Abstract
The randomized method of Sign-Perturbed Sums (SPS) is applied within the framework of the incubation time approach to evaluate the dynamic strength of ice. The experimental data of [Carney et al., 2006; Wu and Prakash, 2015; Saletti et al., 2019] is analysed in order to estimate strength parameters of ice and describe the observed strain-rate sensitivity curves. The independence of incubation time value on the ice temperature is established in contrast with the significant dependency of the critical stress parameter. The obtained confidence interval of the spalled ice is in good correspondence with the scatter observed experimentally.
Highlights
Estimation of materials strength properties is an important daily task of modern industry
These data were analysed by the developed method, and confidence intervals were obtained for each temperature
All confidence intervals seem to be close to each other; it can indicate that the dynamic strength of the materials almost does not change with the temperature drop and the actual value of τ ∈ [7.3; 13.7]μs The data for all temperatures were plotted in the single graph of the dimensionless strength versus strain rate (Figure 2) in order to emphasise that the strain rate sensitivity is stable concerning the ice temperature
Summary
Estimation of materials strength properties is an important daily task of modern industry. The yield deformation is typical to quasi-static loading, whereas the brittle fracture prevails under high rate intensive impacts [Schulson, 2001; Schulson and Buck, 1995] This peculiarity of internal ice structure can be the reason that. The material strength in dynamics is stipulated by this parameter This method has recommended itself as an effective tool for the solution of different problems related to prediction ultimate stress level under intensive high-rate loading[Petrov, 2004; Volkov et al, 2021]. Model function φ(τ, εi) is should be determined by the structural temporal approach It should be noted, that the number of dynamic tests N often is not large enough to apply conventional statistical analysis in order to consider the noise influence. The randomized method of Sign-Perturbed Sums is chosen as a basic tool for this problem
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