Combustion machine learning: Principles, progress and prospects
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
Data fusion approaches for structural health monitoring and system identification: Past, present, and future
During the past decades, significant efforts have been dedicated to develop reliable
methods in structural health monitoring. The health assessment for the target structure of …
methods in structural health monitoring. The health assessment for the target structure of …
[HTML][HTML] Machine learning for combustion
Combustion science is an interdisciplinary study that involves nonlinear physical and
chemical phenomena in time and length scales, including complex chemical reactions and …
chemical phenomena in time and length scales, including complex chemical reactions and …
A deep learning framework to discern and count microscopic nematode eggs
In order to identify and control the menace of destructive pests via microscopic image-based
identification state-of-the art deep learning architecture is demonstrated on the parasitic …
identification state-of-the art deep learning architecture is demonstrated on the parasitic …
Flame image processing and classification using a pre-trained VGG16 model in combustion diagnosis
Z Omiotek, A Kotyra - Sensors, 2021 - mdpi.com
Nowadays, despite a negative impact on the natural environment, coal combustion is still a
significant energy source. One way to minimize the adverse side effects is sophisticated …
significant energy source. One way to minimize the adverse side effects is sophisticated …
Data-driven classification and modeling of combustion regimes in detonation waves
A data-driven approach to classify combustion regimes in detonation waves is implemented,
and a procedure for domain-localized source term modeling based on these classifications …
and a procedure for domain-localized source term modeling based on these classifications …
Image-based deep neural network prediction of the heat output of a step-grate biomass boiler
P Toth, A Garami, B Csordas - Applied energy, 2017 - Elsevier
This work investigates the usage of deep neural networks for predicting the thermal output of
a 3 MW, grate-fired biomass boiler, based on routinely measured operating parameters and …
a 3 MW, grate-fired biomass boiler, based on routinely measured operating parameters and …