نشریه کارافن
سال بیستم شماره 63 (پاییز 1402)

Fish cell cellular metastructures have received wide interest from researchers due to their zero Poisson ratio behaviour. However, their production, which is mainly based on additive manufacturing processes, is one of their limitations. Therefore, in this research, a new method based on the conventional manufacturing processes including laser cutting and metal forming was presented for the production of metallic cylindrical metastructures. Two samples were manufactured using this method and their quality was verified using mechanical and non-destructive tests. The samples’ mechanical and buckling behaviour under uniaxial compression were simulated using ABAQUS FEM package and experimentally validated. This was followed by the effects of the metastructures’ geometrical parameters including the cylinder diameter, height and thickness on their linear buckling being investigated numerically, and the results compared with the outcome of classic theories for conventional cylinder buckling. The results showed that these metastructures can be produced successfully with the conventional manufacturing processes, and t the buckling behaviour of these metastructures does not follow the classical buckling theories of cylinders; their buckling behaviour shows much lower sensitivity to the thickness and radius changes in comparison with conventional cylinders.

Unlike other fabrics, non-woven fabrics are not produced from yarn; rather, during a fibre process, it is directly converted into textiles. In this way, separate fibres are placed together in different ways and are joined to each other to produce fabric so that in the end, a uniform and interwoven layer is formed without texture. The prepared layer is in the form of a spider web sheet in which the fibres are placed in a directed or random manner and are joined to each other by friction or glue or the tendency of the fibres to stick together or hydromechanically. In the old imported machines related to the production lines of non-woven fabrics, the cutting of the final product was done manually by the operator or by an electric element. Control of old devices is managed manually by system operators, leading to low productivity. In this research, an automatic cutting system was designed using PLC, HMI, and DRIVE. In this system, an encoder was used to send a signal to an Autonics controller to determine the length of the product. The cutting blade speed was controlled by DRIVE. HMI was used to control and monitor system performance by the operator. This system provided more than 40% productivity through practical testing in a factory. Furthermore, due to the elimination of manual cutting and the use of industrial automation, while increasing the speed, the output product was of high quality.

In this research, the thermal-hydraulic behaviour of fluid in the shell and tube heat exchanger with new segmental perforated baffles and hollow spiral baffles with basic structures (simple segmental and simple helical) were investigated. By using evaluation parameters such as heat transfer, pressure drop, ratio of heat transfer to pressure drop, and efficiency evaluation coefficient (EEC), the effect of the proposed baffles was compared with the basic structure (segmental baffle, single pass helical baffle). Based on the obtained results, the perforated continuous helical baffle reduced the pressure drop by 22.46% compared to the simple helical baffle and the perforated segmental baffle reduced the pressure drop by 19.76% compared to the simple segmental baffle. In a more comprehensive evaluation, the efficiency evaluation coefficient of pore helical and segmental baffle structures showed an increase of 18.3 and 11.17 per cent, respectively compared to the basic configuration. The concept of changing the flow pattern from helix to helix-longitudinal and from zigzag to zigzag-longitudinal made the flow distribution on the shell side more uniform. These conditions reduced areas prone to sedimentation (dead areas) and maintenance costs, and improved system performance. In addition, this new structure can replace conventional segmental baffles to save energy in the long term.

In the present investigation, the energy, exergy, economic and environmental (4E) characteristics of a waste heat recovery (WHR) system including a dual-loop Organic Rankine Cycle (ORC) and a heavy-duty diesel was investigated. The proposed system recovers the available waste heat of the engine exhaust gas, intake air, and the coolant. Central composite design (CCD) which is a standard technique of response surface methodology (RSM) was employed for the design of experiments (DoE). Parametric study of the output responses to the effective input parameters was performed. The results showed that increasing the amount of the engine variables led to a significant increase in power production and exergy destruction rate of the system and vice versa. The minimum amount of payback period (5.57 years) was observed in the high values of the engine parameters. The maximum output power of the WHR system was 330 kW, which was equal to 33% of the diesel engine brake power. The maximum value for the sustainability index was also observed at approximately 3.28.

