Parallelized sigma-point Kalman filtering for structural dynamics
► Sigma-point Kalman filter is adopted to track the state of composite structures undergoing impact-induced delamination. ► Starting from the independent evolution of sigma-points, we propose a parallel implementation of the filter. ► A shared-memory (OpenMP) architecture is adopted. In this paper,...
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| Published in | Computers & structures Vol. 92; pp. 193 - 205 |
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| Language | English |
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01.02.2012
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| Abstract | ► Sigma-point Kalman filter is adopted to track the state of composite structures undergoing impact-induced delamination. ► Starting from the independent evolution of sigma-points, we propose a parallel implementation of the filter. ► A shared-memory (OpenMP) architecture is adopted.
In this paper, the sigma-point Kalman filter (S-PKF) is adopted to track the state of composite structures undergoing impact-induced delamination. Estimates provided by the S-PKF are obtained through a set of sigma-points, which independently evolve in time according to the system dynamics. Since the number of sigma-points grows proportionally to the number of degrees of freedom of the space-discretized structural system, the S-PKF can become computationally demanding. Starting from the aforementioned independent evolution of the sigma-points, we propose a parallel implementation of the S-PKF within a shared-memory (OpenMP) architecture. Scalability and accuracy issues are eventually discussed. |
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| AbstractList | In this paper, the sigma-point Kalman filter (S-PKF) is adopted to track the state of composite structures undergoing impact-induced delamination. Estimates provided by the S-PKF are obtained through a set of sigma-points, which independently evolve in time according to the system dynamics. Since the number of sigma-points grows proportionally to the number of degrees of freedom of the space-discretized structural system, the S-PKF can become computationally demanding. Starting from the aforementioned independent evolution of the sigma-points, we propose a parallel implementation of the S-PKF within a shared-memory (OpenMP) architecture. Scalability and accuracy issues are eventually discussed. ► Sigma-point Kalman filter is adopted to track the state of composite structures undergoing impact-induced delamination. ► Starting from the independent evolution of sigma-points, we propose a parallel implementation of the filter. ► A shared-memory (OpenMP) architecture is adopted. In this paper, the sigma-point Kalman filter (S-PKF) is adopted to track the state of composite structures undergoing impact-induced delamination. Estimates provided by the S-PKF are obtained through a set of sigma-points, which independently evolve in time according to the system dynamics. Since the number of sigma-points grows proportionally to the number of degrees of freedom of the space-discretized structural system, the S-PKF can become computationally demanding. Starting from the aforementioned independent evolution of the sigma-points, we propose a parallel implementation of the S-PKF within a shared-memory (OpenMP) architecture. Scalability and accuracy issues are eventually discussed. |
| Author | Mariani, Stefano Ghisi, Aldo Eftekhar Azam, Saeed |
| Author_xml | – sequence: 1 givenname: Saeed surname: Eftekhar Azam fullname: Eftekhar Azam, Saeed – sequence: 2 givenname: Aldo surname: Ghisi fullname: Ghisi, Aldo – sequence: 3 givenname: Stefano surname: Mariani fullname: Mariani, Stefano email: stefano.mariani@polimi.it |
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| Cites_doi | 10.1016/B978-008043896-2/50102-9 10.1016/S0045-7825(99)00222-4 10.1016/j.compscitech.2004.12.026 10.1016/j.cma.2004.02.003 10.1016/0010-4361(91)90549-V 10.1016/S0020-7683(00)00088-3 10.3390/a2020808 10.1016/j.ijsolstr.2007.05.007 10.1007/BF00037233 10.1109/ACC.2002.1025369 10.1016/0020-7683(93)90154-Y 10.1016/0020-7683(95)00255-3 10.1016/0263-8223(92)90060-P 10.1007/s11071-008-9349-z 10.1002/nme.761 10.1145/106974.106981 10.1007/s11071-006-9118-9 10.1016/S0266-3538(01)00123-3 10.1016/j.compscitech.2004.12.024 10.1016/S0022-5096(02)00100-X 10.1016/j.cma.2005.01.007 10.1016/0263-8223(95)00002-X 10.1080/00207170410001704998 10.1016/j.jsv.2009.09.009 10.1115/1.3662552 10.1109/9.855552 10.1109/ACC.1995.529783 10.1002/nme.93 10.1109/9.847726 |
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| Keywords | Sigma-point (unscented) transformation Nonlinear dynamics Interface models Composite delamination Kalman filter Set point Unscented transformation Parallel algorithm Vibration Scalability Punctual transformation Dynamical system Modeling System with n degrees of freedom Mechanical system System identification Non linear effect Delamination Shared memory Structural analysis Mechanical shock Damaging |
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| Snippet | ► Sigma-point Kalman filter is adopted to track the state of composite structures undergoing impact-induced delamination. ► Starting from the independent... In this paper, the sigma-point Kalman filter (S-PKF) is adopted to track the state of composite structures undergoing impact-induced delamination. Estimates... |
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| SubjectTerms | Applied sciences Composite delamination Composite structures Computation Computer science; control theory; systems Control theory. Systems Degrees of freedom Dynamical systems Dynamics Evolution Exact sciences and technology Fracture mechanics (crack, fatigue, damage...) Fundamental areas of phenomenology (including applications) Interface models Kalman filter Kalman filtering Mathematical analysis Modelling and identification Nonlinear dynamics Physics Sigma-point (unscented) transformation Solid mechanics Structural and continuum mechanics Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...) |
| Title | Parallelized sigma-point Kalman filtering for structural dynamics |
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