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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0"><?xmltex \makeatother\@nolinetrue\makeatletter?>
  <front>
    <journal-meta><journal-id journal-id-type="publisher">TC</journal-id><journal-title-group>
    <journal-title>The Cryosphere</journal-title>
    <abbrev-journal-title abbrev-type="publisher">TC</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">The Cryosphere</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1994-0424</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/tc-13-1487-2019</article-id><title-group><article-title>Brief communication: Full-field deformation measurement<?xmltex \hack{\break}?> for uniaxial
compression of sea ice using the digital<?xmltex \hack{\break}?> image correlation
method</article-title><alt-title>Full-field deformation measurement for uniaxial compression of sea ice</alt-title>
      </title-group><?xmltex \runningtitle{Full-field deformation measurement for uniaxial compression of sea ice}?><?xmltex \runningauthor{A. Wang et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Wang</surname><given-names>Anliang</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Wei</surname><given-names>Zhijun</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Chen</surname><given-names>Xiaodong</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff3">
          <name><surname>Ji</surname><given-names>Shunying</given-names></name>
          <email>jisy@dlut.edu.cn</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Liu</surname><given-names>Yu</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff4">
          <name><surname>Qing</surname><given-names>Longbang</given-names></name>
          <email>qing@hebut.edu.cn</email>
        </contrib>
        <aff id="aff1"><label>1</label><institution>Marine Disaster Forecasting and Warning Division, National Marine Environmental Forecasting Center,<?xmltex \hack{\break}?> Beijing, 100081, China</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian, 116024, China</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology,<?xmltex \hack{\break}?> Dalian, 116024, China</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>School of Civil Engineering and Transportation, Hebei University of Technology, Tianjin, 300401, China</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Longbang Qing (qing@hebut.edu.cn) and Shunying Ji (jisy@dlut.edu.cn)</corresp></author-notes><pub-date><day>20</day><month>May</month><year>2019</year></pub-date>
      
      <volume>13</volume>
      <issue>5</issue>
      <fpage>1487</fpage><lpage>1494</lpage>
      <history>
        <date date-type="received"><day>29</day><month>November</month><year>2018</year></date>
           <date date-type="rev-request"><day>21</day><month>January</month><year>2019</year></date>
           <date date-type="rev-recd"><day>29</day><month>April</month><year>2019</year></date>
           <date date-type="accepted"><day>4</day><month>May</month><year>2019</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2019 </copyright-statement>
        <copyright-year>2019</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://tc.copernicus.org/articles/.html">This article is available from https://tc.copernicus.org/articles/.html</self-uri><self-uri xlink:href="https://tc.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://tc.copernicus.org/articles/.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e156">The study of the mechanical properties of sea ice benefits the
parameterization of sea-ice numerical models and the optimization of
engineering design. Deformation measurement of sea ice has been seen as the
essential foundation for the study of these properties. However, this
measurement has proved to be difficult due to the complex and nonhomogeneous
mechanical properties of sea ice. In this paper, we took advantage of DIC
(digital image correlation) to obtain the full-field displacement and strain
of sea-ice specimens in a uniaxial compression experiment. Full-field
deformations of sea ice under both vertical and horizontal loading were
measured. Different mechanical behaviors such as microcracks and failure
modes due to the anisotropic properties of sea ice were successfully
captured. The nonuniformity and local concentration of the strain field were
observed and analyzed. Additionally, we evaluated the displacement and strain
field of the specimens to verify the feasibility and accuracy of the method.
This successful application provides a convenient and powerful option for the
study of sea-ice mechanical properties including failure modes, nonlinear
behavior and crack propagation.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

      <?xmltex \hack{\newpage}?>
<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e170">Human activities in polar areas have been increasing as more space becomes
available to be exploited (Laliberté et al., 2016; Rabatel et al., 2018).
This trend calls for better numerical models of sea ice and cold region
technology to reduce risks posed by the ice (Rabatel et al., 2018). Studies
of the mechanical properties of sea ice are believed to have made such
contributions (e.g., Timco and Weeks, 2010; Shokr and Sinha, 2015; Weiss and
Dansereau, 2017). For example, the strength of flexure and compression (Ji et
al., 2011), failure and fracture mode (Schulson et al., 2006; Weiss, 2013;
Lian et al., 2017), and the Young modulus and Poisson ratio (Schulson and
Duval, 2009) are all essential for the parameterization of sea-ice models
(Hibler, 1979; Feltham, 2008; Weiss and Dansereau, 2017) and the optimization
of polar engineering designs (Ibrahim et al., 2007). Deformation measurements
at the laboratory scale are an essential foundation of those studies.
However, it has been found to be difficult to measure the deformation due to
the complex material properties of sea ice (Cole, 2001), even under the
controlled conditions of a well-equipped laboratory (Sinha, 1984; Moslet,
2007). In particular, the measurement of full-field deformation has not been
reported for sea-ice specimens.</p>
      <p id="d1e173">In traditional ice mechanics, displacement actuators, strain gauges and
extensometers are occasionally applied to<?pagebreak page1488?> measure the deformation of
specimens (Moslet, 2007; Schulson and Duval, 2009; Timco and Weeks, 2010).
