ASYST4.1 validation for gas cooled SMR applications using the HTTF experiment
Bibliographic record
Abstract
Small Modular Reactors (SMRs) based on High Temperature Gas Cooled Reactors (HTGR) concepts are being considered for remote communities in Canada (power ∼ 5 MWe or less) and elsewhere. One such design is Micro-Modular Reactor (MMR) from USNC (Ultra-Safe Nuclear Corporation). It uses helium as primary coolant and molten salt as intermediate coolant and for thermal energy storage (TES). The molten salt can then be used to generate steam on-demand to match the local communities’ energy requirements. Reliable computational tools are needed for thermal hydraulic analysis of the integrated nuclear and molten salt systems. ASYST4.1 (Advanced SYStem Thermal system) is one such tool which has been recently validated for Solar Salt (40 % NaNO3 + 60 %KNO3) applications and has capability to simulate the helium coolant and reactor core behaviour. To enable the code to model the primary and intermediate loops of MMR there is a need to validate the code for helium coolants and its capabilities to simulate lateral conduction, natural circulation, and radiative heat transfer. The HTTF (High Temperature Test Facility) experiment PG-26, a Depressurized Conduction Cooldown transient, is used for this validation exercise. The results are compared with those of the experiment and those from RELAP5-3D calculations. The reference case and sensitivity analyses for the important parameters are presented. Mass flow rate and temperatures in the primary loop are compared for the steady-state and for the transient PG-26. For the initial assessment ASYST4.1 predictions are found in good agreement with RELAP5-3D, but these results deviate from the experiment. Significant improvement in simulation results is observed when simulations consider the entire trajectory of the warm-up period and of the experiment, indicating that the experiment was not in a steady-state condition at the time of the depressurization test. This is an important factor to be considered in all HTTF cases going forward.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".