Diego Queiroz Faria de Menezes

@portal.peq.coppe.ufrj.br

PEQ/COPPE/UFRJ and ISI B&F
COPPETEC and SENAI CETIQT

Diego Queiroz Faria de Menezes


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https://researchid.co/dmenezes
Currently working in the Chemical Engineering Program at UFRJ/COPPETEC and SENAI CETIQT as a researcher. Have research interests in data reconciliation, parameter estimation, robust statistics, time series analysis, distillation, membrane process separation, simulation, modeling, and process optimization. Working as a researcher in the development of monitoring techniques, identification, and diagnosis of failures with an industrial process.

EDUCATION

D.Sc. in Chemical Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Chemical Engineering, Statistics, Probability and Uncertainty, Filtration and Separation, Process Chemistry and Technology
11

Scopus Publications

378

Scholar Citations

7

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Semi-empirical and statistical models for renewable liquid fuel process optimization
    Diego Q.F. de Menezes, Ana Claudia Dias, Raquel de F.D. Milão, Stefano F. Interlenghi, Leandro D.R. Novaes, et al.
    Engineering Science and Technology an International Journal, 2026
    The production of renewable liquid fuels from captured CO2 and green H2 via Proton Exchange Membrane offers a sustainable alternative to fossil fuels, mitigating climate change while optimizing reaction routes to reduce energy consumption. This process involves syngas generation, Fischer–Tropsch Synthesis (FTS), and, when required, downstream upgrading such as hydroprocessing. This study models and simulates a simplified FTS process to enhance real-time optimization, monitoring, and dynamic simulations in Power-to-Liquid routes. Two modeling approaches were developed: a data-driven statistical conversion model and a semi-empirical model using Langmuir-Hinshelwood-Hougen-Watson (LHHW) kinetics with Anderson-Schulz-Flory (ASF) product distribution. These strategies focus on key hydrocarbon fractions, fitting experimental data to reduce model complexity. Results showed high accuracy in predicting syncrude distributions within the experimental range, with the semi-empirical approach showing better robustness across temperature variations. These methods provide a solid foundation for improving real-time monitoring, simulation, and optimization of renewable fuel production.
  • A Robust Numerical Framework for Hollow-Fiber Membrane Module Simulation and Solver Performance Analysis
    Diego Queiroz Faria de Menezes, Marília Caroline Cavalcante de Sá, Nayher Andres Clavijo Vallejo, Thainá Menezes de Melo, Luiz Felipe de Oliveira Campos, Thiago Koichi Anzai, José Carlos Costa da Silva Pinto
    Membranes, 2026
    Robust numerical frameworks are essential for the simulation, design, monitoring, and control of membrane-based separation units, particularly under highly nonlinear and industrially relevant operating conditions. In this context, a comprehensive phenomenological and numerical framework is proposed for the simulation of hollow-fiber membrane modules, incorporating coupled mass, momentum (through pressure drop), and energy transport equations. The governing equations are discretized using a rigorous orthogonal collocation formulation, and the performances of two numerical solution strategies are systematically investigated for the first time to allow the in-line and real-time implementation of the model: a steady-state approach based on the Newton–Raphson method with careful treatment of initial estimates, and a pseudotransient formulation. Particularly, an original and consistent numerical treatment is introduced for the energy balance at boundaries where the permeate flow vanishes, enabling the stable incorporation of thermal effects and Joule–Thomson phenomena. The results clearly show that the steady-state Newton–Raphson approach provides the best overall performance in terms of computational efficiency, numerical robustness, and accuracy when physically consistent initial profiles are employed. In particular, the combination of a linear initial guess and a numerical mesh constituted of four collocation points yielded the most favorable balance between convergence speed, numerical robustness, and accuracy for the base-case sensitivity analysis. For monitoring-oriented applications, the numerical choice should be weighted primarily toward computational performance once physical consistency and convergence criteria are satisfied, rather than toward maximum mesh-refinement accuracy. In this context, small differences in internal-fiber profiles can be compensated through real-time permeance estimation and are negligible when compared with measurement uncertainty