1D Shock Tube

A shock tube is a tube containing high and low pressure gas separated by a thin diaphragm. A shock wave is produced when the diaphragm is quickly removed. The color in the upper plot shows the pressure. The lower plot shows the density. The following Mathematica code solves Euler’s equations using the finite volume method with the Jameson-Schmidt-Turkel (JST) scheme and Runge-Kutta time stepping.

(* runtime: 5 seconds *)
gamma = 1.4;
R[W_] := Module[{}, rho = W[[All, 1]]; u = W[[All, 2]]/rho; p = (gamma - 1)(W[[All, 3]] - rho u^2/2); F = u W + Transpose[{Table[0, {n}], p, u p}]; h = Table[(F[[Min[n, i + 1]]] + F[[i]])/2, {i,1, n}]; Q = Table[h[[Max[i, 2]]] - h[[Max[i, 2] - 1]], {i, 1, n}]; nu = Table[i = Max[2, Min[n - 1, i]]; Abs[(p[[i + 1]] - 2p[[i]] + p[[i - 1]])/(p[[i + 1]] + 2p[[i]] + p[[i - 1]])], {i, 1, n}]; S = Table[Max[nu[[Min[n, i + 1]]], nu[[i]]], {i, 1, n}]; alpha1 = 1/2; beta1 = 1/4;alpha2 = alpha1; beta2 = beta1; epsilon2 = Map[Min[alpha1, alpha2#] &, S];epsilon4 = Map[Max[0, beta1 - beta2#] &, epsilon2];dW = Table[W[[Min[n - 1, i] + 1]] - W[[Min[n - 1, i]]], {i, 1, n}];dW3 = Table[i = Max[2, Min[n - 2, i]]; -W[[i - 1]] + 3W[[i]] - 3W[[i + 1]] + W[[i + 2]], {i, 1, n}];d = (epsilon2 dW - epsilon4 dW3)(Abs[u] + a); Dflux = Table[d[[Max[2, i]]] - d[[Max[2, i] - 1]], {i, 1, n}]; (Q - Dflux)/dx];
n = 50; dx = 1.0/n; a = 1.0; dt = dx/(1.0 + a); W = Table[{If[i > n/2, 0.125, 1], 0, If[i > n/2, 0.1, 1]/(gamma - 1)}, {i, 1, n}];
Do[W -= dt R[W - dt R[W - dt R[W]/4]/3]/2;ListPlot[W[[All, 1]], PlotJoined -> True,PlotRange -> {0, 1}, AxesLabel -> {"i", "rho"}], {t, 0, 100dt, dt}];

Driven Cavity

Here is the flow inside a square box where the flow across the top of the box is moving to the right at Reynolds number 1000. This program uses the finite volume method to solve the Navier-Stokes equations assuming steady, incompressible, viscous, laminar flow. This was calculated on a 300×300 non-uniform grid and took 3 hours to run on my laptop. The animation shows the motion along the streamlines/pathlines.

Driven Cavity – calculated in Fortran 90, plotted in Mathematica 4.2, 11/2/05

The following Mathematica code is not completely accurate at the boundaries, but it gives the basic idea:

