Heat and Mass Transfer

, Volume 55, Issue 2, pp 445–465 | Cite as

Comparative investigation and multi objective design optimization of R744/R717, R744/R134a and R744/R1234yf cascade rerfigeration systems

  • Mert Sinan TurgutEmail author
  • Oguz Emrah Turgut


This study aims to make a comparative investigation on performance analysis of cascade refrigeration systems using R744/R717, R744/R134a, and R744/R1234yf refrigerant pairs. Artificial Cooperative Search methaheuristic algorithm is put into practice to obtain the optimal values of eight design parameters including Condenser and evaporator temperature, R744 condensing temperature, temperature difference in the cascade condenser, and amount of subcooling and superheating at the bottom and the top of the cascade cycle. Second law efficiency and total annual cost of the cascade refrigeration system are chosen as design objectives to be optimized individually and concurrently in order to obtain the optimal operating conditions of the system. Single optimization results show that R744/R1234yf system has the lowest operating cost while having the highest second law efficiency compared to other cycle configurations. A set of non-dominated solutions obtained through multi objective Artificial Cooperative Search algorithm is represented in the form of Pareto front and the best result is chosen from the well-reputed decision makers of TOPSIS and LINMAP for each cycle configuration. Multi objective optimization results reveal that design variables of the refrigeration system can create a trade off between problem objectives. A sensitivity analysis is performed to investigate the influences of varying values of design variables upon problem objectives while the system is operated under optimal conditions.



Heat transfer area (m2)


Baffle spacing (m)


Boiling number


Capital cost ($)


Unit electricity cost ($)


Specific heat (kJ/kgK)


Compression ratio


Coefficient of performance


Capital Recovery Factor


Shell diameter (m)


Tube and fin diameter (m)


Fang number


Mass flux (kg/m2s)


Gravitational acceleration (m/s2)


Height (m) – Annual working hour of the system component (hour)


Heat transfer coefficient (W/m2K) - Enthalpy (J/kg)


Enthalpy of vaporization (J/kg)


Interest rate (%)


Thermal conductivity (W/mK)


Length (m)

\( \dot{\mathrm{m}} \)

Mass flow rate (kg/s)


Number of tube pass


Number of tube rows in the pack - Operating period of the system


Tube pitch (m)


Fin pitch (fin/m)


Heat flow (W)


Prandtl number


Fouling resistance (m2K/W)


Reynold number


Entropy (kj/kgK)


Temperature (°C - K)


Mean logarithmic temperature difference


Temperature difference in the cascade condenser


Ambient temperature (K)


Tube thickness (m)


Overall heat transfer coefficient (W/m2K)


Compressor power (kW)


Martinelli parameter


Vapor quality


Capital cost ($)

Greek Symbols


Fin thickness (m)


Void fraction


Second law efficiency


Isentropic compressor efficiency


Mechanical compressor efficiency


Maintenance factor


Dynamic viscosity (Pa.s)


Density (kg/m3)


Surface tension (N/m)


C – cond


E – evap



High temperature circuit


Hot temperature medium




Low temperature circuit


Low temperature medium






Two phase




Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Mechanical Engineering DepartmentEge UniversityBornovaTurkey

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