In this study, the effects of fluid-solid interaction with an elastic rubber baffle in an inclined cavity were modelled numerically. In the upper and lower walls of the insulated chamber, the left wall is hot and the right wall is cold. The goal of the present research was to investigate the rate of heat transfer from the hot wall by calculating the Nusselt number and the von Mises stress at the root of the baffle at different slopes of the cavity. For this purpose, the solution geometry was modelled in the workbench software environment. k-ɛ method was used to solve the turbulent displacement flow (Ra>107). First, the effect of the presence of an elastic baffle compared to a rigid baffle was investigated. The values of the Nusselt number as the heat transfer rate from the hot wall for the elastic Baffle were 5% higher than the rigid Baffle. Then, the effect of the Inclined Cavity on the heat transfer rate, Nusselt number and von Mises stress in the root of the baffle was investigated. The heat transfer in the hot wall increased by approximately 4% with an increase in the slope of the cavity from a=0.01 to a=0.035. The maximum Nusselt number was obtained at slope a=0.035, and its maximum value was 40. It was also observed that the von Mises stress in the vane root in the cavity with a slope of a=0.035 was 40% higher than the von Mises stress in the vane root in the cavity with a slope of a=0.01. The Von Mises stress value of the root of the baffle underwent severe fluctuations tending towards a constant number and reaching a steady state after a few seconds.

Incremental forming process has the ability to make sheet parts with different cross-sections and sizes using simple and cheap forming tools. Using this process, it is possible to produce tubular sections, which are usually formed by hydroforming process. In this paper, the incremental forming of aluminum tubes with axisymmetric cross-section was investigated. A forming die setup was designed and manufactured to create symmetrical bulge on aluminum tubes, and the movement of the forming punch was performed by a CNC milling machine. In order to increase the formability of material, temperature of the tube was increased to a maximum of 300 degrees Celsius and the diameter of the formed part studied. Simulation of process was carried out using Abaqus software and ductile fracture criteria was used to find maximum formability. The results showed that the normalized Cockcroft-Latham criterion can be used with a small error to predict the maximum forming diameter. By increasing the process temperature from 100 to 200 °C, the forming diameter increased by 4%. The greatest effect of the forming step was observed at 300 °C, and with the increase of the step from 0.5 to 1.5 mm, the forming diameter decreased by 3.7%. The fracture section of the tubes was also examined by scanning electron microscope (SEM).

Valve originates from the French word, Soupape, meaning valve and its role is to control the mixture of air and fuel entering the engine and the exhaust fumes. In this research, dimensional defects and valve cracks were diagnosed with the help of machine vision and acoustic emission. After offline transfer of the images to MATLAB software, the images were processed and the dimensional parameters of the valve such as length, stem diameter, large diameter (seat) and valve stem curvature were measured. These parameters were compared with the actual sizes and the percentages of measurement error for these parameters which were estimated as 0.45%, 1.8% and 1.18%, respectively. Because there was no real way to measure the valve stem, the error percentage was not calculated for this parameter. To detect cracks from 60 similar new valves, an acoustic diagram prepared by AE-MAP 1.0 device and the acoustic diagram of 30 new and used valves were compared. The accuracy of the system in crack detection was estimated to be approximately 96.7%.

In the present research, the possibility of designing and manufacturing a gear mechanism including a unilobe elliptical gear and a spur gear was investigated. The innovation of this mechanism is the engagement of a circular gear with a non-circular gear and the creation of a continuous movement in one of the two shafts on which the gears are placed. First, the geometry of both gears was assessed and the two-dimensional cross-sectional model of the gears was drawn by Gearotic motion software. Then, 3D models of the gears were produced and assembled, followed by a scrutinization of the engagement of the gears, the proper design of teeth shapes, and the driven shaft movement. The wire electrical discharge machining was employed to manufacture the gears from the Al 7075. Next, the surface roughness of the gear teeth was measured and their engagement checked. The results revealed that the designed mechanism provides cyclic movement in the driven shaft of the spur gear during engagement with the elliptical gear. Moreover, the smooth and proper movement of the gears shows that the use of the software and the correct selection of the input parameters did not cause any errors in the manufacturing process.

