Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2019, , 237 - 250, 24.06.2019
https://doi.org/10.18186/thermal.581750

Öz

Kaynakça

  • [1] Getu, H. M., Bansal, P. K. (2006). Simulation model of a low-temperature supermarket refrigeration system. HVAC&R Research, 12(4), 1117-1139.
  • [2] Getu, H. M., Bansal, P. K. (2008). Thermodynamic analysis of an R744–R717 cascade refrigeration system. International journal of refrigeration, 31(1), 45-54.
  • [3] Messineo, A. (2012). R744-R717 cascade refrigeration system: performance evaluation compared with a HFC two-stage system. Energy Procedia, 14, 56-65.
  • [4] Pearson, A. (2001). New developments in industrial refrigeration. Ashrae Journal, 43(3), 54.
  • [5] Devotta, S., Padalkar, A. S., Sane, N. K. (2005). Performance assessment of HC-290 as a drop-in substitute to HCFC-22 in a window air conditioner. International Journal of Refrigeration, 28(4), 594-604.
  • [6] Chen, W. (2008). A comparative study on the performance and environmental characteristics of R410A and R22 residential air conditioners. Applied thermal engineering, 28(1), 1-7.
  • [7] Lee, T. S., Liu, C. H., Chen, T. W. (2006). Thermodynamic analysis of optimal condensing temperature of cascade-condenser in CO2/NH3 cascade refrigeration systems. International Journal of Refrigeration, 29(7), 1100-1108.
  • [8] Bhattacharyya, S., Bose, S., Sarkar, J. (2007). Exergy maximization of cascade refrigeration cycles and its numerical verification for a transcritical CO2–C3H8 system. International Journal of Refrigeration, 30(4), 624-632.
  • [9] Mafi, M., Naeynian, S. M., Amidpour, M. (2009). Exergy analysis of multistage cascade low temperature refrigeration systems used in olefin plants. International journal of refrigeration, 32(2), 279-294.
  • [10] Keshtkar, M. M., Talebizadeh, P. (2017). Multi-objective optimization of cooling water package based on 3E analysis: A case study. Energy, 134, 840-849.
  • [11] Rahdar, M. H., Heidari, M., Ataei, A., Choi, J. K. (2016). Modeling and optimization of R-717 and R-134a ice thermal energy storage air conditioning systems using NSGA-II and MOPSO algorithms. Applied Thermal Engineering, 96, 217-227.
  • [12] Najjar, Y. S., Abubaker, A. M. (2017). Thermoeconomic analysis and optimization of a novel inlet air cooling system with gas turbine engines using cascaded waste-heat recovery. Energy, 128, 421-434.
  • [13] Rezayan, O., Behbahaninia, A. (2011). Thermoeconomic optimization and exergy analysis of CO2/NH3 cascade refrigeration systems. Energy, 36(2), 888-895.
  • [14] Raja, B. D., Jhala, R. L., Patel, V. (2018). Multiobjective thermo‐economic and thermodynamics optimization of a plate–fin heat exchanger. Heat Transfer—Asian Research, 47(2), 253-270.
  • [15] Dubey, A. M., Kumar, S., Agrawal, G. D. (2014). Thermodynamic analysis of a transcritical CO2/propylene (R744–R1270) cascade system for cooling and heating applications. Energy conversion and management, 86, 774-783.
  • [16] Parekh, A. D., Tailor, P. R., Sutaria, N. (2012). Thermoeconomic Optimization of Cascade Refrigeration System using Refrigerant Pair R404A-R508B. In Applied Mechanics and Materials (Vol. 110, pp. 677-684). Trans Tech Publications.
  • [17] Keshtkar, M. M. (2016). Effect of subcooling and superheating on performance of a cascade refrigeration system with considering thermo-economic analysis and multi-objective optimization. Journal of Advanced Computer Science and Technology, 5(2), 42-47.
  • [18] Toghyani, S., Kasaeian, A., Ahmadi, M. H. (2014). Multi-objective optimization of Stirling engine using non-ideal adiabatic method. Energy Conversion and Management, 80, 54-62.
  • [19] Sadatsakkak, S. A., Ahmadi, M. H., Ahmadi, M. A. (2015). Optimization performance and thermodynamic analysis of an irreversible nano scale Brayton cycle operating with Maxwell–Boltzmann gas. Energy Conversion and Management, 101, 592-605.
  • [20] Kaushik, S. C., Kumar, R., Arora, R. (2016). Thermo-economic optimization and parametric study of an irreversible regenerative Brayton cycle. Journal of Thermal Engineering (ICES2015).
  • [21] Heidarnejad, P. (2017). Exergy Based Optimization of a Biomass and Solar Fuelled CCHP Hybrid Seawater Desalination Plant. Journal of Thermal Engineering, 3(1), 1034-1043.
  • [22] Keshtkar, M. M. (2017). Performance analysis of a counter flow wet cooling tower and selection of optimum operative condition by MCDM-TOPSIS method. Applied Thermal Engineering, 114, 776-784.
  • [23] Wouagfack, P. A. N., Tchinda, R. (2011). Irreversible three-heat-source refrigerator with heat transfer law of QαΔ (T− 1) and its performance optimization based on ECOP criterion. Energy Systems, 2(3-4), 359-376.
  • [24] Kotas, T. J. (1986). Exergy method of thermal and chemical plant analysis. Trans IChemE, 64, 212-229.
  • [25] Bejan, A., Tsatsaronis, G., Moran, M., Moran, M. J. (1996). Thermal design and optimization. John Wiley & Sons.
  • [26] Aminyavari, M., Najafi, B., Shirazi, A., Rinaldi, F. (2014). Exergetic, economic and environmental (3E) analyses, and multi-objective optimization of a CO2/NH3 cascade refrigeration system. Applied Thermal Engineering, 65(1-2), 42-50.
  • [27] Rao, R. V., Saroj, A. (2018). Multi-objective design optimization of heat exchangers using elitist-Jaya algorithm. Energy Systems, 9(2), 305-341.
  • [28] Klein, S. A., Alvarado, F. L. (1992). EES: Engineering equation solver for the Microsoft Windows operating system. F-Chart software.
  • [29] Nellis, G., Klein, S. (2009). Mass transfer. Heat Transfer, Cambridge University Press, New York.
  • [30] Kays, W.M., London, A.L., “Compact Heat Exchangers”, Krieger Publishing Company, (1984).
  • [31] Shah, R.K., Sekulic, D.P., “Fundamentals of Heat Exchanger Design”, Wiley, (2003)
  • [32] Thirumaleshwar, M., “Software Solutions to Problems on Heat Transfer - Boiling and Condensation”, (2013)
  • [33] Harrell Jr, F. E. (2015). Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis. Springer.
  • [34] Konak, A., Coit, D. W., Smith, A. E. (2006). Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety, 91(9), 992-1007.
  • [35] Holland, J. H. (1992). Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT press.

MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES)

Yıl 2019, , 237 - 250, 24.06.2019
https://doi.org/10.18186/thermal.581750

Öz

This work presents the
optimization of a two stage-cascade refrigeration system (TS-CRS), based on
exergetic, economic, environmental, and sensitive analysis (3ES). R134a and
R744 are considered as the refrigerants of high and low temperature circuits,
respectively. Two single-optimization strategies including exergetic and
economic optimizations and a multi-objective optimization are applied on the
problem. In the first step, a comprehensive performance evaluation of different
effective parameters, based on the genetic algorithm, used to indicate the
optimum operative conditions in single objective strategies. In the next step,
a multi-objective optimization is performed with considering a decision-making
strategy based on the Pareto frontier using TOPSIS method. The higher exergetic
efficiency and lower cost found in the exergetic and economic
single-optimization, respectively. The multi-objective optimization results
demonstrate that, the total system cost and the exergetic efficiency increase
28.6% and 99.5%, respectively, compared to the base design, and 46.6% higher
energy can be saved in the compressors.

Kaynakça

  • [1] Getu, H. M., Bansal, P. K. (2006). Simulation model of a low-temperature supermarket refrigeration system. HVAC&R Research, 12(4), 1117-1139.
  • [2] Getu, H. M., Bansal, P. K. (2008). Thermodynamic analysis of an R744–R717 cascade refrigeration system. International journal of refrigeration, 31(1), 45-54.
  • [3] Messineo, A. (2012). R744-R717 cascade refrigeration system: performance evaluation compared with a HFC two-stage system. Energy Procedia, 14, 56-65.
  • [4] Pearson, A. (2001). New developments in industrial refrigeration. Ashrae Journal, 43(3), 54.
  • [5] Devotta, S., Padalkar, A. S., Sane, N. K. (2005). Performance assessment of HC-290 as a drop-in substitute to HCFC-22 in a window air conditioner. International Journal of Refrigeration, 28(4), 594-604.
  • [6] Chen, W. (2008). A comparative study on the performance and environmental characteristics of R410A and R22 residential air conditioners. Applied thermal engineering, 28(1), 1-7.
  • [7] Lee, T. S., Liu, C. H., Chen, T. W. (2006). Thermodynamic analysis of optimal condensing temperature of cascade-condenser in CO2/NH3 cascade refrigeration systems. International Journal of Refrigeration, 29(7), 1100-1108.
  • [8] Bhattacharyya, S., Bose, S., Sarkar, J. (2007). Exergy maximization of cascade refrigeration cycles and its numerical verification for a transcritical CO2–C3H8 system. International Journal of Refrigeration, 30(4), 624-632.
  • [9] Mafi, M., Naeynian, S. M., Amidpour, M. (2009). Exergy analysis of multistage cascade low temperature refrigeration systems used in olefin plants. International journal of refrigeration, 32(2), 279-294.
  • [10] Keshtkar, M. M., Talebizadeh, P. (2017). Multi-objective optimization of cooling water package based on 3E analysis: A case study. Energy, 134, 840-849.
  • [11] Rahdar, M. H., Heidari, M., Ataei, A., Choi, J. K. (2016). Modeling and optimization of R-717 and R-134a ice thermal energy storage air conditioning systems using NSGA-II and MOPSO algorithms. Applied Thermal Engineering, 96, 217-227.
  • [12] Najjar, Y. S., Abubaker, A. M. (2017). Thermoeconomic analysis and optimization of a novel inlet air cooling system with gas turbine engines using cascaded waste-heat recovery. Energy, 128, 421-434.
  • [13] Rezayan, O., Behbahaninia, A. (2011). Thermoeconomic optimization and exergy analysis of CO2/NH3 cascade refrigeration systems. Energy, 36(2), 888-895.
