Search results for: Monte Carlo N-Particle Code

Authors: M. R. Akbari , H. Yousefnia, E. Mirrezaei

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Range uncertainties of protons are currently a topic of interest in proton therapy. Two of the parameters that are often used to specify proton range are water equivalent thickness (WET) and water equivalent ratio (WER). Since WER values for a specific material is nearly constant at different proton energies, it is a more useful parameter to compare. In this study, WER values were calculated for different proton energies in polymethyl methacrylate (PMMA), polystyrene (PS) and aluminum (Al) using FLUKA and TRIM codes. The results were compared with analytical, experimental and simulated SEICS code data obtained from the literature. In FLUKA simulation, a cylindrical phantom, 1000 mm in height and 300 mm in diameter, filled with the studied materials was simulated. A typical mono-energetic proton pencil beam in a wide range of incident energies usually applied in proton therapy (50 MeV to 225 MeV) impinges normally on the phantom. In order to obtain the WER values for the considered materials, cylindrical detectors, 1 mm in height and 20 mm in diameter, were also simulated along the beam trajectory in the phantom. In TRIM calculations, type of projectile, energy and angle of incidence, type of target material and thickness should be defined. The mode of 'detailed calculation with full damage cascades' was selected for proton transport in the target material. The biggest difference in WER values between the codes was 3.19%, 1.9% and 0.67% for Al, PMMA and PS, respectively. In Al and PMMA, the biggest difference between each code and experimental data was 1.08%, 1.26%, 2.55%, 0.94%, 0.77% and 0.95% for SEICS, FLUKA and SRIM, respectively. FLUKA and SEICS had the greatest agreement (≤0.77% difference in PMMA and ≤1.08% difference in Al, respectively) with the available experimental data in this study. It is concluded that, FLUKA and TRIM codes have capability for Bragg curves simulation and WER values calculation in the studied materials. They can also predict Bragg peak location and range of proton beams with acceptable accuracy.

Keywords: water equivalent ratio, dosimetric materials, proton therapy, Monte Carlo simulations

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Authors: Jessica A. Soto-Bear, Virginia González-Vélez, Norma Castañeda-Villa, Amparo Gil

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Glutamate release of the cochlear inner hair cell (IHC) ribbon synapse is a fundamental step in transferring sound information in the auditory pathway. Otoferlin is the calcium sensor in the IHC and its activity has been related to many auditory disorders. In order to simulate secretion dynamics occurring in the IHC in a few milliseconds timescale and with high spatial resolution, we proposed an active-zone model solved with Monte Carlo algorithms. We included models for calcium buffered diffusion, calcium-binding schemes for vesicle fusion, and L-type voltage-gated calcium channels. Our results indicate that calcium influx and calcium binding is managing IHC secretion as a function of voltage depolarization, which in turn mean that IHC response depends on sound intensity.

Keywords: inner hair cells, Monte Carlo algorithm, Otoferlin, secretion

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Authors: Mohammad Rahim Rahnama

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The study employs Monte Carlo method for simulation of rented housing in Mashhad second largest city in Iran. A total number of 334 rental residential units in Mashhad, including both apartments and houses (villa), were randomly selected from advertisements placed in Khorasan Newspapers during the months of July and August of 2015. In order to simulate the monthly rent price, the rent index was calculated through combining the mortgage and the rent price. In the next step, the relation between the variables of the floor area and that of the number of bedrooms for each unit, in both apartments and houses(villa), was calculated through multivariate regression using SPSS and was coded in XML. The initial model was called using simulation button in SPSS and was simulated using triangular and binominal algorithms. The findings revealed that the average simulated rental index was 548.5$ per month. Calculating the sensitivity of rental index to a number of bedrooms we found that firstly, 97% of units have three bedrooms, and secondly as the number of bedrooms increases from one to three, for the rent price of less than 200$, the percentage of units having one bedroom decreases from 10% to 0. Contrariwise, for units with the rent price of more than 571.4$, the percentage of bedrooms increases from 37% to 48%. In the light of these findings, it becomes clear that planning to build rental residential units, overseeing the rent prices, and granting subsidies to rental residential units, for apartments with two bedrooms, present a felicitous policy for regulating residential units in Mashhad.

