Extension of an Object Oriented Multidisciplinary Analysis Optimization (MDAO) Environment

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National Aeronautics and Space Administration
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Phase I
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Small Business Information
9489 E. Ironwood Square Drive, Scottsdale, AZ, 85258
Hubzone Owned:
Minority Owned:
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Principal Investigator:
Dong-Hwan Lee
Principal Investigator
() -
Business Contact:
Jennifer Scherr
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(480) 945-9988
Research Institution:
Virginia Polytechnic Institute and State University

1880 Pratt Drive, Suite 2006
Blackburg, VA, 24061
(540) 231-5281
Nonprofit college or university
Multidisciplinary design, analysis, and optimization (MDAO) tools today possess limited disciplines with little fidelity modeling capability. These tools are typically developed as a single large software application that performs analysis for all disciplines but has little or no capability to integrate multi-fidelity and multi-discipline components that have already been developed as stand-alone analysis codes. Even though a multitude of tools have been developed and well adapted to the interdisciplinary aircraft design/analysis, they have not been developed to work together. The objective of the development of the MDAO tool is to generate a "central executive" that can integrate disparate software packages in a cross platform network environment so as to perform optimization and design tasks in a cohesive streamlined manner. This object-oriented framework can integrate the analysis codes for multiple disciplines, instead of relying on one code to perform the analysis for all disciplines. ZONA Technology and its team member Virginia Polytechnic Institute propose to develop three object-oriented components that will fully leverage tools currently under development within NASA's MDAO framework. The three major components are: (1) an automatic re-meshing tool that can provide a fast and efficient mesh generation capability for complex structures like curved panels with curved stiffeners and aircraft wings of any shape with curved spars and ribs. (2) a hybrid optimization tool that combines a non-gradient based optimization method and a gradient based optimization method. The advantage of this hybrid optimization is that a global optimum point can be achieved through the non-gradient optimization and acceleration of the convergence can be obtained by aiding gradient based optimization algorithm. (3) a fast transonic unsteady aerodynamics method for accurate aeroelastic analysis and shape sensitivity information due to the change of external wing shape.

* information listed above is at the time of submission.

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