# Presentation: 583600

## Successes and Challenges for Flow Control Simulations (Invited)

- Christopher L. Rumsey
- NASA Langley Research Center
- Hampton, VA

- AIAA  2008-4311
- 4th AIAA Flow Control Conference, Seattle, WA

## Outline

- Introduction
- Perspectives on 3 workshop cases
- Synthetic Jet into Quiescent Air
- Synthetic Jet in a Crossflow
- Flow over a Hump Model
- For each, summary given and remaining challenges identified

## Introduction

- Synthetic jets have many practical applications
- Jet vectoring, separation control, enhanced mixing, skin friction reduction, virtual aeroshaping
- How accurate is CFD for predicting these types of unsteady flows?
- CFDVAL2004 workshop was held in March 2004 and addressed this question
- (_[http://cfdval2004.larc.nasa.gov](http://cfdval2004.larc.nasa.gov/)_)
- Special issue of AIAA Journal (Vol 44, No 2, 2006) had summary paper and 6 CFD papers
- Many other papers have appeared as well (both AIAA conference papers as well as in journals)
- Purpose of this paper: Summarize progress and answer the questions
- Has CFD gotten better at computing these types of flows?
- Are more advanced methodologies being applied?
- What challenges remain?

## Introduction, cont’d

- CFDVAL2004 workshop
- Case 1: Synthetic jet into quiescent air
- Case 2: Synthetic jet in a crossflow
- Case 3: Flow over a Hump model
- Three conditions: no-flow-control, steady suction, oscillatory control
- In ERCOFTAC database (Classic Collection), Case C.83
- Overall summary from AIAA Journal, Vol 44 No 2, 2006
- CFD only able to qualitatively predict synthetic jet flow physics
- In part due to uncertainty in how to model the BCs
- Need identified: building-block experiments to focus on obtaining extremely detailed data at and near slot/orifice exits
- A plug for workshops of this type:
- Many people computing same problems
- Improves synergy between CFDers and experimentalists
- Easier to discern trends & deficiencies
- “Outliers” easier to recognize

## Turbulent shear stressesfrom CFDVAL2004 workshop, Case 3, separated region, SA model

- Turbulent shear stressesfrom CFDVAL2004 workshop, Case 3, separated region, SA model

## Description of methodologies

- Reduced-order or low-order
- Simplifications to RANS/URANS
- E.g., lumped element models, quasi-one-D models, proper orthogonal decomposition (POD) models
- Less expensive than RANS/URANS
- Useful to find viable design from among hundreds of possibilities

## Description of methodologies

- RANS/URANS
- Both solve Reynolds-averaged equations (RANS is steady-state, URANS is time-accurate)

- - Then equations written in terms of        (long-time-average or phase-average)
- - End up with unclosed term(s), turbulent stress:
- - Modeled with turbulence model (e.g., 1-eqn, 2-eqn, EASM, RSM): models the MEAN EFFECTS of turbulent fluctuations
- - RANS/URANS assumed to be valid if time scale of turbulent fluctuations << physical time step << important global unsteady time scales in the flow

- (incompressible)

## Description of methodologies

- LES & blended RANS/LES
- Derived by applying low-pass filter to N-S eqns
- Idea is to resolve larger turbulent eddies, model smaller ones
- Resulting filtered eqns are functionally identical to RANS equations: again unclosed terms        must be modeled
- LES subgrid-scale (SGS) models are different from RANS turbulence models in that they include filter (typically dependent on local grid size)
- Blended RANS/LES works by blending the SGS model and turbulence model
- Sometimes problems in blending region (e.g., if in log-layer)

## Description of methodologies

- LES & blended RANS/LES, cont’d
- LES is difficult to analyze - easily complicated by numerics
- Excessive numerical dissipation affects ability to resolve features
- Numerical dissipation can behave like SGS model
- This fact taken advantage of in implicit LES (ILES)
- No SGS model used
- Inherent numerical dissipation provides filtering needed at smallest scales
- Theoretically justified in MILES (specific numerical methods employed)

