Monte Carlo Modeling Method Research Articles

Design and verification of a hybrid electrostatic discharge model for Gate-Controlled silicon controlled rectifier

The DC breakdown characteristic of electrostatic discharge (ESD) protection device, which is an important indicator of its transparency and circuit compatibility, has received widespread attention. Currently, methods such as Verilog-A hardware description language, circuit-level SPICE simulation, and process-level device modeling cannot simultaneously achieve high accuracy, good convergence, and fast simulation speed. Therefore, in this paper, a hybrid ESD model based on Technology Computer Aided Design (TCAD) device-level simulation, Monte Carlo numerical modeling and Verilog-A behavioral modeling is proposed to characterize the ESD characteristics of gate-controlled silicon-controlled rectifier (GCSCR). A device-level model of GCSCR was established using TCAD, and the working mechanism was simulated. By extracting the electric field from TCAD and using the Monte Carlo modeling method, the DC characteristic of GCSCR was accurately characterized. In addition, the snapback characteristic of the device was successfully simulated by Verilog-A. The effectiveness of the above approaches was further verified based on the 0.18 μm standard BCD (Bipolar-CMOS-DMOS) process. Comparison results indicate that the hybrid model exhibits high simulation accuracy, good convergence and good universality and scalability, providing a simple and effective modeling solution for ESD devices of different structures and sizes.1This work is supported by the National Natural Science Foundation of China (Grant No. 62174052, 61827812), Hunan Science and Technology Department Huxiang High-level Talent Gathering Project (Grant No. 2019RS1037) and Innovation Project of Science and Technology Department of Hunan Province (Grant No. 2020GK2018).

Simplified Method for Calculation of Internal Exposure Dose to Bone Metastases During Radionuclide Therapy

Purpose: Development of a simplified method for calculating internal doses of bone metastases during radionuclide therapy with radiopharmaceuticals.
 Material and methods: A comparative analysis of the advantages and disadvantages of 3 existing methods of dosimetry of internal irradiation (MIRD formalism, the method of the dose kernel of a point isotropic source and the Monte Carlo modeling method) was carried out in relation to the task of dosimetry of bone metastases. It has been shown that all of them, having a high accuracy of dose estimation, remain unsuitable for wide clinical practice due to their mathematical complexity, laboriousness, low availability, and overestimated requirements for user qualifications.
 A simplified method is proposed for determining doses of internal irradiation of tumor foci based on quantitative data from SPECT/CT scanning of an X-ray phantom and a real patient who has been injected with a b-g-radiating therapeutic radiopharmaceutical.
 Results: On a clinical example of radionuclide therapy with 177Lu-PSMA of a patient with stage 4 prostate cancer, dose estimates were obtained for both internal exposure to b-particles and g-quanta from the radiopharmaceutical accumulated in bone foci, and external exposure to g-quanta of the same radiopharmaceutical contained at the time of measurements in the tissues surrounding the focus and environments of the whole body of the patient. Calculations were made for bone metastases of 7 localizations in dynamics for each of the 5 fractions of radionuclide therapy. It is shown that the total focal doses for 5 fractions of internal exposure vary from 70.6 to 116.8 Gy for different foci, which corresponds to the literature data obtained by more accurate methods of dosimetry of internal exposure.
 Conclusion: The developed simplified method for obtaining dose estimates for radionuclide therapy of bone metastases is characterized by an accuracy acceptable for clinical purposes while ensuring simplicity and low labor intensity of its practical application by a wide range of medical physicists and radiologists.

Atomistic modeling to the investigation of irradiation effect on optical properties of LiI/ZnS scintillator in a research reactor-based neutron radiography facility

Scintillation material presents a variety of applications used in radiation environments such as dosimetry, spectrometry, and radiography facility. Neutron radiography is a non-destructive testing (NDT) method that uses a proper scintillator such as LiI/ZnS for neutron detection. This paper investigated the effect of neutron-induced point defects on the optical properties of this scintillator used in TRR’s neutron radiography system. The combination of Monte Carlo and atomistic modeling methods was utilized in this regard. The results showed that the induced point defects lead to a more than 10 and 22% reduction in the refractive index and reflectivity of the LiI scintillator at optical wavelength respectively. Moreover, the refractive index of the ZnS scintillator decreases more than 6.4 % by Zn interstitial, Zn vacancy, and S vacancy and increases 8.9 % by S interstitial at optical wavelength.