In this research, the life of the tool and the wear rate of the cutting edge of the tool were investigated using R410a coolant in cooling the cutting edge of the tool and comparing it with the traditional fluid of soapy water. In addition, dimensional deviation and surface roughness of steel (ck45) 1045 in chipping with a high-speed steel (HSS) tool at cutting speeds of 15, 25, 40, and 55 meters per minute cutting depths of 0.5, 1, and 1.5 mm and feed rate of 0.05, 0.12, and 0.2 mm /rev were investigated in two modes of liquid cooling, soapy water and R410a coolant. The obtained results showed that cooling with R410a refrigerant, due to its high cooling power and better control of the temperature of the cutting area compared to the soapy water fluid in the machining process, reduced the amount of tool wear and can be used as one of the suitable cooling fluids. Based on the minimum values of dimensional deviation and surface roughness under different conditions, by using R410a refrigerant, the cutting speed can be increased by 60% from 25 m/min to 40 m/min. Furthermore, in the most optimal mode, at a cutting speed of 40/min, the chipping depth is 1 mm and the advance values are 0.05 mm per round, the dimensional deviation and surface roughness are improved by up to 6 and 10 times. In the optimal state, the dimensional deviation based on the diameter difference in 300 mm length is 14 microns and the surface roughness will decrease to 3.1 micrometers after 60 minutes of chipping time.

Today, solar desalination is one of the promising solutions for the problem of drinking water shortage, mainly in remote and low-population areas. In the present research, a solar still with passive external condensers was designed. To store the thermal energy in the basin of this solar still, paraffin wax was used in copper tubes as phase change materials. To compare and investigate the performance of the proposed solar still, a conventional solar still with the same specifications and dimensions was built and tested. Both solar stills were investigated on the days of 28 April, 5 and 9 May. The results of the experiments showed that the performance of the proposed solar still was better than the conventional solar still; the highest produced fresh water was 3.55 and 3.04 lit/m2 day, respectively, for the proposed and conventional solar stills, which showed a 17% increase in productivity per day. It is clear from past research that the condenser increases the temperature difference between the glass covers and the saltwater of the basin, but causes the temperature of the saltwater basin to decrease. However, in this research, in addition to the increase in the temperature difference between the glass cover and salt water, the amount of salt water also increased, and this trend of increasing temperature was observed until the end of the day in all three experiments, which shows the effective performance of paraffin wax in the basin of solar still.

In the present research, a three-degree-of-freedom haptic device was used to simulate a virtual object located on a point on a two-dimensional wall. Two spatial coordinates of the operating point on the wall were arbitrary. Therefore, the robot would have two degrees of freedom redundancy for this task. These two degrees of robot redundancy were specified by the artificial bee colony optimization and crow optimization algorithm in such a way that while ensuring the stability of the robot, the damping coefficient of the simulated virtual object was also maximized. The optimization process was performed in two different ways. In the first case, the stiffness of the robot was assumed to be a constant value in the whole workspace, while in the second case, the stiffness was considered a function of the robot configuration. In each case and at each operating point, first an effective mass, an effective damping coefficient, and an effective stiffness for the robot were obtained, and then using some theoretical relations, a stable operation boundary was obtained. Finally, the optimization methods specify the location of the operating point in such a way that the simulated damping coefficient was maximized. The results show that in the case of constant robot stiffness, both of the mentioned methods were able to simulate the maximum value of 1.825 for the virtual damping coefficient. However, in the case of variable robot stiffness, the crow and bee algorithms reached the values of 2502 and 2498, respectively as the maximum damping coefficient that could be simulated. In addition, although the number of cost function calculations is the same in both methods, the crow optimization algorithm was faster and more repeatable.

