Development of the Multifactor Computational Models of the Solid Propellants Combustion by Means of Data Science Methods. Propellant Combustion Genome Conception
The results of usage of data science methods, in particular artificial neural networks, for the creation of new multifactor computational models of the solid propellants (SP) combustion that solve the direct and inverse tasks are presented. The own analytical platform Loginom was used for the models...
Main Authors: | Abrukov Victor, Anufrieva Darya, Lukin Alexander, Oommen Charlie, Sanalkumar V. R., Chandrasekaran Nichith |
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Format: | Article |
Language: | English |
Published: |
EDP Sciences
2020-01-01
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Series: | MATEC Web of Conferences |
Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2020/26/matecconf_icome2019_01048.pdf |
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