## Description of methodologies

- DNS
- Direct simulation of N-S equations
- By implication & standard definition: requires that all spatial and temporal scales are resolved down to Kolmogorov scales
- Impossible at high Re on today’s computers
- More common: “coarse-grid” DNS - finest scales not resolved
- What is the difference between ILES and “coarse-grid” DNS?
- Equations identical
- No SGS model - numerical dissipation “models” the effects of smallest eddies & prevents artificial build-up of energy at smallest scales
- Numerics can be similar

## Representation of different methods in Fourier space

## Case 1:Synthetic jet into quiescent air

- Case 1:Synthetic jet into quiescent air

## Time-averaged centerline velocityfrom original CFDVAL2004 workshop 

- Time-averaged centerline velocityfrom original CFDVAL2004 workshop

- (PIV = Particle Image Velocimetry)

## Analysis

- Workshop CFD results “all over the map”
- Turb models and slot BCs had big impact
- Experiment PIV & hotwire different near slot in original experiment
- New experiment (post-workshop) - at slightly different conditions
- New experiment PIV & Laser Doppler Velocimetry (LDV) agreed well
- Hotwire not accurate near slot

## Velocity measured near slot exit

- Original data

- Newer data

## New experiment

- - Slot end effects:
- 	-intrude toward center, cause axis-switching phenomenon (vortex structures deform & orient long axis perpendicular to initial orientation)
- 	-“2-D” approximation likely poor above 8h or so

## Published results for case 1

- _Yamaleev & Carpenter _- low-order (1-D Euler) method for internal cavity coupled to laminar flow N-S in field
- _Vatsa & Turkel _- URANS with FFT curve fitting of internal slot BC to match flow at exit
- _Zhang & Wang _- URANS with similar FFT internal BC
- _Park et al _- URANS with internal BC curve fit to data
- _Carpy & Manceau _- URANS with no cavity; exp data at exit used for BC
- _Xia & Qin _- DES with predictive moving wall internal BC
- _Cui & Agarwal _- DES & SST-LES; simple sinusoidal internal BC to try to match PIV & hotwire
- _Kotapati et al _- N-S; simple sinusoidal internal BC to try to match PIV

## Subsequent CFD improvementsexample from Vatsa & Turkel

- Subsequent CFD improvementsexample from Vatsa & Turkel

- - Key: better matching experimental conditions at exit (FFT used to help match temporal variations)

## Subsequent CFD improvementsexample from Carpy & Manceau

- Subsequent CFD improvementsexample from Carpy & Manceau

- - Used PIV experimental conditions at exit
-  RSM much better than k-epsilon model
-  time lag between strain & anisotropy tensors (yielding negative production) cannot be captured by E.V. models

## Subsequent CFD improvementsXia & Qin

- Subsequent CFD improvementsXia & Qin

- - Drum-like motion simulated with moving grid on 2-D section shape (predictive)
- - 3-D DES computations with periodic BCs

## Subsequent CFD improvementsexample from Kotapati et al

- Subsequent CFD improvementsexample from Kotapati et al

- - Full simulation of turbulent structures in near-field (periodic BCs)

## Summary - case 1

- What’s new
- Recognition of importance of end effects
- Development/recognition of techniques to better match BCs at exit
- Internal cavity shape itself not a major factor
- But you need exp data at exit to match
- Predictive modeling of membrane motion used 2-D version of actual cavity shape
- DES and N-S simulations (as well as URANS) have been successful in the near-field

## Summary - case 1

- Remaining challenges
- Unclear whether URANS is adequate & which models are best
- SA & SST appear reasonable, but Carpy & Manceau suggest linear models miss key physics
- When is simulation (e.g., DES, N-S) necessary?
- Capturing 3-D end effects (and physics further into the field) possible?
- How well will a predictive moving-grid BC for 3-D diaphragm shape work?

