{"title":"测量来自高分辨率晶粒尺度应变场的代表性体积元素","authors":"Renato B. Vieira, J. Lambros","doi":"10.1111/str.12423","DOIUrl":null,"url":null,"abstract":"Most crystalline materials present a highly heterogeneous response at the microscale, which can be affected by both internal factors (such as microstructural parameters) and external factors (such as loading). Relating microscale inhomogeneities to the macroscale response of a material requires the use of homogenisation techniques, usually based on the concept of a representative volume element (RVE)—the smallest volume of material that represents the global average response. In this work, we present a new and robust experimental method of measuring the size of a strain‐based RVE from high‐resolution grain‐scale strain fields obtained using digital image correlation (DIC). The proposed method is based on the statistical (stereological) nature of the RVE, which has been widely adopted in numerical studies, and involves dividing a strain field into randomly selected regions of varying sizes and statistically analysing the distributions of average strains within them. To validate the new method, we generate a large number of synthetic strain fields from a fractional Gaussian noise algorithm. The proposed stereological method is shown to be capable of producing reliable RVE measurements from a very large range of possible microscale strain fields while at the same time being robust in that it can produce RVE measurement results even in cases where other existing methods may be unable to do so. The proposed method has a low field‐of‐view requirement, only needing a field‐of‐view about 1.2 times as large as the RVE to produce reliable measurements. In addition, the stereological method offers significant flexibility since its statistical nature allows for control over how strict the RVE measurement should be in each case.","PeriodicalId":51176,"journal":{"name":"Strain","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring representative volume elements from high‐resolution grain‐scale strain fields\",\"authors\":\"Renato B. Vieira, J. Lambros\",\"doi\":\"10.1111/str.12423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most crystalline materials present a highly heterogeneous response at the microscale, which can be affected by both internal factors (such as microstructural parameters) and external factors (such as loading). Relating microscale inhomogeneities to the macroscale response of a material requires the use of homogenisation techniques, usually based on the concept of a representative volume element (RVE)—the smallest volume of material that represents the global average response. In this work, we present a new and robust experimental method of measuring the size of a strain‐based RVE from high‐resolution grain‐scale strain fields obtained using digital image correlation (DIC). The proposed method is based on the statistical (stereological) nature of the RVE, which has been widely adopted in numerical studies, and involves dividing a strain field into randomly selected regions of varying sizes and statistically analysing the distributions of average strains within them. To validate the new method, we generate a large number of synthetic strain fields from a fractional Gaussian noise algorithm. The proposed stereological method is shown to be capable of producing reliable RVE measurements from a very large range of possible microscale strain fields while at the same time being robust in that it can produce RVE measurement results even in cases where other existing methods may be unable to do so. The proposed method has a low field‐of‐view requirement, only needing a field‐of‐view about 1.2 times as large as the RVE to produce reliable measurements. In addition, the stereological method offers significant flexibility since its statistical nature allows for control over how strict the RVE measurement should be in each case.\",\"PeriodicalId\":51176,\"journal\":{\"name\":\"Strain\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2022-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Strain\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1111/str.12423\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, CHARACTERIZATION & TESTING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Strain","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1111/str.12423","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, CHARACTERIZATION & TESTING","Score":null,"Total":0}
Measuring representative volume elements from high‐resolution grain‐scale strain fields
Most crystalline materials present a highly heterogeneous response at the microscale, which can be affected by both internal factors (such as microstructural parameters) and external factors (such as loading). Relating microscale inhomogeneities to the macroscale response of a material requires the use of homogenisation techniques, usually based on the concept of a representative volume element (RVE)—the smallest volume of material that represents the global average response. In this work, we present a new and robust experimental method of measuring the size of a strain‐based RVE from high‐resolution grain‐scale strain fields obtained using digital image correlation (DIC). The proposed method is based on the statistical (stereological) nature of the RVE, which has been widely adopted in numerical studies, and involves dividing a strain field into randomly selected regions of varying sizes and statistically analysing the distributions of average strains within them. To validate the new method, we generate a large number of synthetic strain fields from a fractional Gaussian noise algorithm. The proposed stereological method is shown to be capable of producing reliable RVE measurements from a very large range of possible microscale strain fields while at the same time being robust in that it can produce RVE measurement results even in cases where other existing methods may be unable to do so. The proposed method has a low field‐of‐view requirement, only needing a field‐of‐view about 1.2 times as large as the RVE to produce reliable measurements. In addition, the stereological method offers significant flexibility since its statistical nature allows for control over how strict the RVE measurement should be in each case.
期刊介绍:
Strain is an international journal that contains contributions from leading-edge research on the measurement of the mechanical behaviour of structures and systems. Strain only accepts contributions with sufficient novelty in the design, implementation, and/or validation of experimental methodologies to characterize materials, structures, and systems; i.e. contributions that are limited to the application of established methodologies are outside of the scope of the journal. The journal includes papers from all engineering disciplines that deal with material behaviour and degradation under load, structural design and measurement techniques. Although the thrust of the journal is experimental, numerical simulations and validation are included in the coverage.
Strain welcomes papers that deal with novel work in the following areas:
experimental techniques
non-destructive evaluation techniques
numerical analysis, simulation and validation
residual stress measurement techniques
design of composite structures and components
impact behaviour of materials and structures
signal and image processing
transducer and sensor design
structural health monitoring
biomechanics
extreme environment
micro- and nano-scale testing method.