The equipment for measuring displacement is generally installed onto the
specimen's surface. Thus, the operation sometimes causes local damage and
subsequently increases the local stress concentration. Another option is to
obtain the equivalent displacement of the specimen from an indenter (Schulson
and Duval, 2009; Wang et al., 2018). The loading surface of the specimen and
indenter on it move together and thus have the same displacement all the
time. Therefore, the strain of the specimens can be deduced from the
displacement of indenter without considering the deformation of the rig
itself. This method provides only one value to represent the overall
deformation of the specimen, even under the assumption that the loading
system has sufficient stiffness compared with that of the sea-ice specimen.
For sea-ice material, the local variation in deformation cannot be ignored
due to the existence of brine pockets and air bubbles inside the material
(Schulson and Duval, 2009; Li et al., 2011). Therefore, full-field
deformation is needed to capture the local conditions of sea-ice specimens
and depict the failure characteristics during the loading process.</p>
      <p id="d1e176">Fortunately, the digital image correlation (DIC) method has been developed
(Sutton et al., 2009, 2016), which is suitable for deformation measurements.
Based on DIC, full-field displacement and strain can be accurately
obtained by comparing the digital images of specimen surfaces for the
initial and deformed states (Pan et al., 2009). This method has been widely
used in many fields to obtain the full-field deformation (Sutton et al.,
2016). Recently, Lian et al. (2017) used DIC to investigate the uniaxial
compressive strength and fracture mode of natural lake ice under moderate
strain rates. They found that the strain rate calculated from DIC is quite
different from that deduced from actuator displacement under dynamic
loading conditions (Lian et al., 2017). Based on the DIC technique, the
full-field deformation is accurately deduced and the damage process of the
specimen is clearly obtained at a high spatiotemporal resolution (Lian et al.,
2017). In fact, a similar principle has been applied to sea-ice satellite
images to compute the velocity and strain fields on a geophysical scale
(Muckenhuber and Sandven, 2017). Nevertheless, we are not aware of the
application of DIC in sea-ice mechanical property experiments in the
laboratory or in situ. This is partly due to the complex material
properties and intricate mechanical behaviors of sea ice, which make such
applications more difficult.</p>
      <p id="d1e179">In this paper, we attempt to apply the DIC technique to a sea-ice uniaxial
compression experiment in situ. First, we introduce the experimental
procedure and briefly interpret the DIC theory. Then the displacement and
the strain field of specimens are illustrated and analyzed to certify the
feasibility and accuracy of the method. To our knowledge, this is the first
attempt to experimentally capture sequential full-field deformations in the
mechanical properties of sea ice. This achievement will extend the ability
to further explore the complex mechanical behaviors of sea ice.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Materials and methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Specimens and equipment</title>
      <p id="d1e197">The experiment was carried out at the Bayuquan ocean station
(40<inline-formula><mml:math id="M1" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>07<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula>15.32<inline-formula><mml:math id="M3" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> N, 121<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>57<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula>34.77<inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> E) in Liaodong
Bay, where there is an ice-covered season of approximately 3 months each year.
A large ice block 1.0 m <inline-formula><mml:math id="M7" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1.0 m <inline-formula><mml:math id="M8" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 30 cm (the latter being the thickness) was cut from a level ice sheet
using a chain saw. Meanwhile, we measured the salinity of
seawater and collected several pieces of sea ice for
salinity measurements. The crystal structure of the ice was columnar
with a column diameter of approximately 4 mm. The seawater salinity was
33 ppt at the sampling site, and the ice salinities were between 5.5 and
7.4 ppt with a mean value of 6.1 ppt. The environmental temperature during
our experiment was about <inline-formula><mml:math id="M9" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M10" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C, and the ice temperatures were
between <inline-formula><mml:math id="M11" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4.5</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M12" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5.6</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M13" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C with a mean value of <inline-formula><mml:math id="M14" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4.9</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M15" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C.
These ice blocks were finely processed into cuboid specimens with sizes of
50 mm <inline-formula><mml:math id="M16" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 50 mm <inline-formula><mml:math id="M17" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 107 mm using a band saw. This size
ensured that the specimens contained enough ice crystals to avoid grain
boundary effects (Timco and Weeks, 2010; Ji et al., 2011) and to meet the
maximum load requirement of 3 t for our loading system.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><?xmltex \currentcnt{1}?><label>Figure 1</label><caption><p id="d1e359">Specimen preparation, definition of coordinates and loading system.
<bold>(a)</bold> Black/white speckles from spraying the oil paints onto the
specimen surfaces. <bold>(b–c)</bold> The matching process between the initial
subset and the deformed subset. <bold>(d)</bold> A magnified section of the prepared
specimen corresponding to the yellow line in panel <bold>(a)</bold>.
<bold>(e)</bold> The load applied the specimen from bottom to top.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://tc.copernicus.org/articles/13/1487/2019/tc-13-1487-2019-f01.png"/>

        </fig>

      <p id="d1e383">To obtain a high-contrast speckle pattern, we first sprayed white paint
uniformly onto the specimen's surface as the background and then sprayed black
paint randomly to produce speckles on the white surface, as shown in Fig. 1a.
The specimen surface tended to be flat and smooth after the white
paint was sprayed at least four times. Every spraying required an interval
of 10 min. Half an hour or more after applying the white paint, the
black paint was sprayed onto the white surface. During spray-painting, we
kept the outlet of the black paint a specific distance – greater than 40 cm – from the white
surface. This control ensured that the mist of black paint randomly fell onto the white surface
and resulted in a random gray intensity pattern on the surface. Note
that touching the sprayed surface of the specimen was forbidden
during the experiment to prevent the contamination of the speckle pattern.
