Understanding and Prediction of Thermohydraulic Phenomena Relevant to Supercritical Water Cooled Reactors (SCWRs) - Final Report of a Coordinated Research Project
Bibliographic record
Abstract
FOREWORD \nThe supercritical water cooled reactor (SCWR) is an innovative concept that operates at a pressure \nhigher than the thermodynamic critical point of water, allowing the core outlet coolant temperature \nto be much higher than that of the current generation of WCRs. The key technological advantages \nof the SCWR include its high thermal efficiency and simplified system configuration compared \nwith conventional WCRs. \nThere has been a high level of interest in research and development of SCWRs in several Member \nStates. In 2007, the IAEA started the coordinated research project (CRP) entitled Heat Transfer \nBehaviour and Thermo-hydraulics Code Testing for Super-critical Water Cooled Reactors \n(SCWRs), which promoted international collaboration among 16 institutes from 9 Member States \nand 2 international organizations. The CRP was successfully completed in September 2012. \nInformation generated from that CRP was documented in numerous IAEA publications and reports. \nA database of thermohydraulic parameters of interest to SCWR development was compiled and is \nhoused in the Nuclear Energy Agency’s central server. \nAfter the completion of the CRP, collaboration continued between several participating institutes. \nMost of these institutes expressed their strong interest in and support for a new CRP on \nthermohydraulics of SCWRs to continue the momentum of international collaboration. The overall \nobjective of this second CRP, which started in 2014, was to improve the understanding of \nthermohydraulic phenomena and the prediction accuracy of thermohydraulic parameters related to \nSCWRs and to benchmark numerical toolsets for SCWR thermohydraulic analyses. Scientific \ninvestigators from participating institutes identified specific research objectives to improve the \npredictive capability of key technology areas (e.g. heat transfer and pressure drop for SCWR fuel \nrelated geometries, parallel channel stability boundary, natural circulation flow, critical heat flux at \nnear critical pressures, critical flow, subchannel and plenum mixing). The predictive capability of \nsubchannel codes and computational fluid dynamic tools was assessed through benchmarking \nexercises for heat transfer in tubes, annuli and bundles as well as pressure drops in annuli and \nbundles. In total, 12 institutes from 10 Member States and 2 international organizations were \ninvolved in this second CRP, which was completed with the planned outputs in 2019. \nThe present publication provides the background and objectives of the CRP; descriptions of a \nrevised Canadian SCWR design concept and a new SCWR design concept being developed at the \nNuclear Power Institute of China; updated information on key technology areas (e.g. heat transfer \nin simple geometries, stability and critical flow) obtained since the completion of the previous CRP; \nnew experiments and data on supercritical heat transfer in bundles and on critical heat flux; and \napplication of the direct numerical simulation approach for supercritical heat transfer. Results of \nthree benchmarking exercises with subchannel codes and computational fluid dynamic tools are \nalso presented, to demonstrate successes and show areas for further improvement. Experimental \ninformation and data were contributed by participating institutes through close collaboration. \nThis publication illustrates the state of the art of SCWR research and development. It is expected \nto be a key supporting publication for researchers and engineers pursuing the development of \nSCWRs or equipment/components operating at supercritical pressures. \nThe IAEA is grateful for the contributions of the chief scientific investigators of all participating \ninstitutes and of the CRP chairpersons, L. Leung (Canada) and W. Ambrosini (Italy). In particular, \nthe efforts of L. Leung to collect and organize the contributions and to continuously encourage \nprogress in the work are gratefully recognized. The IAEA officers responsible for this publication \nwere T. Jevremovic and K. Yamada of the Division of Nuclear Power.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".