Underground Space最新文献_第7页

Benchmark study of three statistical methods for six intact rock failure criteria constrained by different rock strength data 不同岩石强度数据约束下六种完整岩石破坏准则三种统计方法的基准研究

IF 8.3 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-10-01 Epub Date: 2025-07-23 DOI: 10.1016/j.undsp.2025.04.006

Peng-fei He , Xin Li , Xu-long Yao , Zhi-gang Tao , Yan-ting Du

To reduce the impact of potential strength outliers on parameter estimation, statistical methods based on the least median square and least absolute deviation have been proposed as alternatives to the traditional least square method. However, little research has been conducted to compare the performance of these different statistical methods. This study introduces a novel procedure for evaluating the three statistical approaches across six selected rock failure criteria, constrained by various rock strength datasets. The consistency of the best-fitting failure criterion and the robustness of the strength parameter estimations serve as the primary benchmarks for evaluation. Based on the benchmark analysis, the following conclusions are drawn. First, both the least square and least absolute deviation methods perform equivalently in identifying the best-fitting failure criterion for a given rock strength dataset, whereas the least median square method does not. Second, when estimating the strength parameters in a two-dimensional failure criterion with the conventional test data of low complexity, the least absolute deviation method is recommended for obtaining robust parameter estimations. Third, as the complexity of conventional test data increases or when true triaxial test data are used to estimate strength parameters for a three-dimensional failure criterion, it is essential to evaluate the outlier-proneness by analyzing the prediction error. If the kurtosis of the prediction error is less than 3, the least square method is preferred. Otherwise, the least absolute deviation method should be used to mitigate the influence of potential strength outliers. This benchmark study offers valuable insights for the future application of different statistical methods in rock mechanics.

为了减少潜在强度异常值对参数估计的影响，提出了基于最小中位数平方和最小绝对偏差的统计方法来替代传统的最小二乘法。然而，很少有研究对这些不同统计方法的性能进行比较。本研究介绍了一种新的程序，用于评估六个选定岩石破坏标准的三种统计方法，受各种岩石强度数据集的约束。最佳拟合破坏准则的一致性和强度参数估计的鲁棒性是评价的主要标准。基于基准分析，得出以下结论。首先，最小二乘法和最小绝对偏差法在确定给定岩石强度数据集的最佳拟合破坏准则方面表现相当，而最小中位数二乘法则不然。其次，在使用复杂度较低的常规试验数据进行二维破坏准则强度参数估计时，建议采用最小绝对偏差法获得鲁棒参数估计。第三，随着常规试验数据复杂性的增加或使用真三轴试验数据估计三维破坏准则的强度参数时，通过分析预测误差来评估异常值倾向是必要的。如果预测误差的峰度小于3，则首选最小二乘法。否则，应采用最小绝对偏差法来减轻潜在强度异常值的影响。这一基准研究为未来不同统计方法在岩石力学中的应用提供了有价值的见解。

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引用次数: 0

Continuum-discrete coupling model for mechanical response analysis of tunnels subjected to non-uniform reverse faulting 非均匀逆断层作用下隧道力学响应分析的连续-离散耦合模型

IF 8.2 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-10-01 Epub Date: 2025-07-04 DOI: 10.1016/j.undsp.2025.03.005

Zhenning Ba , Yao Wang , Zhiwei Fang , Dongqiao Li

In recent decades, there have been numerous reports of damage cases involving tunnels crossing active faults. The mechanical response and failure mechanisms of cross-fault tunnels have become a key issue in the field of tunnel engineering. This study established a continuum-discrete coupling model comprising intact rock mass, fault zones, and tunnel. In this model, the tunnel and intact rock are modeled as continuous media, while the fault zone is modeled as a discrete medium. The non-uniform fault displacement is adopted to simulate the mechanical response and damage patterns of tunnels crossing active faults under reverse faulting. The simulation results are validated by comparison with the damage of Longchi tunnel observed from 2008 Wenchuan earthquake in China, as well as the experimental phenomenon from the model test. The results demonstrate that the proposed coupling model effectively reproduces the tunnel failure modes caused by reverse faulting. In addition, the high consistency between the simulation results and experimental data further confirms computational accuracy and reliability of the coupling model. A parametric analysis based on the Xianglushan tunnel in China is carried out to investigate the effects of fault displacements, fault widths, dip angles and fault zone rock mass qualities on damage patterns of crossing-fault tunnels. This study provides a valuable reference for seismic fortification of the tunnel crossing reverse faults.

