Abstract

Rapid identification of dynamic forces is an important research subject. To reduce the computing time, a parallel computing-oriented method is proposed in this study for dealing with a long-time duration problem of force identification. The proposed method is implemented via three continues steps, i.e., partition of parallel computing tasks, solution of parallel computing tasks and fusion of the identified results. In the first step, moving time window is applied for splitting an original problem into several sub-problems in time domain. Then the next step focuses on solving the sub-problems which can be executed in parallel. Herein, influences of unknown initial conditions are considered. Sparse regularization such as weighted l1-norm regularization method is introduced for ensuring that the identified result is sparse and stable. In the last step, the identified results calculated from all the sub-problems are fused via a weighted average method. Numerical simulations are carried out on a frame structure and a truss structure, respectively. A cluster constructed from three personal computers is used for implementation of the proposed method. Illustrated results show that the proposed method can be used for identifying the dynamic forces in long-time duration and saving the computing time. Some related issues are discussed as well.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.