Accurate inversion of high-resolution snow penetrometer signalsfor microstructural and micromechanical properties

摘要

Measurements of snow using a high-resolution micropenetrometer can be used todiscriminate between different snow types; in lower-density snow the signal is sensitive tomicrostructure, and micromechanical properties can be estimated. Although aphysics-based snow penetration theory was first developed almost a decade ago, since thattime the majority of studies using snow micropenetrometers have focused on using directhardness measurements in statistical relationships. We use Monte-Carlo simulations torigorously test the existing physics-based snow micropenetration theories over a widerange of parameters. These tests revealed four major sources of error in the inversion,which are corrected in this analysis. It is shown that this improved inversion algorithm canrecover micromechanical parameters in synthetic data with much greater accuracy overthe entire range of micromechanical properties observed in natural snow. Detailedexamples of the inversion results are shown for eight different snow types, collected inboth Alaskan and alpine snowpacks. The resulting micromechanical properties aredistinctly different, indicating that a snow characterization from snow micropenetrometerestimates of micromechanical properties is likely possible. Estimates of the microscaleelastic modulus, microscale strength, and structural element length make sense physicallywhen compared to the qualitative descriptions of the different snow types. Microscalestrength estimates are used to estimate macroscale strength values, and results from33 different snow samples, covering a wide range of densities and snow types, areconsistent with previously reported values from macroscale tests.