Research articles using Fortran

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associated with the paper

Bovari, Emmanuel, Gael Giraud, and Florent McIsaac. “Financial impacts of climate change mitigation policies and their macroeconomic implications: a stock-flow consistent approach.” Climate Policy 20.2 (2020): 179-198.

and

associated with the paper

@article{aldaas2021robust,
    Author = {Al Daas, Hussam and Jolivet, Pierre and Scott, Jennifer A.},
    Title = {A Robust Algebraic Domain Decomposition Preconditioner for Sparse Normal Equations},
    Year = {2021},
    Journal = {SIAM Journal on Scientific Computing},
    Pages = {submitted for publication},
    Url = {https://github.com/prj-/aldaas2021robust}
}
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The repo has both Matlab and Fortran versions of the program associated with the paper.

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I created a GitHub repo Research Articles Using Fortran. Here are some GitHub codes and associated papers that I don’t think have been posted on this thread.

CPDINV: Software for estimating Curie depth using centroid method with wavelet spectrum and Fourier spectrum , for paper
Yin Y.H, Li C.-F., Lu Y., 2021, “Estimating Curie-point depths using both wavelet-based and Fourier spectral centroid methods in the western Pacific marginal seas.” Geophysical Journal International, DOI: 10.1093/gji/ggab257

ULMAtp for paper
Felipe O.S. Zanon, Osis E.S. Leal, Alberto De Conti, “Implementation of the universal line model in the alternative transients program”, Electric Power Systems Research, vol. 197, p. 107311, Aug. 2021, doi: 10.1016/j.epsr.2021.107311.

fctables: Fortran 2003 program that computes FC-Gram tables and SPECTER (Special Periodic Continuation Turbulence Solver) for paper
Fontana, M., Bruno, O. P., Mininni P. D. & Dmitruk P.; “Fourier continuation method for incompressible fluids with boundaries”. Comp. Phys. Comm. 256, 107482 (2020).DOI: 10.1016/j.cpc.2020.107482.
and paper
Rosenberg D. L., Mininni P. D., Reddy R. & Pouquet A.; “GPU parallelization of a hybrid pseudospectral fluid turbulence framework using CUDA” Atmosphere 11, 178 (2020). DOI: 10.3390/atmos11020178.

Town Energy Balance (TEB) model for paper
Meyer, D., Schoetter, R., Masson, V., Grimmond, S., 2020: Enhanced software and platform for the Town Energy Balance (TEB) model. Journal of Open Source Software, 5(50), 2008.

Supersonic TuRbulEnt Accelerated navier stokes Solver (STREAMS) for paper
Bernardini, M., Modesti, D., Salvadore, F., & Pirozzoli, S. (2021). STREAmS: A high-fidelity accelerated solver for direct numerical simulation of compressible turbulent flows. Computer Physics Communications, 263, 107906.

Incompact3d: Fortran-MPI based, finite difference high-performance code for solving the incompressible Navier-Stokes equation for paper
(2021) Schuch, F. N., Meiburg, E., & Silvestrini, J. H., “Plunging criterion for particle-laden flows over sloping bottoms: Three-dimensional turbulence-resolving simulations”, Computers & Geosciences, 104880,
and many other papers listed here

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From @Beliavsky (cannot post 3 times in a row):

For the Research articles using Fortran thread:

Another batch – see this repo for a cumulative list.

FFTE: A Fast Fourier Transform Package (version 7.0) for paper
Daisuke Takahashi: “Implementation of Parallel 3-D Real FFT with 2-D Decomposition on Intel Xeon Phi Clusters”, Proc. 13th International Conference on Parallel Processing and Applied Mathematics (PPAM 2019), Part I, Lecture Notes in Computer Science, Vol. 12043, pp. 151-161, Springer (2020).

