In petroleum production processes, stable emulsions are extracted along with crude oil. The stability of these emulsions, primarily due to the presence of naturally occurring surface-active compounds in crude oil, leads to various operational and environmental challenges. Therefore, the effective separation of these emulsions is considered one of the critical and essential challenges in the petroleum industry. To provide an effective solution to this challenge, a hyperbranched polymeric demulsifier based on a polyester structure was synthesized in this study via direct polycondensation between a trifunctional polyalkylene glycol as the branching agent and a difunctional isophthalic acid. The hyperbranched structure, with a higher density of end-groups, enables multi-point and faster adsorption at the interface. A series of characterization analyses were performed to confirm the structure and the successful synthesis of the demulsifier, and the results verified the effectiveness of the synthesis process. The performance of the synthesized demulsifier in water-in-oil emulsion separation was evaluated under various operational conditions, specifically demulsifier concentrations ranging from 50 to 100 mg/L, temperatures from 40 to 70°C, and settling times from 10 to 60 minutes. Under the optimal conditions, including concentration of 90 mg/L, temperature of 70°C, and settling time of 50 minutes, demulsification efficiency of approximately 85% was achieved. In addition to its amphiphilic nature, the hyperbranched polymeric demulsifier exhibits acceptable separation performance due to its hyperbranched structure and favorable properties, including an appropriate molecular weight, relatively uniform structure, and high flexibility of the polymer chains. Subsequently, in order to further enhance the performance of the hyperbranched polymeric demulsifier and investigate the effect of magnetic nanoparticles on this system, magnetic graphene oxide nanoparticles were synthesized and incorporated into the system as a modifying agent. Under the previously determined optimal conditions and at a concentration of 0.025wt%, these nanoparticles increased the demulsification efficiency to 95.6%. In addition, the magnetic properties of the nanoparticles enabled their efficient recovery from the system, which not only reduced material consumption and operational costs but also demonstrated the potential for their reuse. Overall, the results of this study demonstrate that the synthesis of a hyperbranched polymeric demulsifier and its modification with magnetic graphene oxide nanoparticles provide a novel and innovative approach for the demulsification of water-in-oil emulsions. Furthermore, due to the high potential of this system in emulsion separation, the findings of this research can be utilized for industrial applications and further research studies in the petroleum industry.   

Unsaturated polyester resin (UPR) is widely used in the composite industry due to its desirable properties such as low cost and good processability. However, its low corrosion resistance, high brittleness, and flammability limit its applications in various industrial fields. To overcome these limitations, the incorporation of reinforcing particles into the resin has recently been proposed as an effective approach. In this study, bimetallic metal–organic frameworks (Fe/Al-BDC-NH?) were employed as reinforcing additives to investigate their effect on the physical–mechanical properties and corrosion resistance of unsaturated polyester resin. Owing to their hybrid structure, the MOF particles—with metallic sites enhancing mechanical performance and organic linkers enabling interfacial bonding with polymer chains—prevented particle sedimentation and improved the uniformity and adhesion of the polymer network. Structural and performance analyses of the composites were carried out using XRD, FT-IR, FE-SEM, DMA, and electrochemical impedance spectroscopy (EIS). The results revealed that the incorporation of a small amount of Fe/Al-MOF significantly increased the storage modulus, improved interfacial adhesion, enhanced electrochemical stability, and reduced the permeability of the resin in corrosive environments. Overall, the presence of bimetallic MOF particles remarkably improved the mechanical and anti-corrosion performance of the unsaturated polyester resin and offers a promising route for developing high-performance, corrosion-resistant coatings and composites for industrial applications.   

Classifying non-stationary signals, such as electroencephalogram (EEG) signals, is a major challenge in signal processing. Non-stationary signals are signals whose statistical properties, such as mean and variance, change over time, making them more difficult to analyze compared to stationary signals, where these properties remain constant. EEG signals, commonly used to study brain activity, are non-stationary, meaning their patterns change over time. Detecting abnormal brain activity, like epilepsy, which shows different patterns from normal activity, requires advanced techniques to classify these signals accurately. In this study, we explore how well a combination of Continuous Wavelet Transform (CWT) and pre-trained Convolutional Neural Networks (C  ) can classify non-stationary signals. As a case study, we use multi-channel neonatal EEG data, where each segment of the signal is labeled as either healthy or showing a seizure. A novel approach was developed in this research, where continuous wavelet transform representations from all EEG channels were combined into a single RGB image by stacking the continuous wavelet transform representations into the red, green, and blue channels. This creates a multivariable image that captures important time-frequency information from all EEG channels. These images were then classified using two advanced convolutional neural network models, ResNet and MobileNet, which were pre-trained on large datasets. Both models achieved high classification accuracy, with results above 80%, as well as high area under receiver operating characteristic curve scores, also above 80%. The findings show that combining continuous wavelet transform with convolutional neural networks is effective for recognizing patterns and classifying non-stationary signals. This work highlights the potential of this method, especially for medical applications like detecting seizures in newborns.

