Two-dimensional Monte Carlo Simulation Research Articles

Assessing and mitigating health risks of workers exposed to volatile organic compounds in contaminated soils during active pit excavation: accounting for exposure variability and uncertainty

Health risks to workers involved in the active pit excavation of volatile organic compound (VOC)-contaminated soils have been overlooked, despite the prevalence of ex-situ remediation practices in China. This study developed a new VOC exposure in pit excavation (VEPE) model that comprehensively accounts for the release of gas-phase VOCs in soil pores, surface volatilization of newly exposed agglomerates, and volatilization of newly exposed excavation pit bottom surfaces. Additionally, the model incorporates the concentration variation of soil contaminants, spatial heterogeneity of soil properties, and the variability and uncertainty of worker exposure using two-dimensional Monte Carlo simulation (2D MCS), highlighting the importance of controlling area of new exposure surfaces, soil saturation, and air exchange during the pit excavation to mitigate risks. The study evaluated worker-health-based risks during the excavation of a VOC-contaminated site in Beijing and revealed that the inhalation cancer risk for trichloroethylene (2.35×10-6) and its hazard quotient (143.92) exceed the acceptable levels (10-6 and 1.0, respectively). The comparison of models demonstrated the theoretical advancements of the VEPE model over existing pit excavation models, while the field test comparison showed a significant improvement in the predication accuracy. This study addresses the under-researched area of worker safety in contaminated excavation sites. The findings have the potential to promote cleaner and more sustainable practices in ex-situ contaminated site remediation by providing valuable insights for implementing effective control measures to mitigate the emission of toxic VOCs, thereby reducing adverse social and environmental impacts.

Two- and Three-Dimensional Modeling and Simulations of Grain Growth Behavior in Dual-Phase Steel Using Monte Carlo and Machine Learning.

Dual-phase (DP) steel has been widely used in automotive steel plates with a balance of excellent strength and ductility. Grain refinement in DP steel is important to improve the properties further; however, the factors affecting grain growth need to be well understood. The remaining problem is that acquiring data through experiments is still time-consuming and difficult to evaluate quantitatively. With the development of materials informatics in recent years, material development time and costs are expected to be significantly reduced through experimentation, simulation, and machine learning. In this study, grain growth behavior in DP steel was studied using two-dimensional (2D) and three-dimensional (3D) Monte Carlo modeling and simulation to estimate the effect of some key parameters. Grain growth can be suppressed when the grain boundary energy is greater than the phase boundary energy. When the volume fractions of the matrix and the second phase were equal, the suppression of grain growth became obvious. The long-distance diffuse frequency can promote grain growth significantly. The simulation results allow us to better understand the factors affecting grain growth behavior in DP steel. Machine learning was performed to conduct a sensitivity analysis of the affecting parameters and estimate the magnitude of each parameter's effects on grain growth in the model. Combining MC simulation and machine learning will provide one promising research strategy to gain deeper insights into grain growth behaviors in metallic materials and accelerate the research process.

New insights into health risk assessment on soil trace metal(loid)s: Model improvement and parameter optimization

Trace metal(loid)s (TMs) in soils may pose potential health risks to humans. Due to model uncertainty and variability of exposure parameters, the traditional health risk assessment (HRA) model may lead to inaccurate risk assessment results. Therefore, this study developed an improved HRA model to assess health risks by combining two-dimensional Monte Carlo simulation (2-D MCS) with a Logistic Chaotic sequence based on published data from 2000 to 2021. The results showed children and adult females were the high-risks populations for Non-carcinogenic risk and Carcinogenic risk, respectively. Meanwhile, children’s Ingestion rate (IngR < 160.233 mg/day) and adult females’ Skin adherence factor (0.026 mg/(cm2•d) < AF < 0.263 mg/(cm2•d)) were used as recommended exposure to make the health risk within acceptable range. Additionally, when performing risk assessment using actual exposure parameters, priority control TMs were identified, with As being the priority control TM for Southwest China and Inner Mongolia, whereas Cr and Pb for Tibet and Yunnan, respectively. Compared to health risk assessment, improved models increased risk assessment accuracy and provided recommended exposure parameter for high-risk populations. This study will provide new insights for soil-related health risk assessment.

