Add dataset card

README.md

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+---
+license: apache-2.0
+task_categories:
+  - image-to-image
+tags:
+  - physics
+  - cfd
+  - digital-twin
+  - datacenter
+  - surrogate-model
+  - neural-operator
+  - nvidia
+  - physicsnemo
+pretty_name: "Boreas: Datacenter Digital Twin Surrogate Predictions"
+size_categories:
+  - 1K<n<10K
+---
+
+# Boreas Data — Datacenter Digital Twin Surrogate Predictions
+
+Prediction outputs from five neural surrogate models trained on [NVIDIA PhysicsNeMo-Datacenter-CFD](https://huggingface.co/datasets/nvidia/PhysicsNeMo-Datacenter-CFD) for **Project Boreas** (SJSU MSDA capstone, Spring 2026).
+
+This dataset powers the [Boreas Omniverse Kit operator console](https://github.com/irangareddy/kit-app-template) — a custom NVIDIA Omniverse application with an LLM agent (GPT-4o) and Apple Vision Pro AR streaming.
+
+## Contents
+
+| Folder | What | Count | Size each |
+|--------|------|-------|-----------|
+| test_data/inputs/ | 10-channel input tensors (80x96x960) | 10 | 282 MB |
+| test_data/targets/ | 5-channel CFD ground truth (80x96x960) | 10 | 141 MB |
+| outputs/predictions/ | Model predictions (5-ch, 80x96x960) | 50 | 141 MB |
+| stl/ | OpenFOAM datacenter geometry | 6 | < 1 MB |
+| results/ | Evaluation metrics JSON | 2 | < 1 MB |
+
+**Total: 79 files, ~11 GB**
+
+## Five surrogate models
+
+| Model | Family | Params | T MAE (C) | Inference (ms) |
+|-------|--------|--------|-----------|----------------|
+| **U-Net** | Spatial (CNN) | 22.6M | **0.205** | 177 |
+| PI-U-Net | Spatial + physics | 344K | 0.244 | 87 |
+| FNO | Spectral (FFT) | 28.3M | 0.489 | 636 |
+| PI-FNO | Spectral + physics | 28.3M | 0.505 | 674 |
+| Transolver | Transformer | 545K | 0.598 | 4,972 |
+
+Trained at full resolution (960x96x80 = 7.37M points) on NVIDIA GB10 (Grace Blackwell, 128 GB).
+
+## File naming
+
+Predictions: `outputs/predictions/sample_NNNN_MODEL.npy`
+
+- NNNN = 0000-0009 (from PhysicsNeMo test split)
+- MODEL = unet, fno, pifno, pi_unet, or transolver
+- Shape: (5, 80, 96, 960) — channels: Ux, Uy, Uz, T, p (Z-score normalized)
+
+## Denormalization
+
+| Field | Mean | Std | Unit |
+|-------|------|-----|------|
+| T | 39.0 | 4.0 | C |
+| Ux, Uy, Uz | 1.5984 | 1.3656 | m/s |
+| p | 6.1227 | 4.1660 | Pa |
+
+To convert: `T_celsius = prediction[3] * 4.0 + 39.0`
+
+## Quick start with Kit app
+
+```bash
+git lfs install
+git clone https://huggingface.co/datasets/irangareddy/boreas-data ~/boreas-data
+git clone https://github.com/irangareddy/kit-app-template.git
+cd kit-app-template
+.\repo.bat build
+.\run_streaming.bat
+```
+
+## Quick start in Python
+
+```python
+import numpy as np
+
+gt = np.load("test_data/targets/sample_0000.npy")
+pred = np.load("outputs/predictions/sample_0000_unet.npy")
+
+T_gt = gt[3] * 4.0 + 39.0
+T_pred = pred[3] * 4.0 + 39.0
+print(f"Temperature MAE: {abs(T_pred - T_gt).mean():.3f} C")
+```
+
+## Source
+
+Derived from [nvidia/PhysicsNeMo-Datacenter-CFD](https://huggingface.co/datasets/nvidia/PhysicsNeMo-Datacenter-CFD) (Apache 2.0).
+
+## Citation
+
+```bibtex
+@misc{boreas2026,
+  title={Evaluating Neural Operator Architectures for Datacenter Digital Twin Surrogate Models},
+  author={Nukala, Sai Ranga Reddy and Kankanala, Shaila Reddy and Singh, Sadhvi and Jonnalagadda, Akshith Reddy and Shim, Simon},
+  year={2026},
+  institution={San Jose State University},
+  url={https://github.com/irangareddy/298AB}
+}
+```
+
+## Links
+
+- Research: [github.com/irangareddy/298AB](https://github.com/irangareddy/298AB)
+- Kit app: [github.com/irangareddy/kit-app-template](https://github.com/irangareddy/kit-app-template)
+- Source data: [nvidia/PhysicsNeMo-Datacenter-CFD](https://huggingface.co/datasets/nvidia/PhysicsNeMo-Datacenter-CFD)