Search results for: Monte Carlo simulations

Authors: Edlira Donefski, Tina Donefski, Lorenc Ekonomi

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Edgeworth Approximation, Bootstrap, and Monte Carlo Simulations have considerable impacts on achieving certain results related to different problems taken into study. In our paper, we have treated a financial case related to the effect that has the components of a cash-flow of one of the most successful businesses in the world, as the financial activity, operational activity, and investment activity to the cash and cash equivalents at the end of the three-months period. To have a better view of this case, we have created a vector autoregression model, and after that, we have generated the impulse responses in the terms of asymptotic analysis (Edgeworth Approximation), Monte Carlo Simulations, and residual bootstrap based on the standard errors of every series created. The generated results consisted of the common tendencies for the three methods applied that consequently verified the advantage of the three methods in the optimization of the model that contains many variants.

Keywords: autoregression, bootstrap, edgeworth expansion, Monte Carlo method

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Authors: H. Donya

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Monte Carlo (MC) techniques play a fundamental role in radiotherapy. A two non-water-equivalent of different media were used to evaluate the dose in water. For such purpose, Lu2SiO5 (LSO) and Y2SiO5 (YSO) orthosilicates scintillators are chosen for MC simulation using Penelope code. To get higher efficiency in dose calculation, variance reduction techniques are discussed. Overall results of this investigation ensured that the LSO/YSO bi-media a good combination to tackle over-response issue in dynamic photon radiotherapy.

Keywords: Lu2SiO5 (LSO) and Y2SiO5 (YSO) orthosilicates, Monte Carlo, correlated sampling, radiotherapy

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Authors: K. R. Phaneesh, Anirudh Bhat, G. Mukherjee, K. T. Kashyap

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Extensive Monte Carlo Potts model simulations were performed on 2D square lattice to investigate the effects of simulated higher temperatures effects on grain growth kinetics. A range of simulation temperatures (KTs) were applied on a matrix of size 10002 with Q-state 64, dispersed with a wide range of second phase particles, ranging from 0.001 to 0.1, and then run to 100,000 Monte Carlo steps. The average grain size, the largest grain size and the grain growth exponent were evaluated for all particle fractions and simulated temperatures. After evaluating several growth parameters, the critical temperature for a square lattice, with eight nearest neighbors, was found to be KTs = 0.4.

Keywords: average grain size, critical temperature, grain growth exponent, Monte Carlo steps

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Authors: Thomas Gerstner, Bastian von Harrach, Daniel Roth

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The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions. Our main tool is the one-step survival idea of Glasserman and Staum. Although this technique yields to new terms per observation, while differentiating, the algorithm is still efficient. As an application, we use the results for a two-dimensional calibration of a Coco-Bond, which we model with different types of discretely monitored barrier options.

Keywords: Monte Carlo, discretely monitored barrier options, pathwise sensitivities, Coco-Bond

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Authors: M. R. Akbari, H. Yousefnia, A. Ghasemi

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Al2O3:C,Mg fluorescent nuclear track detector (FNTD) and Al2O3:C optically stimulated luminescence detector (OSLD) are becoming two of the applied detectors in ion dosimetry. Therefore, the response of these detectors to hadron beams is highly of interest in radiation therapy (RT) using ion beams. In this study, these detectors' responses to proton and Helium-4 ion beams were compared using Monte Carlo simulations. The calculated data for proton beams were compared with Markus ionization chamber (IC) measurement (in water phantom) from M.D. Anderson proton therapy center. Monte Carlo simulations were performed via the FLUKA code (version 2011.2-17). The detectors were modeled in cylindrical shape at various depths of the water phantom without shading each other for obtaining relative depth dose in the phantom. Mono-energetic parallel ion beams in different incident energies (100 MeV/n to 250 MeV/n) were collided perpendicularly on the phantom surface. For proton beams, the results showed that the simulated detectors have over response relative to IC measurements in water phantom. In all cases, there were good agreements between simulated ion ranges in the water with calculated and experimental results reported by the literature. For proton, maximum peak to entrance dose ratio in the simulated water phantom was 4.3 compared with about 3 obtained from IC measurements. For He-4 ion beams, maximum peak to entrance ratio calculated by both detectors was less than 3.6 in all energies. Generally, it can be said that FLUKA is a good tool to calculate Al2O3:C,Mg FNTD and Al2O3:C OSLD detectors responses to therapeutic proton and He-4 ion beams. It can also calculate proton and He-4 ion ranges with a reasonable accuracy.

