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Highlights • A parameterized SILs verification approach is proposed on baseline of IEC61508. • Fully correctness proving is done by implementing and comparing with IEC61508-6. • Parametric features facilitate model reuse in large-scale, complex systems. • PFH relies on the balance between CCF and the number of the redundancy channels. • Systems with static components can be simulated by this approach. Abstract The paper proposed an approach of verifying the Safety Integrity Level (SIL) for the high demand safety system. This approach is based on the Stochastic Petri Nets models and Monte Carlo simulation (SPN-MC) and follows the requirements of IEC61508, which is a commonly accepted standard in the domain of functional safety of programmable electronic and control engineering systems. The paper provides a comparative analysis of the SIL with the application of SPN-MC and the Reliability Block Diagram (RBD) method given by EN61508 to prove the correctness and feasibility of the SPN-MC approach. Additionally, a typical large scaled complex system was adopted to apply the novel approach, which is hard for classical analytical methods. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic DG planning problem considering uncertainties related to the intermittent nature of the DG technologies such as wind turbines and solar units in addition to the stochastic economic conditions. The stochastic economic situation includes the uncertainties related to the fuel and electricity price of each year. The Monte Carlo simulation is used to generate the possible scenarios of uncertain situations and the produced scenarios are reduced through backward reduction program. The aim of this paper is to maximize the revenue of the distribution system through the benefit cost analysis alongside the encouraging and punishment functions. In order to close to reality, the different growth rates for the planning period are selected. In this paper the Covariance Matrix Adaptation Evolutionary Strategy is introduced and is used to find the best planning scheme of the DG units. The different DG types are considered in the planning problem. The main assumption of this paper is that the DISCO is the owner of the distribution system and the DG units. The proposed method is tested on a 9 bus test distribution system and the results are compared with the known genetic algorithm and PSO methods to show the applicability of the CMAES method in this problem. [ABSTRACT FROM AUTHOR]

In the paper we compare several parameterized estimators for the positive extreme value index, which is a very important parameter appearing in the estimation of the probability of rare events. Firstly, asymptotic comparison at optimal levels of the corresponding tail index estimators is performed. Secondly, the practical validation of asymptotic results for moderate finite samples is done by means of Monte-Carlo simulations. We demonstrate that theoretical domination of the positive extreme value index estimators, which are asymptotically normal with a null asymptotic bias, is not reflected in Monte-Carlo simulations. Moreover, the estimators of such type do not demonstrate stability in the sense of empirical mean-squared error. [ABSTRACT FROM AUTHOR]

Abstract: In a dynamically changing environment, the manager of a maintenance and remodeling (M/R) program is confronted with an increasing complexity of coordinating and cooperating multi-resource constrained multiple projects. Uncertainty and interdependence are sources of the complexity, and cause an internal disruption of an activity and chain reactions of disturbance propagation that deteriorate the stability and manageability of the program. This paper evaluates previous endeavors to apply production control and management techniques to the construction industry, and investigates the possibility of applying other production concepts and theories to organizational program management. In particular, this paper proposes a buffer allocation strategy by which periodic buffers are allocated in the flows of program constraint resources (PCRs) to stabilize a master construction schedule instead of protecting individual activities. Comparative experiments by Monte Carlo simulations illustrate better performance of the proposed strategy in terms of program goals: productivity, flexibility, and long-term stability. [Copyright &y& Elsevier]

The Bayesian method is widely used to identify a joint distribution, which is modeled by marginal distributions and a copula. The joint distribution can be identified by one-step procedure, which directly tests all candidate joint distributions, or by two-step procedure, which first identifies marginal distributions and then copula. The weight-based Bayesian method using two-step procedure and the Markov chain Monte Carlo (MCMC)-based Bayesian method using one-step and two-step procedures were recently developed. In this paper, the one-step weight-based Bayesian method and two-step MCMC-based Bayesian method using the parametric marginal distributions are proposed. Comparison studies among the Bayesian methods have not been thoroughly carried out. In this paper, the weight-based and MCMC-based Bayesian methods using one-step and two-step procedures are compared to see which Bayesian method accurately and efficiently identifies a correct joint distribution through simulation studies. It is validated that the two-step weight-based Bayesian method has the best performance. [ABSTRACT FROM AUTHOR]

