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Journal articles on the topic 'MONTE-CARLO TRACK STRUCTURE'

Author: Grafiati

Published: 11 March 2023

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1

Toburen, Larry H. "Challenges in Monte Carlo track structure modelling." International Journal of Radiation Biology 88, no. 1-2 (2011): 2–9. http://dx.doi.org/10.3109/09553002.2011.574781.

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2

Douglass, Michael, Scott Penfold, and Eva Bezak. "Preliminary Investigation of Microdosimetric Track Structure Physics Models in Geant4-DNA and RITRACKS." Computational and Mathematical Methods in Medicine 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/968429.

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The major differences between the physics models in Geant4-DNA and RITRACKS Monte Carlo packages are investigated. Proton and electron ionisation interactions and electron excitation interactions in water are investigated in the current work. While these packages use similar semiempirical physics models for inelastic cross-sections, the implementation of these models is demonstrated to be significantly different. This is demonstrated in a simple Monte Carlo simulation designed to identify differences in interaction cross-sections.

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3

Endo, S., E. Yoshida, H. Nikjoo, et al. "A Monte Carlo track structure code for low energy protons." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 194, no. 2 (2002): 123–31. http://dx.doi.org/10.1016/s0168-583x(02)00497-4.

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4

Pater, Piotr, Jan Seuntjens, Issam El Naqa, and Mario A. Bernal. "On the consistency of Monte Carlo track structure DNA damage simulations." Medical Physics 41, no. 12 (2014): 121708. http://dx.doi.org/10.1118/1.4901555.

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5

Díaz-Díaz, Jorge A., Eugenio Torres-García, Rigoberto Oros-Pantoja, Liliana Aranda Lara, and Patricia Vieyra-Reyes. "New track-structure Monte Carlo code for 4D ionizing photon transport." Radiation Effects and Defects in Solids 173, no. 7-8 (2018): 567–77. http://dx.doi.org/10.1080/10420150.2018.1484744.

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6

Pasciak, A. S., and J. R. Ford. "High-speed evaluation of track-structure Monte Carlo electron transport simulations." Physics in Medicine and Biology 53, no. 19 (2008): 5539–53. http://dx.doi.org/10.1088/0031-9155/53/19/018.

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7

Emfietzoglou, D., A. Akkerman, and J. Barak. "New Monte Carlo calculations of charged particle track-structure in silicon." IEEE Transactions on Nuclear Science 51, no. 5 (2004): 2872–79. http://dx.doi.org/10.1109/tns.2004.835061.

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8

Nikjoo, H., P. O'Neill, M. Terrissol, and D. T. Goodhead. "Quantitative modelling of DNA damage using Monte Carlo track structure method." Radiation and Environmental Biophysics 38, no. 1 (1999): 31–38. http://dx.doi.org/10.1007/s004110050135.

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9

Sattinger, D., and Y. S. Horowitz. "Track structure calculations in LiF:Mg,Ti: A Monte Carlo study of the ‘track escape’ parameter." Radiation Measurements 43, no. 2-6 (2008): 185–89. http://dx.doi.org/10.1016/j.radmeas.2007.12.024.

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10

Uehara, Shuzo, and Hooshang Nikjoo. "Monte Carlo Track Structure Code for Low-Energy Alpha-Particles in Water." Journal of Physical Chemistry B 106, no. 42 (2002): 11051–63. http://dx.doi.org/10.1021/jp014004h.

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11

Quiroga, L. M., and E. Schnieder. "Monte Carlo simulation of railway track geometry deterioration and restoration." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 226, no. 3 (2011): 274–82. http://dx.doi.org/10.1177/1748006x11418422.

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Travelling safely and comfortably on high-speed railway lines requires excellent conditions of the whole railway infrastructure in general and of the railway track geometry in particular. The maintenance process required to achieve such excellent conditions is complex and expensive, demanding a large amount of both human and technical resources. In this framework, choosing the right maintenance strategy becomes a critical issue. A reliable simulation of the railway geometry ageing process would offer a great advantage for the optimization of planning and scheduling of maintenance activities. A

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12

Podwórna, M. "Modelling Of Random Vertical Irregularities Of Railway Tracks." International Journal of Applied Mechanics and Engineering 20, no. 3 (2015): 647–55. http://dx.doi.org/10.1515/ijame-2015-0043.

