PhasurgeDirect Cooling

Technology

AI-driven direct cooling, validated before delivery

The technical stack links simulation, hardware-in-the-loop validation, control optimization and real-condition testing across compute, storage and EV testing scenarios.

Governing equations
DNS / OpenFOAM
Engineering correlations
Design envelope output

AI two-phase-flow simulation platform

Combines OpenFOAM customization, micro-scale DNS, engineering solvers and high-fidelity correlations to turn physics and test data into engineering rules.

Prototype parameters

Performance envelope

Hardware-in-the-loop rapid simulation

Scans design variables, geometry, materials and boundary conditions to generate reduced-order performance envelopes for faster prototype iteration.

Illustrative control interface · Example values

Load

78%

Cooling

64%

Efficiency

92%

Two-phase stability optimization

Uses efficiency maps, operating constraints, historical power, task queues, utilization and environment variables for cooling feed-forward and efficiency optimization.

1TTV thermal source
2Cold-plate sample
3T-P-Q acquisition
4Automated report

Standardized real-condition testing

Uses test benches, cold-plate samples, TTV thermal vehicles and automated reports to pull validation ahead of delivery.

System blueprint

From cooling to energy operation

Connect solar, storage and compute equipment to coordinate power supply and cooling.

Power and cooling blueprint

Ecosystem

Joint labs and algorithm stack

XJTU national two-phase-flow research platform

Joint thermal-management materials lab · Foshan Hebang New Materials

Advanced low-GWP refrigerant joint lab · Zhejiang Juhua

Full-lifecycle scenario test lab · Shenzhen Precise

Balanced flow allocation

Energy scheduling algorithm

Short/long-term compute-load forecast

Curious what phase-change direct cooling does in your operating envelope?

We bring the demo kit and the test rig to you — rebuilt for your scenario from cold plate up to rack-level CDU.