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Multiple Linear Regression Analysis-Based Weight Estimation of Turbofan Engines
(*) Corresponding author
DOI: https://doi.org/10.15866/irease.v16i1.22961
Abstract
Turbofan engines are the primary propulsion units of commercial aviation today. Weight Turbofan engines are the primary propulsion units of commercial aviation today. Weight prediction of turbofan engines is an important step in the engine design. There are several models available in the literature with statistical and component-based approaches. In this study, a statistical multiple linear regression analysis-based approach was used for the estimation of engine weight with a targeted error margin of ±10%. Novel weight estimation equations were obtained in five different thrust intervals of turbofan engines available in market. The model was shown to have higher accuracy than most statistical models available in literature. The novel weight estimation equations are developed as a set of five formulas and correlates the engine weight by four engine design parameters which are bypass ratio, total pressure ratio, air mass flow rate, and thrust. Since those four parameters can be obtained easily from literature, the novel weight estimation equations do not require any proprietary engine data (geometry, component dimensions etc.) and simple to use with a ±10% accuracy.
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