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In fluid mechanics, buoyancy and stability are key concepts for understanding the behavior of submerged and floating bodies. When a stationary body is fully or partially submerged in a fluid, the fluid exerts a force on the body known as the buoyant force. This force acts vertically upward through a point called the center of buoyancy, which is the center of the displaced fluid volume. According to Archimedes' principle, the magnitude of the buoyant force is equal to the weight of the fluid...
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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
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水下堆基础缺陷检测方法基于扩散概率模型和改进点MLP.

Tongyuan Ji1,2, Dingwen Zhang1

  • 1School of Transportation, Southeast University, Nanjing 211189, China.

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|September 27, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的方法,用于检测水下堆基础损伤,使用扩散概率模型和改进的PointMLP. 该技术在识别缺陷方面达到很高的准确性,为基础设施安全提供了至关重要的支持.

关键词:
时间点MLP注意力机制注意力机制扩散概率模型是一个扩散概率模型.堆基础缺陷检测缺陷检测 堆基础缺陷检测一个点云,一个点云.

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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
  • 计算机视觉 计算机视觉

背景情况:

  • 水下堆基础是关键基础设施.
  • 损坏检测对于结构完整性和安全性至关重要.
  • 现有的方法可能缺乏准确性或效率.

研究的目的:

  • 开发和验证一种用于检测水下堆基础损坏的新方法.
  • 为了提高缺陷检测的准确性和可靠性.
  • 为水下基础设施检查提供技术支持.

主要方法:

  • 使用声纳系统来采集点云数据.
  • 应用PCA-ICP注册,过算法和RANSAC进行点云处理.
  • 采用扩散概率模型来生成和增强缺陷点云.
  • 将特征注意机制集成到PointMLP中,用于缺陷识别.

主要成果:

  • 成功收集和处理码头堆基础的点云数据.
  • 改进的PointMLP有效地识别了堆基础缺陷.
  • 在计算体积评估中达到高达95%的准确性.
  • 证明了0.0756 m3的体积误差,准确率为95.238%.

结论:

  • 拟议的方法为水下堆基础损坏检测提供了一个强大的解决方案.
  • 在体积计算和缺陷识别方面实现了高精度.
  • 这种技术为防止与基础故障有关的重大事故提供了宝贵的技术支持.