Exhaustive review of acceleration strategies for Monte Carlo simulations in photon transit

Monte Carlo simulation techniques have become the quintessence and a pivotal nexus of inquiry in the realm of simulating photon movement within biological fabrics.Through the stochastic sampling of tissue archetypes delineated by explicit optical characteristics,Monte Carlo simulations possess the theoretical capacity to render unparalleled accuracy in the depiction of exceedingly intricate phenomena.Nonetheless,the quintessential challenge associated with Monte Carlo simulation methodologies resides in their extended computational duration,which significantly impedes the refinement of their precision.Consequently,this discourse is specifically dedicated to exploring innovations in strategies and technologies aimed at expediting Monte Carlo simulations.It delves into the foundational concepts of various acceleration tactics,evaluates these strategies concerning their speed,accuracy,and practicality,and amalgamates a comprehensive overview and critique of acceleration methodologies for Monte Carlo simulations.Ultimately,the discourse envisages prospective trajectories for the employment of Monte Carlo techniques within the domain of tissue optics.

Machine learning-enhanced Monte Carlo and subset simulations for advanced risk assessment in transportation infrastructure

The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation networks.This study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in MS-Excel.Focused on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning requirements.The chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an escalation.The SS approach showed exceptional efficacy in calculating odds of failure that are notably low.Within computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO models.The ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most promising.This study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation infrastructure.These findings contribute to the enhancement of safety and reliability in real-world situations.

Optimization of the Use of Spherical Targets for Point Cloud Registration Using Monte Carlo Simulation

Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience without scientific evidence supported by numerical analysis.This paper presents a comprehensive investigation,based on Monte Carlo simulation,into determining the optimal number and positions for efficient target placement in typical scenes consisting of a pair of facades.It demonstrates new check-up statistical rules and geometrical constraints that can effectively extract and analyze massive simulations of unregistered point clouds and their corresponding registrations.More than 6×10^(7) sets of the registrations were simulated,whereas more than IOO registrations with real data were used to verify the results of simulation.The results indicated that using five spherical targets is the best choice for the registration of a large typical registration site consisting of two vertical facades and a ground,when there is only a box set of spherical targets available.As a result,the users can avoid placing extra targets to achieve insignificant improvements in registration accuracy.The results also suggest that the higher registration accuracy can be obtained when the ratio between the facade-to-target distance and target-to-scanner distance is approximately 3:2.Therefore,the targets should be placed closer to the scanner rather than in the middle between the facades and the scanner,contradicting to the traditional thought. Besides,the results reveal that the accuracy can be increased by setting the largest projected triangular area of the targets to be large.

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.

Monte Carlo Simulations of Doping Properties of a Spin-3/2 Ising Nanotube

The effect of spin-1 impurities doping on the magnetic properties of a spin-3/2 Ising nanotube is investigated using Monte Carlo simulations within the Blume-Emery-Griffiths model in the presence of an external magnetic field. The thermal behaviors of the order parameters and different macroscopic instabilities as well as the hysteretic behavior of the material are examined in great detail as a function of the dopant density. It is found that the impurities concentration affects all the system magnetic properties generating for some specific values, compensation points and multi-cycle hysteresis. Doping conditions where the saturation/remanent magnetization and coercive field of the investigated material can be modified for permanent or soft magnets synthesis purpose are discussed.

Simulation study of the performance of the Very Large Area gamma-ray Space Telescope

The Very Large Area gamma-ray Space Telescope(VLAST)is a mission concept proposed to detect gamma-ray photons through both Compton scattering and electron–positron pair production mechanisms,thus enabling the detection of photons with energies ranging from MeV to TeV.This project aims to conduct a comprehensive survey of the gamma-ray sky from a low-Earth orbit using an anti-coincidence detector,a tracker detector that also serves as a low-energy calorimeter,and a high-energy imaging calorimeter.We developed a Monte Carlo simulation application of the detector using the GEANT4 toolkit to evaluate the instrument performance,including the effective area,angular resolution,and energy resolution,and explored specific optimizations of the detector configuration.Our simulation-based analysis indicates that the current design of the VLAST is physically feasible,with an acceptance above 10 m^(2)sr which is four times larger than that of the Fermi-LAT,an energy resolution better than 2%at 10 GeV,and an angular resolution better than 0.2◦at 10 GeV.The VLAST project promises to make significant contributions to the field of gamma-ray astronomy and enhance our understanding of the cosmos.

