ESTIMATING GAS TURBINE ENGINE WEIGHT, COSTS, AND DEVELOPMENT TIME DURING THE PRELIMINARY AIRCRAFT ENGINE DESIGN PROCESS

摘要

This paper describes the application of a weight and cost-estimating methodology used in an undergraduate aircraft engine design course that is taught in concert with a companion course in airframe design. The two preliminary designs,, one for the engine and the other for the airframe, must be integrated as subsystems within a system to satisfy the performance requirements of a given mission as outlined in a single "request for proposals". In recent years, systems engineering management majors have been added to the design teams to work alongside the aeronautical engineering majors to analyze and report on costs, schedule, and technical risk factors in addition to the operational performance factors that have previously been the sole focus of the course. The teaming of technical management majors and aeronautical engineering majors has been driven by a heightened emphasis on system affordability. The cost-estimating methodology for gas turbine engines uses cycle parameters such as turbine rotor inlet temperature, overall pressure ratio, specific fuel consumption, level of technology, and engine dry weight as inputs. A methodology for estimating dry engine weight was developed which uses engine cycle parameters and fan face diameter as inputs in a volume analog scaling factor which was correlated against historical engine weight data. To tie all of the performance, weight, cost, and development time issues together, the paper presents an "analysis of alternatives" example that considers three different engine cycle alternatives. The design tools presented in this paper will provide a strong foundational understanding of how to systematically weigh and evaluate the important tradeoffs between aircraft turbofan engine performance, cost, schedule, and risk factors. Equipping students with the insight and ability to perform these multidisciplinary trade studies during the preliminary engine design process is this paper's most important contribution.