فصلنامه مدل سازی در مهندسی
پیاپی 59 (زمستان 1398)

In our previous work [1], pristine and functionalized carbon nanotubes with 1, 2 and 4 hours refluxing times and concentrations of 0.1, 0.25 and 0.5 Vol% were used to prepare nanofluids and their thermal conductivity was measured at 20, 30, 40 and 50 °C. Lots of empirical works cannot be done because they are time consuming and costly. One of the best methods for investigation of low cost and wide range of empirical works is using the modeling methods. The artificial neural network model is a method which replicates the initial sensory processes of the brain. It is possible to design a virtual laboratory using artificial neural networks to predict the results for the same conditions even not measured experimentally. In this work, a multilayer perceptron (MLP) neural network was used to design a virtual lab and modeling the experimental data including the thermal conductivity of ethylene glycol nanofluids containing CNTs. In order to achieve a minimum error, neural networks with different hidden layers (1, 2 and 3 layers) and different number of neurons in each layer (2, 3, 4, 5, 6, 10 and 15 neurons) were studied. The minimum error of 6.5% was obtained for the neural network with two hidden layers by 3 neurons in the first layer and 2 neurons in the second one. This network was used to predict the results in the conditions which were closed to experimental conditions and it was observed that the predicted results were in good agreement with the experimental results.

The study of earth dams behavior during the construction, completion and also the first impoundment as one of the most critical times during the life time of the dam because of the stress and water pure pressure in the core and also water level in this period has special importance. For this purpose, the behavior of the Chahchahe dam was studied by using of obtained results from monitoring recorded data and back analysis was done by GeoStudio finite element software. This dam is an earth dam with core clay and its maximum height is 47 meters from the natural bed of river. Chahchahe dam which has been constructed on Chahchahe river is located in the Kalat basin watershed, in 95 kilometers northeast of Mashhad. In order to consider the parameters in design process and simulate as real conditions of dam construction, back analysis was done base on the results of monitoring to can be predict the behavior of dam. In this study, the comparison of numerical model and monitoring results show acceptable and suitable accordance, so that the amount of settlement in the clay core was obtained 65 cm from monitoring result and evaluated 66 cm by numerical model. Also, the maximum stress at the 530 meter level in the core was read 820 kPa, which was calculated 950 kPa based on the numerical model at the same level, and in all of cases, the obtained values from numerical models are as confidence.

In this study, the optimization of heat transfer in serpentine micro heat exchangers using the genetic algorithm based multi-objective optimization was investigated. The effects of geometric parameters of the serpentine microchannels including curvature radius and straight length between the bends on friction factor (f) and Nusselt number (Nu) were investigated experimentally. As was expected, increasing the heat transfer rate and pressure drop occurs simultaneously, which leads to the more energy required for pumping. Hence, both phenomena should be considered at the same time. The constants of two empirical equations for estimating Nusselt number and friction factor were obtained by the genetic algorithm searching method. The mean relative error of 7.49% and 9.76% were calculated for Nu and f correlation, respectively. These empirical equations were employed in two objective functions for genetic algorithm based multi-objective optimization. The optimum geometrical parameters of the investigated serpentine microchannels which lead to a trade-off between heat transfer and pressure drop were presented.

Rotating Packed Beds (RPBs) are used in many processes of chemical engineering, such as distillation, absorption, production of nanoparticles, natural gas sweetening, and etc. The fluid flow analysis in this equipment is necessary to obtain the hydrodynamic information and investigation of transport phenomena. In this paper, 3D simulation of single phase and two phase flows are carried out using Computational Fluid Dynamics (CFD). The effect of some parameters such as rotational speed, gas and liquid flow rates, number of rotor holes, fixed and moving baffle are investigated on the pressure drop. The single phase flow analysis showed that the tangential velocity has the most effect on the velocity magnitude comparison with the radial and axial velocities. The simulation results showed that dry and wet pressure drop increase with increasing gas flow rate as the average errors between experimental data and simulation results with and without baffle are 5.3% and 3.6%, respectively. It was also known that increasing liquid flow rate has negligible effect on the pressure drop. It was seen that wet pressure drop increases with increasing both rotational speed and rotor holes. The moving baffle insertion into the bed was caused that wet pressure drop decreases 14%.

