Sharif Digital Repository

Unanticipated failure of reinforced concrete structures due to corrosion of steel rebar embedded in concrete causes to increase the demand for finding methods to forecast the service life of concrete structures. In this field, the success of machine learning-based methods leads to the use of multi-gene genetic programming (MGGP) method for classifying the degree of corrosion destruction of steel in reinforced concrete in this paper. Despite the common application of MGGP that is the symbolic regression, in this research, MGGP was adapted to use in classification tasks. Accordingly, a large field database has been collected from different regions in the Persian Gulf for modeling of MGGP and... 

In Industry 4.0, the emergence of new information technology and advanced manufacturing technology (e.g., digital twin, and robot) promotes the flexibility and smartness of manufacturing systems to deal with production task fluctuation. Digital twin-driven manufacturing system with human-robot collaboration is a typical paradigm of intelligent manufacturing. When production task changes, manufacturing system reconfiguration with dynamic opeartion task allocation between operator (human) and robot is a key manner to maintain the production efficiency of intelligent manufacturing system with human-robot collaboration. However, the differences between operator and robot are neglected during... 

In the present study, the solubility of paracetamol in supercritical CO2 is measured at temperatures between 311 and 358 K and pressures between 95 and 265 bar. It was shown that the solubility of paracetamol through a static solubility measurement method was between 0.3055 × 10−6 to 16.3582 × 10−6 based on mole fraction. The obtained experimental solubility data revealed the direct effect of pressure on the paracetamol experimental data, while the temperature has a dual effect of both increasing and decreasing effect considering the shifting point known as crossover pressure which was measured to be around 110 bar for paracetamol. Besides, two theoretical approaches were applied to predict... 

Multilateral well is a promising technology in developing oil reservoirs. Because this technology may increase the production rate per well and reduce the costs of field development, it is rapidly replacing the old methods. This study uses a three-dimensional line-source model with direct search methods, including pattern search and genetic algorithms to optimize the well trajectories. This method was applied to several cases, with different forms of wells and reservoirs. In all cases, significant improvement was observed in the production rate. Furthermore, the production enhancement using the optimized well trajectories which have curved-paths is compared to the case with linear well... 

So the design and control of an accurate robot for this purpose is very critical for saving the patients. Modification of the model and designing two optimized nonlinear robust controllers for the first time for the parallel manipulator medical robot and cardiopulmonary resuscitation. The main objective of the current study in order to decrease the overshoot and increase the accuracy of the position and convergence speed and robustness to destructive factors affecting the precision of the robot. In this paper firstly, the kinematics and dynamics analysis of a translational parallel manipulator robot is presented and a non-linear model in the presence of uncertainties, disturbances, and... 

Distribution systems are one of the most important infrastructures of each country which are exposed to numerous damages through unexpected events. The development of distributed energy resources (DERs) is one of the solutions which can bring several benefits to the operation and planning of distribution systems in both normal and event situations. This paper proposes a new multi-objective planning model for optimal siting and sizing of DERs in distribution systems to minimize the total planning costs including operation and active power loss costs, as the normal operation objective, and to minimize the expected prioritized load shedding exposed to an earthquake incident, as the resilience... 

The Internet of Things (IoT) is a new concept in the world of technology and information and has many applications in industry, communications, and various other fields. In the lowest layer of the IoT, wireless sensor networks (WSNs) play an important and pivotal role. WSN consists of a large number of sensors and is commonly used to monitor a target. It is important to reduce energy consumption in WSNs to extend network life, since it is usually impossible to replace sensor batteries. In this paper, a novel clustering and routing method is proposed. It is mainly based on genetic algorithms and equilibrium optimization. To improve scalability, the sensor nodes are clustered in the first... 

The reinforcement of concrete columns with fabric reinforced cementitious matrix (FRCM) is one of the most challenging issues in the construction of concrete structures, as there is still an absence of a promising model to assess their performance. This is because the behavior of such elements is complex and accompanied by a high margin of uncertainty. To address this issue, this study compiles a large dataset of the performance of FRCM-reinforced concrete columns under monotonic load. The obtained dataset is then used to train an artificial neural network (ANN) as a promising method for predicting the compressive strength of concrete columns with acceptable accuracy. Afterward, using a... 

This article presented an efficient deep learning technique to predict the compressive strength of high-performance concrete (HPC). This technique combined the convolutional neural network (CNN) and genetic algorithm (GA). Six CNN architectures were considered with different hyper-parameters. GA was employed to determine the optimum number of filters in each convolutional layer of the CNN architectures. The resulted CNN architectures were then compared to each other to find the best architecture in terms of accuracy and capability of generalization. It was shown that all of the proposed CNN models are capable of predicting the HPC compressive strength with high accuracy. Finally, the best of... 

In this paper, several new control strategies for employing the battery energy storage systems (BESSs) and demand response (DR) in the load frequency control (LFC) task are proposed. In this way, first, the unit commitment problem considering the BESSs’ constraints in presence of wind farms and responsive loads is solved and the best location and the optimal size of the BESSs as well as the regulation power of the responsive loads are obtained. A rule-based plan is then suggested to improve the frequency regulation considering participation of wind farms. This plan is takes into account different states associated with power system frequency response as well as BESSs’ state of charge (SOC).... 

