Characterization of geo-material parameters: Gene concept and big data approach in geotechnical engineering

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Abstract

Due to their inherent natural properties, the basic physio-mechanical properties of geo-materials generally exhibit varying degrees of spatial variability. Therefore, describing and characterizing the global traits of geo-materials based on very limited analytical data pose a great challenge. Furthermore, the differences of their characteristics significantly impact the determination of geotechnical engineering stability as well as the relevant engineering design results. With a view to resolve this issue, in this study, we apply the concept of “Gene” from biology, and propose a novel approach to describe the “genetic” characteristics of geo-materials based on general attributes of the specific rock (soil) materials belongings to a certain region or zone. We propose the definition of genetic characteristics as well as the basic attributes in this paper. Our study provides the methodology of utilizing the big data theory to statistically analyze the geo-material parametric data identified in the previous projects and the framework for search of the genetic characteristics. We also developed a software system for big data management and analysis of genetic characteristics of geo-materials, which can fulfill the tasks of collecting, transmitting, classifying, screening, managing and analyzing the big data. Based on more than 80,000 sets of standard geo-material physio-mechanical data from a representative region, the genetic features of typical geo-materials are analyzed to obtain the corresponding gene maps. The findings from this study offer a reliable guidance for the determination of geo-material parameters, data support for engineering construction, and potential application in the mitigation of natural disasters.

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Liu, D., Liu, H., Wu, Y., Zhang, W., Wang, Y., & Santosh, M. (2022). Characterization of geo-material parameters: Gene concept and big data approach in geotechnical engineering. Geosystems and Geoenvironment, 1(1). https://doi.org/10.1016/j.geogeo.2021.09.003

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