فصلنامه مدل سازی در مهندسی
پیاپی 62 (پاییز 1399)

Friction stir welding (FSW) is one of the solid state bonding methods. One of the influential factors in the mechanical and metallurgical properties of the final joint is the tool shape, which, with its proper design, can ultimately achieve optimal joint quality. Among the improvements and modifications to improve the mechanical properties of the final joint is the out-centering of the tool pin against the tool shoulder. Off centering the pin will cause the heat generated in the larger area to be distributed and the volume of the deformed material will increase with the eccentric tool pin. In the present study, the development of a thermal model for tool with an out of center pin has been addressed. The modified model is a function of the temperature dependent friction coefficient and the temperature dependent yield stress, in which the effect of key parameters on the amount of heat generated in the FSW process is considered. In order to validate the developed model, three-dimensional simulation using ABAQUS package and two subroutines of USDFLD and DFLUX have been used. The results of the temperature distribution of the developed model have been compared with the experimental and analytical results of previous studies. Based on the results, the present thermal model with high precision is able to predict the maximum temperature and temperature distribution in the FSW process with an out of center tool pin.

Today, with the expansion of communications and the high volume of data, the need for processing them at a low time and high speed has increased. On the other hand, conducting this high volume of computing operations requires systems with high processing and storage capacities, which increase total costs. Therefore, proposing a suitable and affordable infrastructure can be very significant. The purpose of this article is to design and build an infrastructure with low cost and low response time using cloud computing and fog computing. In addition, one of the key issues for creating such systems at a high speed and minimum time is to allocate appropriate system resources to user requests and, as a result, load balances in the system. Among the various meta-heuristic methods, the Tabu search makes it a common practice because of its high expansion in various optimization issues, as well as memory and high-speed features. Therefore, in this paper, a new method based on Tabu Search is proposed that is optimized using approximate nearest neighbor (ANN) and Fruit Fly Optimization (FOA) Algorithms. Finally, to evaluate and validate the proposed method, a case study is simulated on a smart home using the proposed infrastructure and the real dataset. Both methods have been implemented in this infrastructure and their performance has been calculated based on runtime and memory consumption. The results show the capability and efficiency of the proposed method for the various problems.

With the increase of wind penetration in the power systems, analysis of the probabilistic production on the market prices becomes more essential. Researches in this field are often focused on the simulation tools and analytical modeling is rarely used. The aim of this paper is to provide an analytical method for assessing the effects of wind power plants on the Locational Marginal Price (LMP) based on some strong mathematical foundation. In order to achieve this goal, we utilize the LMP decomposition in the transmission-constrained electricity market. In this regard, using Rayleigh distribution for wind speed, nonlinear relationship between the wind power output and the wind speed and mathematical principles of probability, the probability density function of the wind power is determined analytically. Then, the average wind power with a precise mathematical formulation is obtained in a closed form and as a function of the wind turbine parameters and the probabilistic characteristic of wind speed. Finally, for the average LMP of each bus, an exact analytical relationship is determined. The proposed method is tested on the IEEE 24 bus system. The results show the efficiency of the proposed model.

A comprehensive model is developed for a MOS capacitor implemented using an n-channel depletion-mode MOSFET fabricated in a submicron CMOS technology, which accounts for the voltage dependence of the MOS capacitance over the entire range of operating voltages. Notably, the model, whose active component is derived based on the industry-standard BSIM3 MOSFET model, fits the measured capacitance-voltage data with a goodness of fit characterized by coefficient of correlation of 0.99. By considering the gate capacitance and the associated series resistance as a distributed RC network, a realistic compact subcircuit representation is obtained for the MOS capacitor, which allows modeling of the limitations imposed by the series resistance on high-frequency performance as well as the quality factor. The model is also validated based on SPICE simulations with the channel resistance associated with the inversion layer modeled as a voltage-controlled resistor in order to account for the nonlinearity of the parasitic series resistance associated with the MOS capacitor.