## Case 2:Synthetic jet in a crossflow

- Case 2:Synthetic jet in a crossflow

## Published results for case 2

- _Iaccarino et al _- URANS (v2f and k-eps models) without & with plenum
- _Biedron et al _- URANS (SA model) with plenum
- _Rumsey et al _- URANS (SA, SST, EASM models) with plenum
- _Cui & Agarwal _- DES and URANS (SST model) with plenum
- _Xia & Qin _- DES with moving-wall BC in plenum
- _Dandois et al _- LES (mixed scale model) and URANS (SST model) with plenum

## Sample CFD results over orificeusing simple periodic BCs in plenum (Rumsey)

- Sample CFD results over orificeusing simple periodic BCs in plenum (Rumsey)

- Dip likely caused by large
- cross-flow component in exp,
- not modeled in CFD

## Unexplained asymmetry in expabove center of orifice

- Unexplained asymmetry in expabove center of orifice

## Sample CFD resultsu-velocity 1D downstream (Dandois et al)

- Sample CFD resultsu-velocity 1D downstream (Dandois et al)

## Sample CFD resultsturbulent normal and shear stresses 1D downstream (Dandois et al)

- Sample CFD resultsturbulent normal and shear stresses 1D downstream (Dandois et al)

## Summary - case 2

- What’s new
- LES (with appropriate upstream inflow BCs) better than URANS at predicting turbulent quantities
- Earlier: recognition at CFDVAL2004 workshop that URANS & LES could both predict mean flow quantities reasonably well
- Including orifice important for capturing complex flowfield in its immediate vicinity
- Simple top-hat wall BCs miss physics
- Dandois demonstrated potential effects of large periodic cross-flow velocity component in experiment
- Xia & Qin used moving wall BC in plenum
- Results appeared to be similar to usual simple periodic transpiration BC

## Summary - case 2

- Remaining challenges
- Can a predictive (moving wall) BC in plenum be used to achieve closer agreement with velocities at orifice exit?
- In light of unexplained large v-velocity component in workshop experiment, revisit experiment or establish new benchmark dataset

## Case 3:Flow over a hump model

- Case 3:Flow over a hump model

- - Based on earlier experiment by Seifert & Pack (AIAA J, Vol. 40, No. 7, 2002, pp. 1363-1372)
- - This case also used in subsequent 11th & 12th ERCOFTAC/IAHR Workshops on Refined Turbulence Modelling

## Hump model – 3 conditions

## Hump configuration

- Blockage effects due to endplates must be accounted for in CFD
- (affects surface Cp)

## Results from workshopreattachment location

- Results from workshopreattachment location

## Phase-averaged Cp

## Long-time-average Cposcillatory case

- Long-time-average Cposcillatory case

## RANS/URANS problem identified

- Eddy viscosity underpredicted in separated shear layer region
- Too little mixing
- Too late a reattachment downstream
- Occurs for baseline, steady suction, or oscillatory control
- Similar problem seen in a separate 2-D hill workshop case
- Hump case has been computed by no less than 16 different groups

## Movie (turbulent shear stress)example RANS (SA compared with experiment)

- Movie (turbulent shear stress)example RANS (SA compared with experiment)

## Long-time-average streamlinesexample RANS

- Long-time-average streamlinesexample RANS

## Numerical experimenteffect of arbitrarily doubling eddy viscosity in separated region, SA

- Numerical experimenteffect of arbitrarily doubling eddy viscosity in separated region, SA

## RANS/URANS results for case 3

- _Iaccarino et al_
- _Capizzano et al _- used Neumann surface BCs
- _Cui & Agarwal _
- _Balakumar_ - employed higher order WENO
- _Morgan et al _- employed higher order compact scheme
- _Bettini & Cravero _- commercial package
- _He et al _- commercial package; looked at plasma control
- k-epsilon attached earlier
- but because it separated later, not due to better physics!
- _Madugundi et al _- commercial package
- _Rumsey et al _- included parametric studies at other conditions from the experiment

