![]() The next step of reading in an STL file was straightforward, and then I used the STL data to mark the grid with ‘cut-cells’ where the STL triangles intersect the mesh cells. The first part of the code to be completed was the writing of the VTK solution a simple 100x100x100 (1 million) cell mesh was written out and then read into ParaView, and that was the starting point. The code was written ‘back-to-front’ in some ways. ![]() The solver code was developed over about a year, using gfortran throughout. Now the software compiles in a 32-bit Linux mode also, although that version is largely untested. But that’s not at all bad for freeware on laptop at home. The F1 car demo that I started ran at approx 3 iterations per minute on 8 processors, which means a weekend is required for 10,000 iterations of a 20 million cell mesh. This was a leap forward for the CFD software since (with minor modifications to the source code) the 64-bit parallel solver became easily achievable. (), which fortunately allowed 64-bit compilation using the OpenMP flag. The version of gfortran that I eventually used was from So then the limiting factor becomes the number of processors that you have available. I then did a 20 million cell mesh on a F1 car and found that this used only 3GB RAM. Then after the 64-bit executable was available, the max mesh size depends how much RAM you have available on your machine/cluster. I initially found that the limit of the 32-bit solver was about 10 million cells. This allows the user to specify small arrays for small problems, and vice-versa. The solver is streamlined in terms of the arrays which are stored no additional arrays are stored unless they have to be stored, and all arrays are allocated. That said, for simple test cases it is feasible to complete the CFD cycle (geometry to flow solution) within an hour, when familiar with the format of the simple input text file.Īnother of the driving forces was to reduce the RAM dependency of the solver. Obviously the solver time depends on other factors such as mesh size and available brute force (number of CPU and RAM). One of the driving forces behind the new software comes from impatience, meaning that I should be able to obtain a geometry, setup the test-case and run the solver within an hour or two this is certainly true whatever the geometry (whether it be a simple cylinder/sphere or an F1 car). When CFD is made this easy-to-use, it becomes both more accessible and applicable. ![]() By simplified framework, I mean 1) get geometry and solver, 2) edit input text file, 3) run solver, and 4) visualise the solution using ParaView. Having used snappyHex Mesh, I wanted something that could also robustly handle complex STL geometry, but in a much more simplified framework. The aims of this new CFD freeware were driven by problems with some of the existing CFD methods, namely cost, excessive time spent meshing, over complexity of solvers, and accessibility (for a wide range of users). Like many, I first came to use ParaView whilst using OpenFoam, and after that came to use ParaView for other tasks such as STL file viewing and manipulation. The geometry (in STL format) is the main input to the CFD solver, and the solver output is mainly a ParaView VTK file and some convergence data. The software uses (and relies upon) ParaView for pre and post-processing of the solver inputs and outputs. The software named “ufo-cfd” is available from, and is loosely described as a ‘freeware aerodynamics CFD solver’ (but is not open-source). During the last year, a new computational fluid dynamics (cfd) software has been made available as freeware for public use.
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