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相关概念视频

Quantifying Heat02:46

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Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a higher...
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If the temperature of an object is changed while it is prevented from expanding or contracting, the object is subjected to stress. The stress is compressive if the object expands in the absence of constraint and tensile if it contracts. This stress resulting from temperature change is known as thermal stress. It can be quite large and can cause damage. To avoid this stress, engineers may design components so they can expand and contract freely. For instance, on highways, gaps are deliberately...
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San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in temperature (ΔT) is 55...
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The Use of Thermal Infra-Red Imaging to Detect Delayed Onset Muscle Soreness
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基于ANN的桥梁支固定度量化使用实时无线传感器的热响应数据.

Prakash Bhandari1, Shinae Jang1, Ramesh B Malla1

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概括
此摘要是机器生成的。

研究人员开发了一种新的方法来评估桥梁支的健康状况,使用热数据和人工神经网络 (ANN). 该技术量化了支固定性,这对于准确的桥梁结构健康监测和防止故障至关重要.

关键词:
人工神经网络 (ANN) 是一个人工神经网络.轴承的硬性 轴承的硬性桥梁联合监测 桥梁联合监测有限元素建模有限元素建模结的轴承 结的轴承低成本的无线传感网络 (WSN)支持固定性的固定性.桥梁的热反应

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科学领域:

  • 土木工程 土木工程是指土木工程.
  • 结构健康监测 结构健康监测
  • 人工智能的人工智能

背景情况:

  • 老化的桥梁带来了重大风险,支和关节故障是崩的常见原因.
  • 目前的结构健康监测往往忽略了桥梁支,尽管它们在整体桥梁完整性中的关键作用.
  • 准确评估桥梁支固定性对于早期检测轴承退化和加强监测系统至关重要.

研究的目的:

  • 开发和验证一种使用热应答数据量化桥梁支固定性的新方法.
  • 调查热位移与不同支刚度,超结构损坏和热负荷之间的关系.
  • 通过关注支条件,提高桥梁结构健康监测系统的准确性和可靠性.

主要方法:

  • 使用人工神经网络 (ANN) 模型开发支持固定性量化方法.
  • 创建一座高速公路桥的有限元 (FE) 模型,以模拟各种条件下的热位移.
  • 使用来自康涅狄格州两个运营桥梁的现场监测数据验证FE模型和ANN预测.

主要成果:

  • 该研究成功模拟了不同支固定度水平的热位移模式.
  • 经过训练的ANN模型表现出了基于热应答数据预测支刚性的能力.
  • 现场数据验证证实了FE-ANN开发方法的实际适用性和准确性.

结论:

  • 拟议的基于人工神经网络 (ANN) 的方法为使用热反应量化桥梁支固定性提供了可靠的方法.
  • 这种技术为评估轴承健康状况和提高桥梁结构健康监测精度提供了有价值的工具.
  • 调查结果强调了监测桥梁支的重要性,以确保关键基础设施的安全性和寿命.