Hormonal-regulation-of-growth-in-juvenile-fish for paper
17 FEBRUARY 2020, Open Biology, “Hormones as adaptive control systems in juvenile fish”, by Jacqueline Weidner, Camilla Håkonsrud Jensen , Jarl Giske, Sigrunn Eliassen, and Christian Jørgensen

angio: 3D phase-field modelling for tumor angiogenesis for paper
M. Moreira-Soares, R. Coimbra, L. Rebelo, J. Carvalho & R. D. M. Travasso. “Angiogenic Factors produced by Hypoxic Cells are a leading driver of Anastomoses in Sprouting Angiogenesis–a computational study”. Scientific Reports 8, 8726 (2018)

d3q and thermal2 for
“Limits of the quasiharmonic approximation in MgO: Volume dependence of optical modes investigated by infrared reflectivity and ab initio calculations” E Calandrini, L Paulatto, et.al. Physical Review B 103 (5), 054302 (2021)
“Functional Monochalcogenides: Raman Evidence Linking Properties, Structure, and Metavalent Bonding” C Bellin, et.al. Physical Review Letters 125 (14), 145301 (2020)
“Thermal conductivity of from bulk to thin films: Theory and experiment”. L Paulatto, D Fournier, M Marangolo, M Eddrief, P Atkinson, M Calandra Physical Review B 101 (20), 205419 (2020)
“Anharmonic coupling, thermal transport and acoustic wave attenuation in cubic semiconductors and bismuth” . M Markov, J Sjakste, N Vast, B Perrin, L Paulatto Journal of Physics: Conference Series 1461 (1), 012165 (2020)

Scalable Computing for Advanced Library and Environment (SCALE) for
Sato, Y., Y. Miyamoto, and H. Tomita, 2021, Lightning frequency in an idealized hurricane-like vortex from initial to steady-state using a coupled meteorological and explicit bulk lightning model. Mon. Wea. Rev., 149, 753-771, doi:10.1175/MWR-D-20-0110.1

and other papers

F2A: aero-hydro-servo-elastic for performing fully coupled analysis of floating offshore wind turbines for paper
Yang, Y., Bashir, M., Michailides, C., Li, C., & Wang, J. (2020). Development and application of an aero-hydro-servo-elastic coupling framework for analysis of floating offshore wind turbines. Renewable Energy,161 (23): 606-625. Redirecting

Multi-component Flow Code (MFC) for papers
S. H. Bryngelson, K. Schmidmayer, V. Coralic, K. Maeda, J. Meng, T. Colonius (2020). “MFC: An open-source high-order multi-component, multi-phase, and multi-scale compressible flow solver” Computer Physics Communications 4655, 107396
S. H. Bryngelson and T. Colonius (2020). “Simulation of humpback whale bubble-net feeding models” Journal of the Acoustical Society of America, Vol. 147, pp. 1126-1135
K. Schmidmayer, S. H. Bryngelson, T. Colonius (2020). “An assessment of multicomponent flow models and interface capturing schemes for spherical bubble dynamics” Journal of Computational Physics, Vol. 402, 109080

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F. Roters, M. Diehl, P. Shanthraj, P. Eisenlohr, C. Reuber, S.L. Wong, T. Maiti, A. Ebrahimi, T. Hochrainer, H.-O. Fabritius, S. Nikolov, M. Friák, N. Fujita, N. Grilli, K.G.F. Janssens, N. Jia, P.J.J. Kok, D. Ma, F. Meier, E. Werner, M. Stricker, D. Weygand, D. Raabe
DAMASK – The Düsseldorf Advanced Material Simulation Kit for modeling multi-physics crystal plasticity, thermal, and damage phenomena from the single crystal up to the component scale
Computational Materials Science 158 (2019)
https://doi.org/10.1016/j.commatsci.2018.04.030.

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Another batch from the cumulative list:

Wogan_and_Catling_2020_pre_revisions for paper
Nicholas F. Wogan and David C. Catling (2020). “When is Chemical Disequilibrium in Earth-like Planetary Atmospheres a Biosignature versus an Anti-biosignature? Disequilibria from Dead to Living Worlds”, The Astrophysical Journal, Volume 892, Number 2

WorkflowCodes for paper
Jie Liu & Regenauer-Lieb, (2021). “Applications of percolation theory on micro-tomography of rocks, Earth-Science Reviews”, V.104, 103519, doi: 10.1016/j.earscirev.2021.103519

