Publicacións

@article{deligant_very_2025,

title = {Very high order finite volume solver for multi component two-phase flow with phase change using a posteriori Multi-dimensional Optimal Order Detection},

author = {Michael Deligant and Carlos-Jesús Romero-Casado and Xesús Nogueira-Garea and Luis Ramírez-Palacios and Mathieu Specklin and Farid Bakir and Sofiane Khelladi},

url = {https://www.sciencedirect.com/science/article/pii/S0045793024003402},

doi = {10.1016/j.compfluid.2024.106509},

issn = {0045-7930},

year  = {2025},

date = {2025-02-01},

urldate = {2025-02-01},

journal = {Computers & Fluids},

volume = {288},

pages = {106509},

abstract = {In this work we propose a very high-order compressible finite volume scheme with a posteriori stabilization for the computation of multi-component two-phase flow with phase change. It is based on finite volume approach using moving least squares (MLS) reproducing kernels for high order reconstruction of the Riemann states. Increased robustness is achieved by using the multi-dimensional optimal order detection (MOOD) method to get a high-accurate and low-dissipation scheme while maintaining boundedness and preventing numerical oscillations at interfaces and strong gradient zones. The properties of the proposed framework are demonstrated on classical test problems starting with convergence order verification on simple scalar advection test cases. More complex shock and more stringent tube tests with various water, steam and air concentration are then simulated and compared with available references in the literature. Finally, the ability of the proposed approach to compute multi-component flows with phase change is illustrated with the simulation of a liquid oxygen jet in gaseous hydrogen.},

keywords = {Homogeneous relaxation model, MOOD, Multi-dimensional Optimal Order Detection, Two-phase flow},

pubstate = {published},

tppubtype = {article}

}

@article{farmakis_weno_2020,

title = {WENO schemes on unstructured meshes using a relaxed textita posteriori MOOD limiting approach},

author = {Pericles S. Farmakis and Panagiotis Tsoutsanis and Xesús Nogueira-Garea},

url = {https://www.sciencedirect.com/science/article/pii/S0045782520301043},

doi = {10.1016/j.cma.2020.112921},

issn = {0045-7825},

year  = {2020},

date = {2020-05-01},

urldate = {2026-08-06},

journal = {Computer Methods in Applied Mechanics and Engineering},

volume = {363},

pages = {112921},

abstract = {In this paper a relaxed formulation of the a posteriori Multi-dimensional Optimal Order Detection (MOOD) limiting approach is introduced for weighted essentially non-oscillatory (WENO) finite volume schemes on unstructured meshes. The main goal is to minimise the computational footprint of the MOOD limiting approach by employing WENO schemes—by virtue of requiring a smaller number of cells to reduce their order of accuracy compared to an unlimited scheme. The key characteristic of the present relaxed MOOD formulation is that the Numerical Admissible Detector (NAD) is not uniquely defined for all orders of spatial accuracy, and it is relaxed when reaching a 2nd-order of accuracy. The augmented numerical schemes are applied to the 2D unsteady Euler equations for a multitude of test problems including the 2D vortex evolution, cylindrical explosion, double-Mach reflection, and an implosion. It is observed that in many events, the implemented MOOD paradigm manages to preserve symmetry of the forming structures in simulations, an improvement comparing to the non-MOOD limited counterparts which cannot be easily obtained due to the multi-dimensional reconstruction nature of the schemes.},

keywords = {MOOD, RMI, UCNS3D, Unstructured, WENO},

pubstate = {published},

tppubtype = {article}

}