A New Goodness of Fit Test for Multivariate Normality and Comparative Simulation Study

The testing of multivariate normality remains a significant scientific problem. Although it is being extensively researched, it is still unclear how to choose the best test based on the sample size, variance, covariance matrix and others. In order to contribute to this field, a new goodness of fit test for multivariate normality is introduced. This test is based on the mean absolute deviation of the empirical distribution density from the theoretical distribution density. A new test was compared with the most popular tests in terms of empirical power. The power of the tests was estimated for the selected alternative distributions and examined by the Monte Carlo modeling method for the chosen sample sizes and dimensions. Based on the modeling results, it can be concluded that a new test is one of the most powerful tests for checking multivariate normality, especially for smaller samples. In addition, the assumption of normality of two real data sets was checked.

Parallelized Monte Carlo Photon Transport Simulations for Arbitrary Multi-Angle Wide-Field Illumination in Optoacoustic Imaging

Optoacoustic imaging (OAI) or photoacoustic imaging can resolve the distribution of tissue chromophores and optical contrast agents deep inside tissue from the optoacoustic detection with multi-spectral illumination. The development of a fast and accurate modeling method for the photon transport in OAI is necessary to quantitatively evaluate the tissue optical parameters. This paper presents a parallelized Monte Carlo modeling method especially for OAI (MCOAI) to simulate photon transport in bio-tissues with arbitrary multi-angle wide-field illumination. The performance of the MCOAI method is verified by comparison with the graphics processing unit (GPU)-accelerated MCX method in the typical cases with the pencil beam and ring source illumination. The simulation results demonstrate the GPU-based MCOAI method has equivalent accuracy and significantly improved computation efficiency, compared to the MCX method. The simulations with cylindrical and hemispherical source illumination further illustrate that the MCOAI method can effectively implement three-dimensional photon transport simulation for typical illumination geometries of OAI systems. A cross-section of Digimouse is selected as a realistic heterogeneous phantom illuminated with six different light sources usually employed in OAI, in order to prove the necessity of establishing photon transport modeling in OAI for the quantitative visualization in deep tissues. The MCOAI method can provide a powerful tool to efficiently establish photon transport modeling with arbitrary illumination modes for OAI applications.

Автоматизированное моделирование распространения инфекционных заболеваний среди населения мегаполиса с помощью метода монте карло с учётом аспектов информационной безопасности

Infection spread among the megalopolis population depends on many factors, the most important of which are social activity level of citizens, pathogen contagiousness, climatic conditions. The factors are variable, according to this, the calculation of infection spread could be referred to the problem of prediction the state of a complex system, consisting of many elements. To carry out the calculation (at the current level of computer technologies development) the most effective would be using Monte-Carlo modeling method. Besides the data about contamination of each citizen are personal, information security aspects should be used while design process of the automated modeling system.

Rapid Simulation of Unprocessed DEER Decay Data for Protein Fold Prediction

Despite advances in sampling and scoring strategies, Monte Carlo modeling methods still struggle to accurately predict de novo the structures of large proteins, membrane proteins, or proteins of complex topologies. Previous approaches have addressed these shortcomings by leveraging sparse distance data gathered using site-directed spin labeling and electron paramagnetic resonance spectroscopy to improve protein structure prediction and refinement outcomes. However, existing computational implementations entail compromises between coarse-grained models of the spin label that lower the resolution and explicit models that lead to resource-intense simulations. These methods are further limited by their reliance on distance distributions, which are calculated from a primary refocused echo decay signal and contain uncertainties that may require manual refinement. Here, we addressed these challenges by developing RosettaDEER, a scoring method within the Rosetta software suite capable of simulating double electron-electron resonance spectroscopy decay traces and distance distributions between spin labels fast enough to fold proteins de novo. We demonstrate that the accuracy of resulting distance distributions match or exceed those generated by more computationally intensive methods. Moreover, decay traces generated from these distributions recapitulate intermolecular background coupling parameters even when the time window of data collection is truncated. As a result, RosettaDEER can discriminate between poorly folded and native-like models by using decay traces that cannot be accurately converted into distance distributions using regularized fitting approaches. Finally, using two challenging test cases, we demonstrate that RosettaDEER leverages these experimental data for protein fold prediction more effectively than previous methods. These benchmarking results confirm that RosettaDEER can effectively leverage sparse experimental data for a wide array of modeling applications built into the Rosetta software suite.

Occupational Exposure to Endotoxin along a Municipal Scale Fecal Sludge Collection and Resource Recovery Process in Kigali, Rwanda.

