TUFLOW General Discussion: Difference between revisions

The implicit approach is to estimate the future state based on the current state and the future rate of change. There are two common approaches to this “circular reference” problem. One is to reformulate the equations as a matrix problem, and the other is to use an iterative approach whereby the future state is repeatedly updated after successive calculations of the rate of change at the future time – also known as a backward implicit scheme. Both approaches can be very stable and enable larger timesteps, but the solution is permitted to “skip over” physics that happens on timescales smaller than the time increment. The timestep must still be appropriate based on Courant, Celerity, and Peclet numbers, but due to the iterative nature of the solution the time step can often be 10-20 times larger than that required for an explicit solution.<br>

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== What is the difference between a finite difference scheme and a finite volume scheme? ==

A finite difference scheme considers the solution data at discrete points (or nodes) in space and attempts to compute the time derivatives based on the solution data and its spatial derivatives evaluated at those discrete points. While this approach can be relatively simple to implement, the solution is often non-conservative, i.e. the total sum of a certain property (that should be conserved) over all points in the model might increase or decrease slightly from one timestep to the next even in the absence of internal sources or boundary fluxes.<br>

Tuflow HPC utilises an explicit finite volume scheme. This means that it has to use smaller timesteps and is guaranteed to capture the shortest time-scale physics that the given spatial resolution admits. The solution is conserving of mass and momentum to numerical precision. The scheme is not as computationally efficient as the implicit finite difference scheme of TUFLOW classic, if forced to execute on a single CPU core it is many times slower than classic. However, as the cell-by-cell computation of fluxes and derivatives are completely independent, the scheme is well suited to utilise highly parallelised compute hardware such as modern GPUs. The end result is that with a good GPU, TUFLOW HPC can be up to 100 times faster than classic for some models.<br>

== Do I require a TUFLOW licence to create TUFLOW inputs and view results from a TUFLOW simulation? ==

No, a TUFLOW licence is only needed to run simulations. All TUFLOW inputs and outputs use free open formats that are read and editable by third party software, for example QGIS and Notepad++: