Joseph Brent Staubach

CAD-Based Parametric Cross-Section Designer for Gas Turbine Engine MDO Applications

AbstractBecause gas turbine engines are among the most complicated mechanical assemblies produced to date, there is an increasing need for computer-aided modeling programs that facilitate the incorporation of Multi-Disciplinary Optimization at the conceptual design stage. Here we report the development of Cross-Section Designer, a software tool for manipulating gas turbine engine geometry using the UGS NX CAD system [1]. Cross-Section Designer provides the user with an editable version of the engine gaspath based on output from a cycle specification program in the form of geometric and thermodynamic parameters. The system was designed to accommodate multiple parameterizations, and allows users to manipulate the geometry according to various different design schemes that best fit the design intent. The multiple-parameterization modeling methods described in this paper can be extended to the design of any system, providing real cost savings via design time reduction.

Multilevel Hierarchical Decomposition: Identification Procedures for Edge of Design Space Feasibility

In high performance machines, multiple active MDO constraints dictate the edge of feasibility, i.e. boundary of the design space. It is essential to have an accurate description of the boundary in terms of design variables. Given a sample of data, the recognition of a design feature (e.g. design shape) is not usually familiar to the design domain experts but must be extracted based on data-driven procedures. The “edge of feasibility” could be evaluated as a continuous or piece wise continuous function of active constraints. In this work, the focus is on a class of quasiseparable optimization problems. The subsystems for these problems involve local design shape variables and global system variables, but no variables from other subsystems. The system in this particular case is the engine component (i.e. HPT) and the subsystem is the turbine disk. The system is hierarchically decomposed to the system and subsystem components respectively. The HPT flowpath and its defined thermodynamic and geometric parameters define the system. The subsystem is the HPT turbine disk and its associated geometric shape variables. A system level DOE determines the design space of the HPT system. The optimized subsystem turbine disk is the solution to the DOE of the system and feasible disk designs are the shapes that can withstand the design loads and stresses. The focus of the paper is to develop a methodology that would systematically utilize minimum weight optimum shape designs across the design space and predict new designs close to being optimal in performance for a specified range of design conditions. The shape of minimum weight disks are identified as a solution of a system of inverse response surface equations that can determine disk shapes with good confidence. The methodology is developed using synthetic turbine disk problems with known regions of feasibility and infeasibility. The edge of feasibility is determined and the functional dependence on the design variables estimated.Copyright