Charging demand of electric vehicles in fast charging stations can have a significant impact on the process of distribution network reconfiguration and islanding. In this paper, the problem of dynamic islanding and reconfiguration of distribution network taking into account the interaction between the electrical and traffic networks is presented in the form of a two-stage model. In the first step, considering the tendency of electric vehicle to charge at nearby fast charging stations, a linear model has been proposed to determine the charging demand of the stations in the traffic network. In the second step, a scenario-based mixed integer linear model is proposed with the aim of maximizing the resiliency index of the distribution network equipped with dispersed production resources using dynamic islanding and reconfiguration plans. The resiliency index consists of two objectives, including maximizing network load recovery and maximizing the power supply of fast charging stations. In order to provide a realistic model, the uncertainty in predicting the productive capacity of renewable wind resources has been considered. The proposed model has been implemented on the 118 bus network by applying several simultaneous faults and the presence of electric vehicles in the 25-node traffic network in the GAMS software. The simulation results illustrate the effectiveness of the proposed model in evaluating the resiliency of the active distribution network in the presence of electric vehicles.

Design and atomic modeling of multimode sliding electromechanical switch based on bilayer armchair α-graphyne nanoribbons is presented by applying density functional theory combined with non-equilibrium Green's function. In the proposed switch structure, bottom graphyne layer is fixed and the top layer is movable. Different configurations of the layers are created by moving the top layer over the bottom layer along the horizontal axis with the displacement distances of 1.36 Å, 2.61 Å, 3.97 Å, 8.41 Å, 9.44 Å and 12.6 Å. There are six stacking modes for the proposed device, namely, Ab, Aa, AB, AB2, Aa2 and AA, respectively. These configurations cause current of the proposed switch changes significantly in each stacking mode. To better analysis, electronic transport properties of the proposed device including transmission spectrum, band structure, molecular energy spectrum, molecular projected self-consistent hamiltonian and transmission pathway are calculated. The results demonstrate that current switching ratio of the proposed device depends on the type of layers atomic configuration and varies significantly from one mode to another. Maximum switching ratio of the proposed device can reach to 34 under the bias voltage of 0.6 V when the mode of device changes from AA to Aa2. This suggests that the controlled movement of layers in bilayer graphyne nanoribbon device could be a useful method to design multimode sliding electromechanical switch in nanoelectronics field. Furthermore, the results exhibit that the proposed device in AB2, Aa and AA modes reveals negative differential resistance which provides ability of its usage in quantum tunneling device.

The environmental laws cause industries to find solutions for reducing greenhouse gas emissions. In this paper, the study and simulation of a domestic gas compression station by the Aspen-Hysys software has been considered. At this station, the gas turbines are applied to make mechanical energy from a combustible fuel to drive the compressors. Furthermore, the glycol dehydration process is used to absorb water from the natural gas stream. In order to reduce the glycol heater fuel consumption, the heat recovery of the turbine stacks, and restoring the exit glycol vapors, a new design is proposed and simulated. In this design, the heat of the flue gas leaving the turbine is transferred to the rich glycol stream exiting the absorption column. This will lead to a reduction in the daily consumption of sweet gas by 2.5 million cubic feet. The comparison of the simulation results with plant data shows that the proposed process could achieve the temperature requirements of glycol regeneration (198 °C). By restoring the glycol vapors from the regeneration tower to the consumption cycle, it is possible to decrease the Glycol consumption by 188.8 kgmole/h. Finally, by transferring the flue gas from the turbine (after heat exchanging with rich glycol stream) to the safe area outside the gas compression station, it helps to prevent the release of hazardous pollutants and increase the occupational exposure indices. In addition, the cost evaluation shows that the proposed process is capable of saving 24017 million rials per day by consuming 21340 million rials.

Nowadays, the determination of in place concrete strength is more considered. The necessity of in situ testing can be expressed in a variety of applications such as structural change or development, quality control, strength evaluation and concrete performance. In this study the performance of Artificial neural network, Adaptive neuro-fuzzy and Multivariate regression function for measuring the concrete compressive strength with point load method are studied. Also, a computational relation is presented based on multivariate regression method for prediction of concrete compressive strength with point load method. The results indicated that the neural network, neuro-fuzzy and regression models are suitable in prediction of concrete strength with point load method. The correlation coefficients of neural network, neuro-fuzzy and nonlinear regression models were obtained 0.9412, 0.8244 and 0.8938 respectively. This indicates less error and as a result better accuracy and performance of neural network in prediction of concrete strength with point load method. The results of this study showed that there is good agreement between concrete compressive strength test with soft computing methods and real observations. The proposed method of this study, in addition to ease, reduces the time of evaluation of in situ concrete strength and reduces the cost of laboratory studies.

