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Quantitative characterisation of metals using multiple scattering of ultrasonic waves

Quantitative characterisation of metals using multiple scattering of ultrasonic waves
使用超声波多重散射对金属进行定量表征
批准号:
2737848
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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中文摘要
翻译
本项目将致力于利用超声多次散射现象来定量描述金属材料的微观结构特性(颗粒大小和形状或尺寸以及微织构区域的各向异性晶体取向)。与使用单一传感器的传统测量相比,有几个主要的优点。首先,该方法完全基于发射机接收机后向散射阵数据的后处理,不需要对阵列硬件进行任何改变,也不需要对样品的几何形状提出特殊要求。其次,可以提取材料的每个局部区域的数据,这导致了每个局部材料区域的微观结构表征的可能性。第三,该方法还可以用于弱局部材料不均匀的检测和定位,这是传统成像无法检测到的(例如,微纹理区域、蠕变损伤)。该项目由几项任务组成,简要概述如下。-开发粗晶材料阵列数据的快速半解析模型,其中包括超声波的多次散射。-开发有效的算法,从阵列数据中提取多个散射参数。-不同多次散射参数对材料微观结构的敏感性研究。-开发有效的方案,以解决从提取的多重散射特征估计微结构特性的反问题。--实验验证。-软件演示器的开发。
英文摘要
This project will focus on exploiting ultrasound multiple scattering phenomenon to quantitatively characterise microstructural properties of metallic materials (grain size and shape or size and the anisotropic crystal orientation of micro-textured regions). There are several major advantages compared to the traditional measurements using a single transducer. Firstly, the approach is based entirely on post-processing of the transmitter receiver backscattering array data and does not require any changes in array hardware or specific requirements on the specimen's geometry. Secondly, it is possible to extract data for each local area of the material, which leads to the possibility of microstructural characterisation of each local material region. Thirdly, the method can also be used for detection and localisation of weak local material inhomogeneities, which are undetectable using conventional imaging (for example, microtextured regions, creep damage). The project consists of several tasks, briefly outlined below. - Development of the fast semi-analytical model of array data for coarse grain materials, which includes multiple scattering of ultrasonic waves. - Development of efficient algorithms to extract multiple scattering parameters from the array data. - Sensitivity study of different multiple scattering parameters to material microstructure. - Development of efficient scheme to solve the inverse problem of estimating microstructural properties from extracted multiple scattering characteristics. - Experimental validation. - Development of software demonstrator.
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