Assessing MEMS devices from the point of view of functional or thermomechanical reliability, the quantitative knowledge of two basic mechanical characteristics, material strain and stress, plays a significant part. Mechanical behavior of moving MEMS structures or mechanical failure occurrences under environmental or functional loads is often described by secondary characteristics, which rely on strain and stress. For example, material fatigue leading finally to damage can be a result of accumulated creep strain during cyclic deformations. Crack initiation and propagation are driven by both material stress and energy release and consumption around the critical damage area. The chapter presents advanced methods to measure strain and stress values on MEMS devices with a respective micro- or nanoscale spatial resolution. Besides a description of the basic measurement approaches, special technical skills, for example, for fracture mechanics analyses, and necessary tools like software codes are described. Some emphasis is made on stress relief methods for local stress measurement, which make use of measured microscale deformations, and which have been developed starting from a few years ago. For both strain and stress determination, measurement examples on MEMS devices are depicted. Prospects to measure locally material properties as constitutive link between material strain and stress are demonstrated for the measurement of elastic material properties.
Digital Volume Correlation (DVC) is a powerful set of techniques used to compute the local shifts of 3D images obtained, for instance, in tomographic experiments. It is utilized to analyze the geometric changes of the investigated object as well as to correct the corresponding image misalignments for further analysis. It can therefore be used to evaluate the local density changes of the same regions of the inspected specimens, which might be shifted between measurements. In recent years, various approaches and corresponding pieces of software were introduced. Accuracies for the computed shift vectors of up to about 1‰ of a single voxel size have been reported. These results, however, were based either on synthetic datasets or on an unrealistic setup. In this work, we propose two simple methods to evaluate the accuracy of DVC-techniques using more realistic input data and apply them to several DVC programs. We test these methods on three materials (tuff, sandstone, and concrete) that show different contrast and structural features.
International Review of MissionVolume 106, Issue 2 p. 436-439 Documentation Explorations in Evangelism: A Partnership between WCC and CWM Peter Cruchley, Peter Cruchley CWMSearch for more papers by this authorKyriaki Avtzi, Kyriaki Avtzi WCCSearch for more papers by this author Peter Cruchley, Peter Cruchley CWMSearch for more papers by this authorKyriaki Avtzi, Kyriaki Avtzi WCCSearch for more papers by this author First published: 07 December 2017 https://doi.org/10.1111/irom.12196Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume106, Issue2December 2017Pages 436-439 RelatedInformation
