Name
Abstract | ||
|---|---|---|
In this study, ANNs are introduced to act as a bridge between detailed computer codes and compact simulators with an aim to improve the capabilities of compact expert system. The ANNs compensate for the inaccuracies of a compact expert system occurring from simplified governing equations and a reduced number of physical control volumes, and predict the critical parameter usually calculated from the sophisticated computer code. To verify the appli-cability of the proposed methodology, computer simulations are undertaken for loss of flow accidents (LOFA). |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11760023_180 | ISNN (2) |
Keywords | Field | DocType |
artificial neural network,expert system,computer simulation | Thermal hydraulics,Simulation,Source code,Computer science,Expert system,Back propagation neural network,Critical parameter,Nuclear power plant,Artificial neural network | Conference |
Volume | ISSN | ISBN |
3972 | 0302-9743 | 3-540-34437-3 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Malrey Lee | 1 | 197 | 41.30 |
| Hye-Jin Jeong | 2 | 2 | 3.07 |
| Young Joon Choi | 3 | 4 | 0.89 |
| Thomas M. Gatton | 4 | 33 | 9.28 |