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.

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.

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.

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.

Reconstructing in vivo spatially offset Raman spectroscopy of human skin tissue using a GPU-accelerated Monte Carlo platform

As one type of spatially offset Raman spectroscopy(SORS), inverse SORS is particularly suited to in vivo biomedical measurements due to its ring-shaped illumination scheme. To explain inhomogeneous Raman scattering during in vivo inverse SORS measurements, the light–tissue interactions when excitation and regenerated Raman photons propagate in skin tissue were studied using Monte Carlo simulation. An eight-layered skin model was first built based on the latest transmission parameters. Then, an open-source platform, Monte Carlo e Xtreme(MCX), was adapted to study the distribution of 785 nm excitation photons inside the model with an inverse spatially shifted annular beam. The excitation photons were converted to emission photons by an inverse distribution method based on excitation flux with spatial offsets Δs of 1 mm, 2 mm, 3 mm and 5 mm. The intrinsic Raman spectra from separated skin layers were measured by continuous linear scanning to improve the simulation accuracy. The obtained results explain why the spectral detection depth gradually increases with increasing spatial offset, and address how the intrinsic Raman spectrum from deep skin layers is distorted by the reabsorption and scattering of the superficial tissue constituents. Meanwhile, it is demonstrated that the spectral contribution from subcutaneous fat will be improved when the offset increases to 5 mm, and the highest detection efficiency for dermal layer spectral detection could be achieved when Δs = 2 mm. Reasonably good matching between the calculated spectrum and the measured in vivo inverse SORS was achieved, thus demonstrating great utility of our modeling method and an approach to help understand the clinical measurements.

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.

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.

A Simple Monte Carlo Method for Locating the Three-dimensional Critical Slip Surface of a Slope

Based on the assumption of the plain-strain problem, various optimization or random search methods have been developed for locating the critical slip surfaces in slope-stability analysis, but none of such methods is applicable to the 3D case. In this paper, a simple Monte Carlo random simulation method is proposed to identify the 3D critical slip surface. Assuming the initial slip to be the lower part of a slip ellipsoid, the 3D critical slip surface is located by means of a minimized 3D safety factor. A column-based 3D slope stability analysis model is used to calculate this factor. In this study, some practical cases of known minimum safety factors and critical slip surfaces in 2D analysis are extended to 3D slope problems to locate the critical slip surfaces. Compared with the 2D result, the resulting 3D critical slip surface has no apparent difference in terms of only cross section, but the associated 3D safety factor is definitely higher.

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.

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.

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.

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 Fractures Using Isogeometric Boundary Element Methods Based on POD-RBF

This paper presents a novel framework for stochastic analysis of linear elastic fracture problems.Monte Carlo simulation(MCs)is adopted to address the multi-dimensional uncertainties,whose computation cost is reduced by combination of Proper Orthogonal Decomposition(POD)and the Radial Basis Function(RBF).In order to avoid re-meshing and retain the geometric exactness,isogeometric boundary element method(IGABEM)is employed for simulation,in which the Non-Uniform Rational B-splines(NURBS)are employed for representing the crack surfaces and discretizing dual boundary integral equations.The stress intensity factors(SIFs)are extracted by M integral method.The numerical examples simulate several cracked structures with various uncertain parameters such as load effects,materials,geometric dimensions,and the results are verified by comparison with the analytical solutions.

On the energy conservation electrostatic particle-in-cell/Monte Carlo simulation: Benchmark and application to the radio frequency discharges

We benchmark and analyze the error of energy conservation （EC） scheme in particle-in-cell/Monte Carlo （PIC/MC） algorithms by simulating the radio frequency discharge. The plasma heating behaviors and electron distributing functions obtained by one-dimensional （1D） simulation are analyzed. Both explicit and implicit algorithms are checked. The results showed that the EC scheme can eliminated the self-heating with wide grid spacing in both cases with a small reduction of the accuracies. In typical parameters, the EC implicit scheme has higher precision than EC explicit scheme. Some ＂numerical cooling＂ behaviors are observed and analyzed. Some other errors are also analyzed. The analysis showed that the EC implicit scheme can be used to qualitative estimation of some discharge problems with much less computational resource cost without much loss of accuracies.

Monte Carlo simulation of reflection effects of multi-element materials on gamma rays

To study the effects of the gamma reflection of multi-element materials,gamma ray transport models of single-element materials,such as iron and lead,and multielement materials,such as polyethylene and ordinary concrete,were established in this study.Relationships among the albedo factors of the gamma photons and energies and average energy of the reflected gamma rays by material type,material thickness,incident gamma energy,and incidence angle of gamma rays were obtained by Monte Carlo simulation.The results show that the albedo factors of single-element and multi-element materials increase rapidly with an increase in the material thickness.When the thickness of the material increases to a certain value,the albedo factors do not increase further but rather tend to the saturation value.The saturation values for the albedo factors of the gamma photons,and energies and the reflection thickness are related not only to the type of material but also to the incident gamma energy and incidence angle of the gamma rays.At a given incident gamma energy,which is between 0.2 and 2.5 MeV,the smaller the effective atomic number of the multi-element material is,the higher the saturation values of the albedo factors are.The larger the incidence angle of the gamma ray is,the greater the saturation value of the gamma albedo factor,saturation reflection thickness,and average saturation energy of the reflected gamma photons are.