Keywords: comparison, FNTD and OSLD detectors response, light ion beams, Monte Carlo simulations

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Authors: E. Al Daoud

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In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.

Keywords: Feynman rules, hadrons, Lagrangian, Monte Carlo, simulation

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Authors: Marzieh Jafarzadeh, Fatemeh Rezaee

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Introduction: The effect of ionizing radiation on human health can be effective for genomic integrity and cell viability. It also increases the risk of cancer and malignancy. Therefore, X-ray behavior and absorption dose calculation are considered. One of the applicable tools for calculating and evaluating the absorption dose in human tissues is Monte Carlo simulation. Monte Carlo offers a straightforward way to simulate and integrate, and because it is simple and straightforward, Monte Carlo is easy to use. The Monte Carlo BEAMnrc code is one of the most common diagnostic X-ray simulation codes used in this study. Method: In one of the understudy hospitals, a certain number of CT scan images of patients who had previously been imaged were extracted from the hospital database. BEAMnrc software was used for simulation. The simulation of the head of the device with the energy of 0.09 MeV with 500 million particles was performed, and the output data obtained from the simulation was applied for phantom construction using CT CREATE software. The percentage of depth dose (PDD) was calculated using STATE DOSE was then compared with international standard values. Results and Discussion: The ratio of surface dose to depth dose (D/Ds) in the measured energy was estimated to be about 4% to 8% for bone and 3% to 7% for bone marrow. Conclusion: MC simulation is an efficient and accurate method for simulating bone marrow and calculating the absorbed dose.

Keywords: Monte Carlo, absorption dose, BEAMnrc, bone marrow

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Authors: Encarnación Álvarez, Rosa M. García-Fernández, Juan F. Muñoz

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Estimation of a proportion has many applications in economics and social studies. A common application is the estimation of the low income proportion, which gives the proportion of people classified as poor into a population. In this paper, we present this poverty indicator and propose to use the logistic regression estimator for the problem of estimating the low income proportion. Various sampling designs are presented. Assuming a real data set obtained from the European Survey on Income and Living Conditions, Monte Carlo simulation studies are carried out to analyze the empirical performance of the logistic regression estimator under the various sampling designs considered in this paper. Results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the customary estimator under the various sampling designs considered in this paper. The stratified sampling design can also provide more accurate results.

Keywords: poverty line, risk of poverty, auxiliary variable, ratio method

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Authors: Mehdi Homayouni, Karim Adinehvand, Bakhtiar Azadbakht

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In this study, we used Monte Carlo code (MCNP4C) that is a general method, for simulation, electron source and electric field, a disc source with 0.05 cm radius in direct of anode are used, radius of disc source show focal spot of X-ray tube that here is 0.05 cm. In this simulation, the anode is from tungsten with 18.9 g/cm3 density and angle of the anode is 18°. We simulated X-ray tube for 140 kv. For increasing of speed data acquisition, we use F5 tally. With determination the exact position of F5 tally in the program, outputs are acquired. In this spectrum the start point is about 0.02 Mev, the absorption edges are about 0.06 Mev and 0.07 Mev, and average energy is about 0.05 Mev.

