Mesh Refinement: Aiding Research in Synthetic Jet Actuation By: Brian Cowley.

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Presentation transcript:

Mesh Refinement: Aiding Research in Synthetic Jet Actuation By: Brian Cowley

Background – Definition and Implementation: Synthetic Jet flow actuation is a method for controlling airflow over airplane wings Implementation: Electrodes over leading edge High frequency pulse from boot-like actuators Standard Boot Actuator: Internal Structure:

Background – Benefits and Results: Benefits: Reduced boundary layer thickness (Translates to reduction in drag) Delays the onset of boundary layer separation at high angles of attack Helps flow re-attach after post stalled conditions Results: Airplanes would require less fuel to fly the same distance An increased flight envelope Standard flow at moderate angle of attack: Flow with synthetic jet at moderate angle of attack: tu.be

Current Research at Embry-Riddle – Overview: Objective: test current hypotheses 1:Generating an optimized Synthetic Jet Flow will result in a re-attached boundary layer in posed stalled conditions 2:Synthetic Jet flow will reduce boundary layer height in attached flow conditions 3:There exists a parameter space (set of flight conditions) that will optimize the results of synthetic jet flow

Current Research at Embry-Riddle – Methods: Currently use CFD to model synthetic jet flow In house made software written in FORTRAN95 Uses a Direct Navier-Stokes solver with a forward time, central space solving scheme Geometry is fixed to a NACCA 0012 Current software allows the user to: Specify mesh size and spacing Reynolds Number Angle of attack Boundary conditions Synthetic jet strength and location

Research Limitations – The Problem: Models that are needed to effectively test the hypotheses need to be scaled up compared to previous models In terms of both Reynolds number and mesh size Allow more detail to be shown in boundary layer-jet interaction Allow the study of larger wings (Such as a Boeing 747) The problem: current software cannot effectively scale current models to test larger wings or more detailed problems Result of time it takes to run on large meshes or at high Reynolds numbers Result of computational complexity

Research Limitations – Complexity: For Example: A mesh the research group considers large is 800 X 1600 Number of nodes = 1.28 million Number of time steps = 1.2 million Average iterations to converge per time step = 4 Calculations = 6.14 X Computation time = 1.5 days The example mesh of realistic quality is 4.5 million nodes Example Mesh:

Research Limitations – Complexity: Clearly moving up the complexity of the problem leads to unrealistic time to collect data – So what do we do? We define a quantity known as the “Residual” LHS – RHS = 0 Result gives us the error within the calculation at that point between each time step We are held back from using a courser mesh for a problem because of the errors that are associated with it Lead to inaccurate or flat out wrong results

Current Project – Beginning Investigation: I wanted to simply plot the residuals to see where they were Residuals migrate to the right Appear directly above the leading edge of airfoil Beginning question: What if they could be contained? Residual Field for 200 X 400 model:

Solution Write an add on (new sub-routines) to the existing code eliminate, or reduce the residuals within models Allows them to be scaled as desired

Current Project – Code Development Part 1: First subroutine searches for the highest residual value Draws a box around the region to user specified dimensions Activates after user specified time steps

Current Project – Code Development Part 2: Subroutine two increases mesh density within the region Leads to high precision calculation within region Eliminates residual between time steps Original Mesh Refined Mesh Note: Blue Nodes: Original, contain original values Black Nodes: Re-Meshed nodes -Edge nodes are weighted average of adjacent values -Interior initially calculated by solver

Current Project – Code Development Part 3: The next subroutines run values through the DNS solver Each routine is defined for the new mesh size The solver calculates to a user defined tolerance within this configuration

Current Project – Code Development Part 4: Last subroutine places processed data into main program Does this with respect to original position Program then continues to compute the result Result of Refined mesh Region within Main Program

Progress: This is an ongoing project: Each subroutine within the new code has been added Debugging is current stage of development

Next Steps: Finish debugging the code Run trial runs with the new code VS. original Done to validate code Use the new version of the code to test hypotheses

Project Goals: Reduce the time required to compute the needed data Enable the ability to acquire higher quality data within a timely manor Both goals to be met on student’s personal computers

Questions?