Publicacións

@article{hilo_computational_2026,

title = {Computational modelling of hydrodynamic loads on offshore monopiles in concurrent wave and current conditions},

author = {Ali Kareem Hilo-Al-Behadili and Félix Nieto-Mouronte and Gabriel Barajas and Javier L. Lara and Byoung-Kwon Ahn and Antonio J. Álvarez-Naveira and Hrvoje Kozmar},

url = {https://www.sciencedirect.com/science/article/pii/S0029801826000387},

doi = {10.1016/j.oceaneng.2026.124204},

issn = {0029-8018},

year  = {2026},

date = {2026-04-01},

urldate = {2026-08-17},

journal = {Ocean Engineering},

volume = {352},

pages = {124204},

abstract = {Offshore monopile wind-turbine systems face significant design challenges due to complex environmental loading conditions, including wind, waves, current, and their intricate coupling effects. Computational Fluid Dynamics (CFD) simulations of complex nonlinear wave-structure interactions have become essential for understanding offshore systems. However, high-fidelity (HF) CFD analyses are computationally demanding, making it impractical to use them alone for extensive parametric studies. Surrogate models provide a promising alternative, as they can deliver efficient and accurate predictions once trained. This study presents a methodology for combining HF computational models and a data-driven approach to assess hydrodynamic loads on an offshore monopile subjected to waves and current. A three-dimensional numerical wave tank was developed in the OpenFOAM environment and validated using experimental and theoretical data. This model accurately accounts for complex wave-current interactions and the resulting force variations on the monopile. The obtained results indicate that the hydrodynamic forces on the monopile are significantly affected when waves and current act concurrently. To reduce the extensive computational HF simulations, a Gaussian Process Regression (GPR)-based surrogate model was developed using HF simulations sampled via Latin Hypercube Sampling. The surrogate model was trained to predict peak inline and transverse forces for various wave heights, frequencies, and current velocities. The GPR model exhibits high accuracy with R2 = 0.98 (coefficient of determination) and MAE = 0.03 (Mean Absolute Error) for the inline force, and R2 = 0.94 and MAE = 0.01 for the transverse force, thus demonstrating its ability to accurately assess complex nonlinear responses, while reducing the computational demand significantly. These findings provide a practical and applicable solution for offshore structural design, especially during early-stage assessments or probabilistic load evaluations.},

keywords = {Computational fluid dynamics, Current, Gaussian process regression, Hydrodynamic forces, Offshore monopile, Surrogate model, Wave},

pubstate = {published},

tppubtype = {article}

}

@article{garcia-feal_iberwq_2020,

title = {IberWQ: A GPU Accelerated Tool for 2D Water Quality Modeling in Rivers and Estuaries},

author = {Orlando García-Feal and Luis Cea-Gómez and José González-Cao and José Manuel Domínguez and Moncho Gómez-Gesteira},

url = {https://www.mdpi.com/2073-4441/12/2/413},

doi = {10.3390/w12020413},

issn = {2073-4441},

year  = {2020},

date = {2020-02-01},

urldate = {2026-08-06},

journal = {Water},

volume = {12},

number = {2},

pages = {413},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {Numerical models are useful tools to analyze water quality by computing the concentration of physical, chemical and biological parameters. The present work introduces a two-dimensional depth-averaged model that computes the most relevant and frequent parameters used to evaluate water quality. High performance computing (HPC) techniques based on graphic processing unit (GPU) parallelization have been applied to improve the efficiency of the package, providing speed-ups of two orders of magnitude in a standard PC. Several test cases were analyzed to show the capabilities and efficiency of the model to evaluate the environmental status of rivers and non-stratified estuaries. IberWQ will be freely available through the package Iber.},

keywords = {Computational fluid dynamics, CUDA, depth-averaged modeling, environmental quality standards, graphic processing unit (GPU), high performance computing (HPC), Water quality},

pubstate = {published},

tppubtype = {article}

}

@article{nogueira_posteriori-implicit_2020,

title = {An a posteriori-implicit turbulent model with automatic dissipation adjustment for Large Eddy Simulation of compressible flows},

author = {Xesús Nogueira-Garea and Luis Ramírez-Palacios and Javier Fernández-Fidalgo and Michael Deligant and Sofiane Khelladi and Jean-Camille Chassaing and Fermín Navarrina-Martínez},

url = {https://www.sciencedirect.com/science/article/pii/S0045793019303147},

doi = {10.1016/j.compfluid.2019.104371},

issn = {0045-7930},

year  = {2020},

date = {2020-01-01},

urldate = {2026-08-06},

journal = {Computers & Fluids},

volume = {197},

pages = {104371},

abstract = {In this work we present an a posteriori high-order finite volume scheme for the computation of compressible turbulent flows. An automatic dissipation adjustment (ADA) method is combined with the a posteriori paradigm, in order to obtain an implicit subgrid scale model and preserve the stability of the numerical method. Thus, the numerical scheme is designed to increase the dissipation in the control volumes where the flow is under-resolved, and to decrease the dissipation in those cells where there is excessive dissipation. This is achieved by adding a multiplicative factor to the dissipative part of the numerical flux. In order to keep the stability of the numerical scheme, the a posteriori approach is used. It allows to increase the dissipation quickly in cells near shocks if required, ensuring the stability of the scheme. Some numerical tests are performed to highlight the accuracy and robustness of the proposed numerical scheme.},

keywords = {A posteriori shock capturing, Compressible flows, Computational fluid dynamics, High-order methods, Implicit large eddy simulation},

pubstate = {published},

tppubtype = {article}

}

@article{Regueiro-Picallo2016,

title = {Experimental and numerical analysis of egg-shaped sewer pipes flow performance},

author = {Manuel Regueiro-Picallo and Juan Naves-García-Rendueles and Jose Anta-Álvarez and Jerónimo Puertas-Agudo and Joaquín Suárez-López},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010403607&doi=10.3390%2fw8120587&partnerID=40&md5=d5d993ccc06211d1812b90fbd6a21635},

doi = {10.3390/w8120587},

issn = {20734441},

year  = {2016},

date = {2016-01-01},

urldate = {2016-01-01},

journal = {Water (Switzerland)},

volume = {8},

number = {12},

publisher = {MDPI AG},

abstract = {A Computational Fluid Dynamics (CFD) model was developed to analyze the open-channel flow in a new set of egg-shaped pipes for small combined sewer systems. The egg-shaped cross-section was selected after studying several geometries under different flow conditions. Once the egg-shaped cross-section was defined, a real-scale physical model was built and a series of partial-full flow experiments were performed in order to validate the numerical simulations. Furthermore, the numerical velocity distributions were compared with an experimental formulation for analytic geometries, with comparison results indicating a satisfactory concordance. After the hydraulic performance of the egg-shaped pipe was analyzed, the numerical model was used to compare the average velocity and shear stress against an equivalent area circular pipe under low flow conditions. The proposed egg shape showed a better flow performance up to a filling ratio of h/H = 0.25. © 2016 by the authors.},

note = {cited By 15},

keywords = {CFD modeling; Combined sewer systems; Computational fluid dynamics modeling; Egg-shaped cross sections; Egg-shaped section; Experimental and numerical analysis; Hydraulic performance; Sewer design, Computational fluid dynamics, computational fluid dynamics; geometry; low flow; numerical method; pipe flow; pipeline; sewer network; shear stress, Numerical models; Open channel flow; Sewers; Shear flow; Shear stress; Velocity distribution; Water pipelines},

pubstate = {published},

tppubtype = {article}

}