Add joss paper to main for 1.1.0 release

.github/workflows/draft-pdf.yml

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+name: Draft PDF
+on: [push]
+
+jobs:
+  paper:
+    runs-on: ubuntu-latest
+    name: Paper Draft
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - name: Build draft PDF
+        uses: openjournals/openjournals-draft-action@master
+        with:
+          journal: joss
+          # This should be the path to the paper within your repo.
+          paper-path: doc/paper.md
+      - name: Upload
+        uses: actions/upload-artifact@v4
+        with:
+          name: paper
+          # This is the output path where Pandoc will write the compiled
+          # PDF. Note, this should be the same directory as the input
+          # paper.md
+          path: doc/paper.pdf

doc/paper.bib

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+@article{openfoam,
+   abstract = {In this article the principles of the field operation and manipulation (FOAM) C++class library for continuum mechanics are outlined. Our intention is to make it as easy as possible to develop reliable and efficient computational continuum-mechanics codes: this is achieved by making the top-level syntax of the code as close as possible to conventional mathematical notation for tensors and partial differential equations. Object-orientation techniques enable the creation of data types that closely mimic those of continuum mechanics, and the operator overloading possible in C++ allows normal mathematical symbols to be used for the basic operations. As an example, the implementation of various types of turbulence modeling in a FOAM computational-fluid-dynamics code is discussed, and calculations performed on a standard test case, that of flow around a square prism, are presented. To demonstrate the flexibility of the FOAM library, codes for solving structures and magnetohydrodynamics are also presented with appropriate test case results given.},
+   author = {H. G. Weller and G. Tabor and H. Jasak and C. Fureby},
+   doi = {10.1063/1.168744},
+   issn = {08941866},
+   issue = {6},
+   journal = {Computers in Physics},
+   pages = {620},
+   title = {A tensorial approach to computational continuum mechanics using object-oriented techniques},
+   volume = {12},
+   year = {1998},
+}
+
+@techreport{ALE3D,
+  title={ALE3D: An arbitrary Lagrangian-Eulerian multi-physics code},
+  author={Noble, Charles R and Anderson, Andrew T and Barton, Nathan R and Bramwell, Jamie A and Capps, Arlie and Chang, Michael H and Chou, Jin J and Dawson, David M and Diana, Emily R and Dunn, Timothy A and others},
+  year={2017},
+  institution={Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States)}
+}
+
+@Manual{FLOW-3D,
+  author = {Flow Science, Inc.},
+  title = {FLOW-3D, Version~2023R1},
+  year = {2023},
+  address = {Santa Fe, NM},
+  url = {https://www.flow3d.com/}
+}
+
+@manual{abaqus,
+  title        = {Abaqus Documentation},
+  author       = {{Dassault Systèmes Simulia Corp.}},
+  organization = {Dassault Systèmes},
+  address      = {Providence, RI, USA},
+  year         = {2024},
+  note         = {Version 2024},
+  url          = {https://www.3ds.com/products-services/simulia/products/abaqus/}
+}
+
+@manual{ansys,
+  title        = {ANSYS Documentation},
+  author       = {{ANSYS Inc.}},
+  organization = {ANSYS Inc.},
+  address      = {Canonsburg, PA, USA},
+  year         = {2024},
+  note         = {Release 2024 R1},
+  url          = {https://www.ansys.com/products/structures/ansys-mechanical}
+}
+
+@software{adamantine,
+  author = {Turcksin, Bruno and DeWitt, Stephen},
+  doi = {10.11578/dc.20211129.1},
+  title = {{adamantine}},
+  url = {https://github.com/adamantine-sim/adamantine}
+}
+
+@Article{deal.ii,
+  title   = {The \texttt{deal.II} Library, Version 9.5},
+  author  = {Daniel Arndt and Wolfgang Bangerth and Maximilian Bergbauer and
+             Marco Feder and Marc Fehling and Johannes Heinz and
