Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines wi...
Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries
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Publisher
London: Nature Publishing Group UK
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Language
English
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Publisher
London: Nature Publishing Group UK
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Scope and Contents
Contents
This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. The incorporation of nanotechnology, through the addition of nanoparticles to conventional fuels,...
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Full title
Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries
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TN_cdi_doaj_primary_oai_doaj_org_article_cebce30feec84d8e8fbf92accc483a3a
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_cebce30feec84d8e8fbf92accc483a3a
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-024-83211-y