Simulation of the behavior of the plate-type research reactors such as JRR-3M and CARR poses a challenge for traditional neutronics calculation tools and schemes for power reactors, due to the characteristics of complex geometry, highly heterogeneity and large leakage of the research reactors. Two different theoretical approaches, the deterministic and the stochastic methods, are used for the neutronics analysis of the JRR-3M plate-type research reactor in this paper. For the deterministic method the neutronics codes DRAGON and DONJON are used, while the continuous-energy Monte Carlo code RMC (Reactor Monte Carlo code) is employed for the stochastic approach. The goal of this research is to examine the capability of the deterministic code system DRAGON and DONJON to reliably simulate the research reactors. The results indicate that the DRAGON and DONJON code system agrees well with the continuous-energy Monte Carlo simulation on both k eff and flux distributions if the appropriate treatments (such as the ECCO option) are applied. [ABSTRACT FROM AUTHOR]

Purpose: Yittrium-90 (90Y) is traditionally thought of as a pure beta emitter, and is used in targeted radionuclide therapy, with imaging performed using bremsstrahlung single-photon emission computed tomography (SPECT). However, because 90Y also emits positrons through internal pair production with a very small branching ratio, positron emission tomography (PET) imaging is also available. Because of the insufficient image quality of 90Y bremsstrahlung SPECT, PET imaging has been suggested as an alternative. In this paper, the authors present the Monte Carlo-based simulation-reconstruction framework for 90Y to comprehensively analyze the PET and SPECT imaging techniques and to quantitatively consider the disadvantages associated with them. Methods: Our PET and SPECT simulation modules were developed using Monte Carlo simulation of Electrons and Photons (MCEP), developed by Dr. S. Uehara. PET code (MCEP-PET) generates a sinogram, and reconstructs the tomography image using a time-of-flight ordered subset expectation maximization (TOF-OSEM) algorithm with attenuation compensation. To evaluate MCEP-PET, simulated results of 18F PET imaging were compared with the experimental results. The results confirmed that MCEP-PET can simulate the experimental results very well. The SPECT code (MCEP-SPECT) models the collimator and NaI detector system, and generates the projection images and projection data. To save the computational time, the authors adopt the prerecorded 90Y bremsstrahlung photon data calculated by MCEP. The projection data are also reconstructed using the OSEM algorithm. The authors simulated PET and SPECT images of a water phantom containing six hot spheres filled with different concentrations of 90Y without background activity. The amount of activity was 163 MBq, with an acquisition time of 40 min. Results: The simulated 90Y-PET image accurately simulated the experimental results. PET image is visually superior to SPECT image because of the low background noise. The simulation reveals that the detected photon number in SPECT is comparable to that of PET, but the large fraction (approximately 75%) of scattered and penetration photons contaminates SPECT image. The lower limit of 90Y detection in SPECT image was approximately 200 kBq/ml, while that in PET image was approximately 100 kBq/ml. Conclusions: By comparing the background noise level and the image concentration profile of both the techniques, PET image quality was determined to be superior to that of bremsstrahlung SPECT. The developed simulation codes will be very useful in the future investigations of PET and bremsstrahlung SPECT imaging of 90Y. [ABSTRACT FROM AUTHOR]

The Birnbaum–Saunders (BS) distribution is a positively skewed distribution, frequently used for analysing lifetime data. In this paper, we propose a simple method of estimation for the parameters of the two-parameter BS distribution by making use of some key properties of the distribution. Compared with the maximum likelihood estimators and the modified moment estimators, the proposed method has smaller bias, but having the same mean square errors as these two estimators. We also discuss some methods of construction of confidence intervals. The performance of the estimators is then assessed by means of Monte Carlo simulations. Finally, an example is used to illustrate the method of estimation developed here. [ABSTRACT FROM AUTHOR]

In this paper, we have reviewed 25 test procedures that are widely reported in the literature for testing the hypothesis of homogeneity of variances under various experimental conditions. Since a theoretical comparison was not possible, a simulation study has been conducted to compare the performance of the test statistics in terms of robustness and empirical power. Monte Carlo simulation was performed for various symmetric and skewed distributions, number of groups, sample size per group, degree of group size inequalities, and degree of variance heterogeneity. Using simulation results and based on the robustness and power of the tests, some promising test statistics are recommended for practitioners. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we study the depth at which a cosmic ray shower reaches its maximum ( ) as predicted by Monte Carlo simulation. The use of in the determination of the primary particle mass can only be done by comparing the measured values with simulation predictions. For this reason it is important to study the differences between the available simulation models. We have done a study of the first and second moments of the distribution using the Corsika and Conex programs. The study was done with high statistics in the energy range from to eV. We focus our analysis in the different implementations of the hadronic interaction models Sibyll2.1 and QGSJetII in Corsika and Conex. We show that the predictions of the and RMS depend slightly on the combination of simulation program and hadronic interaction model. Although these differences are small, they are not negligible in some cases (up to 5g/cm2 for the worse case) and they should be considered as a systematic uncertainty of the model predictions for and RMS . We have included a table with the suggested systematic uncertainties for the model predictions. Finally, we present a parametrization of the distribution as a function of mass and energy according to the models Sibyll2.1 and QGSJetII, and showed an example of its application to obtain the predicted distributions from cosmic ray propagation models. [Copyright &y& Elsevier]