  In recent decades, the energy crisis has caused the concern of the international community, and numerous researches have been carried out in various scientific fields, and this concern has been partially resolved by using various solutions. On the other hand, architecture, as a discipline that is directly related to building design and construction, plays an important role in optimizing the energy consumption of buildings. One of the parts of the building that is very important to pay attention to in the design process is the window of the building, which is the border between the interior and exterior of the building, and the optimization of this part is very important in reducing the energy consumption of the entire building. This research tries to find the effect of window design on the energy consumption of a residential building. The energy consumption of the building is highly dependent on the thermal characteristics of its external shell. In the meantime, windows have a considerable effect on the thermal characteristics of the building shell due to their low thermal resistance in addition to the direct passage of radiant energy, so determining the optimal window-to-wall ratio in any climate is very important. The purpose of this research is to determine the design of the window suitable for the climate in order to reduce energy consumption. In the first step, the design of the building is designed based on internal regulations and resources and it is simulated in the DesignBuilder software, and then to enter the inputs and compare the effect of window design on the energy consumption pattern of the building, the inputs are designed in two groups of contract and 8 window models and with attention We have done the simulation to the groups and analyzed the obtained results, in the end, according to the inputs and the obtained results, we will choose the sample that has the best performance in energy consumption compared to other models and then we will strengthen its inputs. After carrying out this design and simulations in the desired climate, we were able to achieve the desired reduction in energy consumption by designing a vertical window model of 180 x 70 cm, observing the wall-to-window ratio and also strengthening the inputs such as increasing the thickness and layer of the external and internal walls. To achieve 10,000 to 20,000 kilowatt hours in the consumption of cooling energy, which is one of the dominant energy consumptions compared to other energies in a hot and dry climate.

Network Functions Virtualization of architecture means providing various network services without the need for hardware and not depending on it. Network Functions Virtualization is a new field in the network, with the help of which hardware devices can be implemented in virtual and software form. Network Functions Virtualization improves network functions such as: proxies, firewalls, load balancing, etc. In other words, using virtualization technology, this architecture is able to convert hardware devices into software modules known as virtual network functions and provide the desired service to the user. Providing the service requested by the user in the network is done by a sequence of virtual network functions, which are known as service functions chain. One of the main challenges in the development of network functions virtualization architecture is the allocation of resources to the requested network services in network infrastructures based on network functions virtualization, this challenge is called network function virtualization resource allocation problem. Therefore, in this research, the problem of allocating resources to virtual network functions in Network Functions Virtualization architecture has been solved by using mathematical programming techniques. In this research, a multi-objective mixed integer linear programming model is presented for the problem of resource allocation to virtual network functions. In this model, constraints related to the resource capacity of nodes and connections and delay constraints are desired. Also, the objective functions in this research are: maximum flows accepted in the network, reduction of resource costs of nodes (including: the number of CPU cores and the amount of memory), reduction capital costs, reduction operational costs and checking execution time. These constraints and objective functions are expressed precisely and explicitly by mathematical functions. The proposed mathematical model is implemented and solved with the Cplex solver. To evaluate the proposed mathematical model, several different topology are considered. The optimal cost is evaluated under changing parameters such as the length of service functions chain, the number of flows, the length of flows, the amount of resources of nodes, the number of nodes and the number of virtual network functions. And finally, the increase in execution time is checked by changing the number of nodes and the number of virtual network functions. The numerical results of this research show the effectiveness of the model in resources allocation to virtual network functions. Keywords: Network Functions Virtualization architecture, Virtualized Network Functions, Resource allocation, Mathematical programming, Mixed integer linear programming   

Research Aim: Tailings dams play a critical role in the mining industry, responsible for safely collecting and disposing of tailings while also conserving water and protecting the environment. However, the practice of constructing these structures using the tailings themselves, coupled with inadequate design and supervision, has resulted in a high number of tailings dam failures. This research aims to investigate the potential impact of tailings dam failures in terms of tailings output. The goal is to use this information to prevent future losses and protect against the negative consequences of tailings dam failures. Research method: This research focuses on the specific scenario of tailings dam failure near the support, where a nearby pond is present and the tailings are not prone to liquefaction. In order to conduct a thorough investigation, a large-scale pond was used to ensure that the results are not influenced by the dimensions of the dam reservoir. Additionally, a valve was incorporated into the laboratory model to simulate local failure scenarios. The tests were carried out at varying water levels and repeated three times to ensure the validity of the results. Findings: In this research, the bed erosion pattern and sediment transfer rate were studied in relation to the impact of increasing water levels in the tailings dam reservoir during a local failure near the abutment. Conclusion: The results of the study indicate that over time, as water and sediment are released from the dam reservoir, a pit forms in the sedimentary bed. This pit eventually develops into a submerged hydraulic jump. Additionally, it was observed that the length of the scour hole along the direction of the dam body is roughly twice that of the scour hole's length in the direction perpendicular to the dam body.   