Keywords: X-spectrum, simulation, Monte Carlo, tube

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Authors: Jan-Tore H. Horn, Jørgen Juncher Jensen

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Uncertainties related to fatigue damage estimation of non-linear systems are highly dependent on the tail behaviour and extreme values of the stress range distribution. By using a combination of the First Order Reliability Method (FORM) and Monte Carlo simulations (MCS), the accuracy of the fatigue estimations may be improved for the same computational efforts. The method is applied to a bottom-fixed, monopile-supported large offshore wind turbine, which is a non-linear and dynamically sensitive system. Different curve fitting techniques to the fatigue damage distribution have been used depending on the sea-state dependent response characteristics, and the effect of a bi-linear S-N curve is discussed. Finally, analyses are performed on several environmental conditions to investigate the long-term applicability of this multistep method. Wave loads are calculated using state-of-the-art theory, while wind loads are applied with a simplified model based on rotor thrust coefficients.

Keywords: fatigue damage, FORM, monopile, Monte Carlo, simulation, wind turbine

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Authors: Ana Staneva, Vessela Stoimenova

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A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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Authors: Kaouther Bergaui, Nafaa Reguigui, Charles Gary

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Characterization and the applications of deuterium-deuterium (DD) neutron generator developed by Adelphie technology and acquired by the National Centre of Nuclear Science and Technology (NCNST) were presented in this work. We study the performance of the neutron generator in terms of neutron yield, production efficiency, and the ionic current as a function of the acceleration voltage at various RF powers. We provide the design and optimization of the PGNAA chamber and thus give insight into the capabilities of the planned PGNAA facility. Additional non-destructive techniques were studied employing the DD neutron generator, such as PGNAA and neutron radiography: The PGNAA is used for determining the concentration of 10B in Si and SiO2 matrices by using a germanium detector HPGe and the results obtained are compared with PGNAA system using a Sodium Iodide detector (NaI (Tl)); Neutron radiography facility was tested and simulated, using a camera device CCD and simulated by the Monte Carlo code; and the explosive detection system (EDS) also simulated using the Monte Carlo code. The study allows us to show that the new models of DD neutron generators are feasible and that superior-quality neutron beams could be produced and used for various applications. The feasibility of Boron neutron capture therapy (BNCT) for cancer treatment using a neutron generator was assessed by optimizing Beam Shaping Assembly (BSA) on a phantom using Monte-Carlo (MCNP6) simulations.

Keywords: neutron generator deuterium-deuterium, Monte Carlo method, radiation, neutron flux, neutron activation analysis, born, neutron radiography, explosive detection, BNCT

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Authors: N. Massoum, B. Bouazza

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In this paper, we have developed a numerical simulation model to describe the electrical properties of GaInP MESFET with submicron gate (Lg = 0.5 µm). This model takes into account the three-dimensional (3D) distribution of the load in the short channel and the law effect of mobility as a function of electric field. Simulation software based on a stochastic method such as Monte Carlo has been established. The results are discussed and compared with those of the experiment. The result suggests experimentally that, in a very small gate length in our devices (smaller than 40 nm), short-channel tunneling explains the degradation of transistor performance, which was previously enhanced by velocity overshoot.

Keywords: Monte Carlo simulation, transient electron transport, MESFET device, simulation software

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Authors: Hamid Khachab, Yamani Abdelkafi, Mouna Barhmi

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The epitaxial growth has great important in the fabricate of the new semi-conductors devices and upgrading many factors, such as the quality of crystallization and efficiency with their deferent types and the most effective epitaxial technique is the molecular beam epitaxial. The MBE growth modeling allows to confirm the experiments results out by atomic beam and to analyze the microscopic phenomena. In of our work, we determined the growth processes specially the ZnSe epitaxial technique by Kinetic Monte Carlo method and we also give observations that are made in real time at the growth temperature using reflection high energy electron diffraction (RHEED) and photoemission current.

Keywords: molecular beam epitaxy, II-VI, morpholy, photoemission, RHEED, simulation, kinetic Monte Carlo, ZnSe

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Authors: Encarnación Álvarez, Rosa M. García-Fernández, Juan F. Muñoz, Francisco J. Blanco-Encomienda

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The problem of estimating a proportion has important applications in the field of economics, and in general, in many areas such as social sciences. A common application in economics is the estimation of the headcount index. In this paper, we define the general headcount index as a proportion. Furthermore, we introduce a new quantitative method for estimating the headcount index. In particular, we suggest to use the logistic regression estimator for the problem of estimating the headcount index. Assuming a real data set, results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the traditional estimator of the headcount index.

