Moving Beyond Prediction to Control Free Surface Turbulence

Moving Beyond Prediction to Control Free Surface, Turbulence, and Magnetohydrodynamics: Interactions and effects on flow control and interfacial transport Mohamed Abdou Professor, Mechanical & Aerospace Engineering, UCLA Seminar on Science in Fusion’s Enabling R&D Program Gaithersburg, MD, March 13, 2001 Acknowledgment: This presentation was prepared in collaboration with Profs. N. Morley and S. Smolentsev and draws on the work of many scientists in the field.

Liquid Wall Researchers are Advancing the Understanding of Interacting Multi-Scale Phenomena at the Frontiers of Fluid Dynamics Fluid In SCALAR TRANSPORT -+ r V r r JJ FREE SURFACE PHENOMENA Plasma-Liquid Interactions Plasma r ÄB MHD TURBULENCE Fluid Out

Fusion LW Researchers are Contributing to the Resolution of GRAND CHALLENGES in Fluid Dynamics SCALAR TRANSPORT Liquid Walls: many interacting phenomena FREE SURFACE PHENOMENA • Turbulence redistributions at free surface • Turbulence-MHD interactions MHD • MHD effects on mean flow and surface stability • Influence of turbulence and surface waves on interfacial transport and surface renewal Teraflop Computer Simulation TURBULENCE

CHALLENGE: FREE SURFACE FLOW “Open Channel Flows are essential to the world as we know it” Munson, Young, Okiishi (from their Textbook) Free surface flow forms: films, droplets, jets, bubbles, etc. Fluid regions can coalesce, break up, and exhibit non-linear behavior • The term free surface is often used for any gas/void to liquid interface, but denotes an interface between a liquid and a second medium that is unable to support an applied pressure gradient or shear stress. • Formation of surface waves, a distinguishing feature (for LW - Fr > 1, supercritical flow) • Interfacial flows are difficult to model computational domain changes in time making application of BCs difficult • Interfacial tension effects make equations “stiff”- differing time scales for surface wave celerity compared to liquid velocity Watermark - Shear layer instability at water surface - Cal. Tech Data

Numerically tracking moving interfaces is an ongoing challenge in CFD Still NO IDEAL Interface Tracking Method Volume-of-Fluid (VOF): The method is based on the concept of advection of a fluid volume fraction, . It is then possible to locate surfaces, as well as determine surface slopes and surface curvatures from the VOF data. VOF Level-Set Method: The method involves advecting a continuous scalar variable. An interface can thus be represented by a level set of the scalar variable. This is a different approach from VOF where the discontinuity represents the interface. OTHERS: Lagrangian Grid Methods Surface Height Method Marker-and-Cell (MAC) Method Watermark - milk drop splash simulation using VOF- Kunugi, Kyoto Univ.

CHALLENGE: TURBULENCE • In Turbulent Motion the “various flow quantities exhibit random spatial and temporal variations” where “statistically distinct average values can be discerned. ” - Hinze Center for Computations Science and Engineering (LBNL). LES simulation of instability in a submerged plane jet. Horace Lamb, British physicist: “I am an old man now, and when I die and go to heaven there are two matters on which I hope for enlightenment. One is quantum electrodynamics, and the other is the turbulent motion of fluids. And about the former I am rather optimistic. ” • Turbulence is the rule, not the exception, in most practical flows. Turbulence is not an unfortunate phenomena. Enhancing turbulence is often the goal. • Vastly different length and time scales make equations stiff - requiring large number of computational cycles. High resolution required to capture all length scales and geometrical complexities.

Teraflop Computers are Making TURBULENCE Accessible Super-computers Averaged Models: Some or all fluctuation scales are modeled in an average sense Turbulence Structure Simulated DNS length ratio: l/ Re 3/4 grid number: N (3 Re )9/4 For Re =104 , N 1010 LES RANS Teraflop computing

Turbulence / free surface interaction produces new phenomena - anisotropic near-surface turbulence • Turbulent production dominated by the generation of wall ejections, formation of spanwise “upsurging vortices” • Upsurging vortices reach free surface, form surface deformation patches, roll back in form of spanwise “downswinging vortices”, with inflow into the bulk. Conceptual illustration of experimental observation of burst-interface interactions - From Rashidi, Physics of Fluids, No. 9, November 1997. Watermark - Vortex structure and free surface deformation (DNS calculation) • The ejection - inflow events are associated with the deformation of the free surface and a redistribution of near surface vorticity and velocity fields.

