Scholarlink

<p>Uncertainty is an inherent property arising from the complexity and diversity of concrete composition and randomness during production and measurement. This study proposed a novel framework to address uncertainty during concrete performance characterization and composition design, incorporating natural gradient boosting (NGBoost), optimization theory, and laboratory tests. NGBoost was employed to capture concrete performance and the associated uncertainty using the data from laboratory tests. Based on the above performance characterization model, the concrete composition was determined through simplicial homology global optimization (SHGO). Laboratory tests were used to generate data based on various concrete compositions. The slag-desulfurization gypsum-based alkali-activated materials were utilized to illustrate and validate the developed framework. The results indicate that the developed framework effectively determines the concrete composition for improved performance and approximates the complex relationship between concrete composition and its corresponding performance. The developed framework also characterized and quantified the uncertainty during the performance characterization and composition.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Uncertainty Quantification of Performance Characterization and Composition Design of Concrete

  • 期刊论文

  • 发表日期：

    2026年6月22日

查看全文
  • Shike Zhang,
  • Xinyi Liu,
  • Youliang Zhang,
  • Jiaolong Ren,
  • Hongbo Zhao

摘要

Uncertainty is an inherent property arising from the complexity and diversity of concrete composition and randomness during production and measurement. This study proposed a novel framework to address uncertainty during concrete performance characterization and composition design, incorporating natural gradient boosting (NGBoost), optimization theory, and laboratory tests. NGBoost was employed to capture concrete performance and the associated uncertainty using the data from laboratory tests. Based on the above performance characterization model, the concrete composition was determined through simplicial homology global optimization (SHGO). Laboratory tests were used to generate data based on various concrete compositions. The slag-desulfurization gypsum-based alkali-activated materials were utilized to illustrate and validate the developed framework. The results indicate that the developed framework effectively determines the concrete composition for improved performance and approximates the complex relationship between concrete composition and its corresponding performance. The developed framework also characterized and quantified the uncertainty during the performance characterization and composition.