In recent years, the number and severity of natural disasters occurring in various regions of the world have increased dramatically incurring heavy financial and human losses. Therefore, decision-makers have been concerned with ways of providing relief to reduce the losses. Here, we present a multi-objective bi-level model for disaster location-routing problem that provides the needed supplies through multiple suppliers, considering the supply risk. Moreover, to reduce the risk and increase efficiency, special attention is given to people's help for supplying goods having high priority and low risk. At the first level of the model, the cost and time objectives are considered, and at the... 

In the present research, the authors have attempted to examine the compressive strength of conventional concrete, which is made using different aggregate sizes and geometries considering various curing temperatures. To this end, different aggregate geometries (rounded and angular) were utilized in various aggregate sizes (10, 20, and 30 mm) to prepare 108 rectangular cubic specimens. Then, the curing process was carried out in the vicinity of wind at different temperatures (5◦ C < T < 30◦ C). Next, the static compression experiments were performed on 28-day concrete specimens. Additionally, each test was repeated three times to check the repeatability of the results. Finally, the mean... 

Abstract: Advancements in microscale technologies have prompted a demand for high precision micro-manipulation. Microgrippers are the primary means of conducting micro-scale operations, and they significantly affect the procedure's performance. This paper presents a novel optimized design for compliant microgrippers, intending to enhance functionality and durability. The mainframe of the proposed microgripper is based on a compact flexure-based compliant structure with four stages of movement amplification. Experiments were designed based on the L25 Taguchi orthogonal arrays. The experiments were conducted using the finite element method in Abaqus 6.14 workbench. Range of motion and maximum... 

Minimum cost of energy is the main goal of a wind farm layout optimization. This is achieved by maximizing the total energy while minimizing the total costs of the farm. In this study, two sizes of commercial turbines were considered to investigate the effect of a non-homogenous farm on the layout optimization process. A cost model consisting of turbines, cable, transformers, foundation, and service vehicle routes was developed. Using Genetic Algorithm and Artificial Neural Network, first the superiority of the new algorithm in turbines and cable layout was verified versus previous studies. Next, two cases were investigated, i.e. (1) a farm populated with identical turbines and (2) a farm... 

Anchored wall system is one of the common methods used for deep excavation stabilization adjacent to sensitive structures in urban areas. A key aspect of the stability analysis of deep excavations is the amount of deformations occurring on the facing wall and the adjacent structures. In this research, a large number of parametric studies considering all aspects of soil-structure interaction is carried out for different excavation geometries to find the optimal design, and the outcome is shown in the form of design tables and charts. Also, by a GA-PSO algorithm and using the large database obtained from the numerical simulations, a simple equation is developed that can predict the deflections... 

In this study, in order to maximize the reaction rate of neutron activation (NA), an approach using combination of the MCNP code, the feed-forward neural network with the Bayesian regularization (FFNN-BR) learning algorithm, and the genetic algorithm (GA) is proposed. The MCNP code calculates the reaction rates based on the different moderator dimensions/ target positions. The calculated reaction rates with appropriate features (i.e. RT, R2S, and Z2S) are applied for training of the FFNN-BR. The trained neural network is utilized for estimating the reaction rates of the generated individuals by the GA. The results show that the trained neural network estimates the reaction rates with... 

Nowadays, deliberate or unwanted fire incidents have created much attention to the behavior of structures against these types of events. Since the properties of structural members are influenced by the increase in the temperature of the members, it is more difficult to predict the general and local behavior of the structures during the fire. In this research, a method has been proposed to calculate the critical temperature in two-dimensional structures at its collapse with desirable accuracy. In this process, the upper-bound theory of plastic analysis is used. The plastic analysis is performed by applying the initial fire scenario to the structure, and its collapse load factor with the... 

An efficient isogeometric-based framework is presented to integrate optimum design and formability analysis of sheet metal forming processes. To assess the quality of the formed parts, several objective functions such as fracture, wrinkling, thickness variation, and stretching are studied. In this framework, geometric parameters of addendum surfaces and middle tools are considered as design variables, the objective functions are calculated using the recently developed one-step and multi-step inverse isogeometric methods, and the optimum design variables are obtained using the genetic global optimization algorithm. The major advantage of employing the inverse methods is to analyze the... 

In this paper, a novel six-phase outer rotor induction motor equipped with pseudo-concentrated windings is introduced as a robust, reliable, and low-cost solution. Multiple aspects of the proposed motor structure have been investigated such as a design algorithm and an analytical modeling based on the modified winding function considering the skew effect. The effect of using variable number of turns for the coils has been examined on the pseudo-concentrated windings. An appropriate optimization problem has been also defined to maximize the power factor and efficiency and to minimize the output torque ripple. The designed motor has been fabricated to verify the accuracy of the design... 

In the seismic design of steel special moment frames, it is necessary to ensure that columns are generally stronger than beams. This reduces the probability of a weak story failure mechanism of the frame and ensures the formation of beams' plastic hinges earlier than the columns'. This criterion is known as strong column-weak beam (SCWB) in seismic design codes and is checked by a formula in the form of a ratio of total flexural strengths of columns to beams framing at each joint. It is common practice to ignore the column section change at the splice location and to use the flexural strength of the larger column section in evaluating this ratio. In this paper, several steel special moment...