结构动力分析中的逐级近似缩聚法

SUCCESSION-LEVEL APPROXIMATE REDUCTION TECHNIQUE(SART) IN STRUCTURAL DYNAMIC ANALYSIS

本文基于逐级逼近理论建立了一种动力模型缩聚的逐级近似减缩法（ＳＡＲＴ）．该方法具有协调和非协调格式．本文基于ＳＡＲＴ导出了一般的ｋ级递推减缩公式，其中一级近似和二级近似减缩式就是现有的Ｇｕｙａｎ／Ｉｒｏｎｓ减缩和ＩＲＳ减缩．算例表明，在物理型减缩技术方面，本文的三级近似减缩模型精度最好．

On the basis of succession-level approach theorem, a Succession-level Approximate Reduction Technique (SART) of dynamic model is developed in this peper. SART has two formats: concordance and unconcordance. Otherwise, the general k-level recurrence reduction formulae are derived from SART, in which the reduction formulae of the first-level and second-level approximation in the concordance recurrence formula are Guyan/Irons reduction and IRS reduction, respectively. The example shows that the precision of condensation model obtained from concordance third-level approximation is be in respect of physicalness-type reduction technique.