Issue |
E3S Web Conf.
Volume 334, 2022
EFC21 - European Fuel Cells and Hydrogen Piero Lunghi Conference
|
|
---|---|---|
Article Number | 05001 | |
Number of page(s) | 6 | |
Section | Power Generation | |
DOI | https://doi.org/10.1051/e3sconf/202233405001 | |
Published online | 10 January 2022 |
Knowledge Based Engineering for Hydrogen Gas Turbines and Burners Design: a review
1 Dipartimento di Ingegneria dell’Innovazione, Università del Salento, via per Monteroni, sn., 73100, Lecce (LE), Italy
2 Dipartimento di Management, Finanza e Tecnologia, Università LUM, km 18 SS.100, 70019 Casamassima (BA), Italy
* Corresponding author: mariangela.lazoi@unisalento.it
Hydrogen gas turbines and burners need high attention and their appropriate realization, yet during their design, can lead important benefits for the whole sector. Realizing the best design, the first time, reduces reworks and requests of design changes from the manufacturing departments. In this field, Knowledge Based Engineering is a good strategy for embedding, in an automatic way, experts’ knowledge into CAD models during the design of a component. It enables a reduction of human errors and costs in several design tasks and improving the final quality of a component model. With these premises, the aim to the study is to lead improvements and appropriate actions in the design and re-configuration of hydrogen power generation systems (i.e. gas turbines and burners) by means of KBE, leading improvements yet in this early phase of the global race for hydrogen. A systematic literature review is carried out to explore the current state of art for the application of KBE for the design of turbines and burners in different industrial sectors. Evidences from the practice are collected in a structured classification and elaborated and summarized for application in the design of gas turbines and burners for the hydrogen production.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.