Facilities built in areas affected by earthquake activity, such as tunnels, which have always been an integral part of human life, must withstand both dynamic and static loading. It has led to the need for practical studies on the effects of earthquakes on underground structures and the factors affecting their destruction. For this purpose, in this research, at first different patterns of tunnel’s excavation were investigated and by using Plaxis 2D software and based on Tabas earthquake in Iran, Sensitivity analysis on geotechnical parameters of the soil surrounding tunnel such as cohesion, friction angle, unit weight and modulus of elasticity was carried out, and the parameters whose changes have the greatest and least effects on the bending moment changes on the tunnel lining are introduced. The results show that tunnel excavation patterns significantly affect the bending moment, axial forces, displacements, and surface settlement of the tunnel. Often, by dividing tunnel excavation area to small parts, the values of bending moment, axial forces, displacements, and surface settlement of the tunnel decreases in static analysis. Also, outputs of Sensitivity analysis on geotechnical parameters of the soil surrounding tunnel showed that modulus of elasticity of the soil surrounding tunnel has the most effect and cohesion changes have the least effect on bending moment induced on tunnel lining..

In many practical applications of structural reliability analysis, one of the preferred sciences is the Sensitivity analysis of failure probability based on design parameters under the limit state function. This information is needed, for example, in design optimization based on reliability. The design parameters are calculated by first- and second-order reliability methods FORM\SORM to Sensitivity analysis of the probability of failure approximately. Therefore, in many cases, these methods are very inaccurate or difficult to solve problems. Accordingly, the Monte Carlo Simulation method is very useful for determining the reliability Sensitivity parameters. The derivation probability of failure into the parameters of the limit state function is calculated by integrating the surface of the performance function. By using the Monte Carlo Simulation to determine this integral will not be efficient due to the small portion probability of failure and will have a high computational cost. Hence, some methods can be used to estimate Monte Carlo Simulations that reduce the computational cost. One of these methods is linear sampling method. In this paper, an approximate method is used to determine the surface integral in terms of a domain integral. The integration domain can be calculated using standard Monte Carlo Simulations or importance sampling Simulations. This article presents two practical examples of sandwich panels to determine the effectiveness of parameters random variables are used in the design.

Aquifers are underground porous domains containing groundwater. Confined aquifers are surrounded by the impermeable layers. They are saturated by pressurized water and are suitable for energy storage purposes. They have low thermal conductivity and large storage volume. In design of aquifer thermal energy storage (ATES) an applicable model is necessary to predict the aquifer behavior. In this research, by developing a three dimensional finite volume model via FLUENT software, the effects of operative parameters on pressure distribution are investigated. In the ATES, heat transfer is performed by both convection and conduction phenomena. The convective heat transfer in the ATES is occurred because of pressure gradient and hence, recognition of effects of operative parameters on pressure distribution is essential. These effective parameters are some geological parameters such as groundwater natural flow, porosity and permeability, injection and withdrawal rates from wells, number and arrangement (being linear, triangular or rectangular) of wells.

The dynamical Simulation model of WOFOST is widely used for yield estimation at farm and regional scales as well as different climate conditions. In modelling processes, there are lots of parameters which have to be estimated (calibrated) and also in the other hand there are limitations for providing enough observational data. Therefor it is required to choose sensitive parameters for model calibration. In this study, a global Sensitivity analysis has presented for maize and wheat Simulation in WOFOST model. Global Sensitivity analysis methods are useful tools to rank the model parameters based on their influence on model outputs and considering the entire range of parameters. In other words, these methods consider the influence of a unique parameter as well as the influence of its combinations with the other parameters. In this paper, Regional Sensitivity analysis (RSA) method is applied as a global method and its results are discussed. The variations of Sensitivity index for the two crops are obtained from minimum 0. 006 (insensitive) to 0. 37 (high sensitive). Furthermore, Results for maize crop showed that the parameters which are related to temperature process (TSUMAM, TSUMEA) and absorbed radiation (SLA, AMAX, EFF) are among the most influential parameters in Simulation of maize crop yield. In case of wheat crop, only the parameters which are related to absorbed radiation process (SLA, RGRLAI, AMAX, and EFF) are identified as most influential parameters.

Soil water content is one of the most important parameters for estimating irrigation frequency and providing the plant’s water requirement. Since measurement of soil water content is both expensive and time consuming, water movement models are used to estimate these values. In this study, LEACHW model was used to estimate soil water content for two “dry” (20-29 Aug) and “wet” (1-6 Jul) periods during the 1995 growing season. Different values of hydraulic parameters were applied to investigate the Sensitivity analysis of these parameters in the estimation of soil water content. Thus the values of b (pore distribution coefficient in Campbell’s equation (2) were selected from 2 to 24, and k(q)/ks ratios of 0.1, 1, 10 and 100 were used. Finally 32 treatments were investigated for each period. Results showed that despite large variation for the hydraulic parameters, similar trends of results were obtained for all soil water content estimations. Statistical analysis comparing the estimated and measured results showed a systematic difference which can be adjusted using a few measured values of soil moistures. As an example, simulated results using b=24 and k(q)/ks=0.1 were calibrated to adjust the simulated results. The results of this study showed that a simple calibration method can be used for the estimation of soil moisture content without using extensive data required to represent hydraulic characteristics of soils.

