Fernando Salazar
Fernando Salazar
Dirección de correo verificada de
Citado por
Citado por
Data-based models for the prediction of dam behaviour: a review and some methodological considerations
F Salazar, R Morán, MÁ Toledo, E Oñate
Archives of Computational Methods in Engineering 24 (1), 1-21, 2017
Possibilities of the particle finite element method for fluid–soil–structure interaction problems
E Oñate, MA Celigueta, SR Idelsohn, F Salazar, B Suárez
Computational Mechanics 48 (3), 307-318, 2011
An empirical comparison of machine learning techniques for dam behaviour modelling
RM F Salazar, MÁ Toledo, E Oñate
Structural Safety 56 (doi:10.1016/j.strusafe.2015.05.0), 9-17, 2015
Interpretation of dam deformation and leakage with boosted regression trees
F Salazar, MÁ Toledo, E Oñate, B Suárez
Engineering Structures 119, 230-251, 2016
Numerical modelling of landslide‐generated waves with the particle finite element method (PFEM) and a non‐Newtonian flow model
F Salazar, J Irazábal, A Larese, E Oñate
International Journal for Numerical and Analytical Methods in Geomechanics …, 2016
Numerical modelling of granular materials with spherical discrete particles and the bounded rolling friction model. Application to railway ballast
J Irazábal, F Salazar, E Oñate
Computers and Geotechnics 85, 220-229, 2017
Early detection of anomalies in dam performance: A methodology based on boosted regression trees
F Salazar, MÁ Toledo, JM González, E Oñate
Structural Control and Health Monitoring 24 (11), e2012, 2017
Development and validation of a multivariate predictive model for rheumatoid arthritis mortality using a machine learning approach
JM Lezcano-Valverde, F Salazar, L León, E Toledano, JA Jover, ...
Scientific reports 7 (1), 10189, 2017
Analysis of the discharge capacity of radial-gated spillways using CFD and ANN–Oliana Dam case study
F Salazar, R Morán, R Rossi, E Oñate
Journal of Hydraulic Research 51 (3), 244-252, 2013
Modelación numérica de deslizamientos de ladera en embalses mediante el método de partículas y elementos finitos (PFEM)
F Salazar, E Oñate, R Morán
Revista Internacional de Métodos Numéricos para Cálculo y Diseño en …, 2012
A Performance Comparison of Machine Learning Algorithms for Arced Labyrinth Spillways
F Salazar, BM Crookston
Water 11 (3), 544, 2019
Physical and numerical modeling of labyrinth weirs with polyhedral bottom
J San Mauro, F Salazar, MA Toledo, FJ Caballero, C Ponce-Farfan, ...
Ingeniería del Agua 20 (3), 127-138, 2016
Engaging soft computing in material and modeling uncertainty quantification of dam engineering problems
MA Hariri-Ardebili, F Salazar
Soft Computing 24 (15), 11583-11604, 2020
A machine learning based methodology for anomaly detection in dam behaviour
F Salazar, E Oñate, MÁ Toledo
PhD Thesis Universitat Politecnica de Catalunya, 2017
Validation of Machine Learning Models for Structural Dam Behaviour Interpretation and Prediction
J Mata, F Salazar, J Barateiro, A Antunes
Water 13 (19), 2717, 2021
Physical and numerical modeling for understanding the hydraulic behaviour of Wedge-Shaped-Blocks spillways
FJ Caballero, F Salazar, J San Mauro, MÁ Toledo
Dam Protections against Overtopping and Accidental Leakage, 193, 2015
Effect of the integration scheme on the rotation of non-spherical particles with the discrete element method
J Irazábal, F Salazar, M Santasusana, E Oñate
Computational Particle Mechanics 6 (4), 545-559, 2019
Numerical analysis of railway ballast behaviour using the Discrete Element Method
JI González, E Oñate, F Salazar
Monograph CIMNE, 2018
An Interactive Tool for Automatic Predimensioning and Numerical Modeling of Arch Dams
DJ Vicente, J San Mauro, F Salazar, CM Baena
Mathematical Problems in Engineering 2017, 2017
Advances in the understanding of the hydraulic behavior of wedge-shape block spillways
FJ Caballero, MÁ Toledo, R Morán, J San Mauro, F Salazar
Protections 2016: 2nd International Seminar on Dam Protection Against …, 2017
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20