In many decision-making issues, fuzzy sets are used to deal with ambiguities in linguistic data, However, this data is be defuzzified to make comparisons between the attributes and determine alternatives rating, during the problem solving process, defuzzification will cause a large part of the problem information to be eliminated. The aim of this paper is to propose a multi- period multi- attribute decision-making method in which the rating of alternatives is determined in a fuzzy form, in this method, to cover more ambiguity in the words, Fuzzy Type-2 sets have used and for integrating type-2 fuzzy data in time periods, a new integrator operator is defined. To confirm the efficiency of the proposed method, first, an applied example presented by previous studies was analyzed using the proposed method, the results showed that the ranking of alternatives in the proposed method is more comprehensive than the mentioned method, Then, the evaluation of the dimensions of service quality of Shahrekurd's public transportation scenarios was presented as a real example application and The fuzzy rating of the alternatives was determined.

Recently, concerns have been raised about the environmental and social impacts of commercial activities. Also, most papers on the design of the supply chain network, focus on economic performance. Recently, some studies have considered environmental and social dimensions. There are still some gaps in modelling social impacts along with environmental and economic impacts. In this study, a multi-objective probabilistic model for designing a sustainable closed-loop logistics network is presented under uncertainty. The goals of this model consist of cost reduction, increasing social impact and decreasing environmental impacts. Then the model was solved not only using well-known Metaheuristic algorithms including genetic algorithm and Simulated Annealing (SA) algorithm, but also new whale optimization algorithm along with its improved combination method was used. Performance of algorithms was compared through examining different experiments and designed test problems. They compared in different situations and some important criteria. The results show the superiority of the whale optimization algorithm.

Considering the importance of controlling the behavior of structures against lateral loads such as earthquakes, the use of dampers in structures is needed to control and improve the structural responses. In this study, the effect of rotational, viscous, and TADAS frictional damper on the behavior and responses of the 8-story steel frame structure with residential use in Mashhad was investigated. These structures were compared in two cases equipped with a damper and without a damper. Seismic earthquake history was used to apply earthquake force. The history of the earthquakes used was obtained by squared squares method and was matched with the soil type 3 soil. Then each of the structures was studied under the analysis of nonlinear time history in SAP2000 software. In this study, the maximum story displacement, the basic shear and the hysteresis curve of each floor were evaluated to determine the effect of dampers on the behavior of the structures. The results of the investigations show that in the study of the structure equipped with the damper, the specifications of the dampers should be based on the behavior of each floor and the adjustment of the damper according to the overall behavior of the structure is inappropriate.

The deposition of pharmaceutical aerosols and pathogenic particles are considered when predicting certain pulmonary disorders or determining the dose of respiratory drugs in order to control and manage the diseases. The breathing and flow pattern, particle size and density, airways geometry and the gravitational force exerted on the particles are among the factors contributing to the deposition in the respiratory tract. In this study, modification of the flow pattern in the respiratory tract was investigated by applying different boundary conditions on the outlet and the effects of various flow patterns on the deposition of the iron particles was studied. Keeping some of these patterns, the impact of exerting gravitational forces with different directions and values (from the microgravity to normal condition on the earth) on the particles was examined. The inflow with velocities of 2 and 4m/s was used in order to change the nature of the flow from laminar to turbulent. Two particle sizes of 4 and 8 microns for iron particles were assumed. As a result, deposition of particles increased with an increase in the gravitational force and the effect of changing the direction of the gravity from the X direction (aligned with the flow direction) to the Y direction (perpendicular to the flow) was shown to be a significant factor in a further increase of particle deposition. The modified flow pattern which was free of any reverse and secondary flow, has reduced the deposition values and resulted in an opposite effect increasing the size of iron particles.

