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Notes Viscosity In reality, nearby molecules travelling at different velocities occasionally bump into each other, transferring energy Differences in velocity reduced (damping) Measure this by strain rate (time derivative of strain,


  1. Notes Viscosity � In reality, nearby molecules travelling at different velocities occasionally bump into each other, transferring energy • Differences in velocity reduced (damping) • Measure this by strain rate (time derivative of strain, or how far velocity field is from rigid motion) • Add terms to our constitutive law cs533d-winter-2005 1 cs533d-winter-2005 2 Strain rate Viscous stress � At any instant in time, measure how fast chunk � As with linear elasticity, end up with two of material is deforming from its current state parameters if we want isotropy: • Not from its original state viscous = 2 µ ˙ ij + � ˙ � ij � � kk � ij • So we’re looking at infinitesimal, incremental strain • µ and � are coefficients of viscosity (first and second) updates • Can use linear Cauchy strain! • These are not the Lame coefficients! Just use the same symbols � So the strain rate tensor is • � damps only compression/expansion � � � Usually � � -2/3 µ (exact for monatomic gases) + � u j � u i ˙ ij = 1 � � � � � � So end up with � � 2 + � u j viscous = µ � u i � 2 � u k � x j � x i � � � ij � � ij � � � � x j � x i 3 � x k � � cs533d-winter-2005 3 cs533d-winter-2005 4 Navier-Stokes Nondimensionalization � Navier-Stokes equations include the viscous � Actually go even further stress � Select a characteristic length L � Incompressible version: • e.g. the width of the domain, ( ) � � � µ � u + � u T u t + u � � u + 1 � � p = g + 1 � And a typical velocity U � � u = 0 • e.g. the speed of the incoming flow � Often (but not always) viscosity µ is constant, � Rescale terms and this reduces to • x’=x/L, u’=u/U, t’=tU/L, p’=p/ � U 2 � � 2 u µ u t + u � � u + 1 � � p = g + so they all are dimensionless • Call � = µ / � the “kinematic viscosity” u ' t + u ' �� u ' + � p ' = Lg U 2 + � UL � 2 u ' cs533d-winter-2005 5 cs533d-winter-2005 6

  2. Nondimensional parameters Why nondimensionalize? � Think of it as a user-interface issue � Re=UL/ � is the Reynold’s number � It lets you focus on what parameters matter • The smaller it is, the more viscosity plays a • If you scale your problem so nondimensional role in the flow parameters stay constant, solution scales • High Reynold’s numbers are hard to simulate � Code rot --- you may start off with code which has true dimensions, but as you hack around � Fr= is the Froude number U g L they lose meaning • The smaller it is, the more gravity plays a role • If you’re nondimensionalized, there should be only in the flow one or two parameters to play with • Note: often can ignore gravity (pressure � Not always the way to go --- you can look up material constants, but not e.g. Reynolds gradient cancels it out) numbers u t + u � � u + � p = (0, � 1,0) + 1 Re � 2 u Fr 2 cs533d-winter-2005 7 cs533d-winter-2005 8 Other quantities Boundary conditions � Inviscid flow: � We may want to carry around auxiliary • Solid wall: u•n=0 quantities • Free surface: p=0 (or atmospheric pressure) • E.g. temperature, the type of fluid (if we have • Moving solid wall: u•n=u wall •n a mix), concentration of smoke, etc. � Also enforced in-flow/out-flow • Between two fluids: u 1 •n=u 2 •n and p 1 =p 2 + �� � Use material derivative as before � Viscous flow: � E.g. if quantity doesn’t change, just is • No-slip wall: u=0 transported (“advected”) around: • Other boundaries can involve coupling tangential components of stress tensor… Dq Dt = q t + u � � q 3 = 0 � Pressure/velocity coupling at boundary: 1 2 • u•n modified by � p/ � n advection cs533d-winter-2005 9 cs533d-winter-2005 10 What now? Vorticity � Can solve numerically the full equations � How do we measure rotation? • Vorticity of a vector field (velocity) is: � = � � u • Will do this later • Proportional (but not equal) to angular velocity of a • Not so simple, could be expensive (3D) rigid body - off by a factor of 2 � Or make assumptions and simplify them, � Vorticity is what makes smoke look interesting then solve numerically • Turbulence • Simplify flow (e.g. irrotational) • Simplify dimensionality (e.g. go to 2D) cs533d-winter-2005 11 cs533d-winter-2005 12