+             Timo Heister and Luca Heltai and Martin Kronbichler and
+             Matthias Maier and Peter Munch and Jean-Paul Pelteret and
+             Bruno Turcksin and David Wells and Stefano Zampini},
+  journal = {Journal of Numerical Mathematics},
+  year    = {2023},
+  doi     = {10.1515/jnma-2023-0089},
+  pages   = {231--246},
+  volume  = {31},
+  number  = {3},
+  url     = {https://dealii.org/deal95-preprint.pdf}
+}
+
+@article{exaca,
+  title={ExaCA: A performance portable exascale cellular automata application for alloy solidification modeling},
+  author={Rolchigo, Matt and Reeve, Samuel Temple and Stump, Benjamin and Knapp, Gerald L and Coleman, John and Plotkowski, Alex and Belak, James},
+  journal={Computational Materials Science},
+  volume={214},
+  pages={111692},
+  year={2022},
+  publisher={Elsevier}
+}
+
+@article{texture-regimes,
+title = {Grain structure and texture selection regimes in metal powder bed fusion},
+journal = {Additive Manufacturing},
+volume = {81},
+pages = {104024},
+year = {2024},
+issn = {2214-8604},
+doi = {10.1016/j.addma.2024.104024},
+url = {https://www.sciencedirect.com/science/article/pii/S2214860424000708},
+author = {Matt Rolchigo and John Coleman and Gerry L. Knapp and Alex Plotkowski}
+}
+
+@article{knapp,
+title = {Calibrating uncertain parameters in melt pool simulations of additive manufacturing},
+journal = {Computational Materials Science},
+volume = {218},
+pages = {111904},
+year = {2023},
+issn = {0927-0256},
+doi = {10.1016/j.commatsci.2022.111904},
+url = {https://www.sciencedirect.com/science/article/pii/S0927025622006152},
+author = {G.L. Knapp and J. Coleman and M. Rolchigo and M. Stoyanov and A. Plotkowski}
+}
+
+@article{haines-1,
+  title = {Experimental and computational analysis of site-specific formation of phases in laser powder bed fusion 17–4 precipitate hardened stainless steel},
+  journal = {Additive Manufacturing},
+  volume = {73},
+  pages = {103686},
+  year = {2023},
+  issn = {2214-8604},
+  doi = {10.1016/j.addma.2023.103686},
+  url = {https://www.sciencedirect.com/science/article/pii/S2214860423002993},
+  author = {Michael P. Haines and Maxwell S. Moyle and Vitor V. Rielli and Vladimir Luzin and Nima Haghdadi and Sophie Primig}
+}
+
+@article{haines-2,
+  title = {Role of scan strategies and heat treatment on grain structure evolution in Fe-Si soft magnetic alloys made by laser-powder bed fusion},
+  journal = {Additive Manufacturing},
+  volume = {50},
+  pages = {102578},
+  year = {2022},
+  issn = {2214-8604},
+  doi = {10.1016/j.addma.2021.102578},
+  url = {https://www.sciencedirect.com/science/article/pii/S2214860421007259},
+  author = {MP Haines and F. List and K. Carver and DN Leonard and A. Plotkowski and CM Fancher and RR Dehoff and SS Babu}
+}
+
+@article{plotkowski,
+  author = {Plotkowski, A. and Coleman, J. and Fancher, C. M. and Haines, M. P. and Whetten, S. R. and Kustas, A. B.},
+  year = {2024},
+  title = {Grain Structure Evolution in Fe-6Si During Directed Energy Deposition},
+  journal = {JOM},
+  pages = {1031},
+  volume = {76},
+  number = {3},
+  doi = {10.1007/s11837-023-06279-3}
+}
+
+@software{AdditiveFOAM_1.0.0,
+  author       = {John Coleman and
+                  Kellis Kincaid and
+                  Gerald L. Knapp and
+                  Benjamin Stump and
+                  Alexander J. Plotkowski},
+  title        = {AdditiveFOAM: Release 1.0},
+  month        = jun,
+  year         = 2023,
+  publisher    = {Zenodo},
+  version      = {1.0.0},
+  doi          = {10.5281/zenodo.8034098}
+}
+
+@INPROCEEDINGS{zoltan,
+ AUTHOR = "K.D. Devine and E.G. Boman and L.A. Riesen and U.V. Catalyurek 
+          and C. Chevalier",
+ TITLE = "Getting Started with Zoltan:  A Short Tutorial",
+ BOOKTITLE = "Proc. of 2009 Dagstuhl Seminar on Combinatorial Scientific 
+              Computing", 
+ YEAR = "2009",
+ NOTE = "Also available as Sandia National Labs Tech Report SAND2009-0578C."
