journal article·2023-06-14Open access

Arbitrary-Order Sensitivity Analysis of Eigenfrequency Problems with Hypercomplex Automatic Differentiation (HYPAD)

Juan C. Velasquez-Gonzalez, Juan David Navarro, Mauricio Aristizabal, Harry R. Millwater, Arturo Montoya, David Restrepo

Applied Sciences· Volume 13· Issue 12

Abstract

The calculation of accurate arbitrary-order sensitivities of eigenvalues and eigenvectors is crucial for structural analysis applications, including topology optimization, system identification, finite element model updating, damage detection, and fault diagnosis. Current approaches to obtaining sensitivities for eigenvalues and eigenvectors lack generality, are complicated to implement, prone to numerical errors, and are computationally expensive. In this work, a novel methodology is introduced that uses hypercomplex automatic differentiation (HYPAD) and semi-analytical expressions to obtain arbitrary-order sensitivities for eigenfrequency problems. The new methodology exhibits no sign of truncation nor subtractive cancellation errors regardless of the order of the sensitivity, it is general, and can obtain any high-order sensitivities with the simplicity of first-order computations. A numerical example is presented to verify the accuracy of the method, where the free vibration of a homogeneous cantilever beam is studied. For this problem, up to third-order sensitivities of the eigenvalues and eigenvectors with respect to the material and geometrical parameters were obtained, considering the cases of close and distinct eigenvalues. The results were verified using analytical equations, showing excellent agreement for the eigenvalues and the eigenvectors. The new method promises to facilitate the computation of sensitivities for eigenfrequency problems into routine practice and commercial software.
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Research context

OpenAlex topics: Probabilistic and Robust Engineering Design · Structural Health Monitoring Techniques · Model Reduction and Neural Networks

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mechanical Engineering, The University of Texas at San Antonio, San Antonio, TX 78249, USA

Department of Civil and Environmental Engineering, The University of Texas at San Antonio, San Antonio, TX 78249, USA

Funding

the Office of Naval Research (ONR)

References (77)

