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.

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.

Monte Carlo Simulation of Kinetics of Ammonia Oxidative Decomposition over the Commercial Propylene Ammoxidation Catalyst (Mo-Bi)

Monte Carlo method is applied to investigate the kinetics of ammonia oxidative decomposition over the commercial propylene ammoxidation catalyst(Mo-Bi).The simulation is quite in agreement with experimetal results.Monte Carlo simulation proves that the process of ammonia oxidation decomposition is a two-step reaction.

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.

Verification of modified sum-peak method in Monte Carlo simulation of full energy peak and sum-peak efficiencies of a HPGe detector

The modified sum-peak method estimates radioactivity by using only the peak and the sum-peak count rates.To verify the modified sum-peak method,the dependence of the full energy peak efficiency on the source-to-detector distance in a high-purity germanium detector system was studied using a Geant4 Monte Carlo simulation.The effect of the deadlayer in the germanium crystal was estimated by reference to experiments on 241 Am and the relative efficiency of the detector.The peak efficiency dependence on the source-to-detector distance was compared between the simulation and measurements.The modified sum-peak method is discussed with respect to these peak efficiencies.

Analysis of Pharmacokinetic/Pharmacodynamic Parameters and Dosage Regimen of Posaconazole against <i>Candida</i>spp. and <i>Aspergillus</i>spp. Using Monte Carlo Simulation

Invasive fungal infections (IFI) have recently become increasingly more prevalent, resulting in an increased risk of morbidity and mortality. Both Candida spp. and Aspergillus spp. are major causes of IFI. In this study, we aimed to evaluate the cumulative fraction of response of various dosage regimens of posaconazole against nine Candida spp. and six Aspergillus spp. in both children and adults. Monte Carlo simulation (MCS) was performed to optimize selection of posaconazole dosage regimens. For children, a dosage regimen of 120 mg/m2 posaconazole tid was sufficient to treat fungal infections caused by all six Aspergillus spp. and six of the nine Candida spp. (but was not effective against C. glabrata, C. guilliermondii and C. krusei). In contrast, a 400 mg dosage regimen of posaconazole bid achieved the target pharmacokinetic/pharmacodynamics (PK/PD) parameters against all six Aspergillus spp. and eight of the nine Candida spp. (but was not effective against C. glabrata) in the adults. Dosage regimens of 50 mg bid, 100 mg bid, or 200 mg bid were not effective. Posaconazole dosage regimens are likely to achieve their desired PK/PD targets against Candida spp. and Aspergillus spp. in both children and adults.

Optimized Reimbursement Scheme of China's New Cooperative Medical System Using Monte Carlo Simulation

China＇s Rural Cooperative Medical System collapsed alongside communal farming at the end of the Maoist period in 1976, leaving most farmers vulnerable[1]. In rural areas, where 80% of people have been without health insurance of any kind, illness has emerged as a leading cause of poverty[24]. To address the poor state of health care among the rural population, in 2003 the Chinese government launched the New Rural Cooperative Medical System （NCMS）,

Three-dimensional Monte Carlo simulation of bulk fin field effect transistor

In this paper, we investigate the performance of the bulk fin field effect transistor （FinFET） through a three- dimensional （3D） full band Monte Carlo simulator with quantum correction. Several scattering mechanisms, such as the acoustic and optical phonon scattering, the ionized impurity scattering, the impact ionization scattering and the surface roughness scattering are considered in our simulator. The effects of the substrate bias and the surface roughness scattering near the Si/SiO2 interface on the performance of bulk FinFET are mainly discussed in our work. Our results show that the on-current of bulk FinFET is sensitive to the surface roughness and that we can reduce the substrate leakage current by modulating the substrate bias voltage.

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.

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.

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.

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.

A MONTE CARLO SIMULATION OF THE CVD DIAMOND FILM

A Monte Carlo algorithm has been developed by the authors to simulate the chemical vapor deposition (CVD) processes of diamond films. The method considers both the diffusion and the incorporation of the growth radicals on the growing surface in simulating the evolution of the morphology and microstructure. The calculation of configuration energy is used to determine the orientation of adsorbed growth radicals. The effect of processing variables such as nucleation density and substrate temperature on the morphology and microstructure is discussed. It is found that competitive characteristic and coarsening effect exist in the simulation results, which agree with the experimental observations.