  • [14] Raja, B. D., Jhala, R. L., Patel, V. (2018). Multiobjective thermo‐economic and thermodynamics optimization of a plate–fin heat exchanger. Heat Transfer—Asian Research, 47(2), 253-270.
  • [15] Dubey, A. M., Kumar, S., Agrawal, G. D. (2014). Thermodynamic analysis of a transcritical CO2/propylene (R744–R1270) cascade system for cooling and heating applications. Energy conversion and management, 86, 774-783.
  • [16] Parekh, A. D., Tailor, P. R., Sutaria, N. (2012). Thermoeconomic Optimization of Cascade Refrigeration System using Refrigerant Pair R404A-R508B. In Applied Mechanics and Materials (Vol. 110, pp. 677-684). Trans Tech Publications.
  • [17] Keshtkar, M. M. (2016). Effect of subcooling and superheating on performance of a cascade refrigeration system with considering thermo-economic analysis and multi-objective optimization. Journal of Advanced Computer Science and Technology, 5(2), 42-47.
  • [18] Toghyani, S., Kasaeian, A., Ahmadi, M. H. (2014). Multi-objective optimization of Stirling engine using non-ideal adiabatic method. Energy Conversion and Management, 80, 54-62.
  • [19] Sadatsakkak, S. A., Ahmadi, M. H., Ahmadi, M. A. (2015). Optimization performance and thermodynamic analysis of an irreversible nano scale Brayton cycle operating with Maxwell–Boltzmann gas. Energy Conversion and Management, 101, 592-605.
  • [20] Kaushik, S. C., Kumar, R., Arora, R. (2016). Thermo-economic optimization and parametric study of an irreversible regenerative Brayton cycle. Journal of Thermal Engineering (ICES2015).
  • [21] Heidarnejad, P. (2017). Exergy Based Optimization of a Biomass and Solar Fuelled CCHP Hybrid Seawater Desalination Plant. Journal of Thermal Engineering, 3(1), 1034-1043.
  • [22] Keshtkar, M. M. (2017). Performance analysis of a counter flow wet cooling tower and selection of optimum operative condition by MCDM-TOPSIS method. Applied Thermal Engineering, 114, 776-784.
  • [23] Wouagfack, P. A. N., Tchinda, R. (2011). Irreversible three-heat-source refrigerator with heat transfer law of QαΔ (T− 1) and its performance optimization based on ECOP criterion. Energy Systems, 2(3-4), 359-376.
  • [24] Kotas, T. J. (1986). Exergy method of thermal and chemical plant analysis. Trans IChemE, 64, 212-229.
  • [25] Bejan, A., Tsatsaronis, G., Moran, M., Moran, M. J. (1996). Thermal design and optimization. John Wiley & Sons.
  • [26] Aminyavari, M., Najafi, B., Shirazi, A., Rinaldi, F. (2014). Exergetic, economic and environmental (3E) analyses, and multi-objective optimization of a CO2/NH3 cascade refrigeration system. Applied Thermal Engineering, 65(1-2), 42-50.
  • [27] Rao, R. V., Saroj, A. (2018). Multi-objective design optimization of heat exchangers using elitist-Jaya algorithm. Energy Systems, 9(2), 305-341.
  • [28] Klein, S. A., Alvarado, F. L. (1992). EES: Engineering equation solver for the Microsoft Windows operating system. F-Chart software.
  • [29] Nellis, G., Klein, S. (2009). Mass transfer. Heat Transfer, Cambridge University Press, New York.
  • [30] Kays, W.M., London, A.L., “Compact Heat Exchangers”, Krieger Publishing Company, (1984).
  • [31] Shah, R.K., Sekulic, D.P., “Fundamentals of Heat Exchanger Design”, Wiley, (2003)
  • [32] Thirumaleshwar, M., “Software Solutions to Problems on Heat Transfer - Boiling and Condensation”, (2013)
  • [33] Harrell Jr, F. E. (2015). Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis. Springer.
  • [34] Konak, A., Coit, D. W., Smith, A. E. (2006). Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety, 91(9), 992-1007.
  • [35] Holland, J. H. (1992). Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT press.
Toplam 35 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Mohammad Mehdi Keshtkar Bu kişi benim

