J. Steuben, B. Graber, A. Iliopoulos, J. Michopoulos
{"title":"应用于材料应用的层析成像系统的计算建模的x射线行军","authors":"J. Steuben, B. Graber, A. Iliopoulos, J. Michopoulos","doi":"10.1115/detc2022-91129","DOIUrl":null,"url":null,"abstract":"\n X-ray tomography (XCT) and microtomography (uCT) are powerful experimental techniques for determining the internal structure of materials and objects. However, the physics governing these systems, particularly the myriad of complex interactions between X-rays and materials, lead to the frequent generation of spurious data “artifacts.” When these techniques are used to determine the quantitatively precise dimensions and morphology of defects and other features present in the objects under study, the presence of these artifacts is highly deleterious. A computational framework for simulating and studying tomographic processes, and the physical origins of such artifacts, may increase the overall utility of these techniques. This work presents the introduction, development, and demonstration of such a framework based on a ray-marching approach. A number of physics-driven and computationally-driven considerations guiding the development of this framework are discussed. A demonstration problem taken from prior literature is examined, and it is shown that even a basic implementation of this framework offers meaningful insight which can be used to improve quantitative measurements made using XCT. We conclude with remarks regarding the usage of this technique in a broader scope, and the work required to approach such tasks.","PeriodicalId":382970,"journal":{"name":"Volume 2: 42nd Computers and Information in Engineering Conference (CIE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"X-Ray Marching for the Computational Modeling of Tomographic Systems Applied to Materials Applications\",\"authors\":\"J. Steuben, B. Graber, A. Iliopoulos, J. Michopoulos\",\"doi\":\"10.1115/detc2022-91129\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n X-ray tomography (XCT) and microtomography (uCT) are powerful experimental techniques for determining the internal structure of materials and objects. However, the physics governing these systems, particularly the myriad of complex interactions between X-rays and materials, lead to the frequent generation of spurious data “artifacts.” When these techniques are used to determine the quantitatively precise dimensions and morphology of defects and other features present in the objects under study, the presence of these artifacts is highly deleterious. A computational framework for simulating and studying tomographic processes, and the physical origins of such artifacts, may increase the overall utility of these techniques. This work presents the introduction, development, and demonstration of such a framework based on a ray-marching approach. A number of physics-driven and computationally-driven considerations guiding the development of this framework are discussed. A demonstration problem taken from prior literature is examined, and it is shown that even a basic implementation of this framework offers meaningful insight which can be used to improve quantitative measurements made using XCT. We conclude with remarks regarding the usage of this technique in a broader scope, and the work required to approach such tasks.\",\"PeriodicalId\":382970,\"journal\":{\"name\":\"Volume 2: 42nd Computers and Information in Engineering Conference (CIE)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 2: 42nd Computers and Information in Engineering Conference (CIE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/detc2022-91129\",\"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 2: 42nd Computers and Information in Engineering Conference (CIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/detc2022-91129","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
X-Ray Marching for the Computational Modeling of Tomographic Systems Applied to Materials Applications
X-ray tomography (XCT) and microtomography (uCT) are powerful experimental techniques for determining the internal structure of materials and objects. However, the physics governing these systems, particularly the myriad of complex interactions between X-rays and materials, lead to the frequent generation of spurious data “artifacts.” When these techniques are used to determine the quantitatively precise dimensions and morphology of defects and other features present in the objects under study, the presence of these artifacts is highly deleterious. A computational framework for simulating and studying tomographic processes, and the physical origins of such artifacts, may increase the overall utility of these techniques. This work presents the introduction, development, and demonstration of such a framework based on a ray-marching approach. A number of physics-driven and computationally-driven considerations guiding the development of this framework are discussed. A demonstration problem taken from prior literature is examined, and it is shown that even a basic implementation of this framework offers meaningful insight which can be used to improve quantitative measurements made using XCT. We conclude with remarks regarding the usage of this technique in a broader scope, and the work required to approach such tasks.