论智能设计系统的开发

本文结合作者在拱坝分析,拱坝优化设计和拱坝智能设计系统方面的研究工作,简述了智能在设计系统中的体现以及智能设计系统的必要性和系统的合理组成部分,探讨了智能设计系统的开发策略。     

心形线双曲拱坝三维建模

心形线作为几何数学上最美最浪漫的一条曲线,第一次在拱坝设计中研 究应用。在研究心形线几何特性时,发现有一段非常扁平的曲线,作为拱坝中轴线非常适合, 可以使得拱坝的合力方向向山里偏转,有利于坝肩的稳定。因此,研究心形线作为拱坝的一 种新线形,理论上具有可行性,并在实际工程中有一定的应用参考价值。该文在研究心形线 双曲拱坝各种参数的基础上,建立心形线双曲拱坝的数学方程,实现图形的三维建模,为拱 坝下一步进行有限元分析提供精确的三维模型,也为今后拱坝坝型的设计提供更多的选择和 有意义的参考。     

计算机模拟拱坝施工中工程量预算方法研究

所述算法建立在对拱坝进行了有限元网格剖分与计算已获得施工数据的基础上 ,提出了对将建拱坝工程量预算较为合理的计算方法 ,并用 C语言编程实现 ,经测试验证后 ,结果正确 ,符合工程要求 ,可将其应用于拱坝施工全过程 ,势必带动水电工程生产自动化 ,产生巨大经济效益     

拱坝的计算机辅助立模施工

本文讨论了拱坝计算机辅助立模施工系统的设计,及其数据库结构,并介绍了系统实例——东风双曲拱坝计算机辅助立模施工系统。     

基于增强现实的智能建造虚拟仿真实验教学系统

针对当前高拱坝施工可视化效果差，导致无法对施工质量和施工进度进行有效管理的问题，提出基于增强现实技术实现高拱坝仓面施工智能建造和仿真模拟。首先，根据高拱坝仓面施工的工序关系，通过增强现实技术对高拱坝仓面施工进行可视化仿真流程构建和数学模型构建；然后计算出仓面的工序历时；最后根据施工机械工作位置和坐标进行仓面施工仿真。工程应用表明，基于增强现实的仿真模型对仓面1施工的实际历时为24.73 h,低于标准平均值为26.38 h,置信度控制在95%以内，由此说明该模型对仓面施工的计算结果准确较高，可准确反映仓面实际施工情况。仿真验证发现，提出的方法可实现高拱坝施工进度的精细仿真，很大程度上提高了可视化效果，施工管理人员可根据虚拟仿真模型结合现场实际情况对施工进度和施工质量进行分析管理，可提升高拱坝整体施工效果。     

统一二次曲线拱坝有限元建模系统设计与实现

为评价拱坝安全,运用设计模式原理,开发统一二次曲线拱坝有限元自动化建模与图形显示系统.拱坝三维模型与有限元网格均采用参数化方法自动生成.将工厂模式、策略模式和外观模式等设计模式应用到系统开发中,并针对通用有限元软件开发提出2种新的设计模式:几何-网格分离模式、嵌入单元.通过设计模式的应用使系统的可复用性、可维护性和可扩...     

大型拱坝多维变形自动观测方法研究

讨论了一种针对大型拱坝多维变形的自动观测方法。该方法沿折线布置多个测点，采用激光与PSD传感技术，实现对线位移和角位移的测量，获得每个测点的多维变形数据。给出了计算公式，并介绍了实现该方法的技术方案。该方法解决了大型拱坝多维变形自动观测问题，也可应用于对大型建筑、桥梁、山体等的多维多点变形自动观测。     

基于第5代HTML标准的拱坝工程三维可视化网络平台

拱坝工程的科学计算可视化是拱坝科学研究的重要辅助工具.针对传统可视化方法存在的问题,提出了面向第5代HTML标准的网络平台可视化方法.通过外部面提取与拓扑转化等算法将有限元模型转化为WebGL模型,并利用Blinn算法实现光照渲染,搭建的网络可视化平台具有兼容性、用户体验性以及开发灵活性的优势.文中详细阐述了有限元模型向WebGL的转化算法以及网络平台的建设方法.针对溪洛渡拱坝工程开发了自动化程序与网络平台,直观、科学地实现了工程三维可视化,并在多种客户端下取得了良好的浏览效果与用户体验,进一步验证了文中方法的可行性;同时也对这种网络平台的发展方向进行了讨论.     

基于C/S体系结构的大坝在线安全监控系统

该文结合作者在参加"二滩拱坝安全在线监控系统"的开发实践,详细讨论了基于Ｃ／Ｓ体系结构的大坝安全监控系统的系统设计、功能设计与实现。     

锦屏一级水电站左岸底层灌浆平洞深孔帷幕灌浆施工

锦屏一级水电站作为世界第一高的拱坝,在超高的水头和复杂的地质条件下,在底层灌浆洞中进行了超过170 m的深孔帷幕灌浆。施工中克服了各种不利条件,解决了多种非常规的施工技术难题,其经验可为其他类似工程提供参考。     

Optimization design of arch dam shape with modified complex method

With the development of arch dam technology, the shapes of arch dam become variable. In order to obtain the reasonable shape, optimization design is the key technology and the important part in the design of arch dam. Based on the engineering example, the geometry model of arch dam is established, the difficulties in the design of arch dam such as more design variables, nonlinearity of the mathematical function and constraint condition, have been solved by using the modified complex method, finally the perfect shape is gained.     