CHALLENGE: MAGNETOHYDRODYNAMICS • Complex non-linear interactions between fluid dynamics and electrodynamics • Powerful mechanism to “influence” fluids • Strong drag effects, thin active boundary layers, large (possibly reversed) velocity jets are characteristic MHD phenomena • Large currents with joule dissipation and even self-sustaining dynamo effects add to computational complexity Computational Challenge Li flow in a chute in a transverse field with: b=0. 1 m (halfwidth); B 0=12 T (field) Ha = B 0 b Free surface flow velocity jets produced from MHD interaction - UCLA calculation Each cross-section requires MANY uniform grids, or special non-uniform meshes.

MHD interactions can change the nature of turbulence - providing a lever of CONTROL • Applied Lorentz forces act mainly in the fluid regions near the walls where they can prevent flow separation or reduce friction drag by changing the flow structure. • Because heat and mass transfer rely strongly on the flow structure, they can in turn be controlled in such fashion. Flow direction Experimental control of flow separation by a magnetic field: fully developed von Kármán vortex street without a magnetic field (upper) with a magnetic field (right) From Dresden University of Technology

Liquid Wall Science is important in many scientific pursuits and applications • Liquid Jet and Film Stability and Dynamics: fuel injection, combustion processes, water jet cutting, ink jet printers, continuous rod/sheet/ribbon/sphere casting, flood/jet soldering, ocean waves, hull design, ocean/river hydraulic engineering, surfing, liquid walls for fusion reactors • Liquid MHD / free surface interactions: melt/mold stirring and heating, liquid jet/flow control and shaping, crystal growth, astrophysical phenomena, liquid metal walls for particle accelerators and fusion reactors • Liquid MHD / turbulence interactions: microstructure control in casting, boundary layer control, astrophysical dynamos and plasmas, liquid walls for particle accelerators and fusion reactors • Free surface heat and mass transfer: oceanography, meteorology, global climate change, wetted-wall absorbers/chemical reactor, condensers, vertical tube evaporator, film cooling of turbine blades, impurity control in casting, liquid walls for particle accelerators and fusion reactors Watermark: Turbulent flow effect on dendrite formation in casting - LANL simulation

Liquid Wall Science is being Advanced in Several MFE & IFE Research Programs HYLIFE-II NSTX Li module 3 D Laser Beams KOH Thin Plastic KOH Jacket APEX CLi. FF Twisted. Tape JUPITER-II IFMIF

MODELING FREE-SURFACE MHD TURBULENCE (from limited DNS/experimental data to real applications) Joule Dissipation DNS for free surface MHD flows developed as a part of collaboration between UCLA and Japanese Profs Kunugi and Satake RANS TURBULENCE MODELS Statistical description of bulk and free surface TURBULENCE Turbulent Prandtl Number EXPERIMENTS underway at UCLA for near surface turbulence and interfacial transport measurements ·K-epsilon ·RST model DNS and Experimental data are used at UCLA for characterizing turbulence phenomena and developing closures in RANS models

A BIG STEP FORWARD (1 st FREE SURFACE, MHD TURBULENT DNS) Ha=0 • Strong redistribution of turbulence by a magnetic field is seen. • Frequency of vortex structures decreases, but vortex size increases. Ha=10, Spanwise Ha=20, Streamwise • Stronger suppresion effect occurs in a spanwise magnetic field • Free surface approximated as a free slip boundary. Work proceeding on a deformable free surface solution. “DNS of turbulent free surface flow with MHD at Ret = 150” - Satake, Kunugi, and Smolentsev, Computational Fluid Dynamics Conf. , Tokyo, 2000

PUTTING DATA TO WORK RANS EQUATIONS: “K- ” model K- TURBULENCE MODEL Comparison of UCLA model to experimental data 1 2 MHD DEPENDENT TURBULENCE CLOSURES Magnetic field direction Streamwise Wall-normal Spanwise K eem s 2 BK r 0 s C 3 B 02 K r C 3 s 2 BK r 0 e eem C 3 C 4 s 2 Be r 0 s C 4 B 02 e r 0. 02 0. 015 C 4 s 2 Be r 0 1. 9 exp{-1. 0 N} 1. 9 exp{-2. 0 N} 1. 9 exp{-1. 0 N} 1. 9 exp{-2. 0 N} Experimental measurements of Turbulent Prandl number

Interfacial Transport Experiments in FLIHY • Large scale test section with water/electrolyte flow will generate LW relevant flow • Tracer dye and IR camera techniques will be used to measure interfacial transport at free surface • PIV and LDA systems for quantitative turbulence comparison to DNS Visualization of sinking and dispersing milk drop in water 2 cm FLIHY Experiment at UCLA Test section length = 4 m

Dye Diagnostics for Interfacial Mass Transport Measurements Profile of dye penetration (red dots) Local free surface (blue dots) flow direction ~2 m/s

