Sin2ψ-based residual stress gradient analysis by energy-dispersive synchrotron diffraction constrained by small gauge volumes. I. Theoretical concept
Sin2ψ-based residual stress gradient analysis by energy-dispersive synchrotron diffraction constrained by small gauge volumes. I. Theoretical concept
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DOI：
10.1107/s0021889813008340
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发表时间：
2013-06-01
影响因子：
6.1
通讯作者：
Genzel, Ch
中科院分区：
文献类型：
--
作者：
Meixner, M.;Klaus, M.;Genzel, Ch
从理论上研究了应变计体积大小和形状对用同步辐射能散衍射法分析近表面残余应力梯度的影响。情况下被认为是受照射的样品体积被限制的窄缝系统，在初级和衍射光束，尺寸相当于“自然”的1/e信息深度τ（1/e）的X射线。结果表明，τ（1/e）（由材料的吸收率定义）和标准体积浸入样品的深度h（GV）之间的比值是决定在X射线应力分析的Psi模式中获得的d（psi）（hkl）或ψ（hkl）（psi）与sin（2）psi分布的关键参数。由于< z >所测量的X射线信号必须被分配到的实际信息深度（GV）是几何和指数加权函数的叠加，所以< z >对于使用窄缝配置执行的测量，可能出现在拉普拉斯应力对（GV）的常规曲线图中的模糊性。为了避免在这些情况下的数据分析中的冲突，提出了一种改进的形式主义的评价的真实的空间残余应力分布σ（平行于）（z），这是基于一个二维最小二乘拟合过程。
The influence of the gauge volume size and shape on the analysis of steep near-surface residual stress gradients by means of energy-dispersive synchrotron diffraction is studied theoretically. Cases are considered where the irradiated sample volume is confined by narrow-slit systems, in both the primary and the diffracted beam, to dimensions comparable to the 'natural' 1/e information depth tau(1/e) of the X-rays. It is shown that the ratio between tau(1/e), defined by the material's absorption, and the immersion depth h(GV) of the gauge volume into the sample is the crucial parameter that shapes the d(psi)(hkl) or epsilon(hkl)(psi) versus sin(2)psi distributions obtained in the Psi mode of X-ray stress analysis. Since the actual information depth < z >(GV) to which the measured X-ray signal has to be assigned is a superposition of geometrical and exponential weighting functions, ambiguities in the conventional plot of the Laplace stresses versus < z >(GV) may occur for measurements performed using narrow-slit configurations. To avoid conflicts in data analysis in these cases, a modified formalism is proposed for the evaluation of the real space residual stress profiles sigma(parallel to)(z), which is based on a two-dimensional least-squares fit procedure.