Static mixers: balancing mixing quality and pressure drop with CFD

The situation

Static mixers sit right at the intersection of performance and cost: you want uniformity, but you can't afford excessive delta-P. Many teams rely on correlations or vendor curves that don't reflect their exact geometry, viscosity regime, or multiphase behavior.

Why it matters

Without defensible performance understanding, teams risk:

• Energy penalties (higher pumping costs)
• Underspecified mixing (quality defects, batch variability)
• Disputes about "guaranteed" performance
• Late redesign when the system is already built

What analysis changes

A focused simulation study can help answer decision-level questions such as:

• The delta-P vs. mixing trade curve for your specific conditions
• Where losses occur and which elements drive them
• Sensitivity to flow rate, viscosity, and phase fraction
• Whether small geometry changes create disproportionate gains

Typical approach

1. Define the decision: sizing, element selection, or a redesign change.
2. Build a bounded simulation model (RANS/LES as justified; scalar mixing metrics where appropriate).
3. Sweep a minimal set of operating points to map sensitivities.
4. Deliver the trade space clearly: what you gain per unit delta-P and where the "knee" is.

Deliverables

• Delta-P curves across operating ranges
• Mixing effectiveness metrics (distribution, scalar uniformity, dead zones)
• Geometry/element recommendations with rationale
• Assumptions/limitations documented for sign-off

Common pitfalls

• Running too many cases without a decision framework
• Reporting only averages (missing maldistribution and dead zones)
• Comparing to correlations without explaining why they diverge