A hybrid plan is one of the solutions to increase the economic efficiency of renewable power plants. Photovoltaic and wind energy are the two major sources of renewable energy that will account for a large part of energy production in the future. The energy supplied from these sources is unpredictable, and as a result, to increase the reliability and availability of the load, the capacity of these power plants and their storage system should be considered much higher than demand. In this article, a hybrid system including wind turbines, solar arrays, and fuel cells for two scenarios, summer and winter load patterns, were designed. This proposed system minimizes the 20-year costs including initial investment, operation, and maintenance, as well as the cost of load losses. The equivalent loss factor of the system should be provided along with other constraints. Therefore, the solar radiation and wind speed data related to a region of Iran (Kerman Province) were considered in addition to the load pattern. The possibility of an emergency exit of three main components of the system, wind turbines, solar arrays, and AC/DC converter, was also considered, and the Crow search algorithm and PSO algorithm were used for optimization and validation. The results showed that the optimal sizing of energy production systems based on renewable resources in addition to the improvement of production technology are the main solutions for reducing the costs of these systems.

Using the capabilities of smart meters and smart grid technologies, a new demand response (DR) participant with considerable load flexibility was created from the residential side called the intelligent residential community. In this paper, smart residential loads were divided into three categories of shiftable, interruptible, and controllable loads and a new method based on binary particle swarm algorithm (BPSO) to solve the DR problem is presented. The type of load shedding was determined for different loads. Then, by solving the continuous variables of the problem, the amount of load shedding at different loads was determined. The proposed system uses distributed generation sources, battery storage, and electric vehicles. Furthermore, in the proposed model, a robust optimization method for dealing with uncertainties is presented using a variety of real-time pricing (RTP), time-of-use (TOU), and critical peak pricing (CPP) schemes in a robust design. A comparison of the different types of demand response schemes was made and the best design for optimal demand response was selected. To validate the proposed method, a simulation was performed on a test system and the results indicated the efficiency of the proposed method in planning and reducing users' consumption costs.

Severe voltage fluctuations at different points of the network are the main concerns of the widespread low-voltage electrical energy distribution networks. In particular, small industrial loads and rural consumers in remote geographical areas, which are fed by long lines, always experience great voltage drops. The use of common distribution transformers equipped with off-load tap changers has not been effective in solving this problem due to issues such as lack of access to all network points for operators, the need to de-energize the line during tap change, and the successive and unpredictable load changes. Therefore, the use of transformers with automatic voltage adjustment at different points of distribution networks has attracted much attention. The present research aimed to implement a simple solid-state voltage regulator (SSVR) in the low power range to automatically eliminate severe voltage fluctuations. In this research, a solid-state voltage regulator with a rated power of 5 KVA was designed and built to automatically compensate for the voltage of a small group of home customers (who have a severe voltage drop due to the distance from the distribution post). The results of the measurements showed that this equipment can limit the voltage changes to 220±3%, while it does not affect the power quality. In addition, various hardware and software protections were designed for the device built against network disturbances and abnormal consumer functions.

Many investigations have been conducted to detect single incipient faults in squirrel cage induction motors. However, there is much less research on detecting and discriminating simultaneous faults within the induction motor. The simultaneous presence of eccentricity fault with some other faults is unavoidable due to some manufacturing imperfections or the possible misalignment of the motor-load shafts. Neglecting the intrinsic eccentricity and simultaneous faults might cause mistakes in the condition motoring of the motor. This article presents an analytical and experimental approach to detecting the simultaneous mix of eccentricity and broken rotor bar faults. Theoretical analyses represented how the indicators appear in the stator current due to mechanical faults according to dynamic equations, MWFA, and Fourier series. Thus, a new frequency indicator was introduced to identify simultaneous faults. The suggestive index is monitored in the modified winding function (MWFA), and finite element (FE) simulations and its amplitude was studied in motors with healthy conditions and separate and simultaneous faults. Simulation and experimental results confirmed the capability of the proposed index to distinguish simultaneous faults from other cases. This method is non-invasive, low-cost, load-independent, and can be implemented in the monitoring system of any motor.

