Cell by Cell Artificial Neural Networks Approach for Modelling Laminar Flow in Two-dimensional Domain
This research is motivated by the rapid growth of soft computing using artificial intelligence. Applying artificial neural networks in fluid mechanics are only effective for specific, predefined geometries without discretizations. Hence, a cell by cell new artificial neural networks approach is prop...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2018
|
| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/id/eprint/18406/1/Osama_PrintThesis01.pdf http://utpedia.utp.edu.my/id/eprint/18406/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Petronas |
| Language: | English |
| id |
oai:utpedia.utp.edu.my:18406 |
|---|---|
| record_format |
eprints |
| spelling |
oai:utpedia.utp.edu.my:184062023-05-15T07:41:08Z http://utpedia.utp.edu.my/id/eprint/18406/ Cell by Cell Artificial Neural Networks Approach for Modelling Laminar Flow in Two-dimensional Domain SABIR, OSAMA FUAD AKASHA TJ Mechanical engineering and machinery This research is motivated by the rapid growth of soft computing using artificial intelligence. Applying artificial neural networks in fluid mechanics are only effective for specific, predefined geometries without discretizations. Hence, a cell by cell new artificial neural networks approach is proposed to predict the characteristics of laminar flow in any arbitrary two-dimensional domain. 2018-04 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/id/eprint/18406/1/Osama_PrintThesis01.pdf SABIR, OSAMA FUAD AKASHA (2018) Cell by Cell Artificial Neural Networks Approach for Modelling Laminar Flow in Two-dimensional Domain. PhD. thesis, Universiti Teknologi PETRONAS. |
| institution |
Universiti Teknologi Petronas |
| building |
UTP Resource Centre |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Petronas |
| content_source |
UTP Electronic and Digitized Intellectual Asset |
| url_provider |
http://utpedia.utp.edu.my/ |
| language |
English |
| topic |
TJ Mechanical engineering and machinery |
| spellingShingle |
TJ Mechanical engineering and machinery SABIR, OSAMA FUAD AKASHA Cell by Cell Artificial Neural Networks Approach for Modelling Laminar Flow in Two-dimensional Domain |
| description |
This research is motivated by the rapid growth of soft computing using artificial intelligence. Applying artificial neural networks in fluid mechanics are only effective for specific, predefined geometries without discretizations. Hence, a cell by cell new artificial neural networks approach is proposed to predict the characteristics of laminar flow in any arbitrary two-dimensional domain. |
| format |
Thesis |
| author |
SABIR, OSAMA FUAD AKASHA |
| author_facet |
SABIR, OSAMA FUAD AKASHA |
| author_sort |
SABIR, OSAMA FUAD AKASHA |
| title |
Cell by Cell Artificial Neural Networks Approach for Modelling
Laminar Flow in Two-dimensional Domain |
| title_short |
Cell by Cell Artificial Neural Networks Approach for Modelling
Laminar Flow in Two-dimensional Domain |
| title_full |
Cell by Cell Artificial Neural Networks Approach for Modelling
Laminar Flow in Two-dimensional Domain |
| title_fullStr |
Cell by Cell Artificial Neural Networks Approach for Modelling
Laminar Flow in Two-dimensional Domain |
| title_full_unstemmed |
Cell by Cell Artificial Neural Networks Approach for Modelling
Laminar Flow in Two-dimensional Domain |
| title_sort |
cell by cell artificial neural networks approach for modelling
laminar flow in two-dimensional domain |
| publishDate |
2018 |
| url |
http://utpedia.utp.edu.my/id/eprint/18406/1/Osama_PrintThesis01.pdf http://utpedia.utp.edu.my/id/eprint/18406/ |
| _version_ |
1768010113390477312 |