Background: Little is known about occupational exposures that occur along fecal sludge collection and resource recovery processes. This study characterizes inhaled endotoxin exposure to workers of a municipal scale fecal sludge-to-fuel processes in Kigali, Rwanda. Methods: Forty-two task-based air samples were collected from workers in five tasks along the fecal sludge collection and resource recovery process. Samples were processed for endotoxin using the limulus amebocyte lysate (LAL) test. To account for exposure variability and compare measured concentrations to established exposure limits, we used Monte Carlo modeling methods to construct distributions representing full eight-hour (8-h) exposures to endotoxin across eight exposure scenarios. Results: Geometric mean (GM) endotoxin concentrations in task-based samples ranged from 11–3700 EU/m3 with exposure concentrations increasing as the dryness of the fecal sludge increased through processing. The thermal dryer task had the highest endotoxin concentrations (GM = 3700 EU/m3) and the inlet task had the lowest (GM = 11 EU/m3). The geometric means (GM) of modeled 8-h exposure concentrations were between 6.7–960 EU/m3 and highest for scenarios which included the thermal dryer task in the exposure scenario. Conclusions: Our data suggest the importance of including worker exposure considerations in the design of nascent fecal sludge management processes. The methods used in this study combine workplace sampling with stochastic modeling and are useful for exposure assessment in resource constrained contexts.

Modeling of lactose enzymatic hydrolysis using Monte Carlo method

Abstract Background Mathematical modeling is useful in the analysis, prediction, and optimization of an enzymatic process. Unlike the conventional modeling methods, Monte Carlo method has special advantages in providing representations of the molecule’s spatial distribution. However, thus far, Monte Carlo modeling of enzymatic system is namely based on unimolecular basis, not suitable for practical applications. In this research, Monte Carlo modeling is performed for enzymatic hydrolysis of lactose for the purpose of real-time applications. Results The enzyme hydrolysis of lactose, which is conformed to Michaelis–Menten kinetics, is modeled using the Monte Carlo modeling method, and the simulation results prove that the model predicts the reaction kinetics very well. Conclusions Monte Carlo modeling method can be used to model enzymatic reactions in a simple way for real-time applications. How to cite: Gao L, Guo Q, Lin H, et al. Modeling of lactose enzymatic hydrolysis using Monte Carlo method. Electron J Biotechnol 2019;41. https://doi.org/10.1016/j.ejbt.2019.04.010

Improvement in the method for borehole caliper measurement based on azimuthal gamma-gamma density well logging

Accurate characterization of the size and shape of the borehole is critical to the effective borehole correction for logging while drilling (LWD) measurements. It is also necessary for the real-time evaluation of geomechanical wellbore stability and for optimizing drilling operation and determining proper completion strategies. The pseudo-caliper measurement can be derived from LWD azimuthal density measurement, where a linear empirical model is employed to calculate the tool standoffs. However, we found that as the tool standoff continues to increase, the model could no longer describe the variation in borehole size accurately. In this paper, the responses of LWD azimuthal density measurement under different logging conditions are studied using the Monte Carlo modeling method. To improve the estimation of borehole geometry, a new model is proposed to determine tool standoffs and measure the borehole caliper. Simulation models with different degrees of borehole enlargement are built to investigate the performance of the model. Compared with the currently used method, the wellbore caliper values calculated using the new method are more consistent with the actual values. A field example with mechanical caliper measured from wireline logs is also presented to validate the effectiveness of the proposed method.

Modeling Light Propagation through the Tissues of the Head Taking Account of Scattering Anisotropy to Optimize the Positioning of Irradiation Detectors and Sources in a Brain–Computer Interface Based on Near Infrared Spectroscopy

We describe here use of the Monte Carlo modeling method to specify the parameters of near infrared light propagation though the tissues of the head, which is needed for optimizing the operation of brain–computer interfaces. The studies used a four-layer spherical model of the head consisting of skin, bone, gray matter, and white matter. The relationship between the parameters of the radiation recorded and the distance between the source and detector were obtained.

A novel muon detector for borehole density tomography

Muons can be used to image the density of materials through which they pass, including geological structures. Subsurface applications of the technology include tracking fluid migration during injection or production, with increasing concern regarding such timely issues as induced seismicity or chemical leakage into aquifers. Current density monitoring options include gravimetric data collection and active or passive seismic surveys. One alternative, or complement, to these methods is the development of a muon detector that is sufficiently compact and robust for deployment in a borehole. Such a muon detector can enable imaging of density structure to monitor small changes in density – a proxy for fluid migration – at depths up to 1500m. Such a detector has been developed, and Monte Carlo modeling methods applied to simulate the anticipated detector response. Testing and measurements using a prototype detector in the laboratory and shallow underground laboratory demonstrated robust response. A satisfactory comparison with a large drift tube-based muon detector is also presented.

