Abstract
The enhanced Craig–Bampton (ECB) method is a novel extension of the original Craig–Bampton (CB) method, which has been widely used for component mode synthesis (CMS). The ECB method, using residual modal compensation that is neglected in the CB method, provides dramatic accuracy improvement of reduced matrices without an increasing number of eigenbasis. However, it also needs additional computational requirements to treat the residual flexibility. In this paper, an efficient parallelization of the ECB method is presented to handle this issue and accelerate the applicability for large-scale structural vibration problems. A new ECB formulation within a substructuring strategy is derived to achieve better scalability. The parallel implementation is based on OpenMP parallel architecture. METIS graph partitioning and Linear Algebra Package (LAPACK) are used to automated algebraic partitioning and computational linear algebra, respectively. Numerical examples are presented to evaluate the accuracy, scalability, and capability of the proposed parallel ECB method. Consequently, based on this work, one can expect effective computation of the ECB method as well as accuracy improvement.
Highlights
The Craig–Bampton (CB) method is one of the most successful component mode synthesis (CMS) techniques [1]
The CB method was originally developed for structural vibration analysis in aerospace engineering, but it has been used in various engineering fields
The implementation of the enhanced Craig–Bampton method is coded in Fortran, using OpenMP [31] for parallelization
Summary
The Craig–Bampton (CB) method is one of the most successful component mode synthesis (CMS) techniques [1]. The ECB method considers the first order term of the residual flexibility in an infinite series expansion for dominant modal correction; it shows dramatic accuracy improvement, over (around) three or four digits, of the CB-reduced matrices, without increasing the number of the dominant modes. Effective computation has been less investigated and, the ECB family has been limited when applied into large-scale structural problems To overcome this issue, an efficient parallelization of the ECB method is presented.
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