EOF for paper
Shr-Chuan Yang & Tony Wen-Hann Sheu (2021). “Analysis of electro-osmotic flow by lattice Boltzmann simulation and Helmholtz-Smoluchowski formula”, Numerical Heat Transfer, Part B: Fundamentals, 79:3, 130-149, https://doi.org/10.1080/10407790.2020.1819694

SUTRASET: extended USGS SUTRA model with incorporation of seepage, evaporation and tide for
Shen, C., Zhang, C., Xin, P., Kong, J., & Li, L. (2018). “Salt Dynamics in Coastal Marshes: Formation of Hypersaline Zones”. Water Resources Research, 1–18. https://doi.org/10.1029/2017WR022021
America, Ilja, Zhang, Chenming, Werner, Adrian D. and Zee, Sjoerd E. A. T. M. (2020). “Evaporation and salt accumulation effects on riparian freshwater lenses”. Water Resources Research, https://doi.org/10.1029/2019wr026380

Soil and Water Erosion Tool (SWAT+) for
Wu, J., H. Yen, J. G. Arnold, Y. E. Yang, X. Cai, M. J. White, S. Chinnasamy, C. Miao, R. Srinivasan (2020) “Development of Reservoir Operation Functions in SWAT+ for National Environmental Assessment.” Journal of Hydrology, 583, 124556. Redirecting and other papers

siQ-ChIP: sans spike-in Quantitative ChIP-seq for
J Biol Chem. 2020 Nov 20;295(47):15826-15837. Redirecting. Epub 2020 Sep 29. “A physical basis for quantitative ChIP-sequencing” by Bradley M Dickson, Rochelle L Tiedemann, Alison A Chomiak, Evan M Cornett, Robert M Vaughan, and Scott B Rothbart

GIMPM-SSA-Damage for
Huth, A., Duddu, R., & Smith, B. (2021a). A generalized interpolation material point method for shallow ice shelves. 1: Shallow shelf approximation and ice thickness evolution. Journal of Advances in Modeling Earth Systems, 13, e2020MS002277. https://doi.org/10.1029/2020MS002277
Huth, A., Duddu, R., & Smith, B. (2021b). A generalized interpolation material point method for shallow ice shelves. 2: Anisotropic nonlocal damage mechanics and rift propagation. Journal of Advances in Modeling Earth Systems, 13, e2020MS002292. https://doi.org/10.1029/2020MS002292

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Another batch from the cumulative list, including a paper from @nicholaswogan

gpmaterials for paper
Computers & Structures, Volume 255, 15 October 2021, 106635, “Damage-driven strain localisation in networks of fibres: A computational homogenisation approach” by Felipe Figueredo Rocha, Pablo Javier Blanco, Pablo Javier Sánchez, Eduardode Souza Neto, and Raúl Antonino Feijóo and other papers

Quasi-DYNamic earthquake simulator (qdyn) for paper
M. van den Ende, J. Chen, J.P. Ampuero and A. Niemeijer, “Rheological transitions facilitate fault‐spanning ruptures on seismically active and creeping faults”, J. of Geophys. Res.: Solid Earth (doi:10.1029/2019JB019328) and other papers

Symplectic Integration Methods for Particle Loss Estimation (SIMPLE) for
C. G. Albert, S. V. Kasilov, and W. Kernbichler, “Symplectic integration with non-canonical quadrature for guiding-center orbits in magnetic confinement devices”. J. Comp. Phys 403, 109065 (2020), Redirecting, preprint on [1903.06885] Symplectic integration with non-canonical quadrature for guiding-center orbits in magnetic confinement devices

disorder for paper
“Algorithm for generating irreducible site-occupancy configurations”, by Ji-Chun Lian, Hong-Yu Wu, Wei-Qing Huang, Wangyu Hu, and Gui-Fang Huang, Phys. Rev. B 102, 134209 – Published 22 October 2020