Simulation and experimental comparison of the performance of four-corner-readout plastic scintillator muon-detector system

Cosmic-ray muons are highly penetrating background-radiation particles found in natural environments.In this study,we develop and test a plastic scintillator muon detector based on machine-learning algorithms.The detector underwent muon position-resolution tests at the Institute of Modern Physics in Lanzhou using a multiwire drift chamber(MWDC)experimental platform.In the simulation,the same structural and performance parameters were maintained to ensure the reliability of the simulation results.The Gaussian process regression(GPR)algorithm was used as the position-reconstruction algorithm owing to its optimal performance.The results of the Time Difference of Arrival algorithm were incorporated as one of the features of the GPR model to reconstruct the muon hit positions.The accuracy of the position reconstruction was evaluated by comparing the experimental results with Geant4 simulation results.In the simulation,large-area plastic scintillator detectors achieved a position resolution better than 20 mm.In the experimental-platform tests,the position resolutions of the test detectors were 27.9 mm.We also analyzed factors affecting the position resolution,including the critical angle of the total internal reflection of the photomultiplier tubes and distribution of muons in the MWDC.Simulations were performed to image both large objects and objects with different atomic numbers.The results showed that the system could image high-and low-Z materials in the constructed model and distinguish objects with significant density differences.This study demonstrates the feasibility of the proposed system,thereby providing a new detector system for muon-imaging applications.

Simulation of space heavy-ion induced primary knock-on atoms in bipolar devices

Bipolar junction transistors(BJTs) are often used in spacecraft due to their excellent working characteristics. However,the complex space radiation environment induces primary knock-on atoms(PKAs) in BJTs through collisions, resulting in hard-to-recover displacement damage and affecting the performance of electronic components. In this paper, the properties of PKAs induced by typical space heavy ions(C, N, O, Fe) in BJTs are investigated using Monte Carlo simulations. The simulated results show that the energy spectrum of ion-induced PKAs is primarily concentrated in the low-energy range(17eV–100eV) and displays similar features across all tested ions. The PKAs induced by the collision of energetic ions have large forward scattering angles, mainly around 88°. Moreover, the distribution of PKAs within a transistor as a function of depth displays a peak characteristic, and the peak position is linearly proportional to the incident energy at a certain energy range. These simulation outcomes serve as crucial theoretical support for long-term semiconductor material defect evolution and ground testing of semiconductor devices.

Sample size adaptive strategy for time-dependent Monte Carlo particle transport simulation

When multiphysics coupling calculations contain time-dependent Monte Carlo particle transport simulations, these simulations often account for the largest part of the calculation time, which is insufferable in certain important cases. This study proposes an adaptive strategy for automatically adjusting the sample size to fulfil more reasonable simulations. This is realized based on an extension of the Shannon entropy concept and is essentially different from the popular methods in timeindependent Monte Carlo particle transport simulations, such as controlling the sample size according to the relative error of a target tally or by experience. The results of the two models show that this strategy can yield almost similar results while significantly reducing the calculation time. Considering the efficiency, the sample size should not be increased blindly if the efficiency cannot be enhanced further. The strategy proposed herein satisfies this requirement.

EJUSTCO:Monte Carlo radiation transport code hybrid with ANN model for gamma-ray shielding simulation