After sitting for at least 2 h following the spray-painting, the specimens were
ready for the compression experiment.</p>
      <p id="d1e387">The experimental system mainly consisted of an optical image acquisition
device and loading system. The CCD (charge coupled device) camera and
high-intensity light source were the major components of the former. The
camera was a Basler acA 1600-20gm with a resolution of
1200 pixels <inline-formula><mml:math id="M18" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1600 pixels. This resolution assured an approximate
specimen surface of 500 pixels <inline-formula><mml:math id="M19" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1070 pixels, which was tantamount
to <inline-formula><mml:math id="M20" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.1</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.005</mml:mn></mml:mrow></mml:math></inline-formula> mm per pixel for each frame. The
camera was placed parallel to the specimen's surface, and an appropriate
distance was maintained between them – greater<?pagebreak page1489?> than 2.5 m in our
experiment. This arrangement was used to alleviate the influence of the
out-of-plane deformation (Pan et al., 2009; Sutton et al, 2009). The camera
had a frequency of 20 fps (frames per second) to trace the deformation of
the specimen surface. With respect to the loading system, the load was
applied from the bottom to the top using a servomotor, which was located at
the bottom of the apparatus and could supply the maximum force requirement of
3 t with a constant speed of 0.001–0.8 mm s<inline-formula><mml:math id="M21" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Here, we used a low loading speed of 0.05 mm s<inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>.
Therefore, the frequency of the CCD camera was sufficient to capture the
development of the full-field deformations. The time history of the load and
displacement of the indenter were simultaneously recorded by the loading
system.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Methods</title>
      <p id="d1e448">The DIC method computes deformation information by matching the speckles on
the specimen's surface before and after the loading stages. Generally, the
equilateral grids are virtually assigned on the (specimen's) region of interest.
The center of the subset carries the displacement information, as
illustrated in Fig. 1b and c. The subset generally consists of an area of
(<inline-formula><mml:math id="M23" display="inline"><mml:mrow><mml:mi>M</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula>) pixel <inline-formula><mml:math id="M24" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> (<inline-formula><mml:math id="M25" display="inline"><mml:mrow><mml:mi>M</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula>) pixel. After the assignment of the subsets, the
appropriate matching method for the centers between the initial image and the
deformed image can be determined. Considering the robust noise-proof
performance, we used the following correlation criterion (Pan et al., 2009):
            <disp-formula id="Ch1.E1" content-type="numbered"><label>1</label><mml:math id="M26" display="block"><mml:mrow><mml:mi>C</mml:mi><mml:mo>=</mml:mo><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mi>M</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mi>M</mml:mi></mml:mrow></mml:munderover><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mi>M</mml:mi></mml:mrow><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mi>M</mml:mi></mml:mrow></mml:munderover><mml:msup><mml:mfenced open="(" close=")"><mml:mrow><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:msub><mml:mi>f</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo>-</mml:mo><mml:mover accent="true"><mml:mi>f</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:mrow><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>f</mml:mi></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>-</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:msub><mml:mi>g</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo>-</mml:mo><mml:mover accent="true"><mml:mi>g</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:mrow><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>g</mml:mi></mml:mrow></mml:mfrac></mml:mstyle></mml:mrow></mml:mfenced><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          where <inline-formula><mml:math id="M27" display="inline"><mml:mrow><mml:msub><mml:mi>f</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M28" display="inline"><mml:mrow><mml:msub><mml:mi>g</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> are gray-level functions for the initial image
and the deformed image, respectively; <inline-formula><mml:math id="M29" display="inline"><mml:mover accent="true"><mml:mi>f</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> and <inline-formula><mml:math id="M30" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>f</mml:mi></mml:mrow></mml:math></inline-formula> are
defined as <inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mover accent="true"><mml:mi>f</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mo>=</mml:mo><mml:mstyle displaystyle="false"><mml:mfrac style="text"><mml:mn mathvariant="normal">1</mml:mn><mml:mrow><mml:mo>(</mml:mo><mml:mn mathvariant="normal">2</mml:mn><mml:mi>M</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:msup><mml:mo>)</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:mfrac></mml:mstyle><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mi>M</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mi>M</mml:mi></mml:mrow></mml:munderover><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mi>M</mml:mi></mml:mrow><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mi>M</mml:mi></mml:mrow></mml:munderover><mml:mfenced close=")" open="("><mml:mrow><mml:msub><mml:mi>f</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfenced></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M32" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>f</mml:mi><mml:mo>=</mml:mo><mml:msqrt><mml:mrow><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mi>M</mml:mi></mml:mrow><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mi>M</mml:mi></mml:mrow></mml:munderover><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mi>M</mml:mi></mml:mrow><mml:mrow><mml:mi>j</mml:mi><mml:mo>=</mml:mo><mml:mi>M</mml:mi></mml:mrow></mml:munderover><mml:msup><mml:mfenced open="(" close=")"><mml:mrow><mml:msub><mml:mi>f</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub><mml:mo>-</mml:mo><mml:mover accent="true"><mml:mi>f</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:mrow></mml:mfenced><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:msqrt></mml:mrow></mml:math></inline-formula> in the initial image; and the same definitions
of <inline-formula><mml:math id="M33" display="inline"><mml:mover accent="true"><mml:mi>g</mml:mi><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> and <inline-formula><mml:math id="M34" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>g</mml:mi></mml:mrow></mml:math></inline-formula> are calculated depending on
<inline-formula><mml:math id="M35" display="inline"><mml:mrow><mml:msub><mml:mi>g</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> in the deformed image. When the correlation coefficient <inline-formula><mml:math id="M36" display="inline"><mml:mi>C</mml:mi></mml:math></inline-formula> reaches
the extrema, the center point of the subset in the initial image is matched to
the deformed image. Figure 1b and c illustrate that the displacement
<inline-formula><mml:math id="M37" display="inline"><mml:mi mathvariant="bold-italic">u</mml:mi></mml:math></inline-formula> of the center point is computed according to the matching
information.</p>
      <p id="d1e836">Based on the displacement information of the center point at the initial
subset, we can further obtain the displacement field for all points. Under
the assumption that the deformation is continuous, all of the neighboring
points in the deformed image remain in the same order in the deformed image.
