多因素影响下高拱坝施工过程自适应仿真与动态控制研究

The key scientific problem demanding prompt solution which exists in the construction process of high arch dam is how to realize adaptive simulation and dynamic control on construction progress under multi-factor coupling. Firstly, a variety of information collection technology is integrated through analyzing various factors influencing the high arch dam construction schedule. The integration and mining method of multi-source heterogeneous information of construction schedule is put forward. Secondly, based on Bayesian theory and self-learning mechanism, the construction simulation parameters and simulation logic are dynamically updated, and the dynamic adaptive construction simulation modeling and analysis method is put forward. Thirdly, the risk analysis method of high arch dam construction schedule based on Monte Carlo simulation and adaptive simulation technology is put forward. Considering the risk probability and simulation results, the dynamic warning mathematical model of high arch dam construction progress is established. Finally, the construction schedule dynamic control system of high arch dam under network environment is built, which can dynamically manage the dam construction schedule information, simulation and schedule early-warning, and provides a supportive platform for dam construction schedule dynamic control. This research will make up the shortage of failure to dynamic accurate prediction of high arch dam construction schedule under multi-factor coupling. It will also solve the basic scientific problems when applying the control on progress for high arch dam construction, and provide theoretic and technical support for high arc dam construction with high standard. This project has important theoretical significance, as well as strong engineering application value.

针对高拱坝工程建设中亟待解决的关键科学问题：多因素耦合作用下的大坝施工过程自适应仿真与动态控制。本研究通过系统分析影响高拱坝施工进度的各种内外部复杂因素，综合多种信息采集技术，提出施工进度多源异构信息融合集成与挖掘方法；基于贝叶斯理论和自学习机制对高拱坝施工仿真参数与仿真逻辑进行动态更新，提出高拱坝施工过程自适应仿真建模与分析方法；提出基于蒙特卡罗模拟-自适应仿真技术的高拱坝施工进度风险分析方法，综合考虑风险概率与仿真结果，建立高拱坝施工进度动态预警数学模型；构建网络环境下的高拱坝施工进度动态控制系统，对大坝施工进度多源信息、仿真分析以及进度预警等进行动态集成管理，为大坝施工进度动态控制提供支撑平台。本研究弥补了多因素耦合作用下难以动态精确预测高拱坝施工进度的不足，解决了高拱坝施工进度控制中的应用基础科学问题，为大坝的高标准建设提供了理论与技术支持，具有重要的理论意义及工程应用价值。

本项目针对高拱坝工程建设中的多因素耦合作用下的大坝施工过程自适应仿真与动态控制关键科学问题，开展了深入的理论方法、关键技术与工程应用研究，取得了重要的创新性研究成果。本研究通过系统分析影响高拱坝施工进度的各种内外部复杂因素，综合集成多种信息采集技术，提出了施工进度多源信息融合集成与挖掘方法；提出了基于贝叶斯更新理论的高拱坝施工过程自适应仿真方法，使仿真模型的参数及逻辑更加真实可靠，实现了高拱坝施工过程自适应仿真分析与优化，为大坝施工进度动态控制与决策提供了科学依据；提出了基于正交试验的高拱坝施工仿真参数全局综合敏感性分析方法以及基于粒子群算法的高拱坝仓面排序多目标优化方法，可以实现对大坝施工进度的动态预警分析与优化控制，为现场高拱坝施工进度科学动态控制与管理提供了理论基础与技术支持；结合国内大岗山实际高拱坝工程，构建了网络环境下的高拱坝施工进度动态控制系统，对大坝施工过程进度信息、仿真分析以及进度预警等进行动态集成管理，为大坝施工进度动态控制提供了支撑平台。研究成果共发表标注基金号的高水平学术论文6篇，其中SCI/EI检索4篇；获得省部级科技奖励2项，申请发明专利3项。本项目共培养了博士研究生2名，硕士研究生2名。