Estimate cleanroom particle recovery time from air-change rate, effective removal efficiency, initial concentration, and target fraction.
Parameters
Air changes ACH
1/h
Input Air changes ACH.
Effective removal efficiency
%
Input Effective removal efficiency.
Initial concentration
count/m3
Input Initial concentration.
Target fraction
%
Input Target fraction.
Results
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Time constant
—
Time to target
—
Concentration after 10 min
—
Removal rate
Particle recovery curve
Ventilation, efficiency, and target
ACH-efficiency recovery map
Model and equations
$$C(t)=C_0\exp(-\eta ACH\,t/60)$$
This simplified model captures the main relationship only. Boundary conditions, losses, nonlinear effects, and code-specific corrections still need separate checks.
How to read it
Use the main plot to read the controlling trend, including break points that a single result card can hide.
Use the sensitivity view to find input combinations where margin collapses quickly.
For early design, focus on which input controls margin before trusting the absolute value.
Learn Cleanroom Air Change Recovery by dialogue
🙋
When reading Cleanroom Air Change Recovery, where should I look first? Moving Air changes ACH changes both the plots and the result cards.
🎓
Start with Time constant, but do not treat the number as the whole answer. Use Particle recovery curve to confirm the assumed state, then read Ventilation, efficiency, and target for the distribution or trend. Use the main plot to read the controlling trend, including break points that a single result card can hide.
🙋
I can see why Air changes ACH changes Time constant. How should I judge the influence of Effective removal efficiency?
🎓
Move Effective removal efficiency in small steps and watch Time to target. That reveals which term is controlling the result. This simplified model captures the main relationship only. Boundary conditions, losses, nonlinear effects, and code-specific corrections still need separate checks. A single operating point is not enough; sweep the realistic scatter range.
🙋
What is ACH-efficiency recovery map for? It feels like the ordinary curve already tells the story.
🎓
ACH-efficiency recovery map is for finding boundaries where the condition becomes risky or margin collapses quickly. Use the sensitivity view to find input combinations where margin collapses quickly. In First-pass comparison of design options before review, the important question is often what happens after a small change, not only the nominal value.
🙋
So if Time constant is within the target, can I accept the condition?
🎓
Treat this as a first-pass review. It helps with Narrowing controlling factors and worst-side conditions before detailed analysis and Teaching or explaining the equation, numbers, and visualization under the same inputs, but final decisions still need standards, measured data, detailed analysis, and vendor limits. For early design, focus on which input controls margin before trusting the absolute value.
Practical use
First-pass comparison of design options before review.
Narrowing controlling factors and worst-side conditions before detailed analysis.
Teaching or explaining the equation, numbers, and visualization under the same inputs.
FAQ
Start with Time constant and Time to target. Then use Particle recovery curve to confirm the assumed state and Ventilation, efficiency, and target to read distribution or bias. Use the main plot to read the controlling trend, including break points that a single result card can hide
Move Air changes ACH alone, then move Effective removal efficiency by a comparable amount and compare the change in Time constant. ACH-efficiency recovery map shows combinations where margin or performance changes quickly.
Use it for First-pass comparison of design options before review. Instead of trusting a single point, widen the input range and check whether Time constant keeps enough margin before moving to detailed analysis.
This simplified model captures the main relationship only. Boundary conditions, losses, nonlinear effects, and code-specific corrections still need separate checks. Final decisions still require standards, measured data, detailed analysis, and vendor limits.