Design and simulation of a short, variable-energy 4 to 10 MV S-band linear accelerator waveguide
Bibliographic record
Abstract
PURPOSE: To modify a previously designed, short, 10 MV linac waveguide, so that it can produce any energy from 4 to 10 MV. The modified waveguide is designed to be a drop-in replacement for the 6 MV waveguide used in the author's current linear accelerator-magnetic resonance imager (Linac-MR). METHODS: Using our group's previously designed short 10 MV linac as a starting point, the port was moved to the fourth cavity, the shift to the first coupling cavity was removed and a tuning cylinder added to the first coupling cavity. Each cavity was retuned using finite element method (FEM) simulations to resonate at the desired frequency. FEM simulations were used to determine the RF field distributions for various tuning cylinder depths, and electron trajectories were computed using a particle-in-cell model to determine the required RF power level and tuning cylinder depth to produce electron energy distributions for 4, 6, 8, and 10 MV photon beams. Monte Carlo simulations were then used to compare the depth dose profiles with those produced by published electron beam characteristics for Varian linacs. RESULTS: For each desired photon energy, the electron beam energy was within 0.5% of the target mean energy, the depth of maximum dose was within 1.5 mm of that produced by the Varian linac, and the ratio of dose at 10 cm depth to 20 cm depth was within 1%. CONCLUSIONS: A new 27.5 cm linear accelerator waveguide design capable of producing any photon energy between 4 and 10 MV has been simulated, however coupling port design and the implications of increased electron beam current at 10 MV remain to be investigated. For the specific cases of 4, 6, and 10 MV, this linac produces depth dose profiles similar to those produced by published spectra for Varian linacs.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".