Freeform Lens Design with Arbitrary Illuminance Distribution in LED Road Lighting
Bibliographic record
Abstract
A new freeform lens design method is proposed to realize arbitrary illuminance distribution in LED road lighting.The purpose is to achieve specific illuminance distribution in both longitudinal and transverse directions on the road surface for a single luminaire,so as to meet the demands of illuminance and luminance uniformity and surrounding ratio on the road surface.Grid divisions of energy both on the light source and the receiver are taken with the combination of variable separation mapping method and iterative minimum energy block method,so as to make sure the equal energy be received in corresponding cells of the source and the receiver.Freeform lens surface is constructed based on edge ray principle,Snell's law and error control.Meanwhile,considering the position and tilt angle of the luminaires,the lens is asymmetric in the transverse direction.Take it for example that the illuminance distribution in longitudinal direction on the road surface is cosine,while in transverse direction trapezoidal,a polycarbonate discontinuous freeform lens was designed according to this method.The simulated illumiance distribution in longitudinal direction on the road surface is similar to cosine,with the error less than 6%.The overall illuminance uniformity reaches 0.93,and the surrounding ratio is 0.55.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".