Microstructure Characterization of Bubbles in Gassy Soil Based on the Fractal Theory

The microscopic characterization of isolated bubbles in gassy soil plays an important role in the macroscopic physical properties of sediments and is a key factor in the study of geological hazards in gas-bearing strata.Based on the box-counting method and the pore fractal features in porous media,a fractal model of bubble microstructure parameters in gassy soil under different gas con-tents and vertical load conditions is established by using an industrial X-ray CT scanning system.The results show that the fractal di-mension of bubbles in the sample is correlated with the volume fraction of bubbles,and it is also restricted by the vertical load.The three-dimensional fractal dimension of the sample is about 1 larger than the average two-dimensional fractal dimension of all the slices from the same sample.The uniform porous media fractal model is used to test the equivalent diameter,and the results show that the variation of the measured pore diameter ratio is jointly restricted by the volume fraction and the vertical load.In addition,the measured self-similarity interval of the bubble area distribution is tested by the porous media fractal capillary bundle model,and the fitting curve of measured pore area ratio in a small loading range is obtained in this paper.

Optimization of the Number and Location of Boreholes for Gassy Soil Site Investigation Considering the Statistical Uncertainty

The research addresses the prevalence of gassy soil, containing methane (CH4), within the soil particles of southeast coastal areas of China, such as the Quaternary deposit in the Hangzhou Bay area. This soil exhibits spatial variability in the distribution of gas pressure, posing a potential threat of engineering disasters, including fire outbreaks and blasting, during the construction of underground projects. Consequently, it is crucial to assess the risk state of gas pressure, involving accurate identification and reduction of associated uncertainty, through site investigation. This is indispensable prior to the commencement of underground projects. However, during the site investigation stage, the random field parameters that quantify the spatial variability distribution of gas pressure (e.g., mean value, standard deviations, and scale of fluctuation) are unknown, introducing corresponding statistical uncertainty. Therefore, the most significant consideration for planning site investigation from an engineering perspective involves determining the risk state of gas pressure while considering the statistical uncertainty of these random field parameters. This consideration heavily relies on the engineering experience gained from current site investigation practices. To address this challenge, the study introduces a probabilistic site investigation optimization method designed for planning the site investigation scheme for gassy soils, including determining the number and locations of boreholes. The method is based on the expected state-identification probability, representing the probability of identifying the risk state of gas pressure, and takes into account the statistical uncertainty of random field parameters. The proposed method aims to determine an optimal investigation scheme before conducting the site investigation, leveraging prior knowledge. This optimal scheme is identified using Subset Simulation Optimization (SSO) in the space of candidate site investigations, maximizing the value of the expected state-identification probability at the minimal value point. Finally, the paper illustrates the proposed approach through a case study.