in real industrial processes. Under extreme operating conditions involving low concentrations, low flow rates, and highly permeable species, the pseudotransient formulation proved to be a reliable auxiliary strategy, enabling robust convergence when suitable initial guesses were not readily available. The proposed framework is validated against experimental data from the literature and subjected to extensive convergence and sensitivity analyses, providing a reliable basis for simulation and for assessing computational feasibility in in-line and real-time monitoring-oriented applications. A full demonstration of digital-twin integration, online parameter updating, reduced-order coupling, and closed-loop control is beyond the scope of the present study and will be addressed in future work.
  • Use of neural networks for data reconciliation and virtual flow metering in oil wells
    Marcelo F. de S. Alves, Gildeir L. Rabello, Diego Q.F. de Menezes, Rafael M. Soares, Bruno F. Vieira, José Carlos Pinto
    Geoenergy Science and Engineering, 2025
  • Using Machine Learning for wet gas flow metering in an actual production site: detailed methodology and case study
    Aiche Annual Meeting Conference Proceedings, 2025
  • Enhancing virtual flow metering on offshore oil platforms through parallel computing and data reconciliation
    Gildeir L. Rabello, Gabriel M.P. Andrade, Diego Q.F. de Menezes, Rafael M. Soares, Tiago S.M. Lemos, Leonardo D. Ribeiro, Bruno F. Vieira, José Carlos Pinto
    Geoenergy Science and Engineering, 2024
  • Virtual flow metering of production flow rates of individual wells in oil and gas platforms through data reconciliation
    Gabriel M.P. Andrade, Diego Q.F. de Menezes, Rafael M. Soares, Tiago S.M. Lemos, Alex F. Teixeira, Leonardo D. Ribeiro, Bruno F. Vieira, José Carlos Pinto
    Journal of Petroleum Science and Engineering, 2022
  • Modeling of spiral wound membranes for gas separations. Part III: A nonisothermal 2D permeation model
    Tahyná B. Fontoura, Marília Caroline C. de Sá, Diego Q. Faria de Menezes, Bruno Francisco Oechsler, Afrânio Melo, Luiz Felipe de O. Campos, Thiago K. Anzai, Fábio C. Diehl, Pedro H. Thompson, José Carlos Pinto
    Chemical Engineering Research and Design, 2022
  • A review on robust M-estimators for regression analysis
    D.Q.F. de Menezes, D.M. Prata, A.R. Secchi, J.C. Pinto
    Computers and Chemical Engineering, 2021
  • Modeling of spiral wound membranes for gas separations. Part I: An iterative 2D permeation model
    Ana Carolina S. Dias, Marília Caroline C. De Sá, Tahyná B. Fontoura, Diego Q. Menezes, Thiago K. Anzai, Fábio C. Diehl, Pedro H. Thompson, José Carlos Pinto
    Journal of Membrane Science, 2020
  • Modeling of spiral wound membranes for gas separations-part II: Data reconciliation for online monitoring
    Diego Queiroz Faria de Menezes, Marília Caroline Cavalcante de Sá, Tahyná Barbalho Fontoura, Thiago Koichi Anzai, Fabio Cesar Diehl, Pedro Henrique Thompson, Jose Carlos Pinto
    Processes, 2020
    The present work presents a methodology based on data reconciliation to monitor membrane separation processes reliably, online and in real time for the first time. The proposed methodology was implemented in accordance with the following steps: data acquisition; data pre-treatment; data characterization; data reconciliation; gross error detection; and critical evaluation of measured data with a soft sensor. The acquisition of data constituted the slowest stage of the monitoring process, as expected in real-time applications. The pre-treatment stage was fundamental to assure the robustness of the code and the initial characterization of collected data was carried out offline. The characterization of the data showed that steady-state modeling of the process would be appropriate, also allowing the implementation of faster numerical procedures for the data reconciliation step. The data reconciliation step performed well, quickly and consistently. Thus, data reconciliation allowed the estimation of unmeasured variables, playing the role of a soft sensor and allowing the future installation of a digital twin. Additionally, monitoring of measurement bias constituted a tool for measurement diagnosis. As shown in the manuscript, the proposed methodology can be successfully implemented online and in real time for monitoring of membrane separation processes, as shown through a real dashboard web application developed for monitoring of an actual industrial site.
  • Eco-efficiency evaluation of acetone-methanol separation processes using computational simulation
    Patrick V. Mangili, Yuri P.D.M. Souza, Diego Q.F. de Menezes, Lizandro S. Santos, Diego M. Prata
    Chemical Engineering and Processing Process Intensification, 2018