近几十年来，有许多关于隧道穿越活动断层的损坏案例的报道。跨断层隧道的力学响应和破坏机制已成为隧道工程领域的一个关键问题。建立了完整岩体、断裂带和隧道的连续-离散耦合模型。在该模型中，隧道和完整岩石被建模为连续介质，而断裂带被建模为离散介质。采用非均匀断层位移模拟逆断层作用下隧道穿越活动断层的力学响应和破坏模式。通过与2008年中国汶川地震龙池隧道的破坏观测以及模型试验的实验现象进行对比，验证了模拟结果。结果表明，所建立的耦合模型能较好地再现逆断层作用下隧道的破坏模式。此外，仿真结果与实验数据的高度一致性进一步证实了耦合模型的计算精度和可靠性。以湘芦山隧道为例，通过参数化分析，探讨了断层位移、断层宽度、断层倾角和断裂带岩体质量对跨断层隧道破坏模式的影响。该研究为逆断层隧道的抗震设防提供了有价值的参考。

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引用次数: 0

Experimental study on the leakage-induced structural collapse of segmental tunnels 管片隧道渗漏致结构倒塌试验研究

IF 8.2 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-10-01 Epub Date: 2025-06-20 DOI: 10.1016/j.undsp.2024.09.006

Qihao Sun , Xian Liu , Yihai Bao , Wouter De Corte , Luc Taerwe

During the construction of segmental tunnels, unexpected leakage poses a significant safety hazard to the tunnel structures, potentially leading to collapse. Worldwide, accidents caused by leakage during the construction of shield tunnels have resulted in substantial losses. However, existing studies have not clearly elucidated the mechanism behind tunnel collapse induced by leakage, making it challenging to propose effective prevention or control measures. To address this issue, a series of model tests on tunnel collapse induced by leakage were designed and conducted. These tests replicated the tunnel collapse process and revealed three stages: seepage erosion, soil cave formation and destabilization, and soil impact. The soil caves develop upward, leading to a redistribution of external pressure on the tunnels. Ultimately, the structural collapse of the tunnel occurs due to soil impact from the unstable soil cave. Comparing tunnel entrance/exit accidents with connecting passage accidents highlights that both accident types share the same underlying mechanism but differ in boundary conditions.

在分段隧道施工过程中，突发性渗漏给隧道结构带来了重大的安全隐患，有可能导致隧道坍塌。在世界范围内，盾构隧道施工过程中发生的泄漏事故造成了巨大的损失。然而，现有的研究尚未明确渗漏引起隧道坍塌的机理，难以提出有效的防治措施。为解决这一问题，设计并开展了隧洞渗漏坍塌模型试验。这些试验模拟了隧道坍塌过程，揭示了三个阶段：渗流侵蚀、土洞形成和失稳以及土壤冲击。土洞向上发展，导致隧道外部压力的重新分配。不稳定土洞的土体冲击最终导致隧道结构坍塌。隧道出入口事故与连接通道事故的比较表明，这两种事故类型具有相同的潜在机制，但边界条件不同。

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引用次数: 0

Data-driven modeling for evaluating deformation of a deep excavation near existing tunnels 现有隧道附近深基坑变形评估的数据驱动建模

IF 8.3 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-10-01 Epub Date: 2025-07-14 DOI: 10.1016/j.undsp.2025.04.003

Fengwen Lai , Songyu Liu , Jim Shiau , Mingpeng Liu , Guojun Cai , Ming Huang

This study explores an integrated framework combining in-situ test-based numerical and data-driven modeling to assess the performance of a deep excavation-tunnel system. To achieve the goal, a case history of deep excavations adjacent to existing tunnels in silt/sand-dominated sediments is introduced to establish a base three-dimensional finite element (3D-FE) model. In-situ tests such as cone penetration test (CPT/CPTU) and seismic dilatometer test (DMT/SDMT), as an alternative to laboratory testing, are used to determine a set of advanced constitutive model parameters. The established excavation-tunnel numerical model is then validated against filed monitoring data. A dataset from numerical simulation is created for training and testing four machine learning models (i.e., artificial neural network (ANN), support vector machines (SVM), random forest (RF), and light gradient boosting machine (LightGBM)), which predict the maximum wall deflection, ground surface settlement, horizontal and vertical displacements of the tunnel. Results show that the ANN model outperforms other models in prediction capacity. Its generalization ability in practice is further enhanced by comparing field measurement data and empirical equations. The findings suggest that, with the integrated in-situ tests, FE and ANN modeling could be used to predict deformation responses of deep excavations close to existing tunnels in soft soil. The present study is useful and valuable for practical risk assessment and mitigation decisions.