More equipment which is used in the mechanical industry has rotating shafts. In the design of the rotating shaft, vibration prediction of the system is very important to reduce and prevent vibrations of the system. One of the important elements that have a more efficacy on the results of the vibration simulation of the rotating shaft is modeling of the bearings. The journal bearings are of great importance in the industries. In this study, firstly, the pressure equation of the lubricant film is derived in any position (angle) using Reynolds hydrodynamic theory for one-dimensional flow. Then using the definition of stiffness and its relationship with the force and pressure, the equivalent stiffness of the journal bearing lubricant film is calculated based on the angle by an analytical approach. Finally, with the solution of governing equations, equivalent stiffness is calculated for a sample journal bearing. Also, the calculated stiffness is validated and error factors of the results are studied. The obtained analytical equations can be helped the designer of the journal bearings to understand the stiffness behavior of the journal bearing versus the angular position and also system parameters of the bearing. The obtained results show that the journal bearing stiffness is directly related with the lubricant viscosity, the angular velocity, the length, and the second power of the journal radius. Also, the journal bearing stiffness is inversely related with the third power of the radial clearance of journal bearing.

In this paper, the geometry of a frog- shape MEMS microphone is optimized using a particle swarm optimization technique to reduce bias voltage and to increase sensitivity. The PSO algorithm is a population based stochastic optimization technique that inspired by social behavior of bird flocking, which is used to solve complicated design spaces and multi physical problems. The proposed method in this paper can be adapted to a variety of MEMS device designs. This approach shows improvements over previous designs that were generated from the conventional design approach (approximate methods based on trial and error). Considering that the performance of the microphone is studied in different directions, and various design parameters are in a trade off with each other, the definition of a multi-purpose target function is very important. In this work, we define the target function such that all three factors of resonance frequency, mechanical sensitivity and pull-in voltage should be considered, simultaneously. The results show that the designed microphone has a good performance. Actually, only by choosing optimal dimensions for length and width of frog-shape diaphragm arms, the mechanical sensitivity and open circuit sensitivity of the microphone increased approximately 4 and 2 times respectively, and the pull-in voltage decreased to half approximately.

In this research, 12 approaches were proposed to create an optimal vector based on supporting vector machine and neural networks based on genetic algorithm, cuckoo and particle swarm Optimization (PSO). In this regard, we have tried to design a system that reduces the cost of data collection. For this purpose, three data sets with time series capability of standard UCI data were used in this study. The results of the approaches used in this research show the good performance of all the used algorithms. However, the ability and performance of each approach vary according to the type and nature of the data. This has sometimes led to better results from the MLP neural network and the GA or Cuckoo algorithm, and in some cases, the PSO algorithm has better outcomes. Regarding the results, it can be said that the use of feature selection based on semi-regulatory classification reduces system error, increases the accuracy and increases the speed of time series estimation. Hence, by using the efficient and powerful MLP Neural Network and backup vector machine along with the optimization algorithm and metamorphic, an optimal combination classification system can be designed for time series estimation.

During lightning discharge, the transient performance of grounding system is influenced by the time-dependent nonlinear behavior related to soil ionization and frequency dependence of soil electrical parameters related to high-frequency spectrum of lightning current. In this paper, for the modeling of grounding system, a new approach based on the combination of the method of moment (MoM) and the harmonic balance method (HBM) has been used. In order to increase the accuracy, the phenomenon of soil ionization in the time domain and the effects of frequency dependence of soil electrical parameters in the frequency domain are considered simultaneously in the modeling. In the presented method, first by analyzing the ground system through solving integral equations with the method of moment (MoM), a Norton’s equivalent circuit is extracted in frequency domain assuming frequency dependent of soil electrical parameters. At this stage, the equivalent circuit is extracted in the absence of soil ionization. Then, by adding the nonlinear load arising from soil ionization to the Norton’s equivalent circuit, the grounding system is changed into a nonlinear Norton’s equivalent circuit. To analyze the obtained nonlinear circuit, the harmonic balance method (HBM) is used. The proposed model is validated by comparing our data with published experimental results. The obtained results confirm efficiency and accuracy of the proposed method.

