DOI: 10.4231/qf39-q924
title: Calibration Data Set for Damage Mechanics Challenge on Brittle-Ductile Material

description: &lt;p&gt;The reliability and sustainability of civil infrastructure, the human body and the Earth&#39;s subsurface all depend on our ability to monitor existing and evolving damage. Damage is a key mode of failure of civil infrastructure, components of the human body and subsurface storage sites, but it is of the highest importance for the success of enhanced energy production from geothermal and traditional subsurface reservoirs. As artificial intelligence methods advance in the detection of anomalous signals in data from sensors, methods are needed to link these readings to the underlying physics/mechanics of failure to determine if failure is imminent. This requires robust computational methods that capture the physics of failure and identify the measurable signatures of failure. While there are many computational approaches for simulating damage, few have been ground-truth tested with either known experimental data or with blind data sets.&lt;/p&gt;

&lt;p&gt;Here, we provide &lt;strong&gt;a benchmark laboratory data&lt;/strong&gt; set from &lt;strong&gt;3 point bending experiments&lt;/strong&gt; for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile material.  &lt;/p&gt;

&lt;p&gt;The benchmark laboratory dataset includes measurements from traditional digital load-displacement sensors, 3D digital image correlation to map surface deformations, 3D X-ray microscopy to ground-truth the crack-failure geometry and notch geometry, and laser profilometry to capture surface roughness.&lt;/p&gt;

&lt;p&gt;The samples were fabricated through additive manufacturing methods (e.g. 3D printing) to produce repeatable samples designed to fail in controlled ways. These methods were selected to ensure that participant-defined repeatable and unbiased metrics were available to quantitatively assess and measure the quality of the theoretical and data-driven models, given the significant influence of inherent uncertainty and variability on the onset and mode of failure.  &lt;/p&gt;

&lt;p&gt;The benchmark data are for a challenge to &lt;/p&gt;

&lt;p&gt;1. compare computational approaches on damage evolution for predicting fracture behavior of 3D printed model rock,&lt;/p&gt;

&lt;p&gt;2. identify the information provided by the different simulation approaches that gives insight into the prediction and interpretation of failure in rock; &lt;/p&gt;

&lt;p&gt;3. identify model parameters that are currently not measured or cannot be measured in the laboratory; and&lt;/p&gt;

&lt;p&gt;4. determine whether there are other experimental measurements that are needed or better methods of performing measurements to monitor damage evolution. &lt;/p&gt;

&lt;p&gt;This challenge exercise is used to determine the state of the art and future directions to improve the community&rsquo;s ability to simulate crack formation and evolution in natural and engineered brittle-ductile materials. The participants are asked to predict the forces and displacements required to initiate and propagate a crack in an additively manufactured specimen to predict failure load, crack propagation path length as a function of load, and fracture surface roughness.&lt;/p&gt;

&lt;p&gt;The following files are available to participants:&lt;/p&gt;

&lt;p&gt;The &lt;strong&gt;&quot;DamageChallenge_SlideDeck_00.pdf&lt;/strong&gt;&quot; provides an overview of the challenge, the questions posed by the challenge, how to report simulation findings by participants, the data provided for the challenge, information on the laboratory testing methods, a description of the calibration results and a description of the format of the calibration data files.&lt;/p&gt;

&lt;p&gt;The &quot;&lt;strong&gt;FracutreSurface.zip&lt;/strong&gt;&quot; file contains laser profilometry data in csv formatted files (one per sample) with 250 rows and 120 columns. The data were collected in 0.1 mm increment between data points in both directions. Information on the laser profilometry measurements and data files can be found on pages 50, 51, 57, and 64  of the DamageChallenge_SlideDeck_00.pdf.&lt;/p&gt;

&lt;p&gt;The &quot;&lt;strong&gt;LD.zip&lt;/strong&gt;&quot; file contains the load-displament data in csv formatted files (opener sample) with 2 columns of data. The first column contains the load (in Newtons) and the second column the displacement (in millimeters).   Information on the load-displacment measurements and data files can be found on pages 39-41, 53, 55 and 63  of the DamageChallenge_SlideDeck_00.pdf.&lt;/p&gt;

&lt;p&gt;The &quot;&lt;strong&gt;MaterialProperite.zip&lt;/strong&gt;&quot; file contains the ultrasonic measurements on 3D printed cubes (in a folder labeled &quot;SEISMIC&quot;) and X-ray diffraction data (XRD) that was used to determine the composition of the samples.  The files in the &quot;SEISMIC&quot; folder are text files that contain the received signal (proposed from eight faces A-to-C, B-toD, or E-to-F) listed as a single column of data with 0.01 microsecond per point.  The files in the &quot;XRD&quot; folder contain images from the XRD system containing information on the content of the samples.  Information on the material property measurements and data files can be found on pages 47-49, 59-61 and 65  of the DamageChallenge_SlideDeck_00.pdf.&lt;/p&gt;

&lt;p&gt;This data set only includes the material properties, load-displacement data and fracture surface roughness data.&lt;/p&gt;

&lt;p&gt;A second supplementary data set is published under &quot;Jiang, L., Pyrak-Nolte, L., Yoon, H., Bobet, A., Morris, J. (2021). Digital Image, X-ray CT , XRD and Ultrasonic Data Sets for Damage Mechanics Challenge on Brittle-Ductile Material. Purdue Unversity Research Repository. &lt;a href="https://doi.org/10.4231/2E8M-W085"&gt;10.4231/2E8M-W085&lt;/a&gt;&quot; that contains digital image correlation data taken during loading, X-ray tomographic images showing the notch geometry for each sample and the induced fracture geometry and also the seismic and XRD datasets.  &lt;/p&gt;
description: Here, we provide a benchmark laboratory data set from 3 point bending experiments for a damage mechanics challenge to compare computational approaches on damage evolution in brittle-ductile material.