+}
+
+@article{amb2018,
+  title={Outcomes and conclusions from the 2018 AM-Bench measurements, challenge problems, modeling submissions, and conference},
+  author={Levine, Lyle E. and
+          Lane, Brandon M. and
+          Heigel, Jarred C. and
+          Migler, Kalman and
+          Stoudt, Mark R. and
+          Phan, Thien Q. and
+          Ricker, Richard E. and
+          Strantza, Maria and
+          Hill, Martin R. and
+          Zhang, Fan and
+          Seppala, Jonathan and
+          Garboczi, Edward and
+          Bain, Erich and
+          Cole, Daniel and
+          Allen, Andrew and
+          Fox, Jason and
+          Campbell, Carelyn},
+  journal={Integrating Materials and Manufacturing Innovation},
+  volume={9},
+  number={3},
+  pages={362--377},
+  year={2020},
+  publisher={Springer},
+  doi={10.1007/s40192-019-00164-1}
+}
+
+

doc/paper.md

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+---
+title: 'AdditiveFOAM: A Continuum Multiphysics Code for Additive Manufacturing'
+tags:
+  - Computational Fluid Dynamics
+  - Heat Transfer
+  - Mass Transfer
+  - Additive Manufacturing
+  - OpenFOAM
+authors:
+  - name: John Coleman
+    affiliation: "1"
+    corresponding: true
+  - name: Kellis Kincaid
+    affiliation: "2"
+  - name: Gerry L. Knapp
+    affiliation: "3"
+  - name: Benjamin Stump
+    affiliation: "1"
+  - name: Samuel Reeve
+    affiliation: "1"
+  - name: Matt Rolchigo
+    affiliation: "1"
+  - name: Alex Plotkowski
+    affiliation: "1"
+affiliations:
+ - name: Computational Science and Engineering Division, Oak Ridge National Laboratory
+   index: 1
+ - name: Nuclear Energy and Fuel Cycle Division, Oak Ridge National Laboratory
+   index: 2
+ - name: Material Science and Technology Division, Oak Ridge National Laboratory
+   index: 3
+date: 12 June 2024
+bibliography: paper.bib
+---
+
+# Summary
+
+AdditiveFOAM is a computational framework that simulates transport phenomena in Additive Manufacturing (AM) processes. It is built on OpenFOAM [@openfoam], the leading free, open-source software package for computational fluid dynamics (CFD). OpenFOAM offers an extensible platform for solving complex multiphysics problems using state-of-the-art finite volume methods. AdditiveFOAM leverages these capabilities to develop specialized tools aimed at addressing challenges in AM processing.
+
+Metal additive manufacturing, also known as metal 3D printing, is an advanced manufacturing technique that creates physical parts from a three-dimensional (3D) digital model by melting metal powder or wire feedstock. A significant area of research in metal AM focuses on process planning to mitigate anomalous features during printing that are deleterious to part performance (e.g., porosity and cracking), as well as controlling localized microstructure and material properties. Given the high costs and substantial time requirements associated with experimental methods for qualifying new materials and processes, there is a compelling incentive for researchers to utilize advanced computational simulations. In this context, AdditiveFOAM offers a simulation framework to better understand undesirable features in printing, thereby enhancing process planning and reducing the reliance on labor-intensive experimental campaigns.
+
+# Statement of need
+
+Numerical models for AM traditionally seek to represent physics at a single length scale depending on the target question. Two main categories of models with available software solutions are distinguished: 1) high-fidelity melt pool-scale models, and 2) part-scale heat transfer models.
+
+The first category contains models that seek to resolve all relevant physics within the melt pool. These models can produce excellent agreement with experiments and offer insights into the underlying causes of anomalous features during processing, but are generally expensive to run, limiting the scan length that can be simulated to a few millimeters with current computational resources. Due to their computational expense, these models are well-suited for use at specialized research institutions with large HPC infrastructure to answer target questions about melt pool scale physical phenomena. For example, ALE3D [@ALE3D] is a versatile multiphysics simulation tool that uses the Arbitrary Lagrangian-Eulerian approach and has been used for powder-resolved simulations of laser-material interactions in AM. However, ALE3D is a limited access code for use by United States Department of Defense/Energy laboratories and their contractors, while ALE3D4I is available for U.S. companies and academics through individual use agreements. Alternatively, FLOW-3D [@FLOW-3D] is a commercial CFD software known for its capabilities in simulating complex free-surface problems, and it has several specialized models for AM. However, FLOW-3D is proprietary, meaning its source code is not available for public inspection or modification, and users must purchase a license to use the software.
