| 基于灰色马尔科夫模型的地基承载力预测 |
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| 引用本文： | 陈飞宇,董利飞,王苗,王凡顺.基于灰色马尔科夫模型的地基承载力预测[J].地质科技通报,2022,41(3):222-227. |
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| 作者姓名： | 陈飞宇 董利飞 王苗 王凡顺 |
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| 基金项目： | 重庆市“三峡水库岸坡与工程结构灾变防控工程技术研究中心”开放基金项目SXAPGC18YB04重庆市“三峡水库岸坡与工程结构灾变防控工程技术研究中心”开放基金项目SXAPGC21MS04重庆三峡学院校级青年项目19QN10重庆三峡学院土木水利硕士研究生开放基金TMSL20YB18重庆三峡学院研究生科研创新项目YJSKY21020 |
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| 摘 要： | 地基是工程建设的基础，其承载力计算和预测十分关键，决定着建筑工程上部结构的安全性与稳定性。为实现小数据量、短周期、较高精度的地基承载力预测。本研究提出以地基静载试验数据为依据，利用灰色模型进行计算，结合马尔科夫优化，建立灰色马尔科夫预测模型，预测固定荷载作用下的地基沉降，进而明确相应沉降下的基地承载力。同时，将该模型与传统的灰色GM(1, 1)模型、指数曲线拟合模型进行对比，分析3种模型的优劣。结果表明，案例一中，静载试验下的地基承载能力完好，灰色马尔科夫模型、GM(1, 1)模型、指数曲线模型预测值与实测值的平均相对误差依次为1.55%，3.80%，10.22%，灰色马尔科夫模型精度最高，更契合地基静载试验，能准确有效地明确地基承载力；案例二中，地基在静载试验下发生破坏，破坏前灰色马尔科夫模型预测值与实测值的平均相对误差仅为0.5%，预测效果良好。破坏时，地基沉降迅速增加，加载点模型预测值与实测值的相对误差出现异常，骤增至26.29%，以此可判断破坏前一级加载序列荷载为该地基的极限承载力。运用此模型指导地基静载试验，在保障工程施工安全的前提下，相邻试验点可以适当减少静载试验次数，节约工程施工成本，为信息化地基静载试验提供一个新的计算工具。
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| 关 键 词： | 地基承载力 灰色马尔科夫模型 灰色GM(1 1)模型 预测 |
| 收稿时间： | 2021-06-20 |
Prediction of foundation bearing capacity based on grey Markov model |
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| Abstract: | 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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