In recently, several studies have been conducted to use meshless methods according to their advantages to investigate fracture mechanical problems. The utilization of meshless methods in fracture mechanics because of using continuous shape functions requires modification of the shape function near the discontinuity surface. In this paper, the discrete least squares Meshless method (DLSM) is used as truly meshless methods for solving the crack problems, by using discontinuities definition techniques. In the discrete least squares method, the problem domain discretization is performed by unrelated node points, for approximate the functions, used moving least squares shape function with high order of continuity. It also used the strong form of equations for discretizated the equations. The DLSM method is based on minimizing the squares of the residuals at a number of neighboring points of the main node. The boundary conditions are easily enforced by the penalty method. The visibility criterion, diffraction and transparency method are used to define the discontinuity. The performance of all three techniques is the same on the crack surfaces except near the crack tip. The efficiency and accuracy of applying each technique in the DLSM method are investigated by comparing the results of example modeling. Comparison of the results and the error rate of each technique indicate the high capability and accuracy of the proposed method for applying different techniques in cracked plate modeling. It has been shown that the diffraction method performs relatively better in dealing of discontinuous boundaries compared to the transparency and visibility criterion techniques.

The Residual Useful Life (RUL) provides an estimate of the amount of remaining useful life before a system failure depends on present conditions and past operating profiles. In this paper, RUL is estimated based on reliability and for convergence to more realistic results, the effect of operating environment conditions in the form of risk factors (covariates) is also involved in the analysis. These environmental conditions are sometimes tangible and "Observable" and sometimes it is not possible to determine and include them in the analysis and are analyzed under the heading of “Un-observed risk factors” using the frailty model. RUL analysis of a case study of the loading system (Shovel Komatsu 1250) of the Sungun copper mine, based on 8-months information, has shown that Weibull mix proportional hazard (W-MPHM) has the best fit on the data. In this model, four factors including shift risk, rock kind, load system type and rainfall with risk rates of 2.66, 3.79, 0.204 and 1.18 have been obtained as the most effective factors. System RUL became zero in the next two scenarios in about 40 hours. Comparing W-MPHM and Ex-PHM over 80 hours showed that the concurrence of the reliability curve in the second model is greater than the first model and in fact, the reliability decline rate is higher at the beginning of the range. This result reflects the impact of intangible risk factors on system performance analysis, regardless of which will result in significant inconsistency of the results.

A structure encounters some defects during its lifetime that their role in structure’s strength must be surveyed . These structural defects as structural corrosion, corrosion and crack are created and expanded by various factors . Predicting residual strength of plate with damages such as cracking and corrosion is important for service life estimation of aged structures . A series of nonlinear finite element method (FEM) is employed for ultimate strength analysis of steel stiffened plates with pitting corrosion and crack . Influential parameters are including crack length, crack angle , pitting corrosion density and number of pits . It is found that ultimate strength is reduced by increasing crack length and crack angle relative to the loaded edge . Reduction of ultimate strength in intermediate plate depends on number of pitting and DOP . Reduction of ultimate strength plate in the effect of these defects dose not obey superposition principle.

This paper presents a robust-H∞ control design for semi-active vehicle suspension system using linear matrix inequality (LMI). In vehicle control systems, the ability of damping vibrations is very important against the external and internal disturbances. Generally, it is impossible to eliminate all of this disturbances. So, it is essential to use the robust control. In this study, the state feedback H∞ control for a semi-active quarter car suspension using an Electro-Rheological damper with spring and damper has been utilized. The dynamic system of the suspension systems is first formed in terms of the control objectives, i.e., ride comfort, road holding, suspension deflection, and maximum actuator control force. Furthermore, using Lyapanov theory and linear matrix inequality (LMI) approach, the existence of admissible controllers is formulated in terms of LMIs. Finally, a quarter-car vehicle model is exploited to demonstrate the effectiveness of the proposed method. A comparison of the results between the semi-active and passive suspension systems shows that the attenuation of the disturbance against the bump and stochastic input is obtained.