تشخيص وسيله­­نقليه، يك بخش مهم در حمل و نقل و هوش مصنوعي است. وسايل­نقليه مي­توانند در قسمت­هاي مختلف تصاوير قرار بگيرند. پيشرفت هاي اخير در روش هاي تشخيص، منجر به طيف وسيعي از تكنيك هاي مختلف شده كه مي­تواند براي شناسايي و تشخيص وسايل­نقليه مورد استفاده قرار گيرد. يادگيري عميق، در سال‌هاي اخير است كه كاربردهاي قابل توجهي در روش­هاي تشخيص وسايل نقليه دارد. باتوجه به اهميت تشخيص وسيله­نقليه در سيستم­هاي حمل و نقل هوشمند، در اين پايان­نامه به بررسي و تشريح روش­هاي تشخيص وسايل­نقليه مختلف از تصاوير دوربين­هاي ترافيكي پرداخته­ و نيز از معماري قدرتمندي به نام يولو[1] براي تشخيص وسايل­نقليه روي ديتاست BVMMR استفاده مي­كنيم.­ به دليل تغييرپذيري در محيط‌هاي رانندگي، تشخيص خودرو ممكن است با مشكلات و چالش‌هاي متفاوتي مواجه شود، مثلا ظاهر وسايل­نقليه در اندازه، شكل و رنگ متفاوت، روشنايي خاص، شرايط آب و هوا و.. است. معماري، YOLOv5 شامل چهار بخش اصلي ورودي، backbone ، neck   و خروجي است. ترمينال ورودي عمدتاً شامل پيش پردازش داده ها است، از جمله افزايش داده موزاييك و پر كردن تطبيقي تصوير. شبكه backbone   عمدتاً از يك شبكه جزئي چند مرحله­اي (CSP) براي كاهش مقدار محاسبات و افزايش سرعت استنتاج و   ادغام هرمي فضايي (  ) براي استخراج feature map   با اندازه­هاي مختلف از ورودي تصوير با هدف بهبود دقت تشخيص با كانولوشن چندگانه و pooling استفاده مي­كند. در شبكه neck، از ساختارهاي هرمي ويژگي FPN و PAN استفاده مي­شود. با استفاده از معماري يولو نسخه پنجم[2] آموزش داده شده، موقعيت خودروها و نوع و دسته­ي آن­ها را نيز مشخص كرده­ايم و به   98.88% و دقت مجموع 99.73% و نيز سرعت 0.03 ثانيه براي تشخيص اشيا موجود در يك تصوير دست مي­يابيم كه خود گواهي بر مناسب بودن اين روش براي كاربردهاي بلادرنگ[3] مي­باشد. كلمات كليدي: تشخيص وسايل­نقليه، تشخيص اشيا، يولو، يادگيري عميق، سرعت و دقت بالا در تشخيص اشيا، شناسايي نوع و مدل وسايل نقليه [4]. [1]. you only look once (YOLO) [2] YOLOv5 [3] real-time

Unsaturated polyester resin is widely used in the composite industry. Addition of particles to unsaturated polyester resin improves thermal, physical-mechanical properties.The use of particles such as graphene, due to its special properties, is widely used in a variety of composites as a resisting and reinforcing agent. In this research, different particles such as graphene, graphene oxide and alumina in different weight percentages have been used to investigate the changes in thermal and physical-mechanical properties of polyunsaturated resin. According to studies, graphene, graphene oxide and alumina have had positive effects on the properties of resins.Thermal conductivity was obtained for samples with different weight percentages containing magnetic graphene oxide, magnetic graphene and alumina.The thermal conductivity of the samples in the cooked state and fully networked in different fluxes (1.024, 2.07, 3.024) watts has been investigated. It was observed that by adding a small amount of particles, the thermal conductivity increases compared to pure resin. It has also been shown that with the addition of magnetic oxide graphene, magnetic graphene and alumina, the thermal conductivity has also increased.The rate of increase in thermal conductivity varies depending on the amount of particles added to the resin. But the highest increase in thermal conductivity is related to magnetic graphene oxide 0.3%. The results obtained from DMA test showed that by adding particles to unsaturated polyester resin due to gravitational interactions between the resin surface functional group and OH functional group on the surface of magnetic graphene and magnetic graphene and thus creating a covalent bond. Strong modulus of storage increased compared to pure resin The first chapter introduces the structure of unsaturated polyester resin and the structure of the particles used and their properties.In the second chapter, according to previous studies, reports on mechanical and thermal properties are presented. Chapter 3 describes the synthesis of graphene oxide, how to convert graphene oxide to graphene, the synthesis of iron and how the particles are magnetized, as well as the tests performed. In the fourth chapter, the results of thermal test and DMA are analyzed in general.

  Unsaturated polyester resins have manyapplications in the composite industry. In thicker pieces made with this resin,a lot of heat is released in a short time during curing, inaddition, they have a low heat transfer coefficient. In thick sections, hightemperature differences between the center and the sample walls cause internalstresses. Therefore, adding particles with high thermal conductivity can helpto eliminate this defect. In this study, to investigate the changes in theproperties of unsaturated polyester resin containing Boehmite nanoparticles inweight percentages of 0.02, 0.05 and 0.3 and its hybrid with graphite andalumina particles in different weight percentages were used. The thermalconductivity of the samples made in heat fluxes of 1, 3 and 4 watts wasinvestigated. Also, DMA test was used to evaluate themechanical properties of the samples and the results were evaluated. Accordingto the results of thermal conductivity test, the highest rate of increase inthermal conductivity was obtained in the sample containing 0.05% by weight ofboehmite nanoparticles, which increased by 149% compared to neat resin. Also, inthe performed hybrid samples, the highest thermal conductivity coefficient isfirst related to boehmite / graphite hybrid, containing 0.025% by weightof boehmite / 0.025 graphite with thermal conductivity of 9.93 watts perkelvin and then for boehmite / alumina hybrid sample. Contains 0.05% by weightof boehmite / 0.5% by weight of alumina with a thermal conductivity of 7.45watts per kelvin, which have increased by 108% and 56%, respectively, comparedto neat resin. Also with you to the results obtained from the DMA test withincreasing the content of boehmite nanoparticles continuous storage modulusincreased. The highest increase in storage modulus was obtained in the 0.3% byweight sample of boehmite, which could be due to the stiffness and hardness ofboehmite nanoparticles. The OH groups at the particle surface can increase thestorage modulus relative to neat unsaturated polyester resin by creatinggravitational interactions with the OH, COOH and ester groups of alkyd chainsof unsaturated polyester resin. The use of boehmite / alumina particle hybridsalso led to better results than boehmite / graphite particle hybrids, due tothe fact that alumina particles have a smooth surface and spherical morphologythat reduce friction and improve mechanical properties in the system. The useof three-part boehmite / graphite / alumina hybrid in unsaturated polyesterresin increased heterogeneity and formed a non-uniform network in the systemcompared to neat resin.

