M. Aktharuzzaman, Shoaib Anwar, D. Borisov, J. Rao, Jiaze He
{"title":"金属弹性材料特性的二维数值超声计算机断层扫描","authors":"M. Aktharuzzaman, Shoaib Anwar, D. Borisov, J. Rao, Jiaze He","doi":"10.1115/imece2022-90232","DOIUrl":null,"url":null,"abstract":"\n Adequate knowledge of the materials through characterization during the development, production, and processing of the material is required for quality assurance and in-service safety. Material characterization involves the evaluation of properties such as elastic coefficients, material microstructures, morphological features, and associated mechanical properties. Ultrasonic signals are sensitive to useful acoustic properties, including wave speeds, attenuation, diffusion backscattering, variations in microstructure, and elastic properties (e.g., elastic modulus, hardness, etc.). To obtain a quantitative estimation of the material properties, an emerging imaging technique known as ultrasound computed tomography (USCT) can be utilized. This paper proposes to map the wave speeds (i.e., longitudinal and shear) inside elastic parts employing a wave-based methodology (known as full waveform inversion (FWI)) for USCT. FWI is a partial differential equation-constraint, nonlinear optimization technique. It is based on full wavefield modeling and inversion to extract material parameter distribution using wave equations. FWI consequently produces high-resolution images by iteratively determining and minimizing a waveform residual, which is the difference between the modeled and the observed signals. The performance of FWI based ultrasound tomography in material property reconstruction in numerical studies has been presented. The results show its application potential in nondestructive material characterization.","PeriodicalId":23648,"journal":{"name":"Volume 1: Acoustics, Vibration, and Phononics","volume":"12 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"2D Numerical Ultrasound Computed Tomography for Elastic Material Properties in Metals\",\"authors\":\"M. Aktharuzzaman, Shoaib Anwar, D. Borisov, J. Rao, Jiaze He\",\"doi\":\"10.1115/imece2022-90232\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Adequate knowledge of the materials through characterization during the development, production, and processing of the material is required for quality assurance and in-service safety. Material characterization involves the evaluation of properties such as elastic coefficients, material microstructures, morphological features, and associated mechanical properties. Ultrasonic signals are sensitive to useful acoustic properties, including wave speeds, attenuation, diffusion backscattering, variations in microstructure, and elastic properties (e.g., elastic modulus, hardness, etc.). To obtain a quantitative estimation of the material properties, an emerging imaging technique known as ultrasound computed tomography (USCT) can be utilized. This paper proposes to map the wave speeds (i.e., longitudinal and shear) inside elastic parts employing a wave-based methodology (known as full waveform inversion (FWI)) for USCT. FWI is a partial differential equation-constraint, nonlinear optimization technique. It is based on full wavefield modeling and inversion to extract material parameter distribution using wave equations. FWI consequently produces high-resolution images by iteratively determining and minimizing a waveform residual, which is the difference between the modeled and the observed signals. The performance of FWI based ultrasound tomography in material property reconstruction in numerical studies has been presented. The results show its application potential in nondestructive material characterization.\",\"PeriodicalId\":23648,\"journal\":{\"name\":\"Volume 1: Acoustics, Vibration, and Phononics\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 1: Acoustics, Vibration, and Phononics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/imece2022-90232\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 1: Acoustics, Vibration, and Phononics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2022-90232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
2D Numerical Ultrasound Computed Tomography for Elastic Material Properties in Metals
Adequate knowledge of the materials through characterization during the development, production, and processing of the material is required for quality assurance and in-service safety. Material characterization involves the evaluation of properties such as elastic coefficients, material microstructures, morphological features, and associated mechanical properties. Ultrasonic signals are sensitive to useful acoustic properties, including wave speeds, attenuation, diffusion backscattering, variations in microstructure, and elastic properties (e.g., elastic modulus, hardness, etc.). To obtain a quantitative estimation of the material properties, an emerging imaging technique known as ultrasound computed tomography (USCT) can be utilized. This paper proposes to map the wave speeds (i.e., longitudinal and shear) inside elastic parts employing a wave-based methodology (known as full waveform inversion (FWI)) for USCT. FWI is a partial differential equation-constraint, nonlinear optimization technique. It is based on full wavefield modeling and inversion to extract material parameter distribution using wave equations. FWI consequently produces high-resolution images by iteratively determining and minimizing a waveform residual, which is the difference between the modeled and the observed signals. The performance of FWI based ultrasound tomography in material property reconstruction in numerical studies has been presented. The results show its application potential in nondestructive material characterization.