+
+The second category contains models that simplify melt pool physics to rapidly simulate heat transport, residual stress, and distortion across an entire part. Commercial finite element thermomechanics software solutions built on Abaqus [@abaqus] and Ansys [@ansys] are available; however, these software packages are not open and free to use and develop upon. Alternatively, Adamantine [@adamantine] is a thermomechanics simulation tool built on an open-source software stack designed for high-performance computing across various architectures, including the deal.II finite element software package [@deal.ii], providing an alternative to proprietary software solutions.
+
+There is an established need for intermediate frameworks that accurately predict melt pool shape, thermal gradients, and other meso-scale quantities across an entire part. These models can inform process design decisions through heuristic estimations of anomalous printing features (e.g., keyhole formation and lack-of-fusion) and predict the final microstructure and material properties of AM components. AdditiveFOAM addresses these challenges, featuring a volumetric source term in the energy equation for multiple heat sources, optional Marangoni-driven fluid flow, and a scheme for implementing tabulated thermodynamic pathways for metal alloys.
+
+# Software Features
+The main feature of AdditiveFOAM is a transient, multiphysics application that solves conservation equations for mass, momentum, and energy during AM processing, built upon the OpenFOAM finite volume software package [@openfoam]. This solver includes a novel thermodynamic algorithm enabling variable-order time integration for tabulated thermodynamic pathways. The available time integration schemes are explicit forward Euler, implicit backward Euler, backward differentiation formula (BDF-2), and Crank-Nicolson. An adaptive time integration and time-stepping method automatically switches between implicit and explicit schemes to balance computational cost and solution accuracy depending on the problem state and user-defined tolerances. Additionally, AdditiveFOAM features boundary conditions for Marangoni-driven fluid flow in the melt pool, as well as convective and radiative heat transfer. Another feature of AdditiveFOAM is the volumetric heat source library that supports any number of independently moving sources with distinct energy profiles that have been validated for several AM processes, including laser powder bed fusion (LPBF), directed energy deposition (DED), and electron beam melting (EBM). Finally, AdditiveFOAM leverages existing OpenFOAM libraries to sample thermal data needed for microstructure predictions with a specific library for coupling to the grain structure prediction software ExaCA [@exaca]. Future releases of AdditiveFOAM will focus on resource-optimized adaptive mesh refinement (AMR), dynamic load-balancing using the Zoltan [@zoltan] library, and the integration of next-generation laser profiles (e.g., nLight AFX series) into the volumetric heat source library.
+
+AdditiveFOAM was designed to be used openly by researchers, industry, and academics. It has already been used in several scientific publications primarily focused on studying how AM process planning influences the development of local microstructural features in a part. Select publications that demonstrate AdditiveFOAM’s usage towards understanding the connection between process planning and microstructure evolution in metal AM include:
+
+- Knapp et al. [@knapp] developed an automated framework for statistical calibration of the gaussian heat source parameters available in AdditiveFOAM to accurately predict the melt pool shape, solidification conditions, and solidification grain structure for single track welds on IN625 plate. 
+
+- Rolchigo et al. [@exaca; @texture-regimes] used AdditiveFOAM to generate thermal data for solidification grain structure predictions is laser powder bed fusion, validated against the NIST 2018 AM-Bench dataset [@amb2018]. 
+
+- Haines et al. used AdditiveFOAM to confirm experimentally observed phase transformation pathways in 17–4 PH stainless steel during the laser powder bed fusion (L-PBF) process [@haines-1], and investigated the role of scan strategy on recrystallization and grain growth in Fe-Si steel made by L-PBF with a pulsed laser [@haines-2].
+
+- Plotkowski et al. [@plotkowski] used AdditiveFOAM to confirm experimentally observed grain growth in Fe-Si steel during the Laser Engineered Net Shaping (LENS) process. 
+
+The free, open-source nature of AdditiveFOAM will continue to enable scientific explorations in AM processing. Documentation for AdditiveFOAM is hosted on GitHub pages with the link: https://ornl.github.io/AdditiveFOAM/. 
+
+# Acknowledgements
+
+This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE). The publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. 
+
+This research used resources of the Oak Ridge Leadership Computing Facility (OLCF), supported by DOE under contract DE-AC05-00OR22725. 
+
+This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. 
+
+# References