RECENT SCHOLAR PUBLICATIONS

  • Semi-empirical and statistical models for renewable liquid fuel process optimization
    DQF de Menezes, ACS Dias, R de FD Milão, SF Interlenghi, LDR Novaes, ...
    Engineering Science and Technology, an International Journal 78, 102390 , 2026
    2026.0
  • A Robust Numerical Framework for Hollow-Fiber Membrane Module Simulation and Solver Performance Analysis
    DQF de Menezes, MCC de Sá, NAC Vallejo, TM de Melo, LFO Campos, ...
    Membranes 16 (4), 154 , 2026
    2026.0
  • On Machine Learning Approaches for Wet Gas Flow Metering with Actual Data: From Handling Available Data to Developing Models
    MFS Alves, GL Rabello, RM Soares, DQ Menezes, LOV Pereira, JC Pinto
    Offshore Technology Conference Brasil, D031S036R005 , 2025
    2025.0
  • Use of neural networks for data reconciliation and virtual flow metering in oil wells
    MFS Alves, GL Rabello, DQF de Menezes, RM Soares, BF Vieira, ...
    Geoenergy Science and Engineering 246, 213543 , 2025
    2025.0
    Citations: 5
  • Modeling of Spiral Wound Membranes for Gas Separations—Part IV: Real-Time Monitoring Based on Detailed Phenomenological Model
    MCC Sá, DQF Menezes, TB Fontoura, LFO Campos, TK Anzai, FC Diehl, ...
    Processes 12 (11), 2597 , 2024
    2024.0
  • Melhorias em metamodelo para medição virtual via restrição nos dados de treinamento
    MF deSouzaAlves, GL Rabello, DQF de Menezes, R Marinho, ...
    Proceedings of PSE-BR 2024 III Brazilian Congress on Process Systems … , 2024
    2024.0
  • Enhancing virtual flow metering on offshore oil platforms through parallel computing and data reconciliation
    GL Rabello, GMP Andrade, DQF de Menezes, RM Soares, TSM Lemos, ...
    Geoenergy Science and Engineering 235, 212695 , 2024
    2024.0
    Citations: 7
  • Uso de redes neuronais para agilizar a medição de vazões individuais de poços produtores de petróleo na bacia de campos
    MFS Alves, GL Rabello, DQF de Menezes, RM Soares, BF Vieira, ...
    Congresso brasileiro de engenharia química 24 , 2023
    2023.0
    Citations: 2
  • Virtual flow metering of production flow rates of individual wells in oil and gas platforms through data reconciliation
    GMP Andrade, DQF de Menezes, RM Soares, TSM Lemos, AF Teixeira, ...
    Journal of Petroleum Science and Engineering 208, 109772 , 2022
    2022.0
    Citations: 39
  • Modeling of spiral wound membranes for gas separations. Part III: A nonisothermal 2D permeation model
    TB Fontoura, MCC de Sá, DQF de Menezes, BF Oechsler, A Melo, ...
    Chemical Engineering Research and Design 177, 376-393 , 2022
    2022.0
    Citations: 10
  • A review on robust M-estimators for regression analysis
    DQF De Menezes, DM Prata, AR Secchi, JC Pinto
    Computers & Chemical Engineering 147, 107254 , 2021
    2021.0
    Citations: 243
  • Monitoramento de processos de separação baseado em reconciliação de dados
    DQF Menezes
    Universidade Federal do Rio de Janeiro , 2021
    2021.0
    Citations: 3
  • Modeling of spiral wound membranes for gas separations. Part I: An iterative 2D permeation model
    ACS Dias, MCC de Sá, TB Fontoura, DQF de Menezes, TK Anzai, ...
    Journal of Membrane Science 612, 118278 , 2020
    2020.0
    Citations: 19
  • Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring
    DQF de Menezes, MCC de Sá, TB Fontoura, TK Anzai, FC Diehl, ...
    Processes 8 (9), 1035 , 2020
    2020.0
    Citations: 21
  • Eco-efficiency evaluation of acetone-methanol separation processes using computational simulation
    PV Mangili, YPDM Souza, DQF de Menezes, LS Santos, DM Prata
    Chemical Engineering and Processing-Process Intensification 123, 100-110 , 2018
    2018.0
    Citations: 25
  • RECONCILIAÇÃO DE DADOS EM REDES DE TROCADORES DE CALOR UTILIZANDO O SOFTWARE EMSO
    DQF de MENEZES, FC PEIXOTO, DM PRATA
    Blucher Chemical Engineering Proceedings 1 (2), 12496-12503 , 2015
    2015.0
  • Reconciliação de dados em colunas de destilação utilizando o simulador EMSO
    DQF de MENEZES, I SARRUF, FC PEIXOTO, DM PRATA
    Blucher Chemical Engineering Proceedings 1 (2), 12520-12527 , 2015
    2015.0
    Citations: 3
  • RECONCILIAÇÃO DADOS EM PROCESSAMENTO DE MINÉRIO UTILIZANDO O SIMULADOR EMSO
    DQF de MENEZES, S AL, FC PEIXOTO, DM PRATA
    Blucher Chemical Engineering Proceedings 1 (2), 12504-12511 , 2015
    2015.0
  • Reconciliação Robusta de Dados utilizando o Simulador EMSO
    I Sarruf, DQF de Menezes, LS Santos, DM Prata
    Blucher Chemical Engineering Proceedings 1 (2), 11127-11134 , 2015
    2015.0
    Citations: 1
  • 12º CONGRESSO BRASILEIRO DE PESQUISA E DESENVOLVIMENTO EM PETRÓLEO E GÁS
    GL Rabelloa, MF de Souza Alvesa, DQF de Menezesb, R Soaresb, ...

