Models of optical characteristics of barrel-vault skylights: development, validation and application
Bibliographic record
Abstract
By admitting natural light deep into a building and connecting occupants with the outside, skylights can improve the aesthetic look of buildings and increase occupant satisfaction. In addition, by allowing the entry of natural light electric light levels can be reduced thereby leading to energy savings. However, the potential energy benefits and amenities of skylights have not been fully exploited in today’s building design due to some theoretical and technical challenges. The lack of design tools is one of the major hurdles building designers face to adopt such products and quantify their energy benefits. The optical characteristics of skylights are the significant factors affecting their energy benefits. Recognizing this gap, the SkyVision tool was developed to assist skylight manufacturers and building designers in developing appropriate skylight designs for given building types and daylighting applications. This paper describes the models implemented in SkyVision to compute the optical characteristics of barrel-vault skylights with clear, fully translucent or partially diffusing glazing under beam and diffuse light. The models are based on the ray-tracing technique. Under diffuse light, two models are developed: (1) a luminance-based model when the sky luminance distribution is known; and (2) an illuminance-based model when the illuminance on a horizontal surface is known. The second model is simpler and faster and more suitable for annual performance calculation. Experimental measurements of the skylight transmittance were conducted under real sky conditions to validate the model predictions. The actual measurements compared reasonably well with the model predictions. The predictions from the luminance-based and illuminance-based models showed good agreement with each other. When applied to an example study, the models predicted that vault skylights with clear glazing are more effective than flat skylights with similar glazing in boosting the beam light transmittance, particularly in winter days. Translucent vault skylights are more effective than flat skylights with similar glazing in reducing solar heat gains, particularly in summer days. Translucent skylights may out-perform transparent skylights, particularly during sunny days in winter.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".