Repository: Freie Universit├Ąt Berlin, Math Department

Smart Speed Imaging in Digital Image Correlation: Application to Seismotectonic Scale Modeling

Rudolf, M. and Rosenau, M. and Ziegenhagen, Th. and Ludwikowski, V. and Schucht, Torsten and Nagel, H. and Oncken, O. (2019) Smart Speed Imaging in Digital Image Correlation: Application to Seismotectonic Scale Modeling. Frontiers in Earth Science, 6 . p. 248.

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Official URL: https://dx.doi.org/10.3389/feart.2018.00248

Abstract

Analogue models of earthquakes and seismic cycles are characterized by strong variations in strain rate: from slow interseismic loading to fast coseismic release of elastic energy. Deformation rates vary accordingly from micrometer per second (e.g. plate tectonic motion) to meter per second (e.g. rupture propagation). Deformation values are very small over one seismic cycle, in the order of a few tens of micrometer, because of the scaled nature of such models. This cross-scale behaviour poses a major challenge to effectively monitor the experiments by means of digital image correlation techniques, i.e. at high resolution ($>$100 Hz) during the coseismic period but without dramatically oversampling the interseismic period. We developed a smart speed imaging tool which allows on-the-fly scaling of imaging frequency with strain rate, based on an external trigger signal and a buffer. The external trigger signal comes from a force sensor that independently detects stress drops associated with analogue earthquakes which triggers storage of a short high frequency image sequence from the buffer. After the event has passed, the system returns to a low speed mode in which image data is downsampled until the next event trigger. Here we introduce the concept of smart speed imaging and document the necessary hard- and software. We test the algorithms in generic and real applications. A new analogue earthquake setup based on a modification of the Schulze ring-shear tester is used to verify the technique and discuss alternative trigger systems.

Item Type:Article
Subjects:Mathematical and Computer Sciences > Mathematics > Applied Mathematics
ID Code:2289
Deposited By: Silvia Hoemke
Deposited On:24 Jan 2019 14:45
Last Modified:24 Jan 2019 15:14

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