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Comparative Study of Two Index Two Methods Applied to Original ADAMS Computer Program

机译：两种指数的比较研究两种应用于原始Adams计算机程序的方法

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Improving the quality of the results by lowering the numerical integration index requires that the velocity constraints be used together with the corresponding geometrical constraints. An STF (Sparse Tableaux Formulation) implemented in the original ADAMS increases the size of the problem, and therefore, the size of the Dynamic Jacobean Matrix in a BDF (Backwards Difference Formula) scheme. The sparse matrix technique increases the number of operations by N~(1.3-1.7), where N is the number of rows, of the structured Dynamic Jacobeans. Hence, reducing the number of equations, at the same time maintaining a reasonable sparsity and ignoring some small value terms, will improve the computation speed during numerical integration. The method that is used to accomplish this task is the one described by Fuhrer and Leimkuhler. It suggests a partition of the Dynamic Jacobeans and two solving steps of two BDF corrector formulas. This idea fits into STF only if two sparse matrix symbolic codes are generated. Here the method is called. Using a real example, this paper compares the results of the 2-Steps method with the results obtained by means of the I2 (index 2) having stabilization as needed.
机译：通过降低数值积分指数提高结果的质量要求，速度约束与相应的几何约束一起使用。在原始ADAM中实现的STF（稀疏的TableAux配方）增加了问题的大小，因此，BDF（向后差式）方案中的动态雅各菜矩阵的大小。稀疏矩阵技术增加了n〜（1.3-1.7）的操作数，其中n是结构化动态jacobeans的行数。因此，减少方程数，同时保持合理的稀疏性并忽略一些小值术语，将在数值积分期间提高计算速度。用于完成此任务的方法是Fuhrer和Leimkuhler描述的方法。它建议两个BDF校正器公式的动态雅各菜和两个求解步骤的分区。仅当生成两个稀疏矩阵符号代码时，此想法仅适合STF。这里调用该方法。使用实例，本文将2步骤方法的结果与通过根据需要具有稳定化的I2（索引2）获得的结果。

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