From 7880d924ee4f27a39ac68243a005fb6d7c5efbab Mon Sep 17 00:00:00 2001 From: Humberto Medina Date: Sun, 22 Sep 2024 03:41:58 +0100 Subject: [PATCH] statement of need draft --- joss-paper/paper.md | 19 ++++--------------- 1 file changed, 4 insertions(+), 15 deletions(-) diff --git a/joss-paper/paper.md b/joss-paper/paper.md index a4c7299e..a8006943 100644 --- a/joss-paper/paper.md +++ b/joss-paper/paper.md @@ -15,35 +15,27 @@ authors: affiliation: 1 - name: Chris Ellis orcid: 0000-0000-0000-0000 - corresponding: true affiliation: 1 - name: Tom Mazin orcid: 0000-0000-0000-0000 - corresponding: true affiliation: 1 - name: Oscar Osborne orcid: 0000-0000-0000-0000 - corresponding: true affiliation: 1 - name: Timothy Ward orcid: 0000-0000-0000-0000 - corresponding: true affiliation: 1 - name: Stephen Ambrose orcid: 0000-0000-0000-0000 - corresponding: true affiliation: 1 - name: Svetlana Aleksandrova orcid: 0000-0000-0000-0000 - corresponding: true - affiliation: 1 + affiliation: 2 - name: Benjamin Rothwell orcid: 0000-0000-0000-0000 - corresponding: true affiliation: 1 - name: Carol Eastwick orcid: 0000-0000-0000-0000 - corresponding: true affiliation: 1 affiliations: - name: The University of Nottingham, UK @@ -62,12 +54,9 @@ Understanding the behaviour of fluid flow, such as air over a wing, water in a p # Statement of need -- Existing CFD solvers -- Commercial and open-source -- General limitations -- Existing CFD solvers in the Julia ecosystem -- How we fill the gap -- What XCALibre.jl offers +Given the importance of fluid flow simulation in engineering applications, it is not surprising that there is a wealth of CFD solvers available, both open-source and commercially available. Well established open-source codes include: OpenFOAM, SU2, CODE_SATURN, Gerris, etc. It is a testament to the open-source philosophy, and their developers, that some of these codes offer almost feature parity with commercial codes. However, the more feature-rich open-source codes have large codebases and, for performance reasons, have been implemented in statically compiled languages which makes it difficult to adapt and incorporate recent trends in scientific computing, for example, GPU computing and interfacing with machine learning frameworks, which is also the case for commercial codes (to a larger extent due to their closed source nature where interfaces to code internals can be quite rigid – although thanks to access to more resources commercial codes have been steadily ported to work on GPUs). As a result, the research community has been actively developing new CFD codes, which is evident within the Julia ecosystem. +The Julia programming language offers a fresh approach to scientific computing, with the benefits of dynamism whilst retaining the performance of statically typed languages thanks to its just-in-time compilation approach (using LLVM compiler technology). Thus, Julia makes it easy to prototype and test new ideas whilst producing machine code that is performant. This simplicity-performance dualism has resulted in a remarkable growth in its ecosystem offering for scientific computing, which includes state-of-the-art packages for solving differential equations (`DifferentialEquations.jl`), building machine learning models (`Flux.jl`, `Knet.jl` and `Lux.jl`), optimisation frameworks (`JUMP.jl`, XXX and XXX, and more), automatic differentiation (), etc. Likewise, CFD packages have also been developed, most notoriously: `Oceananigans.jl`, which provides tools for ocean modelling, `Trixi.jl` which provides high-order for solvers using the Discontinuous Garlekin method, and `Waterlilly.jl` which implements the immerse boundary method on structured grids using a staggered finite volume method. In this context, `XCALibre.jl` aims to complement and extend the Julia ecosystem by providing a cell-centred and unstructured finite volume CFD framework for the simulation of both incompressible and weakly compressible flows. + `Gala` is an Astropy-affiliated Python package for galactic dynamics. Python