Accurate load power sharing and voltage regulation are two critical control objectives to ensure power quality and reliable operation of islanded microgrids. Although voltage regulation can be achieved using a secondary control loop, the inaccuracy of reactive power sharing is a prominent issue due to the varying impedance of lines connected to distributed generation sources. One of the techniques for accurate sharing of reactive power is to modify the production reference voltage by the droop control method. In this paper, a control strategy is proposed to improve the accuracy of reactive power sharing among distributed generation units of islanded microgrids. The proposed control method was based on transient reactive current injection to modify the production reference voltage of the droop control method. The reactive power-sharing error was reduced by changing the reference voltage. In addition, the proposed controller did not require a communication link between distributed generation sources for implementation. The effect of the proposed controller on the stability of the system was demonstrated using the reduced-order small-signal model. To evaluate the performance and effectiveness of the proposed control strategy, it was implemented on an islanded microgrid consisting of three distributed generation units. The simulation results showed the proper performance and efficiency of the proposed method.

This paper presents a novel robust solution to the problem of model predictive control for a nonlinear, discrete-time rocket in the presence of finite disturbances. First, a mathematical model for the rocket in the state space was presented. Then, the basic equations of a typical six-Degree-of-Freedom airframe dynamics (6DoF) were separated as lateral and longitudinal dynamic equations. Linearization of these coupled dynamics was presented by using aerodynamic coefficients. Next, an augmented Model Predictive Control (MPC) was designed by using an observer to estimate states and disturbances, allowing the controller to reject disturbances. Application of the disturbance observer leads to the definition of a new state space and domain for MPC, which was considered in the present research. The predictive model control problem for the uncertain system was solved in finite time and online, and the decision variables were the initial states and disturbance estimations. Finally, the performance of the developed method was evaluated by simulation.

The Antilock Braking System (ABS) technology has an acceptable performance for vehicle control. Thus far, different control strategies have been used to control the Antilock Braking System of vehicles. The aim of this paper was to achieve a sliding mode control system as a better system for vehicle Antilock Braking System control so that the applied control signal leads to smooth and non-sudden operation of the Antilock Braking System. Unavailability of a sensor to sense state variables leads to their estimated values being used in the feedback path of the system instead of using the original values of the state variables. In this article, in addition to the design of the controller, a strategy for designing multiple observers is presented. This leads to the fast and stable performance of the Antilock Braking System control system. Effectiveness of the proposed strategy was confirmed by simulation in the MATLAB environment. The simulations were based on the real-world data and therefore, the results confirmed the performance of the proposed method in real applications.

The Internet of Drones (IoD) is a decentralized network that connects drones to controlled airspace. The connection of drones in these networks is through the Internet of Things. Hence, these networks are vulnerable to all the security and privacy threats that affect IoT networks. In addition, as the application of these networks is highly sensitive in many cases, there are greater potential security threats. The components of these networks work together to identify new and advanced threats. One of the ways to identify new and advanced threats in these networks is distributed machine learning where the data is sent to a central server to learn the general model. This model violates the privacy of network components. It also has a very high level of communication. On the other hand, the central server as the only point of failure may have many problems. In this case, federated learning helps distributed and decentralized networks to share their local model instead of sending their local and secret data. Since the shared models may also disclose some information, we propose a secure and privacy-preserving protocol based on homomorphic encryption. The protocol proposed was for federal learning model and detection of new and advanced threats in the Internet of Drones.