Keywords: Mashhad, Monte Carlo, simulation, rent price, residential unit

Procedia PDF Downloads 247

Authors: Ifigeneia V. Mavragani, Zacharenia Nikitaki, George Kalantzis, George Iliakis, Alexandros G. Georgakilas

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Complex DNA damage consisting of a combination of DNA lesions, such as Double Strand Breaks (DSBs) and non-DSB base lesions occurring in a small volume is considered as one of the most important biological endpoints regarding ionizing radiation (IR) exposure. Strong theoretical (Monte Carlo simulations) and experimental evidence suggests an increment of the complexity of DNA damage and therefore repair resistance with increasing linear energy transfer (LET). Experimental detection of complex (clustered) DNA damage is often associated with technical deficiencies limiting its measurement, especially in cellular or tissue systems. Our groups have recently made significant improvements towards the identification of key parameters relating to the efficient detection of complex DSBs and non-DSBs in human cellular systems exposed to IR of varying quality (γ-, X-rays 0.3-1 keV/μm, α-particles 116 keV/μm and 36Ar ions 270 keV/μm). The induction and processing of DSB and non-DSB-oxidative clusters were measured using adaptations of immunofluorescence (γH2AX or 53PB1 foci staining as DSB probes and human repair enzymes OGG1 or APE1 as probes for oxidized purines and abasic sites respectively). In the current study, Relative Biological Effectiveness (RBE) values for DSB and non-DSB induction have been measured in different human normal (FEP18-11-T1) and cancerous cell lines (MCF7, HepG2, A549, MO59K/J). The experimental results are compared to simulation data obtained using a validated microdosimetric fast Monte Carlo DNA Damage Simulation code (MCDS). Moreover, this simulation approach is implemented in two realistic clinical cases, i.e. prostate cancer treatment using X-rays generated by a linear accelerator and a pediatric osteosarcoma case using a 200.6 MeV proton pencil beam. RBE values for complex DNA damage induction are calculated for the tumor areas. These results reveal a disparity between theory and experiment and underline the necessity for implementing highly precise and more efficient experimental and simulation approaches.

Keywords: complex DNA damage, DNA damage simulation, protons, radiotherapy

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Authors: Nureni O. Adeboye, Dawud A. Agunbiade

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This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.

Keywords: audit fee lagrange multiplier test, heteroscedasticity, lagrange multiplier test, Monte-Carlo scheme, periodicity

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Authors: Manish Chand, Subhrojit Bagchi, R. Kumar

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A new dry tube (DT) has been installed in the tank of KAMINI research reactor, Kalpakkam India. This tube will be used for neutron activation analysis of small to large samples and testing of neutron detectors. DT tube is 375 cm height and 7.5 cm in diameter, located 35 cm away from the core centre. The experimental thermal flux at various axial positions inside the tube has been measured by irradiating the flux monitor (¹⁹⁷Au) at 20kW reactor power. The measured activity of ¹⁹⁸Au and the thermal cross section of ¹⁹⁷Au (n,γ) ¹⁹⁸Au reaction were used for experimental thermal flux measurement. The flux inside the tube varies from 10⁹ to 10¹⁰ and maximum flux was (1.02 ± 0.023) x10¹⁰ n cm⁻²s⁻¹ at 36 cm from the bottom of the tube. The Au and Zr foils without and with cadmium cover of 1-mm thickness were irradiated at the maximum flux position in the DT to find out the irradiation specific input parameters like sub-cadmium to epithermal neutron flux ratio (f) and the epithermal neutron flux shape factor (α). The f value was 143 ± 5, indicates about 99.3% thermal neutron component and α value was -0.2886 ± 0.0125, indicates hard epithermal neutron spectrum due to insufficient moderation. The measured flux profile has been validated using theoretical model of KAMINI reactor through Monte Carlo N-Particle Code (MCNP). In MCNP, the complex geometry of the entire reactor is modelled in 3D, ensuring minimum approximations for all the components. Continuous energy cross-section data from ENDF-B/VII.1 as well as S (α, β) thermal neutron scattering functions are considered. The neutron flux has been estimated at the corresponding axial locations of the DT using mesh tally. The thermal flux obtained from the experiment shows good agreement with the theoretically predicted values by MCNP, it was within ± 10%. It can be concluded that this MCNP model can be utilized for calculating other important parameters like neutron spectra, dose rate, etc. and multi elemental analysis can be carried out by irradiating the sample at maximum flux position using measured f and α parameters by k₀-NAA standardization.