The purpose of this study was to simulate surface runoff of the Ghareh-Chay River that was modeled using SWAT hydrological model. In this regard, GIS software version 10. 4, DEM and waterways and river network characteristics were first extracted. The statistics used for the 2003-2016 Ghareh-Chay Basin Pole Doab Khondab, Joshiravan, and Sarouq stations were considered. Soil curve number (CN) method was used to calculate basin mortality. Model calibration and validation were performed by SWAT-CUP software with SUFI-2 algorithm. To evaluate the model's ability to simulate runoff discharge, Nash-Sutcliffe, R2, p-factor and r-factor indices were used. Eight years of measured data (2004-2011), precipitation, temperature and daily discharge were used to calibrate the model. And model validation with residual data (2012– 2016). The model validation results with Nash-Sutcliffe, R2, p-factor and r-factor indices for the Khondab station were 0. 65, 0. 66, 0. 35, 0. 07%, and for the Pole Doab station, respectively, the results were 0. 57, 0. 72, 0. 07, 0. 05. The model evaluation confirms the SWAT model's ability to simulate surface runoff of the Ghareh-Chay River. Finally, the comparison of simulated hydrographs and monthly observations showed that the model modeled well the peak discharge and base discharge times but estimated the peak discharge values more than the actual values.

The complications of In-Situ Combustion in heavy oil reservoirs cause the investigators to pay more attention to numerical Simulation rather than experimental models. On the other hand, development of numerical Simulation softwares supports them in this way. In this investigation an experimental model is simulated by numerical Simulation software and Sensitivity analysis of crude production in In-Situ Combustion process is evaluated by various parameters. Hence, the value of influence of these parameters is measured by Sensitivity analysis. The operational parameters those are selected are pre-heating temperature, pre-heating by steam, air injection rate, and comparison of air injection to oxygen saturated air injection.

Water supply from groundwater resources because of rapid population growth and coastal zones development, converts the intensity of seawater intrusion to a global concern in these areas. Analyzing the Sensitivity of costal aquifers' behavior to different controlling factors, preventing the seawater intrusion to these resources and the related adverse consequences is an essential effort. This study aimed to analyze the global Sensitivity of factors controlling the seawater intrusion and the interaction of Caspian Sea water and the considered coastal aquifer. To assess the seawater intrusion, SUTRA, a three-dimensional density-dependent calibrated and validated numerical model, was employed. For this purpose, five well-known global Sensitivity analysis methods have been employed and the Sensitivity indices of each methods have been calculated. The permeability of first layer was the most sensitive parameter based on FAST, VBSA, PAWN and RSA methods among five considered methods. The fifth layer’ s permeability was found to be the most sensitive parameter by applying EE. Overall, the higher the permeability of extended layers nearer to coastline, the larger the seawater intrusion. Therefore, the permeability of such layers effectively contributes to seawater intrusion. These findings can be used to support the management-related decisions and prioritize the measurements conducted on the aquifer in the study area. Such decisions are not based on the local findings and consider all possible changes of layers' permeability, therefore cause to more reliability.

A mathematical model for hydrogen recovery from a feed gas using a four-bed, ten step PSA system, is proposed. Methane and Carbon Monoxide is the impurities of the feed gas from which hydrogen is recovered. The numerical solution of the proposed model resulted in pressure, concentration and velocity profiles within the beds. Finally, the effect of some important  parameters such as adsorption pressure, cycle time, etc. are discussed and the optimum operational condition for this separation process is suggested.

Groundwater contaminant transport modeling is a useful tool for identifying how pollutants fate and transport in porous aquifer environments. These models include several parameters, which are often estimated based on personal judgment or in the best case, based on limited field measurements. Therefore, the input data of Simulation models are not accurate and contain several errors. The purpose of this study is parameter uncertainty and Sensitivity analysis in the groundwater solute contaminants transport modeling using probability theory. First, governing equations for groundwater flow and solute contaminant transport have been presented. Then, using MOFLOW for modeling groundwater flow and MT3DMS for modeling solute contaminant transport in a hypothetical problem and using effective parameters in a case study (Qazvin plain), uncertainty analysis through the Monte Carlo method was done. To illustrate the uncertainty analysis, the Complementary Cumulative Distribution Functions (CCDF) of Chloride and Nitrate graphs have been computed. Then using random samples, generated in uncertainty analysis step, local and global Sensitivity analysis of solute transport model parameters have been determined. Result: Using maximum concentration of solute contaminant as a model output, the results of the local Sensitivity analysis show that the most sensitive parameters are hydraulic conductivity (K), decay rate constant (f), porosity (a), distribution coefficient (Kd), and dispersivity (D) respectively. While using time to maximum concentration as output variable, leads to the following order of Sensitivity: K, Kd, a, D, and f. On the other hand, the global Sensitivity analysis using maximum concentration shows that the order of Sensitivity is: K, f, a, D, and Kd, and using time to maximum concentration it is: K, Kd, D, f, and a respectively. According to the CCDF of Chloride, concentrations of 5%, 50% and 95% equal 205. 5, 196 and 185. 4 mg/L respectively. Also, according to the CCDF of Nitrate the concentrations of 5%, 50%, and 95% equal 56, 54. 125 and 51. 5 mg/L respectively. All five parameters are sensitivite in solute transport modeling. The local and global Sensitivity analysis show more or less the same results. In general, the Sensitivity ranking of parameters is K, f, Kd, a, and D.