Therefore, all of the coordinates around the center point in Fig. 1b can
be mapped to the points of the deformed subset in Fig. 1c according to
the shape function, similar to the finite element method. Finally, we
obtained the displacement and strain field for the entire surface of the
specimen.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>Image processing</title>
      <p id="d1e847">The whole process flowchart of the DIC method is shown in Fig. 2. The detailed
steps mainly include the following: (1) capturing speckle images before and after
deformation; (2) drawing continuous analysis region(s) and setting DIC parameters,
such as subset radius and subset spacing; (3) performing the initial guess and
nonlinear optimization to obtain the whole displacement fields; (4) smoothing
the displacement fields, after which the stain fields can be obtained by solving
the gradients of displacements.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><?xmltex \currentcnt{2}?><label>Figure 2</label><caption><p id="d1e852">Flowchart of sea-ice image processing for the DIC method.</p></caption>
          <?xmltex \igopts{width=170.716535pt}?><graphic xlink:href="https://tc.copernicus.org/articles/13/1487/2019/tc-13-1487-2019-f02.png"/>

        </fig>

      <p id="d1e861">In practice, some open source codes on Github can be used to carry out the
implementation of DIC, such as ncorr_2D_matlab
(<uri>https://github.com/justinblaber/ncorr_2D_matlab</uri>, last access: 18 April
2019) and DICe (<uri>https://github.com/dicengine/dice</uri>, last access:
18 April 2019), which are followed by some manual files. Basically,<?pagebreak page1490?> the
abovementioned resources are good options when applying the DIC method to
study sea-ice mechanical properties.</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Results</title>
      <p id="d1e879">Full-field deformations of sea ice under both vertical and horizontal loading
directions were measured. These two loading directions are defined in
reference to the ice crystal orientation, which is parallel to the vertical
loading direction and perpendicular to the horizontal loading direction.
Basically, the loading direction can influence the mechanical behaviors due
to the anisotropic properties of sea ice (Timco and Weeks, 2010). In our
experiment, DIC was able to capture these mechanical characteristics by
full-field deformation.</p>
      <p id="d1e882">The displacement and strain fields for the <inline-formula><mml:math id="M38" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> direction and the
<inline-formula><mml:math id="M39" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> direction were obtained based on the images of the ice surface, as shown
in Fig. 1d. Here, all of the strain fields were computed corresponding to the
definition of nominal strain. The coordinates were defined according to
Fig. 1b and c. In this experiment, minus and plus signs represented
compressive and tensile deformation, respectively. We tested a total of seven
samples in the experiments, three of which were subjected to vertical
loading. However, the failure processes of the three samples were not
captured by the DIC technique, as the black/white speckled surface was not
the surface where the failure process occurred. In order to implement DIC analysis, the region of interest for digital image was selected as
50 mm <inline-formula><mml:math id="M40" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 105 mm on
the specimen's surface. Figure 3 shows the
evolution of the strain fields for the different loading stages. The
full-field strain showed nonuniformity under both vertical and horizontal
loading, and the localization appears to be significant in Fig. 3a and b.
