فصلنامه مدل سازی در مهندسی
پیاپی 71 (زمستان 1401)

Prediction of flow discharge coefficient, Cd, for a sluice gate under free and submerged flow conditions is one of the essential issues in hydraulics. In recent years, various semi-empirical equations have been developed in order to predict Cd for a sluice gate that application of those formulas under submerged flow conditions suffered from large errors. The aim of the present research is to use Gaussian Process Regression (GPR) and Support Vector Machine (SVM) used in soft computing techniques, so that estimating Cd in submerged flow conditions and comparing the results with quasi-experimental methods are of interest, herein. For this purpose, an experimental dataset comprised of 122 data points were used to feed the methods utilized. Different combinations of dimensionless parameters were then prepared and the performance of the afore mentioned methods were assessed. The results showed that SVM with input parameters of 𝑦𝑡⁄𝑤, 𝑦0⁄𝑤, 1/𝐹𝑟2 and S by the values of Root Mean Square Error (RMSE=0.017), correlation coefficient (R=0.97) and Nash-Sutcliffe Equivalent (NSE=0.95) had a better performance than GPR and other semi-empirical approaches, indeed.

In this study, the heat transfer of nanofluids as single-phase, incompressible, laminar, permanent in a two-dimensional sinusoidal channel under the influence of a magnetic field with a porous medium is investigated. Alternating heat flux is applied to the channel walls. The governing equations are discretized using Fluent software with finite volume method (FVM) and velocity and pressure coupling is performed using SIMPLE algorithm. The Reynolds number range is 500 ≤ Re ≤ 200. Water is considered as the base fluid and magnesium oxide nanoparticles have been added to it. The volume percentage of nanofluid is 0.04. Nanofluid flow in 4 different Darcys (0.00001, 0.0001, 0.001, and 0.01) and magnetic field application in 4 Hartmann numbers (0, 4, 7 and 10) have been investigated. The results show that in all cases, with increasing Hartmann number, the heat transferred improves and the pressure drop increases. By increasing the Darcy number from 0.00001 to 0.01 under the same conditions (Reynolds 500 and Hartmann 10), the Nusselt number equals 4.392. Also, with increasing the Darcy number, the viscous resistance decreased and the pressure drop was always lower, so that the numerical pressure drop ratio was less than 1.

Due to the role of the frame, in addition to strength and fatigue analysis, the deformation of the frame is also very important. But unlike strength and fatigue analyzes, there is no specific criterion for analyzing the deformation of the main frame. Therefore, in this paper, in addition to providing a method for deriving specific criteria for evaluating the permissible deformation of the frame and the drivetrain, with the help of simultaneous simulation of the frame and the drivetrain, a solution for determining the displacements and evaluating them under loads is presented. The performance of the main frame has also been examined in terms of strength. Due to the numerical nature of the proposed way, before obtaining the results, the quality of the elements is studied from various aspects to ensure the accuracy of the results. Finally, studies have shown that the presented geometry has the necessary strength, and also has sufficient rigidity against the applied loads on the wind turbine So the drivetrain installed on it without any problems can perform its function. Finally, the main frame strength safety factor is 1.3, the deformation safety factor of yaw bearing is 1.7, and the deformation safety factor of high-speed coupling is 1.1 in both axial and radial directions. Also, the deformation analysis of the drivetrain and frame assembly shows a 15% reduction in the life of the first bearing and a 50% reduction in the life of the second bearing installed on the main shaft of the wind turbine