(* runtime: 20 minutes *)
n = 50; dx = 1.0/(n - 1); RE = 1000; relax = 0.4; residu = residv = residp = 1;
u = Table[If[j == 1 || i == 2 || i == n, 0, 1], {i, 1, n}, {j, 1, n}];
v = p = pstar = ap = an = as = aw = ae = sc = sp = du = dv = Table[0, {n}, {n}];
lisolv[i0_, j0_, phi0_] := Module[{phi = phi0, p = q =Table[0, {n}]}, Do[q[[j0 - 1]] = phi[[i, j0 - 1]]; Do[p[[j]] = an[[i, j]]/(ap[[i, j]] -as[[i, j]]p[[j - 1]]); q[[j]] = (as[[i, j]]q[[j - 1]] + ae[[i, j]] phi[[i + 1, j]] + aw[[i, j]]phi[[i - 1, j]] + sc[[i, j]])/(ap[[i, j]] - as[[i, j]]p[[j - 1]]), {j, j0, n - 1}]; Do[phi[[i,j]] = p[[j]]phi[[i, j + 1]] + q[[j]], {j, n - 1, j0, -1}], {i, i0, n - 1}]; phi];
calc[i0_, j0_] := Module[{}, {cn, cs, ce, cw} = 0.5 {v[[i,j + 1]] + v[[i0, j0 + 1]], v[[i, j]] + v[[i0, j0]], u[[i + 1, j]] + u[[i0 + 1, j0]], u[[i, j]] + u[[i0, j0]]}dx; cp = Max[0, cn - cs + ce - cw]; {an[[i, j]], as[[i, j]], ae[[i, j]], aw[[i, j]]} = Map[Max[0, 1 - 0.5 Abs[#]] &, RE{cn, cs, ce, cw}]/RE + Map[Max[0, #] &, {-cn, cs, -ce, cw}]; sp[[i, j]] = -cp; ap[[i, j]] = an[[i, j]] + as[[i, j]] + ae[[i, j]] + aw[[i, j]] - sp[[i, j]]];
While[Max[residu, residv, residp] > 0.001, residu = residv = residp = 0; Do[calc[i - 1, j]; sc[[i, j]] = cp u[[i, j]] + dx(p[[i - 1, j]] - p[[i, j]]); du[[i, j]] = relax dx/ap[[i, j]]; residu += Abs[an[[i, j]]u[[i, j + 1]] + as[[i, j]]u[[i, j - 1]] + ae[[i, j]]u[[i + 1, j]] + aw[[i, j]]u[[i - 1, j]] - ap[[i, j]]u[[i, j]] + sc[[i, j]]], {i, 3, n - 1}, {j, 2, n - 1}]; ap /= relax; sc += (1 - relax) ap u; u = lisolv[3, 2, u]; Do[calc[i, j - 1]; sc[[i, j]] = cp v[[i, j]] + dx(p[[i, j - 1]] - p[[i, j]]); dv[[i, j]] = relax dx/ap[[i, j]];residv += Abs[an[[i, j]]v[[i, j + 1]] + as[[i, j]]v[[i, j - 1]] + ae[[i, j]]v[[i + 1, j]] + aw[[i, j]]v[[i - 1, j]] - ap[[i, j]]v[[i, j]] + sc[[i, j]]], {i, 2, n - 1}, {j, 3, n - 1}]; ap /= relax; sc += (1 - relax)ap v; v = lisolv[2, 3, v];Do[an[[i, j]] = dx dv[[i, j + 1]]; as[[i, j]] = dx dv[[i, j]]; ae[[i, j]] = dx du[[i + 1, j]]; aw[[i, j]] = dx du[[i, j]]; sp[[i, j]] = 0; sc[[i, j]] = -((v[[i, j + 1]] - v[[i, j]])dx + (u[[i + 1, j]] - u[[i, j]]) dx); residp += Abs[sc[[i, j]]]; ap[[i, j]] = an[[i, j]] + as[[i, j]] + ae[[i, j]] + aw[[i, j]] - sp[[i, j]]; pstar[[i, j]] = 0, {i, 2, n - 1}, {j, 2, n - 1}]; Do[pstar = lisolv[2, 2, pstar], {2}]; Do[If[i != 2, u[[i, j]] += du[[i, j]](pstar[[i - 1, j]] - pstar[[i, j]])]; If[j != 2, v[[i, j]] += dv[[i, j]](pstar[[i, j - 1]] - pstar[[i, j]])]; p[[i, j]] += 0.3(pstar[[i, j]] - pstar[[n - 1, n - 1]]), {i, 2, n - 1}, {j, 2, n - 1}]];