Even during the early stages before yielding, which were identified by the
displacement–load curve of the indenter in Fig. 3c, the nonuniformity
remained the same as that in the following plastic stage. For example,
Fig. 3a exhibits strain fields for the <inline-formula><mml:math id="M41" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> direction and the <inline-formula><mml:math id="M42" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> direction
corresponding to four time points (<inline-formula><mml:math id="M43" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M45" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M46" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>)
that are marked on the displacement–load curve in Fig. 3c; point <inline-formula><mml:math id="M47" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> is
the instant when the maximum load occurs. The first two columns obviously
present irregular strain distributions, although they are in the early stages
before yielding. In particular, some of the bottom parts of the specimens
experienced larger strain values than other regions. This trend became more
obvious as the load applied to the specimen increased. A more perceptible
trend occurred in the strain field of the <inline-formula><mml:math id="M48" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> direction, and the relatively
large values were apparently concentrated in the bottom parts of the
specimens. This coincidence between the <inline-formula><mml:math id="M49" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> direction and the <inline-formula><mml:math id="M50" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> direction
strain fields may mean that local failure began in the bottom parts of some
the specimens, but the time points of <inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M52" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> were still in the
early stages before yielding according to the displacement–load curve in
Fig. 3c. Unlike the typical metal displacement–load curve, sea ice had
no clear yield points in Fig. 3c. Here, we took points located in the linear
segment of the displacement–load curve for elastic analysis. As we
predicted, the specimens under vertical loading failed in splitting failure
mode, as shown in Fig. 3d. The final crack distribution in Fig. 3d further
corroborated our speculation about the initial failure. The local damage
configuration (the dashed circle) and vertical crack distribution in Fig. 3d
were accurately captured by the corresponding strain fields of <inline-formula><mml:math id="M53" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and
<inline-formula><mml:math id="M54" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in Fig. 3a. Some types of strain concentration frequently occurred
during our experiment, but the overall displacement–load curves in Fig. 3c
do not really represented their evolution.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><label>Figure 3</label><caption><p id="d1e1044">The evolution of strain fields in the uniaxial compression
experiment. The strain fields of specimens <bold>(a, b)</bold> with respect to
the vertical and horizontal loading; the <inline-formula><mml:math id="M55" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> direction and the <inline-formula><mml:math id="M56" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> direction strain fields
and shear strain fields are located from the first to the third row. The
columns of <inline-formula><mml:math id="M57" display="inline"><mml:mrow><mml:msub><mml:mi>V</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M58" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (<inline-formula><mml:math id="M59" display="inline"><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>,</mml:mo><mml:mi mathvariant="normal">…</mml:mi><mml:mo>,</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula>) correspond to the time
points labeled in the displacement–load curves in panel <bold>(c)</bold>. The
failure pictures <bold>(d, e)</bold> for the specimens <bold>(a, b)</bold>. Note that
the same color bar is shared by the two neighboring strain fields in
panels <bold>(a)</bold> and <bold>(b)</bold> to enhance the color
contrast.</p></caption>
        <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://tc.copernicus.org/articles/13/1487/2019/tc-13-1487-2019-f03.png"/>

      </fig>

      <?pagebreak page1492?><p id="d1e1129">From Fig. 3a and b, we observed two different failure modes and strain
distributions caused by different loading directions. The strain fields of
the <inline-formula><mml:math id="M60" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> direction in Fig. 3a demonstrate the tendency of layered distribution
parallel to the direction of ice crystal orientation, whereas Fig. 3b does
not exhibit this regularity. However, Fig. 3b shows that the propagation
direction of the main crack was parallel to crystal orientation. One
interesting phenomenon was the reversibility that some parts underwent
relatively large strain in the <inline-formula><mml:math id="M61" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> direction and then alternately took low
strain during the early stages before yielding, such as the two squares
within the white rectangle in Fig. 3b. However, once the fracture took shape
at the maximum loads in <inline-formula><mml:math id="M62" display="inline"><mml:mrow><mml:msub><mml:mi>V</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M63" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in Fig. 3a and b, respectively,
the subsequent fractures could propagate based on that shape and resulted in
an irreversible process. Compared with the maximum loads in <inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:msub><mml:mi>V</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and
<inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, the fractures were notably expanded for the strain fields of the <inline-formula><mml:math id="M66" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> direction and the <inline-formula><mml:math id="M67" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> direction at <inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:msub><mml:mi>V</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M69" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>. Obviously, sea-ice
stiffness parallel to the crystal orientation tended to be higher than that
perpendicular to the ice crystal orientation. In turn, the strength of
vertical loading (<inline-formula><mml:math id="M70" display="inline"><mml:mrow><mml:msub><mml:mi>V</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>) was greater than that of horizontal loading
(<inline-formula><mml:math id="M71" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>), as shown in Fig. 3c. Figure 3d and e show the ductile and
splitting failure for two specimens. Corresponding to these two failure modes
of sea ice, the shear strain <inline-formula><mml:math id="M72" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">ε</mml:mi><mml:mrow><mml:mi>x</mml:mi><mml:mi>y</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> concentrated along the
fracture pathway in Fig. 3a for the splitting failure, whereas the shear
zones with the angles of 45<inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> were apparently observed in Fig. 3b for
the ductile failure. Here, we noticed that even at the same indenter
velocity, the different failure modes existed for two specimens due to the
different orientations of the ice crystals. All of these strain