In this work, the structural and electronic properties of Janus two-dimensional MoSi2PmAsn and MoSi2AsmSbn have been studied using density functional theory. Their stability is confirmed using phonon dispersion. The band structure of these materials shows that except MoSi2As3Sb, the rest of the materials are semiconductors. In the following, the projected density of states is studied and the contribution of orbitals to the conduction and valence band has been explored, where both the valence and conduction bands edges are dominated by the d-orbital of Mo atoms. The electrostatic potential distribution, the charge analysis, and surface work function difference confirm that there is an internal vertical electric field in these structures. In order to adjust the electrical properties of these structures, in-plane biaxial strain is applied. The bandgaps exhibit a maximum at a small compressive or tensile strain. Then the bandgaps decrease at large compressive and tensile strains and semiconductor to metal transition occurs at specific strains. Finally, the interlayer transport in these materials is investigated and the interlayer current is obtained. The results show that the interlayer transport and vertical current depend on the configuration of the group V atoms and the X3Y structure exhibits the largest current. The results and the asymmetry caused by the internal field in positive and negative current values, prove that these materials are promising candidates for application in nanoelectronic devices, especially rectifiers.

This paper discusses the stability analysis of fractional-order polynomial systems by using the sum of squares method. furthermore the feasibility of designing the problems demonstrates which can not be represented in LMIs. unlike the T-S fuzzy model which can only work with fixed matrices, this method deal with polynomial matrices. Therefore, displaying a nonlinear system model using polynomials is a more efficient way. The stabilization of fractional order systems based on the fuzzy T-S model is expressed according to Lyapunov theory of stability by linear matrix inequality (LMI) while stability analysis polynomial fuzzy is based on the sum of the square. The main advantage of the method is the stabilization of fractional order systems based on the fuzzy T-S model. the stabilization conditions are expressed according to Lyapunov theory of stability by linear matrix inequality (LMI) while stability analysis is based on the polynomial fuzzy model. the systems where LMI optimization methods do not work, stability analysis and controller design can be performed by SOSTOOLS. In this paper, the stability conditions of a fractional-order polynomial fuzzy system are investigated then obtained necessary and sufficient conditions for stability. Finally, shown an example of the accuracy and The correctness of the proposed method.

X-rays have wide applications in medicine, industry, scientific research, security issues, etc. The use of X and gamma rays to inspect cargo, cars, as well as persons has about 50 years old and today they are widely used around the world to prevent the carrying of weapons and drugs. In general, nowadays transmission systems have been more developed than back-scattering imaging. On the other hand, x-ray backscatter imaging system have special and unique applications due to their inherent advantages. Also, because the entire imaging system is on one side of the object, mobile imaging is more possible for this type of modality. In this research, an x-ray backscatter imaging system was modeled using the Monte Carlo method by means of MCNPX code. First, a 160 kV X-ray tube was modeled then the tube output was examined with the spectrum of the commercial tube. In the next step, the geometry of the device, the detection system and the scanned object were designed and modeled. The results showed that it is possible to detect bubbles with a diameter of 5, 10 and 20 mm for an object at a distance of 5 cm.

Vehicle traffic congestion control has an essential role in time management and with a case study on clustering-based VANET networks, an algorithm for dependable routing using the re-clustering for vehicular networks with v2v communication has been proposed.The aggregation of vehicles has a direct role in controlling traffic congestion, By observation the index parameters, we obtain the objective function, that merging parameter such as weight and distance, it optimizes the route length compared to previous methods, And by re-clustering, we decreased the number of vehicle collisions using the neighborhood principle. In this case, by considering the Euclidean distance, we can prevent the aggregation of vehicles using the minimum distance to create an optimal route. With the help of the objective function, we will achieve a dependable route to optimize packet delivery and the delay END-TO-END.Ultimately, using the proposed an algorithm, By categorization the inputs and real execution time, we increase the dependable routing compared to the SCRS algorithm, and we also decreased fuel consumption.

In this paper, the effect of installing a hybrid superconducting fault current limiter on the apparent impedance seen by the distance relay in power systems compensated with STATCOM has been analyzed. The STATCOM is installed in the system to meet the increase in electricity demand and increase the capacity of the transmission line. Installing STATCOM in the system increases the level of short circuit current, which is recommended to use HSFCL to control this current. Installing STATCOM and HSFCL changes the amount of impedance calculated by the distance relay. The STATCOM location can be before or after the fault location. Its location and distance from the relay have effect on the performance of the protection systems. The HSFCL location, can be before or after the voltage transformer has effect on the performance of the protection systems also. The fault type, fault location and fault resistance are other parameters that have been investigated in simulation studies. The HSFCL has two structures, RHSFCL and LHSFCL, both of which have been studied in this paper. The two modes have been compared also. The system is modeled and simulated with different equipment in PSCAD / EMTDC software and the results are discussed.

