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In this paper we propose and simulate a new Heterostructure MESFET, Called δ-doped LDD HMESFET. To improve carrier velocity in vicinity of the source in channel of GaAs MESFET, one can replace source with AlxGa 1-x As. By increasing Al content, discontinuity of hetero-interface could be increased. Therefore, the velocity increases in the low field. However, increasing Al mole fraction in excess of some value forces the current to reduce, due to DX centers. To avoid this reduction, we suggest taking the advantage of ?-doped the source-channel hetero-interface. This increase discontinuity of hetero-interface, which is equivalent to increasing Al content. In this paper, we simulate the proposed transistor structure and compare it with the one proposed in [1], ignoring DX centers. In this comparison, we show that the average electron velocity in both transistors is identical.

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In this paper, we examine the effect of the energy difference between the L- and the -valleys in compound semiconductor materials, carrier effective mass, and the scattering processes on the electron transport characteristics in MESFETs. To do this, we use the Monte Carlo simulation to demonstrate the superiority of the InGaAs MESFET, made on a semi-insulating InP substrate, over both InP and GaAs MESFETs. Furthermore, we study the effects of device structure on the electron transport characteristics. For the first time we study electron transport characteristics in the channel of a LDD InGaAs MESFET with an InP source. This structure demonstrates to have the highest average electron velocity through out its channel among the other MESFETs

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Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In this paper, generation reliability is considered, and a method for its assessment using intelligent systems is proposed. Also, because of power market and generators’ forced outages stochastic behavior, Monte Carlo simulation is used for reliability evaluation. Generation reliability, merely focuses on interaction between generation complex and load. Therefore, in this research, based on market type and its concentration, reserve margin, and various future times, a Neuro-Fuzzy system is proposed for evaluation of generation reliability which is valid and usable for all kinds of power pool markets. Finally, the proposed method is assessed on IEEE-Reliability Test System; and generation reliability indices of various markets are evaluated with different reserve margins and different load levels.

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In restructured power systems and in a wholesale power market, a distribution company as a market player intends to maximize its profit by utilizing its options. Hence determining an optimal energy acquisition strategy for a distribution company is vital, for attaining to this goal. However an important challenge for determining these strategies is forecasting other competitors and Generation companies' strategies and competitors' incomplete information must be considered as uncertainties in the problem. In this paper, an energy acquisition model for a distribution company with considering distributed generations, interruptible loads and information's uncertainties in a day-ahead electricity market has been presented. In the proposed method, distribution company energy acquisition strategy has been modeled as a two-level multi-objective optimization problem and has been solved by using nonlinear complementarities and L-P metric methods and then, the uncertainties in the competitors' information, has been applied to the model by using Monte Carlo method. An 8-bus system is employed to illustrate the proposed model and algorithm.

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One of the key concepts in risk managing of financial portfolios is the probability based risk measurement method known as value at risk. During recent years, various methods have been introduced by researchers to compute this criterion. Because of their dissimilar assumptions and procedures, making the use of each of which creates different results. Therefore, this paper uses two main methods in order to measure the value at risk of foreign exchange portfolio. They comprise generalized autoregressive conditional heteroskedasticity model and Monte Carlo Simulation. Using failure rate back testing, the results of these methods are compared. The results of the evaluation demonstrate that the mentioned methods have different performances.

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In this article, Monte Carlo simulation method is used in conjunction with finite elements (FEs) for probabilistic free vibration and stability analysis of pipes conveying fluid. For fluid-structure interaction, Euler-Bernoulli beam model is used for analyzing pipe structure and plug flow model for representing internal fluid flow in the pipe. By considering structural parameters of system as random fields, the governing deterministic partial differential equation (PDE) of continuous system is transformed into a stochastic PDE. The continuous random fields are discretized by mid-point and local average discretization methods; then, by Monte Carlo simulations in each iteration loop, every distributed-parameter PDE having stochastic lumped-parameters is transformed into a deterministic distributed-parameter PDE. Each PDE is transformed into a system of deterministic ordinary differential equations (ODEs) by using FEs. Accordingly, all of the deterministic and stochastic parameters of system are discretized. For free vibration analysis, the eigenvalue problem is solved for investigating the complex-valued eigenvalues and critical eigenfrequencies. Consequently, having complex eigenfrequencies and divergence points, the statistical responses of stochastic problem are obtained like expected values, standard deviations, probability density functions, and the probability of occurrence for divergence instabilities.

