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Optimization of an Annular Combustion Chamber for Micro Turbo Jet System
Habibi F.I.a, Hartono F.a, Prayogo H.a
a Aero-propulsion Laboratory, Faculty of Mechanical and Aerospace Engineering, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 Published under licence by IOP Publishing Ltd.This Annular combustion Chamber is designed for micro turbo jet engine. Combustion chamber is positioned in between compressor and turbine of turbojet. Combustion chamber is designed to increase enthalpy without significant pressure loss. Existing combustion chamber is designed by conventional method of trial and error. To further increase its performance then a optimization is needed. The geometry of the combustion chamber is optimized to maximized efficiency, minimized Pattern Factor, minimized pressure loss and lower temperature on the combustion wall. Varying Parameter is chosen based on Sensitivity Analysis with Spearman Correlation method to choose influential changes on geometry. After sampling process with Latin Hypercube Sampling (LHS) method and followed by interpolation with Kriging method, the combustion chamber then optimized using Multi Objective Genetic-Algorithm (MOGA). Performance of the combustion chamber then evaluated by numerical simulation. The combustion chamber will be chosen if it fulfilled pressure loss and temperature on wall criteria. Final design give better performance with a little increase in efficiency and good Pattern Factor.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Annular combustion chambers,Conventional methods,Latin hypercube sampling,Lower temperatures,Multi-objective genetic algorithm,Sampling process,Spearman correlation,Varying parameters[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1757-899X/645/1/012009[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]