Cooling systems are becoming increasingly complex, shifting the challenge from initial system design to day-to-day operations at scale. Greater system density, tighter tolerances, and highly dynamic workloads, particularly from AI, mean thermal management is now as much a software problem as an engineering one. In response, operators are adopting digital tools, from sensors and advanced controls to digital twins, to simulate, predict, and optimize cooling in real time, improving efficiency while reducing operational risk. This episode will discuss:
- How fluctuating AI driven heat loads are complicating traditional controls strategies
- The growing ecosystem of digital tools to simulate and optimize performance
- Using predictive analytics to detect, isolate, and prevent leaks and contamination
- How digital tools can be leveraged to de-risk the commissioning phase
