[HTML][HTML] Artificial intelligence for waste management in smart cities: a review
The rising amount of waste generated worldwide is inducing issues of pollution, waste
management, and recycling, calling for new strategies to improve the waste ecosystem, such …
management, and recycling, calling for new strategies to improve the waste ecosystem, such …
Recent advancements in sustainable aviation fuels
Sustainable alternative fuels, or SAFs, are recognized to have lower carbon footprints and
emit fewer greenhouse emissions. As a carbon-neutral alternative and intended drop-in …
emit fewer greenhouse emissions. As a carbon-neutral alternative and intended drop-in …
Feature selection and feature learning in machine learning applications for gas turbines: A review
The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of gas turbine (GT) modelling. However, successful implementation of ML …
to the field of gas turbine (GT) modelling. However, successful implementation of ML …
Advances in plasma-assisted ignition and combustion for combustors of aerospace engines
The improvement of the ignition and combustion performance of aerospace engines under
extreme conditions such as high altitude, low temperature, low pressure, and high speed is …
extreme conditions such as high altitude, low temperature, low pressure, and high speed is …
Performance diagnostics of gas turbines operating under transient conditions based on dynamic engine model and artificial neural networks
E Tsoutsanis, I Qureshi, M Hesham - Engineering Applications of Artificial …, 2023 - Elsevier
Gas turbine engines are machines of high complexity and non-linearity. Interpreting the vast
amount of data from a gas turbine and converting them into customer value requires the …
amount of data from a gas turbine and converting them into customer value requires the …
Performance prediction and design optimization of turbine blade profile with deep learning method
Q Du, Y Li, L Yang, T Liu, D Zhang, Y Xie - Energy, 2022 - Elsevier
Aerodynamic design optimization of the blade profile is a critical approach to improve
performance of turbomachinery. This paper aims to achieve the performance prediction with …
performance of turbomachinery. This paper aims to achieve the performance prediction with …
Prediction of operating characteristics for industrial gas turbine combustor using an optimized artificial neural network
In this study, the operating characteristics of a gas turbine combustor are predicted using
real-time data from industrial gas turbines. The turbine exhaust temperature (TET) and major …
real-time data from industrial gas turbines. The turbine exhaust temperature (TET) and major …
[PDF][PDF] Optimization of a 660 MW e supercritical power plant performance—a case of industry 4.0 in the data-driven operational management part 1. Thermal efficiency
This paper presents a comprehensive step-wise methodology for implementing industry 4.0
in a functional coal power plant. The overall efficiency of a 660 MWe supercritical coal-fired …
in a functional coal power plant. The overall efficiency of a 660 MWe supercritical coal-fired …
Key wastes selection and prediction improvement for biogas production through hybrid machine learning methods
As history shows, a linear production process results in a waste of resources. Using
renewable energy can not only reduce waste but also protect the earth's resources …
renewable energy can not only reduce waste but also protect the earth's resources …
A sequential cross-product knowledge accumulation, extraction and transfer framework for machine learning-based production process modelling
Machine learning is a promising method to model production processes and predict product
quality. It is challenging to accurately model complex systems due to data scarcity, as mass …
quality. It is challenging to accurately model complex systems due to data scarcity, as mass …