In this paper, the effect of germanium content in Zn1-xGexO as a buffer layer on the performance and efficiency of a solar cell based copper oxide (Cu2O) is investigated. The physical parameters of the solar cell model were selected according to the experimental data and then the new parameters of ZnGeO buffer layer was calculated based on the interpolated parameters of the energy levels of the band structure of binary compounds ZnO and GeO2 to study the solar cell performance for the germanium composition, ranged from 0.35 to 0.75. First, the accuracy of the initial model of the solar cell was verified by comparing its electrical characteristics with experimental data. Then, the characteristics of the initial model were analyzed and characterized in presence of buffer layer. By examining the cell efficiency for the changes of buffer composition (35% to 75% germanium), the minimum efficiency was observed 5.31% at x = 0.35 and the maximum was 7.02% at x = 0.65. The results show that using Zn0.35Ge0.65O buffer, the short circuit current of the cell reaches 11.15 mA with an open circuit voltage up to 1.08 volts.

Accurate Attitude and Heading Reference System (AHRS) play an essential role in navigation and guidance Unmanned vehicles. Today, the use of various algorithms and methods, including adaptive filter, neural network and predictor filters, to increase the accuracy of these systems and reduce the noise of its sensors, has received much attention from researchers. In this paper, the combination of LSTM deep neural network and kalman filter is used to improve the accuracy of AHRS system. In this method, first the deep network used is trained and then as a corrector, it corrects the effective coefficients of Filter Kalman. This method removes all the limitations of Kalman filter, including its linearity and non-memory, and improves the accuracy of the output attitudewithout the use of GPS. The experiments in this study, are based on real low-cost MEMS-based IMU sensors, which is less accurate than sensors used in similar article, installed on high-maneuverability UAV, present about 35% accuracy improvement in attitude estimation and 40% reduction of the output noise.

This paper designs a robust control system for wind turbines using a fuzzy sliding mode controller. Due to the increasing use of wind turbines and the importance of reliability and efficiency of these systems, in this paper the tolerance of wind turbine system using a combination of classical nonlinear and intelligent control methods against the occurrence of possible faults has been investigated. The wind turbine system based on the permanent magnet synchronous generator has been studied in this paper. In the design of the fault tolerant controller, a combination of the sliding mode controller based on advanced exponential acquisition law and fuzzy system is employed and the control goal is to track the reference input when the system is under fault conditions. Also, the designed controller is able to reduce the chattering phenomenon. To evaluate the performance of the proposed control system, simulated faults with different characteristics such as amplitude, occurrence time and dynamic change speed have been developed. Results confirm that the designed controller is robust against to actuator faults in the wind turbine system. Also, the output voltage is perfectly set to the constant reference value.

Detection of salient objects is done with the aim of identifying and segmenting prominent objects or areas in an image. Fully Convolutional Networks (FCNs) have shown their advantages in salient object detection; however, many previous works have focused on the accuracy of the prominent area without paying attention to its edge. This paper focuses on the complementarity between edge information and salient object one and added an edge recognition module to explicitly model edge information to maintain salient object boundaries. Our proposed network is trying to improve these two tasks simultaneously. The presence of objects with different scales in related datasets is another problem in this area. It requires an appropriate cost function to deal with the imbalance problem between background and foreground in images. So, we have used the hybrid cost function in the training phase, which is not sensitive to the scale of objects and can better manage the problem of spatial coherence and uniformly highlight salient areas without additional parameters. A Comparison of the quantitative and qualitative results obtained by the proposed method with other advanced methods in six widely used protrusion detection datasets shows that the proposed method has a good performance and can quickly identify prominent areas. In particular, according to the quantitative results, our method gets the best result on three widely used test datasets in terms of F-measure and MAE criteria, demonstrating the proposed method's efficiency.

