The EPQ Code System for Simulating the Thermal Response of Plasma-Facing Components to High-Energy Electron Impact
Bibliographic record
Abstract
The generation of runaway electrons during a thermal plasma disruption is a concern for the safe and economical operation of a tokamak power system. Runaway electrons have high energy, 10 to 300 MeV, and may potentially cause extensive damage to plasma-facing components (PFCs) through large temperature increases, melting of metallic components, surface erosion, and possible burnout of coolant tubes. The EPQ code system was developed to simulate the thermal response of PFCs to a runaway electron impact. The EPQ code system consists of several parts: UNIX scripts that control the operation of an electron-photon Monte Carlo code to calculate the interaction of the runaway electrons with the plasma-facing materials; a finite difference code to calculate the thermal response, melting, and surface erosion of the materials; a code to process, scale, transform, and convert the electron Monte Carlo data to volumetric heating rates for use in the thermal code; and several minor and auxiliary codes for the manipulation and postprocessing of the data. The electron-photon Monte Carlo code used was Electron-Gamma-Shower (EGS), developed and maintained by the National Research Center of Canada. The Quick-Therm-Two-Dimensional-Nonlinear (QTTN) thermal code solves the two-dimensional cylindrical modified heat conduction equation using the Quickest third-order accurate and stable explicit finite difference method and is capable of tracking melting or surface erosion. The EPQ code system is validated using a series of analytical solutions and simulations of experiments. The verification of the QTTN thermal code with analytical solutions shows that the code with the Quickest method is better than 99.9% accurate. The benchmarking of the EPQ code system and QTTN versus experiments showed that QTTN’s erosion tracking method is accurate within 30% and that EPQ is able to predict the occurrence of melting within the proper time constraints. QTTN and EPQ are verified and validated as able to calculate the temperature distribution, phase change, and surface erosion successfully.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".