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Abstract The study presents state-of-the-art in analytical and numerical modelling of random vertical irregularities of continuously welded ballasted railway tracks. The common model of railway track irregularity vertical profiles is applied, in the form of a stationary and ergodic Gaussian process in space. Random samples of track irregularity vertical profiles are generated with the Monte-Carlo method. Based on the numerical method developed in the study, the minimum and recommended sampling number required in the random analysis of railway bridges and number of frequency increments (harmoni

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13

Champion, Christophe, Mouhamad Elbast, Ting-Di Wu, and Nicole Colas-Linhart. "Thyroid cell irradiation by radioiodines: a new Monte Carlo electron track-structure code." Brazilian Archives of Biology and Technology 50, spe (2007): 135–44. http://dx.doi.org/10.1590/s1516-89132007000600017.

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The most significant impact of the Chernobyl accident is the increased incidence of thyroid cancer among children who were exposed to short-lived radioiodines and 131-iodine. In order to accurately estimate the radiation dose provided by these radioiodines, it is necessary to know where iodine is incorporated. To do that, the distribution at the cellular level of newly organified iodine in the immature rat thyroid was performed using secondary ion mass microscopy (NanoSIMS50). Actual dosimetric models take only into account the averaged energy and range of beta particles of the radio-elements

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14

Hilgers, G., M. U. Bug, E. Gargioni, and H. Rabus. "Comparison of measured and Monte Carlo simulated track structure parameters in nanometric volumes." Radiation Protection Dosimetry 161, no. 1-4 (2013): 441–44. http://dx.doi.org/10.1093/rpd/nct265.

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15

Uehara, Shuzo, Hooshang Nikjoo, and Dudley T. Goodhead. "Comparison and Assessment of Electron Cross Sections for Monte Carlo Track Structure Codes." Radiation Research 152, no. 2 (1999): 202. http://dx.doi.org/10.2307/3580095.

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16

Vandoorne, Rick, and Petrus J. Gräbe. "Stochastic rail life cycle cost maintenance modelling using Monte Carlo simulation." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 232, no. 4 (2017): 1240–51. http://dx.doi.org/10.1177/0954409717714645.

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The need for decision support systems to guide maintenance and renewal decisions for infrastructure is growing due to tighter budget requirements and the concurrent need to satisfy reliability, availability and safety requirements. The rail of the railway track is one of the most important components of the entire track structure and can significantly influence maintenance costs throughout the life cycle of the track. Estimation of life cycle cost is a popular decision support system. A calculated life cycle cost has inherent uncertainty associated with the reliability of the input data used i

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17

Liamsuwan, T., S. Uehara, and H. Nikjoo. "Microdosimetry of the full slowing down of protons using Monte Carlo track structure simulations." Radiation Protection Dosimetry 166, no. 1-4 (2015): 29–33. http://dx.doi.org/10.1093/rpd/ncv204.

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18

Tajik-Mansoury, M. A., H. Rajabi, and H. Mozdarani. "A comparison between track-structure, condensed-history Monte Carlo simulations and MIRD cellularS-values." Physics in Medicine and Biology 62, no. 5 (2017): N90—N106. http://dx.doi.org/10.1088/1361-6560/62/5/n90.

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19

Champion, C., A. L'Hoir, M. F. Politis, A. Chetioui, B. Fayard, and A. Touati. "Monte-Carlo simulation of ion track structure in water: ionization clusters and biological effectiveness." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 146, no. 1-4 (1998): 533–40. http://dx.doi.org/10.1016/s0168-583x(98)00438-8.

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20

Uehara, S., L. H. Toburen, and H. Nikjoo. "Development of a Monte Carlo track structure code for low-energy protons in water." International Journal of Radiation Biology 77, no. 2 (2001): 139–54. http://dx.doi.org/10.1080/09553000010012536.

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21

Champion, C., and C. Le Loirec. "Positron follow-up in liquid water: I. A new Monte Carlo track-structure code." Physics in Medicine and Biology 51, no. 7 (2006): 1707–23. http://dx.doi.org/10.1088/0031-9155/51/7/005.

