Simple Monte Carlo Simulation Research Articles

Dose calculation of 3D printing lead shield covered by biocompatible silicone for electron beam therapy.

This study aims to calculate the dose delivered to the upstream surface of a biocompatible flexible absorber covering lead for electron beam treatment of skin and subcutaneous tumour lesions for head and neck. Silicone (Ecoflex™ 00-30, Smooth-On, Easton, PA, USA) was used to cover the lead to absorb backscattered electrons from lead. A 3D printer (Zortrax M300, Zortrax, Olsztyn, Poland) was used to fabricate the lead shield. Analytic calculation, simplified Monte Carlo (MC) simulation, and detailed MC simulation which includes a modeling of metal-oxide-semiconductor field-effect transistor (MOSFET) detector were performed to determine the electron backscatter factor (EBF) for 6MeV and 9MeV electron beams of a Varian iX Silhouette. MCNP6.2 was used to calculate the EBF and corresponding measurements were carried out by using MOSFET detectors. The EBF was experimentally measured by the ratio of dose at the upstream surface of the silicone to the same point without the presence of the lead shield. The results derived by all four methods agreed within 2.8% for 6MeV and 3.4% for 9MeV beams. In detailed MC simulations, for 6MeV, dose to the surface of 7-mm-thick absorber was 103.7 [Formula: see text] 1.9% compared to dose maximum (Dmax) without lead. For 9MeV, the dose to the surface of the 10-mm-thick absorber was 104.1 [Formula: see text] 2.1% compared to Dmax without lead. The simplified MC simulation was recommended for practical treatment planning due to its acceptable calculation accuracy and efficiency. The simplified MC simulation was completed within 20min using parallel processing with 80 CPUs, while the detailed MC simulation required 40h to be done. In this study, we outline the procedures to use the lead shield covered by silicone in clinical practice from fabrication to dose calculation.

The effect of unequal constrained at branching point on phase diagrams

The effect of unequal constrained at branching point on phase diagrams is investigated by a totally asymmetric simple exclusion process (TASEP). At the junction point, the chosen rates of the two branches are r 1/2 and r 2/2, respectively. Based on simple mean field theory and Monte Carlo simulations, the phase diagrams and density profiles attached to the ratio n (n = r 1/r 2) and r 2 are investigated. When the chosen rates are under the unequal constrained condition, there are two thresholds and leading to the obvious difference of phase diagrams. Additionally, the area functions and saturation point pairs of current, n and r 2 are given to predict the alterations of the phase boundaries. An optimal parameter n = r 2 = 0.8 is found to ensure the probability of traffic congestion reaches the minimum level in our model. All outcomes of theory and simulations related to density profiles and phase diagrams are in good agreement.

HD 142527: quantitative disk polarimetry with SPHERE

Aims. We present high-precision photometry and polarimetry based on visual and near-infrared imaging data for the protoplanetary disk surrounding the Herbig Ae/Be star HD 142527, with a strong focus on determining the light scattering parameters of the dust located at the surface of the large outer disk. Methods. We re-reduced existing polarimetric differential imaging data of HD 142527 in the VBB (735 nm) and H-band (1625 nm) from the ZIMPOL and IRDIS subinstruments of SPHERE at the VLT. With polarimetry and photometry based on reference star differential imaging (RDI), we were able to measure the linearly polarized intensity and the total intensity of the light scattered by the circumstellar disk with high precision. We used simple Monte Carlo simulations of multiple light scattering by the disk surface to derive constraints for three scattering parameters of the dust: the maximum polarization of the scattered light Pmax, the asymmetry parameter g, and the single-scattering albedo ω. Results. We measure a reflected total intensity of 51.4 ± 1.5 mJy and 206 ± 12 mJy and a polarized intensity of 11.3 ± 0.3 mJy and 55.1 ± 3.3 mJy in the VBB and H-band, respectively. We also find in the visual range a degree of polarization that varies between 28% on the far side of the disk and 17% on the near side. In the H-band, the degree of polarization is consistently higher by about a factor of 1.2. The disk also shows a red color for the scattered light intensity and the polarized intensity, which are about twice as high in the near-infrared when compared to the visual. We determine with model calculations the scattering properties of the dust particles and find evidence for strong forward scattering (g ≈ 0.5–0.75), relatively low single-scattering albedo (ω ≈ 0.2–0.5), and high maximum polarization (Pmax ≈ 0.5–0.75) at the surface on the far side of the disk for both observed wavelengths. The optical parameters indicate the presence of large aggregate dust particles, which are necessary to explain the high maximum polarization, the strong forward-scattering nature of the dust, and the observed red disk color.

