This study focuses on improving the safety of embankment dams by considering the effects of vibration due to powerhouse operation on the dam body. The study contains two main parts. In the first part, ANSYS-CFX is used to create the three-dimensional (3D) Finite Volume (FV) model of one vertical Francis turbine unit. The 3D model is run by considering various reservoir conditions and the dimensions of units. The Re-Normalization Group (RNG) k-ε turbulence model is employed, and the physical properties of water and the flow characteristics are defined in the turbine model. In the second phases, a 3D finite element (FE) numerical model for a rock-fill dam is created by using ANSYS®, considering the dam connection with its powerhouse represented by four vertical Francis turbines, foundation, and the upstream reservoir. Changing the upstream water table minimum and maximum water levels, standers earth gravity, fluid-solid interface, hydrostatic pressure, and the soil properties are considered. The dam model runs to cover all possibilities for turbines operating in accordance with the reservoir discharge ranges. In order to minimize stresses in the dam body and increase dam safety, this study optimizes the turbine operating system by integrating turbine and dam models.
According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through
... Show MoreIn this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application
This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1) is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to
... Show MoreThis work presents the construction of a test apparatus for air-conditioning application that is flexible in changing a scaled down adsorbent bed modules. To improve the heat and mass transfer performance of the adsorbent bed, a finned-tube of the adsorbent bed heat exchanger was used. The results show that the specific cooling power (SCP) and the coefficient of performance (COP) are 163 W/kg and 0.16, respectively, when the cycle time is 40 min, the hot water temperature is 90oC, the cooling water temperature is 30oC and the evaporative water temperature is 11.4oC.
The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrien
... Show MoreThe increasing Global Competitive and the continuous improvement in information technology has led the way to the development of the modern systems and using modern techniques. One of these techniques is benchmarking style and Total Quality Management all of them are used to improve the production process and target rid from the losts on the other side.
The Benchmarking style has become a very important for all the industrial systems and the serving systems as well. And an instrument to improve their performance specially those which are suffering from the highness of the costs or waste in time on the other side.
This study aims to depend on virtual Benchmarking style in the eval
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