VolcGases for paper
“Abundant Atmospheric Methane from Volcanism on Terrestrial Planets Is Unlikely and Strengthens the Case for Methane as a Biosignature”, by Nicholas Wogan, Joshua Krissansen-Totton, and David C. Catling, Published 2020 October 29, The Planetary Science Journal, Volume 1, Number 3

specfab for
Rathmann, N., Hvidberg, C., Grinsted, A., Lilien, D., & Dahl-Jensen, D. (2021). Effect of an orientation-dependent non-linear grain fluidity on bulk directional enhancement factors. Journal of Glaciology, 67(263), 569-575. doi:10.1017/jog.2020.117 and
Rathmann, N., & Lilien, D. (2021). Inferred basal friction and mass flux affected by crystal-orientation fabrics. Journal of Glaciology, 1-17. doi:10.1017/jog.2021.88

arXiv preprint: Accelerating an Iterative Eigensolver for Nuclear Structure Configuration Interaction Calculations on GPUs using OpenACC,

To accelerate the solution of large eigenvalue problems arising from many-body calculations in nuclear physics on distributed-memory parallel systems equipped with general-purpose Graphic Processing Units (GPUs), we modified a previously developed hybrid MPI/OpenMP implementation of an eigensolver written in FORTRAN 90 by using an OpenACC directives based programming model.

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Articles from The Journal of Open Source Software (free downloads) in the last year with a Fortran tag:

Coral: a parallel spectral solver for fluid dynamics and partial differential equations

uDALES: large-eddy-simulation software for urban flow, dispersion, and microclimate modelling

J2suscep: Calculation of magnetic exchange coupling and temperature dependence of magnetic susceptibility

Nyx: A Massively Parallel AMR Code for Computational Cosmology

h5fortran: object-oriented polymorphic Fortran interface for HDF5 file IO

geoclaw-landspill: an oil land-spill and overland flow simulator for pipeline rupture events

ParaMonte: A high-performance serial/parallel Monte Carlo simulation library for C, C++, Fortran

Simulating instrumental systematics of Cosmic Microwave Background experiments with s4cmb

UltraNest - a robust, general purpose Bayesian inference engine

The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained

hawen: time-harmonic wave modeling and inversion using hybridizable discontinuous Galerkin discretization

nap: A molecular dynamics package with parameter-optimization programs for classical and machine-learning potentials

gospl: Global Scalable Paleo Landscape Evolution

FHI-vibes: Ab Initio Vibrational Simulations

PorousFlow: a multiphysics simulation code for coupled problems in porous media

ELECTRIC: Electric fields Leveraged from multipole Expansion Calculations in Tinker Rapid Interface Code

pyOptSparse: A Python framework for large-scale constrained nonlinear optimization of sparse systems

CASTRO: A Massively Parallel Compressible Astrophysics Simulation Code

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A couple of publications from the domain of computational chemistry based on open source Fortran projects I’m familiar with. I give the main publication introducing the respective project and linked the associated source code for all of them, there you will usually find a section with more publications related to the development of those projects.

  • C. Bannwarth, E. Caldeweyher, S. Ehlert, A. Hansen, P. Pracht, J. Seibert, S. Spicher, S. Grimme, Extended tight-binding quantum chemistry methods, WIREs Comput. Mol. Sci. 11, e1493 (2021). DOI: 10.1002/wcms.1493 (xtb source code)

  • B. Hourahine, B. Aradi, V. Blum, F. Bonafé, A. Buccheri, C. Camacho, C. Cevallos, M. Y. Deshaye, T. Dumitrică, A. Dominguez, S. Ehlert, M. Elstner, T. van der Heide, J. Hermann, S. Irle, J. J. Kranz, C. Köhler, T. Kowalczyk, T. Kubař, I. S. Lee, V. Lutsker, R. J. Maurer, S. K. Min, I. Mitchell, C. Negre, T. A. Niehaus, A. M. N. Niklasson, A. J. Page, A. Pecchia, G. Penazzi, M. P. Persson, J. Řezáč, C. G. Sánchez, M. Sternberg, M. Stöhr, F. Stuckenberg, A. Tkatchenko, V. W.-z. Yu, and T. Frauenheim, DFTB+, a software package for efficient approximate density functional theory based atomistic simulations, J. Chem. Phys. 152, 124101 (2020), DOI: 10.1063/1.5143190 (dftb+ source code)

  • P. Pracht, F. Bohle, S. Grimme , Automated exploration of the low-energy chemical space with fast quantum chemical methods, Phys. Chem. Chem. Phys. (2020), 22 , 7169–7192. DOI: 10.1039/c9cp06869d (crest source code)