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22

Batmunkh, Munkhbaatar, Lkhagvaa Bayarchimeg, Aleksandr N. Bugay, and Oidov Lkhagva. "Monte Carlo track structure simulation in studies of biological effects induced by accelerated charged particles in the central nervous system." EPJ Web of Conferences 204 (2019): 04008. http://dx.doi.org/10.1051/epjconf/201920404008.

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Simulating the biological damage induced by charged particles trajectories (tracks) in the central nervous system (CNS) at different levels of its organization (molecular, cellular, and tissue) is a challenge of modern radiobiology studies. According to the recent experimental studies at particle accelerators, the most radiation-sensitive area of the CNS is the hippocampus. In this regards, the development of measurement-based Monte Carlo simulation of radiation-induced alterations in the hippocampus is of great interest to understand the radiobiological effects on the CNS. The present work in

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23

Francis, Z., S. Incerti, R. Capra, et al. "Molecular scale track structure simulations in liquid water using the Geant4-DNA Monte-Carlo processes." Applied Radiation and Isotopes 69, no. 1 (2011): 220–26. http://dx.doi.org/10.1016/j.apradiso.2010.08.011.

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24

Nikjoo, H., D. E. Charlton, and D. T. Goodhead. "Monte Carlo track structure studies of energy deposition and calculation of initial DSB and RBE." Advances in Space Research 14, no. 10 (1994): 161–80. http://dx.doi.org/10.1016/0273-1177(94)90466-9.

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25

Champion, Christophe. "Moving from organ dose to microdosimetry: contribution of the Monte Carlo simulations." Brazilian Archives of Biology and Technology 48, spe2 (2005): 191–99. http://dx.doi.org/10.1590/s1516-89132005000700029.

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When living cells are irradiated by charged particles, a wide variety of interactions occurs that leads to a deep modification of the biological material. To understand the fine structure of the microscopic distribution of the energy deposits, Monte Carlo event-by-event simulations are particularly suitable. However, the development of these track structure codes needs accurate interaction cross sections for all the electronic processes: ionization, excitation, Positronium formation (for incident positrons) and even elastic scattering. Under these conditions, we have recently developed a Monte

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26

Batmunkh, Munkhbaatar, Alexander Bugay, Lkhagvaa Bayarchimeg, and Oidov Lkhagva. "Radiation Damage to Nervous System: Designing Optimal Models for Realistic Neuron Morphology in Hippocampus." EPJ Web of Conferences 173 (2018): 05004. http://dx.doi.org/10.1051/epjconf/201817305004.

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The present study is focused on the development of optimal models of neuron morphology for Monte Carlo microdosimetry simulations of initial radiation-induced events of heavy charged particles in the specific types of cells of the hippocampus, which is the most radiation-sensitive structure of the central nervous system. The neuron geometry and particles track structures were simulated by the Geant4/Geant4-DNA Monte Carlo toolkits. The calculations were made for beams of protons and heavy ions with different energies and doses corresponding to real fluxes of galactic cosmic rays. A simple comp

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27

Wang, Xiu Fang, Jin Ye Peng, Bin Chen, and Wei Qi. "Tracking Algorithm Design and Comparison of High Speed High Maneuvering Target." Applied Mechanics and Materials 713-715 (January 2015): 2053–57. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.2053.

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Aiming at the problem that the traditional tracking method cannot track high speed high maneuvering target effectively, one modified fixed structure multiple model algorithm (M-FSMM) and one modified variable structure multiple model (M-VSMM) algorithm were proposed. The Constant Velocity (CV) model, Current Statistical (CS) and Modified Coordinate Turn (MCT) model were adopted in the M-FSMM algorithm, by means of Connected Graph (CG) thinking, the model connected graph was made up by models that can describe possible motion, the connected relation was set up and model self-adapting was design

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28

Nikjoo, Hooshang, Dimitris Emfietzoglou, Ritsuko Watanabe, and Shuzo Uehara. "Can Monte Carlo track structure codes reveal reaction mechanism in DNA damage and improve radiation therapy?" Radiation Physics and Chemistry 77, no. 10-12 (2008): 1270–79. http://dx.doi.org/10.1016/j.radphyschem.2008.05.043.

