An AI algorithm-based method for adaptively adjusting the proportion of a modifier

By using an AI algorithm-driven adaptive modifier ratio method, combined with sensor monitoring and a multi-field coupling model, the modifier ratio is dynamically adjusted to solve the problems of frost heave deformation and insufficient mechanical stability in the treatment of thick and cold foundations, thus achieving adaptive control and long-term stability of the foundation.

CN121960206BActive Publication Date: 2026-07-24中国市政工程西北设计研究院有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
中国市政工程西北设计研究院有限公司
Filing Date
2026-02-27
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing technologies cannot effectively adapt to the heterogeneity of geological space and dynamic environmental fluctuations in the treatment of foundations in high-altitude and cold regions, resulting in insufficient frost heave deformation and mechanical stability.

Method used

An AI-based adaptive adjustment method for the modifier ratio is adopted. By monitoring the formation parameters through a sensor array and combining a thermal-hydraulic-mechanical multi-field coupling model and artificial intelligence decision-making, the modifier ratio is dynamically adjusted. The physical thermal barrier of the composite micropile group and the chemical response of the phase change material are utilized to achieve adaptive control of the foundation.

Benefits of technology

It improves the stability and long-term service reliability of thick, cold-resistant foundations in complex environments, effectively suppresses frost heave deformation, and ensures the mechanical constitutive stability of the foundation during freeze-thaw cycles.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application relates to the technical field of artificial intelligence, and discloses a method for self-adaptive adjustment of modifier proportioning based on an AI algorithm, which acquires multi-field parameters by using a composite material micro pile with an embedded sensing array, and predicts a stratum evolution trend through a heat-water-force multi-field coupling evolution model. An artificial intelligence algorithm calculates a modifier proportioning vector changing with depth according to a prediction result, and drives a grouting system to adjust the concentration of active components. The physical boundary of a micro pile group is used to guide a flow field to form a transverse overlapping reinforcement zone. A latent heat of a phase change component in the modifier is released at a preset temperature, and stratum heat balance is intervened in cooperation with the physical thermal resistance of the micro pile. The system performs parameter inversion and updates algorithm weights through measured data. The application realizes accurate matching of a treatment scheme and stratum heterogeneity, effectively suppresses foundation frost heaving deformation, and guarantees the structural stability of a high-cold and large-thickness foundation.
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Citation Information

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