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MODULO: Introduction

MODULO (MODal mULtiscale pOd) is a software developed at the von Karman Institute for Fluid Dynamics to perform data-driven modal decompositions. Initially focused on the Multiscale Proper Orthogonal Decomposition (mPOD), it has recently been extended to perform also other decompositions that include POD, SPODs, DFT, DMD, mPOD.

What are data-driven decompositions? Some literature

Data-driven decompositions seek to partition a dataset as a linear combination of elementary contributions called modes. For a brief overview of the context, we refer to:

The first article also presents the first version of MODULO and its GUI developed by D. Ninni (available in the Old_Matlab_Implementation branch). The second article introduces MODULO v2 from this branch and alternative open source projects. While many projects allows for computing common decompositions such as POD, DMD and the SPODs, MODULO is currently the only opensource code allowing to compute the mPOD.

For a more comprehensive overview on the theory of data-driven decompositions, we refer to the chapter:

  • Mendez, M. A. (2023) “Generalized and Multiscale Modal Analysis”. In : Mendez M.A., Ianiro, A., Noack, B.R., Brunton, S. L. (Eds), “Data-Driven Fluid Mechanics: Combining First Principles and Machine Learning”. Cambridge University Press, 2023:153-181. https://doi.org/10.1017/9781108896214.013. The pre-print is available at https://arxiv.org/abs/2208.12630.

and the article that first presented the complete theory of the mPOD :

The first version of the mPOD was based on wavelet decomposition and was presented here :

Ongoing works on nonlinear methods are discussed here:

Some examples of applications of mPOD for processing experimental and numerical are listed below:

  • Zhang ,Y., Ma, H., Guo, G. (2023), Multi-scale proper orthogonal decomposition (mPOD) analysis of vortex evolution and viscous dissipation in a circular-cylinder wake controlled by parallel symmetric jets, Ocean Engineering, 289(2), 116280 (https://doi.org/10.1016/j.oceaneng.2023.116280)

  • Chi, C., Thevenin, D., Smits, A.J., Wolligandt, S., Theisel, H (2022),Identification and analysis of very-large-scale turbulent motions using multiscale proper orthogonal decomposition, Phys Rev. Fluids 7, 084603, https://doi.org/10.1103/PhysRevFluids.7.084603

  • Procaci, A., Kamal, M.M., Mendez, M.A., Hochgreg, S., Coussement, A., Parente, A. (2022) Multi-scale proper orthogonal decomposition analysis of instabilities in swirled and stratified flames, Physics of Fluids 34, 124103, https://doi.org/10.1063/5.0127956

  • Barreiro-Villaverde, Gosset, A., Mendez, M.A. (2021), On the dynamics of jet wiping: Numerical simulations and modal analysis, Physics of Fluids 33, 062114, https://doi.org/10.1063/5.0051451

  • Esposito, C., Mendez, M.A., Steelant, J., Vetrano, M.R. (2021), Spectral and modal analysis of a cavitating flow through an orifice, Experimental Thermal and Fluid Science, Vol 121, February 2021, 110251, https://doi.org/10.1016/j.expthermflusci.2020.110251

  • Mendez, M.A., Hess, D. Watz, B., Buchlin, J.-M. (2020) Multiscale proper orthogonal decomposition (mPOD) of TR-PIV data—a case study on stationary and transient cylinder wake flows, Meas. Sci. Technol. 31 https://iopscience.iop.org/article/10.1088/1361-6501/ab82be/meta. Preprint at https://arxiv.org/abs/2001.01971.

  • Mendez, M.A., Gosset, A., Buchlin, J.-M. (2019) Experimental Analysis of the Stability of the Jet Wiping Process, Part II: Multiscale Modal Analysis of the Gas Jet-Liquid Film Interaction, Experimental Thermal and Fluid Science, Vol 106, September 2019, pp. 48-67 (https://doi.org/10.1016/j.expthermflusci.2019.03.004).

Previous versions of MODULO

The first version was developed in Matlab and was equipped with a GUI by D. Ninni. A minicourse on data-driven decompositions and the usage of MODULO was provided here:

https://www.youtube.com/watch?v=ED3x00H4yN4&list=PLEJZLD0-4PeKW6Ze984q08bNz28GTntkR&index=1

Although much of the material covered in these videos is still relevant, a new version of this minicourse is being prepared. This is a compressed version of the course “Data-Driven Modal Analysis” that I give as part of the Research Master Program at the von Karman Institute (https://www.vki.ac.be/index.php/research-master-in-fluid-dynamics)

This first MODULO version implemented POD, DFT and mPOD and was already equipped with the first version of the memory-saving feature. The GUI was also available as an executable that the user could install without needing a Matlab license.

This first version is still accessible from the branch “Old_Matlab_Implementation”, but it is no longer maintained.

The main functions were then imported to Python, and L. Schena developed the first package PyPi. A tutorial on how to use that version is given here:

https://www.youtube.com/watch?v=y2uSvdxAwHk&list=PLEJZLD0-4PeKW6Ze984q08bNz28GTntkR&index=9

The current architecture of MODULO v2 is built from that version but has been considerably expanded. This first Python version is still accessible from the branch “Old_Python_Implementation” together with the first (unpackaged) versions of the codes. These are still used in some courses for didactic purposes.