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Abstract It has been proved that developing a supercaviting flow over under-water projectiles has an important role on their drag reduction, so many of researchers have focused on this subject during recent decade. In this research, the geometrical characteristics of supercavitaties developed behind three different conical cavitators with conic angles of 30, 45 and 60 degrees are studied numerically and experimentally. The experiments were done in an open-loop water tunnel. The fluid flow velocity in the test section was between 27 to 38 m/s. Also the 3D multiphase fluid flow over the cavitators within the test section are modeled and analyzed numerically by solving the corresponding governing equations using finite volume method and mixture model. Good agreement was observed in comparison between the numerical and experimental results. Finally, effects of some important parameters .i.e. the cavitation index, inlet velocity and conic angle of the cavitators on the geometrical characteristics of the supercavities are discussed

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The effect of bubbles on frictional drag reduction has been studied experimentally using a vertical Taylor-Couette system. Air bubbles are injected into water flow at the bottom of the system. The flow between cylinders is a fully turbulent flow and Taylor vortices are formed in annulus gap. In these experiments, the variations range of rotational Reynolds number is 5000<=Re_w<=70000 . The variations of drag reduction in the presence of bubbles have been investigated by measuring the exerted torque on the inner cylinder. The results show that increasing rotational Reynolds number up to a certain amount leads to enhancement of bubbles effects on drag reduction while the effects are inversed for higher rotational Reynolds number. In this work, the acquired maximum drag reduction is about 5%.

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In this study a safe and smooth path planning containing the slightest risk is considered for an Unmanned Underwater Vehicle (UUV). To do so, three smooth and continues functions resembling the three dimensional path are introduced and then their parameters are optimized using the particle swarm optimization method to find the safest possible path. For each point in space a numeric value is considered as vulnerability and the objective function is the integral of the vulnerability over the path produced. This path forms controlling signals which through a TSK fuzzy controller, the UUV is guided. The new arrangement of the propulsion vehicle subsurface was modeled. Since for the design of the controller, the parameters of the Under Water Vehicle dynamic system not used, so the control system is robust with respect to parameter Uncertainties. In the last section three environments with different complexities are considered to illustrate the creating process’s performance of the path and it is concluded that this method demonstrates desired performance in the development of a safe and smooth path through a harmful environment and the design of an adequate controller.

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In order to assess the effect of turbulence models in prediction of flow structure with adverse pressure gradient, steady state Reynolds-averaged Navier-Stokes (RANS) equations in an annular axisymmetric diffuser are solved. After selection of the best turbulence model, an approach for the shape optimization of annular diffusers is presented. The goal in our optimization process is to maximize diffuser performance and, in this way, pressure recovery by optimizing the geometry. Our methodology is the optimization through wall contouring of a given two-dimensional diffuser length and area ratio. The developed algorithm uses the CFD software: Fluent for the hydrodynamic analysis and employs surrogate modeling and an expected improvement approach to optimization. The non-uniform rational basic splines (NURBS) are used to represent the shape of diffuser wall with two to ten design variables, respectively. In order to manage solution time, the Kriging surrogate model is employed to predict exact answers. The CFD software and the Kriging model have been combined for a fully automated operation using some special control commands on the Matlab platform. In order to seek a balance between local and global search, an adaptive sample criterion is employed. The optimal design exhibits a reasonable performance improvement compared with the reference design.

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In present paper, the effect of combined cooling, heating and power generation systems(CCHP) in the reduction of pollutants emission have been investigated and a hotel with 80 rooms in Zahedan have been selected as case study , also gas engine (With part-load operation) as prime mover for design CCHP system. In this work is assumed that sell electricity to grid is possible. At the first phase, optimization for access to maximum reduce Pollutants emission have been done, at the other phase, a multi-criteria function has been introduced and the optimization process, with Percentage of Relative Annual Benefit (PRAB) has been investigated and the results of these two phases, have been compared together. Results show, CCHP systems have a high effect in reduce environmental pollutants emission CO, CO2 and NOx, as the percent reduce pollutants emission is positive in an extensive range of nominal power of gas engine. Also results show for access to maximum reduce pollutants emissions , CO2, CO and NOx, annual benefit as multi-ceritria objective function a gas engine with nominal power 2050kW is needed; in this case in addition to the most annual benefit also have a good effect for reducing Pollutants emission. In the end, the effect of the number of prime mover as designing parameter assessed with increase from one into two and three numbers. Results show increasing prime mover, cause decrease Relative Annual Benefit and pollutants emission.