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Failure of a concrete gravity dam will cause unavoidable human loss and financial damages. In this study SARIYAR concrete gravity dam, located in turkey was chosen as a case study and its probability of sliding failure in various condition was studied. The most important reason in sliding failure of a concrete dam was lateral and uplift loads, caused by increase in the level of reservoir water. Different scenarios were considered in which might happen for a dam, all the possible height of reservoir water simulated. Afterward, Probability of failure and reliability index was calculated with Monte Carlo simulation and FORM method in all conditions and comparison with each other. The influence of the Number of Simulations (NOS) in the Monte Carlo method was also discussed. Results showed that, in some cases, the resistance of the system was much more than the loads and limit state function had a significant distance from samples. In such states, Monte Carlo was unable to calculate the probability of failure with each NOS but FORM method obtained the Reliability Index (β) in these situations. It became clear that these values were far from reality. With increase in the forces, responses from Monte Carlo had a high degree of precision. The probability of failure generated by FORM method was less than a reality. Failure of a concrete gravity dam will cause unavoidable human loss and financial damages. In this study SARIYAR concrete gravity dam, located in turkey was chosen as a case study and its probability of sliding failure in various condition was studied. The most important reason in sliding failure of a concrete dam was lateral and uplift loads, caused by increase in the level of reservoir water. Different scenarios were considered in which might happen for a dam, all the possible height of reservoir water simulated. Afterward, Probability of failure and reliability index was calculated with Monte Carlo simulation and FORM method in all conditions and comparison with each other. The influence of the Number of Simulations (NOS) in the Monte Carlo method was also discussed. Results showed that, in some cases, the resistance of the system was much more than the loads and limit state function had a significant distance from samples. In such states, Monte Carlo was unable to calculate the probability of failure with each NOS but FORM method obtained the Reliability Index (β) in these situations. It became clear that these values were far from reality. With increase in the forces, responses from Monte Carlo had a high degree of precision. The probability of failure generated by FORM method was less than a reality. Failure of a concrete gravity dam will cause unavoidable human loss and financial damages. In this study SARIYAR concrete gravity dam, located in turkey was chosen as a case study and its probability of sliding failure in various condition was studied. The most important reason in sliding failure of a concrete dam was lateral and uplift loads, caused by increase in the level of reservoir water.

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In this paper the methodology of reliability analysis in aerial structures has been developed. This methodology has been carried out on a special specimen. The selected specimen is a cylinder strut of the landing gear system of a training airplane. This specimen is one of the most important part of the landing gear system. Because of it’s special shape, there is no analytical solution for calculation of stress in it. Therefore, by means of the surface response method and Box-Behnken tables, a deterministic equation for calculating the stresses in critical points of the specimen has been produced. Then in order to obtain the reliability of this part via probabilistic method, Monte Carlo simulation has been used. The applied loads have been modeled whit one pressure, one bending moment and one concentrated force. These loads have been assumed to be independent random variables. Also, the probability distribution function of the pressure and the bending moment have been assumed to be normal and the probability distribution function of the concentrated force has been assumed to be lognormal. The dimensions of the specimen is deterministic and the mechanical properties of the material is a normal distribution with standard deviation equals to be 10 percent of its mean value. The results showed that the minimum reliability of this specimen is 99.9997 percent. So, the design of the cylinder strut is safe for aerial applications in reliability viewpoint.

