Nishioka, S.; Matsubara, K.; Tansho, R.; Suzuki, T.
2011-11-01
We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU- and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU- and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30-16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9-67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning.
Mallory, Joel D; Mandelshtam, Vladimir A
2015-01-01
The Diffusion Monte Carlo (DMC) method is applied to the water monomer, dimer, and hexamer, using q-TIP4P/F, one of the most simple, empirical water models with flexible monomers. The bias in the time step ($\\Delta\\tau$) and population size ($N_w$) is investigated. For the binding energies, the bias in $\\Delta\\tau$ cancels nearly completely, while a noticeable bias in $N_w$ still remains. However, for the isotope shift, (e.g, in the dimer binding energies between (H$_2$O)$_2$ and (D$_2$O)$_2$) the systematic errors in $N_w$ do cancel. Consequently, very accurate results for the latter (within $\\sim 0.01$ kcal/mol) are obtained with relatively moderate numerical effort ($N_w\\sim 10^3$). For the water hexamer and its (D$_2$O)$_6$ isotopomer the DMC results as a function of $N_w$ are examined for the cage and prism isomers. For a given isomer, the issue of the walker population leaking out of the corresponding basin of attraction is addressed by using appropriate geometric constraints. The population size bias f...
Wang, Yuting; 10.1103/PhysRevD.81.083523
2010-01-01
In this paper, the holographic dark energy model with new infrared (IR) cut-off for both the flat case and the non-flat case are confronted with the combined constraints of current cosmological observations: type Ia Supernovae, Baryon Acoustic Oscillations, current Cosmic Microwave Background, and the observational hubble data. By utilizing the Markov Chain Monte Carlo (MCMC) method, we obtain the best fit values of the parameters with $1\\sigma, 2\\sigma$ errors in the flat model: $\\Omega_{b}h^2=0.0230^{+0.0008 +0.0012}_{-0.0010-0.0014}$, $\\alpha=0.9788^{+0.1297 +0.1354}_{-0.0927 -0.1249}$, $\\beta=0.4739^{+0.0793 +0.1055}_{-0.0723 -0.0984}$, $\\Omega_{de0}=0.7869^{+0.0291 +0.0370}_{-0.0304 -0.0455}$, $\\Omega_{m0}=0.2131^{+0.0304 +0.0455}_{-0.0291 -0.0370}$, $H_0=70.46^{+2.82 +3.89}_{-2.97 -4.02}$. In the non-flat model, the constraint results are found in $1\\sigma, 2\\sigma$ regions: $\\Omega_{b}h^2=0.0229^{+0.0010 +0.0013}_{-0.0010 -0.0014}$, $\\Omega_k=0.0014^{+0.0604 +0.0604}_{-0.0597 -0.0743}$, $\\alpha=0.9637^...
Calculation of Nonlinear Thermoelectric Coefficients of InAs1-xSbx Using Monte Carlo Method
Sadeghian, RB; Bahk, JH; Bian, ZX; Shakouri, A
2011-12-28
It was found that the nonlinear Peltier effect could take place and increase the cooling power density when a lightly doped thermoelectric material is under a large electrical field. This effect is due to the Seebeck coefficient enhancement from an electron distribution far from equilibrium. In the nonequilibrium transport regime, the solution of the Boltzmann transport equation in the relaxation-time approximation ceases to apply. The Monte Carlo method, on the other hand, proves to be a capable tool for simulation of semiconductor devices at small scales as well as thermoelectric effects with local nonequilibrium charge distribution. InAs1-xSb is a favorable thermoelectric material for nonlinear operation owing to its high mobility inherited from the binary compounds InSb and InAs. In this work we report simulation results on the nonlinear Peltier power of InAs1-xSb at low doping levels, at room temperature and at low temperatures. The thermoelectric power factor in nonlinear operation is compared with the maximum value that can be achieved with optimal doping in the linear transport regime.
Study of Phase Equilibria of Petrochemical Fluids using Gibbs Ensemble Monte Carlo Methods
NASA Astrophysics Data System (ADS)
Nath, Shyamal
2001-03-01
Knowledge of phase behavior of hydrocarbons and related compounds are highly of interest to chemical and petrochemical industries. For example, design of processes such as supercritical fluid extraction, petroleum refining, enhanced oil recovery, gas treatment, and fractionation of wax products. A precise knowledge of the phase equilibria of alkanes, alkenes and related compounds and their mixtures are required for efficient design of these processes. Experimental studies to understand the related phase equilibria often become unsuitable for various reasons. With the advancement of simulation technology, molecular simulations could provide a useful complement and alternative in the study and description of phase behavior of these systems. In this work we study vapor-liquid phase equilibria of pure hydrocarbons and their mixtures using Gibbs ensemble simulation. Insertion of long and articulated chain molecules are facilitated in our simulations by means of configurational bias and expanded ensemble methods. We use the newly developed NERD force field in our simulation. In this work NERD force field is extended to provide coverage for hydrocarbons with any arbitrary architecture. Our simulation results provide excellent quantitative agreement with available experimental phase equilibria data for both the pure components and mixtures.
Percolation of the site random-cluster model by Monte Carlo method
NASA Astrophysics Data System (ADS)
Wang, Songsong; Zhang, Wanzhou; Ding, Chengxiang
2015-08-01
We propose a site random-cluster model by introducing an additional cluster weight in the partition function of the traditional site percolation. To simulate the model on a square lattice, we combine the color-assignation and the Swendsen-Wang methods to design a highly efficient cluster algorithm with a small critical slowing-down phenomenon. To verify whether or not it is consistent with the bond random-cluster model, we measure several quantities, such as the wrapping probability Re, the percolating cluster density P?, and the magnetic susceptibility per site ?p, as well as two exponents, such as the thermal exponent yt and the fractal dimension yh of the percolating cluster. We find that for different exponents of cluster weight q =1.5 , 2, 2.5 , 3, 3.5 , and 4, the numerical estimation of the exponents yt and yh are consistent with the theoretical values. The universalities of the site random-cluster model and the bond random-cluster model are completely identical. For larger values of q , we find obvious signatures of the first-order percolation transition by the histograms and the hysteresis loops of percolating cluster density and the energy per site. Our results are helpful for the understanding of the percolation of traditional statistical models.
Gurevich, M. I.; Oleynik, D. S.; Russkov, A. A.; Voloschenko, A. M.
