the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Sep 2025
Brief Communication: Hypergravity Testing of Thawing Rates in Frozen Sand
Abstract. The active layer above permafrost experiencing seasonal freeze-thaw can range from a few centimeters to tens of meters in thickness, which complicates physical modeling of this phenomenon. This study shows capabilities developed to investigate freeze-thaw in a hypergravity environment that will enable system-level experiments which tie model predictions of permafrost behavior to field observations of permafrost temperature cycling. By leveraging scaling in a hypergravity setting, this research will allow for permafrost layers to be generated on a prototype scale that capture the full thickness of the active layer on the order of tens of meters. We present preliminary results showing requirements and techniques for sample preparation, insulation, and feasible experiment run times in a 1-m radius centrifuge.
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Status: open (until 26 Nov 2025)
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RC1: 'Comment on egusphere-2025-2965', Anonymous Referee #1, 31 Oct 2025
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AC1: 'Reply on RC1', Michael Gardner, 08 Nov 2025
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Thank you for this comment. We fully acknowledge and agree with the reviewer's comment that this comparison should be based on sensors at similar locations to make valid comparisons. We have included an updated Figure 6 that compares sensors at the same locations. In the original comparison in Figure 6, the dense sample sensors at the top and center (RTD 21 and 20, respectively) were deeper compared to RTD 21 and 20 in the loose sample. This showed slower temperature changes in the dense sample compared to the loose sample. In the updated Figure 6, sensors at the same locations are compared (RTD 10 for the dense vs RTD 21 in the loose, and RTD 9 for the dense vs RTD 20 for the loose, location of RTD 18 is the same between tests). As shown in the updated Figure 6, this trend still holds and the discussion of soil density effects remains valid.
Similarly, Figure 4b was updated to show RTDs 10, 9, and 18 from the dense sample to compare thawing rates with those shown for the loose sample in Figure 4a. In this updated comparison, all sensors are at similar locations to make comparisons valid. The trends observed remain consistent with what was observed previously where the uninsulated samples show faster thawing from both the bottom and top of the sample, while the insulated case shows a 1-D thawing profile from the top downward. However, since the RTDs 10 and 9 are relatively closer to the surface of the dense sample compared to RTDs 20 and 21 (which were plotted in the previous Figure 4b), the timing of thawing in the updated Figure 4b occurs earlier.
As to why there were different numbers of sensors between the loose and dense samples, this is related to the number of signal conditioners that were available at the time when tests were conducted. We only had 4 signal conditioners available for the loose test, so we decided to place the RTDs in such a way that we could capture the temperature behavior near the boundaries and center of the sample. When the dense tests were conducted, we had procured additional signal conditioners so that we could get a broader spatial resolution of the time-varying temperatures within the sample. However, we did make sure to place sensors in similar locations compared to the loose tests so that we could have direct comparison between the dense and loose tests.
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AC1: 'Reply on RC1', Michael Gardner, 08 Nov 2025
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Hypergravity Testing of Thawing Rates in Frozen Sand M. Gardner et al. https://doi.org/10.17603/ds2-mwar-sp11
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The number and elevation of sensors in dense and loose sand samples are inconsistent. For valid comparison, sensors should be placed at the same elevations and in equal numbers across both sample types. Please clarify the rationale for the current setup.
In Figure 6, direct comparisons are made between samples with different sensor positions, which can affect the validity of the results. It is recommended to justify this approach clearly, or revise the figure and analysis to focus on results from consistent sensor locations, discussing the potential impacts of any inconsistencies.