Keywords: poverty line, poor, risk of poverty, Monte Carlo simulations, sample

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Authors: Betim Bahtiri, B. Arash, R. Rolfes

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Epoxy-based materials are frequently exposed to high-humidity environments in many engineering applications. As a result, their material properties would be degraded by water absorption. A full characterization of the material properties under hygrothermal conditions requires time- and cost-consuming experimental tests. To gain insights into the physics of diffusion mechanisms, atomistic simulations have been shown to be effective tools. Concerning the diffusion of water in polymers, spatial trajectories of water molecules are obtained from molecular dynamics (MD) simulations allowing the interpretation of diffusion pathways at the nanoscale in a polymer network. Conventional MD simulations of water diffusion in amorphous polymers lead to discrepancies at low temperatures due to the short timescales of the simulations. In the proposed model, this issue is solved by using a combined scheme of autonomous basin climbing (ABC) with kinetic Monte Carlo and reactive MD simulations to investigate the diffusivity of water molecules in epoxy resins across a wide range of temperatures. It is shown that the proposed simulation framework estimates kinetic properties of water diffusion in epoxy resins that are consistent with experimental observations and provide a predictive tool for investigating the diffusion of small molecules in other amorphous polymers.

Keywords: epoxy resins, water diffusion, autonomous basin climbing, kinetic Monte Carlo, reactive molecular dynamics

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Authors: Luca Indovina, Carmela Coppola, Carlo Altucci, Riccardo Barberi, Rocco Romano

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In this paper a real court case, held in Italy at the Court of Nola, in which a correct physical description, conducted with both a Monte Carlo and biophysical analysis, would have been sufficient to arrive at conclusions confirmed by documentary evidence, is considered. This will be an example of how forensic physics can be useful in confirming documentary evidence in order to reach hardly questionable conclusions. This was a libel trial in which the defendant, Mr. DS (Defendant for Slander), had falsely accused one of his neighbors, Mr. OP (Offended Person), of having caused him some damages. The damages would have been caused by an external plaster piece that would have detached from the neighbor’s property and would have hit Mr DS while he was in his garden, much more than a meter far away from the facade of the building from which the plaster piece would have detached. In the trial, Mr. DS claimed to have suffered a scratch on his forehead, but he never showed the plaster that had hit him, nor was able to tell from where the plaster would have arrived. Furthermore, Mr. DS presented a medical certificate with a diagnosis of contusion of the cerebral cortex. On the contrary, the images of Mr. OP’s security cameras do not show any movement in the garden of Mr. DS in a long interval of time (about 2 hours) around the time of the alleged accident, nor do they show any people entering or coming out from the house of Mr. DS in the same interval of time. Biophysical analysis shows that both the diagnosis of the medical certificate and the wound declared by the defendant, already in conflict with each other, are not compatible with the fall of external plaster pieces too small to be found. The wind was at a level 1 of the Beaufort scale, that is, unable to raise even dust (level 4 of the Beaufort scale). Therefore, the motion of the plaster pieces can be described as a projectile motion, whereas collisions with the building cornice can be treated using Newtons law of coefficients of restitution. Numerous numerical Monte Carlo simulations show that the pieces of plaster would not have been able to reach even the garden of Mr. DS, let alone a distance over 1.30 meters. Results agree with the documentary evidence (images of Mr. OP’s security cameras) that Mr. DS could not have been hit by plaster pieces coming from Mr. OP’s property.