2006-07-01
The tracing algorithm that is implemented in the geometrical module of Monte-Carlo transport code MCU is applied to calculate the volume fractions of original materials by spatial cells of the mesh that overlays problem geometry. In this way the 3D combinatorial geometry presentation of the problem geometry, used by MCU code, is transformed to the user defined 2D or 3D bit-mapped ones. Next, these data are used in the volume fraction (VF) method to approximate problem geometry by introducing additional mixtures for spatial cells, where a few original materials are included. We have found that in solving realistic 2D and 3D core problems a sufficiently fast convergence of the VF method takes place if the spatial mesh is refined. Virtually, the proposed variant of implementation of the VF method seems as a suitable geometry interface between Monte-Carlo and S{sub n} transport codes. (authors)
Dioszegi, I. [Nonproliferation and National Security Department, Brookhaven National Laboratory, Upton, New York 11973 (United States); Rusek, A.; Chiang, I. H. [NASA Space Radiation Laboratory, Brookhaven National Laboratory, Upton, NY 11973 (United States); Dane, B. R. [Medical School, State University of New York at Stony Brook, Stony Brook, NY 11794 (United States); Meek, A. G. [Department of Radiation Oncology, State University of New York at Stony Brook, Stony Brook, NY 11794 (United States); Dilmanian, F. A. [Department of Radiation Oncology, State University of New York at Stony Brook, Stony Brook, NY 11794 (United States); Medical Department, Brookhaven National Laboratory, Upton, NY 11973 (United States)
2011-06-01
Recent upgrades of the MCNPX Monte Carlo code include transport of heavy ions. We employed the new code to simulate the energy and dose distributions produced by carbon beams in rabbit's head in and around a brain tumor. The work was within our experimental technique of interlaced carbon microbeams, which uses two 90 deg. arrays of parallel, thin planes of carbon beams (microbeams) interlacing to produce a solid beam at the target. A similar version of the method was earlier developed with synchrotron-generated x-ray microbeams. We first simulated the Bragg peak in high density polyethylene and other materials, where we could compare the calculated carbon energy deposition to the measured data produced at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL). The results showed that new MCNPX code gives a reasonable account of the carbon beam's dose up to {approx}200 MeV/nucleon beam energy. At higher energies, which were not relevant to our project, the model failed to reproduce the Bragg-peak's extent of increasing nuclear breakup tail. In our model calculations we determined the dose distribution along the beam path, including the angular straggling of the microbeams, and used the data for determining the optimal values of beam spacing in the array for producing adequate beam interlacing at the target. We also determined, for the purpose of Bragg-peak spreading at the target, the relative beam intensities of the consecutive exposures with stepwise lower beam energies, and simulated the resulting dose distribution in the spread out Bragg-peak. The details of the simulation methods used and the results obtained are presented.
NASA Astrophysics Data System (ADS)
Dioszegi, I.; Rusek, A.; Dane, B. R.; Chiang, I. H.; Meek, A. G.; Dilmanian, F. A.
2011-06-01
Recent upgrades of the MCNPX Monte Carlo code include transport of heavy ions. We employed the new code to simulate the energy and dose distributions produced by carbon beams in rabbit's head in and around a brain tumor. The work was within our experimental technique of interlaced carbon microbeams, which uses two 90° arrays of parallel, thin planes of carbon beams (microbeams) interlacing to produce a solid beam at the target. A similar version of the method was earlier developed with synchrotron-generated x-ray microbeams. We first simulated the Bragg peak in high density polyethylene and other materials, where we could compare the calculated carbon energy deposition to the measured data produced at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL). The results showed that new MCNPX code gives a reasonable account of the carbon beam's dose up to ˜200 MeV/nucleon beam energy. At higher energies, which were not relevant to our project, the model failed to reproduce the Bragg-peak's extent of increasing nuclear breakup tail. In our model calculations we determined the dose distribution along the beam path, including the angular straggling of the microbeams, and used the data for determining the optimal values of beam spacing in the array for producing adequate beam interlacing at the target. We also determined, for the purpose of Bragg-peak spreading at the target, the relative beam intensities of the consecutive exposures with stepwise lower beam energies, and simulated the resulting dose distribution in the spread out Bragg-peak. The details of the simulation methods used and the results obtained are presented.
NASA Astrophysics Data System (ADS)
Wen, Xiulan; Xu, Youxiong; Li, Hongsheng; Wang, Fenglin; Sheng, Danghong
2012-09-01
Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product specification(GPS) requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on "The Guide to the Expression of Uncertainty in Measurement(GUM)". In order to compute spatial straightness error(SSE) accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization(QPSO) is proposed to solve the minimum zone SSE and Monte Carlo Method(MCM) is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function(PDF) for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine(CMM) is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.
Czyzycki, Mateusz; Lankosz, Marek [AGH-University of Science and Technology, Faculty of Physics and Applied Computer Science, Al. Mickiewicza 30, 30-059 Krakow (Poland); Bielewski, Marek [AGH-University of Science and Technology, Faculty of Physics and Applied Computer Science, Al. Mickiewicza 30, 30-059 Krakow (Poland); European Commission, Joint Research Centre, Institute for Transuranium Elements, P.O. Box 2340, D-76125 Karlsruhe (Germany)
2010-04-06
Recently a considerable interest has been triggered in the investigation of the composition of individual particles by X-ray fluorescence microanalysis. The sources of these micro-samples are mostly diversified. These samples come from space dust, air and ash, soil as well as environment and take the shape of a sphere or an oval. In analysis this kind of samples the geometrical effects caused by different sizes and shapes influence on accuracy of results. This fact arises from the matrix effect. For these samples it is not possible to find analytically a solution of equation taking into account an absorption of X-rays. Hence, a way out is to approximate the real sample shape with the other one or to use Monte Carlo (MC) simulation method. In current work authors utilized the iterative MC simulation to assess an elemental percentage of individual particles. The set of glass micro-spheres, made of NIST K3089 material of known chemical composition, with diameters in the range between 25 and 45 {mu}m was investigated. The microspheres were scanned with X-ray tube primary radiation. Results of MC simulation were compared with these of some analytical approaches based on particle shape approximation. An investigation showed that the low-Z elements (Si, Ca, Ti) were the most sensitive on changes of particle shape and sizes. For high-Z elements (Fe--Pb) concentrations were nearly equal regardless of method used. However, for the all elements considered, results of MC simulation were more accurate then these of analytical relationships taken into comparison.
NASA Astrophysics Data System (ADS)
Chen, X.; Rubin, Y.; Baldocchi, D. D.
2005-12-01
Understanding the interactions between soil, plant, and the atmosphere under water-stressed conditions is important for ecosystems where water availability is limited. In such ecosystems, the amount of water transferred from the soil to the atmosphere is controlled not only by weather conditions and vegetation type but also by soil water availability. Although researchers have proposed different approaches to model the impact of soil moisture on plant activities, the parameters involved are difficult to measure. However, using measurements of observed latent heat and carbon fluxes, as well as soil moisture data, Bayesian inversion methods can be employed to estimate the various model parameters. In our study, actual Evapotranspiration (ET) of an ecosystem is approximated by the Priestley-Taylor relationship, with the Priestley-Taylor coefficient modeled as a function of soil moisture content. Soil moisture limitation on root uptake is characterized in a similar manner as the Feddes' model. The inference of Bayesian inversion is processed within the framework of graphical theories. Due to the difficulty of obtaining exact inference, the Markov chain Monte Carlo (MCMC) method is implemented using a free software package, BUGS (Bayesian inference Using Gibbs Sampling). The proposed methodology is applied to a Mediterranean Oak-Savanna FLUXNET site in California, where continuous measurements of actual ET are obtained from eddy-covariance technique and soil moisture contents are monitored by several time domain reflectometry probes located within the footprint of the flux tower. After the implementation of Bayesian inversion, the posterior distributions of all the parameters exhibit enhancement in information compared to the prior distributions. The generated samples based on data in year 2003 are used to predict the actual ET in year 2004 and the prediction uncertainties are assessed in terms of confidence intervals. Our tests also reveal the usefulness of various types of soil moisture data in parameter estimation, which could be used to guide analyses of available data and planning of field data collection activities.