In this paper, a detailed modeling of energy consumption in the processes of producing aluminum and cement industrial units based on the linear piece-wise approximation (LPWA) method is presented. The presented model has been implemented in the day-ahead energy management planning of a microgrid including these industrial units. In order to increase the profit of the mentioned industrial units, the demand response programs are implemented and therefore these units are able to participate in the energy and ancillary services market. The energy management planning proposed in this paper, considers the exact model and all constraints of the industrial units and microgrid in order to maximize the profit of the microgrid and these units. The performance of the model and the proposed planning has been evaluated through two case studies, with and without implementation of demand response programs. In addition, the effect of the changes in the profit obtained by selling the product of each industrial unit and the prices of sold energy by microgrid to the electricity market, on the profit of the units and the microgrid, have been examined using the sensitivity analysis. The obtained results, besides validating the proposed model, show that the implementation of demand response programs and the participation of industrial units in the energy and ancillary services market, not only modifying the demand curve but also increase the profit of the microgrid and units.

Today's online communities play an important role in the flow of information such as news, educational contents, entertainment, and so on. Millions of users create different posts in this environment on a daily basis. Users will re-post some posts if they wish. Reposting has a significant effect on the transfer of information between users. Due to the large number of posts, users in these communities face the information overload problem. In this paper, the repost behavior of users in online communities is modeled. Firstly, effective factors have been identified in the behavior of user reposting, and then, using a reinforcement learning approach, users' repost behavior is anticipated. This reinforcement learning method is designed as a game for a team of random learning automata as a common pay-off game. To evaluate the proposed method, three large data sets have been gathered. Various scenarios have been used to evaluate the proposed method. Based on the results, randomized learning automata have great performance due to the features of the environment and online learning power.

Underlap between gate and drain/source area is one of the important items non-ideal effects in the device manufacturing process in the nanometer scale. In this paper, for the first time, the effect of underlap between the gate and drain/source area for tunneling carbon nanotube field effects transistor is investigated. To simulate the device, self- consistent solution of Schrodinger and Poisson equations and Non-equilibrium Green’s Function method have been employed. The function of the device is evaluated in terms of the on-state current, off-state current, current ratio, sub-threshold swing, delay time, and the power delay product. The simulation results show that the underlap effect improves some of the device characteristics and has some adverse effects on other characteristics. In the case where the length of underlap area is optimally chosen, the device performance will be improved considerably. Simulation results indicate that underlap significantly reduces the off-state current and thus reduces band-to-band tunneling and ambipolar behavior of the device. Also, the underlap effect by improving the power delay product parameter is a suitable option for low power applications compared with the conventional structure.

In the mining industry, different departments undertake the control task of a system. The failure data from different sections in a variety of formats are collected in different times and operation conditions and these heterogeneity problems will result in the collected data and the data bank. While the studies that are done so far, two items of time and environmental effects have been examined and in fact, the data are assumed homogeneously. However, a part of heterogeneity by the help of observed covariate is omitted, but the problem starts where entering all environmental conditions is not possible. Since some factors such as the effect of management decisions, different brands, operator skills cannot be recorded or they cannot be quantifiable; and in spite of being observable, some are not recorded or not classified. These categories of environmental factors that lead to heterogeneity in the data are categorized as the unobserved covariate. For this purpose, in this paper, a coherent approach was proposed for system performance analysis based on the reliability index with the impact of environmental conditions. Environmental conditions are considered in two observed categories, which include factors such as road conditions, weather conditions, rock types, and unobserved ones that include heterogeneity. The proposed approach was evaluated with data from the mining fleet of Jajarm Bauxite mine consisting of 5 trucks. The significant difference between the results of the inclusion of heterogeneity with its lack of consideration indicates the importance of the impact of unobserved covariates on determining the system's behavior.

