Finite Element Analysis of a Combined White Beam Filter and Visual Screen Using CVD Diamond for the BXDS Beamline
Bibliographic record
Abstract
A white beam filter and visual screen are required for the undulator beamline at the Brockhouse X-Ray Diffraction and Scattering Sector. Reusing a water-cooled copper paddle with a 0.1 mm thick chemical vapor deposition (CVD) diamond foil, a combined filter and screen design is presented. The Canadian Light Source previously experienced failure of CVD diamond filters when exposed to high flux density white beam. Finite element analysis (FEA) was done to determine if the CVD diamond will fracture under the undulator heat load. Conservative failure criteria are selected for CVD diamond based on available literature for the following failure mechanisms: high temperature, thermal fatigue, and temperature induced stress. Four designs are analyzed using FEA models simulating effects of clamping pressure and heat load on the CVD diamond. The simulations are verified by optimizing the model mesh, comparing results against hand calculations, and comparing theoretical absorbed heat load to simulated values. Details of the modeling method are reviewed and results for the different designs evaluated. Suggestions for future testing of CVD diamond in a synchrotron setting will be discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".