From incident to insight: Fire risk in modern data centers

Modern data centers are becoming increasingly vital infrastructure, yet several recent high-profile fire incidents have exposed persistent vulnerabilities. As artificial intelligence (AI) technologies continue to advance, these risks will only intensify. Contributing causes of such fires include electrical faults, battery failures, cooling system malfunctions, and human error. This perspective paper synthesizes key information from recently reported incidents and discusses practical fire safety strategies for both prevention (i.e., AI-driven fault detection and fire-safe battery storage) and suppression (i.e., clean agents and liquid nitrogen system). Emerging technologies are highlighted as potential fire safety enhancements, and their development and implementation in modern data centers are recommended. Two relevant methods for fire risk assessment are explored, specifically non-scenario-based consideration of common fire causes and scenario-based examination of recent incidents. These assessment methods should be utilized while considering engineering design practices, operational feasibility, and regulatory alignment to enhance resilience and promote adoption in modern data centers. This work intends to offer a perspective on data center fire risk assessment by examining past incidents, presenting insights into current knowledge gaps, and proposing future research and stakeholder efforts for the improvement of data center fire safety. • Fire incident risk across modern data centers is increasing rapidly. • Contributing causes of these fires are analyzed based on representative case studies. • Practical fire safety strategies for both prevention and suppression are discussed. • Emerging technologies are highlighted as potential enhancements to fire safety.

Authors

Institutions

Publication Details

Journal
Journal of Loss Prevention in the Process Industries
Published
2025-12-17
DOI
https://doi.org/10.1016/j.jlp.2025.105890
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From incident to insight: Fire risk in modern data centers

Qingsheng Wang, Chi‐Yang Li, Michael J. Gollner, Jiejia Wang et al.
Journal of Loss Prevention in the Process Industries
Software System Performance and Reliability
article

From incident to insight: Fire risk in modern data centers

Qingsheng Wang, Chi‐Yang Li, Michael J. Gollner, Jiejia Wang, Tylee L. Kareck
article en

Abstract

Modern data centers are becoming increasingly vital infrastructure, yet several recent high-profile fire incidents have exposed persistent vulnerabilities. As artificial intelligence (AI) technologies continue to advance, these risks will only intensify. Contributing causes of such fires include electrical faults, battery failures, cooling system malfunctions, and human error. This perspective paper synthesizes key information from recently reported incidents and discusses practical fire safety strategies for both prevention (i.e., AI-driven fault detection and fire-safe battery storage) and suppression (i.e., clean agents and liquid nitrogen system). Emerging technologies are highlighted as potential fire safety enhancements, and their development and implementation in modern data centers are recommended. Two relevant methods for fire risk assessment are explored, specifically non-scenario-based consideration of common fire causes and scenario-based examination of recent incidents. These assessment methods should be utilized while considering engineering design practices, operational feasibility, and regulatory alignment to enhance resilience and promote adoption in modern data centers. This work intends to offer a perspective on data center fire risk assessment by examining past incidents, presenting insights into current knowledge gaps, and proposing future research and stakeholder efforts for the improvement of data center fire safety. • Fire incident risk across modern data centers is increasing rapidly. • Contributing causes of these fires are analyzed based on representative case studies. • Practical fire safety strategies for both prevention and suppression are discussed. • Emerging technologies are highlighted as potential enhancements to fire safety.

Journal of Loss Prevention in the Process IndustriesVol. 100
George Washington University (US), Texas A&M University (US), University of California, Berkeley (US)
Openalex Percentile: Top 54%
Software System Performance and Reliability
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.