This thesis reduces the sensitivity of turbine flow meter to viscosity change by optimize the structure and the geometric parameters of its design.
本论文从优化涡轮流量传感器设计结构与几何参数的角度出发，从根本上降低其对粘度变化的敏感程度。
This thesis deduces computational formulations of displacement sensitivity and stress sensitivity in structural shape optimization considering geometric nonlinear element.
推导了考虑几何非线性项的结构形状优化位移灵敏度和应力灵敏度计算列式。
The geometric factor of sensitivity related to device geometry resulting from short-circuit-effect of power supply electrodes and out-put electrodes can be obtained.
得到了电源电极短路效应和输出电极短路效应引起的灵敏度几何因子与器件尺寸的关系。
In order to investigate the relationship between the surface geometric errors and the uncertainty parameters, the sensitivity matrix was deduced.
为了确定曲面误差与不确定度参数之间的关系，推导了曲面最佳适配的灵敏度矩阵。
The practical algorithm of sensitivity analysis of geometric programming is improved to reduce calculation error, and this method is applied in structure optimal design.
对使用几何规划进行灵敏度分析的实用算法进行了改进，提高了计算准确度，并把几何规划的灵敏度分析成功地用于结构优化设计中。
The sensitivity matrix was then decomposed by singular value decomposition (SVD) method, and the relationship between the surface geometric errors and the uncertainty parameters was formulated.
采用矩阵的奇异值分解原理，对曲面最佳适配的灵敏度矩阵进行分解，得到不确定度参数与测点随机误差的关系表达式。
The sensitivity matrix was then decomposed by singular value decomposition (SVD) method, and the relationship between the surface geometric errors and the uncertainty parameters was formulated.
采用矩阵的奇异值分解原理，对曲面最佳适配的灵敏度矩阵进行分解，得到不确定度参数与测点随机误差的关系表达式。
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