Instances of combinatorial optimization problems: complexity and generation

138 p.

Robust design optimization of gas turbine compression systems

Gas turbine compression systems are required to perform adequately over a range of operating conditions. Complexity has encouraged the conventional design process for compressors to focus initially on one operating point, usually the most commonor arduous, to draw up an outline design. Generally, only as this initial design is refined is its offdesign performance assessed in detail. Not only does this necessarily introduce a potentially costly and timeconsuming extra loop in the design process, but it also may result in a design whose offdesign behavior is suboptimal. Aversion of nonintrusive polynomial chaos was previously developed in which a set of orthonormal polynomials was generated to facilitate a rapid analysis of robustness in the presence of generic uncertainties with good accuracy. In this paper, this analysis method is incorporated in real time into the design process for the compression system of a three-shaft gas turbine aeroengine. This approach to robust optimization is shown to lead to designs that exhibit consistently improved system performance with reduced sensitivity to offdesign operation.

Optimization of thermal environment during crystal growth of large-sized Nd : YAG by Temperature Gradient Technique

A finite-element model is employed to analysis the thermal environments in Temperature Gradient Technique (TGT) furnace during the growth of large-sized Nd:YAG crystal. The obtained results show that when the crucible is located at the lower position inside of the heater, a flatter solid-liquid interface is established, which makes it easier to obtain the core-free Nd:YAG crystal. Meanwhile, the lower crucible position can induce higher axial temperature gradient, which is beneficial to the release of latent heat. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of near-field optical field of multi-layer dielectric gratings for pulse compressor

Multi-layer dielectric (MLD) gratings for pulse compressors in high-energy laser systems should provide high diffraction efficiency as well as high laser induced damage thresholds (LIDT). Nonuniform optical near-field distribution is one of the important factors to limit their damage resistant capabilities. Electric field distributions in the gratings and multi-layer film region are analyzed by using Fourier modal method. Optimization of peak electric field in the gratings ridge is performed with a merit function, including both diffraction efficiency and electric field enhancement when the top layer material is HfO2 and SiO2, respectively. A set of optimized gratings parameters is obtained for each structure, which reduce the peak electric field within the gratings ridge to being respective 1.39 and 1.84 times the value of incident light respectively. Finally, we also discuss the effects of gratings refractive index, gratings sidewall angle and incident angle on peak electric field in the gratings ridge. (c) 2006 Elsevier B.V. All rights reserved.

Analysis, optimization and development of an answer scoring system

The main contribution of this work is to analyze and describe the state of the art performance as regards answer scoring systems from the SemEval- 2013 task, as well as to continue with the development of an answer scoring system (EHU-ALM) developed in the University of the Basque Country. On the overall this master thesis focuses on finding any possible configuration that lets improve the results in the SemEval dataset by using attribute engineering techniques in order to find optimal feature subsets, along with trying different hierarchical configurations in order to analyze its performance against the traditional one versus all approach. Altogether, throughout the work we propose two alternative strategies: on the one hand, to improve the EHU-ALM system without changing the architecture, and, on the other hand, to improve the system adapting it to an hierarchical con- figuration. To build such new models we describe and use distinct attribute engineering, data preprocessing, and machine learning techniques.