Keywords: neutron flux, neutron activation analysis, neutron flux shape factor, MCNP, Monte Carlo N-Particle Code

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Authors: Muhammad Farooq, Ahtasham Gul

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To meet the desired standard, it is important to monitor and analyze different engineering processes to get desired output. The bivariate distributions got a lot of attention in recent years to describe the randomness of natural as well as artificial mechanisms. In this article, a bivariate model is constructed using two independent models developed by the nesting approach to study the effect of each component on reliability for better understanding. Further, the Bayes analysis of system availability is studied by considering prior parametric variations in the failure time and repair time distributions. Basic statistical characteristics of marginal distribution, like mean median and quantile function, are discussed. We use inverse Gamma prior to study its frequentist properties by conducting Monte Carlo Markov Chain (MCMC) sampling scheme.

Keywords: reliability, system availability Weibull, inverse Lomax, Monte Carlo Markov Chain, Bayesian

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Authors: Erich Gomes Schaitza, Antônio Francisco Savi, Glaucia Aparecida Prates

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The penetration of renewable energy into the electricity supply in Brazil is high, one of the highest in the World. Centralized hydroelectric generation is the main source of energy, followed by biomass and wind. Surprisingly, mini and micro-generation are negligible, with less than 2,000 connections to the national grid. In 2015, a new regulatory framework was put in place to change this situation. In the agricultural sector, the framework was complemented by the offer of low interest rate loans to in-farm renewable generation. Brazil proposed to more than double its area of planted forests as part of its INDC- Intended Nationally Determined Contributions to the UNFCCC-U.N. Framework Convention on Climate Change (UNFCCC). This is an ambitious target which will be achieved only if forests are attractive to farmers. Therefore, this paper analyses whether planting forests for in-farm energy generation with a with a woodchip gasifier is economically viable for microgeneration under the new framework and at if they could be an economic driver for forest plantation. At first, a static case was analyzed with data from Eucalyptus plantations in five farms. Then, a broader analysis developed with the use of Monte Carlo technique. Planting short rotation forests to generate energy could be a viable alternative and the low interest loans contribute to that. There are some barriers to such systems such as the inexistence of a mature market for small scale equipment and of a reference network of good practices and examples.

Keywords: biomass, distribuited generation, small-scale, Monte Carlo

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Authors: Wararit Panichkitkosolkul

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The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results show that all unit root tests can control the probability of Type I error for all situations. The empirical power of the unit root tests based on the robust estimator are higher than the unit root tests based on the OLS estimator.

Keywords: autoregressive, ordinary least squares, type i error, power of the test, Monte Carlo simulation

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Authors: N. Massoum, A. Guen. Bouazza, B. Bouazza, A. El Ouchdi

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The progress of industry integrated circuits in recent years has been pushed by continuous miniaturization of transistors. With the reduction of dimensions of components at 0.1 micron and below, new physical effects come into play as the standard simulators of two dimensions (2D) do not consider. In fact the third dimension comes into play because the transverse and longitudinal dimensions of the components are of the same order of magnitude. To describe the operation of such components with greater fidelity, we must refine simulation tools and adapted to take into account these phenomena. After an analytical study of the static characteristics of the component, according to the different operating modes, a numerical simulation is performed of field-effect transistor with submicron gate MESFET GaInP. The influence of the dimensions of the gate length is studied. The results are used to determine the optimal geometric and physical parameters of the component for their specific applications and uses.

