5 citations · 10 across the 12 of their papers we have counts for
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ExPUFFIN: Thermodynamic Consistent Viscosity Prediction in an Extended Path-Unifying Feed-Forward Interfaced Network
Carine Menezes Rebello, Ulderico Di Caprio, Jenny Steen-Hansen +6
Accurate prediction of liquid viscosity is essential for process design and simulation, yet remains challenging for novel molecules. Conventional group-contribution models struggle…
Offset-Free Robust Nonlinear Control Using Data-Driven Model: A Nonlinear Multi-Model Computationally Efficient Approach
Carine Menezes Rebello, Erbet Almeida Costa, Idelfonso B. R. Nogueira
Robust model predictive control (MPC) aims to preserve performance under model-plant mismatch, yet robust formulations for nonlinear MPC (NMPC) with data-driven surrogates remain l…
Optimizing Capture in Pressure Swing Adsorption Units: A Deep Neural Network Approach with Optimality Evaluation and Operating Maps for Decision-Making
Carine Menezes Rebello, Idelfonso B. R. Nogueira
This study presents a methodology for surrogate optimization of cyclic adsorption processes, focusing on enhancing Pressure Swing Adsorption units for carbon dioxide () cap…
PUFFIN: A Path-Unifying Feed-Forward Interfaced Network for Vapor Pressure Prediction
Vinicius Viena Santana, Carine Menezes Rebello, Luana P. Queiroz +3
Accurately predicting vapor pressure is vital for various industrial and environmental applications. However, obtaining accurate measurements for all compounds of interest is not p…
A nested loop for simultaneous model topology screening, parameters estimation, and identification of the optimal number of experiments: Application to a Simulated Moving Bed unit
Rodrigo V. A. Santos, Carine M. Rebello, Anderson Prudente +6
Simulated Moving Bed (SMB) chromatography is a well-known technique for the resolution of several high-value-added compounds. Parameters identification and model topology definitio…