[HTML][HTML] Towards predicting liquid fuel physicochemical properties using molecular dynamics guided machine learning models

RSM Freitas, ÁPF Lima, C Chen, FA Rochinha, D Mira… - Fuel, 2022 - Elsevier
Accurate determination of fuel properties of complex mixtures over a wide range of pressure
and temperature conditions is essential to utilizing alternative fuels. The present work aims …

Nondestructive evaluation of thermal barrier coatings thickness using terahertz Time-Domain spectroscopy combined with hybrid machine learning approaches

R Li, D Ye, Z Xu, C Yin, H Xu, H Zhou, J Yi, Y Chen… - Coatings, 2022 - mdpi.com
To ensure the thermal stability of aero-engine blades under high temperature and harsh
service environments, it is necessary to quickly and accurately evaluate the thickness of …

[HTML][HTML] Average Carbon Number Analysis and Relationship with Octane Number and PIONA Analysis of Premium and Regular Gasoline Expended in Ecuador

K Pazmiño-Viteri, K Cabezas-Terán, D Echeverría… - Processes, 2024 - mdpi.com
The quality of fuel depends on its chemical composition, which influences engine
performance. Gas chromatography, a cornerstone of global oil and fuel R&D, remains …

[HTML][HTML] Higher order dynamic mode decomposition to model reacting flows

A Corrochano, G D'Alessio, A Parente… - International Journal of …, 2023 - Elsevier
This work presents a new application of higher order dynamic mode decomposition
(HODMD) for the analysis of reactive flows. Due to the high complexity of the data analysed …

Improved chimpanzee algorithm based on CEEMDAN combination to optimize ELM short-term wind speed prediction

W Sun, X Wang - Environmental Science and Pollution Research, 2023 - Springer
The world energy structure dominated by fossil energy has brought about the depletion of
fossil energy and a series of environmental pollution problems. The development of new …

Automated adaptive chemistry for Large Eddy Simulations of turbulent reacting flows

R Amaduzzi, G D'Alessio, P Pagani, A Cuoci… - Combustion and …, 2024 - Elsevier
Abstract Large Eddy Simulations (LES) of turbulent reacting flows carried out with detailed
kinetic mechanisms have a key role for the discovery of the physical and chemical …

Intelligent Petroleum Processing: A Short Review on Applying AI/ML to Petroleum Products Optimization

A Alzahawy, H Issa - 2024 - preprints.org
Improving the quality of petroleum products and refining processes through the use of
artificial intelligence and machine learning techniques is the topic of this article. It shows that …

Prediction of octane numbers for commercial gasoline using distillation curves: a comparative regression analysis between principal component and partial least …

HM Issa - Petroleum Science and Technology, 2024 - Taylor & Francis
In this study, it was found that limiting the number of explanatory distillation curves input
variables in a multivariate regression method to the most significant ones (10%, 50%, 90 …

Predicting the health status of a pulp press based on deep neural networks and hidden markov models

A Martins, B Mateus, I Fonseca, JT Farinha… - Energies, 2023 - mdpi.com
The maintenance paradigm has evolved over the last few years and companies that want to
remain competitive in the market need to provide condition-based maintenance (CBM). The …

[HTML][HTML] Hierarchical higher-order dynamic mode decomposition for clustering and feature selection

A Corrochano, G D'Alessio, A Parente… - … & Mathematics with …, 2024 - Elsevier
This article introduces a novel, fully data-driven method for forming reduced order models
(ROMs) in complex flow databases that consist of a large number of variables. The algorithm …