characteristics of the two failure modes and the local fracture propagation
were exactly captured by the DIC.</p>
</sec>
<sec id="Ch1.S4">
  <label>4</label><title>Discussion</title>
      <p id="d1e1282">For this application of DIC, producing a high-quality speckle pattern on the
specimen surface becomes to some extent the most challenging operation. The
specimen surface needs to be covered with a random speckle pattern (Pan et
al., 2009), which is in fact the carrier of deformation information during
the loading process. Unfortunately, there is no natural texture on the
surface of sea-ice specimen that can be used. Therefore, the high quality of the
speckle pattern is an essential prerequisite for our experiment. In
practice, the speckle patterns may show distinctly different intensity
distribution characteristics and have a significant influence on DIC
measurements. Our major challenge came from the natural properties of sea
ice that entrap salt brine pockets and air bubbles. As a result, the surface
of the cut specimens retained some faults, which could not be polished off in
the same fashion as those on the surface of lake ice (Lian et al., 2017). We
artificially created the speckle pattern by spraying the ice with black and white
paints to overcome this drawback. We then applied the mean intensity
gradient to the quality assessment of the speckle pattern. This method is
straightforward and uses easy-to-calculate global parameters to assess the
quality of the speckle pattern. The mean intensity gradient is given as
follows (Pan et al., 2010):
          <disp-formula id="Ch1.E2" content-type="numbered"><label>2</label><mml:math id="M74" display="block"><mml:mrow><mml:msub><mml:mi mathvariant="italic">δ</mml:mi><mml:mi>f</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mi>i</mml:mi><mml:mi>W</mml:mi></mml:munderover><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mi>j</mml:mi><mml:mi>H</mml:mi></mml:munderover><mml:mfenced close="|" open="|"><mml:mrow><mml:mi mathvariant="normal">∇</mml:mi><mml:mi>f</mml:mi><mml:mfenced open="(" close=")"><mml:mrow><mml:msub><mml:mi mathvariant="bold">x</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfenced></mml:mrow></mml:mfenced><mml:mo>/</mml:mo><mml:mo>(</mml:mo><mml:mi>W</mml:mi><mml:mo>×</mml:mo><mml:mi>H</mml:mi><mml:mo>)</mml:mo><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
        where <inline-formula><mml:math id="M75" display="inline"><mml:mi>W</mml:mi></mml:math></inline-formula>and <inline-formula><mml:math id="M76" display="inline"><mml:mi>H</mml:mi></mml:math></inline-formula> are the width and height of the specimen in units of pixels,
<inline-formula><mml:math id="M77" display="inline"><mml:mrow><mml:mfenced open="|" close="|"><mml:mrow><mml:mi mathvariant="normal">∇</mml:mi><mml:mi>f</mml:mi><mml:mfenced close=")" open="("><mml:mrow><mml:msub><mml:mi mathvariant="bold">x</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:mfenced></mml:mrow></mml:mfenced><mml:mo>=</mml:mo><mml:msqrt><mml:mrow><mml:msubsup><mml:mi>f</mml:mi><mml:mi>x</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>f</mml:mi><mml:mi>y</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msubsup></mml:mrow></mml:msqrt></mml:mrow></mml:math></inline-formula>
is the modulus of the local intensity gradient
vector and <inline-formula><mml:math id="M78" display="inline"><mml:mrow><mml:msub><mml:mi>f</mml:mi><mml:mi>x</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M79" display="inline"><mml:mrow><mml:msub><mml:mi>f</mml:mi><mml:mi>y</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> are intensity derivatives at
<inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="bold">x</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> with respect to the <inline-formula><mml:math id="M81" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> direction and the <inline-formula><mml:math id="M82" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> direction. Here, we
took advantage of the Sobel operator to compute the intensity derivatives.
The mean intensity gradients of the initial images for specimens of
Fig. 3a and b were 172.01 and 182.20, respectively. All the values of
specimens for this experiment were between 146.11 and 182.20 with an average
of 164.08. These values suggest a high-quality speckle pattern and
subsequently a high-accuracy subset match in the DIC (Pan et al., 2010).
From Fig. 4a, we found that the gray-level histogram for the speckle
pattern tended to be a random distribution. Here, we took advantage of
false color to enhance the contrast of the gray-level histogram. The randomness
also indicated that we achieved a high-quality speckle pattern on the
specimen surface for the measurements.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><label>Figure 4</label><caption><p id="d1e1452"><bold>(a)</bold> The distribution of gray-level histograms of subset grids
in false color on the surface of a spray-painted specimen and
<bold>(b)</bold> the comparison of displacements from the indenter and the DIC method
during the loading process.</p></caption>
        <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://tc.copernicus.org/articles/13/1487/2019/tc-13-1487-2019-f04.png"/>

      </fig>

      <p id="d1e1466">Our selection for the subset size was 35 pixels <inline-formula><mml:math id="M83" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 35 pixels, as
shown in Fig. 4a. This took the large, complex and nonhomogeneous deformation
of sea-ice specimens into consideration. On the one hand, the size of this
subset was large enough to contain distinctive intensity variations so that
every subset could have a unique speckle pattern and thus benefit the matching process of DIC; on the other hand, this
selection reduced the additional systematic errors in measured displacements.
From Fig. 4a, we can see that every subset is distinct from the others, as
each subset comprises enough speckles to possess its own unique gray-level
distribution.</p>
      <p id="d1e1477">In our experiments, strain concentrations in localized sections were often
observed from the strain fields of specimens. This is most likely due to
the existence of sea-ice defaults. These defaults are generally caused by
air bubbles and salt brine pockets that are entrapped during the growth
process of sea ice (Shokr and Sinha, 2015). In nature, these bubbles and pockets are randomly
distributed inside the sea ice. Therefore, the strain concentration caused
by the defaults could not be avoided by simply artificially handling
the specimen's surface. This random distribution of defaults, to some
degree, defines the difference in the mechanical properties of sea ice with respect to lake
ice and other materials (Schulson, 1999; Cole, 2001; Shokr and Sinha, 2015;
Weiss and Dansereau, 2017). Furthermore, the strength, failure mode and
nonlinear mechanical behavior of sea ice are all related to these defaults
and their random distribution (Schulson, 1999; Cole, 2001; Li et al., 2011).
The strain concentration was exactly captured and further supported the
feasibility of the use of DIC to study the mechanical properties of sea-ice
material.</p>
      <p id="d1e1480">Additionally, we compared the displacement with that obtained from the
indenter to evaluate the results from the DIC method. In our experiment, the indenter and
the bottom of the specimen shown in Fig. 1e should have the same
displacement. The displacements of the indenter were recorded by the loading
system during our experiment. The bottom displacements can be derived from
the digital images based on the DIC. Here, we averaged the displacements of
two bottom lines of pixels as the bottom displacements of the specimen.
