INL Contributions to Draft HTTF Benchmark Specifications
Bibliographic record
Abstract
The High-Temperature Test Facility (HTTF) is an integral effects thermal hydraulics test facility at Oregon State University designed as a 1/4 length scale model of the Modular High-Temperature Gas-Cooled Reactor 350 MW core (mHTGR-350). In the spring and summer of 2019, several experiments were conducted at HTTF providing a valuable source of gas-cooled reactor thermal hydraulics data. Idaho National Laboratory (INL), Oregon State University, Argonne National Laboratory, and Canadian Nuclear Laboratories have partnered to use this experimental data to develop a gas-cooled reactor thermal hydraulics benchmark led by INL under the auspices of the Advanced Reactor Technologies (ART) program. This report provides some context on the benchmark, HTTF, and previous Reactor Excursions and Leak Analysis Program (RELAP)5-3D modeling of HTTF. It also provides a draft of the benchmark specifications for the Depressurized Conduction Cooldown problem, which is the INL-led benchmark problem.
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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 | 0.012 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.069 | 0.031 |
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".