Monte Carlo Analytic Hierarchy Process (MAHP) approach to selection of optimum mining method

One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developing a Monte Carlo simulation to selection the optimum mining method by using effective and major criteria and at the same time,taking subjective judgments of decision makers into consideration.Proposed approach is based on the combination of Monte Carlo simulation with conventional Analytic Hierarchy Process(AHP).Monte Carlo simulation is used to determine the confdence level of each alternative’s score,is calculated by AHP,with the respect to the variance of decision makers’opinion.The proposed method is applied for Jajarm Bauxite Mine in Iran and eventually the most appropriate mining methods for this mine are ranked.

Monte Carlo simulation of sequential structure control of AN-MA-IA aqueous copolymerization by different operation modes

The regulation of polyacrylonitrile(PAN)copolymer composition and sequence structure is the precondition for producing high-quality carbon fiber high quality.In this work,the sequential structure control of acrylonitrile(AN),methyl acrylate(MA)and itaconic acid(IA)aqueous copolymerization was investigated by Monte Carlo(MC)simulation.The parameters used in Monte Carlo were optimized via machine learning(ML)and genetic algorithms(GA)using the experimental data from batch copolymerization.The results reveal that it is difficult to control the aqueous copolymerization to obtain PAN copolymer with uniform sequence structure by batch polymerization with one-time feeding.By contrary,it is found that the PAN copolymer with uniform composition and sequence structure can be obtained by adjusting IA feeding quantity in each reactor of a train of five CSTRs.Hopefully,the results obtained in this work can provide valuable information for the understanding and optimization of AN copolymerization process to obtain high-quality PAN copolymer precursor.

Groundwater pollution and human health risk based on Monte Carlo simulation in a typical mining area in Northern Anhui Province,China

The main objective of this study was to evaluate eight kinds of trace element pollutants in groundwater from a typical coal mine area,and carry out a corresponding health risk assessment for the local populace.To do this,34 shallow groundwater(SG)samples and 18 mid-layer groundwater(MG)samples were collected from the Sulin mining area.To minimize the uncertainties in the health risk assessment,this paper relied on Monte Carlo simulations and sensitivity analysis.The results revealed that Sr and Mn contents exceeded their corresponding WHO(Guidelines for drinking water quality,4th edn.Geneva,2011)guidelines and Chinese groundwater standards(GB/T14848-2017),while the other analyzed trace elements remain below those threshold values.The calculated hazard quotient and hazard index values for adults from ingestion exposure to SG and MG were well below the threshold limit of 1.Probabilistic simulations further show that the total cancer risk value above the limit of 1×10^(-6) is 0%for SG and 29.39%for MG.Sensitivity analysis identified the Sr and Cr contents as the most relevant element variables affecting the probabilistic non-carcinogenic and carcinogenic risk values in the model,respectively.

Magnetic properties of La2CuMnO6 double perovskite ceramic investigated by Monte Carlo simulations

We present a theoretical study of the magnetic properties of the lanthanum copper manganate double perovskite La2CuMnO6 ceramic,using Monte Carlo simulations.We analyze and discuss the ground state phase diagrams in different planes to show the effect of every physical parameter.Based on the Monte Carlo simulations,which combine Metropolis algorithm and Ising model,we explore the thermal behavior of the total magnetization and susceptibility.We also present and discuss the influence of physical parameters such as the external magnetic field,the exchange coupling interactions between magnetic atoms,and the exchange magnetic field on the magnetization of the system.Moreover,the critical temperature of the system is about Tc=70 K,in agreement with the experimental value.Finally,the hysteresis loops of La2CuMnO6 are discussed.

Monte Carlo study on abnormal growth of Goss grains in Fe-3%Si steel induced by second-phase particles

The selective abnormal growth of Goss grains in magnetic sheets of Fe-3%Si （grade Hi-B） induced by second-phase particles （AlN and MnS） was studied using a modified Monte Carlo Ports model. The starting microstructures for the simulations were generated from electron backscatter diffraction （EBSD） orientation imaging maps of recrystallized samples. In the simulation, second-phase particles were assumed to be randomly distributed in the initial microstructures and the Zener drag effect of particles on Goss grain boundaries was assumed to be selectively invalid because of the unique properties of Goss grain boundaries. The simulation results suggest that normal growth of the matrix grains stagnates because of the pinning effect of particles on their boundaries. During the onset of abnormal grain growth, some Goss grains with concave boundaries in the initial microstructure grow fast abnormally and other Goss grains with convex boundaries shrink and eventually disappear.