Dynamic Infrared measurements of jet surface temperature Water jet Impact of hot droplets on cold water jet (~8 m/s) thermally imaged in SNL/UCLA test hot droplets Hot droplet penetrating jet

NEW PHENOMENA IN LM-MHD FLOW 2 D Turbulence 3 D fluctuations on free surface N=0 Surface fluctuations become nearly 2 D along field N=6 SOME PROPERTIES OF 2 -D MHD TURBULENCE: Surface fluctuations are nearly suppressed B N=10 LM free surface images with motion from left to right Riga Data ·Inverse energy cascade; ·Large energy containing vortices; ·Low Joule and Viscous dissipation; ·Insignificant effect on the hydraulic drag. 2 -D turbulence could be very useful as a mean of intensifying heat transfer.

Electromagnetic Control of Heat Transfer Velocity profiles with favorable features could be formed by making the side-walls slightly electrically conducting. Isolated walls: In the near-surface jet the velocity is about 2 times higher than the mean velocity Conducting walls: In the near-surface jet the velocity is about 10 times higher than the mean velocity

Simulations of Flowing Lithium in NSTX Upper - “Center Stack +Inboard Divertor”, 2. 5 -D model; Lower – “Inboard Divertor”, Flow 3 D-M MHD and Heat Transfer Conclusions: ·Stable Li film flow can be established over the Center Stack; ·The Center Stack projected heat load can be removed by a 4 mm film ejected at 2 m/s.

State-of-the-Art Computational Techniques are Required for Intensive LW Simulation • Grid adaption or multi-resolution • Parallel Algorithm Implementation • Unstructured Meshes • High-order advection and free surface tracking algorithms Lithium Jet start-up without and with grid adaption Hyper. Comp Simulation

USING MHD FORCES TO CONTROL FLOW Soaker Hose Concept • Leak liquid radially inward from supply tubes • Stagnate inward flow and drive liquid radially over short path with applied poloidal current • Complex interaction with other field components seen in simulations B u Ja B Toroidal u Radial u Ja Poloidal UCLA Simulation

Exploring Free Surface LM-MHD in MTOR Experiment • Study toroidal field and gradient effects: Free surface flows are very sensitive to drag from toroidal field 1/R gradient, and surface-normal fields • 3 -component field effects on drag and stability: Complex stability issues arise with field gradients, 3 -component magnetic fields, and applied electric currents • Effect of applied electric currents: Magnetic Propulsion and other active electromagnetic restraint and pumping ideas • Geometric Effects: axisymmetry, expanding / contacting flow areas, inverted flows, penetrations Timeof-flight • NSTX Environment simulation: module testing and design MTOR Magnetic Torus and LM Flowloop: Designed in collaboration between UCLA, PPPL and ORNL

Liquid Jet Research for IFE Chambers High-velocity, oscillating jets for liquid “pocket” • flow trajectory and jet deformation • primary breakup / droplet formation • dissembly processes • liquid debris interaction / clearance • partial head recovery High-velocity, low surfaceripple jets for liquid “grid” • surface smoothness control • pointing accuracy / vibration • primary breakup / droplet ejection Graphics from UCB

Oscillating IFE jet experiments and simulations Flow Direction • Single jet water experiments and numerical simulations demonstrate control of jet trajectory and liquid pocket formation at near prototypic Re Experimental Data from UCB Flow Direction Regions flattened by interaction with neighboring jet Simulations from UCLA

Understanding mechanisms of flow instability leads to improved control of jet surface smoothness for IFE • Upstream turbulence and nozzle boundary layer thickness heavily influence downstream jet stability • Turbulence conditioning and boundary layer trimming in nozzle dramatically improves jet quality Re = 75, 000 L/D = 44 Re = 100, 000 L/D = 44 w/ conditioning w/o conditioning UC Berkeley data

Modeling of Stationary Jet Deformation Modeling UCLA Experiment • Initially rectangular jets deform due to surface tension and corner pressurization in nozzle • Capillary waves from corner regions fan across jet face - largest source of surface roughness! • Numerical simulations and quantitative surface topology measurements are critical tools for understanding jet deformation, and controlling jet behavior with nozzle shaping LIF measurement of surface topology at Georgia Tech

Liquid Wall Science is important in many scientific pursuits and applications • Liquid Jet and Film Stability and Dynamics: fuel injection, combustion processes, water jet cutting, ink jet printers, continuous rod/sheet/ribbon/sphere casting, flood/jet soldering, ocean waves, hull design, ocean/river hydraulic engineering, surfing, liquid walls for fusion reactors • Liquid MHD / free surface interactions: melt/mold stirring and heating, liquid jet/flow control and shaping, crystal growth, astrophysical phenomena, liquid metal walls for particle accelerators and fusion reactors • Liquid MHD / turbulence interactions: microstructure control in casting, boundary layer control, astrophysical dynamos and plasmas, liquid walls for particle accelerators and fusion reactors • Free surface heat and mass transfer: oceanography, meteorology, global climate change, wetted-wall absorbers/chemical reactor, condensers, vertical tube evaporator, film cooling of turbine blades, impurity control in casting, liquid walls for particle accelerators and fusion reactors Watermark: Turbulent flow effect on dendrite formation in casting - Juric simulation

