A model for determining the cyclic swell–shrink behavior of argillaceous rock

Doostmohammadi, R.; Moosavi, M.; Araabi, Babak Nadjar

doi:10.1016/j.clay.2007.11.008

Cited by 14 publications

(5 citation statements)

References 18 publications

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“…At present, expansive rocks are divided into two categories [13][14][15][16][17][18]: the first one is caused by chemical expansion reaction, the mechanism is complex, and the time is long (such as anhydrite and glauberite); the second one is caused by hydrophilic minerals, and the expansion of this type of rock is cyclically reciprocated under the action of water absorption and loss (such as mudstone and tuff) [19]. The main indicators for judging the expansion potential of expansive rocks include water content [20][21][22], viscous material content [9,15,[23][24][25], free expansion rate [25], ultimate expansion rate [26], dry saturated water absorption rate [27], and ultimate expansion force [9,25].…”

Section: Introductionmentioning

confidence: 99%

Study on Expansion Characteristics and Expansion Potential of Gypsum Rock

Zhu

et al. 2022

Geofluids

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In this study, the relationship between four expansion indices and the expansion potential of gypsum rock was studied; on this basis, a criterion for judging expansion potential is established for gypsum rock. The results show that the free expansion rate is unsuitable for grading gypsum rocks’ expansion potential. Setting the gypsum rock in the Wuzhishan tunnel as the research subject, the ultimate expansion rate is 24.28% on the 7th day and 34.08% on the 30th day; the ultimate expansion rate on the 7th day of the indoor rock sample can be estimated by the fitting formula on the 30th day, the ultimate expansion force is 304.51 kPa, and the BET-specific surface area is 6.31 m2/g. The ultimate expansion ratio and BET-specific surface area have an excellent linear relationship with the ultimate expansion force. Setting the ultimate expansion force, ultimate expansion ratio and BET-specific surface area as the standard, the criterion for judging the expansion potential of gypsum rock is determined, which is more convenient and accurate than existing standards. The standard in this paper can predict the potential disasters that may occur in underground engineering.

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Section: Introductionmentioning

confidence: 99%

Study on Expansion Characteristics and Expansion Potential of Gypsum Rock

Zhu

et al. 2022

Geofluids

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“…The recorded nonlinear behavior of the mudrock is modeled using an artificial neural network (ANN). Using this method facilitates the prediction of the swelling pressure of the argillaceous rocks with different swelling potentials and site conditions [13]. An artificial neural network is used to predict the surface subsidence caused by coal mining [14].…”

Section: Introductionmentioning

confidence: 99%

Prediction of the First Weighting from the Working Face Roof in a Coal Mine Based on a GA-BP Neural Network

et al. 2019

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The accidents caused by roof pressure seriously restrict the improvement of mines and threaten production safety. At present, most coal mine pressure forecasting methods still rely on expert experience and engineering analogies. Artificial neural network prediction technology has been widely used in coal mines. This new approach can predict the surface pressure on the roof, which is of great significance in coal mine production safety. In this paper, the mining pressure mechanism of coal seam roofs is summarized and studied, and 60 sets of initial pressure data from multiple working surfaces in the Datong mining area are collected for gray correlation analysis. Finally, 12 parameters are selected as the input parameters of the model. Suitable back propagation (BP) and GA(genetic algorithm)-BP initial roof pressure prediction models are established for the Datong mining area and trained with MATLAB programming. By comparing the training results, we found that the optimized GA-BP model has a larger determination coefficient, smaller error, and greater stability. The research shows that the prediction method based on the GA-BP neural network model is relatively reliable and has broad engineering application prospects as an auxiliary decision-making tool for coal mine production safety.

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“…Wong and Wang [7] constructed a threedimensional mathematical model to simulate the expansion of argillaceous rock by considering the three elements of mineral particle expansion, fabric, and stress-induced anisotropy. Some researchers discussed the influence of strain change and number of dry and wet cycles on expansive force based on the expansion test of argillaceous rock [8][9][10]. From the perspective of energy, the energy transfer and energy dissipation model of the process of soft rockfall was established through quantitative characterization of the process [11].…”

Section: Introductionmentioning

confidence: 99%

Research on the Disintegration Characteristics of Carbonaceous Mudstone and Properties of Modified Materials

Xin-xi

et al. 2019

Advances in Civil Engineering

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This work presents the results of an experimental investigation aimed to study the disintegration of carbonaceous mudstone and properties of modified materials. The mineralogical composition of carbonaceous mudstone was determined with X-ray diffraction. The microscopic characteristics of carbonaceous mudstone disintegration were determined with scanning electron microscopy. The surface modification effect of carbonaceous mudstone was researched by comparative tests on coatings’ hydrophobic property, fastness, and waterproof before and after modification, and the modification mechanism of polymer-cement composite modified carbonaceous mudstone was analyzed. The results show that the mineral composition of carbonaceous mudstone mainly contains illite, quartz, and kaolinite. It is found that the disintegration of carbonaceous mudstone can be divided into external factors and internal factors. External factors are water and temperature difference, and internal factors are the swelling of the kaolinite and illite mineral particles. There are differences in the modification effects under different cement dosage. When the cement dosage is 30%, the modification effect is the best. The results may provide a reference for the prevention and control of soft rock slopes.

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A model for determining the cyclic swell–shrink behavior of argillaceous rock

Cited by 14 publications

References 18 publications

Study on Expansion Characteristics and Expansion Potential of Gypsum Rock

Study on Expansion Characteristics and Expansion Potential of Gypsum Rock

Prediction of the First Weighting from the Working Face Roof in a Coal Mine Based on a GA-BP Neural Network

Research on the Disintegration Characteristics of Carbonaceous Mudstone and Properties of Modified Materials

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