Predicting the stochastic behavior of uncertainty sources in planning a stand-alone renewable energy-based microgrid using Metropolis–coupled Markov chain Monte Carlo simulation

Due to the lack of available flexibility sources to cope with different uncertainties in the real-time operation of stand-alone renewable energy-based microgrids, the stochastic behavior of uncertainty sources needs to be included in the planning stage. Since there is a high association between some of the uncertainty sources, defining a proper time series to represent the behavior of each source of uncertainty is a challenging issue. Consequently, uncertainty sources should be modeled in such a way that the designed microgrid be able to cope with all scenarios from probability and impact viewpoints. This paper proposes a modified Metropolis–coupled Markov chain Monte Carlo (MC)3 simulation to predict the stochastic behavior of different uncertainty sources in the planning of a stand-alone renewable energy-based microgrid. Solar radiation, wind speed, the water flow of a river, load consumption, and electricity price have been considered as primary sources of uncertainty. A novel data classification method is introduced within the (MC)3 simulation to model the time-dependency and the association between different uncertainty sources. Moreover, a novel curve-fitting approach is proposed to improve the accuracy of representing the multimodal distribution functions, modeling the Markov chain states, and the long-term probability of uncertainty sources. The predicted representative time series with the proposed modified (MC)3 model is benchmarked against the retrospective model, the long-term historical data, and the simple Monte Carlo simulation model to capture the stochastic behavior of uncertainty sources. The results show that the proposed model represents the probability distribution function of each source of uncertainty, the continuity of samples, time dependency, the association between different uncertainty sources, short-term and long-term trends, and the seasonality of uncertainty sources. Finally, results confirm that the proposed modified (MC)3 can appropriately predict all scenarios with high probability and impact.

Surface and Grain Boundary Effect in the Local Ionic Transport of (La,Sr)(Co,Fe)O3 Observed By in Situ Scanning Probe Microscopy

Ionic transport in solid oxides lays the fundamentals of solid-state electrochemical energy and sensor devices. The transport is understood as a thermally activated hopping of point defects (i.e. oxygen vacancies), and its kinetics is highly dependent upon the bonding state of the ionic species with their surrounding lattice environment. While the heterogeneous ionic transport in polycrystalline oxides has been studied for decades, the exact role of interfaces and surfaces in the transport is still an open question.In this presentation, we report our recent effort to directly observe the ionic transport in (La,Sr)(Co,Fe)O3 (LSCF), the most widely used cathode material for intermediate temperature solid oxide fuel cells, by the use of Kelvin probe force microscopy (KPFM) and conductive atomic force microscopy (CAFM). By providing a positive bias to the tip-LSCF contact in a CAFM mode, oxygen vacancies are generated via oxygen evolution reaction and the amount of newly formed oxygen vacancies are quantified by measuring the total charge transferred during the bias application. Subsequently, the evolution of charge distribution (and thus the distribution of oxygen vacancies) are observed by KPFM at various temperatures. The resulting KPFM maps were analyzed to gauge the heterogeneous ionic transport, in particular, around the grain boundary (GB) areas, and the effective ionic diffusivity within each grain and across GBs were to quantified. From this practice, a direct observation of charge transport was made to confirm the ionic diffusion across GBs is indeed much slower than those within each GB, and the effective resistance in ionic transport through GB was quantified.In addition, 3D KPFM maps were also acquired by an in situ etching with a diamond-coated tip, providing the charge distribution map with depth. From this, it was directly observed that the ionic transport along the surface (~5 nm) is significantly higher than the transport through the interior of a grain. In combination with a simplified Monte Carlo simulation, the ionic diffusivity and its activation energy were quantified for both surface and bulk diffusion, respectively.The authors acknowledge the support by U.S. National Science Foundation CAREER Award (DMR 1753383).

