ICONE23-1734 HITACHI-GE-SMALL MODULAR REACTOR BALANCE OF PLANT THERMAL UTILIZATION STUDY
Bibliographic record
Abstract
The Province of Saskatchewan and Hitachi Canada have established a collaborative relationship to research design options and conduct feasibility analyses of Small Modular Reactor (SMR) technology with the goal of safely and reliably generating clean energy and helping to achieve a low-carbon society. The focus of this study is to optimize the design of an SMR Balance of Plant (BOP) for the supply of steam and heat to various residential, industrial and commercial applications. The study includes a review to examine if waste heat available from the proposed SMR could be used for producing potable water using nuclear desalination technology. It is in the context that large volumes of groundwater and brackish water are available in Saskatchewan, Canada. The existing literature on desalination processes are being reviewed, including technologies for water production such as Multiple Effect Distillation (MED), Multi Stage Flash (MSF), and Reverse Osmosis (RO). The review includes comparison of various technologies for energy efficiency and overall economics of the process. The Desalination Economic Evaluation program (DEEP) computer model available from International atomic energy agency (IAEA) is also used as a tool for examination. Factors such as salinity of the feedwater, advantages gained by pre-heating the feedwater and efficient utilization of waste heat generated in the SMR showed that technology based on RO will be the most cost effective technology. The conclusions are also supported in previous reviews done by GE and AMEC for the government of Alberta, Canada. The quality of product water produced using RO technology depends on impurities in the feed water. Therefore, trials in a pilot plant and in a semi commercial plant are proposed as next steps.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".