The structure of molten CuCl: Reverse Monte Carlo modeling with high-energy X-ray diffraction data and molecular dynamics of a polarizable ion model.

The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å(-1) related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.

First-principles study of phase equilibrium in Ti–V, Ti–Nb, and Ti–Ta alloys

The subsolidus equilibrium phase diagrams of Ti–V, Ti–Nb and Ti–Ta alloys have been computed through cluster expansion, lattice dynamics and Monte Carlo modeling methods combined with Density Functional Theory total-energy calculations. Computed phase boundaries in Ti–V alloy are found to be in good agreement with reported CALPHAD assessed experimental boundaries. For Ti–Ta system, the computed phase boundaries agree well with CALPHAD boundaries for Ta-rich alloys. For Ti-rich alloys, the transformation temperatures are overestimated by up to 200K. In the case of Ti–Nb system, the calculated boundary of the bcc-solid-solution phase decreases rapidly in temperature with increasing Nb concentration compared to CALPHAD boundary, deviating from the latter by up to 600K at 80% Nb. Our calculation gives qualitatively correct hcp-solid-solution regions for all the three alloy systems (i.e., solubility of V/Nb/Ta in hcp Ti). A key difficulty in modeling these systems is the presence of mechanical instability in the bcc phase at high Ti concentration. In this work, we circumvent this difficulty by excluding structures exhibiting instability in the cluster expansion construction process. We find that, while such a scheme is often appropriate (as in the Ti–V and Ti–Ta systems), it can become unreliable when the result exhibit a too strong sensitivity to the exclusion rule used (as in the Ti–Nb system). In all systems, we find that the inclusion of lattice vibration effects is crucial to obtain even qualitative agreement with experiment.

Assessing aflatoxin B1 distribution and variability in pistachios: Validation of a Monte Carlo modeling method and comparison to the Codex method

Aflatoxin B1 (AFB1) has genotoxic carcinogenic effects with no threshold. This mycotoxin, produced by Aspergillus fungi species, can be found at a very low incidence in pistachios. More precisely, the contaminant is heterogeneously distributed. Moreover, it is usually found at high concentration levels in contaminated individual nut kernels. For this reason, it is crucial to assess AFB1 distribution and variability accurately in pistachio samples, in order to establish informed sampling schemes for health protection purposes. A modeling method using Monte Carlo simulations for AFB1 distribution in pistachio samples, developed in previous work, required validation. For this purpose, the simulation was adjusted to the distribution observed in 30 kg samples as calculated from the RASFF (Rapid Alert System for Food and Feed) levels reported by Germany for Iranian pistachio imports from September 2002 to September 2004, for the lots tested. As a final result, when the simulated distribution in 10 kg samples was computed from the prior simulation, it was very similar to the distribution observed in representative samples for the same sample size from the RASFF. The simulation method was then compared to another method, for AFB1 distribution and variability assessment, used by the Codex to design aflatoxin sampling plans for tree nuts. Indeed, the distribution observed in 30 kg samples from the RASFF was considered as an input distribution. The output distribution for 10 kg representative samples, as computed using the method, was close to the observed distribution. Results of both simulation methods were very similar. Finally, an extensive comparison of the principles of both methods was performed.

Quantitative analysis of the local atomic structure in disordered carbon

The quantitative characteristics of a short- and a medium-range order in amorphous carbon synthesized by electric discharge treatment of hydrocarbons are determined by a combined application of X-ray diffraction analysis, Reverse Monte Carlo modeling and Voronoi diagram method. The obtained characteristics exhibit a graphite- or a mixed graphite–diamond-like type of short-range order and, at the same time, a large portion of carbon atoms within chemical bond lengths is combined into 3-fold rings of the tetrahedral structures. Statistical analysis of Voronoi polyhedra has revealed a wide distribution of their topological and metric characteristics that are inherited by disordered materials with predominated 5-fold faces which are typical for amorphous structures. The regular configuration polyhedra (clusters) are virtually absent in the synthesized carbon nanomaterials.

Numerical Simulations of Biological Droplet Transport in an Indoor Environment

In this paper, the biological droplet transport and deposition in the turbulent airflow inside an indoor environment was studied using the Lagrangian computational method. Meanwhile, as to the mathematic simulation, the Monte Carlo modeling method was coupled into this simulation program to describe the bio-particle transport. Many influent factors such as indoor airflow velocity, the bio-aerosol generator velocity, particle diameter, and evaporation and death were considered synthetically in this paper. Serratia marcescens was used as tracer microorganism to simulate the droplet nuclei exhaled by patients, and the spatial distribution of its concentration was measured. Collected bacteria were quantified using standard cultivating assays. It showed the simulation results were comparable with the data of the experimental findings.