Nowadays, people all around the world are suffering from many problems and diseases, one of the most important of that in recent years is covid-19, which causes many social, economy and other harms to human society. Therefore, treatment of this disease is one of the priorities of human beings today to return to normal living condition. One of the most significant steps and backgrounds for treatment of this disease and other similar diseases is nothing but diagnose this disease in accurate and fast methods that are useful for providing the ground for treatment, increasing knowledge about of that and preventing from spreading new strains. There are many different kinds of ways to diagnose this disease, which one of the most accurate and best is imaging and scan the lung and analyze it. On the other hand, artificial neural networks have many applications such as, processing and analyzing various data based on existing data sets from numbers to images, etc. one of these types of networks, is called convolutional neural networks, which are specifically used for analyzing, classification and processing various images. In this research, our goal is processing lung scan images by convolutional neural networks and receive the results in the output. Our results appear in the output according to predefined classifications based on the primary data sets, which include conid-19, normal and pneumonia. We can benefit from these results to diagnose and combat this disease. Because of the attractiveness and practicality of this field, before the present research, various researches have been done in this field. One of most important goals of this research is improve and optimize the convolutional networks by utilizing meta- heuristic algorithms in order to reduce the layers and network connections for easier and more cost-effective implementation while maintaining network speed and accuracy.

  In this study, the effects of Janus, hydrophilic and hydrophobic hollow graphene oxide (HO) particles on the thermal conductivity of binary polymer blends were investigated. The HO Janus (HOJ) micro- and nanoparticles were synthesized via buoyancy-induced desymmetrization process. The characteristics of the produced HO and HOJ micro- and nanoparticles were investigated using FTIR, TGA, EDX, FE-SEM, centrifuge and contact angle tests. Different PS/PMMA micro- and nanocomposite samples were prepared via solution mixing and subjected to the thermal conduction test. The results revealed that the presence of HO micro- and nanoparticles in either phase could increase the conduction coefficient of the PS/PMMA blend (K) though their simultaneous presence in both phases had significantly more impact on K. On the other hand, comparing the results of the blend samples with and without HOJ micro- and nanoparticle defined an outstanding improvement in the thermal conductivity of the polymer/polymer interface due to the presence of Janus particles. Also, the thermal stability of the samples decreased with the increment of their thermal conductivity and this effect was more significant in the case of the samples containing both HO and HOJ micro- and nanoparticles.

  In this thesis, the dynamic response of sandwich beams with carbon nanotube-reinforced surfaces and foam cores on a viscoelastic foundation under low-velocity vertical impact in the middle of the upper surface is investigated. In this research, an analytical model for nonlinear modeling is presented to calculate the amount of central Deflection and Contact Force. Beam is a sandwich panel with a nanotube composite surface and a foam core. Using the strain-displacement and stress-strain relationships and using the conditions of compatibility in between core and sheets, the displacement field of the core is determined. To model the impact force, the two degree of freedom model is used, and the Hamiltonian principle is used to determine the equations governing the problem. In order to validate the results of the analysis, the results of previous studies and numerical simulation with Abaqus software have been used. For the sandwich beam, the effect of the parameters of velocity and mass of impactor, modulus of elasticity of the core and thickness of the core on the Contact force and Central Deflection has been investigated. For beam sandwiches, increasing the mass and velocity of impactor , modulus of elasticity of the core increases the central Deflection and contact force, and also increasing the thickness of the core decreases the Central Deflection and contact force.

   In this study, janus nanosheets are synthesized using a spontaneous process at the oil/water interface based on the corporation of(3-Aminopropyl) triethoxysilane and tetraethyl orthosilicate molecules in the formation reaction of plate shape silica nanoparticles. The presence of acidic/alkali catalyst in the water phase increases the reaction rate at the proximity of the interface. Cooling down the system after a specific time causes the melted paraffin (oil phase) to solidify which completely stops the reaction and entraps the formed nanosheets at the interface. Considering the enrichment of the oil and waterphases with the reactants and catalyst, respectively, it is possible to reuse them   multiple times after harvesting the formed silica janus nanosheets. The amine groups at one side and the ethoxy groups on the other side of the silica janus nanosheets help them to serve perfectly as solid emulsifiers in pickering emulsions.

  gt; In this study, pure chitosan membranes and its matrix mixed with nanoparticles of graphene oxide quantum dots (fabricated in this study) crosslinked with glutaraldehyde were used to dehydrate ethanol. High hydrophilicity of chitosan resulted in acceptable dehydration function of chitosan membrane in ethanol dehydration process. Also, due to the hydrophilic functional groups and good dispersion of graphene oxide quantum dots in the chitosan network, the mixed matrix membranes performed better dehydration than the chitosan membrane. Matrix membrane mixed in optimal loading of quantum dots graphene oxide (1.5 wt%) flux0.811 kg/m2h and separation factor of 801 for dehydration of water / ethanol mixture (90/10) at 40°C Showed that compared to chitosan membrane, the flux base increased by 84% and the separation coefficient increased 7.6 times