Abstract: An environmental impact assessment model for secondary batteries under uncertainty is proposed, which is a combination of the life cycle assessment (LCA), Eco-indicator 99 system and Monte Carlo simulation (MCS). The LCA can describe the environmental impact mechanism of secondary batteries, whereas the cycle performance was simulated through MCS. The composite LCA–MCS model was then carried out to estimate the environmental impact of two kinds of experimental batteries. Under this kind of standard assessment system, a comparison between different batteries could be accomplished. The following results were found: (1) among the two selected batteries, the environmental impact of the Li-ion battery is lower than the nickel–metal hydride (Ni–MH) battery, especially with regards to resource consumption and (2) the lithium ion (Li-ion) battery is less sensitive to cycle uncertainty, its environmental impact fluctuations are small when compared with the selected Ni–MH battery and it is more environmentally friendly. The assessment methodology and model proposed in this paper can also be used for any other secondary batteries and they can be helpful in the development of environmentally friendly secondary batteries. [Copyright &y& Elsevier]

Abstract: We have extended our previous experimental and Monte–Carlo work on the detection of Gd by in vivo prompt gamma neutron activation analysis to include X ray emission. In this paper we incorporate the characteristic K X ray emission that occurs due to internal conversion from the de-excitation of the 155Gd(n,γ)156Gd∗ and 157Gd(n,γ)158Gd∗ reactions. The experimental Gd K X ray intensities are compared with the Monte–Carlo model and demonstrate excellent agreement. The experiment was consistently higher than simulation by 5%. For the detection system used, the Gd K α X rays are about 1.5 times as intense as the most dominant prompt gamma ray from the 157Gd(n,γ) reaction. The partial elemental cross section for K α X ray emission is ∼1.35 times larger than that of the most dominant prompt gamma ray from neutron capture of 157Gd alone. The use of the K X rays was found to improve the sensitivity of the proposed system to measure Gd retention after exposure to a Gd-based MRI contrast agent. The detection limit in phantoms was ∼30% better when the X ray signal was incorporated into the analysis method, reducing the detection limit from 0.89 to 0.64ppm Gd. [Copyright &y& Elsevier]

One of the critical limits on the sensitivity of direct neutrino mass experiment, such as MARE, is the background generated by unidentified double pulses. In our work developing an analysis system for MARE we have focused on comparing algorithms, and developing and testing an optimum algorithm for the identification (and removal) of double pulses. To test the algorithms we developed a Monte Carlo simulation that, based on the detectors physical parameters, generates realistic single and double events with known characteristics. In this paper we present our preliminary results on two algorithms used for double pulse identification and their efficiency as a function of pulse heights and separation. [ABSTRACT FROM AUTHOR]

In this paper, we consider the bootstrap procedure for the augmented Dickey–Fuller (ADF) unit root test by implementing the modified divergence information criterion (MDIC, Mantalos et al. [An improved divergence information criterion for the determination of the order of an AR process, Commun. Statist. Comput. Simul. 39(5) (2010a), pp. 865–879; Forecasting ARMA models: A comparative study of information criteria focusing on MDIC, J. Statist. Comput. Simul. 80(1) (2010b), pp. 61–73]) for the selection of the optimum number of lags in the estimated model. The asymptotic distribution of the resulting bootstrap ADF/MDIC test is established and its finite sample performance is investigated through Monte-Carlo simulations. The proposed bootstrap tests are found to have finite sample sizes that are generally much closer to their nominal values, than those tests that rely on other information criteria, like the Akaike information criterion [H. Akaike, Information theory and an extension of the maximum likelihood principle, in Proceedings of the 2nd International Symposium on Information Theory, B.N. Petrov and F. Csáki, eds., Akademiai Kaido, Budapest, 1973, pp. 267–281]. The simulations reveal that the proposed procedure is quite satisfactory even for models with large negative moving average coefficients. [ABSTRACT FROM PUBLISHER]