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In the present study, the convergence behavior of the direct simulation Monte Carlo (DSMC) method is extensively explored. The Simplified Bernoulli Trials (SBT) collision algorithm is applied to simulate a one-dimensional nano Fourier heat conduction problem, which consists of rarefied gas confined between two infinite parallel plates with unequal temperatures. The investigations compares the Sonine-polynomial coefficients ak calculated from the DSMC results with theoretical predictions of the Chapman-Enskog (CE) theory. In addition, the convergence behavior of the wall heat flux and the ratio of the DSMC-calculated bulk thermal conductivity (KDSMC) to the infinite-approximation of CE theoretical value (K) is studied. The numerical accuracy of the DSMC method is found to be restricted in regards to three parameters: time step, cell size, and number of computational particles per cell. The dependency of the SBT collision algorithm on these discretization errors has been investigated in comparison with the standard collision algorithm, i.e., no time counter (NTC). The results indicate that SBT can achieve analytical solutions of the Sonine polynomials using fewer particles per cell than NTC. Moreover, in the SBT algorithm, the effective parameter in the convergence is Δx/Δt ratio, which should be adjusted accurately. This study shows that by decreasing the number of particle per cell to even one particle in a constant Δx/Δt setting, the SBT algorithm accurately predicts solutions where the NTC algorithm fails.

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Reinforcement inside the concrete is protected from corrosion and its damages until several years after the construction. After corrosion initiation, the Cross Section of Reinforcement begins to reduce and often load bearing of the reinforced concrete structure will be reduced significantly. Corrosion of reinforcements in concrete in polluted and contaminated areas can be occurred in two ways: Chloride and Carbonation. Chloride ion ingress is one of the major problems that affect the durability of reinforced concrete structures such as bridge decks, concrete pavements, and other structures exposed to harsh saline environments. Corrosion occurrence and development in reinforced concrete structures increase the steel volume and produce products with volume of about 2-7 times the steel initial volume. This volume increase, which is due to cracks, reduces the compressive and tensile strengths in reinforced concrete structures. Therefore, durability based design of concrete structures in marine areas has gained great significance in recent decades and various mathematical models for estimating the service life of reinforced concrete have been proposed. In spite of comprehensive researches on the corrosion of reinforced concrete, there are still various controversial concepts. Effect of environmental conditions on durability of concrete structures is one of the most important issues. Hence, regional investigations are necessary for durability-based design and evaluation of the models proposed for service-life prediction. The Persian Gulf is one of themost aggressive regions of the world because of elevated temperature and humidity as well as high content of chloride ions in seawater. Corrosion of reinforcement due to chloride ions attack causes enormous damages to structures in severe condition of marine environments. Normally, high alkaline property of concrete (PH≈13) forms a protective oxide layer on the steel surface. This is called a passive protection. The dioxide existing in the atmosphere or the chloride in the concrete environment along with the moisture and the oxygen can penetrate via the concrete pores and cracks and can reach the armature surface; then, by reducing concrete alkalinity, they cause armature corrosion inside the concrete by destroying the protective oxide layer on the steel. Chloride ions reach the passive layer according to the explained pattern and they begin to react in the passive layer when the amount of chloride ions go beyond the critical value and cause perforation corrosion. Since each influencing factor in the life time of the structure is subject to random variability and inherent uncertainties, a stochastic approach is utilized to predict the time for initiation of the corrosion. Based on Fick’s law, time for corrosion is a function of surface chloride, critical chloride, concrete cover thickness, and diffusion coefficient. The most common models service-life prediction of reinforced concrete structures under load chloride, only produce a limited definite time for the start of corrosion. In this paper monte carlo simulation use for service-life prediction of reinforced concrete structures of predict the time of corrosion initiation, and shown the influence of mean and standard deviation variations for each of the parameters that affect the occurrence of corrosion, on the time of initiation corrosion and impact of these factors on the probability initiation corrosion.

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In this paper, reliability of missile system in its total life cycle is evaluated in terms of its subsystems’ reliability, using Continuous Time Markov Chains (CTMC) and Monte Carlo simulation method, finally results of both methods are compared. Missile system’s life cycle includes storage, pre-launch and operation states. Missile system is composed of variety of components and materials, hence different environmental conditions and various stresses imposed on missile system in each state during its life cycle, stimulates diverse failure modes and mechanisms. Therefore, failure probability distribution function differs for each subsystem in each state. Flight control, mechanical parts and equipment, engine and warhead are four main subsystems of the missile system. They are linked in series therefore each one’s failure will result in system’s failure. Exponential, Weibull, Lognormal and Gompertz distributions are used for subsystems’ modeling in different life cycle states. Unlike many other researches in this field, failure rates are time variant. System is supposed to be unrepairable during life cycle. Finally, Continuous Time Markov Chain’s superiority in comparison with Monte Carlo method, both in accuracy and required amount of calculations is demonstrated and a few suggestions, based on obtained results, are presented for system reliability improvement.