With the rapid expansion and growth of web data, the web graph structure, which is a graphical representation of the web world, is getting larger and larger and has gradually changed from a content structure to a non-content structure. The presence of junk data such as noisy hyperlinks in the web structure graph has caused problems for many link mining algorithms and reduced the speed and efficiency of information retrieval algorithms. Research has been conducted to remove noisy hyperlinks using structural and string approaches. These approaches incorrectly remove some useful hyperlinks and are unable to detect noisy hyperlinks in some situations. In this paper, a dataset of noisy and useful hyperlinks was first created by an interactive crawler using website crawling. Then, through semantic web approaches and facilities such as the Dbpedia ontology, attention was paid to the semantic and relational structure of these hyperlinks. This was followed by activating the DBpedia ontology reasoner, the process of removing noisy hyperlinks from the web structure graph taking place. The tests performed on this system showed the accuracy and capability of Semantic Web technologies to remove noisy hyperlinks.

The increasing growth of computers and the internet has provided a new and widely used platform for providing network services. This has significantly increased the provision of administrative, social, financial, educational and recreational services on the network, particularly the internet. The expansion of the use of Internet applications creates an opportunity to abuse the network and its information for criminal purposes. Based on this, intrusion into the network and unauthorized access to information have become the main concerns of network users as well as network managers. Intrusion detection systems include a set of tools and mechanisms for monitoring computer systems and network traffic. Various methods are used for intrusion detection, such as statistical techniques, cognitive-based methods, and machine learning methods. In the present research, a method for intrusion detection using machine learning algorithms was reviewed and proposed. The proposed model is a multi-class method that, in addition to intrusion detection, also determines the type of attack. This method is a hybrid model in which the combination of the Seagull optimization algorithm, thermal exchange optimization algorithms and random forest algorithm are used. CICIDS-2017 dataset was used for analysis in this research. The proposed method was compared with several different algorithms and the accuracy value of the proposed method was equal to 98.8, which is higher than that of many machine learning methods.

Today, with the increase in the use of the internet, people have turned to the internet to buy their products or to learn about various topics. There are a large number of virtual pages where users post their opinions on various topics. A large amount of data exists which extracting useful information from is a costly and time-consuming task. Opinion mining is the process of intelligent analysis of the sentiments of users who have expressed their opinions in relation to a specific topic with the capability of extract them. The machine learning method is one of the most optimal and efficient methods for extracting knowledge from users' opinions on the offered products. In these methods, the training data of a system is given to classify user opinions. One of the most important classification steps is data reduction. By using the new feature combination method, the set of extracted features can be reduced to a greater extent than the feature selection method, which leads to a subset of useful information with a much smaller volume and higher recognition power. In this research, particle group optimization algorithm was used to optimize the combination of features. To evaluate the proposed method, MATLAB software was used to evaluate the proposed method, and experiments were conducted on four data sets. The results of the research showed that the use of the feature combination method increased the efficiency of classification and reduced the effect of this increase in the decrease of the efficiency of the classifier.

With the increasing expansion of networks connected to the internet, attackers' efforts against these networks have also grown. Therefore, many researchers have proposed solutions to deal with botnets that lead to remote contamination of systems. One of the main problems of existing methods is the high rate of false alarms produced by attack detection systems, including the rate of false positives and false negatives. In the present research, by using machine learning algorithms, these alarm rates were reduced. In the first stage of the proposed solution, the dataset entered a pre-processing stage so that outliers and noise data were identified and discarded. Then, using the K-Nearest Neighbor algorithm, the non-useful features that had no effect in determining the data class were excluded from the dataset. In the next step, the Gradient Descent algorithm was used to accurately detect the class of data and categorize them into normal data or botnet attack. Finally, by performing various tests on the CTU-13 and BoT-IoT datasets in both binary and multi-class modes, the values of the important criteria for evaluating the effectiveness of the botnet attack detection system were obtained. The results showed that in the CTU-13 dataset, in binary and multi-class mode, the false negative rates were 0.01 and 0.04, and the false positive rates were 0.01 and 0.05, respectively; and for the BoT-IoT dataset, in binary and multi-class mode, the false negative rates were 0.02 and 0.05 and the false positive rates were 0.03 and 0.05, respectively. Compared to other existing methods, the proposed method is superior and demonstrates a reduction in the rate of false alarms and improves efficiency.