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

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Authors: Athmane Bakhta, Sebastien Leclaire, David Vidal, Francois Bertrand, Mohamed Cheriet

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This work presents a new three-dimensional variational model proposed for the simulation of ink seepage into paper sheets at the fiber level. The model, inspired by the Hising model, takes into account a finite volume of ink and describes the system state through gravity, cohesion, and adhesion force interactions. At the mesoscopic scale, the paper substrate is modeled using a discretized fiber structure generated using a numerical deposition procedure. A modified Monte Carlo method is introduced for the simulation of the ink dynamics. Besides, a multiphase lattice Boltzmann method is suggested to fine-tune the mesoscopic variational model parameters, and it is shown that the ink seepage behaviors predicted by the proposed model can resemble those predicted by a method relying on first principles.

Keywords: fibrous media, lattice Boltzmann, modelling and simulation, Monte Carlo, variational model

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Authors: E. Krishna

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An Extended form of exponential distribution using Marshall and Olkin method is introduced.The location scale family of these distributions is considered. For location scale free family, exact expressions for single and product moments of upper record statistics are derived. The mean, variance and covariance of record values are computed for various values of the shape parameter. Using these the BLUE's of location and scale parameters are derived.The variances and covariance of estimates are obtained.Through Monte Carlo simulation the condence intervals for location and scale parameters are constructed.The Best liner unbiased Predictor (BLUP) of future records are also discussed.

Keywords: BLUE, BLUP, condence interval, Marshall-Olkin distribution, Monte Carlo simulation, prediction of future records, record statistics

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Authors: Adem Acır

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In this study, time dependent neutronic analysis of incineration of minor actinides of a Laser Fusion Inertial Confinement Fusion Fission Energy (LIFE) engine was performed. The calculations were carried out by using MCNP codes with ENDF/B.VI neutron data library. In the neutronic calculations, TRISO particles fueled with minor actinides with natural lithium coolant were performed. The natural lithium cooled LIFE engine used 10 % TRISO fuel minor actinides composition. Tritium breeding ratios (TBR) and energy multiplication factor (M) burnup values were computed as 1.46 and 3.75, respectively. The reactor operation time was calculated as ~ 21 years. The burnup values were obtained as ~1060 GWD/MT, respectively. As a result, the very higher burnup were achieved of LIFE engine.

Keywords: Monte Carlo, minor actinides, nuclear waste, LIFE engine

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Authors: Randa Alharbi, Vladislav Vyshemirsky

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Systems biology is an important field in science which focuses on studying behaviour of biological systems. Modelling is required to produce detailed description of the elements of a biological system, their function, and their interactions. A well-designed model requires selecting a suitable mechanism which can capture the main features of the system, define the essential components of the system and represent an appropriate law that can define the interactions between its components. Complex biological systems exhibit stochastic behaviour. Thus, using probabilistic models are suitable to describe and analyse biological systems. Continuous-Time Markov Chain (CTMC) is one of the probabilistic models that describe the system as a set of discrete states with continuous time transitions between them. The system is then characterised by a set of probability distributions that describe the transition from one state to another at a given time. The evolution of these probabilities through time can be obtained by chemical master equation which is analytically intractable but it can be simulated. Uncertain parameters of such a model can be inferred using methods of Bayesian inference. Yet, inference in such a complex system is challenging as it requires the evaluation of the likelihood which is intractable in most cases. There are different statistical methods that allow simulating from the model despite intractability of the likelihood. Approximate Bayesian computation is a common approach for tackling inference which relies on simulation of the model to approximate the intractable likelihood. Particle Markov chain Monte Carlo (PMCMC) is another approach which is based on using sequential Monte Carlo to estimate intractable likelihood. However, both methods are computationally expensive. In this paper we discuss the efficiency and possible practical issues for each method, taking into account the computational time for these methods. We demonstrate likelihood-free inference by performing analysing a model of the Repressilator using both methods. Detailed investigation is performed to quantify the difference between these methods in terms of efficiency and computational cost.