Keywords: biophysics analysis, Monte Carlo simulations, Newton’s law of restitution, projectile motion

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Authors: Wheyming Tina Song, Chi-Hao Hong, Peisyuan Lin

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An important performance measure for stochastic manufacturing networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that eighteen archival publications, containing twenty-one examples, provide incorrect values of the system reliability. The author recently published the Song Rule, which provides the correct analytical system-reliability value; it is, however, computationally inefficient for large networks. In this paper, we use Monte Carlo simulation (implemented in C and Flexsim) to provide estimates for the above-mentioned twenty-one examples. The simulation estimates are consistent with the analytical solution for small networks but is computationally efficient for large networks. We argue here for three advantages of Monte Carlo simulation: (1) understanding stochastic systems, (2) validating analytical results, and (3) providing estimates even when analytical and numerical approaches are overly expensive in computation. Monte Carlo simulation could have detected the published analysis errors.

Keywords: Monte Carlo simulation, analytical results, leading digit rule, standard error

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Authors: A. S. Cheliyan, S. K. Bhattacharyya

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Dynamic Positioning System (DPS) is employed in marine vessels of the offshore oil and gas industry. It is a computer controlled system to automatically maintain a ship’s position and heading by using its own thrusters. Reliability assessment of the same can be analyzed through conventional fault tree. However, the complex behaviour like sequence failure, redundancy management and priority of failing of events cannot be analyzed by the conventional fault trees. The Dynamic Fault Tree (DFT) addresses these shortcomings of conventional Fault Tree by defining additional gates called dynamic gates. Monte Carlo based simulation approach has been adopted for the dynamic gates. This method of realistic modeling of DPS gives meaningful insight into the system reliability and the ability to improve the same.

Keywords: dynamic positioning system, dynamic fault tree, Monte Carlo simulation, reliability assessment

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Authors: N. Dahbi, M. Daoudi

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This paper deals with the use of computational method based on Monte Carlo simulation in order to investigate the transport phenomena of the electron in HgCdTe narrow band gap semiconductor. Via this method we can evaluate the time dependence of the transport parameters: velocity, energy and mobility of electrons through matter (HgCdTe).

Keywords: Monte Carlo, transport parameters, HgCdTe, computational mechanics

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Authors: Obioma Uche

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Due to the recent volatility in oil & gas prices as well as increased development of non-conventional resources, it has become even more essential to critically evaluate the profitability of petroleum prospects prior to making any investment decisions. Traditionally, simple Monte Carlo (MC) algorithms have been used to randomly sample probability distributions of economic and geological factors (e.g. price, OPEX, CAPEX, reserves, productive life, etc.) in order to obtain probability distributions for profitability metrics such as Net Present Value (NPV). In recent years, second-order MC algorithms have been shown to offer an advantage over simple MC techniques due to the added consideration of uncertainties associated with the probability distributions of the relevant variables. Here, a strategy for the application of the second-order MC technique to a case study is demonstrated to analyze its effectiveness as a tool for portfolio management.

Keywords: Monte Carlo algorithms, portfolio management, profitability, risk analysis

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Authors: Sajjad Asefi, Hossein Afrakhte

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This paper presents the evaluation of reliability indices of an electrical distribution system using Monte Carlo simulation technique accounting Time To Switch (TTS) for each section. In this paper, the distribution system has been assumed by accounting random repair time omission. For simplicity, we have assumed the reliability analysis to be based on exponential law. Each segment has a specified rate of failure (λ) and repair time (r) which will give us the mean up time and mean down time of each section in distribution system. After calculating the modified mean up time (MUT) in years, mean down time (MDT) in hours and unavailability (U) in h/year, TTS have been added to the time which the system is not available, i.e. MDT. In this paper, we have assumed the TTS to be a random variable with Log-Normal distribution.

Keywords: distribution system, Monte Carlo simulation, reliability, repair time, time to switch (TTS)

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Authors: Hamidreza Jabal Ameli, Anahita Movahedi

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Purpose: In radionuclide therapy, radioactive atoms are coupled to monoclonal antibodies (mAbs) for treating cancer tumor while limiting radiation to healthy tissues. We know that tumoral and normal tissues are not equally sensitive to radiation. In fact, biological effects such as cellular repair processes or the presence of less radiosensitive cells such as hypoxic cells should be taken account. For this reason, in this paper, we want to calculate biological effect dose (BED) inside tumoral area and healthy cells around tumors. Methods: In this study, deposited doses of a radionuclide, gold-198, inside cells lattice and surrounding healthy tissues were calculated with Monte Carlo method. The elemental compositions and density of malignant and healthy tissues were obtained from ICRU Report 44. For reaching to real condition of oxygen effects, the necrosis and hypoxia area inside tumors has been assessed. Results: With regard to linear-quadratic expression which was defined in Monte Carlo, results showed that a large amount of BED is deposited in the well-oxygenated part of the hypoxia area compared to necrosis area. Moreover, there is a significant difference between the curves of absorbed dose with BED and without BED.