Optimizing the energy consumption of gas pressure reducing station heaters is very important and vital due to their low efficiency. In this research, atmospheric burners of gas pressure reducing station heaters have been analyzed and simulated. The effect of the two main parameters of the inlet air temperature to the burner and the initial air flow has been analyzed. The effect of inlet air temperature on the combustion chamber in the temperature range of 253 K to 313 K was investigated. The results show that with increasing air temperature, the effects on burner performance and pollution rate are less than 10%, the initial air flow rate was considered from 1 g / s to 8 g / s and it was observed that NO pollution decreased from 32 ppm to 20 ppm and Secondary air flow rate from 0.05 kg / s to 0.35 kg / s was compared to compare flame shape and flue gas temperature as well as combustion pollution and the results showed that NO pollution was reduced from 32 ppm to 5 ppm and CO2 content was 60%. Decreased.

The penetration of distributed generation resources and energy storage units in distribution networks is increasing and the effect of these units can affect the efficiency of the network. In this study, the problem of distribution network reconfiguration in the presence of distributed generation units and energy storage systems is modeled in a dynamic framework. Conventional distribution network reconfiguration studies usually pay more attention to the loss objective function, but the importance of newer objective functions such as network reliability and security has been less explored. In this paper, the objective functions of energy not supplied as a reliability index, voltage stability index as a function of network security along with operational cost for the dynamic distribution network reconfiguration problem are introduced. The problem of distribution network reconfiguration is a nonlinear and non-convex problem, considering the effect of distributed generation and energy storage units further complicates the optimization problem. Hence, the fuzzy logic-based student psychology optimization algorithm for the single-objective and multi-objective optimization problem of the dynamic distribution network reconfiguration problem is proposed. The accuracy of the proposed method is evaluated on two test systems of 33 bass and 119 bass test and its superiority is shown by comparison with other evolutionary methods.

For a long time, waste materials have been used to produce compost by different methods. Despite the high importance of compost as an organic fertilizer for the fertility of agricultural products, the literature review on the compost supply chain shows that this issue has not received much attention. On the other hand, the quality of the compost produced is very important, which is considered by an innovative glance in the form of analytical hierarchical analysis method, in this paper. Therefore, a multi-objective model proposed which discusses the compost production process, compost supply chain design, compost quality, compost supply chain costs and furthermore the reduction of greenhouse gases emission. The multi-objective model is solved by weighted sum and epsilon constraint methods. The model is implemented for a case study to discover the efficiency of the proposed model. According to the sensitivity analyses, useful managerial insights regarded to determining the optimal capacity of suppliers and producers, improving the efficiency of the compost supply chain by considering the quality objective function, determining the appropriate transportation equipment taking into account the management priorities based on the entire supply chain cost and the legal requirements based on the emission of pollutants and determining the optimal method of compost production are extracted.

In this paper, We purpose to analyze the large bending of elastic curved structures that found in the engineering, science and nature. We investigated large bending of an open sector circular cylindrical tube into a complete circular cylindrical tube such that the solid is modeled via an incompressible, homogenous and isotropic hyperelastic material. According to the finite deformation of the structure, in the compressed side of bended beam wrinkles and local buckling may appear. We interpret the onset this instability by using the theory of incremental deformation superimposed on the finite deformation and analytical WKB method for Mooney-Rivilin strain energy function is utilized and boundary loads are defined for bending analysis. Moreover, the instability and numbers of wrinkles is studied in detail. The main results are that the obtained bending conditions are depended on the sector angles before and after deformation, exterior traction and the numbers of wrinkles per surface area. The trend of changes and dependence of these geometric parameters are examined by drawing diagrams