FDTD Model of Noise Pollution from an AI Data Center

Abstract:The sudden growth in AI data centers is raising numerous environmental concerns. Low-frequency noise pollution is a concern for local residents, that may not just be an annoyance but also carry significant health impacts. An FDTD model of sound propagation over the topography near an AI data center is presented. The topography plays a large role in the level of noise pollution, with areas of sudden elevation on either side of the river near the AI data center more susceptible to high noise levels, while areas further afield largely protected from noise pollution by the topography. Understanding the role that topography plays in noise pollution, and capturing the noise pollution in specific topographies, can help identify areas where noise mitigation strategies might be best employed.

Computational Physics (physics.comp-ph); Machine Learning (cs.LG)

arXiv:2610.14899 [physics.comp-ph]

(or arXiv:2610.14899v1 [physics.comp-ph] for this version)

https://doi.org/10.48550/arXiv.2610.14899 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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