Monitoring the long term stability of civil buildings through the MRPC telescopes of the EEE Project

Cosmic ray muons are a penetrating component of extensive air showers created in the Earth atmosphere by the interaction of highly energetic primary particles, mostly protons, which continuously bombard our Planet. The secondary cosmic radiation is the result of the complex interplay between the production cross section and the interaction mechanisms with the atmosphere (including the energy loss, multiple scattering and particle decay). Cosmic muons have been considered since several decades as a powerful probe to exploit our environment, from muography of volcanoes to absorption radiography of possible hidden rooms inside large structures, such as Pyramids, to the detection of high-Z illicit nuclear materials inside containers and many other applications of social interest.This paper discusses the possibility to employ the Multigap Resistive Plate Chambers (MRPC) of the Extreme Energy Events (EEE) Project as muon tracking detectors to monitor the long term stability of civil buildings and structures when used in conjunction with additional detectors. For this application the average direction of the cosmic muon tracks passing through the MRPC telescope and an additional detector located some distance apart in the same building may be reconstructed with good precision and any small variation over long time acquisition periods may be monitored. The performance of such setup is discussed and experimental results from first coincidence measurements obtained with a 40 × 60 cm2 scintillator detector operated in the same building with one of the EEE telescopes, at about 15 m vertical distance from it, are presented. Simple Monte Carlo and GEANT simulations were also carried out to evaluate typical acceptance values for the operating conditions employed so far, to extrapolate to other geometrical configurations, and to evaluate multiple scattering effects.

Control of Lateral Composition Distribution in Graded Films of Soluble Solid Systems A1−xBx by Partitioned Dual-Beam Pulsed Laser Deposition

Lateral compositionally-graded thin films are powerful media for the observation of phase boundaries as well as for high-throughput materials exploration. We herein propose a method to prepare epitaxial lateral compositionally-graded films using a dual-beam pulsed laser deposition (PLD) method with two targets separated by a partition. Tuning the ambient pressure and the partition—substrate gap makes it possible to control of the gradient length of the deposits at the small sizes (≤ 10 mm) suitable for commercial oxide single crystal substrates. A simple Monte Carlo simulation qualitatively reproduced the characteristic features of the lateral thickness distribution. To demonstrate this method, we prepared (1−x)PbTiO3—xPbZrO3 and (1−x)LaMnO3—xLa0.6Sr0.4MnO3 films with lateral composition gradient widths of 10 and 1 mm, respectively, with the partitioned dual PLD.

Opportunistic Constant Target Matching—A New Method for Satellite Intercalibration

AbstractOpportunistic constant target matching is a new method for satellite intercalibration. It solves a long‐standing issue with the traditional simultaneous nadir overpass (SNO) method, namely, that it typically provides only data points with cold brightness temperatures for humidity sounding instruments on sun‐synchronous satellites. In the new method, a geostationary infrared sensor (SEVIRI) is used to select constant target matches for two different microwave sensors (MHS on NOAA 18 and Metop A). We discuss the main assumptions and limitations of the method and explore its statistical properties with a simple Monte Carlo simulation. The method was tested in a simple case study with real observations for this combination of satellites for MHS Channel 3 at 183 ± 1 GHz, the upper tropospheric humidity channel. For the studied 3‐month test period, real observations are found to behave consistently with the simulations, increasing our confidence that the method can be a valuable tool for intercalibration efforts. For the selected case study, the new method confirms that the bias between NOAA 18 and Metop A MHS Channel 3 is very small, with absolute value below 0.05 K.

Minimum Volume Confidence Regions for Parameters of Exponential Distributions from Different Samples

Independent samples from different exponential distributions are available in many statistical applications, for example, in queuing or reliability models, where the random variables describe waiting times and lifetimes, respectively. When two samples are observed, inference is then carried out for two location and two scale parameters. In multivariate setups including common location and common scale parameter assumptions, we provide confidence regions for the parameters of interest, which have minimum Lebesgue measure among all those based on the usual pivotal quantities and with the same or higher confidence level; in particular, they improve in terms of area (volume) upon the standard ‘trapezoidal’ confidence regions being constructed by combining independent univariate pivot statistics. The proposed confidence regions do not require any factorization of the overall confidence level, and their calculations need simple Monte Carlo simulations, only. Although focusing on two complete samples, generalizations of the results to more than two and doubly type-II censored samples are possible.

