Weight Estimation of Gas Turbine Engines

Abstract

The need for more efficient aircraft has spawned the conception of a variety of novel engine and aircraft architectures, such as the combined-cycle engine proposed by researchers at Delft University of Technology. To evaluate the potential benefits of these concepts comprehensively, in-depth performance simulations are required. Furthermore, penalties with regard to weight and drag are critical considerations, thus new engine technologies must be evaluated within their full airframe-level integration and mission profile. Accurate weight estimations of a variety of design alternatives are therefore necessary in order to properly assess the validity of such technologies and to reach an optimal design with respect to the tradeoffs between weight, drag, and efficiency. No weight estimation tools with sufficient accuracy are publically available at present, thus a new, component-based preliminary engine design tool, named ‘Weight Estimation of Aeronautical Gas Turbine Engines’ (or WEST), was developed. WEST can be used to predict the weight of novel engine architectures to a reasonable degree of accuracy, all the while accounting for sensitivity to design parameters such as turbine inlet temperature, overall pressure ratio, mass flow rate, power, and choice of turbomachinery configuration. Similar methodologies are able to design components worth between 60 and 110% of the actual weight of an existing engine, whereas WEST was able to account for about 70-90%, thus exceeding initial expectations and improving the reliability of the estimations. This tool can therefore be used to estimate the weight of a variety of existing engines, and is sufficiently flexible to model novel architectures as well, since the results are based on the application-specific design of real engine components. Among the potential uses of WEST, a promising one would be to evaluate the weight of a large set of designs for a particular application. Upon these estimates, single-equation surrogate models could be developed using statistical regression, allowing for these equations to be used as a more computationally-efficient weight estimation methodology in a wide range of aircraft-level design and optimization studies. These equations would build upon the work described in this paper and could be used to accelerate the development and introduction of new aircraft-related technologies.