# The Crameri et al. benchmarks
*This section was contributed by Ian Rose.*
This section follows the two free surface benchmarks described by {cite:t}`crameri:etal:2012`.
## Case 1: Relaxation of topography.
The first benchmark involves a high viscosity lid sitting on top of a lower
viscosity mantle. There is an initial sinusoidal topography which is then
allowed to relax. This benchmark has a semi-analytical solution (which is
exact for infinitesimally small topography). Details for the benchmark setup
are in {numref}`fig:crameri-benchmark-initial-topography`.
```{figure-md} fig:crameri-benchmark-initial-topography
Setup for the topography relaxation benchmark. The box is 2800 km wide and 700 km high, with a 100 km lid on top. The lid has a viscosity of $10^{23} \, {Pa\,s}$, while the mantle has a viscosity of $10^{21} \, {Pa\,s}$. The sides are free slip, the bottom is no slip, and the top is a free surface. Both the lid and the mantle have a density of $3300 \,{kg/m^3}$, and gravity is $10 \, {m/s^2}$. There is a $7 \, {km}$ sinusoidal initial topography on the free surface.
```
The complete parameter file for this benchmark can be found in
[benchmarks/crameri_et_al/case_1/crameri_benchmark_1.prm](https://www.github.com/geodynamics/aspect/blob/main/benchmarks/crameri_et_al/case_1/crameri_benchmark_1.prm), the most relevant
parts of which are excerpted here:
```{literalinclude} crameri_benchmark_1.prm
```
In particular, this benchmark uses a custom geometry model to set the initial
geometry. This geometry model, called "`ReboundBox`," is based on
the `Box` geometry model. It generates a domain in using the same parameters
as `Box`, but then displaces all the nodes vertically with a sinusoidal
perturbation, where the magnitude and order of that perturbation are specified
in the `ReboundBox` subsection.
The characteristic timescales of topography relaxation are significantly
smaller than those of mantle convection. Taking timesteps larger than this
relaxation timescale tends to cause sloshing instabilities, which are
described further in {ref}`sec:methods:freesurface`. Some sort of
stabilization is required to take large timesteps. In this benchmark, however,
we are interested in the relaxation timescale, so we are free to take very
small timesteps (in this case, 0.01 times the CFL number). As can be seen in
{numref}`fig:crameri-benchmark-relaxation-topography`, the results of all the codes which are included in this
comparison are basically indistinguishable.
```{figure-md} fig:crameri-benchmark-relaxation-topography
Results for the topography relaxation benchmark, showing maximum topography versus time. Over about 100 ka the topography completely disappears. The results of four free surface codes, as well as the semi-analytic solution, are nearly identical.
```
## Case 2: Dynamic topography.
Case two is more complicated. Unlike the case one, it occurs over mantle
convection timescales. In this benchmark there is the same high viscosity lid
over a lower viscosity mantle. However, now there is a blob of buoyant
material rising in the center of the domain, causing dynamic topography at the
surface. The details for the setup are in the caption of {numref}`fig:crameri-benchmark-rising-blob`.
```{figure-md} fig:crameri-benchmark-rising-blob
Setup for the dynamic topography benchmark. Again, the domain is 2800 km wide and 700 km high. A 100 km thick lid with viscosity $10^{23}$ overlies a mantle with viscosity $10^{21}$. Both the lid and the mantle have a density of $3300\,kg/m^3$. A blob with diameter 100 km lies 300 km from the bottom of the domain. The blob has a density of $3200\,kg/m^3$ and a viscosity of $10^{20}$ Pa s.
```
Case two requires higher resolution and longer time integrations than case
one. The benchmark is over 20 million years and builds dynamic topography of
$\sim 800$ meters.
```{figure-md} fig:crameri-2-comparison
Evolution of topography for the dynamic topography benchmark. The maximum topography is shown as a function of time, for as well as for several other codes participating in the benchmark. This benchmark shows considerably more scatter between the codes.
```
Again, we excerpt the most relevant parts of the parameter file for this
benchmark, with the full thing available in
[benchmarks/crameri_et_al/case_2/crameri_benchmark_2.prm](https://www.github.com/geodynamics/aspect/blob/main/benchmarks/crameri_et_al/case_2/crameri_benchmark_2.prm). Here we use the
"Multicomponent" material model, which allows us to easily set up
a number of compositional fields with different material properties. The first
compositional field corresponds to background mantle, the second corresponds
to the rising blob, and the third corresponds to the viscous lid.
Furthermore, the results of this benchmark are sensitive to the mesh
refinement and timestepping parameters. Here we have nine refinement levels,
and refine according to density and the compositional fields.
```{literalinclude} crameri_benchmark_2.prm
```
Unlike the first benchmark, for case two there is no (semi) analytical
solution to compare against. Furthermore, the time integration for this
benchmark is much longer, allowing for errors to accumulate. As such, there is
considerably more scatter between the participating codes. does, however, fall
within the range of the other results, and the curve is somewhat less wiggly.
The results for maximum topography versus time are shown {numref}`fig:crameri-2-comparison`.
The precise values for topography at a given time are quite dependent on the
resolution and timestepping parameters. Following {cite:t}`crameri:etal:2012` we
investigate the convergence of the maximum topography at 3 Ma as a function of
CFL number and mesh resolution. The results are shown in {numref}`fig:crameri-benchmark-convergence`.
```{figure-md} fig:crameri-benchmark-convergence
Convergence for case two. Left: Logarithm of the error with decreasing CFL number. As the CFL number decreases, the error gets smaller. However, once it reaches a value of ∼ 0.1, there stops being much improvement in accuracy. Right: Logarithm of the error with increasing maximum mesh resolution. As the resolution increases, so does the accuracy.
```
We find that at 3 Ma converges to a maximum topography of $\sim 396$
meters. This is slightly different from what MILAMIN_VEP reported as its
convergent value in {cite:t}`crameri:etal:2012`, but still well within the range of
variation of the codes. Additionally, we note that is able to achieve good
results with relatively less mesh resolution due to the ability to adaptively
refine in the regions of interest (namely, the blob and the high viscosity
lid).
Accuracy improves roughly linearly with decreasing CFL number, though stops
improving at CFL $\sim 0.1$. Accuracy also improves with increasing mesh
resolution, though its convergence order does not seem to be excellent. It is
possible that other mesh refinement parameters than we tried in this benchmark
could improve the convergence. The primary challenge in accuracy is limiting
numerical diffusion of the rising blob. If the blob becomes too diffuse, its
ability to lift topography is diminished. It would be instructive to compare
the results of this benchmark using particles with the results using
compositional fields.