Description: The objective of this proposed project is to provide a new set of sensitivity analysis theory and codes, the Sensitivity Analysis for Design Optimization Integrated Software Tool set, to work within the existing NASA O3 Tool. In this Phase I effort, the sensitivity approach will be implemented for two basic types of analysis, namely static systems of equations (linear and non-linear) and eigen-problems. This implementation will focus on the elements most commonly used for aerospace design; beam, plate, and shell elements. The following specific goals are identified: 1 Integrated Multidisciplinary Sensitivity Analysis Toolset for Design Optimization (software) 2 Use of Advanced Algorithms to Maximize Computational Efficiency (analytic sensitivities) 3 Compatibility with Existing NASA Software Design Tools for computational integration to O3.

Benefits: Specifically at NASA we see direct application in the efficient integration into the optimization environment of analysis modules already built in the Object-Oriented Optimization Tool. At the conclusion of Phase I we see immediate benefit to optimizing for Weight or to determine sizing and shape for structural members of aircraft. Mechanical Deflection, Stress, and Strain analysis, and Buckling analysis codes will also benefit. Frequency and Mode Shape analysis and others future modules can then provide first order sensitivity. This information can then be fed directly to the optimizer or to an approximation concepts approach. Having standalone sensitivity modules will also provide NASA flexibility in evaluating constraints and responses not necessarily available in standard commercial codes.

Sensitivity analysis is required for efficient optimal design and reliability analysis. Optimization is today widely used in the aerospace industry, automotive industry, sports equipment design and medical equipment design, just to mention a few. Building sensitivity analysis modules that can flexibly connect with analysis and finite elements has a tremendous potential for these industries since we can provide tailored solutions for their particular needs. Not only has the optimization become more efficient but also sensitivities provide guidance on determining the importance of variables by their effect on other system components.