## Blended RANS-LES, LES, & DNS

- _Israel et al _- EASM combined with FSM
- _Hiller & Seitz _- SAS model
- _Krishnan et al_ - DES
- Also RANS with many variants, including 3-D with endplates
- Helped discover blockage issues
- _Biswas_ - LES (dynamic model with KE eqn)
- _Saric et al _- LES (Smagorinsky - const Cs), DES, and RANS
- _Morgan et al _- ILES
- _You et al _- LES (dynamic Smagorinsky)
- _Franck & Colonius _- LES (both types Smag) & ILES
- _Postl & Fasel _- “coarse-grid” DNS

## RANS parametric studysteady suction, from Rumsey & Greenblatt

- RANS parametric studysteady suction, from Rumsey & Greenblatt

- - RANS consistently overpredicted bubble length, as increased suction lessened its size

## RANS parametric studysteady suction, from Rumsey & Greenblatt

- RANS parametric studysteady suction, from Rumsey & Greenblatt

## RANS parametric studysteady suction, from Rumsey & Greenblatt

- RANS parametric studysteady suction, from Rumsey & Greenblatt

## RANS parametric studysteady suction, from Rumsey & Greenblatt

- RANS parametric studysteady suction, from Rumsey & Greenblatt

- - RANS did fair job predicting suction trends (bubble-length slope low)
- - URANS Results for oscillatory control not as favorable

## Subsequent CFD improvementssteady suction case, figure from You et al

- Subsequent CFD improvementssteady suction case, figure from You et al

- URANS

- DES

- LES (3 sets)

## Subsequent CFD improvementsLES example from You et al

- Subsequent CFD improvementsLES example from You et al

- LES

- experiment

## Results from workshop

## Results from workshop+some newer results

- Results from workshop+some newer results

## Summary - case 3

- What’s new
- RANS/URANS
- Trends for steady suction can be obtained in fair agreement with experimental trends (oscillatory control not so good)
- Can get right answer (bubble length) for wrong reason with k-epsilon, for example
- Computing with or without plenum not a big factor when looking at global flow field properties
- DES
- Shown to work well for baseline case
- Generally no benefit for smaller bubbles (issues related to RANS-LES interface location and insufficient eddy content)
- LES & coarse-grid DNS
- Can yield very good results

## Summary - case 3

- Remaining challenges
- Is there bubble size small enough for which RANS/URANS predicts physics & reattachment well?
- Improve blended RANS-LES methods like DES to work more consistently, especially for cases with small separations
- How well can LES predict trends due to jet strength, Re, frequency, etc?
- Can LES-type simulations be used to help improve RANS/URANS models for this class of flows?

## Conclusions

- CFD increasingly called upon to predict synthetic-jet flows
- Need to establish confidence in CFD
- Through verification/validation studies and records of documented successes & failures
- Workshops such as CFDVAL2004 are an important part of this documentation

## Important to “follow through” and address challenges that remain- additional follow-up flow control CFD workshops would be useful

- Important to “follow through” and address challenges that remain- additional follow-up flow control CFD workshops would be useful

## End

## Backup slides

## Hump configuration Two 2-D grids employed: fine=210,000 points, medium=53,000 points

- Hump configuration Two 2-D grids employed: fine=210,000 points, medium=53,000 points

## 2-D oscillatory controlachieved by use of rigid piston spanning the model, driven by series of voice coil actuators

- 2-D oscillatory controlachieved by use of _rigid_ piston spanning the model, driven by series of voice coil actuators

## Phase-averaged profiles at x/c=0.66

## Phase-averaged profiles at x/c=0.8

## Phase-averaged profiles at x/c=1.0