Gradient-Based Trade-Off Design for Engineering Applications

Abstract

The goal of the trade-off design method presented in this study is to achieve newly targeted performance requirements by modifying the current values of the design variables. The trade-off design problem is formulated in the framework of Sequential Quadratic Programming. The method is computationally efficient as it is gradient-based, which, however, requires the performance functions to be differentiable. A new equation to calculate the scale factor to control the size of the design variables is introduced in this study, which can ensure the new design achieves the targeted performance objective. Three formal approaches are developed in this study for trade-off design to handle various design scenarios, which include one that can handle cases with linearly dependent constraints and with more constraints than the number of design variables. Three engineering design problems are presented as examples to validate and demonstrate the use of these trade-off approaches to find the best way to adjust the design variables to meet the revised performance requirements.

On the Fine-Tuning of the Stick-Beam Wing Dynamic Model of a Tiltrotor: A Case Study

“…Once the objective function has been minimized, these weights are useful for defining the best trade-off among the errors of the final model (see Ref. [18] for further details and applications).…”