Simulation of in-core dose rates for an offline CANDU reactor
Bibliographic record
Abstract
This thesis describes the development of a Monte Carlo simulation to predict the dose rates that will be encountered by a novel robotic inspection system for the pressure tubes of an offline CANDU reactor. Simulations were performed using the Monte Carlo N-Particle (MCNP) radiation transport code, version 6.1. The radiation fields within the reactor, even when shut down, are very high, and can cause significant damage to certain structural components and the electronics of the inspection system.\nGiven that the robotic system will rely heavily on electronics, it is important to know the dose rates that will be encountered, in order to estimate the component lifetimes.\nThe MCNP simulation was developed and benchmarked against information obtained from Ontario Power Generation and the Canadian Nuclear Laboratories. The benchmarking showed a good match between the simulated values and the expected values. This simulation, coupled with the accompanying user interface, represent a tool in dose field prediction that is currently unavailable. Predicted dose rates for a postulated inspection at 7 days after shutdown, with 2:5 cm of tungsten shielding around the key components, would survive for approximately 7 hours in core. This is anticipated to be enough time to perform an inspection and shows that the use of this tool can aid in designing the new inspection system.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".