Estimation of the Distribution of Dietary Exposure to Lead Using Two-Dimensional Monte Carlo Simulation: An Attempt to Apply to Total Diet Samples

The average dietary exposure to lead (Pb) in male and female Japanese individuals >1 year of age was estimated using 280 total diet samples representing 14 food groups from 10 areas over a two-year period. A probabilistic exposure estimation was performed using a two-dimensional Monte Carlo simulation (2D-MCS) with a Bayesian estimation that consided the uncertainty of the estimation process. The Bayesian estimation was performed using the likelihood function with cumulative distribution function between the lower and upper boundary values for no-detected values. The median dietary exposure to Pb was estimated as 5.82 μg/person/day. The 90% interval was 2.51-16.9 μg/person/day. Comparison with previously reported Pb exposure values indicates that the estimation of Pb exposure distribution using total diet samples is reasonable. The contribution to Pb exposure was highest in the order of food group 8 (light-colored vegetables, mushrooms, and seaweeds: 20.0±16.1%)>food group 1 (rice and rice products: 12.3±19.0%)>food group 10 (fish and shellfish: 10.5±13.9%). Owing to the high uncertainties of contribution ratios, it was not possible to identify dominant food groups contributing to Pb exposure. However, it was evident that the uncertainty of the estimation of Pb exposure was influenced by the uncertainty of Pb concentration than the uncertainty of food consumption rate. In particular, the effect of uncertainty from the Pb concentration of the food group 1 was 68.2%. When the margin of exposures were calculated, the estimated probabilities that a value would be <1 were 14.5% for developmental neurotoxicity to children (1-6 years old), 0.13% for blood pressure and 0.93% for kidney disease in Japanese individuals ≥1 year of age. The findings suggest that the health risk due to dietary Pb exposure is small but not negligible.

Kinetic approach to the analysis of the flow around a levitating microdroplet

Two-dimensional direct Monte Carlo simulation of the flow around an evaporating water microdroplet in the air atmosphere above a dry or liquid surface has been carried out. We consider a cylindrical droplet 1 μm in diameter at a distance of 1 μm above the surface. The temperature of the droplet is taken equal to 65°C and 80°C. A significant decrease in the air concentration between the droplet and the liquid film surface is observed. The features of water vapor flow separately from the droplet surface and from the liquid film surface are considered. It is shown that, under certain conditions, condensation on the lower side and evaporation on the upper side on the droplet can occur simultaneously.

Monte Carlo simulation of dead-end diafiltration of bidispersed particle suspensions.

A two-dimensional Monte Carlo simulation of dead-end diafiltration of bidispersed particle suspensions was performed. The diafiltration process involves separation of components based on their size by using a permeable membrane. The continuous model was applied to study separation of mixture of disks with diameter d and D (D>d). It was assumed that the membrane at the bottom was permeable to the particles of the smaller diameter d, and impermeable to the particles of the larger diameter D. The process of vertical filtration was accompanied by the simultaneous Brownian motion of the particles and downward movement of the piston. The mixtures with different numerical concentrations of particles, diameter ratio, and initial size of the systems in the vertical direction L_{y} have been studied. The time dependencies of the rejection coefficient k and relative height of suspension h/L_{y} revealed the presence of complete and incomplete separation regimes. The presence of filtration and diffusion-driven stratification of the disks in the vertical direction was observed. The phenomenon of incomplete separation was explained by the formation of an impenetrable barrier from larger particles at the bottom of the deposit.

Toward an efficient hybrid method for pricing barrier options on assets with stochastic volatility

Alexander Lipton and Artur Sepp combine the one-dimensional Monte Carlo simulation and the semi-analytical one-dimensional heat potential method to design an efficient technique for pricing barrier options on assets with correlated stochastic volatility. The authors� approach to barrier options valuation utilizes two loops. First, the authors run the outer loop by generating volatility paths via the Monte Carlo method. Second, the authors condition the price dynamics on a given volatility path and apply the method of heat potentials to solve the conditional problem in closed form in the inner loop. Lipton and Sepp illustrate the accuracy and efficacy of their semi-analytical approach by comparing it with the two-dimensional Monte Carlo simulation and a hybrid method, which combines the finite-difference technique for the inner loop and the Monte Carlo simulation for the outer loop. The authors apply their method for computation of state probabilities (Green's function), survival probabilities, and values of call options with barriers. The approach provides better accuracy and is orders of magnitude faster than the existing methods. As a by-product of their analysis, Lipton and Sepp generalize Willard's (1997) conditioning formula for valuation of path-independent options to path-dependent options and derive a novel expression for the joint probability density for the value of drifted Brownian motion and its running minimum.

