5 papers
MultiPUFFIN: A Multimodal Domain-Constrained Foundation Model for Molecular Property Prediction of Small Molecules
Idelfonso B. R. Nogueira, Carine M. Rebello, Mumin Enis Leblebici +1
MultiPUFFIN is a domain-informed multimodal foundation model for predicting thermophysical properties of small molecules, addressing a critical gap in chemical engineering, drug di…
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…