Supercritical water gasification thermodynamic study and hybrid modeling of machine learning with the ideal gas model: Application to gasification of microalgae …
ÍAM Zelioli, ACD Freitas, AP Mariano - Energy, 2024 - Elsevier
This study presents a hybrid modeling approach that combines a simplified
phenomenological model with machine learning techniques for predicting variables in the …
phenomenological model with machine learning techniques for predicting variables in the …
The forefront of chemical engineering research
L Torrente-Murciano, JB Dunn… - Nature Chemical …, 2024 - nature.com
The forefront of chemical engineering research | Nature Chemical Engineering Skip to main
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A tutorial review of machine learning-based model predictive control methods
Z Wu, PD Christofides, W Wu, Y Wang… - Reviews in Chemical …, 2024 - degruyter.com
This tutorial review provides a comprehensive overview of machine learning (ML)-based
model predictive control (MPC) methods, covering both theoretical and practical aspects. It …
model predictive control (MPC) methods, covering both theoretical and practical aspects. It …
[HTML][HTML] Model predictive control of an electrically-heated steam methane reformer
Steam methane reforming (SMR) is one of the most widely used hydrogen (H 2) production
processes. In addition to its extensive utilization in industrial sectors, hydrogen is expanding …
processes. In addition to its extensive utilization in industrial sectors, hydrogen is expanding …
Feedback control of an experimental electrically-heated steam methane reformer
Steam methane reforming (SMR) is the most common industrial process to produce
hydrogen (H 2) from methane and water vapor. The SMR reactions are overall highly …
hydrogen (H 2) from methane and water vapor. The SMR reactions are overall highly …
[HTML][HTML] Machine learning-based predictive control of an electrically-heated steam methane reforming process
Hydrogen plays a crucial role in improving sustainability and offering a clean and efficient
energy carrier that significantly reduces greenhouse gas emissions. However, the primary …
energy carrier that significantly reduces greenhouse gas emissions. However, the primary …
[HTML][HTML] The enabling technologies for digitalization in the chemical process industry
In this paper, we provide an overview of the technologies that enable digitalization in the
chemical process industry and describe their applications to solve problems in industrial …
chemical process industry and describe their applications to solve problems in industrial …
[HTML][HTML] Improved Fault Detection and Diagnosis Using Graph Auto Encoder and Attention-based Graph Convolution Networks
A powerful fault detection and diagnosis (FDD) system plays a pivotal role in achieving
operational excellence by maximizing system performance, optimizing maintenance …
operational excellence by maximizing system performance, optimizing maintenance …
High-throughput automated membrane reactor system: The case of CO2/bicarbonate electroreduction
AB Navarro, R Garcia-Valls, A Nogalska - Chemical Engineering and …, 2024 - Elsevier
Nowadays, CO 2 capture and valorization are vital centers of investigation to help mitigate
the effects of climate change. Considering that to achieve high conversion efficiencies a …
the effects of climate change. Considering that to achieve high conversion efficiencies a …
Learning-based Model Predictive Control of an Ammonia Synthesis Reactor
We investigate the application of state-of-the-art recurrent machine learning methods to
tackle the computational challenges associated with the real-time solvability of a packed …
tackle the computational challenges associated with the real-time solvability of a packed …