Volgen
Carlos Mauricio Ruiz-Díaz
Carlos Mauricio Ruiz-Díaz
Estudiante de doctorado en ciencias (Ingeniería Mecánica) en la Universidad de São Paulo
Geverifieerd e-mailadres voor usp.br - Homepage
Titel
Geciteerd door
Geciteerd door
Jaar
Estudio de los fluidos aceite-agua a través del sensor basado en la permitividad eléctrica del patrón de fluido
MM Hernández-Cely, CM Ruiz-Diaz
Revista UIS Ingenierías 19 (3), 177-186, 2020
122020
Modelo predictivo para la identificación de la fracción volumétrica en flujo bifásico
CM Ruiz-Diaz, MM Hernández-Cely, OA González-Estrada
Ciencia en Desarrollo 12 (2), 2021
72021
Specialist system in flow pattern identification using artificial neural Networks
JAG Camperos, CMR Diaz, MMH Cely
Journal of Applied Engineering Science 21 (1), 285-299, 2023
62023
Hybrid machine learning model applied to phase inversion prediction in liquid-liquid pipe flow
PB Bazon, JE Castro-Bolivar, CM Ruiz-Diaz, MM Hernández-Cely, ...
Multiphase Science and Technology 35 (1), 2023
42023
Analysis of liquid-liquid (water and oil) two-phase flow in vertical pipes, applying artificial intelligence techniques
CM Ruiz-Diaz, MM Hernández-Cely, OA González-Estrada
Journal of Physics: Conference Series 2046 (1), 012016, 2021
42021
Two-phase oil and water flow pattern identification in vertical pipes applying long short-term memory networks
CM Ruiz-Díaz, B Quispe-Suarez, OA González-Estrada
Emergent Materials 7 (5), 1983-1995, 2024
32024
Two-Phase Flow Pattern Identification in Vertical Pipes Using Transformer Neural Networks
CM Ruiz-Díaz, EE Perilla-Plata, OA González-Estrada
Inventions 9 (1), 15, 2024
32024
Modelo predictivo para el cálculo de la fracción volumétrica de un flujo bifásico agua-aceite en la horizontal utilizando una red neuronal artificial
CM Ruiz-Díaz, MM Hernández-Cely, OAG Estrada
Revista UIS ingenierías 21 (2), 155-164, 2022
32022
Flow pattern identification of liquid-liquid (oil and water) in vertical pipelines using machine learning techniques
CM Ruiz-Diaz, JA Gómez-Camperos, MM Hernández-Cely
Journal of Physics: Conference Series 2163 (1), 012001, 2022
32022
A Predictive Model for the Identification of the Volume Fraction in Two-Phase Flow
CM Ruiz-Diaz, MM Hernández-Cely, OA González-Estrada
Ciencia en Desarrollo 12 (2), 49-55, 2021
32021
Predictive modeling of holdup in horizontal wateroil flow using a neural network approach
C Díaz, OA González-Estrada, M Cely
14th WCCM-ECCOMAS Congress, no. January. Paris, Francia: CIMNE, 11-15, 2021
32021
Chordal measurement of phase fraction distribution in a static gas-liquid system using collimated gamma-ray densitometer and artificial neural networks
CEÁ Pacheco, CMR Diaz, OMH Rodriguez
Revista Ingenio 21 (1), 29-35, 2024
2024
Detecção de anomalias em tubulações de transporte de petróleo e gás utilizando long short-term memory networks
MS Carr, CM Ruiz Diaz, OM Hernandez Rodriguez
Livro de Resumos Expandidos, 2023
2023
Metodologia experimental para simular vazamentos em plataformas offshore usando escoamento bifásico gás denso/óleo
CM Ruiz Diaz, OM Hernandez Rodriguez
Anais, 2023
2023
Modelo predictivo para el cálculo de la fracción volumétrica de un flujo bifásico agua-aceite en la horizontal utilizando una red neuronal artificial
CMR Diaz, MMH Cely, OAG Estrada
Revista UIS Ingenierías 21 (2), 155-164, 2022
2022
Análises de escoamentos multifásicos através de redes neurais artificiais
HL Cavalheiro, CMR Diaz, MMH Cely
Universidade Federal de Pelotas, 2022
2022
Experimental insights into Dense-Gas/Liquid two-phase flow in horizontal and inclined pipes
CMR Diaz, AT Postal, OMH Rodriguez
COB-2023-0185 CHORDAL MEASUREMENT OF PHASE FRACTION DISTRIBUTION IN STRATIFIED FLOW PATTERN IN DENSE-GAS/LIQUID PIPE FLOW VIA GAMMA-RAY DENSITOMETRY.
CE Alvarez-Pacheco, CM Ruiz-Diaz, LFA Alegria, OMH Rodriguez
DETERMINATION OF VOLUMETRIC FRACTION IN OIL-WATER TWO-PHASE FLOW THROUGH WIRE-MESH SENSOR AND ARTIFICIAL NEURAL NETWORKS
MMH Cely, CMR Diaz, S Pagliarini, OMH Rodriguez, EAG Peñaloza
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–19