Construction and Application of a Multi-Dimensional Quality Gain–Loss Function for Dam Concrete Based on Gaussian Process

As a critical component of China’s major infrastructure, the quality and safety of hydraulic engineering projects are directly linked to national economic security. Therefore, research on construction quality management of hydraulic concrete is of great importance. Traditional quality gain–loss functions often fail to fully capture the correlations among multiple quality characteristics, the varying weights of these characteristics in overall quality performance, and the presence of multiple influencing factors. To address these limitations, this study employs Gaussian process regression to construct a multivariate and multidimensional quality gain–loss function model. The signal-to-noise ratio is used to represent the interactions among different quality characteristics, while a gain–loss cost matrix is introduced to account for the contribution of each characteristic to the overall function. A case study on summer dam concrete construction is presented to demonstrate the applicability of the proposed model. The results show that the gain–loss values range from a minimum of 1.09 to a maximum of 11.7, which are significantly lower than those obtained using the dimensionless standardized multivariate quality gain–loss function developed by Artiles-León, thereby validating the effectiveness and rationality of the proposed approach.