2010
DOI: 10.1016/j.nucengdes.2009.10.005
|View full text |Cite
|
Sign up to set email alerts
|

Neural network and genetic algorithms for optimizing the plate element of Egyptian research reactor problems

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2011
2011
2022
2022

Publication Types

Select...
2
2

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(2 citation statements)
references
References 4 publications
0
2
0
Order By: Relevance
“…More recently, these techniques have been applied to other reactor types including high temperature gas cooled reactors [24][25][26][27], molten salt reactors [28], and research reactors [29][30][31][32]. A more complete summary of the open-ended nuclear design R&D that predates and motivated this work are provided in Section 2.1.…”
Section: Artificial Intelligence For Nuclear Engineeringmentioning
confidence: 99%
“…More recently, these techniques have been applied to other reactor types including high temperature gas cooled reactors [24][25][26][27], molten salt reactors [28], and research reactors [29][30][31][32]. A more complete summary of the open-ended nuclear design R&D that predates and motivated this work are provided in Section 2.1.…”
Section: Artificial Intelligence For Nuclear Engineeringmentioning
confidence: 99%
“…Examples of predictive features of ANNs include thermal-hydraulic performance analysis of the printed circuit heat exchangers (PCHE) [Kim 09, Ridluan 2009], and prediction of key safety parameters in nuclear research reactors [Mazrou 2009]. ANNs have been used to optimally design compact heat exchangers (CHE) [Jia 2003] and to optimize plate elements or plate-fin heat exchangers (PFHE) of reactors [Waheda 2010, Peng 2007. Control modeling and simulation related ANN applications include feedwater controllers in pressurized water reactors (PWRs) [Jia 2003].…”
Section: Introductionmentioning
confidence: 99%