ACR-1000™ Design and Safety Performance
Bibliographic record
Abstract
The ACR-1000™ design has evolved from AECL’s in depth knowledge of CANDU® systems, components and materials based on the CANDU 6 design, as well as the experience and feedback received from owners and operators of CANDU plants. The ACR® design retains the proven strengths and features of CANDU reactors, while incorporating innovations and state-of-the-art technology. It also features major improvements in inherent safety characteristics, safety margin and operational performance. The ACR design has been reviewed by domestic and international regulatory bodies, and has been given a positive regulatory opinion about its licensability in Canada and internationally. The Canadian regulator, the Canadian Nuclear Safety Commission (CNSC) completed the Phase 1 [1] and Phase 2 [2] pre-project design reviews in December 2008 and August 2009 respectively, and concluded that there are no fundamental barriers to licensing the ACR-1000 design in Canada. The generic PSAR for ACR-1000 was completed in September 2009. The PSAR contains the ACR-1000 design details, the safety and design methodology, and the safety analysis that demonstrate ACR-1000 safety case and compliance with Canadian and international regulatory requirements and expectations. The final stage of the ACR-1000 design is currently underway including documentation and additional confirmatory analysis, and the basic engineering will be completed in 2011. This paper provides an overview of the ACR-1000 design including a summary of the safety methodology used and compliance with regulatory and customer requirements, along with a demonstration of how modern expectations on safety margins and operational performance (i.e., typically characterized as Generation III+) are met. It also provides a summary of the safety analysis results (both deterministic and probabilistic) from the generic safety analysis that has been completed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".