the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Apr 2024
Evolution of crystallographic preferred orientations of ice sheared to high strains by equal-channel angular pressing
Abstract. Plastic deformation of polycrystalline ice 1 h induces crystallographic preferred orientations (CPOs), which give rise to anisotropy in the viscosity of ice, thereby exerting a strong influence on the flow of glaciers and ice sheets. The development of CPOs is governed by two pivotal mechanisms: recrystallization dominated by subgrain/lattice rotation and by strain-induced grain boundary migration (GBM). To examine the impact of strain on the transition of the dominant mechanism, synthetic ice (doped with ∼1 vol.% graphite) was deformed using equal-channel angular pressing technique, enabling multiple passes to accumulate substantial shear strains. Nominal shear strains up to 6.2, equivalent to a nominal von Mises strain of ε′ ≈ 3.6, were achieved in samples at a temperature of −5 °C. Cryo-electron backscatter diffraction analysis reveals a primary cluster of crystal c axes perpendicular to the shear plane in all samples, accompanied by a secondary cluster of c axes at an oblique angle to the primary cluster antithetic to the shear direction. With increasing strain, the primary c-axis cluster strengthens, while the secondary cluster weakens. The angle between the clusters remains within the range of 45° to 60°. The c-axis clusters are elongated perpendicular to the shear direction, with this elongation intensifying as strain increases. Subsequent annealing of the highest-strain sample reveals the same CPO patterns as observed prior to annealing, albeit slightly weaker. A synthesis of various experimental data suggest that the CPO pattern, including the orientation of the secondary cluster, results from a balance of two competing mechanisms: lattice rotation due to dislocation slip, which fortifies the primary cluster while rotating and weakening the secondary one, and grain growth by strain-induced GBM, which reinforces both clusters while rotating the secondary cluster in the opposite direction. As strain increases, GBM contributes progressively less. This investigation supports the previous hypothesis that a single cluster of c axes could be generated in high-strain experiments, while further refining our comprehension of CPO development in ice.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Status: closed
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RC1: 'Comment on egusphere-2024-331', Anonymous Referee #1, 10 Jul 2024
It was a pleasure reading and reviewing this manuscript. My detailed comments can be found in the Supplement, and I hope the authors find them helpful.
All the best
- AC1: 'Reply on RC1', Chao Qi, 30 Sep 2024
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RC2: 'Comment on egusphere-2024-331', Christopher Gerbi, 01 Sep 2024
This is a very valuable study to provide additional constraints on the crystallographic development of Ice Ih. As the authors note, the ice fabric plays a significant role in glacier and ice sheet mechanics, so being able to predict and explain fabric development provides a much stronger grounding for describing and modeling ice flow.
I particularly appreciate the authors explaining their experimental steps in such detail – it makes it easy for the reader to follow and understand the strengths of their approach. In addition, the primary conclusion of this study, namely the persistence of a secondary, albeit weak, c-axis cluster even at high shear strain, appears quite robust. I offer my suggestions below in the spirit of making the analysis more transparent, and thus easier to compare with other work.
1. Sensitivity. Line 175 and following suggest that all calculations related to the fabric use all orientation data. However, determining which pixels are labeled as ice vs graphite seems to have been a non-trivial exercise. Did the authors perform any sensitivity to evaluate how their processing algorithm may affect the final orientation or other datasets? As part of this, I would like to see an explanation of why the EDS and EBSD data were collected separately at different step sizes, as I would have thought that the hardware and software would allow for simultaneous collection.
2. With some work, I think I can understand which figures and interpretations rely on the 15um vs 30um step size EBSD data. At the same time, I think that could be more clearly explained in the text.
3. Number of data points. I may have missed it, but I didn't see a total of the number of datapoints used in the orientation data analysis. I suggest adding that value to perhaps Figure 7 or Table 1.
4. Line 219: when discussing stress, presumably you mean differential, deviatoric, or shear stress? Please clarify.
5. Line 257 refers to larger analysis areas used than presented in the paper. I would appreciate seeing the full maps (in appendix), as they help the reader evaluate heterogeneity. Similarly, for Figure 10, I would find it useful to indicate that the histograms and rose diagrams use larger datasets than shown if that is accurate.
6. For the reader to best appreciate the comparison of the experimental data with the modeled data, I suggest adding a section to Results to present the SpecCAF calculations. That way, the model results can stand somewhat independently for the later comparison.
7. Lines 182-3 and Figure 7d. It isn't clear to me how the data that lie off the profile line are used in the production of the histogram. Are all data projected onto the profile line? Or does the histogram include only a subset within a certain angular distance from the profile line? This may be explained in Qi et al. (2019), but a short review here (could also be in the appendix) would be helpful.
8. In a similar vein, how do the authors define the boundaries of the clusters to calculate the ratio plotted in Figure 8c?
9. Section 4.5. Another natural dataset for comparison is from the temperate Jarvis Glacier in Alaska [Gerbi C et al. (2021). Microstructures in a shear margin: Jarvis Glacier, Alaska. Journal of Glaciology 67(266), 1163–1176. https://doi.org/10.1017/jog.2021.62]. The results paint a different picture than the experimental results here, but the conditions are also quite different, thus providing some assessment of the applicability of the present work.
