Passive safety systems of light water SMR plants
Bibliographic record
Abstract
The goal of the thesis is to present and compare major global light water small modular reactor (SMR) plants and their passive safety systems. The thesis provides theory on SMR plants and their passive safety systems on a general level. Subsequently, it goes into detail regarding the passive safety systems of each design. These SMR designs include CAREM, ACP100, NUWARD, UK SMR, VOYGR and BWRX-300, of which three are integrated pressurised water reactors (iPWRs), one is a loop-type reactor, and one is a boiling water reactor (BWR). Moreover, the thesis introduces future projections regarding the commercial viability and technical aspects of these designs. The thesis is conducted as a literature review primarily based on technical publications. \n \nResults state that the designs have certain similarities such as PWRs opting for an integrated design, larger PWRs relying on forced circulation while smaller SMRs apply natural circulation, and utilisation of control rod driving mechanism (CRDM). Typically, soluble, or injected boron and/or burnable poison systems are used for reactivity control. Ultimately, safety is considered as a main priority in the designs. Future projections for the designs could be affected by the success of the first SMR design achieving criticality. It is also found that political alliances play a vital role in SMR development and commercial possibilities worldwide as well as that safety systems wouldn’t most likely be a deciding factor for global success of the designs. Comparing the designs remains largely theoretical as none of the referenced SMR designs in the thesis are operational.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".