Modelling of an arch dam by polynomial interpolation

Polynomial curves controlled by points as well as by the tangents in them allow for a great margin of freedom, far from the conditions implied by the use of conventional curves, in the design of free-form curves.The lofting technique, in turn, permits us to generate surfaces that include a series of given curves.The algorithms propitiated to generate these curves and surfaces are very suitable for the geometric design of the arch dam, since they provide for a design of the curves forming the horizontal arches in which the dam can conceivably be divided taking into account, besides, the angle among the tangents to the arch at its ends as well as the hillsides of the closed arch. Once these curves are designed, the facings of a dam can be generated as the surfaces involving both series of previous curves.This paper presents the geometric calculations behind the generation of both surfaces and their computerized processing, in addition to a practical example of the use of the proposed methodology.     

The development and verification of relocating mesh method for the computation of temperature field of RCC dam

Based on the construction property of rolled compacted concrete dam cast layer by layer, three-dimensional finite element relocating mesh method was developed in the paper to simulate construction process and compute temperature field. The computation model of relocating mesh method is expatiated in detail. The feasibility and error of the relocating mesh method were analyzed and demonstrated. The computation results were verified with the temperature observation data of an RCC arch dam. The results show that the method has high calculation precision, less computer run time and less memory. The values computed with the method are in the same trend with the observation data. The method has proved to be effective in simulating construction process and computing temperature field of RCC dam.     

Multi-zone parametric inverse analysis of super high arch dams using deep learning networks based on measured displacements

Parametric inverse analysis/identification provides significant information for structural damage detection and construction in dam engineering. The main challenge in inverse analysis is to enhance the computational accuracy and efficiency for complex structures, especially for super high arch dams with many zone parameters. This study developed a high-precision deep learning-based surrogate model for rapid inverse analysis of concrete arch dams. The relationship between mechanical parameters and multi-point displacement response is interpreted by convolutional neural networks (CNN)-based surrogate model. The proposed model is integrated with the Latin hypercube sampling and a meta-heuristic optimization algorithm for rapid inverse analysis strategy. The objective function is defined as the distance between the displacement predicted by the surrogate model and the measured displacement. The proposed approach is tested on an actual super high concrete arch dam. Results show that the proposed approach can achieve high accuracy and improve the computational efficiency by 95.83 % compared with the direct finite element method.     

Dynamic material parameter inversion of high arch dam under discharge excitation based on the modal parameters and Bayesian optimised deep learning

Vibration-based dam safety monitoring methods have increasingly become a research hotspot for assessing dam safety. The accurate material parameters of a high arch dam and its foundation are critical for monitoring vibration safety. Accordingly, a dynamic material parameter inversion framework for an arch dam is developed based on modal parameters and deep learning. Firstly, an determined-order stochastic subspace identification method with adaptive variational modal decomposition is proposed based on the prototype vibration signal obtained under the discharge excitation, which can effectively identify the modal parameters. Secondly, the sensitivity of the dynamic elastic modulus (DEM) in different regions to the modal parameters of the arch dam was analysed using the orthogonal test method and variance analysis method, and it was utilised to ascertain the DEM to be inverted. Finally, a Bayesian optimised multi-output long short-term memory neural network is used to establish a nonlinear mapping relationship between the DEM and the modal parameters as an alternative to finite element calculations, and the identified modal parameters are employed as network inputs to inverse the actual DEM of each zoning. An engineering example shows that the proposed DEM inversion method for high arch dams is effective and accurate, providing a good basis for the vibration safety analysis of arch dams. This study overcomes the limitations of difficult to effectively extract modal parameters of arch dams under discharge excitation, and advances the application of deep learning technology in hydraulic engineering by combining modal parameters.     

广东省小型水库雨水情测报和大坝安全监测系统建设

由于部分小型水库的先天不足加上后天的粗放管理,雨水情测报和大坝安全监测设施严重缺失,导致不能及时发现水库存在的安全隐患,2021年水利部对小型水库雨水情测报和大坝安全监测系统提出了建设要求。广东省共有小型水库7141座,如何有序高效的开展小型水库雨水情和大坝安全监测设施建设需要严谨可行的顶层设计,本文分析广东省小型水库雨水情测报和大坝安全监测的现状,提出了相关建设原则、建设目标、建设内容、技术方案及典型设计,并在博罗县、花都市三座水库开展试点建设,取得良好的应用效果和示范作用,本文提出的技术方案和典型设计写入《广东省小型水库雨水情测报和大坝安全监测设施建设与运行技术指南》,为广东省开展该项工作提供技术指导,也为其他省份相关工作提供借鉴。