Stochastic analysis of concrete dams with alkali aggregate reaction

Following a comprehensive literature survey, this paper will first address the theoretical underpinnings of stochastic modeling. An algorithm to model arch dam inhomogeneity in terms of characteristic length is presented next and is applied to assess the impact of concrete's elastic modulus and volumetric AAR expansion. Results are contrasted with both a single deterministic analysis, and a series of classical Monte Carlo simulations in which non-Gaussian stochastically varying properties are used.The impact of randomness in material properties on displacements, joint openings, and stresses are investigated. It is found that whereas mean values of these responses are for the most part little impacted, standard deviations exhibit a greater variation vis a vis simple Monte Carlo simulations. Furthermore, the safety is assessed through fragility surfaces, and meta-modeling. This study determined that whereas randomness may affect local results e.g. stresses, their impact may be neglected for globally averaged responses e.g. displacements.

A simple lattice Monte Carlo simulation to model interfacial and crowded water rearrangements

A finite, two-dimensional lattice model of liquid water captures the essential nearly four-coordinate hydrogen bonding network, while permitting a simple Metropolis Monte Carlo simulation in conditions ranging from crowded to dilute. This model examines excluded volume perturbations of hydrogen bond switching, avoiding complex topological and chemical heterogeneity of realistic interfaces. Retardation factors (relative to bulk) for switching agree with previous statistical models and atomistic molecular dynamics simulations of hydrated proteins. The model enables straightforward spatial mapping of retardation factors that are difficult to measure in atomistic simulations. The spatially-dependent retardation factors decrease exponentially from the interface. Simulating varying degrees of crowding, we do not find any cooperative, collective contributions anticipated from some recent spectroscopic observations suggesting correlated hydrogen bonding rearrangements of confined water. Longer-range cooperative interfacial influences may arise from complex chemical patterning of the surface, or to non-entropic influences such as multi-body interactions or altered hydrogen bond strengths.

(Invited) Characterization of Isotropic Thermal ALE of Oxide Films in Nanometer-Size Structures

Isotropic atomic layer etching (ALE) is increasingly becoming an option and even a necessity for modern chip manufacturing. Especially for application such as 3D-NAND memory, the ability to perform isotropic etches will be a critical addition to the established suite of reactive ion etching. In this work, we have characterized the reaction of aluminum oxide (Al2O3) via the vapor-based DMAC ligand exchange mechanism in nanometer-size structures in which the oxide is buried below a silicon nitride mask. In the oxide, we measured vertical and horizontal etch rates and found that the etch showed some residual anisotropy even though all elements of the etch itself (flow, no plasma) were none-directional. We applied a simple Monte-Carlo simulation to show that anisotropy is caused by a delay in the onset of the horizontal etch beneath the mask and by molecular scattering effects in the vapor phase above the nano-structures. We are contrasting these results with experimental findings in structures without an anisotropy of the etch.

Free-energy cost of localizing a single monomer of a confined polymer

We describe a simple Monte Carlo simulation method to calculate the free-energy cost of localizing a single monomer of a polymer confined to a cavity. The localization position is chosen to be on the inside surface of the confining cavity. The method is applied to a freely jointed hard-sphere polymer chain confined to cavities of spherical and cubic geometries. In the latter case, we consider localization at a corner and at the center of a face of the confining cube. We consider cases of end-monomer localization both with and without tethering of the other end monomer to a point on the surface. We also examine localization of monomers at arbitrary positions along the contour of the polymer. We characterize the dependence of the free energy on the cavity size and shape, the localization position, and the polymer length. The quantitative trends can be understood using standard scaling arguments and use of a simple theoretical model. The results are relevant to those theories of polymer translocation that focus on the importance of the free-energy barrier as the translocation process requires an initial localization of a monomer to the position of a nanopore.