Hendricks, J. S. (John S.)
2003-01-01
MCNPX is a Fortran 90 Monte Carlo radiation transport computer code that transports all particles at all energies. It is a superset of MCNP4C3, and has many capabilities beyond MCNP4C3. These capabilities are summarized along with their quality guarantee and code availability. Then the user interface changes from MCNP are described. Finally, the n.ew capabilities of the latest version, MCNPX 2.5.c, are documented. Future plans and references are also provided.
NASA Astrophysics Data System (ADS)
Jones, Andrew; Thompson, Andrew; Crain, Jason; Müser, Martin H.; Martyna, Glenn J.
2009-04-01
The quantum Drude oscillator (QDO) model, which allows many-body polarization and dispersion to be treated both on an equal footing and beyond the dipole limit, is investigated using two approaches to the linear scaling diffusion Monte Carlo (DMC) technique. The first is a general purpose norm-conserving DMC (NC-DMC) method wherein the number of walkers, N , remains strictly constant thereby avoiding the sudden death or explosive growth of walker populations with an error that vanishes as O(N-1) in the absence of weights. As NC-DMC satisfies detailed balance, a phase space can be defined that permits both an exact trajectory weighting and a fast mean-field trajectory weighting technique to be constructed which can eliminate or reduce the population bias, respectively. The second is a many-body diagrammatic expansion for trial wave functions in systems dominated by strong on-site harmonic coupling and a dense matrix of bilinear coupling constants such as the QDO in the dipole limit; an approximate trial function is introduced to treat two-body interactions outside the dipole limit. Using these approaches, high accuracy is achieved in studies of the fcc-solid phase of the highly polarizable atom, xenon, within the QDO model. It is found that 200 walkers suffice to generate converged results for systems as large as 500 atoms. The quality of QDO predictions compared to experiment and the ability to generate these predictions efficiently demonstrate the feasibility of employing the QDO approach to model long-range forces.
Giles, Mike
estimate for the variance 2 and hence add to the plot upper and lower confidence bounds based on 3 standardMonte Carlo Methods for Uncertainty Quantification: Practical 1 1. Suppose that a and b are two . By considering = ± E[a2]/E[b2] prove that |E[ab]| E[a2] E[b2]. Hence, prove that for any two scalar random
N. B. Zheleznov
2010-01-01
The probability of an asteroid colliding with a planet can be estimated by the Monte Carlo method, in particular, through\\u000a the statistical simulation of the possible initial conditions for the motion of an asteroid based on the probability density\\u000a distribution set by the respective covariance matrix to be further projected with the orbital model onto the supposed time\\u000a point of
NASA Astrophysics Data System (ADS)
Gheorghe, Munteanu Bogdan; Alexei, Leahu; Sergiu, Cataranciuc
2013-09-01
We prove the limit theorem for life time distribution connected with reliability systems when their life time is a Pascal Convolution of independent and identically distributed random variables. We show that, in some conditions, such distributions may be approximated by means of Erlang distributions. As a consequnce, survival functions for such systems may be, respectively, approximated by Erlang survival functions. By using Monte Carlo method we experimantally confirm the theoretical results of our theorem.
NASA Astrophysics Data System (ADS)
Asllanaj, Fatmir; Contassot-Vivier, Sylvain; Liemert, André; Kienle, Alwin
2014-01-01
We examine the accuracy of a modified finite volume method compared to analytical and Monte Carlo solutions for solving the radiative transfer equation. The model is used for predicting light propagation within a two-dimensional absorbing and highly forward-scattering medium such as biological tissue subjected to a collimated light beam. Numerical simulations for the spatially resolved reflectance and transmittance are presented considering refractive index mismatch with Fresnel reflection at the interface, homogeneous and two-layered media. Time-dependent as well as steady-state cases are considered. In the steady state, it is found that the modified finite volume method is in good agreement with the other two methods. The relative differences between the solutions are found to decrease with spatial mesh refinement applied for the modified finite volume method obtaining <2.4%. In the time domain, the fourth-order Runge-Kutta method is used for the time semi-discretization of the radiative transfer equation. An agreement among the modified finite volume method, Runge-Kutta method, and Monte Carlo solutions are shown, but with relative differences higher than in the steady state.
NASA Astrophysics Data System (ADS)
Ródenas, José; Gallardo, Sergio; Ballester, Silvia; Primault, Virginie; Ortiz, Josefina
2007-10-01
A gamma spectrometer including an HP Ge detector is commonly used for environmental radioactivity measurements. The efficiency of the detector should be calibrated for each geometry considered. Simulation of the calibration procedure with a validated computer program is an important auxiliary tool for environmental radioactivity laboratories. The MCNP code based on the Monte Carlo method has been applied to simulate the detection process in order to obtain spectrum peaks and determine the efficiency curve for each modelled geometry. The source used for measurements was a calibration mixed radionuclide gamma reference solution, covering a wide energy range (50-2000 keV). Two measurement geometries - Marinelli beaker and Petri boxes - as well as different materials - water, charcoal, sand - containing the source have been considered. Results obtained from the Monte Carlo model have been compared with experimental measurements in the laboratory in order to validate the model.
Wada, Takao; Ueda, Noriaki
2013-01-01
The process of low pressure organic vapor phase deposition (LP-OVPD) controls the growth of amorphous organic thin films, where the source gases (Alq3 molecule, etc.) are introduced into a hot wall reactor via an injection barrel using an inert carrier gas (N2 molecule). It is possible to control well the following substrate properties such as dopant concentration, deposition rate, and thickness uniformity of the thin film. In this paper, we present LP-OVPD simulation results using direct simulation Monte Carlo-Neutrals (Particle-PLUS neutral module) which is commercial software adopting direct simulation Monte Carlo method. By estimating properly the evaporation rate with experimental vaporization enthalpies, the calculated deposition rates on the substrate agree well with the experimental results that depend on carrier gas flow rate and source cell temperature. PMID:23674843
NASA Astrophysics Data System (ADS)
Määttänen, Anni; Douspis, Marian
2015-04-01
In the last years several datasets on deposition mode ice nucleation in Martian conditions have showed that the effectiveness of mineral dust as a condensation nucleus decreases with temperature (Iraci et al., 2010; Phebus et al., 2011; Trainer et al., 2009). Previously, nucleation modelling in Martian conditions used only constant values of this so-called contact parameter, provided by the few studies previously published on the topic. The new studies paved the way for possibly more realistic way of predicting ice crystal formation in the Martian environment. However, the caveat of these studies (Iraci et al., 2010; Phebus et al., 2011) was the limited temperature range that inhibits using the provided (linear) equations for the contact parameter temperature dependence in all conditions of cloud formation on Mars. One wide temperature range deposition mode nucleation dataset exists (Trainer et al., 2009), but the used substrate was silicon, which cannot imitate realistically the most abundant ice nucleus on Mars, mineral dust. Nevertheless, this dataset revealed, thanks to measurements spanning from 150 to 240 K, that the behaviour of the contact parameter as a function of temperature was exponential rather than linear as suggested by previous work. We have tried to combine the previous findings to provide realistic and practical formulae for application in nucleation and atmospheric models. We have analysed the three cited datasets using a Monte Carlo Markov Chain (MCMC) method. The used method allows us to test and evaluate different functional forms for the temperature dependence of the contact parameter. We perform a data inversion by finding the best fit to the measured data simultaneously at all points for different functional forms of the temperature dependence of the contact angle m(T). The method uses a full nucleation model (Määttänen et al., 2005; Vehkamäki et al., 2007) to calculate the observables at each data point. We suggest one new and test several m(T) dependencies. Two of these may be used to avoid unphysical behaviour (m > 1) when m(T) is implemented in heterogeneous nucleation and cloud models. However, more measurements are required to fully constrain the m(T) dependencies. We show the importance of large temperature range datasets for constraining the asymptotic behaviour of m(T), and we call for more experiments in a large temperature range with well-defined particle sizes or size distributions, for different IN types and nucleating vapours. This study (Määttänen and Douspis, 2014) provides a new framework for analysing heterogeneous nucleation datasets. The results provide, within limits of available datasets, well-behaving m(T) formulations for nucleation and cloud modelling. Iraci, L. T., et al. (2010). Icarus 210, 985-991. Määttänen, A., et al. (2005). J. Geophys. Res. 110, E02002. Määttänen, A. and Douspis, M. (2014). GeoResJ 3-4 , 46-55. Phebus, B. D., et al. (2011). J. Geophys. Res. 116, 4009. Trainer, M. G., et al. (2009). J. Phys. Chem C 113 , 2036-2040. Vehkamäki, H., et al. (2007). Atmos. Chem. Phys. 7, 309-313.
