Nonlinear dynamic analysis considering explicit and implicit time marching techniques with adaptive time integration parameters

2018 ◽  
Vol 229 (5) ◽  
pp. 2097-2116 ◽  
Author(s):  
Delfim Soares
Keyword(s):  
Dynamic Analysis ◽  
Nonlinear Dynamic ◽  
Time Integration ◽  
Nonlinear Dynamic Analysis ◽  
Implicit Time ◽  
Adaptive Time Integration ◽  
Time Marching ◽  
Adaptive Time

Mixed Time Integration Parallel Algorithm for Nonlinear Dynamic Analysis

2014 ◽  
Vol 580-583 ◽  
pp. 3038-3041
Author(s):  
Chao Jiang Fu
Keyword(s):  
Dynamic Analysis ◽  
Parallel Algorithm ◽  
Nonlinear Dynamic ◽  
Time Integration ◽  
Nonlinear Dynamic Analysis ◽  
Integration Technique ◽  
Explicit Time Integration ◽  
Implicit Algorithm ◽  
Integration Techniques ◽  
Implicit And Explicit

The mixed time integration parallel algorithm for nonlinear dynamic analysis was presented by synthesising the implicit and explicit time integration techniques. The parallel algorithm employing mixed time integration technique was devised with domain decomposition. Concurrency was introduced into this algorithm by integrating interface nodes with explicit time integration technique and solving local subdomains with implicit algorithm. Numerical example was implemented to validate the performance of the parallel algorithm. Numerical studies indicate that the proposed algorithm is superior in performance to the implicit algorithm.

An Optimized Explicit–Implicit Time-Marching Formulation for Dynamic Analysis

2020 ◽  
pp. 2050045
Author(s):  
Delfim Soares ◽  
Matheus M. Rodrigues
Keyword(s):  
Dynamic Analysis ◽  
Time Domain ◽  
Optimization Algorithm ◽  
Computational Efficiency ◽  
Implicit Time ◽  
Excellent Performance ◽  
Time Step ◽  
Time Marching ◽  
Adaptive Time

In this paper, an optimized approach is proposed to enhance the performance of combined explicit–implicit time-domain analyses. In this context, an entirely automated explicit-implicit adaptive time-marching procedure is discussed as well as an optimization algorithm is introduced to compute the adopted time-step value of the analysis, so that the amount of explicit and implicit elements occurring along the model may be optimally provided, in terms of computational efficiency. The proposed formulation is very effective, allowing evaluating highly accurate responses considering much reduced computational efforts. At the end of the manuscript, numerical applications are presented, illustrating the excellent performance of the proposed formulation.

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