TY - JOUR
T1 - Optimization Design of Hypersonic Inward Turning Inlet Based on SSPNS Algorithm
AU - Gao, Kun Peng
AU - Chen, Bing
AU - Xu, Xu
N1 - Publisher Copyright:
© 2017, Editorial Department of Journal of Propulsion Technology. All right reserved.
PY - 2017/5/1
Y1 - 2017/5/1
N2 - To reduce computational consumption in the optimization process of hypersonic inward turning inlet, single and multi-objective optimization designs were carried out based on single sweep parabolized Navier-Stokes(SSPNS) algorithm. The free-stream mach number of 4.5 and convergence ratio of 5 were set as the computational conditions. The flow field structure calculated by SSPNS algorithm was similar to that by NS algorithm, and the total pressure recovery, Mach number and pressure rise of outlet section showed good agreements, while the computing time by SSPNS was less than one percent of that by NS. The results verified the accuracy and efficiency of SSPNS algorithm. Single objective optimization aimed at the maximum total pressure recovery coefficient was implemented using a single combinational optimization strategy of MIGA and NLPQL, as well as Pointer automatic optimization strategy(Pointer-2). The optimized objective increased to 0.530 and 0.559 from the initial value 0.464, improved by 14% and 20%, respectively. Less iterations are needed using Pointer-2 and the results are better, which indicates that the Pointer-2 algorithm has higher computational efficiency and performs better in global exploration. Multi objective optimization aimed at the highest total pressure recovery coefficient and pressure rise was carried out based on multi-objective genetic algorithm. Both the Pareto front and the relationship formula between total pressure recovery and pressure rise of non-inferior solution proposed are helpful for further engineering application.
AB - To reduce computational consumption in the optimization process of hypersonic inward turning inlet, single and multi-objective optimization designs were carried out based on single sweep parabolized Navier-Stokes(SSPNS) algorithm. The free-stream mach number of 4.5 and convergence ratio of 5 were set as the computational conditions. The flow field structure calculated by SSPNS algorithm was similar to that by NS algorithm, and the total pressure recovery, Mach number and pressure rise of outlet section showed good agreements, while the computing time by SSPNS was less than one percent of that by NS. The results verified the accuracy and efficiency of SSPNS algorithm. Single objective optimization aimed at the maximum total pressure recovery coefficient was implemented using a single combinational optimization strategy of MIGA and NLPQL, as well as Pointer automatic optimization strategy(Pointer-2). The optimized objective increased to 0.530 and 0.559 from the initial value 0.464, improved by 14% and 20%, respectively. Less iterations are needed using Pointer-2 and the results are better, which indicates that the Pointer-2 algorithm has higher computational efficiency and performs better in global exploration. Multi objective optimization aimed at the highest total pressure recovery coefficient and pressure rise was carried out based on multi-objective genetic algorithm. Both the Pareto front and the relationship formula between total pressure recovery and pressure rise of non-inferior solution proposed are helpful for further engineering application.
KW - Inward turning inlet
KW - Multi-objective optimization
KW - SSPNS algorithm
KW - Single-objective optimization
UR - https://www.scopus.com/pages/publications/85029323097
U2 - 10.13675/j.cnki.tjjs.2017.05.006
DO - 10.13675/j.cnki.tjjs.2017.05.006
M3 - 文章
AN - SCOPUS:85029323097
SN - 1001-4055
VL - 38
SP - 998
EP - 1007
JO - Tuijin Jishu/Journal of Propulsion Technology
JF - Tuijin Jishu/Journal of Propulsion Technology
IS - 5
ER -