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Uncertainty at experimental results usually adds to experimental data in the form of error bound. Since uncertainties at input parameters play an important part at the discrepancy between numerical and experimental results, considering uncertain parameters in comparison of numerical and experimental results would be logical. Electroosmotic flow is one of the cases which uncertainty quantification on its numerical simulation is necessary because of the presence of uncertain parameters. In this study, uncertainty quantification of electroosmotic flow in the micro T-channel has been presented. Numerical method was first validated by comparison between numerical simulation results of electroosmotic flow with certain inputs and experimental data. At the first step of uncertainty quantification, sample generation of the uncertain parameters has been performed by Latin hypercube method. At the next step, governing equation of electroosmotic flow has been solved by finite element method for every sample. Mass flow rate and velocity field have been selected as objective functions and adjoint method was employed for calculating the derivatives of them. At the final stage uncertainty quantification has been performed by enhanced Monte Carlo method. Results of the adjoint method show geometry parameters and fluid viscosity as the most effective factors on the results. While temperature and density of fluid demonstrate the least effect on the objective functions. Results of the Monte Carlo method illustrate 22.4% uncertainty for the results of mass flow rate and 12.6% on average for the results of velocities.

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In recent years, development of polymer electrolyte membrane fuel cells (PEMFCs) has been considered to generate electricity and heat. Among main components of PEMFCs, bipolar plates (BPPs) have significant influence on cost and performance of the system. Metallic BPPs, formed using thin sheets, have been developed as alternative to conventional graphite plates because of advantages such as suitable cost, mechanical strength and power density. Flexibility of the sheets and spring back during forming process make dimensional errors inevitable and lead to inappropriate contact pressure distribution between BPPs and gas diffusion layer (GDL), resulting in decrease of fuel cell performance. Excessive accuracy in BPP production leads to increase the final cost and decrease the general usability of the technology. Therefore, to reduce unnecessary costs, managing design process and improving efficiency, analysis of BPP dimensional errors is done using finite element method and Monte Carlo simulation (MCS). First, contact model of the metallic BPP and GDL is developed and heights of each channel and each rib of BPP are fully parameterized due to stochastic variations of dimensional errors with normal distribution. Then, contact pressure distributions of GDL (Pave, Pstd) for different dimensional errors are obtained by MCSs. Increasing dimensional tolerance from 0.015 mm to 0.075 mm, average contact pressure (Pave) has decreased by 11% and standard deviation of contact pressure (Pstd) has increased up to 90%. Namely desirable distribution of GDL pressure is reduced by increasing the dimensional error and suitable dimensional tolerances for BPPs can be determined according to engineering requirements.