Keywords: Approximate Bayesian computation(ABC), Continuous-Time Markov Chains, Sequential Monte Carlo, Particle Markov chain Monte Carlo (PMCMC)

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Authors: Li-hsing Shih, Wei-Jen Hsu

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Recently, the sale of electrical vehicles (EVs) has increased dramatically due to maturing technology development and decreasing cost. Governments of many countries have made regulations and policies in favor of EVs due to their long-term commitment to net zero carbon emissions. However, due to uncertain factors such as the future price of EVs, forecasting the future market share of EVs is a challenging subject for both the auto industry and local government. This study tries to forecast the market share of EVs using conjoint models and Monte Carlo simulation. The research is conducted in three phases. (1) A conjoint model is established to represent the customer preference structure on purchasing vehicles while five product attributes of both EV and internal combustion engine vehicles (ICEV) are selected. A questionnaire survey is conducted to collect responses from Taiwanese consumers and estimate the part-worth utility functions of all respondents. The resulting part-worth utility functions can be used to estimate the market share, assuming each respondent will purchase the product with the highest total utility. For example, attribute values of an ICEV and a competing EV are given respectively, two total utilities of the two vehicles of a respondent are calculated and then knowing his/her choice. Once the choices of all respondents are known, an estimate of market share can be obtained. (2) Among the attributes, future price is the key attribute that dominates consumers’ choice. This study adopts the assumption of a learning curve to predict the future price of EVs. Based on the learning curve method and past price data of EVs, a regression model is established and the probability distribution function of the price of EVs in 2030 is obtained. (3) Since the future price is a random variable from the results of phase 2, a Monte Carlo simulation is then conducted to simulate the choices of all respondents by using their part-worth utility functions. For instance, using one thousand generated future prices of an EV together with other forecasted attribute values of the EV and an ICEV, one thousand market shares can be obtained with a Monte Carlo simulation. The resulting probability distribution of the market share of EVs provides more information than a fixed number forecast, reflecting the uncertain nature of the future development of EVs. The research results can help the auto industry and local government make more appropriate decisions and future action plans.

Keywords: conjoint model, electrical vehicle, learning curve, Monte Carlo simulation

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Authors: Mojtaba Aghamiri Esfahani, Mohammad Karkon, Seyed Majid Hosseini Nezhad, Reza Hosseini-Ara

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In this study, the effect of uncertainty in elastic modulus of a plate on free vibration response is investigated. For this purpose, the elastic modulus of the plate is modeled as stochastic variable with normal distribution. Moreover, the distance autocorrelation function is used for stochastic field. Then, by applying the finite element method and Monte Carlo simulation, stochastic finite element relations are extracted. Finally, with a numerical test, the effect of uncertainty in the elastic modulus on free vibration response of a plate is studied. The results show that the effect of uncertainty in elastic modulus of the plate cannot play an important role on the free vibration response.

Keywords: stochastic finite elements, plate bending, free vibration, Monte Carlo, Neumann expansion method.