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  در پايان­نامه حاضر جريان پايا و گذراي خون در مدل

The stability of the power system refers to the ability to maintain or return to the working point of the persistent state of the power system when it is disturbed. Turbulence may have a serious effect on the stability of the power system due to the stability of the small signal and the large signal. Increasing the consumption and diversity of consumers of electrical energy in power systems has led to an increase in the amount of energy transmitted in power systems. This increase has led to the interconnectedness of power systems to provide the required energy. In these interconnected systems, low frequency fluctuations can increase. These fluctuations affect the security and stability of large power systems and limit the current of power in the communication lines between the power sub-systems. Normally, synchronous generators maintain a constant vetting and a constant relative angle between stator and rotor coils, which is called synchronous generators in power systems. As soon as disturbances occur, the ability of the synchronum generator to balance the mechanical power of the turbine generator and the electrical power of the load to maintain stability is controlled. Traditionally, in the control of synchronous generators, a power system stabilizer (  ) produces an additional drive signal for the AVR excitation system to drive low frequency fluctuations. The goal is to create more mirant torque. On the other hand, installing    on all production units may lead to unwanted dynamic interactions. Matlab programming to combine probable load spreading analyses, linear modeling of multi-machine power system, small signal analysis and    optimization with pso metaheuristic algorithm for critical generator based on single-way stabilizers that have performance capability To have the best, it will be done.  

Today, electric vehicles are a suitable alternative to internal combustion vehicles due to their higher efficiency and far less environmental damage than internal combustion vehicles. But the factors that limit the use of these vehicles are issues such as the limitation of a city in having adequate communication routes and parking infrastructure and their charging stations. On the other hand, although the capacity of these vehicles alone is limited, a set of these electric vehicles at charging stations turns them into a unit that has the ability to appear in the role of a relatively large load for the network. Therefore, in order to make the best use of electricity distribution networks, it is necessary to operate and find the optimal location and capacity of charging stations for electric vehicles. In this regard, in this thesis, an attempt has been made to improve the IEEE 69_BUS TEST SYSTEM by determining the optimal location and capacity of electric vehicle charging stations based on the actual conditions of the power system.. For this purpose, uncertainty due to the number of vehicles in each charging station has been considered. The objective function in the present problem is multi-objective with the objectives of reducing losses (active and reactive) and reducing voltage deviation, which is optimized using the particle swarm algorithm and genetic algorithm in the MATLAB software platform and the results obtained from the location are compared.   

Abstract    In this study, in order to investigate the effect of iron additive on the heat transfer coefficient as well as the dynamic properties of unsaturated polyester resin, pure iron particles in powder form with a size of 45 microns have been used. For this purpose, in the continuation of the research, samples of unsaturated polyester resin containing iron particles with weight percentages of one, three, seven and fifteen weight percent were made and thermal conductivity measurement tests and dynamic properties measurement test (DMTA) were made. Also, to investigate the effect of modified iron particles on the properties of the composite, four samples of unsaturated polyester resin with similar weight percentages containing modified iron particles were tested.    Examination of the results of measuring the thermal conductivity of the samples, it was observed that in general, the addition of iron powder to the polyester resin improved by about 30 Percentage the thermal conductivity of the samples and also the addition of modified iron powder to the polyester resin by about 70 Percentage, its thermal conductivity has increased. Also, by observing the change curve of the thermal conductivity of the samples in different weight percentages, it was found that adding iron particles from one to three weight percent increased the thermal conductivity of the resin and adding more values ??up to fifteen wt %, the thermal conductivity. It has reduced. The reason for this could be the increase in the contact surface of iron particles with the resin and, of course, the increase in interfacial thermal resistance in samples above 3 % by weight. It should be noted that this trend is also repeated in the diagrams of samples containing modified iron particles.    Examination of the dynamic measurement test results showed that the amount of storage modulus increased with the addition of iron particles to the polyester resin and indicates that the unsaturated polyester resin containing iron particles has a higher strength during heating than pure polyester resin. Observation of the change curves of the storage modulus with temperature shows that this increase of the storage modulus did not have a constant trend with increasing the weight percentage of the samples, so that, for example, the storage modulus in the sample was 7 % by weight higher than other samples.    Keywords: Unsaturated polyester resin, Iron microparticles, Modified Iron Particle, Thermal conductivity, Physical and Mechanical Properties.   

Abstract You've definitely seen a variety of movies and animations in the cinema that make for spectacular special effects. These special effects are quite similar to the real world, and the movements of the characters are similar to those in the real world. With the advent of 3D motion capture technology and its move to computers, movies, computer games and especially animations have entered a new world. When movies started using 3D models, the goal was for them to create real motion and speed up the workflow so that the motion was not manually animated. The solution is to capture the movements of an actor in 3D and apply them to 3D computer models. The purpose of this technology is to allow us to create more effective and realistic characters and effects that we were not able to do before. The purpose of this dissertation is to design and implement an actor's face recording system using digital image processing techniques and machine learning algorithms, which is performed without the use of a specific hardware system. In this design, the camera is first captured by a computer webcam and then detected the face in the image and then the key points of the face are detected, then the two-dimensional points are identified. The camera parameters and two-dimensional mapping algorithms and their combination with facial feature points are mapped to the 3D coordinate space and a three-dimensional model of the face is created. This three-dimensional model is independent of head rotation and a particular face. Finally, the data obtained from the previous steps are transferred to a 3D virtual character in Maya 3D software by connecting to a TCP / IP socket.  