NASA Astrophysics Data System (ADS)
Whitmore, Alexander Jason
Concentrating solar power systems are currently the predominant solar power technology for generating electricity at the utility scale. The central receiver system, which is a concentrating solar power system, uses a field of mirrors to concentrate solar radiation onto a receiver where a working fluid is heated to drive a turbine. Current central receiver systems operate on a Rankine cycle, which has a large demand for cooling water. This demand for water presents a challenge for the current central receiver systems as the ideal locations for solar power plants have arid climates. An alternative to the current receiver technology is the small particle receiver. The small particle receiver has the potential to produce working fluid temperatures suitable for use in a Brayton cycle which can be more efficient when pressurized to 0.5 MPa. Using a fused quartz window allows solar energy into the receiver while maintaining a pressurized small particle receiver. In this thesis, a detailed numerical investigation for a spectral, three dimensional, cylindrical glass window for a small particle receiver was performed. The window is 1.7 meters in diameter and 0.0254 meters thick. There are three Monte Carlo Ray Trace codes used within this research. The first MCRT code, MIRVAL, was developed by Sandia National Laboratory and modified by a fellow San Diego State University colleague Murat Mecit. This code produces the solar rays on the exterior surface of the window. The second MCRT code was developed by Steve Ruther and Pablo Del Campo. This code models the small particle receiver, which creates the infrared spectral direction flux on the interior surface of the window used in this work. The third MCRT, developed for this work, is used to model radiation heat transfer within the window itself and is coupled to an energy equation solver to produce a temperature distribution. The MCRT program provides a source term to the energy equation. This in turn, produces a new temperature field for the MCRT program; together the equations are solved iteratively. These iterations repeat until convergence is reached for a steady state temperature field. The energy equation was solved using a finite volume method. The window's thermal conductivity is modeled as a function of temperature. This thermal model is used to investigate the effects of different materials, receiver geometries, interior convection coefficients and exterior convection coefficients. To prevent devitrification and the ultimate failure of the window, the window needs to stay below the devitrification temperature of the material. In addition, the temperature gradients within the window need to be kept to a minimum to prevent thermal stresses. A San Diego State University colleague E-Fann Saung uses these temperature maps to insure that the mounting of the window does not produce thermal stresses which can cause cracking in the brittle fused quartz. The simulations in this thesis show that window temperatures are below the devitrification temperature of the window when there are cooling jets on both surfaces of the window. Natural convection on the exterior window surface was explored and it does not provide adequate cooling; therefore forced convection is required. Due to the low thermal conductivity of the window, the edge mounting thermal boundary condition has little effect on the maximum temperature of the window. The simulations also showed that the solar input flux absorbed less than 1% of the incoming radiation while the window absorbed closer to 20% of the infrared radiation emitted by the receiver. The main source of absorbed power in the window is located directly on the interior surface of the window where the infrared radiation is absorbed. The geometry of the receiver has a large impact on the amount of emitted power which reached the interior surface of the window, and using a conical shaped receiver dramatically reduced the receiver's infrared flux on the window. The importance of internal emission is explored within this research. Internal emission produces a mo
Park, H.; Densmore, J. D.; Wollaber, A. B.; Knoll, D. A.; Rauenzahn, R. M.
2013-07-01
We have developed a moment-based scale-bridging algorithm for thermal radiative transfer problems. The algorithm takes the form of well-known nonlinear-diffusion acceleration which utilizes a low-order (LO) continuum problem to accelerate the solution of a high-order (HO) kinetic problem. The coupled nonlinear equations that form the LO problem are efficiently solved using a preconditioned Jacobian-free Newton-Krylov method. This work demonstrates the applicability of the scale-bridging algorithm with a Monte Carlo HO solver and reports the computational efficiency of the algorithm in comparison to the well-known Fleck-Cummings algorithm. (authors)
A study of the fluctuations of the optical properties of a turbid media through Monte Carlo method
Terán-Bobadilla, Emiliano
2015-01-01
In this work we present a theoretical study on the propagation of light in heterogeneous systems with fluctuating optical properties. To understand the consequences of the fluctuations we perform numerical calculations with uniform and non uniforms systems using Monte Carlo simulations. We consider two distributions to represent a non-uniform medium: delta function and an exponential negative distributions.The results show that even with finite moments distributions, may require a large number of interactions for a convergence towards Gaussian statistics. This can be important when estimating the optical properties of thin films.
Beake, E O R; Dove, M T; Phillips, A E; Keen, D A; Tucker, M G; Goodwin, A L; Bennett, T D; Cheetham, A K
2013-10-01
The zeolitic imidazolate framework ZIF-4 undergoes an amorphization transition at about 600 K, and then transforms at about 700 K to ZIF-zni, the densest of the crystalline ZIFs. This series of long-range structural rearrangements must give a corresponding series of changes in the local structure, but these have not previously been directly investigated. Through analysis of neutron total diffraction data by reverse Monte Carlo modelling, we assess the changes in flexibility across this series, identifying the key modes of flexibility within ZIF-4 and the amorphous phase. We show that the ZnN4 tetrahedra remain relatively rigid, albeit less so than SiO4 tetrahedra in silicates. However, the extra degrees of freedom afforded by the imidazolate ligand, compared to silicate networks, vary substantially between phases, with a twisting motion out of the plane of the ligand being particularly important in the amorphous phase. Our results further demonstrate the feasibility of reverse Monte Carlo simulations for studying intermolecular interactions in solids, even in cases, such as the ZIFs, where the pair distribution function is dominated by intramolecular peaks. PMID:24002115
NASA Astrophysics Data System (ADS)
Beake, E. O. R.; Dove, M. T.; Phillips, A. E.; Keen, D. A.; Tucker, M. G.; Goodwin, A. L.; Bennett, T. D.; Cheetham, A. K.
