Trane Technologies Optimizes Industry‑First Thermal Management Reference Design for AI Factories, Introduces Two New Designs
Company improves design efficiency by nearly 10% and launches two additional Trane® Continuum Rubin DSX reference designs
SWORDS,
Engineered specifically to integrate with the NVIDIA® Omniverse™ DSX Blueprint for AI data centers, the new system optimizations achieve a nearly 10% improvement in overall thermal management performance compared to the original 1-gigawatt reference design announced in October. This frees up 22 megawatts of cooling capacity that can be redirected to IT power, helping boost compute output without increasing total energy consumption.
“Since the launch of our industry-first thermal management system reference design, our team has continued to work hand-in-hand with NVIDIA to push the boundaries of efficiency, scalability and intelligent simulation for gigawatt-scale AI infrastructure,” said
“Efficiently scaling gigawatt-scale AI factories requires a fundamental shift in how we approach thermal management and data center infrastructure simulation,” said
Through continued collaboration with NVIDIA, including as an NVIDIA Partner Network member,
- 250-Megawatt Duplex Simplified System Design: This new design, available now, supports extended free cooling use and incorporates integrated heat recovery, which helps reduce system complexity and results in a 14% increase in thermal management system efficiency with 10% of the heat rejection load going to heat recovery.
- 1-Gigawatt AI Factory Mag-Bearing Air-Cooled System Architecture: This new design, available soon, features a streamlined air-cooled approach using 3-megawatt units to help reduce equipment count and eliminate the need for integrated waterside economizers. The architecture incorporates Trane’s latest magnetic-bearing air-cooled chiller, providing oil-free operation, high efficiency and quieter, more efficient performance through Trane chiller plant controls.
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Forward Looking Statements
This news release includes “forward-looking statements” within the meaning of securities laws, which are statements that are not historical facts, including statements that relate to our product and service innovations for AI data centers and the anticipated benefits of these innovations. These forward-looking statements are based on our current expectations and are subject to risks and uncertainties, which may cause actual results to differ materially from our current expectations. Factors that could cause such differences can be found in our Form 10-K for the year ended
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