Pemodelan Simulasi Aliran Udara terhadap Bangunan 3d Berbasis CityGML dan Computational Fluid Dynamics
Bibliographic record
Abstract
Lingkungan di wilayah kota Malang mengalami pertumbuhan permukiman yang semakin padat serta tata kota semakin tak teratur, sehingga menyebabkan suhu menjadi panas dan warga menjadi tidak nyaman. Angin adalah pergerakan udara yang terjadi karena adanya tekanan udara dari tekanan tinggi ke tekanan rendah. Untuk mengetahui pergerakan aliran udara tersebut, pada penelitian ini dibuat suatu bentuk pemodelan simulasi aliran udara CFD dengan menggunakan Ansys dan bentuk pemodelan 3D CityGML pada LoD 2. Pembuatan simulasi aliran udara ini menggunakan data angin yang diperoleh dari BMKG dan dianalisa untuk membandingkan nilai RMSE dengan data observasi lapangan yang didapatkan dengan menggunakan 2 alat hand anemometer digital. Hasil simulasi aliran udara menunjukkan pengaruh model 3D LOD2 terhadap aliran angin berupa perubahan arah dan kecepatan.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".