My research activities are mainly focused on numerical analysis and numerical methods for fluid dynamics problems. Since my PhD thesis, I am particularly interested in parallel-in-time methods. I am also interested in domain decomposition methods and reduced-order models. See below for more details on these topics:
The application domains of my research include atmospheric circulation modeling (using the shallow water equations), urban flood modeling (using the shallow water and porosity-based shallow water equations) and nearshore wave propagation modeling (using nonlinear dispersive models such as the KdV and Boussinesq equations). Numerical methods include finite differences, volumes, spectral methods, semi-Lagrangian methods, exponential methods and semi-Lagrangian exponential methods, as well as parallel-in-time and domain decomposition methods.
Some related publications:
J. G. Caldas Steinstraesser, P. da Silva Peixoto, and M. Schreiber, “A second-order semi-Lagrangian exponential scheme with application to the shallow-water equations on the rotating sphere”, ESAIM Mathematical Modelling and Numerical Analysis (M2AN), vol. 59 (2025), pp. 1531-1564. PDF arXiv
J. G. Caldas Steinstraesser, C. Delenne, P. Finaud-Guyot, V. Guinot, J. L. Kahn Casapia, and A. Rousseau,“SW2D-LEMON: a new software for upscaled shallow water modeling”, in SimHydro 2021, 2021 PDF
E. Audusse, J. G. Caldas Steinstraesser, L. Emerald, P. Heinrich, A. Paris, and M. Parisot, “Comparison of models for the simulation of landslide generated tsunamis”, in Proceedings CEMRACS 2019, ESAIM: ProcS, 70:14–30. PDF DOI
Atmospheric circulation modeling
Urban flood modeling
Predictor-corrector iterative Parallel-in-Time (PinT) methods, such as Parareal, MGRIT and PFASST, seek to replace the traditional serial time-stepping approach by the simultaneous computation of several time steps. Their objective is to take more advantage of massively parallel computing systems and accelerate the numerical simulation of time-dependent problems. However, despite their successful application to parabolic problems, PinT methods suffer from stability and convergence issues when applied to simple hyperbolic ones, which has discouraged their application to more complex advection-dominated models, such as those arising in fluid dynamics. My main objective is to better understand these issues, study parametric choices and formulate new PinT approaches in order to give steps towards the temporal parallelization of complex and operational fluid problems.
Some related publications:
J. G. Caldas Steinstraesser, P. d. S. Peixoto e M. Schreiber, “Parallel-in-time integration of the shallow water equations on the rotating sphere using Parareal and MGRIT”, Journal of Computational Physics, vol. 496, p. 112 591, jan. de 2024. PDF arXiv
J. G. Caldas Steinstraesser, V. Guinot, and A. Rousseau, “Modified parareal method for solving the two-dimensional nonlinear shallow water equations using finite volumes”, The SMAI Journal of Computational Mathematics, Volume 7 (2021), pp. 159-184. PDF DOI
PhD thesis in Applied Mathematics (Inria - LEMON team / University of Montpellier, France), 2021: "Coupling large and small scale shallow water models with porosity in the presence of anisotropy". Supervised by Vincent Guinot and Antoine Rousseau. PDF Slides
Domain decomposition methods (DDM) allow solving spatial-dependent differential equations by decomposing the spatial domain into two or more subdomains and solving the problem in each of them. The Schwarz methods, formulated by Schwarz in 1870 and further developed by Lions in the 1980s in the context of parallel computing, are iterative DDMs: when dividing the spatial domain, one needs to define unknown boundary conditions at the artificial interfaces, and the iterations allow correcting these conditions progressively. Among the several parameters determining the convergence of Schwarz methods, my research mainly focuses on formulating and studying optimal boundary operators, called transparent boundary conditions (TBCs), at the interface between subdomains, both on the continuous and discrete levels. These optimal operators yield immediate convergence of the DDM method, but are, in general, difficult to formulate and implement, even in the case of linear problems. The main applications of my work in this subject concern fluid dynamics problems.
Some related publications:
J. G. Caldas Steinstraesser, G. Kemlin, and A. Rousseau, “A domain decomposition method for linearized Boussinesq-type equations”, Journal of Mathematical Study, vol. 52, no. 3, pp. 320–340, 2019.PDF DOI
J. G. Caldas Steinstraesser, R. Cienfuegos, J. D. Galaz Mora, and A. Rousseau, “A Schwarz-based domain decomposition method for the dispersion equation”, Journal of Applied Analysis and Computation, vol. 8,no. 3, pp. 859–872, Jun. 2018.PDF DOI
J. G. Caldas Steinstraesser, G. Kemlin, and A. Rousseau, “Domain decomposition methods for linearized Boussinesq-type equations”, in 16èmes Journées de l’Hydrodynamique, École Centrale de Marseille and Irphé (Institut de Recherche sur les Phenomènes Hors Équilibre), Marseille, France, Nov. 2018. PDF