Adiabatic quantum optimization offers a new method for solving hard optimization problems. In this paper we calculate median adiabatic times (in seconds) determined by the minimum gap during the adiabatic quantum optimization for an NP-hard Ising spin glass instance class with up to 128 binary variables. Using parameters obtained from a realistic superconducting adiabatic quantum processor, we extract the minimum gap and matrix elements using high performance Quantum Monte Carlo simulations on a large-scale Internet-based computing platform. We compare the median adiabatic times with the median running times of two classical solvers and find that, for the considered problem sizes, the adiabatic times for the simulated processor architecture are about 4 and 6 orders of magnitude shorter than the two classical solvers' times. This shows that if the adiabatic time scale were to determine the computation time, adiabatic quantum optimization would be significantly superior to those classical solvers for median spin glass problems of at least up to 128 qubits. We also discuss important additional constraints that affect the performance of a realistic system. [ABSTRACT FROM AUTHOR]

In this paper, influence of crowding by inert particles on the geminate reaction kinetics is theoretically investigated. Time evolution equations for the survival probability of a geminate pair are derived from the master equation taking into account the correlation among all diffusing particles, and the results are compared with those obtained by Monte Carlo simulations. In general, excluded volume interactions by the inert particles slow down the diffusive motion of reactants. However, when the initial concentration of the inert particles is uniform and high, we show that additional influence of interference between reaction and correlated diffusion accelerates the transient decay of the survival probability in the diffusion-controlled limit. We also study the escape probability for a nonuniform initial distribution of the inert particles by taking the continuous limit in space. We show that reaction yield is increased when the reaction proceeds in the presence of a positive density gradient of the inert particles which inhibits the escape of reactants. The effect can be interpreted as a cage effect. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the problem of tackling uncertainty in the prediction of postprandial blood glucose is analyzed. Two simulation approaches, Monte Carlo and interval models, are studied and compared. Interval simulation is carried out using modal interval analysis. Simulation of a glucoregulatory model with uncertainty in insulin sensitivities, glucose absorption and food intake is carried out using both methods. Interval simulation is superior in predicting all severe and mild hyper- and hypoglycemia episodes. Furthermore, much less computational time is required for interval simulation than for Monte Carlo simulation. [Copyright &y& Elsevier]

Abstract: This paper proposes and compares two new sampling schemes for sparse deconvolution using a Bernoulli–Gaussian model. To tackle such a deconvolution problem in a blind and unsupervised context, the Markov Chain Monte Carlo (MCMC) framework is usually adopted, and the chosen sampling scheme is most often the Gibbs sampler. However, such a sampling scheme fails to explore the state space efficiently. Our first alternative, the K-tuple Gibbs sampler, is simply a grouped Gibbs sampler. The second one, called partially marginalized sampler, is obtained by integrating the Gaussian amplitudes out of the target distribution. While the mathematical validity of the first scheme is obvious as a particular instance of the Gibbs sampler, a more detailed analysis is provided to prove the validity of the second scheme. For both methods, optimized implementations are proposed in terms of computation and storage cost. Finally, simulation results validate both schemes as more efficient in terms of convergence time compared with the plain Gibbs sampler. Benchmark sequence simulations show that the partially marginalized sampler takes fewer iterations to converge than the K-tuple Gibbs sampler. However, its computation load per iteration grows almost quadratically with respect to the data length, while it only grows linearly for the K-tuple Gibbs sampler. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a simple analytical formulation for the dispersion relationship of extended electronic states in Graphene Nano-Ribbons (GNRs). The model has been validated by comparison with Tight-Binding calculation of GNRs in the presence of edge disorder. The model is suited for inclusion in semiclassical models for GNRs featuring widths down to approximately 2nm. Monte-Carlo simulations accounting for phonons and edge roughness scattering are then used to understand the ribbon width of the low-field mobility. The mechanisms responsible for the low mobility values measured in narrow ribbons compared to graphene sheets are the increased phonon scattering rate and mobility effective mass due to the strong band structure modification induced by the reduced lateral dimensions and the increased scattering with the edges. However, scattering with phonons and with edges is not sufficient to reproduce the experimental mobility on insulating substrates, suggesting that the effect of remote polar phonons originating in the substrate can be significant in graphene based devices. [Copyright &y& Elsevier]