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Authors: Parimalah Velo, Ahmad Zakaria

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Introduction: Monte Carlo simulations of preclinical imaging systems allow opportunity to enable new research that could range from designing hardware up to discovery of new imaging application. The simulation system which could accurately model an imaging modality provides a platform for imaging developments that might be inconvenient in physical experiment systems due to the expense, unnecessary radiation exposures and technological difficulties. The aim of present study is to validate the Monte Carlo simulation of thyroid phantom imaging using Geant4-GATE for Siemen’s e-cam single head gamma camera. Upon the validation of the gamma camera simulation model by comparing physical characteristic such as energy resolution, spatial resolution, sensitivity, and dead time, the GATE simulation of thyroid phantom imaging is carried out. Methods: A thyroid phantom is defined geometrically which comprises of 2 lobes with 80mm in diameter, 1 hot spot, and 3 cold spots. This geometry accurately resembling the actual dimensions of thyroid phantom. A planar image of 500k counts with 128x128 matrix size was acquired using simulation model and in actual experimental setup. Upon image acquisition, quantitative image analysis was performed by investigating the total number of counts in image, the contrast of the image, radioactivity distributions on image and the dimension of hot spot. Algorithm for each quantification is described in detail. The difference in estimated and actual values for both simulation and experimental setup is analyzed for radioactivity distribution and dimension of hot spot. Results: The results show that the difference between contrast level of simulation image and experimental image is within 2%. The difference in the total count between simulation and actual study is 0.4%. The results of activity estimation show that the relative difference between estimated and actual activity for experimental and simulation is 4.62% and 3.03% respectively. The deviation in estimated diameter of hot spot for both simulation and experimental study are similar which is 0.5 pixel. In conclusion, the comparisons show good agreement between the simulation and experimental data.

Keywords: gamma camera, Geant4 application of tomographic emission (GATE), Monte Carlo, thyroid imaging

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Authors: Ben-Fred Ohia

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Code-switching and code-mixing are linguistic behaviours that arise in a bilingual situation. They limit speakers in a conversation to decide which code they should use to utter particular phrases or words in the course of carrying out their utterance. Every human society is characterized by the existence of diverse linguistic varieties. The speakers of these varieties at some points have various degrees of contact with the non-speakers of their variety, which one of the outcomes of the linguistic contact is code-switching or code-mixing. The work discusses the nature of code-switching and code-mixing in Ogba-English bilinguals’ speeches. It provides a detailed explanation of the concept of code-switching and code-mixing and explains the typology of code-switching and code-mixing and their manifestation in Ogba-English bilingual speakers’ speeches. The findings reveal that code-switching and code-mixing are functionally motivated and being triggered by various conversational contexts.

Keywords: bilinguals, code-mixing, code-switching, Ogba

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Authors: Viriyavudh Sim, Woo Young Jung

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The failure of roof cladding mostly occurs due to the failing of the connection between claddings and purlins, which is the pull-out of the screw connecting the two parts when the pull-out load, i.e. typhoon, is higher than the resistance of the connection screw. As typhoon disasters in Korea are constantly on the rise, probability risk assessment (PRA) has become a vital tool to evaluate the performance of civil structures. In this study, we attempted to determine the fragility of roof cladding with the screw connection. Experimental study was performed to evaluate the pull-out resistance of screw joints between honeycomb panels and back frames. Subsequently, by means of Monte Carlo Simulation method, probability of failure for these types of roof cladding was determined. The results that the failure of roof cladding was depends on their location on the roof, for example, the edge most panel has the highest probability of failure.

Keywords: Monte Carlo Simulation, roof cladding, screw pull-out strength, wind fragility

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Authors: Reza Reiazi

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Attempts to verify Geant4 hadronic physic to transport antiproton beam using standard physics list have not reach to a reasonable results because of lack of reliable cross section data or non reliable model to predict the final states of annihilated particles. Since most of the antiproton annihilation energy is carried away by recoiling nuclear fragments which are result of pions interactions with surrounding nucleons, it should be investigated if the toolkit verified for pions. Geant4 version 9.4.6.p01 was used. Dose calculation was done using 700 MeV pions hitting a water tank applying standards physic lists. We conclude Geant4 standard physics lists to predict the depth dose of Pion minus beam is not same for all investigated models. Since the nuclear fragments will deposit their energy in a small distance, they are the most important source of dose deposition in the annihilation vertex of antiproton beams.

