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Parallel algorithm for explicit finite element analysis based on efficient parallel computational strategy
FU Chaojiang, WANG Tianqi, LIN Yuerong
Journal of Computer Applications 2018, 38 (
4
): 1072-1077. DOI:
10.11772/j.issn.1001-9081.2017092384
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Concerning the time-consuming problem of finite element analysis for solving the nonlinear dynamic problems of large-scale structure, some parallel computational strategies for implementing explicit nonlinear finite element analysis were proposed under the environment of Message Passing Interface (MPI) cluster. Based on the technique of domain decomposition with explicit message passing, using overlapped, non-overlapped domain decomposition techniques and Dynamic Task Allocation (DTA) algorithm, domain decomposition parallel algorithms for overlapped domain, non-overlapped domain, clustering for DTA, DTA and Dynamic Load Balancing (DLB) were researched by overlapping calculations and communications to improve the performance of communication between processors. A parallel finite element analysis program was developed with message passing interface as software development environment. Some numerical examples were implemented on workstation cluster to evaluate the performance of the parallel algorithm, the computation performance was also compared with the conventional Newmark algorithm. The experimental results show that the performance of the algorithm for dynamic task allocation with clustering technique is better than that of the dynamic task allocation, which is lower than that of the domain decomposition algorithm, and the dynamic load balancing algorithm is the best. For the problem with the same size, the proposed algorithms are faster and better than conventional Newmark algorithm. The proposed algorithms are efficient for parallel computing of nonlinear dynamic problems of structure.
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Application of parameter-tuning stochastic resonance for detecting weak signal with ultrahigh frequency
HAO Jing, DU Taihang, JIANG Chundong, SUN Shuguang, FU Chao
Journal of Computer Applications 2016, 36 (
9
): 2374-2380. DOI:
10.11772/j.issn.1001-9081.2016.09.2374
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Aiming at the problem that common nonlinear Stochastic Resonance (SR) system is subject to the restriction of small parameter and is failure to detect the high frequency weak signal, a new detection method of parameter-tuning SR for weak signal with high frequency was proposed. Firstly, the relationship between the damping coefficient and the signal frequency was derived in a bistable system, and by using Kramers rate for analysis, the influence of changing damping coefficient on the SR of the system was verified. Then, the influence of SR phenomenon produced by system shape parameters was deduced, the SR of high frequency weak signal was realized through adjusting the damping coefficient and the system shape parameters, and the effect of output spectrum characteristics of the system and different sampling frequency was discussed, the stability of the algorithm was verified by the results. Finally, using the received actual signals with noise as experimental research data, the experimental results show that ultrahigh frequency weak signal under strong noise background can be extracted effectively and steadily using the strategy even when the signal frequency reaches MHz and GHz. The proposed method extends the application field of SR principle of weak signal detection.
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Finite element parallel computing based on minimal residual-preconditioned conjugate gradient method
FU Chaojiang, CHEN Hongjun
Journal of Computer Applications 2015, 35 (
12
): 3387-3391. DOI:
10.11772/j.issn.1001-9081.2015.12.3387
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Finite element analysis for elastic-plastic problem is very time-consuming. A parallel substructure Preconditioned Conjugate Gradient (PCG) algorithm combined with Minimal Residual (MR) smoothing was proposed under the environment of Message Passing Interface (MPI) cluster. The proposed method was based on domain decomposition, and substructure was treated as isolated finite element model via the interface conditions. Throughout the analysis, each processor stored only the information relevant to its substructure and generated the local stiffness matrix. A parallel substructure oriented preconditioned conjugate gradient method was developed, which combined with MR smoothing and diagonal storage scheme. Load balance was discussed and interprocessor communication was optimized in the parallel algorithm. A substepping scheme to integrate elastic-plastic stress-strain relations was used. The errors in the integration process were controlled by adjusting the substep size automatically according to a prescribed tolerance. Numerical example was implemented to validate the performance of the proposed PCG algorithm on workstation cluster. The performance of the proposed PCG algorithm was analyzed and the performance was compared with conventional PCG algorithm. The example results indicate that the proposed algorithm has good speedup and efficiency and is superior in performance to the conventional PCG algorithm. The proposed algorithm is efficient for parallel computing of 3D elastic-plastic problems.
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