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The purpose of this paper is to find the optimum design of a typical gas turbine exhaust diffuser. In order to access the maximum overall static pressure recovery at the condition of swirling flow, an evolutionary algorithm is used. The optimization process is studied in three independent cases. Firstly, the optimization is done for a single profile of strut cover from hub to shroud. Secondly, two profiles are selected for the strut covers, one in the hub section and the other in the shroud section. Finally, the optimization process is done for the strut cover and diffuser channel geometries simultaneously. In order to produce the strut cover profiles the PARSEC parameterization method is used. The turbulent 3D flow is solved using computational fluid dynamic (CFD). The optimization process starts with the initial sampling of solution domain and subsequently the genetic algorithm (GA) is used to find the global optimum. The swirling flow at the turbine exit with the Reynolds number of 1.7 ×105 based on the hydraulic diameter of the diffuser inlet is optimized. All steps of GA and corresponding processes of model creation, mesh generation by TurboGrid, flow simulation by ANSYS CFX and goal function calculation for all members of each generation are coded in the MATLAB platform. As a result of the optimization, the pressure recovery coefficients increased 1.94%, 3.1% and 7.42% in the first, second and third cases of the optimization process respectively.

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In this paper, the energy absorption capacity of A356 aluminum foam reinforced by SiC particles under impact loading was studied. The foam was manufactured by direct foaming of melts with blowing agent CaCO3. The drop-weight impact testing machine was designed and fabricated. The dynamic load-cell circuit was designed and mounted on the impactor. The impact test was carried out using a hemispherical indenter with a velocity of 6.70 m/s on the foam specimens, and the load-time history data was obtained. The results were compared with the results reported by a piezoelectric force sensor and validated. The obtained impact response of A356/SiCp composite foam is stable, which represents a suitable design of the machine and its reliable output. This is emphasized by comparison of material behavior with the results of other researchers. The response includes three stages: an initial linear behavior, a plateau of load and failure of the foam. In plateau region, the plastic deformations can be tolerated by the foam at nearly constant load. The end of plateau region and beginning of the failure region occur at the moment when the rate of energy absorbed by the foam is decreasing. The values of plateau load and absorbed energy estimated from load-cell are 1.62 kN and 22.04 J respectively, which has a relative error of 1.8% and 7.7% in comparison with piezoelectric sensor. The value and percent of absorbed energy were obtained as 6.07 J, 6.58 J, 9.39 J and 27.5%, 29.9%, 42.6% for elastic, plateau and failure regions respectively.

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In this paper, the effect of heat treatment on the impact behavior of A356 aluminum alloy foams reinforced by SiC particles was studied and new results was generated. The foam was manufactured by direct foaming of melts with blowing agent CaCO3. A number of foam specimens were processed by T6 aging treatment. The drop-weight impact test with a hemispherical striker tip and velocity of 6.70 m/s was carried out on five untreated foam specimens and five heat-treated foam specimens, and the load versus time history data was obtained. The obtained impact response of A356/SiCp composite foam includes three stages: an elastic region, a plateau of load region and complete failure region. In plateau region, the plastic deformations can be tolerated by the foam at nearly constant load. The small amounts of standard deviation and coefficient of variation (for different parameters) obtained from statistical analysis of experimental data indicates the reliance on the results for quantitative analysis of them. The measurements showed that heat treating of Al foam results in an increase of the plateau load level and energy absorption capacity of the foam with 48.1% and 40.3% increase respectively. The length of plateau region is also decreased due to heat treatment. Regarding the significant improvement of mechanical properties of the foam and increase of its impact strength, the heat treatment after foam casting can be considered as a suitable approach for various industrial applications of aluminum foam.

