AUTHOR=Zhao Bing , Xue Er-Wei , Gu Xin-Bao TITLE=Evaluation of coarse aggregate quality grade of recycled concrete based on the principal component analysis-cloud model JOURNAL=Frontiers in Materials VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/materials/articles/10.3389/fmats.2023.1291434 DOI=10.3389/fmats.2023.1291434 ISSN=2296-8016 ABSTRACT=

The quality grade assessment of coarse aggregate in recycled concrete has great significance for engineering quality, so the accurate estimation of its quality grade is vital. However, many factors affect its quality level, and its assessment procedure has a certain fuzziness and randomness. To overcome the abovementioned problems, the principal component analysis-cloud model was introduced. It is a combination of the principal component analytical method (PCA) and the normal cloud model and has the advantages of the two methods, as well as being widely applied to assess the quality level of different construction materials. To evaluate the coarse aggregate quality grade of recycled concrete in the present paper, the principal component analytical method (PCA) was applied to reduce the dimension of data and calculate the weight of each index, then a model of coarse aggregate quality based on cloud theory was constructed. According to the characteristic parameters of the cloud model, the coarse aggregate quality grade was determined. The conclusions indicate that the method is feasible for the accurate assessment of quality grade assessment of coarse aggregate, and its accuracy is very high. So, a new approach can be provided for the quality grade assessment of coarse aggregate in the future.