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基于层次分析法-模糊理论的深部地层全断面盾构法适应性评价模型与试验

Adaptability evaluation model and experiment of full section SBM in deep strata based on AHP-fuzzy theory.

作者信息

Ni Suqian, Xu Ying, Chen Peiyuan, Ge Jinjin, Yang Rongzhou, Yang Ziyi, Yang Guang

机构信息

School of Civil Engineering and Architecture, Anhui University of Science and Technology, Huainan, 232001, Anhui, China.

State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Huainan, 232001, Anhui, China.

出版信息

Sci Rep. 2025 Jan 2;15(1):521. doi: 10.1038/s41598-024-84123-7.

DOI:10.1038/s41598-024-84123-7
PMID:39747976
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11696090/
Abstract

To delve into the adaptability of the full section SBM boring process during its inaugural application, this paper innovatively put forward an adaptability evaluation model for the SBM shaft boring within composite deep strata. This model is with the degree of adaptability T as the quantitative criterion. Initially, the evaluation index system of SBM boring adaptability is established. The determination of the adaptive standard for evaluation indexes and the calculation parameters of the model is based on a comprehensive approach that encompasses rock abrasion testing and extensive field investigations. Furthermore, based on the principle of AHP, the weight total ranking of SBM boring adaptability evaluation indexes is given under this method. Ultimately, fuzzy mathematics theory is introduced, and the fuzzy comprehensive evaluation and its verification is conducted. The results show that: the five factors that have the greatest influence on the adaptability of SBM boring in composite deep strata are, in order: I > I > I > I > I. Based on the adaptability evaluation model of SBM boring and by the principle of weighted average, the adaptability of the SBM boring process response is "strong adaptability". Through the engineering case, the scientific rationality of the SBM adaptability evaluation method in the composite deep strata has been verified.

摘要

为深入研究全断面竖井掘进机(SBM)钻进工艺首次应用时的适应性,本文创新性地提出了一种复合深厚地层中SBM竖井钻进适应性评价模型。该模型以适应性程度T为量化标准。首先,建立了SBM钻进适应性评价指标体系。评价指标的适应标准及模型计算参数的确定基于包括岩石磨损试验和大量现场调查的综合方法。此外,基于层次分析法原理,给出了该方法下SBM钻进适应性评价指标的权重总排序。最后,引入模糊数学理论,进行了模糊综合评价及其验证。结果表明:对复合深厚地层中SBM钻进适应性影响最大的五个因素依次为:I>I>I>I>I。基于SBM钻进适应性评价模型,按加权平均原则,SBM钻进工艺响应的适应性为“强适应性”。通过工程实例,验证了SBM适应性评价方法在复合深厚地层中的科学合理性。

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Research on the deformation laws of buildings adjacent to shield tunnels in clay strata.黏土地层中邻近盾构隧道建筑物变形规律研究
Sci Rep. 2024 Jan 2;14(1):265. doi: 10.1038/s41598-023-50855-1.
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Sci Rep. 2023 Nov 6;13(1):19140. doi: 10.1038/s41598-023-46449-6.
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