2013-10-01
The zeolitic imidazolate framework ZIF-4 undergoes an amorphization transition at about 600 K, and then transforms at about 700 K to ZIF-zni, the densest of the crystalline ZIFs. This series of long-range structural rearrangements must give a corresponding series of changes in the local structure, but these have not previously been directly investigated. Through analysis of neutron total diffraction data by reverse Monte Carlo modelling, we assess the changes in flexibility across this series, identifying the key modes of flexibility within ZIF-4 and the amorphous phase. We show that the ZnN4 tetrahedra remain relatively rigid, albeit less so than SiO4 tetrahedra in silicates. However, the extra degrees of freedom afforded by the imidazolate ligand, compared to silicate networks, vary substantially between phases, with a twisting motion out of the plane of the ligand being particularly important in the amorphous phase. Our results further demonstrate the feasibility of reverse Monte Carlo simulations for studying intermolecular interactions in solids, even in cases, such as the ZIFs, where the pair distribution function is dominated by intramolecular peaks.
NASA Astrophysics Data System (ADS)
Haryanto, Freddy
2010-06-01
In medical linear accelerator, the energy parameter of electron plays important role to produce electron beam. The percentage depth dose of electron beams takes account not only on the value of electron's energy, but also on the type of electron's energy. The aims of this work are to carry on the effect of energy parameter of electron on the percentage depth dose of electron beam. Monte Carlo method is chosen in this project, due to the superior of this method for simulating the random process such as the transport particle in matter. The DOSXYZnrc usercode was used to simulate the electron transport in water phantom. Two aspects of electron's energy parameter were investigated using Monte Carlo simulations. In the first aspect, electron energy's value was varied also its spectrum. In the second aspect, the geometry of electron's energy was taken account on. The parallel beam and the point source were chosen as the geometry of The measurements of percentage depth dose were conducted to compare with its simulation. The ionization chamber was used in these measurements. Presentation of the results of this work is given not only based on the shape of the percentage depth dose from the simulation and measurement, but also on the other aspect in its curve. The result of comparison between the simulation and its measurement shows that the shape of its curve depends on the energy value of electron and the type of its energy. The energy value of electron affected the depth maximum of dose.
1-D EQUILIBRIUM DISCRETE DIFFUSION MONTE CARLO
T. EVANS; ET AL
2000-08-01
We present a new hybrid Monte Carlo method for 1-D equilibrium diffusion problems in which the radiation field coexists with matter in local thermodynamic equilibrium. This method, the Equilibrium Discrete Diffusion Monte Carlo (EqDDMC) method, combines Monte Carlo particles with spatially discrete diffusion solutions. We verify the EqDDMC method with computational results from three slab problems. The EqDDMC method represents an incremental step toward applying this hybrid methodology to non-equilibrium diffusion, where it could be simultaneously coupled to Monte Carlo transport.
NASA Astrophysics Data System (ADS)
Kai, Takeshi; Yokoya, Akinari; Ukai, Masatoshi; Fujii, Kentaro; Watanabe, Ritsuko
2015-10-01
The thermalization length and spatial distribution of electrons in liquid water were simulated for initial electron energies ranging from 0.1 eV to 100 keV using a dynamic Monte Carlo code. The results showed that electrons were decelerated for thermalization over a longer time period than was previously predicted. This long thermalization time significantly contributed to the series of processes from initial ionization to hydration. We further studied the particular deceleration process of electrons at an incident energy of 1 eV, focusing on the temporal evolution of total track length, mean traveling distance, and energy distributions of decelerating electrons. The initial prehydration time and thermalization periods were estimated to be approximately 50 and 220 fs, respectively, indicating that the initial prehydration began before or contemporaneously with the thermal equilibrium. Based on these results, the prehydrated electrons were suggested to play an important role during multiple DNA damage induction.
NASA Astrophysics Data System (ADS)
Matheson, Bruce; Hueser, Joseph
2008-08-01
The Direct Simulation Monte Carlo (DSMC) Analysis Code (DAC), as released by NASA, is a general purpose, gas dynamic, transport analysis suite of codes. These codes have been acquired by Ball Aerospace & Technologies Corp. (BATC) through a software usage agreement and have been modified to do a more detailed analysis of contaminant molecular transport of spacecraft and spacecraft instruments over mission lifetimes, typically 5 to 7 years. This transport model takes advantage of the proven algorithms within DAC to handle complex surface geometries and time-dependant gas dynamics. Additions to the code include diffusion of contaminants through solid surfaces, temperature and coverage-dependant adsorption/desorption for the contaminants being modeled, and input data for molecular diameters, molecular weights, and diffusion parameters for the common contaminants found in spacecraft materials and coatings.
NASA Astrophysics Data System (ADS)
Ustinov, E. A.; Do, D. D.
2012-04-01
We present results of application of the kinetic Monte Carlo technique to simulate argon adsorption on a graphite surface at temperatures below and above the triple point. We show that below the triple point the densification of the adsorbed layer with loading results in the rearrangement of molecules to form a hexagonal structure, which is accompanied by the release of an additional heat, associated with this disorder-order transition. This appears as a spike in the plot of the heat of adsorption versus loading at the completion of a monolayer on the surface. To describe the details of the adsorbed phase, we analyzed thermodynamic properties and the effects of temperature on the order-disorder transition of the first layer.
NASA Astrophysics Data System (ADS)
Truchet, G.; Leconte, P.; Peneliau, Y.; Santamarina, A.; Malvagi, F.
2014-06-01
Pile-oscillation experiments are performed in the MINERVE reactor at the CEA Cadarache to improve nuclear data accuracy. In order to precisely calculate small reactivity variations (<10 pcm) obtained in these experiments, a reference calculation need to be achieved. This calculation may be accomplished using the continuous-energy Monte Carlo code TRIPOLI-4® by using the eigenvalue difference method. This "direct" method has shown limitations in the evaluation of very small reactivity effects because it needs to reach a very small variance associated to the reactivity in both states. To answer this problem, it has been decided to implement the exact perturbation theory in TRIPOLI-4® and, consequently, to calculate a continuous-energy adjoint flux. The Iterated Fission Probability (IFP) method was chosen because it has shown great results in some other Monte Carlo codes. The IFP method uses a forward calculation to compute the adjoint flux, and consequently, it does not rely on complex code modifications but on the physical definition of the adjoint flux as a phase-space neutron importance. In the first part of this paper, the IFP method implemented in TRIPOLI-4® is described. To illustrate the effciency of the method, several adjoint fluxes are calculated and compared with their equivalent obtained by the deterministic code APOLLO-2. The new implementation can calculate angular adjoint flux. In the second part, a procedure to carry out an exact perturbation calculation is described. A single cell benchmark has been used to test the accuracy of the method, compared with the "direct" estimation of the perturbation. Once again the method based on the IFP shows good agreement for a calculation time far more inferior to the "direct" method. The main advantage of the method is that the relative accuracy of the reactivity variation does not depend on the magnitude of the variation itself, which allows us to calculate very small reactivity perturbations with high precision. Other applications of this perturbation method are presented and tested like the calculation of exact kinetic parameters (?eff, ?eff) or sensitivity parameters.
