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.

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.

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.

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.

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.

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.

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.

Monte Carlo simulation of stage separation dynamics of a multistage launch vehicle

This paper provides the formulation used for studing the cold and hot separating stages of a multistage launch vehicle. Monte Carlo simulation is employed to account for the off nominal design parameters of the bodies undergoing separation to evaluate the risk of failure for the separation event. All disturbances, effect of dynamic unbalance, residual thrust, separation disturbance caused by the separation mechanism and misalignment in cold and hot separation are analyzed to find out nonoccurrence of collision between the separation bodies. The results indicate that the current design satisfies the separation requirements.

Monte Carlo Simulation of Propylene Polymerization (Ⅰ) Effects of Impurity on Propylene Polymerization

A comprehensive mechanism for propylene polymerization was proposed by considering the effects of main impurities in the material on propylene polymerization. According to the proposed mechanism, Monte Carlo simulation was employed to investigate the polymerization kinetics in order to determine the effects of the main impurities on the polymerization. Significant influences of the main impurities on the rate, number-average degree and controlling capability of hydrogen of the polymerization were analyzed.

ON THE MONTE CARLO SIMULATION OF NORMAL GRAIN GROWTH

The microstructures and their kinetics of normal grain growth are simulated using different Monte Carlo （MC） algorithms. Compared with the relative figures and the theoretical normal grain growth exponents of n =0.5, the effects of some factors of MC algorithm, i.e. the lattice types, the methods of selecting lattice sites, and the neighbors selection for energy calculations, on the simulation results of grain growth are studied. Two methods of regression were compared, and the three-parameter nonlinear regression is much more suitable for fitting the grain growth kinetics. A better model with appropriate factors included triangular lattice, the attempted site randomly selected, and the first and second nearest neighbors for energy calculations is obtained.

Safety analysis of wheel brake system based on STAMP/STPA and Monte Carlo simulation

The wheel brake system safety is a complex problem which refers to its technical state, operating environment, human factors, etc., in aircraft landing taxiing process. Usually, professors consider system safety with traditional probability techniques based on the linear chain of events. However, it could not comprehensively analyze system safety problems, especially in operating environment, interaction of subsystems, and human factors. Thus,we consider system safety as a control problem based on the system-theoretic accident model, the processes(STAMP) model and the system theoretic process analysis(STPA) technique to compensate the deficiency of traditional techniques. Meanwhile,system safety simulation is considered as system control simulation, and Monte Carlo methods are used which consider the range of uncertain parameters and operation deviation to quantitatively study system safety influence factors in control simulation. Firstly,we construct the STAMP model and STPA feedback control loop of the wheel brake system based on the system functional requirement. Then four unsafe control actions are identified, and causes of them are analyzed. Finally, we construct the Monte Carlo simulation model to analyze different scenarios under disturbance. The results provide a basis for choosing corresponding process model variables in constructing the context table and show that appropriate brake strategies could prevent hazards in aircraft landing taxiing.

Three-Dimensional and Cross-sectional Characteristics of Normal Grain Growth Based on Monte Carlo Simulation

An appropriate Monte Carlo method was developed to simulate the three-dimensional normal grain growth more completely. Comparative investigation on the three-dimensional and the cross-sectional characteristics of normal grain growth was done. It was found that the time exponent of grain growth determined from cross-section exhibits the same rule of increasing slowly with time and approaching the theoretical value n = 0.5 of steadygrain growth as the three-dimensional (3-D) system. From change of the number of grains per unit area with timemeasured in cross-section, the state of 3-D normal grain growth may be predicted. The gtain size distribution incross-section is different from that in 3-D system and can not express the evolution characteristic of the 3-D distribution. Furthermore, there exists statistical connection between the topological parameters in cross-section and thosein three-dimensions.

Accuracy Analysis of Assembly Success Rate with Monte Carlo Simulations

Monte Carlo simulation was applied to Assembly Success Bate (ASK) analyses. ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes, manufacturing tolerances and robot repeatability into account. A statistic arithmetic expression was proposed and deduced in this paper, which offers an alternative method of estimating the accuracy of ASR, without having to repeat the simulations. This statistic method also helps to choose a suitable sample size, if error reduction is desired. Monte Carlo simulation results demonstrated the feasibility of the method.

Grain size distribution and topology in 3D grain growth simulation with large-scale Monte Carlo method

Three-dimensional normal grain growth was appropriately simulated using a Potts model Monte Carlo algorithm. The quasi-stationary grain size distribution obtained from simulation agreed well with the experimental result of pure iron. The Weibull function with a parameter β=2.77 and the Yu-Liu function with a parameter v =2.71 fit the quasi-stationary grain size distribution well. The grain volume distribution is a function that decreased exponentially with increasing grain volume. The distribution of boundary area of grains has a peak at S/〈S〉=0.5, where S is the boundary area of a grain and 〈S〉 is the mean boundary area of all grains in the system. The lognormal function fits the face number distribution well and the peak of the face number distribution is f=10. The mean radius off-faced grains is not proportional to the face number, but appears to be related by a curve convex upward. In the 2D cross-section, both the perimeter law and the Aboav-Weaire law are observed to hold.

Monte Carlo simulation of neutron sensitivity of microfission chamber in neutron flux measurement

Microfission chambers loaded with highly enriched fissile materials are widely used for measuring power in reactors. The neutron sensitivity of the microfission chamber is a key parameter that determines the accuracy of the power measurement. To evaluate the performance of the FC4A microfission chamber, in this work, we introduced an accurate and validated model of the microfission chamber, a performed Monte Carlo simulation of the neutron sensitivity of the microfission chamber with GEANT4 code, and conducted an irradiation experiment on the neutron irradiation effect platform #3 of the Xi’an Pulsed Reactor. We compared the simulated sensitivity with the experimental results, which showed that the sensitivity obtained from the simulation was in good agreement with the experimental results. In addition, we studied the impact of the design parameters of the fission chamber on the calculated neutron sensitivity of the microfission chamber.