Here is some Mathematica code to plot streamlines. The blue lines are rotating clockwise and the red lines are rotating counter-clockwise. The plot on the left agrees fairly well with Ercan Erturk’s results.
psi = Table[0, {n - 1}, {n - 1}]; Do[psi[[i, j]] = psi[[i, j - 1]] + dx(u[[i + 1, j - 1]] + u[[i + 1, j]])/2, {j, 2, n - 1}, {i, 1, n - 1}];
psi = ListInterpolation[psi, {{0, 1}, {0, 1}}];
ContourPlot[psi[x, y], {x, 0, 1}, {y, 0, 1}, PlotPoints -> 50, PlotRange -> All, ContourShading -> False,Contours -> {-0.08, -0.077, -0.07, -0.06, -0.045, -0.025, -0.01, -0.0025, 0, -8*^-6, 2*^-6, 3*^-5, 8*^-5, 1*^-4, 3*^-4, 6*^-4, 9*^-4}, ContourStyle -> Table[{Hue[2(1 - x)/3]}, {x, 0, 1, 1/16}]]

Here is some Mathematica code to plot vorticity contours. The plot on the left agrees fairly well with Ghia’s results.
omega = ListInterpolation[Table[(v[[i, j]] - v[[i - 1, j]])/dx - (u[[i, j]] - u[[i, j - 1]])/dx, {i, 2, n - 1}, {j, 2, n - 1}], {{0, 1}, {0, 1}}];
ContourPlot[omega[x, y], {x, 0, 1}, {y, 0, 1},PlotPoints -> 50, PlotRange -> All, ContourShading -> False, Contours -> Range[-14, 7],ContourStyle -> Table[{Hue[2(1 - x)/3]}, {x, 0, 1, 1/21}]]

Computational Fluid Dynamics (CFD) Links

• CFD Gallery – I especially like the simulations of turbulence
• Turbulent Boundary Layer – large simulation by Said Elghobashi
• More CFD Movies – nice simulations of fire
• Colorful Fluid Mixing Gallery
• Gallery of Fluid Dynamics – excellent web site on fluid dynamics by Mark Cramer
• Gallery of Fluid Motion – from the American Institute of Physics
• CFD code – simple Fortran codes by Abdusamad Salih
• FlowLab – educational resource by Fluent