NASA Astrophysics Data System (ADS)
Ilas, Germina
In the first part, an accurate and fast computational method is presented as an alternative to the Monte Carlo or deterministic transport theory codes currently used to determine the subcriticality of spent fuel storage lattices. The method is capable of analyzing storage configurations with simple or complex lattice cell geometry. It is developed based on two-group nodal diffusion theory, with the nodal cross sections and discontinuity factors determined from continuous-energy Monte Carlo simulations of each unique node (spent fuel assembly type). Three different approaches are developed to estimate the node-averaged diffusion coefficient. The applicability and the accuracy of the nodal method are assessed in two-dimensional geometry through several benchmark configurations typical at Savannah River Site. It is shown that the multiplication constant of the analyzed configurations is within 1% of the MCNP results. In the second part, the high-order cross section homogenization method, recently developed by McKinley and Rahnema, is implemented in the context of two-group nodal diffusion theory. The method corrects the generalized equivalence theory homogenization parameters for the effect of the core environment. The reconstructed fine-mesh (fuel pin) flux and power distributions are a natural byproduct of this method. The method was not tested for multigroup problems, where it was assumed that the multigroup flux expansion in terms of the perturbation parameter is a convergent series. Here the applicability of the method to two-group problems is studied, and it is shown that the perturbation expansion series converges for the multigroup case. A two-group nodal diffusion code with a bilinear intra-nodal flux shape is developed for the implementation of the high-order homogenization method in the context of the generalized equivalence theory. The method is tested by using as a benchmark a core configuration typical of a BWR in slab geometry, which has large variations in the flux distribution across the core. There is a very good agreement between the nodal calculation and the fine-mesh reference calculation: the node-integrated group flux is within 0.5% of the reference solution in all nodes. The reconstructed fine-mesh flux (or equivalently the power distribution) in the core approximates the reference value very well.
NASA Astrophysics Data System (ADS)
Cortés-Giraldo, M. A.; Carabe, A.
2015-04-01
We compare unrestricted dose average linear energy transfer (LET) maps calculated with three different Monte Carlo scoring methods in voxelized geometries irradiated with proton therapy beams with three different Monte Carlo scoring methods. Simulations were done with the Geant4 (Geometry ANd Tracking) toolkit. The first method corresponds to a step-by-step computation of LET which has been reported previously in the literature. We found that this scoring strategy is influenced by spurious high LET components, which relative contribution in the dose average LET calculations significantly increases as the voxel size becomes smaller. Dose average LET values calculated for primary protons in water with voxel size of 0.2?mm were a factor ~1.8 higher than those obtained with a size of 2.0?mm at the plateau region for a 160?MeV beam. Such high LET components are a consequence of proton steps in which the condensed-history algorithm determines an energy transfer to an electron of the material close to the maximum value, while the step length remains limited due to voxel boundary crossing. Two alternative methods were derived to overcome this problem. The second scores LET along the entire path described by each proton within the voxel. The third followed the same approach of the first method, but the LET was evaluated at each step from stopping power tables according to the proton kinetic energy value. We carried out microdosimetry calculations with the aim of deriving reference dose average LET values from microdosimetric quantities. Significant differences between the methods were reported either with pristine or spread-out Bragg peaks (SOBPs). The first method reported values systematically higher than the other two at depths proximal to SOBP by about 15% for a 5.9?cm wide SOBP and about 30% for a 11.0?cm one. At distal SOBP, the second method gave values about 15% lower than the others. Overall, we found that the third method gave the most consistent performance since it returned stable dose average LET values against simulation parameter changes and gave the best agreement with dose average LET estimations from microdosimetry calculations.
Cortés-Giraldo, M A; Carabe, A
2015-04-01
We compare unrestricted dose average linear energy transfer (LET) maps calculated with three different Monte Carlo scoring methods in voxelized geometries irradiated with proton therapy beams with three different Monte Carlo scoring methods. Simulations were done with the Geant4 (Geometry ANd Tracking) toolkit. The first method corresponds to a step-by-step computation of LET which has been reported previously in the literature. We found that this scoring strategy is influenced by spurious high LET components, which relative contribution in the dose average LET calculations significantly increases as the voxel size becomes smaller. Dose average LET values calculated for primary protons in water with voxel size of 0.2?mm were a factor ~1.8 higher than those obtained with a size of 2.0?mm at the plateau region for a 160?MeV beam. Such high LET components are a consequence of proton steps in which the condensed-history algorithm determines an energy transfer to an electron of the material close to the maximum value, while the step length remains limited due to voxel boundary crossing. Two alternative methods were derived to overcome this problem. The second scores LET along the entire path described by each proton within the voxel. The third followed the same approach of the first method, but the LET was evaluated at each step from stopping power tables according to the proton kinetic energy value. We carried out microdosimetry calculations with the aim of deriving reference dose average LET values from microdosimetric quantities. Significant differences between the methods were reported either with pristine or spread-out Bragg peaks (SOBPs). The first method reported values systematically higher than the other two at depths proximal to SOBP by about 15% for a 5.9?cm wide SOBP and about 30% for a 11.0?cm one. At distal SOBP, the second method gave values about 15% lower than the others. Overall, we found that the third method gave the most consistent performance since it returned stable dose average LET values against simulation parameter changes and gave the best agreement with dose average LET estimations from microdosimetry calculations. PMID:25768028
NASA Astrophysics Data System (ADS)
Larsson, Anne; Ljungberg, Michael; Jakobson Mo, Susanna; Riklund, Katrine; Johansson, Lennart
2006-11-01
Scatter and septal penetration deteriorate contrast and quantitative accuracy in single photon emission computed tomography (SPECT). In this study four different correction techniques for scatter and septal penetration are evaluated for 123I brain SPECT. One of the methods is a form of model-based compensation which uses the effective source scatter estimation (ESSE) for modelling scatter, and collimator-detector response (CDR) including both geometric and penetration components. The other methods, which operate on the 2D projection images, are convolution scatter subtraction (CSS) and two versions of transmission dependent convolution subtraction (TDCS), one of them proposed by us. This method uses CSS for correction for septal penetration, with a separate kernel, and TDCS for scatter correction. The corrections are evaluated for a dopamine transporter (DAT) study and a study of the regional cerebral blood flow (rCBF), performed with 123I. The images are produced using a recently developed Monte Carlo collimator routine added to the program SIMIND which can include interactions in the collimator. The results show that the method included in the iterative reconstruction is preferable to the other methods and that the new TDCS version gives better results compared with the other 2D methods.
