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http://dx.doi.org/10.5804/LHIJ.2021.12.3.109

Investigation on the Key Parameters for the Strengthening Behavior of Biopolymer-based Soil Treatment (BPST) Technology  

Lee, Hae-Jin (아주대학교 건설시스템공학과)
Cho, Gye-Chum (한국과학기술원 건설환경공학과)
Chang, Ilhan (아주대학교 건설시스템공학과)
Publication Information
Land and Housing Review / v.12, no.3, 2021 , pp. 109-119 More about this Journal
Abstract
Global warming caused by greenhouse gas emissions has rapidly increased abnormal climate events and geotechnical engineering hazards in terms of their size and frequency accordingly. Biopolymer-based soil treatment (BPST) in geotechnical engineering has been implemented in recent years as an alternative to reducing carbon footprint. Furthermore, thermo-gelating biopolymers, including agar gum, gellan gum, and xanthan gum, are known to strengthen soils noticeably. However, an explicitly detailed evaluation of the correlation between the factors, that have a significant influence on the strengthening behavior of BPST, has not been explored yet. In this study, machine learning regression analysis was performed using the UCS (unconfined compressive strength) data for BPST tested in the laboratory to evaluate the factors influencing the strengthening behavior of gellan gum-treated soil mixtures. General linear regression, Ridge, and Lasso were used as linear regression methods; the key factors influencing the behavior of BPST were determined by RMSE (root mean squared error) and regression coefficient values. The results of the analysis showed that the concentration of biopolymer and the content of clay have the most significant influence on the strength of BPST.
Keywords
Biopolymer; BPST; Machine Learning; Linear Regression; Soil Strengthening;
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