International Training Program in Support of Safety Analysis: 3C S.UN.COP – Scaling, Uncertainty and 3D Thermal-Hydraulics/Neutron-Kinetics Coupled Codes Seminars
Bibliographic record
Abstract
Thermal-hydraulic system computer codes are extensively used worldwide for analysis \nof nuclear facilities by utilities, regulatory bodies, nuclear power plant designers and vendors, \nnuclear fuel companies, research organizations, consulting companies, and technical support \norganizations. The computer code user represents a source of uncertainty that can influence the \nresults of system code calculations. This influence is commonly known as the ‘user effect’ and stems \nfrom the limitations embedded in the codes as well as from the limited capability of the analysts to \nuse the codes. Code user training and qualification is an effective means for reducing the variation \nof results caused by the application of the codes by different users. This paper describes a \nsystematic approach to training code users who, upon completion of the training, should be able to \nperform calculations making the best possible use of the capabilities of best estimate codes. In other \nwords, the program aims at contributing towards solving the problem of user effect. The 3D \nS.UN.COP (Scaling, Uncertainty and 3D COuPled code calculations) seminars have been \norganized as follow-up of the proposal to IAEA for the Permanent Training Course for System Code \nUsers. Eleven seminars have been held at University of Pisa (two in 2004), at The Pennsylvania \nState University (2004), at the University of Zagreb (2005), at the School of Industrial Engineering \nof Barcelona (January-February 2006), in Buenos Aires, Argentina (October 2006), requested by \nAutoridad Regulatoria Nuclear (ARN), Nucleoelectrica Argentina S.A (NA-SA) and Comisión \nNacional de Energía Atómica (CNEA), at the College Station, Texas A&M, (January-February \n2007), in Hamilton and Niagara Falls, Ontario (October 2007) requested by Atomic Energy \nCanada Limited (AECL), Canadian Nuclear Society (CNS) and Canadian Nuclear Safety \nCommission (CNSC), in Petten, The Netherlands (October 2008) in cooperation with the Institute of \nEnergy of the Joint Research Center of the European Commission (IE-JRC-EC), at the Royal \nInstitute of Technology, Stockholm (October 2009) and in Petten, The Netherlands (October 2010) \nin cooperation with the Institute of Energy of the Joint Research Center of the European \nCommission (IE-JRC-EC). It was recognized that such courses represented both a source of \ncontinuing education for current code users and a mean for current code users to enter the formal \ntraining structure of a proposed ‘permanent’ stepwise approach to user training. The 3D S.UN.COP \n2010 at IE-JRC was successfully held with the attendance of 23 participants coming from more than \n10 countries and 20 different institutions (universities, vendors and national laboratories). More \nthan 30 scientists (coming from more than 10 countries and 20 different institutions) were involved \nin the organization of the seminar, presenting theoretical aspects of the proposed methodologies and \nholding the training and the final examination. A certificate (LA Code User grade) was released to \nparticipants that successfully solved the assigned problems. The eleventh seminar has been held \n(March 2011) in Wilmington, North Carolina, involving more than 30 scientists between lecturers \nand code developers (http://www.nrgspg.ing.unipi.it/3dsuncop/).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.147 | 0.061 |
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 source (direct Gemma or distilled Codex), 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".