Keywords: Monte Carlo, Pion, simulation, antiproton beam

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Authors: François Vallée, Jean-François Toubeau, Zacharie De Grève, Jacques Lobry

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When evaluating the capacity of a generation park to cover the load in transmission systems, traditional Loss of Load Expectation (LOLE) and Expected Energy not Served (EENS) indices can be used. If those indices allow computing the annual duration and severity of load non-covering situations, they do not take into account the fact that the load excess is generally shifted from one penury state (hour or quarter of an hour) to the following one. In this paper, a sequential Monte Carlo framework is introduced in order to compute adjusted LOLE and EENS indices. Practically, those adapted indices permit to consider the effect of load excess transfer on the global adequacy of a generation park, providing thus a more accurate evaluation of this quantity.

Keywords: expected energy not served, loss of load expectation, Monte Carlo simulation, reliability, wind generation

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Authors: Ashwani Kumar

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Use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function.

Keywords: NIR light, tissue, blurring, Monte Carlo simulation

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Authors: Seong Do Kim, Woo Young Jung

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Recently, damages due to typhoons and strong wind are on the rise. Considering this issue, we evaluated the performance of soundproofing walls based on the strong wind fragility by means of numerical analysis. Among the components of the soundproof wall, aluminum frame was the most vulnerable member, thus we have considered different section of aluminum frame in the determination of wind fragility. Wind load was randomly generated using Monte Carlo Simulation method. Moreover, limit state was based on the test standard of road construction soundproofing wall. In this study, the strong wind fragility was determined by considering the influence factors of wind exposure category, soundproof wall’s installation position, and shape of aluminum frame section. Results of this study could be used to determine the section shape of the frame that has high resistance to the wind during construction of the soundproofing wall.

Keywords: aluminum frame soundproofing wall, Monte Carlo simulation, numerical simulation, wind fragility

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Authors: N. Zandi, M. Sitarz, J. Jastrzebski, M. Vagheian, J. Choinski, A. Stolarz, A. Trzcinska

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¹³⁵La with the half-life of 19.5 h can be considered as a good candidate for Auger therapy. ¹³⁵La decays almost 100% by electron capture to the stable ¹³⁵Ba. In this study, all important possible reactions leading to ¹³⁵La production are investigated in details, and the corresponding theoretical yield for each reaction using the Monte-Carlo method (MCNPX code) are presented. Among them, the best reaction based on the cost-effectiveness and production yield regarding Poland facilities equipped with medical cyclotron has been selected. ¹³⁵La is produced using 16.5 MeV proton beam of general electric PET trace cyclotron through the ¹³⁵Ba(p,n)¹³⁵La reaction. Moreover, for a consistent facilitating comparison between the theoretical calculations and the experimental measurements, the beam current and also the proton beam energy is measured experimentally. Then, the obtained proton energy is considered as the entrance energy for the theoretical calculations. The production yield finally is measured and compared with the results obtained using the MCNPX code. The results show the experimental measurement and the theoretical calculations are in good agreement.

Keywords: efficient ¹³⁵La production, proton cyclotron energy measurement, MCNPX code, theoretical and experimental production yield

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Authors: Smail Tigani, Mohamed Ouzzif

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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: Asghar Ebrahimi, Elyas Lakzian

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For the analysis of flow inside micro geometries, classical CFD methods can not accurately predict the behavior of flow. Alternatively, the gas flow through micro geometries can be investigated precisely using the direct simulation Monte Carlo (DSMC) method. In the present paper, a pressure boundary condition is utilized to simulate a gaseous flow inside a micro channel using the DSMC method. Accuracy of simulation is guaranteed by choosing proper cell dimension and number of particle per cell analysis. Also, results of simulation are compared with the results of reliable references. Good agreement with results certifies the correctness of new boundary condition implemented on the micro channel.