The EEE MRPC telescopes as tracking tools to monitor building stability with cosmic muons

This paper discusses the possibility to employ the Multi-gap Resistive Plate Chambers (MRPC) of the Extreme Energy Events (EEE) Project as muon tracking detectors to monitor the long term stability of civil buildings and structures when used in conjunction with additional detectors, to reconstruct the average direction of the cosmic muon tracks passing through both devices and any small variation over long time acquisition periods. The performance of such setup is discussed and preliminary experimental coincidence results obtained with a 40× 60 cm2 scintillator detector operated in the same building with one of the EEE telescopes, at about 15 m vertical distance from it, are presented. Simple Monte Carlo and GEANT simulations were also carried out to evaluate typical acceptance values for the operating conditions employed so far, to extrapolate to other geometrical configurations, and to evaluate multiple scattering effects.

Monte Carlo simulations in drug release.

We present methods based on simple sampling Monte Carlo simulations that are used in the study of controlled drug release from devices of various shapes and characteristics. The manuscript is part of a special tribute issue for Prof. Panos Macheras and we have chosen applications of the Monte Carlo method in the field of drug release that were pioneered by him and his research group. Thus, we focus on the investigation of diffusion based release and we present methods that go beyond the application of the classical fickian diffusion equation. We describe methods that have proven to be effective in illuminating the profound effects of the substrate heterogeneity on the drug release profiles and demonstrate some of the most powerful applications of agent based simulations and numerical methods in the field of pharmacokinetics.

SoftBV - a software tool for screening the materials genome of inorganic fast ion conductors.

The identification of materials for advanced energy-storage systems is still mostly based on experimental trial and error. Increasingly, computational tools are sought to accelerate materials discovery by computational predictions. Here are introduced a set of computationally inexpensive software tools that exploit the bond-valence-based empirical force field previously developed by the authors to enable high-throughput computational screening of experimental or simulated crystal-structure models of battery materials predicting a variety of properties of technological relevance, including a structure plausibility check, surface energies, an inventory of equilibrium and interstitial sites, the topology of ion-migration paths in between those sites, the respective migration barriers and the site-specific attempt frequencies. All of these can be predicted from CIF files of structure models at a minute fraction of the computational cost of density functional theory (DFT) simulations, and with the added advantage that all the relevant pathway segments are analysed instead of arbitrarily predetermined paths. The capabilities and limitations of the approach are evaluated for a wide range of ion-conducting solids. An integrated simple kinetic Monte Carlo simulation provides rough (but less reliable) predictions of the absolute conductivity at a given temperature. The automated adaptation of the force field to the composition and charge distribution in the simulated material allows for a high transferability of the force field within a wide range of Lewis acid-Lewis base-type ionic inorganic compounds as necessary for high-throughput screening. While the transferability and precision will not reach the same levels as in DFT simulations, the fact that the computational cost is several orders of magnitude lower allows the application of the approach not only to pre-screen databases of simple structure prototypes but also to structure models of complex disordered or amorphous phases, and provides a path to expand the analysis to charge transfer across interfaces that would be difficult to cover by ab initio methods.

Self-ordering of chemisorbed PTCDA molecules on Ge(001) driven by repulsive forces.

Realization of future hybrid electronic devices combining organic and inorganic semiconductors requires a well-defined interface between both components. Such an interface can be formed generally by self-ordering of organic molecules on inorganic substrates, which is usually hindered by strong covalent bonds to the semiconductor surface. In this paper, the 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA) molecules were unexpectedly found to form a locally self-ordered monolayer on a strongly interacting semiconductor surface of the Ge(001). Molecular arrangements with preferential separations between the molecules were observed by the scanning tunneling microscopy at various coverages of the molecules and substrate temperatures, suggesting strong inter-molecular interaction. Atomic structures of two paired molecules and their inter-molecular interaction energies in five different configurations were calculated by density functional theory. Simple Monte Carlo simulations show that mobility of molecules activated only by the inter-molecular interactions is sufficient to reproduce the local self-ordering. A dominant inter-molecular interaction between neighboring chemisorbed molecules has mostly positive energy (destabilizing) except for a single configuration, which leads to the formation of one-dimensional chains of the molecules and finally a periodic two-dimensional array by increasing the coverage.