Atomic configuration of metal atoms in (Ti 0.676Zr 0.324)D 0.31 metallic glass studied by X-ray, neutron diffraction and reverse Monte Carlo modeling

We have obtained a three-dimensional atomic configuration in (Ti 0.676Zr 0.324)D 0.31 glass using the reverse Monte Carlo (RMC) modeling method with neutron and X-ray diffraction data. Voronoi polyhedral analysis for the RMC configuration of metal atoms revealed the presence of a lot of icosahedral-like clusters.

Structural analysis for crystalline and amorphous RFe 2D x (R: Ho, Tb) by X-ray/neutron diffraction and reverse Monte Carlo modeling

Atomic structures of crystalline (c-)HoFe 2D 3.6 and amorphous (a-)HoFe 2D 3.0 prepared by deuterium absorption of the C15 Laves phase compound HoFe 2 were studied by X-ray and neutron diffraction techniques and these were compared with previous results for c- and a-TbFe 2D x . The structural parameters such as an interatomic distance and a coordination number are qualitatively in agreement with those for c- and a-TbFe 2D x . Namely, a marked difference was observed in the arrangement of metal atoms in a-HoFe 2D 3.0 compared to that in c-HoFe 2D 3.6 from interatomic distances and coordination numbers and there are clusters of Fe and Ho atoms in a-HoFe 2D x . RDF( r)s observed by the neutron diffraction indicated that the D atoms occupy tetrahedral sites consisting of 2Ho+2Fe in c-HoFe 2D 3.6, while the D atoms occupy selectively tetrahedral sites consisting mainly of Ho atoms in a-HoFe 2D 3.0 because of strong affinity between D and Ho atoms. The reverse Monte Carlo (RMC) modeling method was employed to visualize a three-dimensional atomic arrangement by using combined X-ray and neuron diffraction data of RFe 2D x (R: Ho, Tb). Chemical fluctuation was visually observed in the RMC configurations. Moreover, it was found that about 40% of the D atoms occupy sites consisting of 4R.

Structural inhomogeneities in fast ion conducting glasses

The structures of the ion conducting glasses ${\mathrm{L}\mathrm{i}\mathrm{C}\mathrm{l}\ensuremath{-}\mathrm{L}\mathrm{i}}_{2}{\mathrm{O}\ensuremath{-}2\mathrm{B}}_{2}{\mathrm{O}}_{3},$ $({\mathrm{A}\mathrm{g}\mathrm{I})}_{0.6}{\ensuremath{-}(\mathrm{A}\mathrm{g}}_{2}{\mathrm{O}\ensuremath{-}\mathrm{B}}_{2}{\mathrm{O}}_{3}{)}_{0.4},$ ${\mathrm{C}\mathrm{s}\mathrm{I}\ensuremath{-}4\mathrm{AgPO}}_{3},$ and ${\mathrm{PbI}}_{2}{\ensuremath{-}9\mathrm{AgPO}}_{3}$ have been investigated using small- and wide-angle neutron diffraction experiments. We have applied the reverse Monte Carlo modeling method to the experimental data with the aim to reveal the intermediate-range structure on a length scale of 5\char21{}50 \AA{}. The $({\mathrm{A}\mathrm{g}\mathrm{I})}_{0.6}{\ensuremath{-}(\mathrm{A}\mathrm{g}}_{2}{\mathrm{O}\ensuremath{-}\mathrm{B}}_{2}{\mathrm{O}}_{3}{)}_{0.4}$ glass shows exceptionally high scattering intensity at low Q values (0.5 ${\mathrm{\AA{}}}^{\mathrm{\ensuremath{-}}1}$) due to the existence of chemical inhomogeneities on length scales up to at least 50 \AA{}. Both the salt ions and the network atoms are inhomogeneously distributed. The first diffraction peak, located at 0.46 ${\mathrm{\AA{}}}^{\mathrm{\ensuremath{-}}1}$ in the total structure factor, is caused by a characteristic distance between B-O segments separated by salt ions. The ${\mathrm{L}\mathrm{i}\mathrm{C}\mathrm{l}\ensuremath{-}\mathrm{L}\mathrm{i}}_{2}{\mathrm{O}\ensuremath{-}2\mathrm{B}}_{2}{\mathrm{O}}_{3}$ glass shows inhomogeneities only in the distribution of salt ions, where particularly the chlorine ions are very inhomogeneously distributed. The ion concentration fluctuations occur on a wide range of length scales. In contrast to the investigated borate glasses, the two phosphate glasses show only minor structural inhomogeneities on length scales above 10 \AA{}.