Applications of machine learning in thermochemical conversion of biomass-A review
Thermochemical conversion of biomass has been considered a promising technique to
produce alternative renewable fuel sources for future energy supply. However, these …
produce alternative renewable fuel sources for future energy supply. However, these …
A review of physics-informed machine learning in fluid mechanics
Physics-informed machine-learning (PIML) enables the integration of domain knowledge
with machine learning (ML) algorithms, which results in higher data efficiency and more …
with machine learning (ML) algorithms, which results in higher data efficiency and more …
Intensification of catalytic reactors: a synergic effort of multiscale modeling, machine learning and additive manufacturing
M Bracconi - Chemical Engineering and Processing-Process …, 2022 - Elsevier
The intensification of catalytic reactors is expected to play a crucial role to address the
challenges that the chemical industry is facing in the transition to more sustainable …
challenges that the chemical industry is facing in the transition to more sustainable …
[HTML][HTML] Forecasting the influence of the guided flame on the combustibility of timber species using artificial intelligence
AN Olimat, AF Al-Shawabkeh, ZA Al-Qadi… - Case Studies in Thermal …, 2022 - Elsevier
This paper anticipates the burning rate and optical obscuration characteristics of a 10 mm
thick timber species often used in buildings under the influence of a guided flame condition …
thick timber species often used in buildings under the influence of a guided flame condition …
Leveraging machine learning in porous media
The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML),
has had a significant impact on engineering and the fundamental sciences, resulting in …
has had a significant impact on engineering and the fundamental sciences, resulting in …
Mechanisms and modeling of bubble dynamic behaviors and mass transfer under gravity: a review
S Yan, X Wang, L Zhu, X Zhang, Z Luo - Chemical Engineering Science, 2023 - Elsevier
Bubbly flow is a prototypical two-phase flow problem. The dynamic behavior of bubbles
within a reactor is intrinsically linked to their transport, distribution, and mass transfer, all of …
within a reactor is intrinsically linked to their transport, distribution, and mass transfer, all of …
Time series classification, augmentation and artificial-intelligence-enabled software for emergency response in freight transportation fires
In responding to freight transportation fire incidents, first responders refer to the terials
labeled on the freights and the Emergency Response Guidebook (ERG) for guidance on the …
labeled on the freights and the Emergency Response Guidebook (ERG) for guidance on the …
A data-driven reduced-order model for stiff chemical kinetics using dynamics-informed training
A data-based reduced-order model (ROM) is developed to accelerate the time integration of
stiff chemically reacting systems by effectively removing the stiffness arising from a wide …
stiff chemically reacting systems by effectively removing the stiffness arising from a wide …
Model identification in reactor-based combustion closures using sparse symbolic regression
Abstract In Large Eddy Simulations (LES) of combustion, the accuracy of predictions might
be heavily affected by deficiencies in traditional/simplified closure models, especially when …
be heavily affected by deficiencies in traditional/simplified closure models, especially when …
Ab initio neural network MD simulation of thermal decomposition of a high energy material CL-20/TNT
CL-20 (2, 4, 6, 8, 10, 12-hexanitro-2, 4, 6, 8, 10, 12-hexaazaisowurtzitane, also known as
HNIW) is one of the most powerful energetic materials. However, its high sensitivity to …
HNIW) is one of the most powerful energetic materials. However, its high sensitivity to …