The Modeling of Cross Flow Runner With Computational Fluid Dynamics on Microhydro Tube

. The Model of Fluid Dynamics Computation (CFD) aims to obtain cross-tubine flow in microhydro tubes. The parameters used to determine the cross flow turbine power are the blade angle, the number of cross runner blades and the head tube as the production house. Computational Fluid Dynamics (CFD) is software that can load integral and partial equations into discrete algebraic equations (addition, multiplication, multiplication and division) that can be used with the help of computers to find solutions for sources and times. In the era of technology, the development of the Computational Fluid Dynamics (CFD) program is very fast making this method a trend in various fields of industry that utilizes a comparison of pure experimental data and pure theory. The study of turbine cross flow power on microhydro tubes shows 1213 Watt power on the parameters of blade number 16, blade angle of 15 0 and 20 0 at head 4 meters.


Introduction
Microhydro power plant with turbine cross flow becomes attractive because its construction is simple, easy, low maintenance costs, is a clean and environmentally friendly energy source, and has a good future development. Turbine cross flow construction consists of two parts namely nozzle and runner [9]. Turbine Cross flow was originally designed and patented by Australian Engineers in 1903. Then the results of his work were further developed by Donat Banki which was presented in a series of publications in 1917 and 1919. Banki work produce operating theory and experimental results about flow which show an efficiency of 80% [7]. Theoretical and experimental research on flow characteristics and cross flow turbine performance to produce high turbine power is assisted by the Computational Fluid dynamics (CFD) method [1]. The power generated by the turbine is an important factor in a micro-hydro power plant with a tube as a power house in determining production efficiency. Computational Fluid dynamics (CFD) provides an accurate analysis to be able to produce efficient power in turbine cross flow [8].The principles are used with three basic laws, namely the law of conservation of time, Newton's second law/conservation law of momentum and energy conservation law.These three laws are expressed in mathematical equations which in the form of integral or differential equations become discrete algebraic equations (addition, subtraction, multiplication and division) that are possible to be worked on by computer programs [2]. This method is also becoming a trend especially the special new renewable energy sector it is related to fluid / fluid analysis examples for gas turbines, wind turbines and water turbines.
The development of this analysis is supported by the results of experimental tests using computational fluid dynamics as a tool for modeling, estimating, and analyzing turbine crosflow behavior under different operating conditions, with Computational Fluid dynamics (CFD) software using ANSYS-Fluent 18.0 [8]. Computational fluid dynamics to determine the turbine power by treating different models with blade number parameters, blade runner angle, and generator head [10].

Method
Microhydro Installation Analysis with a tube as a powerhouse uses water energy as an energy source to drive a turbine runner. It is possible to set geometric parameters that affect turbine power is number of blades, blade runner angle and generator head [5]. The construction of the power plant as follows:

Components of Microhydro Tube Generators
-Intake serves to direct water into the tube made of PVC pipe / permanent construction.
-Tube (Calm) functions to store water that is while before being discharged through a machine (turbine) as a generator house (tube). -Overflow channel functions to channel water into the generator house (tube) in order to maintain the stability of the electricity gap.
-The engine (turbine) as the generator is chosen as the flow type because it has suitable characteristics (discharge, head and power house). -Exhaust channel, this channel serves to direct the water that comes out of the turbine so as not to damage the power plant location.

Theory of Computational Fluid Dynamics (CFD)
The Computational Fluid dynamics (CFD) method is an art of making changes in the equation of fluid dynamics in derivative and integral forms into discrete algebraic forms (addition, subtraction, multiplication and division) that can be solved by computer programs. The development of Computational Fluid dynamics (CFD) technology can be utilized as a complement to pure theoretical and experimental data. Computational Fluid dynamics (CFD) theory can also function as a research tool that is becoming a trend in the world of engineering design because of its flexibility and ease in finding trends in relation to one parameter to another parameter. There are three governing equations in fluid dynamics, namely continuity equations, equations, momentum and energy equations as follows [4]: Equation for continuity of integral forms, The solution of partial differential analytical equations results in the continuous dependent form dependent variable expression across all domains. Conversely, numerical equation solutions can only give values at discrete points in a domain, also called grid points.

Geometry
In the industrial world Computational Fluid dynamics (CFD) software is developing rapidly and rapidly not only for strength analysis and structural deflection but is often also carried out in determining the optimal configuration based on fluid interactions with turbines. Computational Fluid dynamics (CFD is very popular in solving problems related to mechanics complicated and complex fluid [2]. So in the geometry using a simulation that represents the fluid model (negative) of the rotor and fluid volute. This model is divided into two parts, namely the stator portion of the stationary part and the rotating part of the rotor to facilitate the movement of the rotor:

Meshing / Grinding
Meshing is a process of discretization (addition, subtraction, multiplication and division of fluid domains which continuously become discrete computational domains so that fluid flow equations can be completed / worked on and produce a solution by numerical methods [3]. The following is the result of meshing / grinding of simulated models below this: The following are the computational settings used in the simulation to produce solutions to the problems of fluid mechanics in turbine crossflows in microhydro tube plants [6]. This volume of fluid model is used for two fluids which have different density as in water and air. This simulation presents a fluid model with the following settings: -Rotor: in this domain use the following settings: ( Water material, rotating, gravity direction -9.81 towards z, reference density = 1000 kg / m3 and domain initialization patch, with water volume fraction = 1) -Static: in this domain some settings are used as follows: ( Water material, static, gravity direction -9.81 towards z, reference density = 1000 kg / m3 and domain initialization patch, with air volume fraction = 1) -Inlet Total pressure (stable) = Adjust head : ( Input is the inlet pressure that represents the head pressure used on the generator in this case = 4 m ) -Out Put = 0 Pa : (At the outlet for settings as the reservoir of the flow so that it is expected that all the flow out of the outlet.) -Number of Iterations: 1000 : ( The number of iterations is based on a residual graph and the unchanged flow distribution of additional iterations (depending on converging conditions) this process is done every 1000 iterations repeatedly).
Simulations can be taken to produce data in the form of volume distribution fraction of water that presents the flow patterns that occur in the turbine.

Data on Results of Conversation
Measurement and analysis of data to characterize turbine behavior with 15 0 and 20 0 blade angle parameters, number of blade runners and tube generator head. So that it will produce charts and curves as follows: