Analytical Derivatives Technology for Parametric Shape Design and Analysis in Structural Applications

Author(s):  
Srikanth Akkaram ◽  
Jean-Daniel Beley ◽  
Bob Maffeo ◽  
Gene Wiggs

The ability to perform and evaluate the effect of shape changes on the stress, modal and thermal response of components is an important ingredient in the ‘design’ of aircraft engine components. The classical design of experiments (DOE) based approach that is motivated from statistics (for physical experiments) is one of the possible approaches for the evaluation of the component response with respect to design parameters [1]. Since the underlying physical model used for the component response is deterministic and understood through a computer simulation model, one needs to re-think the use of the classical DOE techniques for this class of problems. In this paper, we explore an alternate sensitivity analysis based technique where a deterministic parametric response is constructed using exact derivatives of the complex finite-element (FE) based computer models to design parameters. The method is based on a discrete sensitivity analysis formulation using semi-automatic differentiation [2,3] to compute the Taylor series or its Pade equivalent for finite element based responses. Shape design or optimization in the context of finite element modeling is challenging because the evaluation of the response for different shape requires the need for a meshing consistent with the new geometry. This paper examines the differences in the nature and performance (accuracy and efficiency) of the analytical derivatives approach against other existing approaches with validation on several benchmark structural applications. The use of analytical derivatives for parametric analysis is demonstrated to have accuracy benefits on certain classes of shape applications.

Author(s):  
Alfonso Callejo ◽  
Daniel Dopico

Algorithms for the sensitivity analysis of multibody systems are quickly maturing as computational and software resources grow. Indeed, the area has made substantial progress since the first academic methods and examples were developed. Today, sensitivity analysis tools aimed at gradient-based design optimization are required to be as computationally efficient and scalable as possible. This paper presents extensive verification of one of the most popular sensitivity analysis techniques, namely the direct differentiation method (DDM). Usage of such method is recommended when the number of design parameters relative to the number of outputs is small and when the time integration algorithm is sensitive to accumulation errors. Verification is hereby accomplished through two radically different computational techniques, namely manual differentiation and automatic differentiation, which are used to compute the necessary partial derivatives. Experiments are conducted on an 18-degree-of-freedom, 366-dependent-coordinate bus model with realistic geometry and tire contact forces, which constitutes an unusually large system within general-purpose sensitivity analysis of multibody systems. The results are in good agreement; the manual technique provides shorter runtimes, whereas the automatic differentiation technique is easier to implement. The presented results highlight the potential of manual and automatic differentiation approaches within general-purpose simulation packages, and the importance of formulation benchmarking.


2011 ◽  
Vol 199-200 ◽  
pp. 1308-1313 ◽  
Author(s):  
Tao Hu ◽  
Ping An Du ◽  
John H.L Ha ◽  
Jian Tao Liu

By studying a typical rectangle PCB, the design parameters affecting natural frequency of PCB are found in the paper. By theoretical deduction and finite element analysis, the sensitivity of the natural frequency of PCB with respect to the design parameters is analyzed, the influence of the design parameters on nature frequency is obtained, and some conclusions for structural optimization of PCB are drawn.


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