Keywords: biological dose, monte carlo, hypoxia, radionuclide therapy

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Authors: Md Abdullah Al Mashud, M. Tariquzzaman, M. Jahangir Alam, Tapan Kumar Godder, M. Mahbubur Rahman

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This paper presents a Monte Carlo (MC) method-based dose distributions on lung tumor for 6 MV photon beam to improve the dosimetric accuracy for cancer treatment. The polystyrene which is tissue equivalent material to the lung tumor density is used in this research. In the empirical calculations, TRS-398 formalism of IAEA has been used, and the setup was made according to the ICRU recommendations. The research outcomes were compared with the state-of-the-art experimental results. From the experimental results, it is observed that the proposed based approach provides more accurate results and improves the accuracy than the existing approaches. The average %variation between measured and TPS simulated values was obtained 1.337±0.531, which shows a substantial improvement comparing with the state-of-the-art technology.

Keywords: lung tumour, Monte Carlo, polystyrene, Elekta synergy, Monaco planning system

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Authors: Sai Sudarshan, Harsh Vyas, Riddhiman Sherlekar

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The oil and gas industry has been unwilling to adopt stochastic definition of reserves. Nevertheless, Monte Carlo simulation methods have gained acceptance by engineers, geoscientists and other professionals who want to evaluate prospects or otherwise analyze problems that involve uncertainty. One of the common applications of Monte Carlo simulation is the estimation of recoverable hydrocarbon from a reservoir.Monte Carlo Simulation makes use of random samples of parameters or inputs to explore the behavior of a complex system or process. It finds application whenever one needs to make an estimate, forecast or decision where there is significant uncertainty. First, the project focuses on performing Monte-Carlo Simulation on a given data set using U. S Department of Energy’s MonteCarlo Software, which is a freeware e&p tool. Further, an algorithm for simulation has been developed for MATLAB and program performs simulation by prompting user for input distributions and parameters associated with each distribution (i.e. mean, st.dev, min., max., most likely, etc.). It also prompts user for desired probability for which reserves are to be calculated. The algorithm so developed and tested in MATLAB further finds implementation in Python where existing libraries on statistics and graph plotting have been imported to generate better outcome. With PyQt designer, codes for a simple graphical user interface have also been written. The graph so plotted is then validated with already available results from U.S DOE MonteCarlo Software.

Keywords: simulation, probability, confidence interval, sensitivity analysis

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Authors: Hatem Mrad, Mohamed Bouazara, Fouad Erchiqui

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Fatigue, is considered as one of the main cause of mechanical properties degradation of mechanical parts. Probability and reliability methods are appropriate for fatigue analysis using uncertainties that exist in fatigue material or process parameters. Current work deals with the study of the effect of the number and counting Rainflow cycle on fatigue lifetime (cumulative damage) of an upper arm of the vehicle suspension system. The major part of the fatigue damage induced in suspension arm is caused by two main classes of parameters. The first is related to the materials properties and the second is the road excitation or the applied force of the passenger’s number. Therefore, Young's modulus and road excitation are selected as input parameters to conduct repetitive simulations by Monte Carlo (MC) algorithm. Latin hypercube sampling method is used to generate these parameters. Response surface method is established according to fatigue lifetime of each combination of input parameters according to strain-life method. A PYTHON script was developed to automatize finite element simulations of the upper arm according to a design of experiments.

