3D-modelling of experimental percussive-abrasive stone tools: opportunities and limitation

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In this study, we present the results of experimental modelling for processing the mineral and organic raw materials through knapping, retouching and grinding using active and passive percussive-abrasive tools. All obtained standards were subjected to three-dimensional modelling by the RangeVision Spectrum structured illumination scanner before and after the experiments. During the research at the post-processing stage, we corrected all model errors and prepared illustrations of tool profiles and their working surfaces, including the construction of grid curvature maps. Based on the results of the work, we identified the possibilities and limitations in the use of three-dimensional visualization methods in the study of the experimental collection. As part of the experimental study of percussive-abrasive stone tools, it is advisable to use 3D-modelling to study the dynamics and main damage mechanics, since the visualization of the data with the ability to measure morphometric characteristics provides detailed results on the change in the appearance of the artefact and its working surface. These advantages are typical only for tools with damage visible at the macro level. For instruments for abrasive treatment, 3D-visualization can be useful to reflect the morphometric characteristics of the original workpiece. This method is effective in the analysis of use-wear traces observed at the macro level when damages that are recorded only at the micro level are poorly distinguishable on the resulting models. In total, percussive-abrasive stone tools seem to be a promising source for studying by 3D-visualization methods. Its use makes it possible to display visible changes in the relief with high accuracy, providing an opportunity to create an evidence base for the functional analysis of the studied instruments and their identification.

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Gorny altai, middle palaeolithic, upper palaeolithic, percussive-abrasive stone tools, 3d-modelling, experimental modelling, functional analysis

Короткий адрес: https://sciup.org/145146343

IDR: 145146343   |   DOI: 10.17746/2658-6193.2022.28.0298-0304

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