Figure 4b demonstrates that these two sources of displacement agree well
throughout the loading history. The red line represents the displacements
of the indenter corresponding to the loading history. Even across the point
of the maximum load where some nonplanar strain may subsequently occur on
the surface of the specimen, the points in Fig. 4b are still close to
the red line. This coincidence suggests that our control of the distance
between the CCD camera and the specimen surface had a beneficial effect on
reducing the influence<?pagebreak page1493?> of out-of-plane strain on the measurement of the
full-field deformation. Nevertheless, when the loading process exceeds
100 s, the deviation seems to be evident. This is mainly due to the large
fracture and damage of the specimen. In addition, the deviation may partly
come from the selection of the analyzed region: the bottom line of the selected region is
1 cm above the bottom line of the specimen in the initial images.
However, the reliability of DIC in the deformation measurement of sea ice is
confirmed by the comparison.</p>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <label>5</label><title>Conclusion</title>
      <p id="d1e1491">Sea ice has heterogeneous mechanical properties due to its multiphase
composition which includes crystalline ice, bubble and brine (Weiss and
Dansereau, 2017). These structural heterogeneities of sea ice make the
measurement of deformation difficult. Subsequently, the mechanical parameter
determination and failure mode analysis for sea ice are influenced. Given the
difficulty, we successfully applied the DIC technique to measure the
deformation of sea ice in a uniaxial compression experiment. The full-field
deformations are obtained and the ability of DIC to capture the strain
concentration and failure modes is confirmed. The local and global
characteristics of ductile and splitting failures are accurately reflected by
the strain fields. In addition, the gray-level distribution and the
comparison of displacements from the indenter and DIC are assessed. The
results corroborate each other and bolster confidence in the reliability of
the method, the quality of speckle pattern and the accuracy of the full-field
deformation measurement in the experiment. The DIC method provides a
convenient and powerful tool for the study of sea-ice mechanical properties
such as the failure mode, nonlinear behavior and crack propagation. According
to the procedure this paper, DIC could easily be extended to other types of
sea-ice mechanical experiments such as flexural strength, shear strength and
fracture toughness. Furthermore, based on the IDIC (integrated digital image
correlation) theory (Roux and Hild, 2006; Leclerc et al., 2009), sea-ice
full-field deformation from DIC should be incorporated into numerical models
such as finite element analysis to realize the parameter identification,
which is able to promote the measurement accuracy of a set of constitutive
parameters such as the Young modulus and Poisson ratio.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability"><title>Data availability</title>

      <p id="d1e1498">All data that support our findings in this paper are
available from the corresponding authors or the first author (wangal@nmefc.cn) upon reasonable request.</p>
  </notes><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e1504">AW wrote the main text and prepared the figures. AW, ZW,
XC and YL carried out the sea-ice experiment in situ. LQ extracted the
full-field deformation based on the DIC method and SJ and AW analyzed the
fracture process of sea-ice specimen. All authors discussed the results, drew
conclusions and contributed to the manuscript text.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <?pagebreak page1494?><p id="d1e1510">The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e1516">This work is supported by the National Key Research and Development Program
of China (grant no. 2016YFC1401500), the National Natural Science Foundation of China
(grant nos. 41506109, 41676189 and 11602051) and the China Postdoctoral Science and
Foundation (grant no. 2016M591433). The authors thank Guorui Cao for many helpful suggestions
regarding the experimental design.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e1521">This research has been supported by the National Key
Research and Development Program of China (grant no. 2016YFC1401500), the
National Natural Science Foundation of China (grant nos. 41506109, 41676189
and 11602051), and the China Postdoctoral Science and Foundation (grant
no. 2016M591433).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e1527">This paper was edited by Christian Haas and reviewed by
Knut Høyland.</p>
  </notes><ref-list>
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  </ref-list></back>
    <!--<article-title-html>Brief communication: Full-field deformation measurement for uniaxial compression of sea ice using the digital image correlation method</article-title-html>
<abstract-html><p>The study of the mechanical properties of sea ice benefits the
parameterization of sea-ice numerical models and the optimization of
engineering design. Deformation measurement of sea ice has been seen as the
essential foundation for the study of these properties. However, this
measurement has proved to be difficult due to the complex and nonhomogeneous
mechanical properties of sea ice. In this paper, we took advantage of DIC
(digital image correlation) to obtain the full-field displacement and strain
of sea-ice specimens in a uniaxial compression experiment. Full-field
deformations of sea ice under both vertical and horizontal loading were
measured. Different mechanical behaviors such as microcracks and failure
modes due to the anisotropic properties of sea ice were successfully
captured. The nonuniformity and local concentration of the strain field were
observed and analyzed. Additionally, we evaluated the displacement and strain
field of the specimens to verify the feasibility and accuracy of the method.
This successful application provides a convenient and powerful option for the
study of sea-ice mechanical properties including failure modes, nonlinear
behavior and crack propagation.</p></abstract-html>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
Cole, D. M.: The microstructure of ice and its influence on mechanical
properties, Eng. Fract. Mech., 68, 1797–1822, 2001.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
Feltham, D. L.: Sea ice rheology, Annu. Rev. Fluid Mech., 40, 91–112,
<a href="https://doi.org/10.1146/annurev.fluid.40.111406.102151" target="_blank">https://doi.org/10.1146/annurev.fluid.40.111406.102151</a>, 2008.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
Hibler, W. D.: A dynamic thermodynamic sea ice model, J. Geophys. Res., 9,
815–846, 1979.
