Rough surface reconstruction of real surfaces for numerical simulations of ultrasonic wave scattering
Rough surface reconstruction of real surfaces for numerical simulations of ultrasonic wave scattering
复制标题
DOI：
10.1016/j.ndteint.2018.04.004
复制
发表时间：
2018-09-01
影响因子：
4.2
通讯作者：
Daniels, William L.
中科院分区：
文献类型：
--
作者：
Choi, Wonjae;Shi, Fan;Daniels, William L.
粗糙表面对波的散射在包括超声波在内的许多物理科学领域中起着重要的作用，其中失效表面通常是粗糙的，并且它们的准确识别至关重要。当粗糙度没有被充分表征时，散射强度的预测可能会受到阻碍，并且当表面粗糙度在入射波长的量级内时，这是一个特别的问题。在这里，我们开发了一种使用自回归（AR）过程重建并准确表示粗糙表面的方法，然后可以快速数值模拟三维超声波粗糙表面散射。基于真实的曲面数据，分别重建了高斯曲面、指数曲面和AR曲面，并对曲面的统计特性进行了比较。AR表面的统计数据与实际粗糙表面的统计数据在高度和梯度方面一致，这是准确预测波散射强度的两个主要因素。超声粗糙表面散射的数值模拟使用基尔霍夫近似，高斯，指数，AR和真实的样品表面进行比较，发现使用AR表面的散射强度显示最好的协议与真实的样品表面。
The scattering of waves by rough surfaces plays a significant role in many fields of physical sciences including ultrasonics where failure surfaces are often rough and their accurate identification is critical. The prediction of the strength of scattering can be hampered when the roughness is not adequately characterised and this is a particular issue when the surface roughness is within an order of the incident wavelength. Here we develop a methodology to reconstruct, and accurately represent, rough surfaces using an AutoRegressive (AR) process that then allows for rapid numerical simulations of ultrasonic wave rough surface scattering in three dimensions. Gaussian, exponential and AR surfaces are reconstructed based on real surface data and the statistics of the surfaces are compared with each other. The statistics from the AR surfaces agree well with those from actual rough surfaces, taken from experimental samples, in terms of the heights as well as the gradients, which are the two main factors in accurately predicting the wave scattering intensities. Ultrasonic rough surface scattering is simulated numerically using the Kirchhoff approximation, and comparisons with Gaussian, exponential, AR and real sample surfaces are performed; scattering intensities found using AR surfaces show the best agreement with the real sample surfaces.