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29

Watanabe, Ritsuko, Shirin Rahmanian, and Hooshang Nikjoo. "Spectrum of Radiation-Induced Clustered Non-DSB Damage – A Monte Carlo Track Structure Modeling and Calculations." Radiation Research 183, no. 5 (2015): 525–40. http://dx.doi.org/10.1667/rr13902.1.

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30

Emfietzoglou, Dimitris, George Papamichael, and Hooshang Nikjoo. "Monte Carlo Electron Track Structure Calculations in Liquid Water Using a New Model Dielectric Response Function." Radiation Research 188, no. 3 (2017): 355–68. http://dx.doi.org/10.1667/rr14705.1.

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31

Zhao, X. F., and S. X. Huang. "Using particle filter to track horizontal variations of atmospheric duct structure from radar sea clutter." Atmospheric Measurement Techniques Discussions 5, no. 4 (2012): 6059–82. http://dx.doi.org/10.5194/amtd-5-6059-2012.

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Abstract. This paper addresses the problem of estimating range-varying parameters of the height-dependent refractivity over the sea surface from radar sea clutter. In the forward simulation, the split-step Fourier parabolic equation (PE) is used to compute the radar clutter power in the complex refractive environments. Making use of the inherent Markovian structure of the split-step Fourier PE solution, the refractivity from clutter (RFC) problem is formulated within a nonlinear recursive Bayesian state estimation framework. Particle filter (PF) that is a technique for implementing a recursive

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32

Zhao, X. F., S. X. Huang, and D. X. Wang. "Using particle filter to track horizontal variations of atmospheric duct structure from radar sea clutter." Atmospheric Measurement Techniques 5, no. 11 (2012): 2859–66. http://dx.doi.org/10.5194/amt-5-2859-2012.

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Abstract. This paper addresses the problem of estimating range-varying parameters of the height-dependent refractivity over the sea surface from radar sea clutter. In the forward simulation, the split-step Fourier parabolic equation (PE) is used to compute the radar clutter power in the complex refractive environments. Making use of the inherent Markovian structure of the split-step Fourier PE solution, the refractivity from clutter (RFC) problem is formulated within a nonlinear recursive Bayesian state estimation framework. Particle filter (PF), which is a technique for implementing a recursi

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33

Lazarakis, P., M. U. Bug, E. Gargioni, S. Guatelli, H. Rabus, and A. B. Rosenfeld. "Comparison of nanodosimetric parameters of track structure calculated by the Monte Carlo codes Geant4-DNA and PTra." Physics in Medicine and Biology 57, no. 5 (2012): 1231–50. http://dx.doi.org/10.1088/0031-9155/57/5/1231.

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34

Bug, M. U., E. Gargioni, S. Guatelli, et al. "Effect of a magnetic field on the track structure of low-energy electrons: a Monte Carlo study." European Physical Journal D 60, no. 1 (2010): 85–92. http://dx.doi.org/10.1140/epjd/e2010-00145-1.

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35

Hu, Ankang, Wanyi Zhou, Zhen Wu, Hui Zhang, Junli Li, and Rui Qiu. "Modeling of DNA Damage Repair and Cell Response in Relation to p53 System Exposed to Ionizing Radiation." International Journal of Molecular Sciences 23, no. 19 (2022): 11323. http://dx.doi.org/10.3390/ijms231911323.

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Repair of DNA damage induced by ionizing radiation plays an important role in the cell response to ionizing radiation. Radiation-induced DNA damage also activates the p53 system, which determines the fate of cells. The kinetics of repair, which is affected by the cell itself and the complexity of DNA damage, influences the cell response and fate via affecting the p53 system. To mechanistically study the influences of the cell response to different LET radiations, we introduce a new repair module and a p53 system model with NASIC, a Monte Carlo track structure code. The factors determining the

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36

Ali, Yasmine, Caterina Monini, Etienne Russeil, et al. "Estimate of the Biological Dose in Hadrontherapy Using GATE." Cancers 14, no. 7 (2022): 1667. http://dx.doi.org/10.3390/cancers14071667.