Show source-provided references
1. Eigenvector sensitivity when tracking modes with repeated eigenvalues10.1016/j.cma.2017.07.031 ↗
2. New theoretical developments on eigenvector derivatives with repeated eigenvalues10.1016/j.ymssp.2019.04.037 ↗
3. Second-Order Sensitivity Analysis of Multimodal Eigenvalues and Related Optimization Techniques10.1080/03601218608907526 ↗
4. A state-of-the-art review on theory and engineering applications of eigenvalue and eigenvector derivatives10.1016/j.ymssp.2019.106536 ↗
5. The sensitivity method in finite element model updating: A tutorial10.1016/j.ymssp.2010.10.012 ↗
6. Highly efficient general method for sensitivity analysis of eigenvectors with repeated eigenvalues without passing through adjacent eigenvectors10.1002/nme.6442 ↗
7. Projection methods for stochastic dynamic systems: A frequency domain approach10.1016/j.cma.2018.04.025 ↗
8. The QR Transformation A Unitary Analogue to the LR Transformation—Part 110.1093/comjnl/4.3.265 ↗
9. The QR Transformation—Part 210.1093/comjnl/4.4.332 ↗
10. Implicit Application of Polynomial Filters in a k-Step Arnoldi Method10.1137/0613025 ↗
11. The iterative calculation of a few of the lowest eigenvalues and corresponding eigenvectors of large real-symmetric matrices10.1016/0021-9991(75)90065-0 ↗
12. Iterative Computation of Derivatives of Eigenvalues and Eigenvectors10.1093/imamat/24.2.209 ↗
13. Computing Derivatives of Eigenvalues and Elgenvectors by Simultaneous Iteration10.1093/imanum/9.1.111 ↗
14. Some acceleration methods for iterative computer of derivatives of eigenvalues and eigenvectors10.1002/nme.1620280704 ↗
15. QR-based algorithm for eigenvalue derivatives10.2514/2.1569 ↗
16. Rates of Change of Eigenvalues, With Reference to Buckling and Vibration Problems10.1017/S0368393100077385 ↗
17. Rates of change of eigenvalues and eigenvectors10.2514/3.5008 ↗
18. Derivatives of eigenvalues and eigenvectors10.2514/3.5795 ↗
19. Derivatives of eigenvalues and eigenvectors in non-self-adjoint systems10.2514/3.6740 ↗
20. Derivatives of eigenvalues and eigenvectors for a general matrix10.2514/3.49330 ↗
21. Exact nth derivatives of eigenvalues and eigenvectors10.2514/3.21170 ↗
22. Multicomplex Newmark-Beta Time Integration Method for Sensitivity Analysis in Structural Dynamics10.2514/1.J053282 ↗
23. Re-examination of eigenvector derivatives10.2514/3.20259 ↗
24. Iott, J., Haftka, R., and Adelman, H.M. (2023, May 24). Selecting Step Sizes in Sensitivity Analysis by Finite Differences. No. NASA-TM-86382, Available online: https://ntrs.nasa.gov/citations/19850025225.
25. Complex variable method for eigensolution sensitivity analysis10.2514/1.19225 ↗
26. Arbitrary-Order Sensitivity Analysis in Phononic Metamaterials Using the Multicomplex Taylor Series Expansion Method Coupled with Bloch’s Theorem
27. Hyper-dual number-based numerical differentiation of eigensystems10.1016/j.cma.2021.114452 ↗
28. Computation of eigenvector derivatives with repeated eigenvalues using a complete modal space10.2514/3.12723 ↗
29. Simplified calculation of eigenvector derivatives10.2514/3.7211 ↗
30. An accurate modal truncation method for eigenvector derivatives10.1016/S0045-7949(98)00227-2 ↗
31. Balmes, E. (1998, January 2–5). Efficient sensitivity analysis based on finite element model reduction. Proceedings of the International Modal Analysis Conference—IMAC, Santa Barbara, CA, USA.
32. Modal expansion method for eigensensitivity with repeated roots10.2514/3.12221 ↗
33. Yang, Q., and Peng, X. (2020). An exact method for calculating the eigenvector sensitivities. Appl. Sci., 10.10.3390/app10072577 ↗
34. Efficient computation of modal sensitivities for systems with repeated frequencies10.2514/3.9897 ↗
35. Eigenvector derivatives with repeated eigenvalues10.2514/3.10137 ↗
36. A new method for computation of eigenvector derivatives with distinct and repeated eigenvalues in structural dynamic analysis10.1016/j.ymssp.2018.01.003 ↗
37. Improved nelson’s method for computing eigenvector derivatives with distinct and repeated eigenvalues10.2514/1.20880 ↗
38. The Derivatives of Repeated Eigenvalues and Their Associated Eigenvectors10.1115/1.2888195 ↗
39. Simplified calculation of eigenvector derivatives with repeated eigenvalues10.2514/3.13156 ↗
40. Calculation of second and higher order eigenvector derivatives10.2514/3.21481 ↗
41. Differentiation of mass and stiffness matrices for high order sensitivity calculations in finite element-based equilibrium problems10.1115/1.2919275 ↗
42. New method for eigenvector-sensitivity analysis with repeated eigenvalues and eigenvalue derivatives10.2514/1.J053362 ↗
