Digital multidisciplinary analysis and design optimization platform for aeroderivative gas turbines

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Gas turbine design is a challenging task because of inherent system complexity. For aero-derivative gas**turbines (AGT) the design process is quite fragmented and relies strongly on historical data obtained from**previous engines. Siemens Canada AGT, a leading industrial gas turbine original equipment manufacturer**(OEM), has determined that currently compartmentalized design activities lead to sub-optimal and non-robust**designs while design engineers spend a considerable amount of their time on non-added value tasks. Therefore,**it has developed a technology strategy that aims at supporting a highly integrated concurrent design process in**order to improve performance and robustness of its products, maximizing thus its competitiveness while**minimizing its financial risks.**The objective of this project is to build a digital platform for models and data management with an integrated**suite of analysis, design, and optimization tools. One of the novelties of the proposed research is to adapt tool**integration best practices and change propagation techniques from software engineering in order to build the**solid foundation of a computational environment that integrates functional data management, model version**control, analysis tools and optimization algorithms in a way that is customizable to the specific workflows of**different engineering teams using machine learning techniques. The analysis, design and optimization modules**of the digital platform will include parametric design models for critical static and rotary components,**lifecycle-related quantification techniques, multidisciplinary design optimization (MDO) methods, and robust**design tools.