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For the evaluation of the biological effects, Monte Carlo toolkits were used to provide an RBE-weighted dose using databases of survival fraction coefficients predicted through biophysical models. Biophysics models, such as the mMKM and NanOx models, have previously been developed to estimate a biological dose. Using the mMKM model, we calculated the saturation corrected dose mean specific energy z1D* (Gy) and the dose at 10% D10 for human salivary gland (HSG) cells using Monte Carlo Track Structure codes LPCHEM and Geant4-DNA, and compared these with data from the literature for monoenergetic

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37

Derksen, Larissa, Tabea Pfuhl, Rita Engenhart-Cabillic, Klemens Zink, and Kilian-Simon Baumann. "Investigating the feasibility of TOPAS-nBio for Monte Carlo track structure simulations by adapting GEANT4-DNA examples application." Physics in Medicine & Biology 66, no. 17 (2021): 175023. http://dx.doi.org/10.1088/1361-6560/ac1d21.

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38

Bug, M. U., H. Rabus, and A. B. Rosenfeld. "Electron emission from amorphous solid water after proton impact: Benchmarking PTra and Geant4 track structure Monte Carlo simulations." Radiation Physics and Chemistry 81, no. 12 (2012): 1804–12. http://dx.doi.org/10.1016/j.radphyschem.2012.07.006.

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39

Thibaut, Yann, Nicolas Tang, Hoang Ngoc Tran, et al. "Nanodosimetric Calculations of Radiation-Induced DNA Damage in a New Nucleus Geometrical Model Based on the Isochore Theory." International Journal of Molecular Sciences 23, no. 7 (2022): 3770. http://dx.doi.org/10.3390/ijms23073770.

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Double-strand breaks (DSBs) in nuclear DNA represents radiation-induced damage that has been identified as particularly deleterious. Calculating this damage using Monte Carlo track structure modeling could be a suitable indicator to better assess and anticipate the side-effects of radiation therapy. However, as already demonstrated in previous work, the geometrical description of the nucleus and the DNA content used in the simulation significantly influence damage calculations. Therefore, in order to obtain accurate results, this geometry must be as realistic as possible. In this study, a new

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40

Rymzhanov, R. A. "ELECTRON KINETICS OF YTTRIUM IRON GARNET AFTER SWIFT HEAVY ION IMPACT." Eurasian Physical Technical Journal 19, no. 3 (41) (2022): 23–28. http://dx.doi.org/10.31489/2022no3/23-28.

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The TREKIS Monte-Carlo model was applied to study the temporal electronic kinetics of yttrium iron garnet after a swift heavy ion impact. Cross sections of incident particles interaction with the target were determined within complex dielectric function-dynamic structure factor formalism. We found two modes of the spatial propagation of electronic excitation: fast delta-electrons form a front of the excitation while electrons produced due to decay of plasmons generated in a track form the second front slowly following behind the first one.Analysis of mechanisms of target lattice heating pointe

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41

Rucinski, Antoni, Anna Biernacka, and Reinhard Schulte. "Applications of nanodosimetry in particle therapy planning and beyond." Physics in Medicine & Biology 66, no. 24 (2021): 24TR01. http://dx.doi.org/10.1088/1361-6560/ac35f1.

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Abstract This topical review summarizes underlying concepts of nanodosimetry. It describes the development and current status of nanodosimetric detector technology. It also gives an overview of Monte Carlo track structure simulations that can provide nanodosimetric parameters for treatment planning of proton and ion therapy. Classical and modern radiobiological assays that can be used to demonstrate the relationship between the frequency and complexity of DNA lesion clusters and nanodosimetric parameters are reviewed. At the end of the review, existing approaches of treatment planning based on

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42

Uehara, S., H. Nikjoo, and D. T. Goodhead. "Cross-sections for water vapour for the Monte Carlo electron track structure code from 10 eV to the MeV region." Physics in Medicine and Biology 38, no. 12 (1993): 1841–58. http://dx.doi.org/10.1088/0031-9155/38/12/010.

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43

Matsuya, Yusuke, Takeshi Kai, Yuji Yoshii, et al. "Modeling of yield estimation for DNA strand breaks based on Monte Carlo simulations of electron track structure in liquid water." Journal of Applied Physics 126, no. 12 (2019): 124701. http://dx.doi.org/10.1063/1.5115519.