طراحي مدارات ديجيتالي ممريستوري براي محاسبات درون حافظه اي

  Incorporation nanofillers and preparation of nanocomposites is an efficient and promising for improvement of the polymer matrixes different properties. In this study, halloysite nanotubes due to their instruction properties, good compatibility and it’s cheapness will incorporate in PEBA matrix for improving their separation performance for CO2/CH4. It’s expected that higher improvement can be achieved by modification the halloysite nanotubes for PEBA based nanocomposites. Optimally it is expected that the halloysite based nanocomposite membranes separation will be passed over the Robson’s upper bound as a measure of the membranes proper separation performance. Additionally, other membranes properties are expected to become better.

  Today, nanotechnology research is underway at a fast pace, and day by day various applications of this technology in various areas of life are made clear to humans. In the case of nanofibres, this is the case, and is used as one of the most important nanotechnology products in many areas. Nano fibers have attracted particular attention in recent decades due to their mechanical, physical and chemical properties, such as the high surface area, the bond between the fibers, the microfacial space between the fibers, and high porosity. Among the many available techniques for the preparation of nanofibres, the electrospinning method is a simple and efficient method that, with precise control of the operating conditions and the characteristics of the polymer solution, results in the production of more uniform nanostructures. In this study, the application of polyacrylonitrile / Schiff base alumoxane nanofibers was tested by electrospining and applied to experimental studies of the effects of conductivity properties and the removal of heavy metals from aqueous solutions using polyacrylonitrile / Schiff base alumoxane nanofibers. First, the Schiff base alumoxane and 2-mercaptoacetic acid alumoxane were synthesized first, and Schiff base alumoxane nanoparticles were investigated in a nanofibre structure to remove heavy metals from aqueous solutions using Design expert7 software. The polyacrylonitrile/Schiff base alumoxane nanocomposites were highly efficient in removing 97% of lead and 94% cadmium ions from aqueous solutions. To test the conductivity of nanofibres, 2-mercaptoacetic acid alumoxane nanoparticles have also been used with palladium nanoparticles in nanofibers with copper electrolytes and silver electroplating. Based on the results, the highest conductivity of 316.45(s/m) is about 2.5% of the 2-mercapto-acetic acid alumoxane nanoparticle and 0.03% of palladium.  

  Unbonded fibre-reinforced elastomeric isolator (U-FREI) is a relatively new seismic base isolator in which fiber layers are used as reinforcement to replace steel shims as are normally used in conventional isolators. Further, the top and bottom end steel connector plates of conventional isolators are also removed. In general, the horizontal response of U-FREI is nonlinear because of reduction in contact area due to rollover deformation and reduction in shear modulus of isolator under large deformation. Thus, evaluation of horizontal stiffness of U-FREI is a challenging problem. The unbonded application leads to rollover deformation that results in advantages such as decreasing the demand tension stress between internal layers and increasing efficiency of the bearing as a seismic isolator. Most of the previous finite element analysis studies on FREIs only have addressed the simulation of the monotonic behavior of this type of isolators. In this thesis, the main objective is to simulate the laterl load-displacement hysteresis loops of U-FREIs. The combination of an effective hyperelastic behavioral model in large deformations with viscoelastic behavior, the hyper-viscoelastic model will be produced that has the ability to consider the time dependency in the finite element analysis of isolator. The hyperelastic parameters are evaluated by curve fitting of theoretical curve to three uniaxial tension test of elastomer dumble-shaped specimens. The viscoelastic behavior is simulated using the Prony Series, and its parameters are determined by using the Nelder-Mead simplex method optimization algorithm, and the cyclic experimental results. The results show that the use of viscoelastic material model in conjunction to hyper-elastic material model leads to the effective simulation of horizontal stiffness and hysteresis load-displacement loops of FREIs. As another component of this thesis, The lateral response of isolator under various vertical compression stresses is studied using the finite element model that is developed in this study. Results show that both the effective horizontal stiffness, and equivalent viscous damping are increased by increasing vertical compression stress.

Many systems have been used for this purpose including seismic base-isolators which are among the most important ones. In this method, structures move isolated from the ground by placing a flexible lateral structure between the structure and the foundation. Isolators have several types, the most common of which are Steel Reinforced Elastomeric Bearings (SREBs). These isolators are made of intermittent and bonded  elastomer layers and reinforced steel plates. Such isolators currently lack required economic justification for many conventional structures due to high expenses. In the last fifteen years, new elastomeric isolators have been developed called Fiber Reinforced Elastomeric Bearing (FREBs). In these isolators fiber reinforced layers are used, instead of heavy metal plates, to control the lateral strains of the elastomeric layers and to provide the necessary hardness along the vertical axis. In terms of bonding to the bearing, the isolators are categorized into three groups of "bonded", "partially bonded" and "unbonded". In unbonded mode, isolators lack the upper and lower steel plates, which reduce the expense and weights of isolators. In unbonded mode, no mechanical connection is made between bearing surfaces. In this situation, shear force is transmitted through friction at contact surface of the isolator with the bearing. These detachers undergo a unique deformation under rollover lateral displacement, which leads to the contact of the initial vertical surface of isolator with the upper and lower bearing of the isolator.   Following a rollover deformation, the effective lateral hardness of the isolator has been reduced further, which means increasing the vibration isolation period and, in fact, increasing the seismic isolation efficiency. In this research, the finite element analysis has been used to model the behavior of force- one-way lateral deformation of Fiber Reinforced Elastomeric Bearing (FREBs) isolators. The modeling of these isolators is conducted in 3D format using MCS MARC finite element software. Providing a 3D model of Fiber Reinforced Elastomeric Bearing isolator with material specifications and geometric dimensional scaled with real dimensions in finite element analysis allows us to avoid some costly and time-consuming laboratory studies. The focus of this thesis is on the modeling of three-dimensional finite elemental behavior of the Fiber Reinforced Elastomeric Bearing circular isolators. Research literature in this area has nothing to say. In the analysis, the effect of the geometry of the rubber layers on horizontal and vertical responses of elastomeric isolators was studied. The effect of thickness is investigated by (