Gamma ray shielding is essential to ensure the safety of personnel and equipment in facilities and environments where radiation exists.The Monte Carlo technique is vital for analyzing the gamma-ray shielding capabilities of materials.In this study,a simple Monte Carlo code,EJUSTCO,is developed to cd simulate gamma radiation transport in shielding materials for academic purposes.The code considers the photoelectric effect,Compton(incoherent)scattering,pair production,and photon annihilation as the dominant interaction mechanisms in the gamma radiation shielding problem.Variance reduction techniques,such as the Russian roulette,survival weighting,and exponential transformation,are incorporated into the code to improve computational efficiency.Predicting the exponential transformation parameter typically requires trial and error as well as expertise.Herein,a deep learning neural network is proposed as a viable method for predicting this parameter for the first time.The model achieves an MSE of 0.00076752 and an R-value of 0.99998.The exposure buildup factors and radiation dose rates due to the passage of gamma radiation with different source energies and varying thicknesses of lead,water,iron,concrete,and aluminum in single-,double-,and triple-layer material systems are validated by comparing the results with those of MCNP,ESG,ANS-6.4.3,MCBLD,MONTEREY MARK(M),PENELOPE,and experiments.Average errors of 5.6%,2.75%,and 10%are achieved for the exposure buildup factor in single-,double-,and triple-layer materials,respectively.A significant parameter that is not considered in similar studies is the gamma ray albedo.In the EJUSTCO code,the total number and energy albedos have been computed.The results are compared with those of MCNP,FOTELP,and PENELOPE.In general,the EJUSTCO-developed code can be employed to assess the performance of radiation shielding materials because the validation results are consistent with theoretical,experimental,and literary results.

Grand canonical Monte Carlo simulation study of hydrogen storage by Li-decorated pha-graphene

Grand canonical Monte Carlo simulation(GCMCs)is utilized for studying hydrogen storage gravimetric density by pha-graphene at different metal densities,temperatures and pressures.It is demonstrated that the optimum adsorbent location for Li atoms is the center of the seven-membered ring of pha-graphene.The binding energy of Li-decorated phagraphene is larger than the cohesive energy of Li atoms,implying that Li can be distributed on the surface of pha-graphene without forming metal clusters.We fitted the force field parameters of Li and C atoms at different positions and performed GCMCs to study the absorption capacity of H_(2).The capacity of hydrogen storage was studied by the differing density of Li decoration.The maximum hydrogen storage capacity of 4Li-decorated pha-graphene was 15.88 wt%at 77 K and100 bar.The enthalpy values of adsorption at the three densities are in the ideal range of 15 kJ·mol^(-1)-25 kJ·mol^(-1).The GCMC results at different pressures and temperatures show that with the increase in Li decorative density,the hydrogen storage gravimetric ratio of pha-graphene decreases but can reach the 2025 US Department of Energy's standard(5.5 wt%).Therefore,pha-graphene is considered to be a potential hydrogen storage material.

Study on kinetics of propylene polymerizationat different temperatures via Monte Carlo simulation

The elementary reactions of propylene polymerization catalyzed by conventional Ziegler-Natta catalysts was proposed according to the comprehensive view and without considering the effect of any impurity in the material on propylene polymerization. The Monte Carlo simulation technique was employed to investigate the kinetics of propylene polymerization in order to determine the validity of the stationary state assumption and the effects of the polymerization temperature on the polymerization. The simulated total amount of active species, which only increases quickly at the beginning of the polymerization, indicates that the stationary state assumption in the studied system is valid. Moreover, significant effects of polymerization temperature on the polymerization conversion, and the molecular weight and its distribution were also analyzed. The simulated results show that the consumption rate of propylene increases with the increase of polymerization temperature; the maximum values of the number-average degree of polymerization are constant at different polymerization temperatures, however, the peak appears earlier with the higher temperature; as the polymerization temperature increases, the average molecular weight decreases and the molecular weight distribution changes greatly.

MONTE CARLO SIMULATION OF RADIATION FIELD OPTIMIZATION FOR MEDICAL LINAC

A method for designing an X-ray flatness filter for medical electron linac is developed. It is used in the optimization process in the electron beam radiation system. Monte Carlo simulation method is used and two examples of real radiation system optimization processes for China-made medical electron linac are provided： 15 MV X- ray system of BJ-20 linac, and 12 MeV electron system of BJ-14. Results are verified by using the traditional method.

Comparison Between Three-Valley Model and Full Band Model in Monte Carlo Simulation of Bulk Wurtzite GaN

The Monte Carlo simulators with the three valley model and the full band Monte Carlo model are used to explore electron transport in bulk wurtzite gallium nitride (GaN).Comparison of the results based on the two models is made.The results based on both models are basically the same at the lower field region,but exhibit some differences at the higher field region.The electron average energy exhibits obvious difference at the high field region between the two models.This difference further causes several other differences of GaN properties,such as the drift velocity versus field characteristics,the repopulation.Because of the complicated energy band structures at the high energy region for wurtzite GaN,the analytical band structures in the three valley model can not cover all properties of the band structures of wurtzite GaN,so the results based on the full band Monte Carlo model should be more exact.

