APPLICATIONS OF MONTE CARLO METHOD IN SCIENCE AND ENGINEERING Edited by Shlomo Mark and Shaul Mordechai Applications of Monte Carlo Method in Science and Engineering Edited by Shlomo Mark and Shaul Mordechai Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2011 InTech All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Ana Nikolic Technical Editor Teodora Smiljanic Cover Designer Martina Sirotic Image Copyright Qiwen, 2010. Used under license from Shutterstock.com First published February, 2011 Printed in India A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Applications of Monte Carlo Method in Science and Engineering, Edited by Shlomo Mark and Shaul Mordechai p. cm. ISBN 978-953-307-691-1 free online editions of InTech Books and Journals can be found at www.intechopen.com Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Preface XI Monte Carlo Simulations in NDT 1 Frank Sukowski and Norman Uhlmann Application of Monte Carlo Simulation in Optical Tweezers 21 Yu-Xuan Ren, Jian-Guang Wu and Yin-Mei Li Enabling Grids for GATE Monte-Carlo Radiation Therapy Simulations with the GATE-Lab 35 Sorina Camarasu-Pop, Tristan Glatard, Hugues Benoit-Cattin and David Sarrut Monte Carlo Simulation for Ion Implantation Profiles, Amorphous Layer Thickness Formed by the Ion Implantation, and Database Based on Pearson Function 51 Kunihiro Suzuki Application of Monte Carlo Simulation in Industrial Microbiological Exposure Assessment 83 Javier Collado, Antonio Falcó, Dolores Rodrigo, Fernando Sampedro, M. Consuelo Pina and Antonio Martínez Monte Carlo Simulation of Radiative Transfer in Atmospheric Environments for Problems Arising from Remote Sensing Measurements 95 Margherita Premuda Monte Carlo Simulation of Pile-up Effect in Gamma Spectroscopy 125 Ali Asghar Mowlavi, Mario de Denaro and Maria Rosa Fornasier Monte Carlo Simulations of Microchannel Plate–Based, Time-Gated X-ray Imagers 141 Craig A. Kruschwitz and Ming Wu Contents Contents VI Many-particle Monte Carlo Approach to Electron Transport 167 G. Albareda, F. L. Traversa, A. Benali and X. Oriols Monte-Carlo Simulation in Electron Microscopy and Spectroscopy 195 Vladimír Starý Monte Carlo Simulation of SEM and SAM Images 231 Y.G. Li, S.F. Mao and Z.J. Ding Monte Carlo Simulation of Insulating Gas Avalanche Development 297 Dengming Xiao Monte Carlo Simulation of Electron Dynamics in Doped Semiconductors Driven by Electric Fields: Harmonic Generation, Hot-Carrier Noise and Spin Relaxation 331 Dominique Persano Adorno A Pearson Effective Potential for Monte-Carlo Simulation of Quantum Confinement Effects in nMOSFETs 359 Marie-Anne Jaud, Sylvain Barraud, Philippe Dollfus, Jérôme Saint-Martin, Arnaud Bournel and Hervé Jaouen Monte Carlo Device Simulations 385 Dragica Vasileska, Katerina Raleva and Stephen M. Goodnick Wang-Landau Algorithm and its Implementation for the Determination of Joint Density of States in Continuous Spin Models 431 Soumen Kumar Roy, Kisor Mukhopadhyay, Nababrata Ghoshal and Shyamal Bhar Characterizing Molecular Rotations using Monte Carlo Simulations 451 Bart Verberck Finite-time Scaling and its Applications to Continuous Phase Transitions 469 Fan Zhong Using Monte Carlo Method to Study Magnetic Properties of Frozen Ferrofluid 495 Tran Nguyen Lan and Tran Hoang Hai Monte Carlo Studies of Magnetic Nanoparticles 513 K. Trohidou and M. Vasilakaki Chapter 9 Chapter 10 Chapter 11 Chapter 12 Chapter 13 Chapter 14 Chapter 15 Chapter 16 Chapter 17 Chapter 18 Chapter 19 Chapter 20 Contents VII Monte Carlo Simulation for Magnetic Domain Structure and Hysteresis Properties 539 Katsuhiko Yamaguchi, Kenji Suzuki and Osamu Nittono Monte Carlo Simulations of Grain Growth in Polycrystalline Materials Using Potts Model 563 Miroslav Morháč and Eva Morháčová Monte Carlo Simulations of Grain Growth in Metals 581 Sven K. Esche Monte Carlo Simulations on Defects in Hard-Sphere Crystals Under Gravity 611 Atsushi Mori Atomistic Monte Carlo Simulations in Steelmaking: High Temperature Carburization and Decarburization of Molten Steel 629 R. Khanna, R. Mahjoub and V. Sahajwalla GCMC Simulations of Gas Adsorption in Carbon Pore Structures 653 Maria Konstantakou, Anastasios Gotzias, Michael Kainourgiakis, Athanasios K. Stubos and Theodore A. Steriotis Effect of the Repulsive Interactions on the Nucleation and Island Growth: Kinetic Monte Carlo Simulations 677 Hu Juanmei and Wu Fengmin Monte Carlo Methodology for Grand Canonical Simulations of Vacancies at Crystalline Defects 687 Döme Tanguy Frequency-Dependent Monte Carlo Simulations of Phonon Transport in Nanostructures 707 Qing Hao and Gang Chen Performance Analysis of Adaptive GPS Signal Detection in Urban Interference Environment using the Monte Carlo Approach 735 V. Behar, Ch. Kabakchiev, I. Garvanov and H. Rohling Practical Monte Carlo Based Reliability Analysis and Design Methods for Geotechnical Problems 757 Jianye Ching A Monte Carlo Framework to Simulate Multicomponent Droplet Growth by Stochastic Coalescence 781 Lester Alfonso, Graciela Raga and Darrel Baumgardner Chapter 21 Chapter 22 Chapter 23 Chapter 24 Chapter 25 Chapter 26 Chapter 27 Chapter 28 Chapter 29 Chapter 30 Chapter 31 Chapter 32 Contents VIII Monte Carlo Simulation of Room Temperature Ballistic Nanodevices 803 Ignacio Íñiguez-de-la-Torre, Tomás González, Helena Rodilla, Beatriz G. Vasallo and Javier Mateos Estimation of Optical Properties in Postharvest and Processing Technology 829 László Baranyai MATLAB Programming of Polymerization Processes using Monte Carlo Techniques 841 Mamdouh A. Al-Harthi Monte Carlo Simulations in Solar Radio Astronomy 857 G. Thejappa and R. J. MacDowall Using Monte Carlo Simulation for Prediction of Tool Life 881 Sayyad Zahid Qamar, Anwar Khalil Sheikh, Tasneem Pervez and Abul Fazal M. Arif Loss of Load Expectation Assessment in Electricity Markets using Monte Carlo Simulation and Neuro-Fuzzy Systems 901 H. Haroonabadi Automating First- and Second-order Monte Carlo Simulations for Markov Models in TreeAge Pro 917 Benjamin P. Geisler Monte Carlo Simulations of Adsorbed Molecules on Ionic Surfaces 931 Abdulwahab Khalil Sallabi Chapter 33 Chapter 34 Chapter 35 Chapter 36 Chapter 37 Chapter 38 Chapter 39 Chapter 40 [...]