MOST CITED SCHOLAR PUBLICATIONS

  • A review on robust M-estimators for regression analysis
    DQF De Menezes, DM Prata, AR Secchi, JC Pinto
    Computers & Chemical Engineering 147, 107254 , 2021
    2021.0
    Citations: 243
  • Virtual flow metering of production flow rates of individual wells in oil and gas platforms through data reconciliation
    GMP Andrade, DQF de Menezes, RM Soares, TSM Lemos, AF Teixeira, ...
    Journal of Petroleum Science and Engineering 208, 109772 , 2022
    2022.0
    Citations: 39
  • Eco-efficiency evaluation of acetone-methanol separation processes using computational simulation
    PV Mangili, YPDM Souza, DQF de Menezes, LS Santos, DM Prata
    Chemical Engineering and Processing-Process Intensification 123, 100-110 , 2018
    2018.0
    Citations: 25
  • Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring
    DQF de Menezes, MCC de Sá, TB Fontoura, TK Anzai, FC Diehl, ...
    Processes 8 (9), 1035 , 2020
    2020.0
    Citations: 21
  • Modeling of spiral wound membranes for gas separations. Part I: An iterative 2D permeation model
    ACS Dias, MCC de Sá, TB Fontoura, DQF de Menezes, TK Anzai, ...
    Journal of Membrane Science 612, 118278 , 2020
    2020.0
    Citations: 19
  • Modeling of spiral wound membranes for gas separations. Part III: A nonisothermal 2D permeation model
    TB Fontoura, MCC de Sá, DQF de Menezes, BF Oechsler, A Melo, ...
    Chemical Engineering Research and Design 177, 376-393 , 2022
    2022.0
    Citations: 10
  • Enhancing virtual flow metering on offshore oil platforms through parallel computing and data reconciliation
    GL Rabello, GMP Andrade, DQF de Menezes, RM Soares, TSM Lemos, ...
    Geoenergy Science and Engineering 235, 212695 , 2024
    2024.0
    Citations: 7
  • Use of neural networks for data reconciliation and virtual flow metering in oil wells
    MFS Alves, GL Rabello, DQF de Menezes, RM Soares, BF Vieira, ...
    Geoenergy Science and Engineering 246, 213543 , 2025
    2025.0
    Citations: 5
  • Monitoramento de processos de separação baseado em reconciliação de dados
    DQF Menezes
    Universidade Federal do Rio de Janeiro , 2021
    2021.0
    Citations: 3
  • Reconciliação de dados em colunas de destilação utilizando o simulador EMSO
    DQF de MENEZES, I SARRUF, FC PEIXOTO, DM PRATA
    Blucher Chemical Engineering Proceedings 1 (2), 12520-12527 , 2015