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The soil formation consists of complex and longtime processes in which many different chemical and physical changes occur in soil deposit, or in its original source rock. This processes cause the soil to show nonhomogeneous characteristics and to have spatial variation in its mechanical properties. The spatial variation of soil properties lead to many uncertainties in prediction of soil mechanical behavior; subsequently the design of structure which depend on soil deposits becomes troublesome. For dealing with such problem the probabilistic and statistical tools are proposed as convenient methods for choosing appropriate design soil parameters and estimating the uncertainties in design. The coupled utilization of random field theory and Monte Carlo simulation technique yield probability distribution functions for geotechnical problems in which different cases of soil distribution is assumed for analyses. In such problems the soil properties are distributed into the field according to the assumptions of random field theory by consideration of a probability distribution (with the given mean and standard deviation) and scale of fluctuations. This distribution of soil properties with the use of random field theory is performed repeatedly until a desired statistical distribution for the results is obtained. This distribution can be used as a basis for extracting the statistical characteristics for the problem in hand. In this paper the effect of spatial variability parameters on the bearing capacity of strip foundations on clayey soils were investigated. The soil un-drained shear strength (Cu) was assumed as spatial variable parameter with the use of logarithmic distribution and the so-called coupled random field theory; the Monte Carlo simulation technique was used for obtaining probability distribution of bearing capacity of foundation on nonhomogeneous clayey soil. The Mohr Coloumb elastic perfectly plastic constitutive model and the Finite Difference Method (FDM) were used for modelling soil behavior and calculating the bearing capacity of foundation. The spatial variability of un-drained shear strength was investigated using three parameters: coefficient of variation of un-drained shear strength (Cov(Cu((, and the scale of fluctuation of shear strength in horizontal and vertical directions (x, and y directions). The range of these parameters were chosen such that the results of current research can be generalized to any field problem. The results obtained from this study, were investigated by average and coefficient of variation of NC parameter which is the cohesion factor in classic bearing capacity equations (i.e. as Terzaghi, Meyerhof, Hansen and Vesic bearing capacity equations). It can be interpreted from the results that by increasing the coefficient of variation of soil un-drained shear strength the average bearing capacity decreases and the coefficient of variation of bearing capacity increases; also the average bearing capacity of foundation has an approximately increasing trend with increasing the scale of fluctuations in both horizontal and vertical directions. Finally at the end of this paper two practical simplified equations were suggested using multiple regression method for estimation of average and coefficient of variation of bearing capacity factor NC, given the spatial variation parameters of soil un-drained shear strength. These equations can be implemented by geotechnical experts for applying the variability of cohesion in the design of foundations on nonhomogeneous clayey soil formations.

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The types and varieties of peppers grown in Mediterranean areas are a response to the demand of European markets, although in each Autonomous Community local varieties are grown to satisfy the national demand. Nowadays, the range of shapes, colours, tastes and uses is wider than ever as a result of greenhouse cultivation, national and international tendencies and increased demand. In Murcia, the growing cycle runs from December to July or August, depending on the market and the growth of the crop. Sweet pepper is normally grown in greenhouses, using a variety of technologies: from simple shaded greenhouses, to the most-advanced multitunnels (large, in the form of a round arch or Gothic arch and with sophisticated ventilation). Due to the high cost of fuel, it is impossible to use heating during winter after transplanting, so alternative techniques are used to raise the temperature a few degrees and improve crop production. The aim of this work was to increase the precocity and productivity of sweet pepper grown in greenhouses. The effect of a Polypropylene Spunbonded Nonwoven Microtunnel (PSNM) was studied. The results show that, although the increase in production was not great (lower than 5% in both years of the study), precocity increased by 16% in both years. Since the increased cost of using this technology is not excessive, crop profitability increases if precocity is taken into account, as all our indicators show. The study suggests that the use of a PSNM raises the marketable production and brings forward the first harvests.