Keywords: fatigue, monte carlo, rainflow cycle, response surface, suspension system

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Authors: Kuan-Jen Lai, Fang-Yi Lin, Shang-Rong Huang, Yun-Zheng Zeng, Po-Chieh Hsu, Jay Wu

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The normalized glandular dose (DgN) estimates the energy deposition of mammography in clinical practice. The Monte Carlo simulations frequently use uniformly mixed phantom for calculating the conversion factor. However, breast tissues are not uniformly distributed, leading to errors of conversion factor estimation. This study constructed a three-layer phantom to estimated more accurate of normalized glandular dose. In this study, MCNP code (Monte Carlo N-Particles code) was used to create the geometric structure. We simulated three types of target/filter combinations (Mo/Mo, Mo/Rh, Rh/Rh), six voltages (25 ~ 35 kVp), six HVL parameters and nine breast phantom thicknesses (2 ~ 10 cm) for the three-layer mammographic phantom. The conversion factor for 25%, 50% and 75% glandularity was calculated. The error of conversion factors compared with the results of the American College of Radiology (ACR) was within 6%. For Rh/Rh, the difference was within 9%. The difference between the 50% average glandularity and the uniform phantom was 7.1% ~ -6.7% for the Mo/Mo combination, voltage of 27 kVp, half value layer of 0.34 mmAl, and breast thickness of 4 cm. According to the simulation results, the regression analysis found that the three-layer mammographic phantom at 0% ~ 100% glandularity can be used to accurately calculate the conversion factors. The difference in glandular tissue distribution leads to errors of conversion factor calculation. The three-layer mammographic phantom can provide accurate estimates of glandular dose in clinical practice.

Keywords: Monte Carlo simulation, mammography, normalized glandular dose, glandularity

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Authors: Cherief Houria, Fouka Mourad

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In this work, the simulation of the radiation attenuation is carried out in a photon detector consisting of different common shielding material using a Monte Carlo program called PTM. The aim of the study is to investigate the effect of atomic weight and the thickness of shielding materials on the gamma radiation attenuation ability. The linear attenuation coefficients of Aluminum (Al), Iron (Fe), and lead (Pb) elements were evaluated at photons energy of 661:7KeV that are considered to be emitted from a standard radioactive point source Cs 137. The experimental measurements have been performed for three materials to obtain these linear attenuation coefficients, using a Gamma NaI(Tl) scintillation detector. Our results have been compared with the simulation results of the linear attenuation coefficient using the XCOM database and Geant4 codes and reveal that they are well agreed with both simulation data.

Keywords: gamma photon, Monte Carlo program, radiation attenuation, shielding material, the linear attenuation coefficient

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Authors: Engy A. Mohamed, Y. G. Hegazy

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This paper presents a novel algorithm for modeling photovoltaic based distributed generators for the purpose of optimal planning of distribution networks. The proposed algorithm utilizes sequential Monte Carlo method in order to accurately consider the stochastic nature of photovoltaic based distributed generators. The proposed algorithm is implemented in MATLAB environment and the results obtained are presented and discussed.

Keywords: comulative distribution function, distributed generation, Monte Carlo

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Authors: Al Omari Moahmmed Ahmed

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These papers describe the Bayesian Estimator using Markov Chain Monte Carlo and Lindley’s approximation and the maximum likelihood estimation of the Weibull distribution with Type-I censored data. The maximum likelihood method can’t estimate the shape parameter in closed forms, although it can be solved by numerical methods. Moreover, the Bayesian estimates of the parameters, the survival and hazard functions cannot be solved analytically. Hence Markov Chain Monte Carlo method and Lindley’s approximation are used, where the full conditional distribution for the parameters of Weibull distribution are obtained via Gibbs sampling and Metropolis-Hastings algorithm (HM) followed by estimate the survival and hazard functions. The methods are compared to Maximum Likelihood counterparts and the comparisons are made with respect to the Mean Square Error (MSE) and absolute bias to determine the better method in scale and shape parameters, the survival and hazard functions.

Keywords: weibull distribution, bayesian method, markov chain mote carlo, survival and hazard functions

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