Temperature Rise (K) What is Global Warming? Increasing Green House Gases: Humidity, CO 2, Methane, NOx, Sox etc. Infra Red Absorption into Green House Gases and on the Earth surface I. R. Absorption Sun Earth I. R. Radiatio n Preserving Heat in the Air Temperature Rise in the Air I. R. : Infra Red Year

Free surface mass transport is affecting CO 2 concentrations Missing Sink Problem over past 30 years Measured atmospheric CO 2 increase (34 ppm) - Spent Fossile Fuel emissions (61 ppm) = Missing Sink(-27 ppm) ? Turbulent Heat and Mass transfer across Free Surface ? Wind flow Free surface contour wind-driven calculation CO 2 absorption at the turbulent free-surface deformed by the shear wind, by means of direct numerical solution procedure for a coupled gas-liquid flow

Coherent Structures in Wind-driven Turbulent Free Surface Flow Wind Water Atmospheric Pressure Contour Surface (Green) High Speed Gas Side Regions (Brown) High Speed Water-Side Regions (Blue) Streamwise Instantaneous Velocity (Color Section) DNS

Some Common Aspects between Global Warming and Fusion Science Thermofluid Research Similar Phenomena • High Pr flow with radiation heating at free surface from plasma • High Sc flow with CO 2 absorption at free surface of sea Similar Flow Characteristics • Re is high, both have the similar turbulence characteristics. • MHD (fusion) and Coriollis (global warming) forces can influence the average velocity Heat and Mass Transfer Similarity • High Pr, very low thermal diffusivity->very thin thermal boundary layer->large temperature gradient at interface • High Sc, very low molecular diffusivity->very thin concentration boundary layer->large concentration gradient at interface.

Liquid Jet Stability and Breakup commercial Inkjet Printer quality is hampered by formation of “satellite” droplets Micro-injector increases relative importance of surface tension by decreasing size eliminates satellite droplets and improves precision micro Simulation of commercial inkjet by Rider, Kothe, et al. - LANL Data from Ho - UCLA

Vertical B field effects on Liquid Metal Film Flows Continuous sheet casting can produce smooth free surfaces and film thickness control via MHD forces Film thickness profiles for various Hartmann Numbers Simulation by Lofgren, et al.

Reflections on 19 th & 20 th Centuries 1850: Navier-Stokes Equation 1873: Maxwell’s Equations 1895: Reynolds Averaging 1900 -1960’s: -Averaging techniques, Semi-empirical approach. Heavy reliance on Prototype Testing (e. g. wind tunnels for aerodynamics). 1960’s - 1970’s: -Supercomputers allow direct solution of N-S for simple problems. Advances in Computational Fluid Dynamics (CFD), e. g. utilization of LES technique. 1980’s - 1990’s: -Rapid advances to Teraflop Computers -Rapid advances in CFD and in experimental techniques -Turbulence structure “simulated” and “observed” for key problems -Better understanding of fluid physics and advanced “Prediction” tools -Paradigm Shift: - From “mostly experimental for empirical global parameters” to “larger share for CFD: simulation first followed by smaller number of carefully planned experiments aimed at understanding specific physics issues and verifying simulation. ”

21 st Century Frontiers Moving Beyond “Prediction” of Fluid Physics To “Control” of Fluid Dynamics • With the rapid advances in teraflop computers, fluid dynamicists are increasingly able to move beyond predicting the effects of fluid behavior to actually controlling them; with enormous benefits to mankind! Examples • Reduction in the Drag of Aircraft The surface of a wing would be moved slightly in response to fluctuations in the turbulence of the fluid flowing over it. The wings surface would have millions of embedded sensors and actuators that respond to fluctuations in the fluids, P, V as to control eddies and turbulence drag. DNS shows scientific feasibility and MEMS can fabricate integrated circuits with the necessary microsensors, control logic and actuators • Fusion Liquid Walls Control of “free surface-turbulence-MHD” interactions to achieve fast interfacial transport and “guided motion” in complex geometries (“smart-liquids”) • Nano Fluidics: Pathway to Bio-Technologies Appropriately controlled fluid molecules moving through nano/micro passages can efficiently manipulate the evolution of the embedded macro DNA molecules or affect the physiology of cells through gene expression.