This study deals with the application of optimization in Finocyl grain design with ballistic objective functions using a genetic algorithm. The classical sampling method is used for space filling; a level-set method is used for simulating the evaluation of a burning surface of the propellant grain. An algorithm is developed beside the level-set code that prepares the initial grain configuration using a computer-aided design (CAD) to export generated models to the level-set code. The lumped method is used to perform internal ballistic analysis. A meta-model is used to surrogate the level-set method in an optimization design loop. Finally, a case study is done to verify the proposed algorithm. Observed results show that the grain design method reduced the design time significantly, and this algorithm can be used in designing any grain type.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Finocyl Grain Design Using the Genetic Algorithm in Combination with Adaptive Basis Function Construction


    Beteiligte:


    Erscheinungsdatum :

    2019




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Design and Performance Optimization of Finocyl Grain

    Kamran, Ali / Gouzhu, Liang / Godil, Junaid et al. | AIAA | 2009


    Particle Swarm Optimizer for Finocyl Grain Configurations

    Kamran, Ali / Guozhu, Liang / Zeeshan, Qasim et al. | AIAA | 2010


    ±3-Sigma based design optimization of 3D Finocyl grain

    Kamran, Ali / Guozhu, Liang / Rafique, Amer Farhan et al. | Elsevier | 2012



    Aeroacoustic Instability in a Solid Rocket Motor with Finocyl Grain

    Shanbhogue, Santosh / Sujith, Raman / Chakravarthy, Sathyanarayanan | AIAA | 2003