Driven Cavity – Mathematica 4.2, 11/16/06

Here is the same driven cavity using the finite difference method. This code uses the Alternating Direction Implicit (ADI) method to solve the vorticity transport equation assuming unsteady, incompressible, viscous flow.
(* runtime: 1 minute *)
<< LinearAlgebra`Tridiagonal`; n = 20; RE = 1000; dx = 1.0/(n - 1); dt = 0.25; cxy = dt/(4dx); sxy = dt/(2RE dx^2); lambda = 1.5; free = Range[2, n - 1];
omega = v = psi = Table[0, {n}, {n}]; u = Table[If[j == n, 1, 0], {n}, {j, 1, n}];
Do[omega[[All, 1]] = 2psi[[All, 2]]/dx^2; omega[[All, n]] = 2 (psi[[All, n - 1]] + dx)/dx^2; omega[[1, All]] = 2 psi[[2, All]]/dx^2; omega[[n, All]] = 2 psi[[n - 1, All]]/dx^2; omega[[free, free]] = Transpose[Partition[TridiagonalSolve[Drop[Flatten[Table[If[i == n - 1, 0, -(cxy u[[i, j]] + sxy)], {j, 2, n - 1}, {i, 2, n - 1}]], -1], Flatten[Table[1 + 2sxy, {j, 2, n - 1}, {i, 2, n - 1}]], Drop[Flatten[Table[If[i == n - 1,0, cxy u[[i + 1, j]] - sxy], {j, 2,n - 1}, {i, 2, n - 1}]], -1], Flatten[Table[(cxy v[[i, j - 1]] + sxy)omega[[i, j - 1]] + (1 - 2sxy)omega[[i, j]] + (-cxy v[[i, j + 1]] + sxy)omega[[i, j + 1]] + If[i == 2, (cxy u[[i - 1, j]] + sxy)omega[[i - 1, j]],0] - If[i == n - 1, (cxy u[[i + 1, j]] - sxy) omega[[i + 1, j]], 0], {j, 2, n - 1}, {i, 2, n - 1}]]], n - 2]]; omega[[free, free]] = Partition[TridiagonalSolve[Drop[Flatten[Table[If[j == n - 1, 0, -(cxy v[[i, j]] + sxy)], {i, 2, n - 1}, {j, 2, n - 1}]], -1], Flatten[Table[1 + 2sxy, {i, 2, n - 1}, {j, 2, n - 1}]], Drop[Flatten[Table[If[j == n - 1, 0, cxy v[[i, j + 1]] - sxy], {i, 2, n - 1}, {j, 2, n - 1}]], -1], Flatten[Table[(cxy u[[i - 1, j]] + sxy)omega[[i - 1, j]] + (1 - 2sxy)omega[[i, j]] + (-cxy u[[i + 1, j]] +sxy)omega[[i + 1, j]] + If[j == 2, (cxy v[[i, j - 1]] + sxy)omega[[i, j - 1]], 0] - If[j == n - 1, (cxy v[[i, j + 1]] - sxy) omega[[i, j + 1]], 0], {i, 2, n - 1}, {j, 2, n - 1}]]], n - 2]; resid = 1; While[resid > 0.001, resid = 0; Do[resid += Abs[psi[[i, j]] - (psi[[i,j]] = lambda(psi[[i, j - 1]] + psi[[i - 1, j]] + psi[[i + 1, j]] + psi[[i, j + 1]] - dx^2omega[[i, j]])/4 + (1 - lambda)psi[[i, j]])], {i, 2, n - 1}, {j, 2, n - 1}]]; Do[u[[i, j]] = (psi[[i, j + 1]] - psi[[i, j - 1]])/(2dx); v[[i, j]] = -(psi[[i + 1, j]] - psi[[i - 1, j]])/(2dx), {i, 2, n - 1}, {j, 2, n - 1}]; ListContourPlot[Transpose[psi], PlotRange -> All, ContourShading -> False], {100}];

Link: Driven Cavity – simple Fortran program by Zheming Zheng that uses this method

Flapping Wing

This flapping wing was calculated using the unsteady vortex panel methodAlan Lai’s Fortran code. It assumes inviscid incompressible potential flow (irrotational). I also have a working Mathematica version of this code, but it is a little lengthy to show here.

Flapping Wing – Fortran 90, rendered in POV-Ray 3.6.1, 4/28/06

Links

• Unsteady Panel Code Simulations – by Kevin Jones
• Insect Flight – Jane Wang made one of the first simulations to predict that an insect can produce sufficient lift to remain aloft. Here is another article about it. See also these Vortex Method Simulations by Jeff Eldredge.
• Robotic Fly – Uses piezoelectric actuators, by Ron Fearing. See also his Microfly with piezoelectric actuators.
• Harvard Microrobotics Lab – see this video
• Flapping MAV – interesting design by Kevin Jones
• Biomimetics – Biomimetics is the study of biological mechanisms in order to engineer machines that can mimic them.
• RoboCup – International robotic soccer competitions. Their goal is to build robots that can defeat champion human soccer players by the year 2050. It looks like they still have a way to go. See also RoboGames.
• Bionic Dolphin – this submarine is too buoyant to go underwater, but when it is going fast enough, its “flippers” work like upside-down airplane “wings” to force it under water.
• Airic’s Arm – bionic arm operated by “Fluidic Muscles”
• more biomimetics links: Air-Ray (very cool flying manta ray), Aqua-Ray (underwater manta ray), Snake Robot (see video and sidewinding snake), robotic dragonfly toy, NASA’s robotic serpent, BigDog, Spinybot II wall climber, RoboPike, robotic caterpillar, RoboSnail, robotic mule, RoboStrider, RoboRoach hexapod, robotic dolphin, RoboLobster adapted from