CSAR

Predictions of physical processes are simply not possible without reliable material parameters. As engineers, we study snow like an engineering material and recognize that even basic properties have hardly been precisely measured. For example, knowledge of fracture properties is essential in order to predict crack growth. Moreover, we lack knowledge of strength, especially in the interaction between normal and shear stresses, which are relevant in inclined terrain. We develop, model, verify, and validate field experiments to determine such parameters. We accompany these processes from the determination of material parameters to their use in modeling and their practical application for hazard assessment in the field.

Engineers are trained to solve complex physical problems analytically using mathematical models. We have found that numerical methods are not essential to accurately describe the deformations of a snowpack. The combination of simple, fundamental mechanical models with modern theories of fracture mechanics provides fast and efficient forecasting tools. Our aim is to describe even the complex microstructure of snow on the basis of simple models. The investigation of material and structural properties on this scale enables an understanding ofthe macroscopic material behavior. Analytical solutions enrich snow research, which can quickly become very complex. They enable evaluation in real time, which is crucial for practical applications.

The Weak-Layer Anticrack Nucleation Tool (WEAC) is an open-source, closed-form analytical model designed for the mechanical analysis of dry-snow slabs on compliant weak layers. It enables the prediction of anticrack onset, and, in particular, allows for the analysis of stratified snow covers. Moreover, it can be applied for the assessment and design of field experiments. Contribute on Github or install the Python package.