Volume 41 Issue 3
May  2022
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Chen Feiyu, Dong Lifei, Wang Miao, Wang Fanshun. Prediction of foundation bearing capacity based on grey Markov model[J]. Bulletin of Geological Science and Technology, 2022, 41(3): 222-227. doi: 10.19509/j.cnki.dzkq.2022.0073
Citation: Chen Feiyu, Dong Lifei, Wang Miao, Wang Fanshun. Prediction of foundation bearing capacity based on grey Markov model[J]. Bulletin of Geological Science and Technology, 2022, 41(3): 222-227. doi: 10.19509/j.cnki.dzkq.2022.0073

Prediction of foundation bearing capacity based on grey Markov model

doi: 10.19509/j.cnki.dzkq.2022.0073
  • Received Date: 20 Jun 2021
  • Foundation is the foundation of engineering construction, and its bearing capacity calculation and prediction are very critical indetermining the safety and stability of the superstructure of the building project. To realize the foundation bearing capacity prediction with small data volume, short period, and higher accuracy, this paper establishes the gray Markov prediction model to predict the foundation settlement under the action of fixed load and clarify the base bearing capacity, based on the foundation static load test data, the gray model for calculation, and Markov optimization. Meanwhile, the model is compared with the traditional gray GM(1, 1) model and exponential curve fitting model to analyze the advantages and disadvantages of the three models. The results show that in case one, the bearing capacity of the foundation underthe static load test is intact, and the average relative errors between the predicted and measured values of the gray Markov model, GM(1, 1) model, and exponential curve model are 1.55%, 3.80% and 10.22% in order, and the gray Markov model has the highest accuracy and fits the static load test of the foundation better, which can clarify the bearing capacity of the foundation accurately and effectively; in case two, the foundation The average relative error between the predicted and measured values of the gray Markov model before the damage occurred under the static load test was only 0.5%, and the prediction effect was good. When the damage occurred, the settlement of the foundation increased rapidly, and the relative error between the predicted and measured values of the model at the loading point was abnormal and increased to 26.29%, so that the load of the loading sequence at the first level before the damage could be judged as the ultimate bearing capacity of the foundation. Using this model to guide the foundation static load test, the number of static load tests can be appropriately reduced at adjacent test points under the premise of ensuring construction safety, saving the construction cost of the project, and providing a new calculation tool for the information foundation static load test.

     

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