使用Mask-RCNN和温度效应分析优化地下室混凝土结构的裂纹控制
1Department of Architectural Arts, Xuancheng Vocational & Technical College, Xuancheng City, China.
PloS one
|October 5, 2023
概括
这项研究优化了地下室混凝土结构,以减少使用Mask-RCNN和温度分析的裂. 该方法显著降低了裂密度,长度,宽度,应力度和变形,提高了结构稳定性.
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
- 计算力学 计算力学 计算力学
背景情况:
- 在地下室混凝土结构中发生裂会损害完整性.
- 温度波动会引起应力和变形,加剧裂的传播.
- 现有的裂缓解方法需要优化.
研究的目的:
- 提出一种优化方法来缓解地下室混凝土结构中的裂.
- 为了利用基于Mask区域的卷积神经网络 (Mask-RCNN) 和温度效应分析.
- 通过尽量减少应力和变形来增强结构稳定性.
主要方法:
- 使用Mask-RCNN用于裂识别的混凝土结构的图像细分.
- 有限元分析以模拟温度变化下的应力和变形.
- 一个优化算法来调整几何和材料参数.
主要成果:
- 裂密度减少了60.22%,平均裂长度减少了40.24%,宽度减少了35.43%.
- 最大应力度减少了25.22%,最大变形减少了30.32%.
- 实时监测验证了结构稳定的显著改善.
结论:
- 拟议的优化方法有效地减少了地下室混凝土结构的裂.
- 这种方法通过减轻应力度和变形来提高结构稳定性.
- 优化算法在裂控制中表现出稳健性和一致性.
相关概念视频
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01:27Cold Weather Concreting
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01:14Design Example: Managing Concrete Workability
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01:28Types of Non-structural Cracks in Concrete
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