accuracy and uncertainty analysis of psbt benchmark exercises using a subchannel code matra
Clicks: 141
ID: 192237
2012
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
141 views
36 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #25 of 65 articles by views in drug metabolism reviews
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
In the framework of the OECD/NRC PSBT benchmark, the subchannel grade void distribution data and DNB data were assessed by a subchannel code, MATRA. The prediction accuracy and uncertainty of the zone-averaged void fraction at the central region of the 5 × 5 test bundle were evaluated for the steady-state and transient benchmark data. Optimum values of the turbulent mixing parameter were evaluated for the subchannel exit temperature distribution benchmark. The influence of the mixing vanes on the subchannel flow distribution was investigated through a CFD analysis. In addition, a regionwise turbulent mixing model was examined to account for the nonhomogeneous mixing characteristics caused by the vane effect. The steady-state DNB benchmark data with uniform and nonuniform axial power shapes were evaluated by employing various DNB prediction models: EPRI bundle CHF correlation, AECL-IPPE 1995 CHF lookup table, and representative mechanistic DNB models such as a sublayer dryout model and a bubble crowding model. The DNBR prediction uncertainties for various DNB models were evaluated from a Monte-Carlo simulation for a selected steady-state condition.
| Reference Key |
hwang2012scienceaccuracy
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Dae-Hyun Hwang;Seong-Jin Kim;Kyong-Won Seo;Hyuk Kwon |
| Journal | drug metabolism reviews |
| Year | 2012 |
| DOI |
10.1155/2012/603752
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.