混凝土XAI:通过基于深度学习的方法来预测混凝土强度的多变量数据集
José A Guzmán-Torres1, Francisco J Domínguez-Mota1, Elia M Alonso-Guzmán1
1Civil Engineering Faculty, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58030, Mexico.
Data in brief
|March 1, 2024
概括
本研究介绍了ConcreteXAI,这是一套为期10年的混凝土机械和非破坏性测试数据集. 它支持人工智能驱动的预测模型,用于具体的性能,增强材料科学研究.
科学领域:
- 材料科学 材料科学 材料科学
- 土木工程 土木工程是指土木工程.
- 数据科学数据科学数据科学
背景情况:
- 混凝土是全球重要的建筑材料,但用新型添加剂制定最佳混合物存在挑战.
- 预测混凝土性能的现有方法缺乏材料和属性的多样性.
- 开发可靠的混凝土属性的预测模型对于推进建筑技术至关重要.
研究的目的:
- 介绍ConcreteXAI数据集,这是一个全面的10年混凝土机械和非破坏性测试结果的综合汇编.
- 为开发具体属性的基于深度学习的先进预测模型提供资源.
- 通过大规模,多样化的数据集,促进具体材料科学和工程方面的研究.
主要方法:
- 进行了长达10年的实验室调查,包括对混凝土材料的机械测试和非破坏性评估.
- 编制了一个数据集 (ConcreteXAI),包括来自12种不同的混凝土配方的18480个数据点,含有各种添加剂和聚合物.
- 设计了数据集,以便与深度学习模型无集成,用于预测分析.
主要成果:
- ConcreteXAI数据集提供了各种混凝土混合物的机械性能和非破坏性测试的广泛数据.
- 它包括对压力强度,屈曲强度,抗拉强度和耐久性指标 (如均性和多孔性) 的详细评估.
- 该数据集作为一种尖端的资源,用于分析混凝土的性能和性能.
结论:
- ConcreteXAI数据集是研究人员的宝贵资源,旨在为混凝土元素开发高质量的预测模型.
- 深度学习技术可以精确地使用这个数据集来预测或估计所需的具体属性.
- 这项工作推动了人工智能在具体材料科学中的应用,使得更准确的性能预测成为可能.
相关概念视频
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Considering the tensile strength of concrete involves recognizing that the theoretical strength of cement paste can be up to a thousand times higher than what is observed in practical applications. This significant discrepancy is largely attributed to the presence of microscopic cracks within the concrete. These cracks tend to amplify stress at their tips when a load is applied, a phenomenon explained by Griffith's theory of brittle fracture.
The dimensions and shape of a concrete specimen...
The dimensions and shape of a concrete specimen...
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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...
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