Two-dimensional Monte Carlo simulations in LCA: an innovative approach to guide the choice for the environmentally preferable option

Two-dimensional Monte Carlo simulations in LCA: an innovative approach to guide the choice for the environmentally preferable option

Installation design of a large tubular caisson in the spatially varying seabed

The installation of large steel tubular caissons, used as protection for underwater production systems, is still a challenge. To evaluate the reliability of installation, soil spatial variability is accounted for in this study through two-dimensional random field establishments and Monte Carlo simulation. As vertical random parameters are identified by field CPT data, the effect of the horizontal scale of fluctuation (δh) is explored, which becomes significant due to the extremely large diameter of the caisson. Probability distributions of self-weight penetration, inclination angle, and the ultimate soil resistance with various δh are derived from conventional installation analyses with spatially varying soil domains. It shows that increasing δh reduces the likelihood of over-tilt, yet raises the possibility of vibratory drivability refusal (failure probability). The effect of stiffeners during caisson installation is also studied, including an increase in penetration resistance and failure probability. This analysis sheds light on the impact of the soil correlation distance as well as caisson stiffeners and is useful to the reliable installation design of the large tubular caisson, particularly in layered soil.

Quantitative microbial risk assessment of human norovirus infection in environmental service workers due to healthcare-associated fomites

Healthcare-associated norovirus outbreaks place a large burden on healthcare staff. Environmental service workers (ESWs), however, remain understudied despite high contact with potentially contaminated surfaces. Understanding the magnitude of the risk of norovirus infection in healthcare ESWs can protect workers and improve infection control. This study simulated the risk of norovirus infection for unprotected ESWs after a single fomite contact, assuming no disinfection or protective equipment, in norovirus-positive patient rooms. In addition, the risk of secondary surface transmission from norovirus-exposed ESWs was simulated. A quantitative microbial risk assessment employing two-dimensional Monte Carlo simulation with parameters extracted from the literature was used to estimate norovirus infection from multiple fomite contact scenarios defined by: norovirus source (patient vomit/diarrhoea), location (bathroom/patient room) and target outcome (ESW/secondary illness). Unprotected ESWs have a maximum estimated risk of norovirus infection of 33% (1:3) for a single fomite contact in a room where a norovirus-positive patient had a diarrhoeal event. Patient vomit events lead to fomite contact risk estimates that are four orders of magnitude lower than those for diarrhoeal events. The estimated risk of secondary illness from touching a common surface is as high as 25% (1:4) after single fomite exposure following a diarrhoeal event. A single fomite contact may lead to sizable risk of norovirus infection in ESWs if personal protective equipment and disinfection are not used appropriately. ESWs can also transfer virus to secondary surfaces, initiating further infections. Interventions are needed to reduce fomite transfer of norovirus, and protect patients and staff from nosocomial infections.

Occurrence and Probabilistic Risk Assessment of Fumonisin B1, Fumonisin B2 and Deoxynivalenol in Nixtamalized Maize in Mexico City.

Fumonisins (FB1+FB2) and deoxynivalenol (DON) are mycotoxins produced by Fusarium species that might be present in maize and maize products. Knowledge on their occurrence in nixtamalized maize from Mexico together with an accompanying risk assessment are scarce, while nixtamalized maize is an important food in Mexico. This study presents the occurrence of FB1 + FB2 and DON in nixtamalized maize samples collected in Mexico City and analyses their distribution and resulting estimated daily intake for Mexican consumers by a probabilistic approach using a two-dimensional Monte-Carlo simulation. The results obtained reveal that for FB1 + FB2, 47% of the Mexican men and 30% of the Mexican women might exceed the provisional tolerable daily intake (PMTDI) of 2 µg/kg bw/day for fumonisins and for DON, 9% of men and 5% of women would be exceeding the PMTDI of 1 µg/kg bw/day, corresponding to the high consumers. The results raise a flag for risk managers in Mexico, to consider regulations and interventions that lower mycotoxin levels in nixtamalized maize for human consumption.