Evaluating Single-Spacecraft Observations of Planetary Magnetotails With Simple Monte Carlo Simulations: 1. Spatial Distributions of the Neutral Line.

A simple Monte Carlo model is presented that considers the effects of spacecraft orbital sampling on the inferred distribution of magnetic flux ropes, generated through magnetic reconnection in the magnetotail current sheet. When generalized, the model allows the determination of the number of orbits required to constrain the underlying population of structures: It is able to quantify this as a function of the physical parameters of the structures (e.g., azimuthal extent and probability of generation). The model is shown adapted to the Hermean magnetotail, where the outputs are compared to the results of a recent survey. This comparison suggests that the center of Mercury's neutral line is located dawnward of midnight by 0.37−1.02+1.21RM and that the flux ropes are most likely to be wide azimuthally (∼50% of the width of the Hermean tail). The downtail location of the neutral line is not self‐consistent or in agreement with previous (independent) studies unless dissipation terms are included planetward of the reconnection site; potential physical explanations are discussed. In the future the model could be adapted to other environments, for example, the dayside magnetopause or other planetary magnetotails.

A framework for performance characterization of energy-resolving photon-counting detectors.

Photon-counting, energy-resolving detectors are subject to intense research interest, and there is a need for a general framework for performance assessment of these detectors. The commonly used linear-systems theory framework, which measures detector performance in terms of noise-equivalent quanta (NEQ) and detective quantum efficiency (DQE) is widely used for characterizing conventional x-ray detectors but does not take energy-resolving capabilities into account. The purpose of this work is to extend this framework to encompass energy-resolving photon-counting detectors and elucidate how the imperfect energy response and other imperfections in real-world detectors affect imaging performance, both for feature detection and for material quantification tasks. We generalize NEQ and DQE to matrix-valued quantities as functions of spatial frequency, and show how these matrices can be calculated from simple Monte Carlo simulations. To demonstrate how the new metrics can be interpreted, we compute them for simplified models of fluorescence and Compton scatter in a photon-counting detector and for a Monte Carlo model of a CdTe detector with pixels. Our results show that the ideal-linear-observer performance for any detection or material quantification task can be calculated from the proposed generalized NEQ and DQE metrics. We also demonstrate that the proposed NEQ metric is closely related to a generalized version of the Cramér-Rao lower bound commonly used for assessing material quantification performance. Off-diagonal elements in the NEQ and DQE matrices are shown to be related to loss of energy information due to imperfect energy resolution. The Monte Carlo model of the CdTe detector predicts a zero-frequency dose efficiency relative to an ideal detector of 0.86 and 0.65 for detecting water and bone, respectively. When the task instead is to quantify these materials, the corresponding values are 0.34 for water and 0.26 for bone. We have developed a framework for assessing the performance of photon-counting energy-resolving detectors and shown that the matrix-valued NEQ and DQE metrics contain sufficient information for calculating the dose efficiency for both detection and quantification tasks, the task having any spatial and energy dependence. This framework will be beneficial for the development and optimization of photon-counting x-ray detectors.

Using the Entire Yield Curve in Forecasting Output and Inflation

In forecasting a variable (forecast target) using many predictors, a factor model with principal components (PC) is often used. When the predictors are the yield curve (a set of many yields), the Nelson–Siegel (NS) factor model is used in place of the PC factors. These PC or NS factors are combining information (CI) in the predictors (yields). However, these CI factors are not “supervised” for a specific forecast target in that they are constructed by using only the predictors but not using a particular forecast target. In order to “supervise” factors for a forecast target, we follow Chan et al. (1999) and Stock and Watson (2004) to compute PC or NS factors of many forecasts (not of the predictors), with each of the many forecasts being computed using one predictor at a time. These PC or NS factors of forecasts are combining forecasts (CF). The CF factors are supervised for a specific forecast target. We demonstrate the advantage of the supervised CF factor models over the unsupervised CI factor models via simple numerical examples and Monte Carlo simulation. In out-of-sample forecasting of monthly US output growth and inflation, it is found that the CF factor models outperform the CI factor models especially at longer forecast horizons.