</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
Ibrahim, R. A., Chalhoub, N. G., and Falzarano, J.: Interaction of ships and
ocean structures with ice loads and stochastic ocean waves, Appl. Mech. Rev.,
60, 246–289, <a href="https://doi.org/10.1115/1.2777172" target="_blank">https://doi.org/10.1115/1.2777172</a>, 2007.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
Ji, S., Wang, A., Su, J., and Yue, Q.: Experimental studies on elastic
modulus and flexural strength of sea ice in the Bohai sea, J. Cold Reg. Eng.,
25, 182–195, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
Laliberté, F., Howell, S. E. L., and Kushner P. J.: Regional variability
of a projected sea ice-free Arctic during the summer months, Geophys. Res.
Lett., 43, 256–263, <a href="https://doi.org/10.1002/2015GL066855" target="_blank">https://doi.org/10.1002/2015GL066855</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>7</label><mixed-citation>
Leclerc, H., Périé, J N., Roux, S., and Hild, F.: Integrated digital
image correlation for the identification of mechanical properties, Lect.
Notes Comput. Sc., 5496, 161–171, 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>8</label><mixed-citation>
Li, Z., Zhang, L., Lu, P., Leppäranta, M., and Li, G. Experimental study
on the effect of porosity on the uniaxial compressive strength of sea ice in
Bohai Sea, Sci. China Technol. Sc., 54, 2429–2436,
<a href="https://doi.org/10.1007/s11431-011-4482-1" target="_blank">https://doi.org/10.1007/s11431-011-4482-1</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>9</label><mixed-citation>
Lian, J., Ouyang, Q., Zhao, X., Liu, F., and Qi, C.: Uniaxial compressive
strength and fracture mode of lake ice at moderate strain rates based on a
digital speckle correlation method for deformation measurement, Appl. Sci.,
7, 495, <a href="https://doi.org/10.3390/app7050495" target="_blank">https://doi.org/10.3390/app7050495</a>, 2017.

</mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>10</label><mixed-citation>
Moslet, P. O.: Field testing of uniaxial compression strength of columnar sea
ice, Cold Reg. Sci. Technol., 48, 1–14, 2007.
</mixed-citation></ref-html>
<ref-html id="bib1.bib11"><label>11</label><mixed-citation>
Muckenhuber, S. and Sandven, S.: Open-source sea ice drift algorithm for
Sentinel-1 SAR imagery using a combination of feature tracking and pattern
matching, The Cryosphere, 11, 1835–1850,
<a href="https://doi.org/10.5194/tc-11-1835-2017" target="_blank">https://doi.org/10.5194/tc-11-1835-2017</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib12"><label>12</label><mixed-citation>
Pan, B., Qian, K., Xie, H., and Asundi, A.: Two-dimensional digital image
correlation for in-plane displacement and strain measurement: a review, Meas.
Sci. Technol., 20, 062001, <a href="https://doi.org/10.1088/0957-0233/20/6/062001" target="_blank">https://doi.org/10.1088/0957-0233/20/6/062001</a>, 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib13"><label>13</label><mixed-citation>
Pan, B., Lu, Z., and Xie, H.: Mean intensity gradient: An effective global
parameter for quality assessment of the speckle patterns used in digital
image correlation, Opt. Laser. Eng., 48, 469–477,
<a href="https://doi.org/10.1016/j.optlaseng.2009.08.010" target="_blank">https://doi.org/10.1016/j.optlaseng.2009.08.010</a>, 2010.
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<ref-html id="bib1.bib14"><label>14</label><mixed-citation>
Rabatel, M., Rampal, P., Carrassi, A., Bertino, L., and Jones, C. K. R. T.:
Impact of rheology on probabilistic forecasts of sea ice trajectories:
application for search and rescue operations in the Arctic, The Cryosphere,
12, 935–953, <a href="https://doi.org/10.5194/tc-12-935-2018" target="_blank">https://doi.org/10.5194/tc-12-935-2018</a>, 2018.
</mixed-citation></ref-html>
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Roux, S. and Hild, F.: Stress intensity factor measurements from digital
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Schulson, E. M.: The structure and mechanical behavior of ice, JOM, 51,
21–27, <a href="https://doi.org/10.1007/s11837-999-0206-4" target="_blank">https://doi.org/10.1007/s11837-999-0206-4</a>, 1999.
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Schulson, E. M. and Duval P.: Creep and fracture of ice, Cambridge University
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Schulson, E. M., Fortt, A. L., Iliescu, D., and Renshaw, C. E. Failure
envelope of first-year Arctic sea ice: The role of friction in compressive
fracture, J. Geophys. Res., 111, C11S25, <a href="https://doi.org/10.1029/2005JC003235" target="_blank">https://doi.org/10.1029/2005JC003235</a>, 2006.
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Shokr, S. and Sinha, N. K.: Sea ice: physics and remote sensing, American
Geophysical Union and John Wiley &amp; Sons, New Jersey, USA, 2015.
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Sinha, N. K.: Uniaxial compressive strength of first-year and multi-year sea
ice, Can. J. Civil Eng., 11, 82–91, 1984.
</mixed-citation></ref-html>
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Sutton, M. A., Orteu, J. J., and Schreier, H.: Image correlation for shape,
motion and deformation measurements: basic concepts, theory and applications,
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</mixed-citation></ref-html>
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Sutton, M. A., Matta, F., Rizos, D., Ghorbani, R., Rajan, S., Mollenhauer,
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