NASA Astrophysics Data System (ADS)
Kurita, Moyuru; Yamaji, Youhei; Morita, Satoshi; Imada, Masatoshi
2015-07-01
We propose an accurate variational Monte Carlo method applicable in the presence of the strong spin-orbit interactions. The algorithm is applicable even in a wider class of Hamiltonians that do not have the spin-rotational symmetry. Our variational wave functions consist of generalized Pfaffian-Slater wave functions that involve mixtures of singlet and triplet Cooper pairs, Jastrow-Gutzwiller-type projections, and quantum number projections. The generalized wave functions allow describing states including a wide class of symmetry-broken states, ranging from magnetic and/or charge ordered states to superconducting states and their fluctuations, on equal footing without any ad hoc ansatz for variational wave functions. We detail our optimization scheme for the generalized Pfaffian-Slater wave functions with complex-number variational parameters. Generalized quantum number projections are also introduced, which imposes the conservation of not only the momentum quantum number but also Wilson loops. As a demonstration of the capability of the present variational Monte Carlo method, the accuracy and efficiency is tested for the Kitaev and Kitaev-Heisenberg models, which lack the SU(2) spin-rotational symmetry except at the Heisenberg limit. The Kitaev model serves as a critical benchmark of the present method: The exact ground state of the model is a typical gapless quantum spin liquid far beyond the reach of simple mean-field wave functions. The newly introduced quantum number projections precisely reproduce the ground state degeneracy of the Kitaev spin liquids, in addition to their ground state energy. An application to a closely related itinerant model described by a multiorbital Hubbard model with the spin-orbit interaction also shows promising benchmark results. The strong-coupling limit of the multiorbital Hubbard model is indeed described by the Kitaev model. Our framework offers accurate solutions for the systems where strong electron correlation and spin-orbit interaction coexist.
Cortes-Giraldo, M A; Carabe-Fernandez, A
2014-06-01
Purpose: To evaluate the differences in dose-averaged linear energy transfer (LETd) maps calculated in water by means of different strategies found in the literature in proton therapy Monte Carlo simulations and to compare their values with dose-mean lineal energy microdosimetry calculations. Methods: The Geant4 toolkit (version 9.6.2) was used. Dose and LETd maps in water were scored for primary protons with cylindrical voxels defined around the beam axis. Three LETd calculation methods were implemented. First, the LETd values were computed by calculating the unrestricted linear energy transfer (LET) associated to each single step weighted by the energy deposition (including delta-rays) along the step. Second, the LETd was obtained for each voxel by computing the LET along all the steps simulated for each proton track within the voxel, weighted by the energy deposition of those steps. Third, the LETd was scored as the quotient between the second momentum of the LET distribution, calculated per proton track, over the first momentum. These calculations were made with various voxel thicknesses (0.2 – 2.0 mm) for a 160 MeV proton beamlet and spread-out Bragg Peaks (SOBP). The dose-mean lineal energy was calculated in a uniformly-irradiated water sphere, 0.005 mm radius. Results: The value of the LETd changed systematically with the voxel thickness due to delta-ray emission and the enlargement of the LET distribution spread, especially at shallow depths. Differences of up to a factor 1.8 were found at the depth of maximum dose, leading to similar differences at the central and distal depths of the SOBPs. The third LETd calculation method gave better agreement with microdosimetry calculations around the Bragg Peak. Conclusion: Significant differences were found between LETd map Monte Carlo calculations due to both the calculation strategy and the voxel thickness used. This could have a significant impact in radiobiologically-optimized proton therapy treatments.
NASA Astrophysics Data System (ADS)
Mazoochi, Alireza; Rahmani, Faezeh; Abbasi Davani, Freydoun; Ghaderi, Ruhollah
2014-11-01
One of the methods for material inspection is the dual-energy X-ray technique. Although this method can be more useful in material distinguishing, but signal's intensities are still dependent on the thicknesses of materials in front of the detector, so the material identification results may be affected. In this paper, the new technique using Composite Simpson numerical method has been introduced for eliminating this conflicting effect which stems from material's thickness in the image. This method has been evaluated for some materials such as aluminum and plastic. Calculations have been performed using MCNP4C code to obtain the received X-ray intensity to the detectors. MATLAB software has been also used for the calculations of removing the effect of thickness and optimizing the system performance. Results have shown good performance in identifying materials independent of their thicknesses. The standard deviation of the R parameter, a common parameter for identification, has been improved from 0.613 to 0.0557 for aluminum and from 0.3043 to 0.0288 for plastic, respectively. This method provides an approximation for the X-ray attenuation at two X-ray energies instead of two energy spectra which greatly improves the material identification.
A. Putze; L. Derome; D. Maurin; L. Perotto; R. Taillet
2009-01-21
Propagation of charged cosmic-rays in the Galaxy depends on the transport parameters, whose number can be large depending on the propagation model under scrutiny. A standard approach for determining these parameters is a manual scan, leading to an inefficient and incomplete coverage of the parameter space. We implement a Markov Chain Monte Carlo (MCMC), which is well suited to multi-parameter determination. Its specificities (burn-in length, acceptance, and correlation length) are discussed in the phenomenologically well-understood Leaky-Box Model. From a technical point of view, a trial function based on binary-space partitioning is found to be extremely efficient, allowing a simultaneous determination of up to nine parameters, including transport and source parameters, such as slope and abundances. Our best-fit model includes both a low energy cut-off and reacceleration, whose values are consistent with those found in diffusion models. A Kolmogorov spectrum for the diffusion slope (delta=1/3) is excluded. The marginalised probability-density function for delta and alpha (the slope of the source spectra) are delta~0.55-0.60 and alpha~2.14-2.17, depending on the dataset used and the number of free parameters in the fit. All source-spectrum parameters (slope and abundances) are positively correlated among themselves and with the reacceleration strength, but are negatively correlated with the other propagation parameters. A forthcoming study will extend our analysis to more physical diffusion models.
Ng, C M
2013-10-01
The development of a population PK/PD model, an essential component for model-based drug development, is both time- and labor-intensive. A graphical-processing unit (GPU) computing technology has been proposed and used to accelerate many scientific computations. The objective of this study was to develop a hybrid GPU-CPU implementation of parallelized Monte Carlo parametric expectation maximization (MCPEM) estimation algorithm for population PK data analysis. A hybrid GPU-CPU implementation of the MCPEM algorithm (MCPEMGPU) and identical algorithm that is designed for the single CPU (MCPEMCPU) were developed using MATLAB in a single computer equipped with dual Xeon 6-Core E5690 CPU and a NVIDIA Tesla C2070 GPU parallel computing card that contained 448 stream processors. Two different PK models with rich/sparse sampling design schemes were used to simulate population data in assessing the performance of MCPEMCPU and MCPEMGPU. Results were analyzed by comparing the parameter estimation and model computation times. Speedup factor was used to assess the relative benefit of parallelized MCPEMGPU over MCPEMCPU in shortening model computation time. The MCPEMGPU consistently achieved shorter computation time than the MCPEMCPU and can offer more than 48-fold speedup using a single GPU card. The novel hybrid GPU-CPU implementation of parallelized MCPEM algorithm developed in this study holds a great promise in serving as the core for the next-generation of modeling software for population PK/PD analysis. PMID:24002801
NASA Astrophysics Data System (ADS)
Brunetti, Antonio; Golosio, Bruno; Melis, Maria Grazia; Mura, Stefania
2015-02-01
X-ray fluorescence (XRF) is a well known nondestructive technique. It is also applied to multilayer characterization, due to its possibility of estimating both composition and thickness of the layers. Several kinds of cultural heritage samples can be considered as a complex multilayer, such as paintings or decorated objects or some types of metallic samples. Furthermore, they often have rough surfaces and this makes a precise determination of the structure and composition harder. The standard quantitative XRF approach does not take into account this aspect. In this paper, we propose a novel approach based on a combined use of X-ray measurements performed with a polychromatic beam and Monte Carlo simulations. All the information contained in an X-ray spectrum is used. This approach allows obtaining a very good estimation of the sample contents both in terms of chemical elements and material thickness, and in this sense, represents an improvement of the possibility of XRF measurements. Some examples will be examined and discussed.