Keywords: pressure boundary condition, DSMC, micro channel, cell dimension, particle per cell

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Authors: Balasundaram Prasaant, Ploix Stephane, Delinchant Benoit, Muresan Cristian

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Hardware in Loop (HIL) testing is done to test and validate a particular product especially in building technology. When it comes to building technology, it is more important to test the products for their efficiency. The test rig in the HIL simulator may contribute to some uncertainties on measured efficiency. The uncertainties include physical uncertainties and scenario-based uncertainties. In this paper, a simple uncertainty analysis framework for an HIL setup is shown considering only the physical uncertainties. The entire modeling of the HIL setup is done in Dymola. The uncertain sources are considered based on available knowledge of the components and also on expert knowledge. For the propagation of uncertainty, Monte Carlo Simulation is used since it is the most reliable and easy to use. In this article it is shown how an HIL setup can be modeled and how uncertainty propagation can be performed on it. Such an approach is not common in building energy analysis.

Keywords: energy in buildings, hardware in loop testing, modelica modelling, Monte Carlo simulation, uncertainty propagation

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Authors: L. Q. Yuan, J. Yang, A. Siddiqui

Abstract:

A new regression uncertainty analysis methodology was applied to determine the uncertainties of the critical heat flux (CHF) power correlation for an advanced 43-element bundle design, which was developed by Canadian Nuclear Laboratories (CNL) to achieve improved economics, resource utilization and energy sustainability. The new methodology is considered more appropriate than the traditional methodology in the assessment of the experimental uncertainty associated with regressions. The methodology was first assessed using both the Monte Carlo Method (MCM) and the Taylor Series Method (TSM) for a simple linear regression model, and then extended successfully to a non-linear CHF power regression model (CHF power as a function of inlet temperature, outlet pressure and mass flow rate). The regression uncertainty assessed by MCM agrees well with that by TSM. An equation to evaluate the CHF power regression uncertainty was developed and expressed as a function of independent variables that determine the CHF power.

Keywords: CHF experiment, CHF correlation, regression uncertainty, Monte Carlo Method, Taylor Series Method

Procedia PDF Downloads 392

Authors: Oh Hyeon Jeon, WooYoung Jung

Abstract:

In this study, seepage analysis was performed by the level difference between upstream and downstream of weir structure for safety evaluation of weir structure against flooding. Monte Carlo Simulation method was employed by considering the probability distribution of the adjacent ground parameter, i.e., permeability coefficient of weir structure. Moreover, by using a commercially available finite element program (ABAQUS), modeling of the weir structure is carried out. Based on this model, the characteristic of water seepage during flooding was determined at each water level with consideration of the uncertainty of their corresponding permeability coefficient. Subsequently, fragility function could be constructed based on this response from numerical analysis; this fragility function results could be used to determine the weakness of weir structure subjected to flooding disaster. They can also be used as a reference data that can comprehensively predict the probability of failur,e and the degree of damage of a weir structure.

Keywords: weir structure, seepage, flood disaster fragility, probabilistic risk assessment, Monte-Carlo simulation, permeability coefficient

Procedia PDF Downloads 324

Authors: Ding Jue, Li Jiahua, Lei Zhidi, Weng Peifen, Li Xiaowei

Abstract:

With the rapid development of national modern industry, people begin to pay attention to environmental pollution and harm caused by industrial dust. Based on above, a numerical study on the dedusting technology of industrial environment was conducted. The dynamic models of multicomponent particles collision and coagulation, breakage and deposition are developed, and the interaction of water droplet and aerosol particle in 2-Dimension flow field was researched by Eulerian-Lagrangian method and Multi-Monte Carlo method. The effects of the droplet scale, movement speed of droplet and the flow field structure on scavenging efficiency were analyzed. The results show that under the certain condition, 30μm of droplet has the best scavenging efficiency. At the initial speed 1m/s of droplets, droplets and aerosol particles have more time to interact, so it has a better scavenging efficiency for the particle.

Keywords: water droplet, aerosol particle, collision and coagulation, multi-monte carlo method

Procedia PDF Downloads 281