Monolithic Approach for Next-Generation Aircraft Design Considering Airline Operations and Economics.

Traditional approaches to design and optimization of a new system often use a system-centric objective that does not consider how the operator will use this new system alongside other existing systems. When the new system design is incorporated into the broader group of systems, the performance of the operator-level objective can be sub-optimal due to the unmodeled interaction between the new system and the other systems. Among the few available references that describe attempts to address this disconnect, most follow an MDO-motivated sequential decomposition approach of first designing an optimal system and then providing this system to the operator who decides the best way to use this new system along with the existing systems. This paper addresses this issue by including aircraft design, airline operations, and revenue management "subspaces"; and presents an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem. The monolithic approach makes the problem an expensive MINLP problem and is extremely difficult to solve. We use a recently developed optimization framework that simultaneously solves the subspaces to capture the "synergy" in the problem. The results demonstrate that simultaneously optimizing the subspaces leads to significant improvement in the fleet-level objective of the airline when compared to the previously developed sequential subspace decomposition approach. The results also showcase that maximizing revenue and minimizing operating cost independently need not lead to a maximized profit solution for the airline.

Spectral analysis of R-lines and vibronic sidebands in the emission spectrum of ruby using genetic algorithms.

The advancement in spectral analysis methods for the emission spectrum of ruby has been driven by the characterization of R-line peak shifts with stress in order to establish piezospectroscopic relationships. These relationships form the basis for the development of photo-stimulated luminescence spectroscopy (PSLS) as a nondestructive method to determine the integrity of the thermally grown oxide (TGO) layer on jet engine turbine blades. Besides the measurement technique, the accuracy of PSLS in stress measurements is influenced by the spectral analysis methodology, which is the focus of this paper. Gradient-based algorithms have been used widely in the methods developed thus far. The approach of using genetic algorithms in the spectral analysis of R-lines and vibronic bands is presented here for the first time and validated with the wellknown piezospectroscopic coefficients of the R-lines. The implementation of this method has led to significant new results in the quantification of peak shifts with uniaxial stress in the vibronic bands of the spectrum. The use of genetic algorithms is instrumental in the deconvolution and fitting of the numerous peaks in these bands. Fitting statistics, such as the fitness function and number of function evaluations, were used to assess the effectiveness of the procedures used in this method.