    2015.0
    Citations: 3
  • Uso de redes neuronais para agilizar a medição de vazões individuais de poços produtores de petróleo na bacia de campos
    MFS Alves, GL Rabello, DQF de Menezes, RM Soares, BF Vieira, ...
    Congresso brasileiro de engenharia química 24 , 2023
    2023.0
    Citations: 2
  • Reconciliação Robusta de Dados utilizando o Simulador EMSO
    I Sarruf, DQF de Menezes, LS Santos, DM Prata
    Blucher Chemical Engineering Proceedings 1 (2), 11127-11134 , 2015
    2015.0
    Citations: 1
  • Semi-empirical and statistical models for renewable liquid fuel process optimization
    DQF de Menezes, ACS Dias, R de FD Milão, SF Interlenghi, LDR Novaes, ...
    Engineering Science and Technology, an International Journal 78, 102390 , 2026
    2026.0
  • A Robust Numerical Framework for Hollow-Fiber Membrane Module Simulation and Solver Performance Analysis
    DQF de Menezes, MCC de Sá, NAC Vallejo, TM de Melo, LFO Campos, ...
    Membranes 16 (4), 154 , 2026
    2026.0
  • On Machine Learning Approaches for Wet Gas Flow Metering with Actual Data: From Handling Available Data to Developing Models
    MFS Alves, GL Rabello, RM Soares, DQ Menezes, LOV Pereira, JC Pinto
    Offshore Technology Conference Brasil, D031S036R005 , 2025
    2025.0
  • Modeling of Spiral Wound Membranes for Gas Separations—Part IV: Real-Time Monitoring Based on Detailed Phenomenological Model
    MCC Sá, DQF Menezes, TB Fontoura, LFO Campos, TK Anzai, FC Diehl, ...
    Processes 12 (11), 2597 , 2024
    2024.0
  • Melhorias em metamodelo para medição virtual via restrição nos dados de treinamento
    MF deSouzaAlves, GL Rabello, DQF de Menezes, R Marinho, ...
    Proceedings of PSE-BR 2024 III Brazilian Congress on Process Systems … , 2024
    2024.0
  • RECONCILIAÇÃO DE DADOS EM REDES DE TROCADORES DE CALOR UTILIZANDO O SOFTWARE EMSO
    DQF de MENEZES, FC PEIXOTO, DM PRATA
    Blucher Chemical Engineering Proceedings 1 (2), 12496-12503 , 2015
    2015.0
  • RECONCILIAÇÃO DADOS EM PROCESSAMENTO DE MINÉRIO UTILIZANDO O SIMULADOR EMSO
    DQF de MENEZES, S AL, FC PEIXOTO, DM PRATA
    Blucher Chemical Engineering Proceedings 1 (2), 12504-12511 , 2015
    2015.0
  • 12º CONGRESSO BRASILEIRO DE PESQUISA E DESENVOLVIMENTO EM PETRÓLEO E GÁS
    GL Rabelloa, MF de Souza Alvesa, DQF de Menezesb, R Soaresb, ...