Compressor Polytropic Efficiency Simulator All tools
Interactive simulator

Compressor Polytropic Efficiency Simulator

Estimate compressor outlet temperature, specific work, and shaft power from pressure ratio, inlet temperature, gamma, and polytropic efficiency.

Parameters
Pressure ratio
-

Input Pressure ratio.

Inlet temperature
K

Input Inlet temperature.

Heat-capacity ratio gamma
-

Input Heat-capacity ratio gamma.

Polytropic efficiency
%

Input Polytropic efficiency.

Mass flow
kg/s

Input Mass flow.

Results
Outlet temperature
Specific work
Shaft power estimate
Temperature rise
Pressure ratio and outlet temperature
Head and power breakdown
PR-efficiency power map
Model and equations

$$T_2=T_1\left[1+\frac{PR^{(n-1)/n}-1}{\eta_p}\right]$$

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 Compressor Polytropic Efficiency by dialogue

🙋
When reading Compressor Polytropic Efficiency, where should I look first? Moving Pressure ratio changes both the plots and the result cards.
🎓
Start with Outlet temperature, but do not treat the number as the whole answer. Use Pressure ratio and outlet temperature to confirm the assumed state, then read Head and power breakdown 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 Pressure ratio changes Outlet temperature. How should I judge the influence of Inlet temperature?
🎓
Move Inlet temperature in small steps and watch Specific work. 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 PR-efficiency power map for? It feels like the ordinary curve already tells the story.
🎓
PR-efficiency power 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 Outlet temperature 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 Outlet temperature and Specific work. Then use Pressure ratio and outlet temperature to confirm the assumed state and Head and power breakdown 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 Pressure ratio alone, then move Inlet temperature by a comparable amount and compare the change in Outlet temperature. PR-efficiency power 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 Outlet temperature 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.