Bibliographic record
Abstract
Abstract 3D printing technology has significant potential to modernize the student laboratory experience in the area of electromagnetic wave propagation and scattering. In this contribution, a fast and low-cost method to 3D print and metallize a variable aperture horn and waveguide launcher are presented. The launcher converts a SubMiniature version A (SMA) coaxial connector to WR 187 waveguide (standard size of waveguide for 3.95 GHz to 5.85 GHz) and is printed from plastic while being metallized with aluminum tape. The launcher provided similar performance to an off the shelf launcher at one 40th the cost. As a teachable extension to this launcher a variable aperture horn is 3D printed and metallized with aluminum tape. The aperture area of the horn is changed by rotating the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mover accent="true"> <mml:mrow> <mml:mi>E</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⃗</mml:mo> </mml:mrow> </mml:mover> </mml:math> walls of the horn away from each other by use of pivot in the transition between the launcher and the horn. This horn showed the expected decrease in beamwidth and increase in peak gain as the aperture area was increased while maintaining a usable impedance match. Modular center ridges were also printed to demonstrate the utility of center ridges in a horn antenna without <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mover accent="true"> <mml:mrow> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⃗</mml:mo> </mml:mrow> </mml:mover> </mml:math> walls. Overall, a modular, inexpensive, and easy to construct waveguide system is presented that is useful for teaching electromagnetics specifically the relationship between aperture area and antenna gain, as well as providing a platform for waveguide experiments.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".