{"title":"基于全场数据驱动识别的材料应变速率相关性实验表征","authors":"","doi":"10.1016/j.ijimpeng.2024.105083","DOIUrl":null,"url":null,"abstract":"<div><p>Mechanical characterization usually relies on standardized sample geometries where homogeneous state of strain and stress are prescribed. Hence, many tests are required to capture the material response over various loading conditions. Using complex geometry allows for exploring wider domain in a single test but would require to have access to local strains and stresses to feed models. In that context, digital image correlation and clustering technique can be used to formulate an inverse problem able to identify fields of stress tensors without <em>a priori</em> constitutive modelling. This study explores the performances of a rate-dependent formulation of such a data-driven stress identification method, for capturing using a single test, the monotonic high strain-rate dependent response of a mild steel alloy. After presenting the problem formulation and resolution framework, a digital twin of a high speed tensile test performed on a notched sample geometry is used to explore identification performances. It allows defining confidence intervals depending on multiple indicators (stress magnitude, multiaxiality) and evaluate the range of strain-rate levels simultaneously captured. The method is eventually applied to a real experiment instrumented with high spatial resolution ultra high speed camera. Stress tensor fields are identified, within a 10 <span><math><mtext>%</mtext></math></span> confidence over the major part of the sample, and its material rate-dependence is retrieved from 20 to 300 s<sup>−1</sup> and found in very good agreement with literature. This is the first experimental application of the DDI in a high strain-rate context. The proposed framework may substantially widen the sample design space for mechanical characterization but also allow for probing local stresses during dynamic localization processes where in-situ quantitative data are still missing.</p></div>","PeriodicalId":50318,"journal":{"name":"International Journal of Impact Engineering","volume":null,"pages":null},"PeriodicalIF":5.1000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Experimental characterization of material strain-rate dependence based on full-field Data-Driven Identification\",\"authors\":\"\",\"doi\":\"10.1016/j.ijimpeng.2024.105083\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Mechanical characterization usually relies on standardized sample geometries where homogeneous state of strain and stress are prescribed. Hence, many tests are required to capture the material response over various loading conditions. Using complex geometry allows for exploring wider domain in a single test but would require to have access to local strains and stresses to feed models. In that context, digital image correlation and clustering technique can be used to formulate an inverse problem able to identify fields of stress tensors without <em>a priori</em> constitutive modelling. This study explores the performances of a rate-dependent formulation of such a data-driven stress identification method, for capturing using a single test, the monotonic high strain-rate dependent response of a mild steel alloy. After presenting the problem formulation and resolution framework, a digital twin of a high speed tensile test performed on a notched sample geometry is used to explore identification performances. It allows defining confidence intervals depending on multiple indicators (stress magnitude, multiaxiality) and evaluate the range of strain-rate levels simultaneously captured. The method is eventually applied to a real experiment instrumented with high spatial resolution ultra high speed camera. Stress tensor fields are identified, within a 10 <span><math><mtext>%</mtext></math></span> confidence over the major part of the sample, and its material rate-dependence is retrieved from 20 to 300 s<sup>−1</sup> and found in very good agreement with literature. This is the first experimental application of the DDI in a high strain-rate context. The proposed framework may substantially widen the sample design space for mechanical characterization but also allow for probing local stresses during dynamic localization processes where in-situ quantitative data are still missing.</p></div>\",\"PeriodicalId\":50318,\"journal\":{\"name\":\"International Journal of Impact Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2024-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Impact Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0734743X24002070\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Impact Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0734743X24002070","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Experimental characterization of material strain-rate dependence based on full-field Data-Driven Identification
Mechanical characterization usually relies on standardized sample geometries where homogeneous state of strain and stress are prescribed. Hence, many tests are required to capture the material response over various loading conditions. Using complex geometry allows for exploring wider domain in a single test but would require to have access to local strains and stresses to feed models. In that context, digital image correlation and clustering technique can be used to formulate an inverse problem able to identify fields of stress tensors without a priori constitutive modelling. This study explores the performances of a rate-dependent formulation of such a data-driven stress identification method, for capturing using a single test, the monotonic high strain-rate dependent response of a mild steel alloy. After presenting the problem formulation and resolution framework, a digital twin of a high speed tensile test performed on a notched sample geometry is used to explore identification performances. It allows defining confidence intervals depending on multiple indicators (stress magnitude, multiaxiality) and evaluate the range of strain-rate levels simultaneously captured. The method is eventually applied to a real experiment instrumented with high spatial resolution ultra high speed camera. Stress tensor fields are identified, within a 10 confidence over the major part of the sample, and its material rate-dependence is retrieved from 20 to 300 s−1 and found in very good agreement with literature. This is the first experimental application of the DDI in a high strain-rate context. The proposed framework may substantially widen the sample design space for mechanical characterization but also allow for probing local stresses during dynamic localization processes where in-situ quantitative data are still missing.
期刊介绍:
The International Journal of Impact Engineering, established in 1983 publishes original research findings related to the response of structures, components and materials subjected to impact, blast and high-rate loading. Areas relevant to the journal encompass the following general topics and those associated with them:
-Behaviour and failure of structures and materials under impact and blast loading
-Systems for protection and absorption of impact and blast loading
-Terminal ballistics
-Dynamic behaviour and failure of materials including plasticity and fracture
-Stress waves
-Structural crashworthiness
-High-rate mechanical and forming processes
-Impact, blast and high-rate loading/measurement techniques and their applications