SimVCCE

SimVCCE

The SimVCCE is the vapor-compression refrigeration cycle steady-state simulator for education.

The simulator is available in Python, C++ and Modelica.

• Python with the sequential-modular approach

• C++ with the sequential-modular approach

• Modelica

We wish that SimVCCE may be a helpful vehicle for you to

• understand Computational Thinking and improve programming skills

• Modeling and Simulation Methods for Design of Engineering Systems

Python Version

Prerequisites：CoolProp

python -m pip install coolprop

Run

type python vccapp.py in the terminal of ./vccpython

python  vccapp.py

C++ Version

Prerequisites：The shared library of CoolProp

• libCoolProp.dll is the library builded with tdm64-gcc-9.2.0 on Windows

• libCoolProp.so.6.4.1 is the library builded with GCC 9.3 and glibc2.29 above on Linux

Install the CoolProp on Linux

type sudo make install in the terminal of ./vcccpp on Linux

$sudo make install

Build and Run

type make in the terminal of ./vcccpp

>make

Modelica Version

Prerequisites：Dymola

The Example vapor-compression refrigeration cycles

The cycles used in the demo simulator are Example 7.2-3,7.2-4 of CHE 302 Chemical and Materials Engineering Thermodynamics I by Thuan Ke Nguyen

• Example 7.2-3,7.2-4

Example 7.2-3

Refrigerant 134a is the working fluid in an ideal vapor-compression refrigeration cycle that communicates thermally with a cold region at 0°C and a warm region at 26°C.

Saturated vapor enters the compressor at 0°C and saturated liquid leaves the condenser at 26°C.

The mass flow rate of the refrigerant is 0.08 kg/s.

Example 7.2-4

Refrigerant 134a is the working fluid in an ideal vapor-compression refrigeration cycle that communicates thermally with a cold region at - 10°C.

Saturated vapor enters the compressor at - 10°C and saturated liquid leaves the condenser at 9 bar.

The mass flow rate of the refrigerant is 0.08 kg/s.

Determine

• (a) the compressor power, in kW

• (b) the refrigeration capacity, in tons

• © the coefficient of performance