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This research aims to determine whether the employment in Iran is affected by goods market based on post-Keynesians theory, or by labor market based on neoclassical theory. Using time series data on profit share, capital accumulation, unemployment rate and capacity utilization in a structural vector auto-regression (SVAR) model, this article evaluates the linkages among unemployment, income distribution and effective demand in Iran during 1967-2013. The results show that an increase in capital accumulation in goods market leads to significant decrease in unemployment rate. In other words, according to the post-Keynesians theory, unemployment in Iran is demand-induced. On the contrary, according to neoclassical theory, income redistribution in favor of profits (change of real wage in labor market) can reduce unemployment directly due to substitution between labor and capital or indirectly through increasing capital accumulation and/or rising capacity utilization. Therefore, in order to pass recession and to increase employment we can focus on goods market by increasing investment and income redistribution in favor of profits.

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One of the most important achievements of the Carnot was creating a limit for heat engines; this limitation is a criterion for measuring and comparing the performance of heat engines. Classical thermodynamics studies completely the equilibrium and reversible processes but transfer phenomena effects have been ignored, while in the real irreversible process, there are finite time processes and finite size systems. On the other hand, the close relationship between thermodynamics, fluid mechanic and heat transfer has caused thermodynamics to move from theoretical analysis toward a comprehensive and real analysis. Another point is that all the practical processes are irreversible. This study analyzed the irreversible combined cycle in finite time thermodynamics. The combined cycle studied consists two endoreversible cycles and three thermal sources. The irreversibility has occurred between the subsystems and the thermal sources and sink on the system boundaries. By solving algebraic equations, obtained dimensionless total power and efficiency were calculated based on dimensionless variables. The MATLAB programming code is used to solve algebraic equations. Finally, it is obtained that the thermal efficiency and dimensionless total power functions of the heat sources temperature, working fluid temperature and thermal conductance. Also, the effects of each dimensionless variable were investigated to the proportion of dimensionless total power and efficiency. In this study, the parameter study has been used for improving the irreversible combined cycle in the finite time thermodynamics. In addition, Optimization results have shown that the maximum dimensionless total power and thermal efficiency associated with it are 0.086102 and 47.81%, respectively.

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In this paper, performance analysis and optimization of a trigeneration system based on different thermodynamic criteria such as energy and exergy efficiency, power and dimensionless power have been investigated. The trigeneration system consists of three subsystems which including the solar subsystem, Kalina subsystem and lithium bromide-water absorption chiller subsystem. The proposed system uses solar energy generates power, cooling and domestic water heating. Power is introduced as a tool for understanding thermodynamic concepts of limited time. Dimensionless power is defined as the ratio of power to the product of total thermal conductivity and minimum temperature of the system. Dimensionless power can be used as a tool to understand the concepts of finite time thermodynamics. The exergy analysis has shown that the most exergy destruction is related to boiler. As a result, energy and exergy efficiencies, capital cost rates and dimensionless power are 17.77%, 18.82% and 9.63 dollars per hour, 0.01781 respectively. Sensitivity analysis has shown that increasing parameters such as ambient temperature, solar radiation, the dimensionless mass flow rate of the Kalina cycle, collector inlet temperature and pressure ratio of the Kalina cycle increase energy and exergy efficiencies. Also increasing pressure ratio the of Kalina Cycle, reducing the dimensionless mass flow rate of the Kalina cycle, the ambient temperature and collector inlet temperature has led to increased dimensional power. In addition, the optimization criteria such as energy efficiency, exergy efficiency, power and dimensional power have been compared. The results showed that power and dimensional power are the best thermodynamic optimization criteria.

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Optimizing energy consumption in industrial robots can reduce operating costs, improve performance, and extend the life of the robot during manufacturing. In recent years, with the progress of science and technology, new technologies such as cloud computing, big data, etc. have continuously emerged, and in particular, cloud computing technology has been used in robot research that improves the real-time performance of the designed robot. It can also provide high energy efficiency, low cost, etc. One of the most important aspects of this technology is its use in continuous monitoring of robots' performance, which can guarantee its optimal performance. In this research, first, an overview of the methods of reducing energy consumption is presented, and then the effectiveness of using edge computing technology in reducing energy is analyzed. For this purpose, the use of algorithms to optimize the performance of the robot, including its trajectory and working times, is controlled by the edge. The results of the simulations show that the energy consumption can be significantly reduced by using edge technology.