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Assignment 2: Cloth & Fluid Simulation
The goal of this assignment is to implement and experiment with
two different physical simulation engines: a spring-mass cloth system
and a grid-based fluid system. The bulk of the rendering,
visualization, and interaction code including the basic data
structures is provided.
In the cloth simulation a 2D grid of point masses are connected
with structural, shear, and flexion/bend springs. To mitigate the
"super-elastic" effect of these springs without increasing
the stiffness (which requires a smaller timestep) you will implement
the correction term described in
"Deformation Constraints in a Mass-Spring Model to Describe Rigid
Cloth Behavior", Xavier Provot, 1995.
For the fluid simulation, you will track a collection of
marker particles as they move through a 3D grid of cells, monitoring
the cell pressure and velocity through each face of each cell. The
implementation requires tri-linear interpolation of the velocities, handling
free-slip and no-slip boundary conditions, and adjustment for incompressible
flows as described in
"Realistic Animation of Liquids", Foster and Metaxas, Graphics Interface 1996.
- Download the provided source code and the sample test datasets.
Compile it on your favorite platform and try the command lines below.
There are a number of visualization options for the cloth system.
Press 'm' to toggle drawing of the masses/particles in the spring-mass
particle system. Press 'w' to toggle drawing of the wireframe
(springs). Press 's' to toggle drawing of the surface represented by
the masses & springs. 'v' and 'f' are used to toggle visualizations
of the velocity and forces at each mass position. Finally, 'b' is
used to toggle the bounding box of the original mass positions.
- First implement basic animation of the masses. You'll need
to compute the spring forces and track the position, velocity, and
acceleration of each particle as time progresses. Simple
forward/explicit Euler integration is sufficient. You can access the
timestep and gravity from the ArgParser class. Initially test your
code on the small example shown below and verify that each of the
spring forces (structural, shear, and bend/flexion) and the force due
to gravity are correct. Pressing 'a' will toggle the animation on and
off. Each loop of this continuous animation will call
Cloth::Animate() 10 times and then refresh the screen. To
take just one step of animation, press the space bar. You can restart
the animation from the beginning by pressing 'r'.
./simulation -cloth small_cloth.txt -timestep 0.001
You will need to complete the implementation for the force
visualization. Your visualization does not need to match the one
above (the blue lines), as long as you find its output informative and
helpful in your debugging.
- Once your basic spring-mass system is working, test it on the
larger example below. As illustrated by Provot, the springs at the
corner will stretch too much. Implement the iterative
correction/adjustment method for springs that have stretched beyond
the specified threshold. The provided code will visualize the
"over-stretched" springs in cyan (shown below).
./simulation -cloth provot_original.txt -timestep 0.001
./simulation -cloth provot_correct_structural.txt -timestep 0.001
./simulation -cloth provot_correct_structural_and_shear.txt -timestep 0.001
- When you are confident that your implementation is complete,
test it on the examples below which use different parameter values to
mimic different types of cloth. Now experiment with your system and
try adjusting the many different parameters. How stable is the
simulation? Discuss in your README.txt. Make at least one
interesting new test scene. You may extend the input file format as
necessary for your new example(s). Describe your new example and how
to run it in your README file.
./simulation -cloth denim_curtain.txt -timestep 0.001
./simulation -cloth silk_curtain.txt -timestep 0.001
./simulation -cloth table_cloth.txt -timestep 0.005
- In your experimentation, you undoubtedly caused the cloth to
"explode" at least once. In theory this instability can always be
fixed by using a smaller timestep. So now, let's implement an
adaptive timestep for the simulator. Start with the timestep provided
on the command line, but if the simulation is too stiff (unstable at
that timestep), back up, halve the timestep, and try again. What
criteria did you use to detect that the system is unstable? Discuss
in your README.txt
- Now for the second part --- fluid simulation, which is
launched like this:
./simulation -fluid fluid_random_xy.txt -timestep 0.01
The images below show some visualizations of this dataset of
random particles on a 5x5x1 grid. On the left we see the random
particles (approximately 64 per cell) and the random initial
velocities measured at the center of each cell. Marker particle
visualization and velocity visualization are toggled by pressing the
'm' and 'v' keys. Remember that the velocities are actually stored as
vectors perpendicular to the face of each cell, visualized by red (x)
and green (y) triangles (toggled by pressing the 'e' key). The
velocity at the center of each cell (drawn as a line segment
colored red->white) is computed by averaging the velocities at the
faces on either side of the cell.
To move particles within the field, we need to compute the
velocity at an arbitrary position within the volume (not just the cell
center). The simplest (but incorrect) thing to do is just use the
velocity at the center of the cell for all particles in that cell.
The image below left shows this discontinuous velocity field (press
'd' to visualize this "dense" velocity field). Go ahead and press 'a'
to animate the particles within this field and you should see why this
isn't a good assignment of velocities.
So, your first task is to implement proper velocity interpolation
as described in Foster & Metaxas. The interpolation is somewhat
complicated because the velocities are defined at the center of each
cell face. Study this image from their paper:
To compute the horizontal component of the velocity at the grey
point, k, we determine the indices for the 4 closest u velocities.
The horizontal component will be a weighted average of these 4 values.
The weights correspond to the 4 subareas in the diagram, formed by
cutting a unit square centered at the grey point with unit squares
centered at the velocity samples. Intuititively, velocity samples
closer to the grey point will have larger area and higher weight.
The sum of the areas (& weights) is 1. To find the vertical component
of the velocity at the same point, we determine the 4 closest v
velocities. Note that the indices (cells) of these points are not
necessarily the same because the u and w velocities are defined on the
cell faces so the grids are shifted. Similarly, the areas (weights)
are not the same.
