基于机器学习的堆组基础垂直承载能力的快速评估方法
Yanmei Cao1, Jiangchuan Ni1, Jianguo Chen2
1School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
一种新的机器学习方法快速评估桥梁基承载能力. 这种方法使用经过验证的3D模型来预测刚度比,使现有桥梁基础的快速,非破坏性评估成为可能.
科学领域:
- 土木工程 土木工程是指土木工程.
- 地质技术工程 地质技术工程
- 机器学习应用 机器学习应用
背景情况:
- 随着桥梁寿命的延长,需要有效的方法来评估现有的基.
- 传统的静态负载测试来确定垂直承载能力是昂贵和耗时的.
- 对桥梁基进行快速,非破坏性评估技术的需求存在.
研究的目的:
- 开发一种快速评估现有桥梁基垂直承载能力的方法.
- 建立一个可靠的数值模型来模拟堆基础负载测试.
- 利用机器学习来根据动态和静态响应预测轴承能力.
主要方法:
- 开发了一个3D数值模型,模拟在静态和动态负载下堆群与土壤的相互作用.
- 数值结果与现场动态和静态负载测试在废弃的桥梁码头进行了验证.
- 机器学习数据集是从数值模拟中构建的,用于预测建模.
主要成果:
- 3D数值模型准确地模拟了堆基础上的静态和动态负载测试.
- 机器学习模型成功预测了静态和动态刚度的比率.
- 该方法可以快速评估堆基础的剩余和最终承载能力.
结论:
- 开发的数值模型提供了有效的模拟,用于负载下堆基础的行为.
- 机器学习提供了一个强大的工具,用于快速,非破坏性评估桥梁基础.
- 这种方法有助于对老化的桥梁基础设施进行高效的维护和安全评估.
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