10. Line 435: The authors suggest that the changing intensity of orientations clusters may relate to the number of grains in particular orientations. Could it instead (or also) be that the sizes of the grains change such that instead of having fewer grains in low-Schmid-factor orientations, it is just that these grains are smaller? This comment is based on the presumption that the data presented are all pixels as suggested in Figure 7, rather than one-point-per-grain.
11. In the discussion, I suggest adding two subsections. One is for the limitations of these experiments: that is, under which natural conditions do the authors think these experiments apply? The second relates to rheological implications. The introduction opens with reference to the value of this work for rheology. I would find it quite valuable for the authors to reflect on how their work impacts the evolution of the mechanical properties of sheared ice.
Citation: https://doi.org/10.5194/egusphere-2024-331-RC2 - AC2: 'Reply on RC2', Chao Qi, 30 Sep 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-331', Anonymous Referee #1, 10 Jul 2024
It was a pleasure reading and reviewing this manuscript. My detailed comments can be found in the Supplement, and I hope the authors find them helpful.
All the best
- AC1: 'Reply on RC1', Chao Qi, 30 Sep 2024
-
RC2: 'Comment on egusphere-2024-331', Christopher Gerbi, 01 Sep 2024
This is a very valuable study to provide additional constraints on the crystallographic development of Ice Ih. As the authors note, the ice fabric plays a significant role in glacier and ice sheet mechanics, so being able to predict and explain fabric development provides a much stronger grounding for describing and modeling ice flow.
I particularly appreciate the authors explaining their experimental steps in such detail – it makes it easy for the reader to follow and understand the strengths of their approach. In addition, the primary conclusion of this study, namely the persistence of a secondary, albeit weak, c-axis cluster even at high shear strain, appears quite robust. I offer my suggestions below in the spirit of making the analysis more transparent, and thus easier to compare with other work.
1. Sensitivity. Line 175 and following suggest that all calculations related to the fabric use all orientation data. However, determining which pixels are labeled as ice vs graphite seems to have been a non-trivial exercise. Did the authors perform any sensitivity to evaluate how their processing algorithm may affect the final orientation or other datasets? As part of this, I would like to see an explanation of why the EDS and EBSD data were collected separately at different step sizes, as I would have thought that the hardware and software would allow for simultaneous collection.
2. With some work, I think I can understand which figures and interpretations rely on the 15um vs 30um step size EBSD data. At the same time, I think that could be more clearly explained in the text.
3. Number of data points. I may have missed it, but I didn't see a total of the number of datapoints used in the orientation data analysis. I suggest adding that value to perhaps Figure 7 or Table 1.
4. Line 219: when discussing stress, presumably you mean differential, deviatoric, or shear stress? Please clarify.
5. Line 257 refers to larger analysis areas used than presented in the paper. I would appreciate seeing the full maps (in appendix), as they help the reader evaluate heterogeneity. Similarly, for Figure 10, I would find it useful to indicate that the histograms and rose diagrams use larger datasets than shown if that is accurate.
6. For the reader to best appreciate the comparison of the experimental data with the modeled data, I suggest adding a section to Results to present the SpecCAF calculations. That way, the model results can stand somewhat independently for the later comparison.
7. Lines 182-3 and Figure 7d. It isn't clear to me how the data that lie off the profile line are used in the production of the histogram. Are all data projected onto the profile line? Or does the histogram include only a subset within a certain angular distance from the profile line? This may be explained in Qi et al. (2019), but a short review here (could also be in the appendix) would be helpful.
8. In a similar vein, how do the authors define the boundaries of the clusters to calculate the ratio plotted in Figure 8c?
9. Section 4.5. Another natural dataset for comparison is from the temperate Jarvis Glacier in Alaska [Gerbi C et al. (2021). Microstructures in a shear margin: Jarvis Glacier, Alaska. Journal of Glaciology 67(266), 1163–1176. https://doi.org/10.1017/jog.2021.62]. The results paint a different picture than the experimental results here, but the conditions are also quite different, thus providing some assessment of the applicability of the present work.
10. Line 435: The authors suggest that the changing intensity of orientations clusters may relate to the number of grains in particular orientations. Could it instead (or also) be that the sizes of the grains change such that instead of having fewer grains in low-Schmid-factor orientations, it is just that these grains are smaller? This comment is based on the presumption that the data presented are all pixels as suggested in Figure 7, rather than one-point-per-grain.
11. In the discussion, I suggest adding two subsections. One is for the limitations of these experiments: that is, under which natural conditions do the authors think these experiments apply? The second relates to rheological implications. The introduction opens with reference to the value of this work for rheology. I would find it quite valuable for the authors to reflect on how their work impacts the evolution of the mechanical properties of sheared ice.
Citation: https://doi.org/10.5194/egusphere-2024-331-RC2 - AC2: 'Reply on RC2', Chao Qi, 30 Sep 2024
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Qinyu Wang
Sheng Fan
Daniel H. Richards
Rachel Worthington
David J. Prior
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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