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As AI power densities continue to rise, liquid cooling has become a necessity, bringing new technical, integration, and operational challenges for manufacturers and operators alike. This session explores where liquid cooling deployments most often encounter risk, and why strong engineering and simulation capability is critical. It also examines how physics-based simulation and digital twins enable early design validation, reducing integration complexity and commissioning risk before systems are deployed on site. This episode will discuss:
- The technical, integration, and operational challenges of scaling liquid cooling for high-density AI workloads
- Why engineering and simulation expertise is critical for reliable and scalable liquid cooling deployments
- How physics-based simulation and digital twins accelerate liquid-cooling design at component and system level
- How early-stage validation and cross-vendor collaboration can enable faster, lower-risk deployment
