5 citations · 10 across the 12 of their papers we have counts for
12 papers
WISE-FM:Operation-Aware, Engineering-Informed Foundation Model for Multi-Task Well Design
Carine de Menezes Rebello, Anderson Rapello dos Santos, Idelfonso B. R. Nogueira
Deploying machine learning models across diverse well portfolios requires generalisation to wells with design parameters outside the training distribution. Current data-driven appr…
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…
A Hybrid Agent-Based and System Dynamics Framework for Modelling Project Execution and Technology Maturity in Early-Stage R&D
R. W. S. Pessoa, M. H. Næss, J. C. Bijos +4
This paper presents a hybrid approach to predict the evolution of technological maturity in R and D projects, using the oil and gas sector as an example. Integrating System Dynamic…
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…
Digital Twin Framework for Optimal and Autonomous Decision-Making in Cyber-Physical Systems: Enhancing Reliability and Adaptability in the Oil and Gas Industry
Carine Menezes Rebello, Johannes Jäschkea, Idelfonso B. R. Nogueira
The concept of creating a virtual copy of a complete Cyber-Physical System opens up numerous possibilities, including real-time assessments of the physical environment and continuo…
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…
Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approach
Vinicius V. Santana, Erbet Costa, Carine M. Rebello +3
This study presents a systematic machine learning approach for creating efficient hybrid models and discovering sorption uptake models in non-linear advection-diffusion-sorption sy…
Bio-inspired Algorithms in the Optimisation of Wireless Sensor Networks
Joana Matos, Carine M. Rebello, Erbet A. Costa +3
WSN are a growing technology in industrial and personal use fields. The Quality of Service (QoS) of WSN is associated to the architecture of WSN nodes and network design. In this w…
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…
A Robust Scientific Machine Learning for Optimization: A Novel Robustness Theorem
Luana P. Queiroz, Carine M. Rebello, Erber A. Costa +4
Scientific machine learning (SciML) is a field of increasing interest in several different application fields. In an optimization context, SciML-based tools have enabled the develo…
A new Reinforcement Learning framework to discover natural flavor molecules
Luana P. Queiroz, Carine M. Rebello, Erbet A. Costa +5
The flavor is the focal point in the flavor industry, which follows social tendencies and behaviors. The research and development of new flavoring agents and molecules are essentia…