  3. Vorticity equation Vorticity equation continued � Start with N-S, constant viscosity and density � Simplify with more vector identities, and assume � � p = g + � � 2 u u t + u � � u + 1 incompressible to get: � Take curl of whole equation D � Dt = � � � u + � � 2 � � � p = � � g + � � � � 2 u ( ) � � u t + � � u � � u ( ) + � � 1 � Important result: Kelvin Circulation Theorem � Lots of terms are zero: • Roughly speaking: if � =0 initially, and there’s no • g is constant (or the potential of some field) viscosisty, � =0 forever after (following a chunk of • With constant density, pressure term too fluid) ) = � � � � 2 u � � u t + � � u � � u ( � If fluid starts off irrotational, it will stay that way � Then use vector identities to simplify… (in many circumstances) ) = � � 2 � � u ( ( ) � u + 1 2 � u 2 ( ) � � u t + � � � � u ) = � � 2 � � t + � � � � u ( cs533d-winter-2005 13 cs533d-winter-2005 14 Potential flow Potential in time � If velocity is irrotational: � What if we have a free surface? � Use vector identity u• � u=( �� u) � u+ � |u| 2 /2 � � u = 0 � Assume • Which it often is in simple laminar flow • incompressible ( � •u=0), inviscid, irrotational ( �� u=0) � Then there must be a stream function (potential) • constant density such that: • thus potential flow (u= �� , � 2 � =0) u = � � � Then momentum equation simplifies � Solve for incompressibility: (using G=-gy for gravitational potential) 2 + 1 ( ) � u + 1 u t + � � u 2 � u � � p = g � � � � = 0 2 + 1 � � t + 1 2 � u � � p = �� G � If u•n is known at boundary, we can solve it cs533d-winter-2005 15 cs533d-winter-2005 16 Bernoulli’s equation Water waves � Every term in the simplified momentum � For small waves (no breaking), can reduce geometry of water to 2D heightfield equation is a gradient: integrate to get 2 u 2 + p � Can reduce the physics to 2D also � t + 1 � = � G • How do surface waves propagate? � Plan of attack • (Remember Bernoulli’s law for pressure?) • Start with potential flow, Bernoulli’s equation � This tells us how the potential should • Write down boundary conditions at water surface evolve in time • Simplify 3D structure to 2D cs533d-winter-2005 17 cs533d-winter-2005 18

  4. Set up Boundaries � y = 0 � We’ll take y=0 as the height of the water at � At sea floor (y=-H), v=0 rest � At sea surface (y=h � 0), v=h t � H is the depth (y=-H is the sea bottom) • Note again - assuming very small horizontal motion � h is the current height of the water at (x,z) � y = h t � Simplification: velocities very small (small amplitude waves) � At sea surface (y=h � 0), p=0 • Or atmospheric pressure, but we only care about pressure differences • Use Bernoulli’s equation, throw out small velocity squared term, use p=0, � t = � gh cs533d-winter-2005 19 cs533d-winter-2005 20 Finding a wave solution Dispersion relation � Plug in � =f(y)sin(K•(x,z)- � t) � So the wave speed c is • In other words, do a Fourier analysis in g c = � k tanh kH k = horizontal component, assume nothing much happens in vertical � Notice that waves of different wave- • Solving � 2 � =0 with boundary conditions on � y numbers k have different speeds gives ( ) cosh K ( y + H ) • Separate or disperse in time � = A � ( ) sin K � ( x , z ) � � t ( ) K sinh K H � For deep water (H big, k reasonable -- not tsunamis) tanh(kH) � 1 • Pressure boundary condition then gives (with k=|K|, the magnitude of K) g c = � = gk tanh kH k cs533d-winter-2005 21 cs533d-winter-2005 22 Simulating the ocean Energy spectrum � Far from land, a reasonable thing to do is � Fourier decomposition of height field: • Do Fourier decomposition of initial surface ˆ ( ) � x , z ( ) � � 1 i , j h ( x , z , t ) = h i , j , t ( ) e height i , j 2 • Evolve each wave according to given wave S ( K ) = ˆ � “Energy” in K=(i,j) is h ( K ) speed (dispersion relation) � Update phase, use FFT to evaluate � Oceanographic measurements have found � How do we get the initial spectrum? models for expected value of S(K) • Measure it! (oceanography) (statistical description) cs533d-winter-2005 23 cs533d-winter-2005 24

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