Logo image
Numerical Investigation of the Thermal Environment in a Data Center Under Dynamic Server Loads Driven by Artificial Neural Network Models
Journal article   Open access   Peer reviewed

Numerical Investigation of the Thermal Environment in a Data Center Under Dynamic Server Loads Driven by Artificial Neural Network Models

Chang Yue, Zimu Li, Jiaqiang Wang, Zhang Quan, Zhiqiang Zhai and Michael W. Jack
Buildings, Vol.16(14), 2780
13/07/2026
Handle:
https://hdl.handle.net/10523/51866

Abstract

This study numerically investigates the transient thermal response of a raised-floor data center under dynamic AI server loads. Power profiles of DGX A100 servers running GEMM, VGG-19, and ResNet-152 workloads were used as time-varying boundary conditions in CFD simulations. Six load scenarios were analyzed to evaluate the dynamic responses of cooling capacity, rack inlet and outlet temperatures, and net airflow rate. The results show that the response lag of air-conditioning units causes a temporary mismatch between cooling supply and server heat dissipation, leading to transient inlet-temperature fluctuations. Fluctuating workloads produce larger outlet-temperature amplitudes and higher temperature change rates than stable workloads, while mixed workloads change the overall fluctuation intensity and affect neighboring-rack airflow through cold-aisle pressure interactions. These findings can support workload-aware rack arrangement and adaptive cooling control for future AI-oriented data centers.
pdf
buildings-16-02780-v27.24 MBDownloadView
Published (Version of record) Open Access CC BY V4.0
url
https://doi.org/10.3390/buildings16142780View
Published (Version of record) Open CC BY V4.0

Metrics

1 File views/ downloads
2 Record Views

Details

Logo image