Garzan oil field is located at the south east of Turkey. It is a mature oil field and the reservoir is fractured carbonate reservoir. After producing about 1% original oil in place (OOIP) reservoir pressure started to decline. Waterflooding was started in order to support reservoir pressure and also to enhance oil production in 1960. Waterflooding improved the oil recovery but after years of flooding water breakthrough at the production wells was observed. This increased the water/oil ratio at the production wells. In order to enhance oil recovery again different techniques were investigated. Chemical enhanced oil recovery (EOR) methods are gaining attention all over the world for oil recovery. Surfactant injection is an effective way for interfacial tension (IFT) reduction and wettability reversal. In this study, 31 different types of chemicals were studied to specify the effects on oil production. This paper presents solubility of surfactants in brine, IFT and contact angle measurements, imbibition tests, and lastly core flooding experiments. Most of the chemicals were incompatible with Garzan formation water, which has high divalent ion concentration. In this case, the usage of 2-propanol as co-surfactant yielded successful results for stability of the selected chemical solutions. The results of the wettability test indicated that both tested cationic and anionic surfactants altered the wettability of the carbonate rock from oil-wet to intermediate-wet. The maximum oil recovery by imbibition test was reached when core was exposed 1-ethly ionic liquid after imbibition in formation water. Also, after core flooding test, it is concluded that considerable amount of oil can be recovered from Garzan reservoir by waterflooding alone if adverse effects of natural fractures could be eliminated. 相似文献
A method for the time suboptimal control of an industrial manipulator from an initial position and orientation to a final
position and orientation as it moves along a specified path is proposed. Nonlinear system equations that describe the manipulator
motion are linearized at each time step along the path. A method which gives the control inputs (joint angular velocities)
for time suboptimal control of the manipulator is developed. In the formulation, joint angular velocity and acceleration limitations
are also taken into consideration. A six degree of freedom elbow type manipulator is used in numerical examples to verify
the method developed. 相似文献
The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. So, vulnerability detection applications play a significant part in software development and maintenance. The ability of the forecasting techniques in vulnerability detection is still weak. Thus, one of the efficient defining features methods that have been used to determine the software vulnerabilities is the metaheuristic optimization methods. This paper proposes a novel software vulnerability prediction model based on using a deep learning method and SYMbiotic Genetic algorithm. We are first to apply Diploid Genetic algorithms with deep learning networks on software vulnerability prediction to the best of our knowledge. In this proposed method, a deep SYMbiotic-based genetic algorithm model (DNN-SYMbiotic GAs) is used by learning the phenotyping of dominant-features for software vulnerability prediction problems. The proposed method aimed at increasing the detection abilities of vulnerability patterns with vulnerable components in the software. Comprehensive experiments are conducted on several benchmark datasets; these datasets are taken from Drupal, Moodle, and PHPMyAdmin projects. The obtained results revealed that the proposed method (DNN-SYMbiotic GAs) enhanced vulnerability prediction, which reflects improving software quality prediction.
Today, the design of antenna arrays is very important in providing effective and efficient wireless communication. The purpose of antenna array synthesis is to obtain a radiation pattern with a low side lobe level (SLL) at a desired half power beam width in far-field. The amplitude and position values of the array elements can be optimized to obtain a radiation pattern with suppressed SLLs. In this paper, swarm-based metaheuristic algorithms including particle swarm optimization (PSO), artificial bee colony (ABC), mayfly algorithm (MA) and jellyfish search (JS) are compared to determine the optimal design of linear antenna arrays. Extensive experiments are conducted on designing 10-, 16-, 24- and 32-element linear arrays by determining the amplitude and positions. Experiments are repeated 30 times due to the random nature of swarm-based optimizers, and statistical results show that the performance of the novel algorithms, MA and JS, is better than that of the well-known PSO and ABC methods.
With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26?% enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.
Two phase-based nanocomposites consisting of dielectric barium titanate (BaTiO3 or BTO) and magnetic spinel ferrite Co0.5Ni0.5Nb0.06Fe1.94O4 (CNNFO) have been synthesized through solid state route. Series of (BaTiO3)1-x + (Co0.5Ni0.5Nb0.06Fe1.94O4)x nanocomposites with x content of 0.00, 0.25, 0.50, 0.75, and 1.00 were considered. The structure has been examined via X-rays diffraction (XRD) and indicated the occurrence of both perovskite BTO and spinel CNNFO phases in various nanocomposites. A phase transition from tetragonal BTO structure to cubic structure occurs with inclusion of CNNFO phase. The average crystallites size of BTO phase decreases, whereas that for the CNNFO phase increases with increasing x in various nanocomposites. The morphological observations revealed that the porosity is highly reduced, and the connectivity between grains is enhanced with increasing x content. The optical properties have been investigated by UV−vis diffuse reflectance spectroscopy. The deduced band gap energy (Eg) value is found to reduce with increasing the content of spinel ferrite phase. The magnetic as well as the dielectric properties were also investigated. The analysis showed that CNNFO ferrite phase greatly affects the magnetic properties and dielectric response of BTO material. The obtained findings can be useful to enhance the performances of magneto-dielectric composite-based systems. 相似文献
This paper presents a continuous adjoint approach for topology optimization of a coupled heat transfer and laminar fluid flow system under tangential thermal gradient (TTG) constraints. In this system, the thermal gradient along the boundary of multiple heat sources needs to be controlled. The design goals are to minimize the temperature of the domain, the fluid power dissipation and the TTG along the boundary of the heat sources. The first two goals are combined into a single cost function with weight variables. The TTG is constrained in one of two forms, an integral form where the integral of TTG squares along the boundaries of heat sources is constrained, or a point-wise form where TTG is constrained point-wise. A gradient-based approach is developed to obtain the optimized designs. A salient feature of our approach is the use of the continuous adjoint approach to derive gradients of both the cost function and two forms of TTG constraints. Numerical examples demonstrate that the continuous adjoint approach leads to successful topological optimization of the constrained thermal-fluid system. The use of TTG constraint is effective in lowering the TTG along the heat source boundaries. The resulting designs exhibit clear black/white contrast. 相似文献
The purpose of this paper is to present a method for developing new truss-like sandwich structures that exhibit desirable
mid-frequency vibratory characteristics. Specifically, a genetic algorithm optimization routine is used to determine candidate
small scale structural topologies, i.e. unit cells, that may be used in the design of larger scale periodic sandwich structures.
This multi-scale procedure is demonstrated starting with several unit cell topology optimization examples. From these examples
a specific optimal unit cell is selected for further investigation and integration into a periodic sandwich beam. Computational
results indicate that the proposed optimization approach is effective when used to design new structures for reduced mid-frequency
vibratory response. 相似文献
Voltage-current characteristics of YBCO superconductor was studied under magnetic field up to 0.4 T at different temperatures below Tc. The critical temperature decreases and the transition width broadens under magnetic field. V-I data below Tc were fitted to a power law expression V I(T,B) in which (T,B) is found to decrease with increase of magnetic field and temperature, gradually approaching unity as T approaches Tc, being independent of magnetic field. Similarly, (T,B) approaches unity as magnetic field increases being independent of temperature. 相似文献