Ganesh, Panchapakesan [ORNL; Kim, Jeongnim [ORNL; Park, Changwon [ORNL; Yoon, Mina [ORNL; Reboredo, Fernando A [ORNL; Kent, Paul R [ORNL
2014-01-01
Highly accurate diffusion quantum Monte Carlo (QMC) studies of the adsorption and diffusion of atomic lithium in AA-stacked graphite are compared with van der Waals-including density functional theory (DFT) calculations. Predicted QMC lattice constants for pure AA graphite agree with experiment. Pure AA-stacked graphite is shown to challenge many van der Waals methods even when they are accurate for conventional AB graphite. Highest overall DFT accuracy, considering pure AA-stacked graphite as well as lithium binding and diffusion, is obtained by the self-consistent van der Waals functional vdW-DF2, although errors in binding energies remain. Empirical approaches based on point charges such as DFT-D are inaccurate unless the local charge transfer is assessed. The results demonstrate that the lithium carbon system requires a simultaneous highly accurate description of both charge transfer and van der Waals interactions, favoring self-consistent approaches.
NASA Astrophysics Data System (ADS)
Martínez, Amalia; Parra-Michel, Jorge; Cordero, Raul; Rayas, J. A.
2011-10-01
Electronic speckle pattern interferometry is a useful technique in the measurement of displacement fields and topography. Traditionally, arrangement with dual collimated illumination to topography measurement is used. In this case, the object analysis is limited to the size of optical collimating lens. In the case of large objects, an optical system with divergent illumination can be used. It is known that displacement fields and the phase are related by the sensitivity vector. At once, to compute the sensitivity vector, illumination sources position and superficial shape need to be considered. The last condition becomes an impediment to surface contouring. In a published work1, a simple iterative algorithm based on the Gauss-Seidel technique is presented to compute contouring measurement. In the present work, the uncertainty associated to the measurement of the topography is calculated by using the Monte Carlo method.
Parent, L; Fielding, A L; Dance, D R; Seco, J; Evans, P M
2007-06-21
For EPID dosimetry, the calibration should ensure that all pixels have a similar response to a given irradiation. A calibration method (MC), using an analytical fit of a Monte Carlo simulated flood field EPID image to correct for the flood field image pixel intensity shape, was proposed. It was compared with the standard flood field calibration (FF), with the use of a water slab placed in the beam to flatten the flood field (WS) and with a multiple field calibration where the EPID was irradiated with a fixed 10x10 field for 16 different positions (MF). The EPID was used in its normal configuration (clinical setup) and with an additional 3 mm copper slab (modified setup). Beam asymmetry measured with a diode array was taken into account in MC and WS methods. For both setups, the MC method provided pixel sensitivity values within 3% of those obtained with the MF and WS methods (mean difference<1%, standard deviation<2%). The difference of pixel sensitivity between MC and FF methods was up to 12.2% (clinical setup) and 11.8% (modified setup). MC calibration provided images of open fields (5x5 to 20x20 cm2) and IMRT fields to within 3% of that obtained with WS and MF calibrations while differences with images calibrated with the FF method for fields larger than 10x10 cm2 were up to 8%. MC, WS and MF methods all provided a major improvement on the FF method. Advantages and drawbacks of each method were reviewed. PMID:17664548
NASA Astrophysics Data System (ADS)
Wilson, Robert H.; Vishwanath, Karthik; Mycek, Mary-Ann
2009-02-01
Monte Carlo (MC) simulations are considered the "gold standard" for mathematical description of photon transport in tissue, but they can require large computation times. Therefore, it is important to develop simple and efficient methods for accelerating MC simulations, especially when a large "library" of related simulations is needed. A semi-analytical method involving MC simulations and a path-integral (PI) based scaling technique generated time-resolved reflectance curves from layered tissue models. First, a zero-absorption MC simulation was run for a tissue model with fixed scattering properties in each layer. Then, a closed-form expression for the average classical path of a photon in tissue was used to determine the percentage of time that the photon spent in each layer, to create a weighted Beer-Lambert factor to scale the time-resolved reflectance of the simulated zero-absorption tissue model. This method is a unique alternative to other scaling techniques in that it does not require the path length or number of collisions of each photon to be stored during the initial simulation. Effects of various layer thicknesses and absorption and scattering coefficients on the accuracy of the method will be discussed.
Barnes, Joshua Edward
Chapter 9 N-Body Methods The Collisionless Boltzmann and Poisson equations can be effectively bodies. 9.1 Numerical Stellar Dynamics Impractically large grids are required to solve the time-dependent 3-D Collisionless Boltzmann Equation by finite-difference methods. N-body simulation is basically
Chen, Jinsong
) developed an integrated method to map occurrence probabilities of different lithofacies and fluid properties. They first defined seismic lithofacies and then used them as the link for tying fluid properties to seismic on the existence of seismic lithofacies and distinction in fluid properties among those facies. The method is site
NASA Astrophysics Data System (ADS)
Bouchard, Hugo; Seuntjens, Jan; Kawrakow, Iwan
2011-04-01
During experimental procedures, an adequate evaluation of all sources of uncertainty is necessary to obtain an overall uncertainty budget. In specific radiation dosimetry applications where a single detector is used, common methods to evaluate uncertainties caused by setup positioning errors are not applicable when the dose gradient is not known a priori. This study describes a method to compute these uncertainties using the Monte Carlo method. A mathematical formalism is developed to calculate unbiased estimates of the uncertainties. The method is implemented in egs_chamber, an EGSnrc-based code that allows for the efficient calculation of detector doses and dose ratios. The correct implementation of the method into the egs_chamber code is validated with an extensive series of tests. The accuracy of the developed mathematical formalism is verified by comparing egs_chamber simulation results to the theoretical expectation in an ideal situation where the uncertainty can be computed analytically. Three examples of uncertainties are considered for realistic models of an Exradin A12 ionization chamber and a PTW 60012 diode, and results are computed for parameters representing nearly realistic positioning error probability distributions. Results of practical examples show that uncertainties caused by positioning errors can be significant during IMRT reference dosimetry as well as small field output factor measurements. The method described in this paper is of interest in the study of single-detector response uncertainties during nonstandard beam measurements, both in the scope of daily routine as well as when developing new dosimetry protocols. It is pointed out that such uncertainties should be considered in new protocols devoted to single-detector measurements in regions with unpredictable dose gradients. The method is available within the egs_chamber code in the latest official release of the EGSnrc system.