Once you've carefully implemented the interpolation in the xy
plane, run the above simulation again and you should see dense
velocity fields like the ones above middle and right.
NOTE: In the implementation provided, each cell stores the
face velocities (u, v, & w) for the face it
shares with the cell in the positive direction along each axis. That
is, celli,j,k stores
ui+1/2,j,k, vi,j+1/2,k, and
wi,j,k+1/2. These values are stored in the
variables u_plus, v_plus, and w_plus, and
the corresponding accessors get_u_plus(),
get_v_plus(), and get_w_plus().
- To perform 3D fluid simulations your interpolation scheme
must correctly account for the z direction as well. Of course
this is more work! Instead of find the 4 closest velocities for
each dimension, you must find the 8 closest values and instead of
computing 4 subareas of a unit square, you will compute 8 subvolumes
of the unit cube. And you need to do this for each dimension
separately. Here are 3 test cases to help you verify that your
interpolation is working in 3D. The resulting animation should be
symmetric and similar in each of the 3 axis-aligned planes. NOTE:
The xy plane is the most important. Even if your z dimension
implementation is incomplete or buggy, you can continue with the
remainder of the assignment.
./simulation -fluid fluid_spiral_xy.txt -timestep 0.01
./simulation -fluid fluid_spiral_yz.txt -timestep 0.01
./simulation -fluid fluid_spiral_zx.txt -timestep 0.01
- Now let's address the issue of compressibility/incompressibility.
You may have noticed that your simulations are a little "bouncy". To
emphasize the fact, try this simulation:
./simulation -fluid fluid_compressible.txt -timestep 0.01
You can press "p" to visualize the pressure in each cell by drawing
little cubes for each cell colored by pressure. Initially all the
cells are white (pressure == 0). After just a few timesteps (press
the spacebar to advance by a single timestep) a negative pressure
(blue) appears in the middle of the grid surrounded by a ring of
positive pressure (red). Later in the simulation these values are
quite chaotic, introducing noise into the velocity field.
In order to enforce the incompressibility of the flow, you will
need to implement the divergence correction originally described by
Harlow & Welch and later by Foster & Metaxas. Compute the divergence
of each "full" cell and adjust each non-boundary face velocity to
absorb its share of excess inflow or outflow. When correctly
implemented, the pressure in each cell should be (within epsilon of)
zero throughout the simulation and the flow should no longer "bounce".
./simulation -fluid fluid_incompressible.txt -timestep 0.01
- Up to this point, all of the cells in our fluid simulation
have been full (had at least one particle). Now let's look at some
interesting cases showing the interaction between air and water. Try
the examples below. Press "c" to visualize the Marker-And-Cell (MAC)
voxels: red == FULL and blue == SURFACE. Press "s" to enable a
triangular mesh rendering of the surface using Marching Cubes/Marching
./simulation -fluid fluid_drop.txt -timestep 0.001
./simulation -fluid fluid_dam.txt -timestep 0.005
To perform these simulations you will need to extend your
incompressibility code to handle surface cells. The divergence of
inflow or outflow should be dissipated over the "free" faces of the
cell (i.e., faces that this cell shares with EMPTY cells).
Note: You can edit the dimensions of your grid by editing the top
line of the simulation data file. The "drop" and "dam" shapes will
adjust to your new dimensions.
- Harlow & Welch, "Numerical Calculation of Time-Dependent Viscous
Incompressible Flow of Fluids with Free Surface," Phys. Fluids,
Vol. 8, p. 2182, 1965.
Practical animation of liquids,
Foster & Fedkiw,
simulation of smoke, Fedkiw, Stam & Jensen, SIGGRAPH 2001
"Melting and Flowing"
Carlson, Mucha, Van Horn III & Turk,
ACM SIGGRAPH Symposium on Computer Animation 2002
Ideas for Extra Credit
Include a short paragraph in your README.txt file describing
- Implement an alternate integration method (Midpoint, Runge-Kutta,
implicit Euler, etc.) for the cloth simulation. Compare the
performance of each method.
- Implement a new visualization/rendering mode (maybe you
already did to debug an earlier step). For example, add gouraud
shading to the cloth simulation, or use transparency or reflection to
improve the water visualization.
- Create a new fluid test scene (you can create it procedurally,
or create a new input file). A fun test scene could include source
and sink cells where mass is created and deleted or a spatial- or
time-varying force field (instead of a uniform gravity).
- Having two physical simulation engines within the same program
makes it possible for us to experiment with coupled simulations.
Compose a cloth simulation and fluid simulation in the same scene
(just load 2 files on the command line). The cloth motion can be
driven by the fluid's velocity field, or the fluid motion can be
driven by the cloth, or both!
- Basic Code (vectors.h, matrix.h, matrix.cpp, argparser.h,
camera.h, camera.cpp, glCanvas.h, glCanvas.cpp, main.cpp,
boundingbox.h, boundingbox.cpp, utils.h, Makefile)
Similar to Assignments 1 & 2.
- Cloth (cloth.h, cloth.cpp)
A class to store, animate, and paint a 2D grid of masses & springs.
- Cloth test scenes (small_cloth.txt, provot_original.txt,
- Fluid (fluid.h, fluid.cpp, cell.h, marching_cubes.h,
Code to store, animate, and render a grid based fluid simulation.
- Fluid test scenes (fluid_random_xy.txt,
fluid_spiral_xy.txt, fluid_spiral_yz.txt, fluid_spiral_zx.txt,
fluid_compressible.txt, fluid_drop.txt, fluid_dam.txt)
Please read the Homework information page again before submitting.