The increasing demand for tunnels as a critical component of the transportation system has caused to establish large face tunnels. In excavation method optimization, it is important to define the number and size of sections. In the presented paper, the distinct element method used to simulate and determine the sequential pattern in the excavation of large face tunnels. The objective function was to minimize the shear strains and extensive displacements of surface and tunnel arch. Therefore 83 different models simulated and implemented to analyze the results. The main variable in presented models is the heading section height in the top heading and benching excavation method. The case study is a binary tunnel with a diagonal pattern. The lower tunnel is with a circular cross-section with 13.7m in diameter. The upper tunnel has a D cross section of 13.2m width and 13.7m height. The tunnels distance is 33m. By verification and implementation of models, the results show that by increasing the heading section height, the displacement has a growing trend. The main point of the result return to the optimum height of the heading section, which is 0.45% and 0.55% of the diameter of circular and height of D shape tunnels, respectively. In these percentage, the growing trend of displacement has a reverse manner.

Reduction of fossil fuel reservoirs along with the environmental crisis associated with the fossil fuel combustion cause find the renewable and green resource of energies. Ethanol is an alternative fuel that is used as fuel in combination with other fuels and improves combustion efficiency and exhaust gasses properties. In this paper, combustion in automotive engines using different blends of gasoline-ethanol are studied to investigate the emissions of pollutants such as carbon monoxide, carbon dioxide, nitrogen oxides, and sulfur oxides. The simulation results showed that the blend of ethanol - gasoline significantly reduces exhaust emissions contain carbon dioxide, and sulfur oxides. The highest percentage of reduction in emission of greenhouse gasses is observed for 10% (V/V) of ethanol; however, by increasing engine speed, emission of carbon dioxide increases due to increased fuel consumption, while, unburned hydrocarbons and carbon monoxide emissions initially increases with increasing engine speed, and decreases by increasing the engine speed and temperature. Therefore, a mixture of gasoline-ethanol can be used as a substitute for fossil fuels.

Privatization has led to the formation dynamic competition in markets, such as airline service providers with a limited number of suppliers and a large number of customers (oligopoly markets). Suppliers of goods and services in these markets are considering the behavior of competitors to determine the amount of products and advertisements in order to maximize their benefits. This paper investigates a differential oligopoly game model under feedback structures. By applying mathematical validation of the optimal levels of production (supply) and advertising cost, the proposed model shows that parameters such as sticky price, substitutability among goods and advertising promotional efficiency on supply and advertising are effective in achieving sustainable equilibrium in such markets. The results of simulations show that in the feedback structures with increasing sticky prices, the optimal supply and promotions are upward. But with the increase in the degree of replacement of a product or service in the market, the optimal amount of supply and advertising is decreasing, as well as the reduction of advertising efficiency, the financial burden of advertising activities that in order to create a level of equilibrium in the market, the amount of optimal supply and advertising has a decreasing trend.

Acne is a common skin lesion which controls the quality of life. Skin analysis is one of the important steps before starting treatment. previously, this detection has been done manually, which cause different results by the various dermatologist. Today, the detection of skin lesions is done automatically, which leads to a more accurate diagnosis. In this paper, the locating and counting of skin lesions is done using Fuzzy Logic algorithm. Although many studies are done to detect the skin lesions, but the results of each method usually take a lot of time. Therefore, one of the advantage of proposed method is in processing time and then data cluster, which the ISODATA method is used. The images used in this study take from the Visio Face Machine, which has no effect to the skin’s texture, and are used in the training phase of system. Given that these images are in RGB color space; colors can be displayed in HSI color space in more details. For lesion detection and feature extraction, Fuzzy Logic algorithm and HSI color space are used. But the purpose of this paper is to build a robot, which burn lesions by Plexr Plus machine automatically. In test phase, using RGB color space and depth sensor of Kinect camera, three dimensional location of lesions are identified. Finally, the average of accuracy, precision and sensitivity were 99.4, 88,2 and 51 respectively.