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docs/paper/paper.bib

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@@ -85,7 +85,6 @@ @inproceedings{Kaus_Popov_Baumann_Pusok_Bauville_Fernandez_Collignon_2016
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rights={All rights reserved},
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ISBN={978-3-95806-109-5},
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url={http://hdl.handle.net/2128/9842},
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doi={2128/9842},
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booktitle={NIC Series},
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author={Kaus, Boris JP and Popov, Anton A. and Baumann, T. and Pusok, A. and Bauville, Arthur and Fernandez, Naiara and Collignon, Marine},
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year={2016},

docs/paper/paper.md

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@@ -176,7 +176,7 @@ julia> Tomo_rect = project_CartData(Tomo_rect, Tomo_Alps, proj);
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julia> write_paraview(Tomo_rect,"Tomo_rect");
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julia> write_paraview(Topo_rect,"Topo_rect");
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```
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We can now use the built-in tools of Paraview to visualise the data (see \autoref{fig:basic} b), and use this as inspiration to create an initial numerical model setup. It is also possible to interpolate other seismic tomography datasets to the same grid and subsequently compute a _votemap_ to count in how many tomographic models a specific seismic anomaly is present [see, e.g., @Shephard_Matthews_Hosseini_Domeier_2017].
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We can now use the built-in tools of Paraview to visualise the data (see \autoref{fig:basic} b), and use this as inspiration to create an initial numerical model setup. It is also possible to interpolate other seismic tomography datasets to the same grid and subsequently compute a _votemap_ to count how many tomographic models contain a specific seismic anomaly [see, e.g., @Shephard_Matthews_Hosseini_Domeier_2017].
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# Examples of usage
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`GeophysicalModelGenerator.jl` comes with build-in (CI/CD) tests and [tutorials](https://juliageodynamics.github.io/GeophysicalModelGenerator.jl/dev) that explain the most important use cases, from importing data to generating input model setups for numerical simulations. In the following, we present a number of examples that illustrate various aspects of the package. Many additional tutorials are available in the online documentation.
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![Example of a geodynamic setup of a subducting oceanic plate beneath a continental lithosphere with a smoothly bending slab. \label{fig:slab3d}](../src/assets/img/Mechanical3D_Tutorial_2.png){ width=100% }
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# Acknowledgements
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We acknowledge funding from ERC Consolidator Grant 771143 (MAGMA) by the German Ministry of Science and Education (BMBF) as part of project DEGREE, by the CHEESE-2p Center of Excellence (co-funded by both EuroHPC-JU and the BMBF), by the German Research Foundation (DFG grants TH2076/7-1 and KA3367/10-1) as part of the SPP 2017 4DMB project project, and by DFG Emmy Noether grant TH2076/8-1.
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We acknowledge funding by 1) the European Research Council as part of Consolidator Grant 771143 (MAGMA), 2) the German Research Foundation through DFG grants KA3367/10-1, TH2076/7-1 (both part of the SPP 2017 4D-MB project) and Emmy Noether grant TH2076/8-1, 3) the German Ministry of Science and Education (BMBF) through project DEGREE, and 4) by the CHEESE-2p Center of Excellence, co-funded by both EuroHPC-JU and the BMBF.
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# References

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