馃挩 Chapter 8: Modeling and Setting of Displacement Compressors
Off-Design Behavior Demystified
Displacement compressors are everywhere鈥攍earn how to model their off-design behavior!
Key Parameters:
- Volumetric efficiency (位): Actual swept volume.
- Isentropic efficiency (畏s): Two models (5-parameter and simplified 3-parameter).
Loss Mechanisms:
- Dead space, pressure drops, thermal effects, leakage.
- Optimal compression ratio and rotation speed.
Thermoptim Implementation:
- Technological design screens for adiabatic and cooled compressors.
- Fixed internal volume ratio (Vi) and its impact on performance.
Why It Matters: Understand real-world behavior鈥攏ot just ideal conditions!
Abstract
This chapter focuses on off-design modeling of displacement compressors. The models assume that displacement compressor behavior can be represented with reasonable accuracy by two parameters: volumetric efficiency 位, which characterizes actual swept volume, and classical isentropic efficiency 畏s. The chapter begins by analyzing loss mechanisms in displacement compressors, including dead space effects, pressure drops in manifolds and valves, wall thermal effects, and leakage losses. Volumetric efficiency laws show variation with compression ratio and rotation speed, with an optimum at relatively high speeds. For isentropic efficiency, two alternative formulations are proposed: a five-parameter model and a simpler three-parameter model with clear physical interpretation based on limiting efficiency, maximum efficiency, and optimal compression ratio. The three-parameter model facilitates identification from experimental data while preventing physically unrealistic behavior at high compression ratios. Practical implementation is demonstrated through Thermoptim’s technological design screens, which accommodate both adiabatic and cooled compressors. Special consideration is given to fixed internal volume ratio (Vi) rotary positive displacement compressors, where under-compression or over-compression occurs when operating pressure ratio differs from constructive ratio. The chapter addresses parameter identification challenges arising from scarce experimental data and calculation procedures for both design and off-design modes.