Modeling the Radiolysis of Supercritical Water by Fast Neutrons: Density Dependence of the Yields of Primary Species at 400°C
Bibliographic record
Abstract
A reliable understanding of radiolysis processes in supercritical water (SCW)-cooled reactors is crucial to developing chemistry control strategies that minimize the corrosion and degradation of materials. However, directly measuring the chemistry in reactor cores is difficult due to the extreme conditions of high temperature and pressure and mixed neutron and gamma-radiation fields, which are incompatible with normal chemical instrumentation. Thus, chemical models and computer simulations are an important route of investigation for predicting the detailed radiation chemistry of the coolant in a SCW reactor and the consequences for materials. Surprisingly, information on the fast neutron radiolysis of water at high temperatures is limited, and even more so for fast neutron irradiation of SCW. In this work, Monte Carlo simulations were used to predict the G values for the primary species e(-)aq, H(•), H2, (•)OH and H2O2 formed from the radiolysis of pure, deaerated SCW (H2O) by 2 MeV monoenergetic neutrons at 400°C as a function of water density in the range of ∼0.15-0.6 g/cm(3). The 2 MeV neutron was taken as representative of a fast neutron flux in a reactor. For light water, the moderation of these neutrons after knock-on collisions with water molecules generated mostly recoil protons of 1.264, 0.465, 0.171 and 0.063 MeV. Neglecting oxygen ion recoils and assuming that the most significant contribution to the radiolysis came from these first four recoil protons, the fast neutron yields were estimated as the sum of the G values for these protons after appropriate weightings were applied according to their energy. Calculated yields were compared with available experimental data and with data obtained for low-LET radiation. Most interestingly, the reaction of H(•) atoms with water was found to play a critical role in the formation yields of H2 and (•)OH at 400°C. Recent work has underscored the potential importance of this reaction above 200°C, but its rate constant is still controversial.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".