Abstract

Automated solid modeling, integrated with computational fluid dynamics (CFD) and optimization of a 3D jet turbine engine has never been accomplished. This is due mainly to the computational power required, and the lack of associative parametric modeling tools and techniques necessary to adjust and optimize the design. As an example, the fluid domain of a simple household fan with three blades may contain 500,000 elements per blade passage. Therefore, a complete turbine engine that includes many stages, with sets of thirty or more blades each, will have hundreds of millions of elements. The fluid domains associated with each blade creates a nearly incomprehensible challenge. One method of organizing and passing geometric and non-geometric data is through the utilization of knowledge based engineering (KBE). The focus of this thesis will be the development of a set of techniques utilizing KBE principles to analyze an assembly which includes multiple fluid domains. This comprehensive system will be referred to as the Parametric Optimization Design System (PODS).

Degree

MS

College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2008-04-22

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd2373

Keywords

parametric, associative, modeling, airfoil, axial compressor, optimization, fluid, multi-disciplinary optimization, MDO, analysis, jet, turbine, engine, computational fluid dynamics, CFD, Knowledge-centric, CAD-centric, DB-centric, finite element analysis, FEA, 3D

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