Authors

Simulation modeling of processes in life support systems

DOI: 10.17586/1606-4313-2018-17-1-67-73
UDC 697.9/004.942

Simulation modeling of processes in life support systems

Marchenko A.S. , Sulin A.B., Afanasev S.M.

For citation: Marchenko A.S., Sulin A.B., Afanasev S.M. Simulation modeling of processes in life support systems. Vestnik Mezhdunarodnoi akademii kholoda. 2018. No 1. p. 67-73

Abstract
The application of the simulation technique for the design of two life support systems is considered: the "filter–fan" system and the "thermoelectric air cooler – the cooling object". The principles of constructing models of these systems in the AnyLogic environment are given, the results of virtual experiments are analyzed. The output data of the model of the "filter–fan" system are the graphs of airflow versus pressure, which are built automatically in the process of virtual experiment. The model allows to consider the operation of the ventilation system and the process of filter contamination during the design phase and to assess which way to maintain a constant air flow will be most effective for a particular ventilation system. The functional of the model of the system "thermoelectric air cooler – cooling object" allows to simulate the process of output of the specified system to the steady-state regime. The calculation in this case is significantly complicated by the presence of phase transitions of water vapor, which affect both the number of calculated parameters and the complexity of the algorithm. The algorithm for calculating the air cooler in this case divides the operation of the system into stages: dry cooling, cooling with the condensation on the fins of the radiator, cooling with frost on the fins of the radiator and dry cooling after freezing all the moisture contained in the air of the chamber. Based on the calculation results, the dependence of the main design characteristics of the system "thermoelectric air cooler – cooling object" on time is constructed.

Keywords: simulation, life support systems, AnyLogic.

All references

1. Purohit, N., Gupta, D.K., Dasgupta, M.S. Energetic and economic analysis of trans-critical CO2booster system for refrigeration in warm climatic condition. International Journal of Refrigeration. 2017. Vol. 80. P. 182-196.

2. Gaudiano P. Agent based simulation as a tool for the built environment. Annals of the New York Academy of Sciences. 2013. vol. 1295. No 1. p. 26-33.

3. Herrmann C. et al. Energy oriented simulation of manufacturing systems–Concept and application. CIRP Annals-Manufacturing Technology. 2011. vol. 60. No 1. p. 45-48.

4. Seow Y., Rahimifard S. A framework for modelling energy consumption within manufacturing systems. CIRP Journal of Manufacturing Science and Technology. 2011. vol. 4. No 3. p. 258-264.

5. Kamenskiy D.P. Simulation models for automating the analysis and synthesis of design solutions for life support systems for buildings. /The dissertation on competition of a scientific degree of candidate of technical Sciences. Moscow, MGSU, 2011. (in Russian)

6. Kuprijashkin A.G. Basics of modeling systems. Norilsk, NII, 2015. 135 p. (in Russian)

7. Yakimov I.M., Kirpichnikov A.P., Mokshin W.W. Modeling of complex systems in the simulation environment AnyLogic. Vestnik Kazanskogo tekhnologicheskogo universiteta [Bulletin of Kazan Technological University], 2014, No. 13. p. 353-357. (in Russian)

8. Barikaeva N.S., Nikolaenko D.A. Study of dustiness of urban environment near highways. Al'ternativnaya energetika i ekologiya. [Alternative energy and ecology]. 2013, No. 11 (133), pp. 75-78. (in Russian)

9. Sadovnikova N. P. et al. The use of system-dynamic approach to analyze the vehicles and landscaping impact on air quality. World Applied Sciences Journal. 2013. vol. 24. No 24. p. 159-164.

10. Grigoryuk E.N. Estimation of the parameters of the industrial room ventilation system model. Mashinostroyeniye i bezopasnost' zhiznedeyatel'nosti [Mechanical engineering and life safety]. 2013, No 3, pp. 5-9. (in Russian)

11. Li Z., Heo Y., Augenbroe G. HVAC design informed by organizational simulation. Proceedings of the Eleventh International IBPSA Conference. 2009.

12. David B., Ramousse J., Luo L. Optimization of thermoelectric heat pumps by operating condition management and heat exchanger design.Energy conversion and management. 2012. vol. 60. p. 125-133.

13. Enescu D., Virjoghe E.O. A review on thermoelectric cooling parameters and performance. Renewable and Sustainable Energy Reviews. 2014. vol. 38. p. 903-916.

14. Rao R.V., Patel V. Multi-objective optimization of two stage thermoelectric cooler using a modified teaching–learning-based optimization algorithm. Engineering Applications of Artificial Intelligence. 2013. vol. 26. No 1. p. 430-445.

15. Zhu L., Tan H., Yu J. Analysis on optimal heat exchanger size of thermoelectric cooler for electronic cooling applications. Energy conversion and management. – 2013. vol. 76. p. 685-690.

Read the full article