A mirror-finished fair-faced concrete mix proportion optimization method, device and storage medium

By collecting basic parameters across all dimensions, calculating objective and subjective weights, and constructing a multi-objective coupled optimization formula, the problem of poor parameter adaptability in the mix proportion optimization of mirror-finish concrete in existing technologies is solved, and the multi-performance objective optimization of mirror-finish concrete is realized.

CN122266566APending Publication Date: 2026-06-23ANHUI CHINA RAILWAY ENG TECH SERVICE CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ANHUI CHINA RAILWAY ENG TECH SERVICE CO LTD
Filing Date
2026-02-03
Publication Date
2026-06-23

AI Technical Summary

Technical Problem

Current concrete mix design optimization relies on engineers' subjective judgment, resulting in poor parameter adaptability, difficulty in quantifying the correlation between multiple factors and performance characteristics, and neglect of the synergistic effect of factors in traditional optimization, leading to a disconnect between data and actual needs.

Method used

By collecting basic parameters across all dimensions, calculating objective and subjective weights, constructing a multi-objective coupled optimization formula, integrating correlation, optimizing the mix proportion of mirror-finished fair-faced concrete, preparing specimens and testing core performance indicators, the optimal mix proportion was obtained.

Benefits of technology

This approach achieves a high degree of alignment between weights and raw materials and the environment, accurately reflects the contribution of factors, ensures the optimization effect of mirror-finished concrete under multiple performance objectives, and avoids subjective assumptions and data dispersion interference.

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Abstract

The application discloses a mirror-facade fair-faced concrete mix proportion optimization method and device and a storage medium. The method comprises the following steps: collecting full-dimension basic parameters to form a core parameter set; screening a plurality of core factors related to core performance indexes according to the core parameter set; setting a factor level according to a raw material performance parameter for each factor; calculating objective weights of the core factors; fusing the objective weights, a correlation degree and subjective weights to obtain final compound weights; constructing an orthogonal test scheme; preparing concrete mix proportion test pieces; curing the concrete mix proportion test pieces to a specified age; testing core performance indexes of each group of the concrete mix proportion test pieces; constructing an innovative multi-target coupling optimization formula; calculating comprehensive performance values of each group of the concrete mix proportions; and obtaining an optimal mix proportion. Through the calculation of the objective weights and the subjective weights and the coupling after the correlation degree, neither the engineering requirement is deviated due to the simple pursuit of data fitting, nor the data rule is ignored due to the experience-based weight distribution.
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