journal article·2023-12

Modeling diameter of jet grouting columns using Bayesian framework

Lin‐Shuang Zhao, Yue Chen, Yanning Wang

Publisher page

Abstract

Abstract This study proposes a new model in explicit form to predict the diameter of the jet grouting column of three popular jet grouting systems (i.e., single, double, and triple). The proposed model can quantify the uncertainty associated with the prediction. Bayesian model selection was used to determine the optimal models and, the bootstrap sampling method was adopted to avoid bias in the collected database. The predictions agree well with the measured data, and the 95% credible intervals can cover almost all the measured data on the testing dataset, which indicates the robustness of the proposed model. A simple formula combined with a table was established to facilitate the engineers in applying the proposed model. The results reveal that soil type has a significant impact on diameter prediction. Uncertainty quantification can reveal possible fluctuations in column diameter and is vital to get a cost‐efficient design.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Grouting, Rheology, and Soil Mechanics · Geotechnical Engineering and Analysis · Geotechnical Engineering and Underground Structures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

MOE Key Laboratory of Intelligence Manufacturing Technology Department of Civil and Environmental Engineering College of Engineering Shantou University Shantou Guangdong China

Central Research Institute of Building and Construction (Shenzhen) Co., Ltd, MCC Group Shenzhen Guangdong China

Funding

National Natural Science Foundation of China

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