AN OPTIMIZATION OF ANTI-ICING CHAMBER BASED ON POD AND KRIGING

Junjie Niu, Weimin Sang, Aoxiang Qiu, Qilei Guo, Dong Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Due to the small load and the limited energy supply ice accretion on the unmanned aerial vehicles (UAVs) has limited the UAVs flight in good weather conditions. To take advantage of the energy of the UAVs as the anti/de-icing energy source may improve the UAVs application. The engine exhaust has a potential as a hot air source used for the anti-icing system. The hot air anti-icing chamber is designed and optimized. The most critical in-flight icing conditions is identified and the basic hot air anti-icing chamber is designed. The location of the piccolo tube, the angle between the jet holes are set as the design variables. The optimized latin hypercubic sampling (OLHS) is utilized and the numerical simulations are conducted. The surrogate model is built based on the proper orthogonal decomposition (POD) and Kriging interpolation. The hot air anti-icing chamber is optimized with the genetic algorithm (GA). The methodology can greatly reduce the time cost of the optimization and successfully results in optimal configurations of the anti-icing chamber.

Original languageEnglish
Title of host publication32nd Congress of the International Council of the Aeronautical Sciences, ICAS 2021
PublisherInternational Council of the Aeronautical Sciences
ISBN (Electronic)9783932182914
StatePublished - 2021
Event32nd Congress of the International Council of the Aeronautical Sciences, ICAS 2021 - Shanghai, China
Duration: 6 Sep 202110 Sep 2021

Publication series

Name32nd Congress of the International Council of the Aeronautical Sciences, ICAS 2021

Conference

Conference32nd Congress of the International Council of the Aeronautical Sciences, ICAS 2021
Country/TerritoryChina
CityShanghai
Period6/09/2110/09/21

Keywords

  • Hot-air anti-icing
  • Optimization
  • Reduced model
  • Surrogated model

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