Kobaka Janusz
Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-720 Olsztyn, Poland.
Materials (Basel). 2021 May 19;14(10):2668. doi: 10.3390/ma14102668.
With the recent and rapid development of concrete technologies and the ever-increasing use of concrete, adapting concrete to the specific needs and applications of civil engineering is necessary. Due to economic considerations and care for the natural environment, improving the methods currently used in concrete design is also necessary. In this study, the author used principal component analysis as a statistical tool in the concrete mix design process. Using a combination of PCA variables and 2D and 3D factors has made it possible to refine concrete recipes. Thirty-eight concrete mixes of different aggregate grades were analyzed using this method. The applied statistical analysis showed many interesting relationships between the properties of concrete and the content of its components such as the clustering of certain properties, showing dependence between the properties and the quantities of certain ingredients in concrete, and reducing noise in the data, which most importantly simplifies interpretation. This method of analysis can be used as an aid for concrete mix design.
随着混凝土技术的快速发展以及混凝土使用量的不断增加，使混凝土适应土木工程的特定需求和应用变得十分必要。出于经济考虑和对自然环境的关注，改进当前混凝土设计中使用的方法也很有必要。在本研究中，作者在混凝土配合比设计过程中使用主成分分析作为一种统计工具。通过结合主成分分析变量以及二维和三维因素，得以优化混凝土配方。使用该方法对38种不同骨料级配的混凝土配合比进行了分析。所应用的统计分析揭示了混凝土性能与其组分含量之间的许多有趣关系，例如某些性能的聚类、混凝土中某些成分的性能与数量之间的相关性，以及减少数据中的噪声，最重要的是简化了解释。这种分析方法可作为混凝土配合比设计的辅助手段。