Full Band Monte Carlo Simulation of Electron Transport in Ge with Anisotropic Scattering Process

The electron transport properties in Ge are calculated by full band Monte Carlo technique with anisotropic scattering consideration.The calculation procedures are as follows:the full band structure is calculated by nonlocal empirical pseudopotential approach;the relative value of density of state (DOS) is computed by counting the number of states located in a certain region of the energy;the phonon dispersion curve is obtained from an adiabatic bond charge model;the electron phonon scattering rates are approximated by the nonparabolic model derived from Fermi’s golden rule at low energy region and scaled by DOS at higher energy region;the energy and momentum conservations are employed for choosing the final state after scattering.The validity of this Monte Carlo simulator and the physical models that are used is fully confirmed by comparing the program output to experimental results listed in references.As this Monte Carlo model can accurately reproduce the velocity and energy characteristics of electrons in Ge and the DOS scaled scattering rate can significantly reduce the computational cost for scattering rates,this approach is suitable for device simulation.

Using Monte Carlo Simulation Technology to Improve Intuitive Effect of Teaching Probability and Mathematical Statistics Course

With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save instructors' effort as well.And it is estimated that Monte Carlo Simulation technology will be one of the major teaching methods for Probability and Mathematical Statistics course in the future.

基于Monte-Carlo仿真的恒应力加速试验方案模拟评价

为了保证可靠性加速试验方案的正确性和可行性,提出基于仿真的模拟评价方法。以最具代表性的Weibull寿命分布产品的恒应力加速寿命试验为例,以代表试验结果准确性和稳定性的指标——中位寿命估计值渐进方差的均值和标准差作为评价指标,通过Monte-Carlo仿真模拟生成失效数据,对不同试验方案的统计精度和稳定性进行评价,为加速寿命试验优化设计的工程实现提供了思路和实例验证。

Growth Mechanism of Microcrystalline Silicon Films by Scaling Theory and Monte Carlo Simulation

Hydrogenated microcrystalline silicon （~c-Si：H） films with a high deposition rate of 1.2nm/s were prepared by hot-wire chemical vapor deposition （HWCVD）. The growth-front roughening processes of the μc-Si..H films were investi- gated by atomic force microscopy. According to the scaling theory, the growth exponent β≈0.67, the roughness exponent α≈0.80,and the dynamic exponent 1/z = 0.40 are obtained. These scaling exponents cannot be explained well by the known growth models. An attempt at Monte Carlo simulation has been made to describe the growth process of μc-Si： H film using a particle reemission model where the incident flux distribution,the type and concentration of growth radical, and sticking,reemission,shadowing mechanisms all contributed to the growing morphology.

Simulation of a soft-gamma-ray polarimeter on board a microsatellite

Gamma-ray polarimetry is a new and prospective tool for studying extremely high-energy celestial objects and is of great significance for the field of astrophysics.With the rapid development of microsatellite technology,the advantages of space exploration have become increasingly apparent.Therefore,we simulated a soft-gamma-ray polarimeter for a microsatellite based on the Compton scattering principle.We performed detailed Monte Carlo simulations using monoenergetic gamma-ray linear-polarization sources and Crab-like sources in the energy range of 0.1-10 MeV considering the orbital background.The polarimeter exhibited excellent polarization detection performance.The modulation factor was 0.80±0.01,and the polarization angles were accurate within an error of 0.2°at 200 keV for on-axis incidence.For the Crab-like sources for on-axis incidence,the polarization degrees were consistent with the set values within the error tolerance,the modulation factor was 0.76±0.01,and the minimum detectable polarization reached 2.4%at 3σfor an observation time of10^(6) s.Additionally,the polarimeter exhibited recoil electron tracking,imaging,and powerful background suppression in a large field of view(FoV;∼2πsr).The proposed polarimeter meets the requirements of a space soft-gamma-ray polarization detector and has promising research prospects.

Statistical Modification Analysis of Helical Planetary Gears based on Response Surface Method and Monte Carlo Simulation

Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system＇s dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error（DTE） fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system＇s dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.