TY - GEN
T1 - Multi-field coupling optimization of anti-icing component for helicopter rotor based on big data
AU - Chen, Long
AU - Zhang, Yidu
AU - Wu, Qiong
AU - Chen, Zhengsheng
AU - Peng, Youyun
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/20
Y1 - 2017/10/20
N2 - Considering the multivariable influence on the temperature field of anti-icing component, a numerical simulation model coupling multi-field for helicopter rotor anti-icing composite structure component under big data environment was presented. The multi-parameters were the main influencing factors in heat transfer numerical simulation. Convective heat transfer and heat conduction coupling was analysis for temperature field of anti-icing component. The traditional orthogonal design method was used as optimization program for analyzing of temperature field optimization of composite material for anti-icing structure. The temperature field distribution of the iron surface after optimization meets the requirements of the relevant anti-icing parameters. Thus, based on the big data environment, the optimization effect of the parameters of the rotor anti-icing component is more ideal. The average temperature and high temperature distribution change after optimization indicate that the optimized anti-icing effect is more evident than the original anti-icing effect which means the optimization performs well.
AB - Considering the multivariable influence on the temperature field of anti-icing component, a numerical simulation model coupling multi-field for helicopter rotor anti-icing composite structure component under big data environment was presented. The multi-parameters were the main influencing factors in heat transfer numerical simulation. Convective heat transfer and heat conduction coupling was analysis for temperature field of anti-icing component. The traditional orthogonal design method was used as optimization program for analyzing of temperature field optimization of composite material for anti-icing structure. The temperature field distribution of the iron surface after optimization meets the requirements of the relevant anti-icing parameters. Thus, based on the big data environment, the optimization effect of the parameters of the rotor anti-icing component is more ideal. The average temperature and high temperature distribution change after optimization indicate that the optimized anti-icing effect is more evident than the original anti-icing effect which means the optimization performs well.
KW - anti-icing component
KW - big data
KW - multi-field coupling
KW - numerical simulation
KW - optimization analysis
UR - https://www.scopus.com/pages/publications/85039997302
U2 - 10.1109/ICBDA.2017.8078865
DO - 10.1109/ICBDA.2017.8078865
M3 - 会议稿件
AN - SCOPUS:85039997302
T3 - 2017 IEEE 2nd International Conference on Big Data Analysis, ICBDA 2017
SP - 468
EP - 472
BT - 2017 IEEE 2nd International Conference on Big Data Analysis, ICBDA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Big Data Analysis, ICBDA 2017
Y2 - 10 March 2017 through 12 March 2017
ER -