How do you predict flow distribution across a multi-channel cold plate?

STAR-CCM+ resolves channel-level flow distribution directly, capturing local starvation or maldistribution that a bulk flow-rate assumption misses. At the system level, Flomaster models the fluid network to predict how flow splits across multiple parallel cold plates fed by a shared manifold.

Why does my cold plate perform worse in the assembly than on the test bench?

Most commonly because the TIM bond-line and applied pressure at the cold-plate-to-die interface differ from the test bench fixture. In-situ measurement with Simcenter Micred DynTIM captures the interface as actually assembled.

When do I need two-phase cooling instead of single-phase liquid cooling?

As local heat flux rises toward the point where nucleate boiling becomes possible, single-phase thermal-hydraulic models no longer capture the physics accurately. STAR-CCM+ resolves boiling and dryout so the transition point and margin can be quantified for a specific design.

01Liquid Cooling & Cold Plate Design

How do I design a cold plate that stays reliable across the full flow-rate and power range, not just the nominal point?

Cold plate and manifold thermal-hydraulic design validated against measured TIM and junction data.

02The problem

A cold plate design meets its target thermal resistance at the nominal flow rate on the test bench, and then shows a localized temperature excursion in service when a channel runs closer to flow starvation or the interface between the plate and the die sees more pressure variation than the bench fixture applied.

Manifold-level flow distribution across multiple cold plates in a rack or system is often assumed uniform, when in practice pressure drop imbalances mean some plates receive noticeably less flow than others.

Why it's hard

Channel-level flow distribution inside a cold plate is sensitive to manufacturing tolerances and can locally starve even when the bulk flow rate looks adequate
Two-phase effects (boiling, dryout) become possible at high heat flux and are not captured by single-phase thermal-hydraulic assumptions
Manifold-level flow distribution across multiple parallel cold plates is rarely uniform, and pressure-drop imbalance is difficult to predict without a system-level fluid network model
TIM performance between the cold plate and the die or substrate depends on real bond-line thickness and applied pressure in the actual assembly, not a datasheet value
Reliability under thermal and pressure cycling (fatigue at solder or braze joints, TIM degradation) is a separate concern from steady-state thermal-hydraulic performance

03How we solve it

Predict — simulation

Resolve detailed channel-level flow distribution, single- and two-phase heat transfer in STAR-CCM+
Model the fluid network and manifold-level flow distribution across parallel cold plates in Flomaster

Measure — hardware

Characterize in-situ TIM performance at the cold-plate-to-die interface with Simcenter Micred DynTIM
Measure junction temperature and thermal transient response of the cooled device with Simcenter Micred T3Ster

Correlate — close the loop

Use measured TIM resistance as the boundary condition at the cold-plate interface in the STAR-CCM+ model
Validate predicted junction temperature against T3Ster measurement to confirm the combined cold-plate and TIM model is accurate before scaling to the full manifold

04Tools applied

STAR-CCM+

Channel-level flow distribution and single/two-phase heat transfer in cold plates

Flomaster

Fluid-network and manifold flow-distribution modelling across parallel cold plates

Simcenter Micred DynTIM

In-situ TIM characterization at the cold-plate interface

Simcenter Micred T3Ster

Measured junction temperature to validate the cold-plate thermal model

05Standards in scope