100
L. Prabhu et al.
4 Conclusion
Identification of an optimal parameters area ratio and operating pressure ratio of a
nozzle to place the normal shock at a specific location in a 3S device is carried out
using meta-heuristic optimization scheme. Initially, for a shockwave location, the
optimal parameters with pressure recovery coefficient as a constraint were identified using a nature-inspired firefly algorithm. The surrogate model using a neural
network was deputed in the optimization scheme to compute the parameters with
a less computational cost. Finally, the convergent-divergent nozzle was designed
using the optimal parameters identified by the firefly algorithm, and flow analysis
was carried out. The shock location from the flow analysis was found to be very close
to the shockwave location used in the optimization scheme. This shows the effective
working of the firefly optimization in the design of a nozzle in the 3S device. In the
future, the experimental investigation of the nozzle design with optimal parameters
will be carried out to validate further.
References
1. Hussaini AA. Gas dynamics. http://uotechnology.edu.iq/dep-MechanicsandEquipment
2. Niknam PH, Mokhtarani B, Mortaheb HR (2016) Prediction of shockwave location in supersonic nozzle separation using self-organizing map classification and artificial neural network
modeling. J Nat Gas Sci Eng 34:917–924
3. Gangadhar Venkata Ramana P, Prabhu L (2020) Identification of nozzle parameters in 3S device
using artificial intelligence and meta-heuristic optimization scheme. American Inst Phy Conf
Proc 2204:030004
4. Shooshtari SHR, Shahsavand A (2017) Maximization of energy recovery inside supersonic
separator in the presence of condensation and normal shock wave. Energy 120:153–163
5. Niknam PH, Mortaheb HR, Mokhtarani B (2018) Dehydration of low-pressure gas using
supersonic separation: experimental investigation and CFD analysis. J Nat Gas Sci Eng
52:202–214
6. Jinnah MA (2013) Numerical simulation of shock induced turbulence in a nozzle flow. J Inst
Eng India Ser C 94:229–237
7. Shooshtari SHR, Shahsavand A (2018) Optimal operation of refrigeration oriented supersonic separators for natural gas dehydration via heterogeneous condensation. Appl Therm Eng
139:76–86
8. Bian J, Cao X, Yang W, Edem MA, Yin P, Jiang W (2018) Supersonic liquefaction properties
of natural gas in the Laval nozzle. Energy 159:706–715
9. Cao X, Yang W (2015) The dehydration performance evaluation of a new supersonic swirling
separator. J Nat Gas Sci Eng 27:1667–1676
10. Yang X-S (2014) Nature-inspired optimization algorithms. Elsevier, Amsterdam, Boston
L. Prabhu et al.
4 Conclusion
Identification of an optimal parameters area ratio and operating pressure ratio of a
nozzle to place the normal shock at a specific location in a 3S device is carried out
using meta-heuristic optimization scheme. Initially, for a shockwave location, the
optimal parameters with pressure recovery coefficient as a constraint were identified using a nature-inspired firefly algorithm. The surrogate model using a neural
network was deputed in the optimization scheme to compute the parameters with
a less computational cost. Finally, the convergent-divergent nozzle was designed
using the optimal parameters identified by the firefly algorithm, and flow analysis
was carried out. The shock location from the flow analysis was found to be very close
to the shockwave location used in the optimization scheme. This shows the effective
working of the firefly optimization in the design of a nozzle in the 3S device. In the
future, the experimental investigation of the nozzle design with optimal parameters
will be carried out to validate further.
References
1. Hussaini AA. Gas dynamics. http://uotechnology.edu.iq/dep-MechanicsandEquipment
2. Niknam PH, Mokhtarani B, Mortaheb HR (2016) Prediction of shockwave location in supersonic nozzle separation using self-organizing map classification and artificial neural network
modeling. J Nat Gas Sci Eng 34:917–924
3. Gangadhar Venkata Ramana P, Prabhu L (2020) Identification of nozzle parameters in 3S device
using artificial intelligence and meta-heuristic optimization scheme. American Inst Phy Conf
Proc 2204:030004
4. Shooshtari SHR, Shahsavand A (2017) Maximization of energy recovery inside supersonic
separator in the presence of condensation and normal shock wave. Energy 120:153–163
5. Niknam PH, Mortaheb HR, Mokhtarani B (2018) Dehydration of low-pressure gas using
supersonic separation: experimental investigation and CFD analysis. J Nat Gas Sci Eng
52:202–214
6. Jinnah MA (2013) Numerical simulation of shock induced turbulence in a nozzle flow. J Inst
Eng India Ser C 94:229–237
7. Shooshtari SHR, Shahsavand A (2018) Optimal operation of refrigeration oriented supersonic separators for natural gas dehydration via heterogeneous condensation. Appl Therm Eng
139:76–86
8. Bian J, Cao X, Yang W, Edem MA, Yin P, Jiang W (2018) Supersonic liquefaction properties
of natural gas in the Laval nozzle. Energy 159:706–715
9. Cao X, Yang W (2015) The dehydration performance evaluation of a new supersonic swirling
separator. J Nat Gas Sci Eng 27:1667–1676
10. Yang X-S (2014) Nature-inspired optimization algorithms. Elsevier, Amsterdam, Boston