  • E. Caldeweyher, S. Ehlert, A. Hansen, H. Neugebauer, S. Spicher, C. Bannwarth, S. Grimme, A generally applicable atomic-charge dependent London dispersion correction, J. Chem. Phys., 150 , 154122 (2019). DOI: 10.1063/1.5090222 (dftd4 source code)

  • W. Dawson and T. Nakajima, Comput. Phys. Commun. 225 , 154 (2018). DOI: 10.1016/j.cpc.2017.12.010 (ntpoly source code)

  • V. W.-z. Yu, F. Corsetti, A. García, W. P. Huhn, M. Jacquelin, W. Jia, B. Lange, L. Lin, J. Lu, W. Mi, A. Seifitokaldani, Á. Vázquez-Mayagoitia, C. Yang, H. Yang, and V. Blum, Comput. Phys. Commun. 222, 267 (2018). DOI: 10.1016/j.cpc.2017.09.007 (elsi source code)

  • A. Marek, V. Blum, R. Johanni, V. Havu, B. Lang, T. Auckenthaler, A. Heinecke, H. J. Bungartz, and H. Lederer, J. Phys.: Condens. Matter 26 , 213201 (2014). DOI: 10.1088/0953-8984/26/21/213201 (elpa source code)

  • S. Grimme, A simplified Tamm-Dancoff density functional approach for the electronic excitation spectra of very large molecules, J. Chem. Phys. 138, 244104 (2013). DOI: 10.1063/1.4811331 (stda source code)

  • S. Grimme, Towards First Principles Calculation of Electron Impact Mass Spectra of Molecules, Angew. Chem. Int. Ed. 52 , 6306-6312 (2013). DOI: 10.1002/anie.201300158 (qcxms source code)

  • H. Kruse, S. Grimme , A geometrical correction for the inter- and intra-molecular basis set superposition error in Hartree-Fock and density functional theory calculations for large systems, J. Chem. Phys. 136 , 154101 (2012). DOI:10.1063/1.3700154 (gcp source code)

  • S. Grimme , J. Antony, S. Ehrlich, H. Krieg, A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu, J. Chem. Phys. 132 , 154104 (2010). DOI:10.1063/1.3382344 (dftd3 source code)

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Here’s another one… And I apologize to the community for using the term FORTRAN 90 in it (it makes my eyes bleed now as I write this):

P. Costa. “A FFT-based finite-difference solver for massively-parallel direct numerical simulations of turbulent flows.” Computers & Mathematics with Applications 76.8 (2018): 1853-1862. arXiv preprint | CaNS source code

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The paper A Fortran-Keras Deep Learning Bridge for Scientific Computing, co-authored by @milancurcic (congratulations!), was named Article of the Year 2020 for the journal Scientific Programming. The associated GitHub repo is here.

Abstract

Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way bridge connects environments where deep learning resources are plentiful with those where they are scarce. The paper describes several unique features offered by FKB, such as customizable layers, loss functions, and network ensembles. The paper concludes with a case study that applies FKB to address open questions about the robustness of an experimental approach to global climate simulation, in which subgrid physics are outsourced to deep neural network emulators. In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to be transferred and used in Fortran. Such a process allows the model’s emergent behavior to be assessed, i.e., when fit imperfections are coupled to explicit planetary-scale fluid dynamics. The results reveal a previously unrecognized strong relationship between offline validation error and online performance, in which the choice of the optimizer proves unexpectedly critical. This in turn reveals many new neural network architectures that produce considerable improvements in climate model stability including some with reduced error, for an especially challenging training dataset.

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Thanks! I didn’t know about it. :slight_smile:

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The Black hole accretion code

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Do you know why they use the .t extension instead of .f90?

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There are curly braces in, atleast some, .t files.

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There are curly braces in, atleast some, .t files.

Yes, probably a preprocessor is used?

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Sorry, it’s in French:

But at the end of this small page you will find the links towards the three cited Fortran codes:

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Thanks – it’s quite readable with Google Translate.

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Mais non, pas du tout Monsieur … no reason to worry.

(The addition of IDRIS’ lectures about Fortran à la Française here followed an earlier call by @Beliavsky, too.)

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