Bibliographic record
Abstract
The ACR-1000™ design is an evolutionary advancement of the proven CANDU® reactor design that delivers enhanced economic performance, safety, operability and maintainability. The fuel for the ACR-1000 design is based on the well established CANDU fuel bundle design that has over 40 years of demonstrated high performance. Building on its extensive experience in fuel design and analysis, and fuel testing, AECL has designed a CANFLEX-ACR™ fuel bundle that incorporates the latest improvements in CANDU fuel bundle design. The ACR-1000 fuel bundle also includes features that enable the ACR-1000 to achieve higher fuel burn-up and improved reactor core physics characteristics. To verify that the CANFLEX-ACR fuel bundle design will meet and exceed all design requirements, an extensive program of design analysis and testing is being carried out. This program rigorously evaluates the ability of the fuel design to meet all design and performance criteria and particularly those related to fuel failure limits. The design analyses address all of the phenomena that affect the fuel during its residence in the reactor core. Analysis is performed using a suite of computer codes that are used to evaluate the temperatures, deformations, stresses and strains experienced by the fuel bundle during its residence in the reactor core. These analyses take into account the impact of fuel power history and core residence time. Complementing the analyses, testing is performed to demonstrate the compatibility of the fuel with the reactor heat transport system and fuel handling systems, and to demonstrate the ability of the fuel to withstand the mechanical forces that it will experience during its residence in the core. The testing program includes direct measurement of prototype fuel element and fuel bundle properties and performance limits. A number of different test facilities are used including a cold test loop and a hot test loop with a full-scale ACR-1000 fuel channel that operates at reactor coolant temperatures, pressures and flows. This paper summarizes the out-reactor test program and related analysis that provide the basis for verifying that the ACR-1000 fuel design meets its requirements.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".