Outbreak-Based Giardia Dose-Response Model Using Bayesian Hierarchical Markov Chain Monte Carlo Analysis.

Giardia is a zoonotic gastrointestinal parasite responsible for a substantial global public health burden, and quantitative microbial risk assessment (QMRA) is often used to forecast and manage this burden. QMRA requires dose-response models to extrapolate available dose-response data, but the existing model for Giardia ignores valuable dose-response information, particularly data from several well-documented waterborne outbreaks of giardiasis. The current study updates Giardia dose-response modeling by synthesizing all available data from outbreaks and experimental studies using a Bayesian random effects dose-response model. For outbreaks, mean doses (D) and the degree of spatial and temporal aggregation among cysts were estimated using exposure assessment implemented via two-dimensional Monte Carlo simulation, while potential overreporting of outbreak cases was handled using published overreporting factors and censored binomial regression. Parameter estimation was by Markov chain Monte Carlo simulation and indicated that a typical exponential dose-response parameter for Giardia is r = 1.6 × 10-2 [3.7 × 10-3 , 6.2 × 10-2 ] (posterior median [95% credible interval]), while a typical morbidity ratio is m = 3.8 × 10-1 [2.3 × 10-1 , 5.5 × 10-1 ]. Corresponding (logistic-scale) variance components were σr = 5.2 × 10-1 [1.1 × 10-1 , 9.6 × 10-1 ] and σm = 9.3 × 10-1 [7.0 × 10-2 , 2.8 × 100 ], indicating substantial variation in the Giardia dose-response relationship. Compared to the existing Giardia dose-response model, the current study provides more representative estimation of uncertainty in r and novel quantification of its natural variability. Several options for incorporating variability in r (and m) into QMRA predictions are discussed, including incorporation via Monte Carlo simulation as well as evaluation of the current study's model using the approximate beta-Poisson.

Empirical modeling and Monte Carlo simulation of secondary electron yield reduction of laser drilled microporous gold surfaces

This work investigates secondary electron yield (SEY) mitigation from a metal surface with a microporous array fabricated using the laser drilling technique. We propose a general empirical model to fit the experimentally measured SEY of a flat gold surface for normal and oblique incidences of primary electrons. Using this empirical model, we develop a two-dimensional Monte Carlo (MC) simulation scheme to determine the effective SEY of a microporous array. It is found that the SEY from a porous surface is significantly reduced compared to that of the flat surface. By taking into account all the generations of secondary electrons inside a well, our MC results are found to be in very good agreement with the experimental data. The dependence of the SEY on the aspect ratio of the micropores and porosity of the surface is examined. A simple empirical formula has been proposed to evaluate the effective SEY of the gold microporous array for pores of arbitrary aspect ratios.

Two-dimensional Ostwald ripening with irreversible absorption or reaction on boundaries

During Ostwald ripening, the growth of larger patches occurs at the expense of smaller ones via detachment, diffusion, and attachment of monomers. Customarily, the processes belonging to this important class are simulated with periodic boundary conditions. The two-dimensional Monte Carlo simulations presented herein are focused on the situation when diffusing monomers disappear as soon as they reach the lattice boundaries. For the Fickian diffusion (without the driving force for ripening), the shape of the corresponding kinetics and the time scale characterizing the drop of the concentration are independent of the initial concentration of monomers, the shape is independent of the lattice size as well, while the time scale is inversely proportional to the square of the lattice size. With attractive interaction between monomers (this is the driving force for ripening), the time scale characterizing the drop of the concentration remains to be nearly inversely proportional to the square of the lattice size but increases with increasing the initial concentration of monomers. The lattice snapshots show that with increasing time the Ostwald-type patches first rapidly reach appreciable size, but then disappear at the periphery due the loss of monomers at the boundaries. The central area where these patches are observed shrinks, and nevertheless the patches grow there.

Giant Piezoresistance Effect of Asymmetric Ferroelectric Tunnel Junction: a Monte Carlo study

Using two-dimensional Ising model and Monte Carlo simulation method, the giant piezoresistance effect (GPE) of ferroelectric tunnel junction (FTJ) is studied. Under different axial pressures, the changes of polarization for different thin ferroelectrics film were simulated. The relationship between pressure and resistance of asymmetric FTJ was numerically investigated. Using this relationship, the giant piezoelectric resistance effect of asymmetric FTJ under different thickness was calculated and discussed. The resistance of FTJ increased at least with an order of magnitude, under the condition of 5 GPa pressure.