43. Multiple eigenvalues in structural optimization problems10.1007/BF01742705 ↗
44. Rigid body motion test against error in semi-analytical sensitivity analysis10.1016/0045-7949(93)90221-X ↗
45. A Method of “Exact” Numerical Differentiation for Error Elimination in Finite-Element-Based Semi-Analytical Shape Sensitivity Analyses10.1080/08905459308905180 ↗
46. Herskovits, J. (1995). Advances in Structural Optimization: Solid Mechanics and Its Applications, Springer.10.1007/978-94-011-0453-1 ↗
47. Approximation of derivatives in semi-analytical structural optimization10.1016/j.compstruc.2007.04.014 ↗
48. Using Multicomplex Variables for Automatic Computation of High-Order Derivatives10.1145/2168773.2168774 ↗
49. Fike, J., and Alonso, J. (2011, January 4–7). The Development of Hyper-Dual Numbers for Exact Second-Derivative Calculations. Proceedings of the 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Orlando, FL, USA.10.2514/6.2011-886 ↗
50. Complex variable methods for shape sensitivity of finite element models10.1016/j.finel.2011.05.003 ↗
51. Fatigue sensitivity analysis using complex variable methods10.1016/j.ijfatigue.2012.01.016 ↗
52. Voorhees, A., Bagley, R., Millwater, H., and Golden, P. (2009, January 4–7). Application of Complex Variable Methods for Fatigue Sensitivity Analysis. Proceedings of the 50th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Palm Springs, CA, USA.10.2514/6.2009-2711 ↗
53. Sensitivity analysis in thermoelastic problems using the complex finite element method10.1080/01495739.2016.1264871 ↗
54. Numerical calculation of thermo-mechanical problems at large strains based on complex step derivative approximation of tangent stiffness matrices10.1007/s00466-015-1139-0 ↗
55. A virtual crack extension method for thermoelastic fracture using a complex-variable finite element method10.1016/j.engfracmech.2017.12.013 ↗
56. A finite element-based adaptive energy response function method for 2D curvilinear progressive fracture10.1016/j.ijfatigue.2019.05.036 ↗
57. A complex-variable cohesive finite element subroutine to enable efficient determination of interfacial cohesive material parameters10.1016/j.engfracmech.2021.107638 ↗
58. Finite-Element Sensitivity for Plasticity Using Complex Variable Methods10.1061/(ASCE)EM.1943-7889.0000837 ↗
59. Complex step derivative approximation of consistent tangent operators for viscoelasticity based on fractional calculus10.1007/s00466-015-1218-2 ↗
60. Residual stress sensitivity analysis using a complex variable finite element method10.1016/j.ijmecsci.2017.08.035 ↗
61. Complex finite element sensitivity method for creep analysis
62. Sensitivity analysis for radiofrequency induced thermal therapies using the complex finite element method10.1016/j.finel.2017.07.001 ↗
63. Efficient estimate of residual stress variance using complex variable finite element methods10.1016/j.ijpvp.2019.05.004 ↗
64. Robust numerical calculation of tangent moduli at finite strains based on complex-step derivative approximation and its application to localization analysis10.1016/j.cma.2013.11.005 ↗
65. Sensitivity analysis of system reliability using the complex-step derivative approximation10.1016/j.ress.2021.107814 ↗
66. Generalized Approach for Incorporating Normalization Conditions in Design Sensitivity Analysis of Eigenvectors10.2514/1.18760 ↗
67. On Hypercomplex Numbers10.1112/plms/s2-6.1.77 ↗
68. 2968. On the definition of dual numbers10.2307/3612794 ↗
69. Multidual Sensitivity Method in Ray-Tracing Transport Simulations10.1080/00295639.2021.1883949 ↗
70. Kantor, I.L., Kantor, I.L., and Solodovnikov, A.S. (1989). Hypercomplex Numbers: An Elementary Introduction to Algebras, Springer.10.1007/978-1-4612-3650-4 ↗
71. The connection between the complex-step derivative approximation and algorithmic differentiation
72. Multicomplex Taylor Series Expansion For Computing High-Order Derivatives10.12732/ijam.v27i4.2 ↗
73. MultiZ: A library for computation of high order derivatives using multicomplex or multidual numbers10.1145/3378538 ↗
74. Price, G.B. (1991). An Introduction to Multicomplex Spaces and Functions, Dekker.
75. A block forward substitution method for solving the hypercomplex finite element system of equations10.1016/j.cma.2021.114195 ↗
76. Bottega, W.J. (2006). Engineering Vibrations, Taylor & Francis.10.1201/9781420020090 ↗
77. Anderson, E., Bai, Z., Bischof, C., Blackford, S., Demmel, J., Dongarra, J., Du Croz, J., Greenbaum, A., Hammarling, S., and McKenney, A. (1999). {LAPACK} Users’ Guide, Society for Industrial and Applied Mathematics.10.1137/1.9780898719604 ↗