Incremental dynamic analysis is one of the most common analyses in evaluating the seismic performance of structures. Usually, in this method, the influence of uncertainties is ignored and only by considering different records, it attempts to evaluate the uncertainty of seismic load. In this research, an attempt was made to investigate the effect of random variables on these curves by using two methods Monte Carlo and Tornado diagram. A 10-story steel frame with a dual bending frame system with a divergent brace was selected and then the effect of uncertainties on its IDA curves was investigated. First, by using the Monte Carlo method, the sensitivity of the IDA curve of the Bam earthquake record with respect to six random variables including yield stress of steel, dead load, live load, span length, damping ratio and elastic modulus was investigated. Then, using the tornado diagram method, the sensitivity of these variables on the average IDA curves obtained from 18 records of different earthquakes was investigated. The results demonstrated that dead load and yield stress had the greatest impact on random variables. In addition, the degree of sensitivity of random variables increased with the increase of spectral acceleration. The comparison of the tornado diagram method with the Monte Carlo method illustrated that the tornado diagram method with a maximum error of 12.4% has a good accuracy in evaluating seismic sensitivity.

Due to the increase in population rates and the extensive growth of the construction industry in developing countries, the trend of occupational accidents in this sector has been increasing in recent years. In order to minimize such accidents, research must be conducted on the cause of occurrence and prevention methods of these accidents. Therefore, the current research was carried out with the aim of identifying and determining the impact of effective factors on the prevention of accidents at construction sites, using a descriptive-analytical method in terms of nature and practical in terms of purpose. The statistical population included supervisors and supervising engineers of construction sites with more than 10 years of experience working on construction sites in Kermanshah city. The primary information was collected through document-library review and based on the expert opinions, the effective factors in preventing accidents at construction sites were classified under three categories: managerial, individual and environmental. The primary research tool was a questionnaire, and SPSS and Smart PLS software were used to analyze the data. Model analysis was conducted by the structural equation modeling method with partial least squares approach. The results showed that the conceptual model of the research had a favorable fit. All relationships between sub-factors and factors were significant, and the managerial factor with a path coefficient of 0.724 had the greatest impact and the environmental factor with a path coefficient of 0.309 had the least impact on the prevention of accidents at construction sites.

The purpose of this research was to design a development model to optimize the production of gasoline products in an oil refinery. The research method was an experimental using non-linear programming with Gomes software, version 24.1.2, Solver Baron, and conducted experiments on octane number, vapor pressure, and benzene amount on slices and mixing slices in the laboratory. One of the innovations of this project is the amount of blending of cuttings effective in the production of gasoline products in different seasons of the year in such a way that the variables of octane number, vapor pressure and benzene of the final product are in accordance with the standard specifications of the National Refining and Distribution Company because currently the change of seasons is not taken into account and cuts in the production of gasoline products are made by guesswork and error. Due to the multi-objective nature of the problem, the weighted sum method was considered for the objective functions. The characteristics of octane number, vapor pressure and benzene amount of the combination of the cut values ​​obtained from the output of the software were tested in the laboratory and compared with the results of the software. Taking into consideration the very small difference between the results of the two methods, the output values ​​of the software were confirmed.