Estimated Thyroid Inhalation Doses Based on Body Surface Contamination Levels of Evacuees After the Fukushima Daiichi Nuclear Power Plant Accident.

Doses of inhaled radionuclides received during evacuation might be correlated with amounts of those radionuclides on an evacuee's body surface. The purpose of the present study was to estimate thyroid equivalent doses based on body surface contamination measured with a Geiger-Mueller survey meter on 2,087 evacuees from Tomioka, Okuma, Futaba, Naraha, Namie, Minamisoma, and other municipalities in Japan. The measurement value in cpm was translated into Bq cm according to the radionuclide composition obtained by germanium gamma-spectrometry analyses of two persons' clothing. Thyroid equivalent dose by inhalation was estimated by two-dimensional Monte Carlo simulation based on the distribution of body surface radionuclide concentration and a uniform distribution of deposition velocity. For evacuees exposed twice on 12 and 15 March, the mean, median, and 90th percentile of inhalation thyroid equivalent dose for 1-y-old children were 21.4 mSv, 4.7 mSv, and 40.1 mSv for the Namie group; 7.3 mSv, 5.1 mSv, and 14.8 mSv for the Minamisoma group; and 2.3 mSv, 0.5 mSv, and 4.0 mSv for the group comprising Tomioka, Okuma, Futaba, and Naraha. These estimates are smaller than estimates in the United Nations Scientific Committee on the Effects of Atomic Radiation 2013 report but closer to estimates based on direct thyroid I measurement or indirect estimates based on Cs measurements made with a whole-body counter under the assumption that the ratio of I to Cs is 3.8.

Two-Dimensional Monte Carlo simulations on Phase Change of the Aggregate Structures of Spheroidal Hematite Particles

Two-Dimensional Monte Carlo simulations on Phase Change of the Aggregate Structures of Spheroidal Hematite Particles

Dynamics of gas cloud expansion under pulsed laser evaporation into vacuum

Two-dimensional direct Monte Carlo simulation of neutral gas expansion under pulsed evaporation into vacuum has been performed. Analysis of temporal evolution of the spatially-averaged characteristics of the plume has been carried out for a wide range of the problem parameters: the spot radius and the evaporation depth. Special attention has been paid to determination of the limits of applicability of one-dimensional approach for gas dynamic simulation.

Two-dimensional Monte Carlo simulations of coarse-grained poly(3-hexylthiophene) (P3HT) adsorbed on striped substrates.

We investigate the structural phases of single poly(3-hexylthiophene) (P3HT) polymers that are adsorbed on a two-dimensional substrate with a striped pattern. We use a coarse-grained representation of the polymer and sophisticated Monte Carlo techniques such as a parallelized replica exchange scheme and local as well as non-local updates to the polymer's configuration. From peaks in the canonically derived observables, it is possible to obtain structural phase diagrams for varying substrate parameters. We find that the shape of the stripe pattern has a substantial effect on the obtained configurations of the polymer and can be tailored to promote either more stretched out or more compact configurations. In the compact phases, we observe different structural motifs, such as hairpins, double-hairpins, and interlocking "zipper" states.

Mathematical Modeling and Simulations for Large-Strain J-Shaped Diagrams of Soft Biological Materials.

Herein, we study stress–strain diagrams of soft biological materials such as animal skin, muscles, and arteries by Finsler geometry (FG) modeling. The stress–strain diagram of these biological materials is always J-shaped and is composed of toe, heel, linear, and failure regions. In the toe region, the stress is almost zero, and the length of this zero-stress region becomes very large (≃150%) in, for example, certain arteries. In this paper, we study long-toe diagrams using two-dimensional (2D) and 3D FG modeling techniques and Monte Carlo (MC) simulations. We find that, except for the failure region, large-strain J-shaped diagrams are successfully reproduced by the FG models. This implies that the complex J-shaped curves originate from the interaction between the directional and positional degrees of freedom of polymeric molecules, as implemented in the FG model.