Yayımlanma Tarihi 24 Haziran 2019
Gönderilme Tarihi 19 Eylül 2017
Yayımlandığı Sayı Yıl 2019

Kaynak Göster

APA Keshtkar, M. M. (2019). MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES). Journal of Thermal Engineering, 5(4), 237-250. https://doi.org/10.18186/thermal.581750
AMA Keshtkar MM. MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES). Journal of Thermal Engineering. Haziran 2019;5(4):237-250. doi:10.18186/thermal.581750
Chicago Keshtkar, Mohammad Mehdi. “MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES)”. Journal of Thermal Engineering 5, sy. 4 (Haziran 2019): 237-50. https://doi.org/10.18186/thermal.581750.
EndNote Keshtkar MM (01 Haziran 2019) MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES). Journal of Thermal Engineering 5 4 237–250.
IEEE M. M. Keshtkar, “MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES)”, Journal of Thermal Engineering, c. 5, sy. 4, ss. 237–250, 2019, doi: 10.18186/thermal.581750.
ISNAD Keshtkar, Mohammad Mehdi. “MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES)”. Journal of Thermal Engineering 5/4 (Haziran 2019), 237-250. https://doi.org/10.18186/thermal.581750.
JAMA Keshtkar MM. MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES). Journal of Thermal Engineering. 2019;5:237–250.
MLA Keshtkar, Mohammad Mehdi. “MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES)”. Journal of Thermal Engineering, c. 5, sy. 4, 2019, ss. 237-50, doi:10.18186/thermal.581750.
Vancouver Keshtkar MM. MULTI-OBJECTIVE OPTIMIZATION OF A R744/R134A CASCADE REFRIGERATION SYSTEM: EXERGETIC, ECONOMIC, ENVIRONMENTAL, AND SENSITIVE ANALYSIS (3ES). Journal of Thermal Engineering. 2019;5(4):237-50.

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