Cost optimization tools for advanced gas turbine technologies

This thesis presents two studies that illustrate how cost modelling can be integrated into the various design process stages, ranging from strategic gas turbine and airframe system design to preliminary and detailed component design and production planning. The first study investigates which cruise speed the next generation of short-haul aircraft with 150 seats should fly at and whether a conventional two- or three-shaft turbofan, a geared turbofan, a turboprop or an open rotor should be employed in order to make the aircraft's direct operating cost robust to uncertain fuel and carbon (CO2) prices in the Year 2030, taking the aircraft productivity, the passenger value of time and the modal shift into account. To answer this question, an optimization loop was set up in MATLAB consisting of nine modules covering gas turbine and airframe design and performance, light and aircraft fleet simulation, operating cost and optimization. If the passenger value of time is included, the most robust aircraft design is powered by geared turbofan engines and cruises at Mach 0.80. If the value of time is ignored, however, then a turboprop aircraft flying at Mach 0.70 is the optimum solution. This demonstrates that the most fuel-efficient option, the open rotor, is not automatically the most cost-efficient solution because of the relatively high engine and airframe costs. The second study shows how a factory cost model can be combined with a parametric component production time model, to not only calculate costs at the manufacturing operation level for production planning, but also the total unit costs of future integrally bladed disc (blisk) designs for component trade-off studies. As future process times can only be estimated and the correlation between operation times and blisk design parameters, including the number of blades, the disc diameter and other design variables, is never perfect, all operation times have uncertainty distributions. These are cascaded through the model to generate a probability distribution of the unit cost