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相关概念视频

Impact Strength of Concrete01:21

Impact Strength of Concrete

177
Impact strength in concrete is a critical measure that reflects the material's capability to endure the forces applied during pile driving and when supporting machinery foundations that experience impulsive loads. It is also essential when handling precast concrete components to prevent accidental damage. The impact strength is assessed by observing the concrete's resistance to repeated impacts and energy absorption capacity. A key indicator of significant damage to concrete is when it...
177
Non-destructive Tests for Concrete Strength01:12

Non-destructive Tests for Concrete Strength

113
The rebound hammer test, also known as the Schmidt hammer test, is a non-destructive technique for evaluating the hardness of concrete and, indirectly, the strength of concrete. It operates on the principle that the rebound of a spring-driven mass from a concrete surface correlates to the surface's hardness. The device comprises a mass within a tubular housing, a spring mechanism, and a plunger that strikes the concrete. Upon release, the energy imparted to the mass by the spring causes it...
113
Relation Between Tensile Strength and Compressive Strength of Concrete01:30

Relation Between Tensile Strength and Compressive Strength of Concrete

169
Concrete is a fundamental building material, and understanding its strengths is crucial for construction projects. The relationship between its tensile and compressive strengths is intricate, showing that while these strengths are related, they do not increase at the same rate. Tensile strength's growth is slower and is affected by various factors such as the methods used for testing, the size and shape of the specimen, the texture of the aggregate used, and the moisture content of the...
169
Behavior of Concrete Under Compressive Load01:23

Behavior of Concrete Under Compressive Load

149
Concrete exhibits specific behaviors under different compressive loads. Understanding this is crucial for understanding its structural integrity. When concrete undergoes uniaxial compression, it tends to develop cracks that run parallel to the direction of the force. These parallel cracks stem from localized tensile stresses that occur perpendicular to the compression direction. Additionally, angled cracks may appear due to the formation of shear planes.
As the concrete specimen fractures under...
149
Fatigue Strength of Concrete01:22

Fatigue Strength of Concrete

169
Fatigue, in the context of materials science and engineering, refers to the weakening or failure of a material caused by repeatedly applied loads, even if these loads are below the strength limit of the material. Fatigue strength in concrete is a critical property that influences its durability and longevity. Concrete can fail in two ways due to fatigue. Static fatigue or creep rupture occurs under a constant load or one that increases slowly. The other failure mode is due to cyclical or...
169
Abrasion Resistance of Concrete01:23

Abrasion Resistance of Concrete

106
Abrasion resistance is an essential characteristic of concrete that determines its durability and longevity under various wear conditions. Concrete surfaces are vulnerable to different types of abrasion. For instance, surfaces may wear down due to the constant movement of vehicles or be eroded by solids carried in water, as seen in concrete canal linings. Specific tests are conducted to measure the abrasion resistance of concrete.
One such test is the revolving disc test, where three plates...
106

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相关实验视频

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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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使用可解释的机器学习模型预测高性能混凝土的压力强度.

Yushuai Zhang1, Wangjun Ren2, Yicun Chen3,4

  • 1Institute of Defense Engineering, AMS, PLA, Beijing, 100850, People's Republic of China.

Scientific reports
|November 16, 2024
PubMed
概括

这项研究开发了可解释的机器学习模型,以预测高性能混凝土的强度. 影响混凝土强度的关键因素包括年龄和含水量,有助于施工质量控制.

关键词:
压力强度预测的预测机器学习是机器学习.相称的特征是相称的特征.随机搜索 随机搜索 随机搜索莎普利的添加式解释

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科学领域:

  • 土木工程 土木工程是指土木工程.
  • 材料科学 材料科学 材料科学
  • 数据科学数据科学数据科学

背景情况:

  • 准确的混凝土强度预测对于建设效率和质量保证至关重要.
  • 当前的方法可能缺乏解释性,阻碍对影响因素的理解.
  • 高性能混凝土 (HPC) 需要精确的强度估计,以实现最佳应用.

研究的目的:

  • 引入一个可解释的机器学习 (ML) 框架来预测HPC的压力强度.
  • 通过结合衍生特征来提高混凝土强度预测的准确性.
  • 确定影响HPC压力强度的最有影响力的特征.

主要方法:

  • 开发并比较了四个可解释的ML模型:随机森林 (RF),AdaBoost,XGBoost和LightGBM.
  • 集成的特征导出和随机搜索,具有5倍的交叉验证,用于超参数优化.
  • 应用了SHapley添加式扩展 (SHAP) 来分析LightGBM模型中的特征重要性.

主要成果:

  • 该研究成功构建了可解释的ML模型,用于HPC压力强度预测.
  • 年龄,水/水泥比,渣渣和水含量被确定为关键预测因素.
  • 超塑料/水泥比率,泥/水泥比率和灰/水泥比率对预测的强度没有显著影响.

结论:

  • 可解释的ML模型,特别是LightGBM,为HPC压力强度提供可靠的预测.
  • 功能工程和先进的ML技术提高了预测准确性并提供了洞察力.
  • 了解关键的影响因素,使得更好的材料选择和施工实践.