  Low density polyethylene is one of the most expensive raw materials of plastic that isproduced in the high temperature and pressure and by free radical polymerization ofsupercritical ethylene. the very important problem that possible occurs for a tubular reactorproducing low density polyethylene, the fouling of polymer in the inner layer is formed.fouling may be defined as the accumulation of undesirable polymer at the reactor surface thatincrease the resistance to heat transmission and heat transfer rate of ethylene andpolyethylene mixed with coolant flow in jacket of reactor is reduced thus reduces the amountof production. the main priority of this thesis presents a model for the analysis of low densitypolyethylene production by taking fouling on the temperature of reactor inner walls. Themathematical model based on heat transfer equations formed, and to solve the equations of it,the matlab and trial and error method is used. Finally, the inlet and outlet water temperatureof the jacket, the temperature of the inner wall, the conversion of monomers to polymers, thethickness of fouling that formed in the walls and resistance of fouling was calculated for eachtube. Due to the two phase mixture of ethylene and polyethylene formed neare the inner wallfouling is formed. Energy balance on different parts of the reactor and its jacket, was used tocalculate heat transfer and wall temperature. by temperature and pressure near the wall andusing the SRK equation of state, equilibrium data are calculated. The results of this sectionindicate that almost all the flow is formed in the form of a single phase and only in the innerregion where the temperature is sufficiently low, the two phase flow is formed. Therefore inthe reactor pressure,the internal wall temperature is the main parameter for the production offouling. The results of model calculations and its use in optimization of model show thatcooling water temperature is more effective than its mass flow rate in quantity and productquality comparing these results with real data as well as validating the model used.

In this study, the graphene oxid/polyacrylonitrile nanofibers were prepared by electrospinning process. The effect of addition of graphene oxide on mechanical properties and removal of heavy metals from aqueous solution were investigated. Graphene oxide (GO) functionalized by tannic acid (GO-TA) in order to remove two kind of the most hazardous heavy metals from aqueous solution. A novel electrospun polyacrylonitrile / modified graphene oxide nanofibrous adsorbent was favorably developed by an electrospinning process. Mechanical property measurements show a 60% enhancement in tensile strength compared to pure polyacrylonitrile nanofibers. Also the nanocamposite is able to remove lead and cadmium from aqueous solution 97% and 94%, respectively.

ساخت واصلاح غشا نانو كامپوزيتي براي جداسازي   محلول اتانول /آب بافرايند تراوش تبخيري

In this study, natural convection flow in a micro enclosure is investigated using direct simulation Monte Carlo (DSMC) method. Argon molecules are used for gaseous medium. The sidewalls of the enclosure are subjected to various boundary conditions including adiabatic, constant temperature and symmetry where symmetry boundary condition simulates the flow in a long channel. The aspect ratio of the enclosure is set to AS = 2. The lower wall is heated to temperature TH and the upper wall is cooled to TL while the thermal ratio is preset to rT = TH/TL= 0.1. Similar problem for macro-scale channels which is known as Rayleigh-Benard problem is widely investigate. However, the micro enclosure problem which classified as rarefied flow is still under study. The Knudsen number is assumed in the range 0.001 ? Kn ? 0.12 and a wide range of 0.2 ? Fr ? 10000 is studied for Froud number. The results show that the thermal creep effect has an important role in formation of convective rolls in the enclosure. Unlike the channel flow where no vortex will appear in adequate low or high Froud numbers (based on Knudsen number), in enclosures we have vortexes in all Froud numbers at all Knudsen numbers due to thermal creep phenomenon.   It is shown that the heat transfer rate is the same for channel and enclosure at very small or very high Froud number. However, for mediate Froud numbers heat transfer rate decreases in enclosure as where the side walls resist against convective rolls. The bounds for the values of high or low Froud number depend on the Knudsen number. Finally, the ability of SBT collision scheme in simulation of Rayleigh-Benard convective flow is evaluated in this study. Comparing to NTC scheme which is conventional collision scheme for DSMC method, it is shown the SBT scheme is accurate enough to simulate the Rayleigh-Benard instability flow.

  AbstractIn this study, Boehmite nanoparticles are made by hydrothermal method and then functionalized with (3-Aminopropyl) triethoxysilane (APTES) by an inert solvent method (ALOOH@APTES) then ALOOH@APTES functionalized with salicylaldehyde (salicyl Schiff - Base functionalized boehmite or   ). The Boehmite functionalized Nano particles were used as a new Nano filler for preparation of nanocomposite membranes based on Polyether sulfone by phase inversion to remove heavy metal ions. FTIR، XRD، FE-SEM، AFM and CA analyses have been done to investigate the structure of nanoparticles and their effect on membrane properties, whey filtration and feed filtration including single solutions of copper sulfate, nickel sulfate, zinc sulfate and Plumbum nitrate in ion-free water at 100 ppm concentration. The results showed that Boehmite functionalized Nano particles in polyether sulfone membrane increased flux and improved removal for the heavy metal ions including nickel, Plumbum, zinc and copper than bare PES. Nanoparticle’ s desire to bond each other on membrane surface By creating interconnected networks make traps for trapping metal ions. By increasing the percentage of Nano particles in the casting solution, agglomeration of Nano particles causes reducing flux and increasing the percentage of removal. The results of the purification showed that membrane with 1Wt. % of    with 93/4% copper removal, 97/85% Plumbum removal, 98/1% Zinc removal, 11/1 Kg/m2h flux and 90% FRR is the best membrane for Cu, Pb and zinc removal. This membranes ability to remove nickel is better than other structured membranes but it isn’t desirable economically.

