scholarly journals Dynamic Sensitivity Analysis of Deployable Flexible Space Structures With a Large Number of Design Parameters

2021 ◽  
Author(s):  
Shuai Wang ◽  
Qiang Tian ◽  
Haiyan Hu ◽  
Junwei Shi ◽  
Lingbin Zeng
Keyword(s):  
Sensitivity Analysis ◽  
Automatic Differentiation ◽  
Differential Algebraic Equations ◽  
Design Parameters ◽  
Space Structures ◽  
Analytical Sensitivity ◽  
Flexible Space Structures ◽  
Dynamic Sensitivity ◽  
Computational Methodology ◽  
Dynamic Sensitivity Analysis

Abstract The reliability and dynamic performance of deployable flexible space structures significantly depend on their key design parameters. Sensitivity analysis of these design parameters in the frame of multibody dynamics can serve as a powerful tool to evaluate and improve the dynamic performances of deployable space structures. Nevertheless, previous studies on the dynamic sensitivity analysis are mainly confined to planar multibody systems with a few design parameters. In this study, an efficient computational methodology is proposed to perform the dynamic sensitivity analysis of the complex deployable space structures with a large number of design parameters. Firstly, the analytical sensitivity analysis formulations of objective functions with the parameter-dependent integration bounds are deduced via the direct differentiation method and adjoint variable method. A checkpointing scheme is further introduced to assist the backward integration of the high dimensional differential algebraic equations of the adjoint variables. The flexible beams in the deployable flexible space structure are described by the locking-free three-node spatial beam elements of absolute nodal coordinate formulation. Furthermore, a parallelized automatic differentiation algorithm is proposed to efficiently evaluate the complex partial derivatives in the sensitivity analysis formulations. Finally, four numerical examples are provided to validate the accuracy and efficiency of the proposed computational methodology.

Direct Sensitivity Analysis of Multibody Systems: A Vehicle Dynamics Benchmark

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
Alfonso Callejo ◽  
Daniel Dopico
Keyword(s):  
Sensitivity Analysis ◽  
Multibody Systems ◽  
Automatic Differentiation ◽  
Time Integration ◽  
General Purpose ◽  
Contact Forces ◽  
Design Parameters ◽  
Computational Techniques ◽  
Computationally Efficient ◽  
Integration Algorithm

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.

Design Sensitivity Analysis of Nonlinear Multidisciplinary Multibody Systems in the MIXEDMODELS Platform

2007 ◽  
Author(s):  
Shilpa A. Vaze ◽  
Prakash Krishnaswami ◽  
James DeVault
Keyword(s):  
Sensitivity Analysis ◽  
Multibody Systems ◽  
Design Sensitivity ◽  
Differential Algebraic Equations ◽  
The State ◽  
Design Sensitivity Analysis ◽  
Design Parameters ◽  
State Variables ◽  
Sensitivity Coefficients ◽  
Design Variables

Most state-of-the-art multibody systems are multidisciplinary and encompass a wide range of components from various domains such as electrical, mechanical, hydraulic, pneumatic, etc. The design considerations and design parameters of the system can come from any of these domains or from a combination of these domains. In order to perform analytical design sensitivity analysis on a multidisciplinary system (MDS), we first need a uniform modeling approach for this class of systems to obtain a unified mathematical model of the system. Based on this model, we can derive a unified formulation for design sensitivity analysis. In this paper, we present a modeling and design sensitivity formulation for MDS that has been successfully implemented in the MIXEDMODELS (Multidisciplinary Integrated eXtensible Engine for Driving Metamodeling, Optimization and DEsign of Large-scale Systems) platform. MIXEDMODELS is a unified analysis and design tool for MDS that is based on a procedural, symbolic-numeric architecture. This architecture allows any engineer to add components in his/her domain of expertise to the platform in a modular fashion. The symbolic engine in the MIXEDMODELS platform synthesizes the system governing equations as a unified set of non-linear differential-algebraic equations (DAE’s). These equations can then be differentiated with respect to design to obtain an additional set of DAE’s in the sensitivity coefficients of the system state variables with respect to the system’s design variables. This combined set of DAE’s can be solved numerically to obtain the solution for the state variables and state sensitivity coefficients of the system. Finally, knowing the system performance functions, we can calculate the design sensitivity coefficients of these performance functions by using the values of the state variables and state sensitivity coefficients obtained from the DAE’s. In this work we use the direct differentiation approach for sensitivity analysis, as opposed to the adjoint variable approach, for ease in error control and software implementation. The capabilities and performance of the proposed design sensitivity analysis formulation are demonstrated through a numerical example consisting of an AC rectified DC power supply driving a slider crank mechanism. In this case, the performance functions and design variables come from both electrical and mechanical domains. The results obtained were verified by perturbation analysis, and the method was shown to be very accurate and computationally viable.

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

2006 ◽  
Author(s):  
Srikanth Akkaram ◽  
Jean-Daniel Beley ◽  
Bob Maffeo ◽  
Gene Wiggs
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Automatic Differentiation ◽  
Thermal Response ◽  
Aircraft Engine ◽  
Design Parameters ◽  
Shape Design ◽  
Computer Simulation Model ◽  
Structural Applications ◽  
Analytical Derivatives

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.

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