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license: mit
pretty_name: MTO 2D v0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
- split: test
path: data/test-*
---
# MTO2D v0
EngiBench-compatible MTO2D dataset published as
`IDEALLab/mto_2d_v0`. It contains 5,666 converged `(400, 200)`
half-domain designs with train/val/test splits of
4,249/283/1,134.
Objectives: `mean_temperature` and `power_dissipation` are historical source-optimization
labels logged before the final MMA/Heaviside update. The stored `app/200/gamma`
design is the subsequent post-update density field.
For the EngiBench problem, a frozen simulator uses the following physics:
`q=0.01`, `alphaMax=5025200`,
`Heaviside=59.8`, with design updates disabled.
`optimal_design` is a flattened float list of length
80,000, reshaping to `(400, 200)` and symmetrical about the vertical axis so as to yield a `(400, 400)` heat sink.
## Citation
```bibtex
@article{drake2026quantize,
title={To Quantize or Not to Quantize: Effects on Generative Models for Topology Optimization Problems},
author={Drake, Arthur and Chen, Qiuyi and Wang, Jun and Nejat, Ardalan and Guest, James K and Fuge, Mark},
journal={Journal of Mechanical Design},
volume={148},
number={10},
pages={101704},
year={2026},
publisher={American Society of Mechanical Engineers}
}
``` |