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44

Lucido, J., I. Popescu, and V. Moiseenko. "SU-E-T-81: Comparison of Microdosimetric Quantities Calculated Using the Track Structure Monte Carlo Algorithms Geant4-DNA and NOREC." Medical Physics 41, no. 6Part12 (2014): 240. http://dx.doi.org/10.1118/1.4888411.

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45

Boscolo, Daria, Michael Krämer, Martina C. Fuss, Marco Durante, and Emanuele Scifoni. "Impact of Target Oxygenation on the Chemical Track Evolution of Ion and Electron Radiation." International Journal of Molecular Sciences 21, no. 2 (2020): 424. http://dx.doi.org/10.3390/ijms21020424.

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The radiosensitivity of biological systems is strongly affected by the system oxygenation. On the nanoscopic scale and molecular level, this effect is considered to be strongly related to the indirect damage of radiation. Even though particle track radiolysis has been the object of several studies, still little is known about the nanoscopic impact of target oxygenation on the radical yields. Here we present an extension of the chemical module of the Monte Carlo particle track structure code TRAX, taking into account the presence of dissolved molecular oxygen in the target material. The impact

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46

Thompson, Shannon J., Aoife Rooney, Kevin M. Prise, and Stephen J. McMahon. "Evaluating Iodine-125 DNA Damage Benchmarks of Monte Carlo DNA Damage Models." Cancers 14, no. 3 (2022): 463. http://dx.doi.org/10.3390/cancers14030463.

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A wide range of Monte Carlo models have been applied to predict yields of DNA damage based on nanoscale track structure calculations. While often similar on the macroscopic scale, these models frequently employ different assumptions which lead to significant differences in nanoscale dose deposition. However, the impact of these differences on key biological readouts remains unclear. A major challenge in this area is the lack of robust datasets which can be used to benchmark models, due to a lack of resolution at the base pair level required to deeply test nanoscale dose deposition. Studies inv

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47

Van der Ven, A., J. C. Thomas, B. Puchala, and A. R. Natarajan. "First-Principles Statistical Mechanics of Multicomponent Crystals." Annual Review of Materials Research 48, no. 1 (2018): 27–55. http://dx.doi.org/10.1146/annurev-matsci-070317-124443.

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The importance of configurational, vibrational, and electronic excitations in crystalline solids of technological interest makes a rigorous treatment of thermal excitations an essential ingredient in first-principles models of materials behavior. This contribution reviews statistical mechanics approaches that connect a crystal's electronic structure to its thermodynamic and kinetic properties. We start with a description of a thermodynamic and kinetic framework for multicomponent crystals that integrates chemistry and mechanics, as well as nonconserved order parameters that track the degree of

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48

Hannachi, Essia, M. I. Sayyed, Suhairul Hashim, Karem Mahmoud, and Yassine Slimani. "Theoretical Examination of the Radiation Protecting Properties of CaTiO3 Material Sintered at Different Temperatures." Crystals 13, no. 1 (2023): 120. http://dx.doi.org/10.3390/cryst13010120.

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This research is devoted to studying the radiation-protecting characteristics of calcium titanate (CaTiO3) perovskite-based ceramic material. The ceramics were made by the solid-state reaction method (SSRM) and treated at temperatures of 1300 °C, 1200 °C, and 1100 °C. The structural characteristics of the ceramics were analyzed by XRD and FT-IR. The results indicated a CaTiO3 phase formation with an orthorhombic structure. The size of the crystallites was in the range of 27–36 nm and was found to increase as the temperatures increased. The relative density showed an increase from 93% to 96% as

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49

Carrasco-Hernández, J., J. Ramos-Méndez, B. Faddegon, A. R. Jalilian, M. Moranchel, and M. A. Ávila-Rodríguez. "Monte Carlo track-structure for the radionuclide Copper-64: characterization of S-values, nanodosimetry and quantification of direct damage to DNA." Physics in Medicine & Biology 65, no. 15 (2020): 155005. http://dx.doi.org/10.1088/1361-6560/ab8aaa.

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50

Lee, B., and C. Wang. "WE-H-BRA-08: A Monte Carlo Cell Nucleus Model for Assessing Cell Survival Probability Based On Particle Track Structure Analysis." Medical Physics 43, no. 6Part43 (2016): 3844. http://dx.doi.org/10.1118/1.4957999.

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