... networks, finance and business, engineering, economics, risk analysis, project management, the study of heat transfer, molecular dynamic analysis, environmental sciences, chemistry, telecommunications, engineering, games and so forth In this book, Applications of Monte Carlo Method in Science and Engineering, we further expose the broad range of applications of Monte Carlo simulation in the fields of Quantum... spectrum, over the excitation of the bulk material with the energy distribution and detection of the excited 18 Applications of Monte Carlo Method in Science and Engineering Fig 15 Sketch of the CT simulation setup of an air cargo container with a LINAC as X-ray source and a 5 m detector array rotating around the container Fig 16 Left side: One slice of the air cargo container and its content (ideal simulation)...Preface Monte Carlo simulation, the iterative computational method used to examine and investigate the behavior of physical and mathematical systems utilizing stochastic techniques It is a widely used method and a successful statistical tool in studying a broad array of problems, areas and cases in which it is infeasible or impossible to compute exact results utilizing deterministic algorithms The Monte Carlo. .. al., 2000) 3.1.1 Indirect converting detectors Most flat-panel detectors convert the X-ray energy deposition in an indirect way into an electrical signal The X-ray detection mechanism is based on a scintillator X-rays interacting with a scintillator ionize the atoms, causing emission of fluorescence light due to exited-state 10 Applications of Monte Carlo Method in Science and Engineering deactivation... tools, the rapid growth of computing power and the availability of ever more advanced and powerful hardware, the need for increasingly complex and powerful computational solutions such as Monte Carlo simulation and applications is growing exponentially The utilization of Monte Carlo methods, simulations and applications, is found in widely disparate fields and areas of application such as nuclear physics,... motion equation of the trapped bead is in the scope of Monte Carlo simulation In this chapter, we start with the description of light induced radiation force and review the hydrodynamic equation that describes the Brownian motion of trapped bead in optical tweezers in the second and third part, followed by adoption of Monte Carlo simulation in this specific case In the fourth and fifth parts of this chapter,... energies in contrast to DIC detectors 3.2.1.2 MTF determination For obtaining MTF images, almost the same parameters were used as for BSR images To save simulation time, a smaller area of only 12.8 mm x 12.8 mm (128x128 pixels) was irradiated 14 Applications of Monte Carlo Method in Science and Engineering (a) IDC (b) DIC Fig 11 Images of EN462-5 double wire test pattern Direct converting (DIC) Indirect... during the inspection With this operation it is possible to get images of the Monte Carlo Simulations in NDT 17 specimen with nearly no intensity of scattered radiation resulting in better contrast and higher sharpness of the image In 14 the simulated projection of a step wegde and the simulated intensity distribution of the scattered radiation is shown Simulation is the only way to get a realistic and. .. setup of a transmission target In the simulation a parallel electron beam with electron kinetic energy between 30 and 120 keV was modeled with a gaussian intensity cross-section in both dimensions The FWHM value of the gaussian distribution was 200 nm The first layer material of the transmission target 6 Applications of Monte Carlo Method in Science and Engineering is tungsten Since the X-ray productivity... development of ROSI still goes on to include more detailed effects and simulation possibilities 20 Applications of Monte Carlo Method in Science and Engineering 6 References Nelson W.R.; Rogers D.W.O & Hirayama H (1985) The EGS4 Code System, Stanford Linear Accelerator Report SLAC-265, Stanford, CA 94305 S Agostinelli et al (2003) Geant4 - A Simulation toolkit, Nuclear Instruments and Methods A 506, . APPLICATIONS OF MONTE CARLO METHOD IN SCIENCE AND ENGINEERING Edited by Shlomo Mark and Shaul Mordechai Applications of Monte Carlo Method in Science and Engineering Edited by Shlomo Mark and. engineering, games and so forth. In this book, Applications of Monte Carlo Method in Science and Engineering, we further expose the broad range of applications of Monte Carlo simulation in the. by adjusting the tube voltage and using various prefilters. Figure 1 shows spectra between 30 and 450 kV with several prefilters. 2 Applications of Monte Carlo Method in Science and Engineering Fig. 1.