A hybrid model for estimation of ground movements due to mechanized tunnel excavation

Zhao, Chenyang; Hölter, Raoul; König, Markus; Lavasan, Arash Alimardani

doi:10.1111/mice.12438

Cited by 15 publications

(4 citation statements)

References 36 publications

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“…Initial developments focused on estimating the maximum induced ground movement using artificial neural networks (ANN) based on several tunneling factors, including a few TBM operational parameters (Shi et al, 1998; Suwansawat and Einstein, 2006; Boubou et al, 2010). Many studies have since employed machine learning algorithms to further develop the system (Cao et al, 2020; Mahmoodzadeh et al, 2020; Zhang et al, 2020a; 2021; Zhao et al, 2019a). Most of the previous studies argued that their proposed models and selected machine learning algorithms demonstrated excellent prediction performance.…”

Section: Ai Systemsmentioning

confidence: 99%

Shaping the future of tunneling with data and emerging technologies

Apoji,

Sheil,

Soga

2023

DCE

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The increase in global population and urbanization is presenting significant challenges to society: space is becoming increasingly scarce, demand is exceeding capacity for deteriorating infrastructure, transportation is fraught with congestion, and environmental impacts are accelerating. Underground space, and particularly tunnels, has a key role to play in tackling these challenges. However, the cost, risk, uncertainty, and complexity of the tunneling process have impeded its growth. In this paper, we envision several technological advancements that can potentially innovate and transform the mechanized tunneling industry, including artificial intelligence (AI), autonomous, and bio-inspired systems. The proliferation of AI may assist human engineers and operators in making informed decisions systematically and quantitatively based on massive real-time data during tunneling. Autonomous tunneling systems may enable precise and predictable tunneling operations with minimal human intervention and facilitate the construction of massive and large-scale underground infrastructure projects that were previously challenging or unfeasible using conventional methods. Bio-inspired systems may provide valuable references and strategies for more efficient tunneling design and construction concepts. While these technological advancements can offer great promise, they also face considerable challenges, such as improving accessibility to and shareability of tunneling data, developing robust, reliable, and explainable machine learning systems, as well as scaling the mechanics and ensuring the applicability of bio-inspired systems from the prototype level to real-world applications. Addressing these challenges is imperative to ensure the successful implementation of these innovations for future tunneling.

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Section: Ai Systemsmentioning

confidence: 99%

Shaping the future of tunneling with data and emerging technologies

Apoji,

Sheil,

Soga

2023

DCE

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“…Slurry shield tunneling is widely used in the construction of large infrastructure facilities such as inner‐city subway tracks, so slurry pumping systems are often on a kilometer scale (Borrmann et al., 2015; Zhao et al., 2019). In recent years, multi‐scale modeling approaches are used to simulate kilometer‐scale pipelines; however, they are only applicable to water transportation (Fascetti & Oskay, 2019).…”

Section: Introductionmentioning

confidence: 99%

Method for calculating pressure losses in the pipelines of slurry shield tunneling based on coupled simulation of computational fluid dynamics and discrete element method

Yang

Guo

et al. 2023

Computer aided Civil Eng

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Hydraulic mucking/transport or slurry pipelining are widely used in dredging, trenching, (deep sea) mining, tunnel boring, and many other applications. Slurry pipelining during slurry shield tunneling is a classic instance of complex hydraulic mucking systems, which is characterized by the complex rheological behavior of the slurry and the inclusion of large and irregular particles. These characteristics make it difficult to estimate the pressure losses along slurry pipelines, compared to other hydraulic mucking systems. This study established a powerful method for predicting the pressure losses in long‐distance slurry pipelining of slurry shield tunneling based on computational fluid dynamics–discrete element method (CFD‐DEM)‐coupled simulations. Rheological tests were carried out to provide reliable slurry flow parameters for CFD calculations. Irregular pebbles with different sizes were digitally scanned using 3D scanning technology, and the scanned models were applied to the DEM. This method was successfully applied to a slurry shield tunnel project in Beijing, China. The mechanical properties of the fluid phase and particle phase were revealed by modeling a typical slurry pipeline. A comparison of the pressure losses along slurry pipelines was made between the proposed method and field data, indicating the validity of the established method. The simulation results indicate that when the slurry flows through the elbow, a secondary flow will be formed due to centrifugal force. Pebbles of different sizes show different motion responses under the combined action of gravity and slurry coupling force. The turbulent flow of particles will increase the frictional pressure losses in the elbow area, compared to the straight section. This work provides a valuable reference for the layout of the slurry circulation system of similar projects.

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“…The surface settlement of the crossing of the existing tunnel was noticeably reduced, indicating that the existing tunnel weakened surface settlement. An innovative simulation technology was developed, combining the computational efficiency of detailed process-oriented finite element (FE) simulations (sub-model) and element models (surrogate model) [5]. The simulation results demonstrated that the proposed hybrid modeling method was effective.…”

Section: Introductionmentioning

confidence: 99%

Study on Interaction Mechanism of Segment in Stratum of TBM Construction Overpass Building

Liu¹,

Wu²,

Xu³

et al. 2023

Preprint

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To solve the problem of deformation and stress in segments when a full-face hard rock tunnel boring machine (TBM) tunnel for an urban subway passes through existing buildings, a three-dimensional mechanical calculation model of TBM tunneling under existing buildings was established based on numerical analysis to comprehensively study the spatial attributes of tunnel segments during TBM tunneling. The Qingdao Metro Line 1 TBM tunnel in the hard rock stratum of Xiaobei District passes through existing buildings. The results indicated that (1) the stress and deformation of the segments were different at different positions. The horizontal and vertical stress and displacement of the segments in front of the building were significantly affected by the building. When the segment was not in the area below the horizontal plane of the building, the vertical stress of the segment was significantly greater than the two stresses in the horizontal direction. (2) The vertical displacements of the vault and the arch bottom were the largest, and the influence of vertical accessories was stronger when the segment was closer to the building.(3) When the tunnel was excavated to approximately one tunnel diameter in front of the building, the building was affected. If the surrounding rock is unstable, the excavation face may collapse and the ground surface may sink, possibly leading to inclination, cracking, and uneven settlement of the building.

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A hybrid model for estimation of ground movements due to mechanized tunnel excavation

Cited by 15 publications

References 36 publications

Shaping the future of tunneling with data and emerging technologies

Shaping the future of tunneling with data and emerging technologies

Method for calculating pressure losses in the pipelines of slurry shield tunneling based on coupled simulation of computational fluid dynamics and discrete element method

Study on Interaction Mechanism of Segment in Stratum of TBM Construction Overpass Building

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