3-D Fracture Network Modelling in Hydropower Engineering Based on Optimal Monte Carlo Simulation

Effectively and accurately modelling the spatial relation of fracture surfaces is crucial in the design and construction of large hydropower dams having a complex underlying geology. However, fracture surfaces are randomly formed and vary greatly with respect to their spatial distribution, which makes the construction of accurate 3-D models challenging. In this study, we use an optimal Monte Carlo simulation and dynamic conditioning to construct a fracture network model. We found the optimal Monte Carlo simulation to effectively reduce the error associated with the Monte Carlo method and use dynamic conditioning to ensure the consistency of the model with the actual distribution of fractures on the excavation faces and outcrops. We applied this novel approach to a hydropower station on the Jinshajiang River, China. The simulation results matched the real sampled values well, confirming that the model is capable of effectively and accurately simulating the spatial relations in a fracture network.

Kinetic Monte Carlo Simulation of EB-PVD Film:Effects of Substrate Temperature

The 2D kinetic Monte Carlo （KMC） simulation was used to study the effects of different substrate temperatures on the microstructure of Ni-Cr films in the process of deposition by the electron beam physical vapor deposition （EB-PVD）. In the KMC model, substrate was assumed to be a ＂surface＂ of tight-packed rows, and the simulation includes two phenomena： adatom-surface collision and adatom diffusion. While the interaction between atoms was described by the embedded atom method, the jumping energy was calculated by the molecular static （MS） calculation. The initial location of the adatom was defined by the Momentum Scheme. The results reveal that there exists a critical substrate temperature which means that the lowest packing density and the highest surface roughness structure will be achieved when the temperature is lower than the smaller critical value, while the roughness of both surfaces and the void contents keep decreasing with the substrate temperature increasing until it reaches the higher critical value. The results also indicate that the critical substrate temperature rises as the deposition rate increases.

Nanocrystallization behaviour of a ternary amorphous alloy during isothermal annealing： a Monte Carlo simulation

The nanocrystallization behaviour of Zr70Cu20Ni10 metallic glass during isothermal annealing is studied by employing a Monte Carlo simulation incorporating with a modified Ising model and a Q-state Potts model. Based on the simulated microstructure and differential scanning calorimetry curves, we find that the low crystal-amorphous interface energy of Ni plays an important role in the nanocrystallization of primary Zr2Ni. It is found that when T〈T1max （where T1max is the temperature with maximum nucleation rate）, the increase of temperature results in a larger growth rate and a much finer mierostrueture for the primary Zr2Ni, which accords with the microstructure evolution in ＂flash annealing＂. Finally, the Zr2Ni/Zr2Cu interface energy σG contributes to the pinning effect of the primary nano-sized Zr2Ni grains in the later formed normal Zr2Cu grains.

Slope reliability analysis based on Monte Carlo simulation and sparse grid method

In order to solve the problem of the reliability of slope engineering due to complex uncertainties, the Monte Carlo simulation method is adopted. Based on the characteristics of sparse grid, an interpolation algorithm, which can be applied to high dimensional problems, is introduced. A surrogate model of high dimensional implicit function is established, which makes Monte Carlo method more adaptable. Finally, a reliability analysis method is proposed to evaluate the reliability of the slope engineering, and is applied in the Sau Mau Ping slope project in Hong Kong. The reliability analysis method has great theoretical and practical significance for engineering quality evaluation and natural disaster assessment.

Accuracy Analysis of Assembly Success Rate with Monte Carlo Simulations

Monte Carlo simulation was applied to Assembly Success Rate (ASR) 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.

The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory Requirements

During the assembly of internal combustion engines, the specific size of crankshaft shell bearing is not known until the crankshaft is fitted to the engine block. Though the build requirements for the engine are consistent, the consumption profile of the different size shell bearings can follow a highly volatile trajectory due to minor variation in the dimensions of the crankshaft and engine block. The paper assesses the suitability of time series models including ARIMA and exponential smoothing as an appropriate method to forecast future requirements. Additionally, a Monte Carlo method is applied through building a VBA simulation tool in Microsoft Excel and comparing the output to the time series forecasts.