Abstract: Weighted histograms in Monte Carlo simulations are often used for the estimation of probability density functions. They are obtained as a result of random experiments with random events that have weights. In this paper, the bin contents of a weighted histogram are considered as a sum of random variables with a random number of terms. Generalizations of the classical chi-square test for comparing weighted histograms are proposed. Numerical examples illustrate an application of the tests for the histograms with different statistics of events and different weighted functions. The proposed tests can be used for the comparison of experimental data histograms with simulated data histograms as well as for the two simulated data histograms. [Copyright &y& Elsevier]

Abstract: This paper presents the formulation of PDS-FEM (particle discretization scheme finite element method) in three dimensional setting and Monte-Carlo simulation of crack propagation by PDS-FEM. The probability density function of the crack paths in a plate with two parallel initial cracks located in an anti-symmetric manner is computed in order to evaluate the statistical and spatial distribution of the crack paths, and it is shown that the crack path in an ideally homogeneous plate is unstable. The simulation results are compared with experimental data. Besides, Monte-Carlo simulation of crack propagation in a heterogeneous elasto-plastic cylinder (as a simplified model of concrete) under uniaxial tension has been carried out and its statistical behavior is discussed. [Copyright &y& Elsevier]

Summary: This paper compares two Monte Carlo sequential data assimilation methods based on the Kalman filter, for estimating the effect of measurements on simulations of state error variance made by a one-dimensional hydrodynamic model. The first method used an ensemble Kalman filter (EnKF) to update state estimates, which were then used as initial conditions for further simulations. The second method used an ensemble transform Kalman filter (ETKF) to quickly estimate the effect of measurement error covariance on forecast error covariance without the need to re-run the simulation model. The ETKF gave an unbiased estimate of EnKF analysed error variance, although differences in the treatment of measurement errors meant the results were not identical. Estimates of forecast error variance could also be made, but their accuracy deteriorated as the time from measurements increased due in part to model non-linearity and the decreasing signal variance. The motivation behind the study was to assess the ability of the ETKF to target possible measurements, as part of an adaptive sampling framework, before they are assimilated by an EnKF-based forecasting model on the River Crouch, Essex, UK. The ETKF was found to be a useful tool for quickly estimating the error covariance expected after assimilating measurements into the hydrodynamic model. It, thus, provided a means of quantifying the ‘usefulness’ (in terms of error variance) of possible sampling schemes. [Copyright &y& Elsevier]

Abstract: 68Ga is an important radionuclide for positron emission tomography. 68Ga can be produced by the 68Zn(p,n)68Ga reaction in a common biomedical cyclotrons. To facilitate optimization of target design and study activation of materials, Monte Carlo code can be used to simulate the irradiation of the target materials with charged hadrons. In this paper, FLUKA code simulation was employed to prototype a Zn target for the production of 68Ga by proton irradiation. Furthermore, the experimental data were compared with the estimated values for the thick target yield produced in the irradiation time according to FLUKA code. In conclusion, FLUKA code can be used for estimation of the production yield. [Copyright &y& Elsevier]

The paper addresses the problem of adaptive manoeuvring targets tracking in clutter with a phased array radar. The tracking algorithm is based on the combination of the interacting multiple models (IMM) algorithm and the joint probabilistic data association filter (JPDAF), the resulting algorithm is named IMMJPDAF algorithm. Moreover, the phased array radar is a multifunction radar with the capability to select adaptively the sampling time interval; consequently, the tracking performance is improved. First, a complete comparative study between the IMMJPDAF algorithm and the multirate IMMJPDAF (MRIMMJPDAF) algorithm for tracking close manoeuvring targets with varying amounts of clutter density is presented. Then a description is made of the integration of a new fast method into the IMMJPDAF algorithm to adaptively select the next update time according to the targets motions. We call the resulting algorithm, the fast adaptive IMMJPDAF (FAIMMJPDAF) algorithm. Furthermore, an enhancement of the tracking accuracy in the FAIMMJPDAF algorithm is made by also taking into account the separation distance between targets in the selection of the next update time. The performance of the proposed algorithm, named improved fast adaptive IMMJPDAF (IFAIMMJPDAF) algorithm is assessed via Monte Carlo Simulations and compared with that of four algorithms that use an adaptive selection of the update time: FAIMMJPDAF algorithm, the adaptive IMMJPDAF that uses a modified version of the van Keuk criterion (MAIMMJPDAF), the adaptive IMMJPDAF that uses the original van Keuk method (AIMMJPDAF), and the IMMJPDAF (CIMMJPDAF) that uses a constant update time. [ABSTRACT FROM AUTHOR]