Optimizing daylight, energy and occupant comfort performance of classrooms with photovoltaic integrated vertical shading devices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This work proposes a multi-objective approach for optimizing the design of fixed vertical, parametrically modeled PV integrated shading devices to achieve their highest benefits to the indoor environment and residents in a classroom. Since the geometric design of conventional shading devices, whether in real-world applications or the literature, is usually restricted to non-amorphous and rectangular shapes, our goal is to gain insight into the likely advantages of employing panels with novel design alternatives. To this end, we initially developed a parametric model of shading devices containing planar PV panels utilizing the Grasshopper program. Next, the environmental plugins of Honeybee and Ladybug were used to assess daylight and energy operations along with occupants’ thermal and visual comfort. Moreover, to lessen the required lighting energy and enhance users’ visual convenience by providing appropriate illuminance levels required for a specific task, we divided the classroom into adjustable lighting zones. The last step was performing the optimization process via the Octopus plugin for Grasshopper and determining the optimal solutions. The numerical results of the annual simulations show that we reached considerable energy saving up to 20% while enhancing occupants’ thermal and visual comfort.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it