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Chloride attack is one of the most destructive phenomena that has an adverse effect on concrete and steel materials in reinforced concrete structures. Corrosion of rebars and damage of concrete can significantly reduce the seismic capacity of these structures over time. Accordingly, it is necessary to model the deterioration of reinforced concrete sections before performing nonlinear analysis to evaluate their seismic behavior. In this regard, Instruction for Seismic Rehabilitation of Existing Buildings (code No. 360) recommends that in order to consider the corrosion effects of reinforced concrete sections, the moment-curvature relationships used in the definition of plastic joints are corrected by a fixed number called the knowledge factor. Due to the fact that the deterioration process of concrete structures under chemical attacks is time-dependent and also there are various uncertainties in modeling this phenomenon, it seems that considering the effects of corrosion with only one constant factor, is not enough and in this regard, more research needs to be done. In this regard, in the present paper, the seismic behavior of a reinforced concrete flexural frame with a lifetime of 50 years under chloride attack on the external aspects of the columns was studied. For this purpose, in the first step, chloride diffusion is modeled according to Fick's law and then the measure of damage in rebars and concrete was calculated using MATLAB software. In order to increase the modeling accuracy, a probabilistic framework based on Monte Carlo simulation was used to consider the uncertainties. In the next step, Moment-curvature curves of the sections were extracted using the results of deterioration modeling and were compared with those recommended by code No. 360. After that, the seismic behavior of the flexural frame was studied using static nonlinear analysis (Pushover) based on the moment-curvature results obtained from the present study and the recommendations of Code No. 360. A summary of the results obtained in this study can be expressed as follows: Corrosion due to chemical attacks can change the behavior of reinforced concrete members over time from deformation-control to force-control. For this reason, the type of failure mechanism of these structures changes from ductile to brittle. In correcting the moment-curvature diagrams of reinforced concrete flexural frame columns using the knowledge factor of Code No. 360, it is necessary to pay attention to the actual behavior of the member subject to corrosion. Using the method used in this research, it is possible to predict the actual behavior of concrete sections under the chloride attacks during the lifetime of the structure based on the modeling results of cross-sectional deterioration. For the studied moment frame, it was concluded that in the first half of the structure life, the use of a knowledge factor 0.75 to modify the curvature, is appropriate to correct the behavior of column sections subject to corrosion. But in the second half of the life of the structure, it is better to correct the moment-curvature relationship by applying the knowledge factor to the moment. In this study, the diameter of the rebars, ductility of steel, and the compressive strength of concrete were considered as indicators of damage due to chloride attacks. Based on statistical calculations, it was concluded that the determination of the reduction in diameter of rebars over time has a higher uncertainty than the other two parameters. Therefore, further research is needed to provide a suitable solution to more accurately estimate this parameter.

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In recent years, the use of photoselective shading nets to mitigate the harmful high radiation caused by the increase in temperatures is growing. The objective of this work was to study the positive effects - in terms of yield and profitability of photoselective shade nets in two types of pepper: Lamuyo (cultivars Alcudia and Pompeo) and California (cultivars Bendigo and Cayetano). The weekly yields, classified into different calibre, were analysed over two years, and for the analysis of economic profitability, the Equivalent Annual Value (EAV) was used with an analysis of sensitivity. The yields obtained with the pearl-colored net giving 30% shading were superior to open cultivation (no netting), in all the studied cultivars; in particular, Cayetano and Pompeo had 136 and 86% greater yields, respectively. This same trend was observed for the red-colored net giving 30% shading, with 88 and 74% increase in yield in Cayetano and Pompeo, respectively. In economic terms, the EAV was superior with the use of the pearl net, especially for the cultivars Alcudia and Cayetano - being €14,864 and €13,326 ha^-1 yr^-1, respectively. The yield and profitability were better for the crops grown under the pearl-colored photoselective net, especially for cultivars Alcudia and Cayetano. The sensitivity analysis showed that the probability of obtaining negative returns was higher in the absence of netting, while under the shade nets it was below 10%.

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This study aimed to investigate the residue levels and dissipation rates of chlorpyrifos, diazinon, and their oxon derivatives in greenhouse-grown tomatoes and to evaluate the acute and chronic Hazard Quotients (HQ) for consumption of these products. The quantification analyses of chlorpyrifos and diazinon and their degradation products were performed using Gas Chromatography Coupled with Mass Spectrometry (GC-MS/MS). The Monte Carlo simulation technique was used to evaluate the variability and uncertainty of the data and to achieve more accurate results in the health risk assessment process. The chronic HQ values of chlorpyrifos and diazinon residues ranged from 0.24 to 0.85 and 0.06 to 1.09 for adults, 0.45 to 1.34 and 0.12 to 1.66 for adolescents, and 0.71 to 1.80 and 0.21 to 3.78 for children, respectively. After five days of storage in room and refrigerator temperatures, the HQ values of diazinon and chlorpyrifos were higher than the acceptable limits. According to the Monte Carlo simulation, the HQ and the estimated daily intake (EDI) values were more affected by the consumption rate followed by pesticide concentration and body weight. Therefore, due to the high frequency of tomato consumption, it is necessary to reduce the concentration of pesticides in this product in order to reduce human health risk.