This study was conducted with the aim of investigating the effect of layer coating of nano polyurethane and nanoclay on improving the properties of cold-storage white top kraft paper used in the packaging industry. For this purpose, white top kraft paper with a base weight of 131 g.m-2 was prepared and tested. To cover the surface of the paper, nano-polyurethane was first applied by spraying with a nozzle in an amount of about 15 g.m-2 on the surface of the white top paper. In the second stage, to improve the performance of the coating material of the first stage, the surfaces of cold-storage white top kraft paper were covered with nanoclay by a laboratory coating machine. In this step, the coating material was coated with the amount of 27 g.m-2 on the upper surface of white kraft paper. After being coated and restrained, the samples were dried at room temperature for one day to stabilize the coating material on its surface. Then, the samples were placed inside the freezer for 2 and 4 months and their properties were measured. Before the tests, the control and coated samples were placed in standard environmental conditions (at a temperature of 20 οC and relative humidity 65%). The results showed that the coating (control) increased the thickness, smoothness of the surface, and the resistance against the ring crush of the paper in the direction of the machine and reduced the water absorption, brightness and other mechanical properties such as the tensile strength index machine direction (MD) and cross direction (CD), burst strength index, tear strength index (MD and CD),  and ring crush test in the cross direction in frozen coating samples with increasing thickness and surface smoothness; a decrease in other mechanical properties was observed. The samples coated twice showed very few pores. The thickness and surface smoothness of white coated kraft paper showed an increase of 30.8% and 37.7%, respectively, compared to the control sample. Water absorption, burst strength index, tear strength index (MD and CD), tensile strength index (MD and CD), ring crush test (MD and CD), and the brightness of the double-coated white kraft paper compared to the control sample, respectively showed a decrease of 151, 87.4, 15, 13, 104.2, 103.2, 67.1, 82.3 and 11.8%. According to the obtained results, it is recommended that papers such as liquid packaging cardboard, juice and milk packets, which have many applications in food packaging, should be tested with these coatings with different times.

Energy is the source of life obtained by exploiting various natural resources, including fossil fuels. Nowadays, one of the most important challenges in this field is the combination of production sources with electric energy storage systems. Supercapacitors have received a great deal of attention as a new technology for producing and storing electrical energy. In this research, a simple hydrothermal method was used to prepare bimetallic mixed hydroxide CuSn(OH)6 on a nickel foam substrate, and then the electrochemical behavior of the electrode was tested for use in electrochemical supercapacitors. Field emission scanning electron microscopy (FESEM) and transmission electron microscopy (TEM) were used to examine the morphology and structure of the synthesized electrodes. In addition, X-ray energy dispersive (EDX) and elemental mapping techniques were used to identify the composition and phase of the produced nanostructures. The electrochemical performance of modified electrodes in 2 M KOH electrolyte solution was investigated by several electrochemical methods including cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), and electrochemical impedance spectroscopy (EIS). The electrode prepared in this study showed high specific capacity (2012.84 F g-1 at a current density of 1 A g-1) and excellent cycle stability (90.44% after 3000 cycles). Moreover, this supercapacitor electrode's maximum energy and power density were 140.88 Wh kg-1 and 29.16 kW kg-1, respectively.

Graphdiyne nanostructures have been considered due to the predictions of quantum calculations regarding the occurrence of special electronic and structural features before the synthesis of these structures. Among these predicted nanostructures, graphdiyne nanotubes show special properties. There are limited studies on these new structures. In this research, an attempt was made to simulate the stable structure and behavior of graphdiyne nanotubes with different chirality in an aqueous environment. Bonding between graphdiyne nanotubes and water molecules is an endothermic process. In this investigation, NVT and NPT simulations were performed in order to study the accumulation of water molecules and their behavior in the walls and inside of different graphdiyne nanotubes. In addition, the effect of pressure on the water-nanotube system was investigated. The results showed that water molecules do not enter into small-diameter nanotubes and aggregate in the walls, and this is due to the hydrophobic property of smaller carbon nanotubes in contrast to the larger nanotubes. In addition, the positive effect of pressure at the constant temperature on the aggregation of water molecules inside graphdiyne nanotubes (2,0) was observed.