  جداسازي يكي از موارد مهم و پركاربرد در مهندسي شيمي مي باشد و غشاء مايع به عنوان يكي از پربازده ترين روش هاي جداسازي است كه در حدود 30 سال به طور جدي مورد مطالعه قرار گرفته است و باتوجه به پيشرفت فراوان آن در دو دهه­ي اخير، در صنايع مختلف استفاده شده است. هزينه­ي كم، نگهداري آسان، مصرف كم انرژي، آسان بودن افزايش مقياس كار با توجه به جمع و جور بودن وسايل فرآيند، بهره برداري آسان و طيف گسترده­ي مناطق عملياتي و استفاده از اين تكنيك در فرايندهاي همزمان استخراج و جداسازي از جمله مزاياي غشاء مايع در مقايسه با ساير فرآيندهاي جداسازي مي باشد. در اين تحقيق، سنتز مايع يوني پليمري انجام شد كه نتايج FTIR و 1H NMR و 13C NMR نشان­دهنده سنتز بهتر مايع يوني مي­باشد. همچنين در اين تحقيق از روش رويه پاسخ جهت مدلسازي راندمان حذف فنل استفاده شده است. پارامترهاي موثر در اين تحقيق شامل غلظت پليمر، غلظت حامل، غلظت امولسيفاير، غلظت فاز داخلي و زمان فرآيند در محدوده آزمايش در نظر گرفته شد. در نتايج حاصل، حداكثر راندمان حذف فنل در مدت زمان 25 دقيقه، غلظت پليمر2%، غلظت حامل2/0، غلظت امولسيفاير3%، غلظت فاز داخليN3/0 در حدود 37/99% بدست آمد. در اين تحقيق مشاهده شد كه تغيير در غلظت پليمر، غلظت امولسيفاير، غلظت فاز داخلي و غلظت حامل تغيير چشمگيري در راندمان كلي حذف فنل ايجاد مي­كند. در اين تحقيق، مدلسازي كه براي فرآيند حذف فنل با استفاده از روش رويه پاسخ و همچنين در بهينه­سازي كه براي اين روش بدست آمده، تطابق خوبي با داده­هاي تجربي داشت.

carbon dioxide / methane separation using nanocomposite membranes and modified nanoparticles

  This study investigates the effect of nanoclay on the optimization of curing cycle for unsaturated polyester resin of thin-sectioned composite parts. There is no study on curing cycle optimization for unsaturated polyester resin containing nanoclay. Hence, this study may provide insights into this optimization. On the other hand, curing cycle optimization is essential for GRP pipe industry since around 80% of composite pipes are produced by unsaturated polyester resin.Optimization is defined as to find the most appropriate solution in the output of an equation with minimum costs. Parameters including temperature, curing time, and curing degree are of highly significant for curing process. If the temperature is increased and not controlled during the curing process, the decomposition is rendered at the center of the composite part, and, thereby, curing is not completed within the composite part. Furthermore, if the curing time is not controlled, it would lead into high costs. Therefore, the cure cycle should be optimized allowing the curing process to complete in minimum time necessary for achieving an efficient production. In this study, using the genetic algorithm in the MATLAB software, an objective function is considered in order to optimize the curing cycle under defined conditions. In order to investigate the influence of nanoclay on optimization, two samples of unsaturated polyester resin were prepared. One of the samples included nanoclay weighting 1% of nanoclay. DSC measurement was carried out in order to investigate the curing synthetic. Given the influences of the individual parameters on the final curing cycle (weighting factor for the objective function), each samples (i.e., unsaturated polyester resin with and without nanoclay) has been examined in different states in which the presented curing cycle is optimized. Furthermore, two types of two- and three-step cycles have been used for each sample, and their merits and demerits have been discussed. The results of optimization shows that the amount of curing degree for the sample containing nanoclay has been increased in different states whereas the total time of this cure cycle has been decreased due to adding nanoclay to the system. In fact, nanoclay decreases the activation energy of reaction leading into reaction rate increase. It is also observed that nanoclay decreases the pre-exponential factor in the system resulting in reaction rate decrease. However, the amount of reaction rate is increased owning to the reason that the reduction of activation energy is more dominant than pre-exponential factor reduction. It is also concluded that curing temperature level for the thin composite part was decreased and controlled in the desired level. These findings are also observed for the sample containing nanpclay both in two- and three step cycles. Furthermore, it is also observed that third step cycle has presented within a short period of time in comparison to two-step cycle (cycle time). Generally, it could be concluded that curing state is improved due to the presence of nanoclay. In other words, nanoclay decreases the processing time and controlles the temperature level of produced part while its presence increases the final curing degree.    Key words: Nanoclay, Optimization of curing cycle, Unsaturated Polyester resin, Thin-sectioned composite parts, Genetic Algorithm