本研究探索了一种将基于原位试验的数值模拟与数据驱动建模相结合的综合框架，以评估深挖-隧道系统的性能。为了实现这一目标，本文以淤泥/砂质沉积物中与既有隧道相邻的深基坑为例，建立了基础三维有限元（3D-FE）模型。作为替代实验室测试的一种方法，采用锥入试验（CPT/CPTU）和地震膨胀试验（DMT/SDMT）等现场测试来确定一组高级本构模型参数。根据现场监测数据对所建立的开挖-隧道数值模型进行了验证。建立了数值模拟数据集，用于训练和测试四种机器学习模型（即人工神经网络（ANN），支持向量机（SVM），随机森林（RF）和光梯度增强机（LightGBM）），这些模型可以预测隧道的最大墙挠度，地表沉降，水平和垂直位移。结果表明，人工神经网络模型的预测能力优于其他模型。通过实测数据与经验方程的对比，进一步增强了其在实践中的泛化能力。研究结果表明，通过现场综合试验，有限元和神经网络模型可用于预测软土中靠近既有隧道的深基坑的变形响应。本研究对实际的风险评估和缓解决策是有用的和有价值的。

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引用次数: 0

A lifecycle carbon emission evaluation model for urban underground highway tunnel facilities 城市地下公路隧道设施全生命周期碳排放评价模型

IF 8.3 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-10-01 Epub Date: 2025-07-18 DOI: 10.1016/j.undsp.2025.04.005

Guosheng Wang , Dechun Lu , Gangao Ji , Xuhua Liang , Qingtao Lin , Jirui Lv , Xiuli Du

Anthropogenic greenhouse gas emissions stand as the primary catalyst of climate perturbations. A precise evaluation of these emissions holds paramount importance in realizing energy conservation and emission reduction goals. Urban underground highway tunnel facilities emerge as a promising recourse for ameliorating traffic congestion and advancing energy conservation and emission mitigation endeavours. Nonetheless, the methodologies for quantifying its carbon emissions remain scant. This study ventures into the realm of carbon footprint appraisal within the lifecycle paradigm of underground highway tunnel facilities. Tailored to the characteristics, functionalities, and design intricacies of urban underground highway tunnel facilities, the physical boundaries and scopes are meticulously calibrated. Subsequently, a carbon emission computational model adept at encapsulating the emission characteristics throughout the entire lifecycle is formulated. Meanwhile, a detailed database is established for emission factors of various carbon emission activities. Leveraging insights garnered from a specific project case, the overarching carbon emission profiles of the urban underground highway tunnel facility, both in aggregate and individual stages, are elucidated. Concomitantly, bespoke recommendations and strategies aimed at energy preservation and emission abatement are proffered, attuned to the idiosyncratic attributes of carbon emissions across distinct stages.

人为温室气体排放是气候扰动的主要催化剂。准确评估这些排放对实现节能减排目标至关重要。城市地下公路隧道设施成为缓解交通拥堵和推进节能减排工作的有希望的资源。尽管如此，量化其碳排放量的方法仍然很少。本研究探索地下公路隧道设施生命周期模式下的碳足迹评估领域。根据城市地下公路隧道设施的特点、功能和设计复杂性，对物理边界和范围进行了精心校准。随后，建立了一个能够封装整个生命周期碳排放特征的碳排放计算模型。同时，建立了各种碳排放活动的详细排放因子数据库。利用从具体项目案例中获得的见解，阐明了城市地下公路隧道设施在总体和单个阶段的总体碳排放概况。与此同时，针对不同阶段碳排放的特殊属性，提供了旨在节能和减排的定制建议和策略。

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引用次数: 0

Development of the Optuna-NGBoost-SHAP model for estimating ground settlement during tunnel excavation 隧道开挖过程中地面沉降估算的Optuna-NGBoost-SHAP模型的建立

IF 8.2 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-10-01 Epub Date: 2025-07-15 DOI: 10.1016/j.undsp.2025.03.006

Yuxin Chen , Mohammad Hossein Kadkhodaei , Jian Zhou

This study aims to develop and evaluate a natural gradient boosting (NGBoost) model optimized with Optuna for estimating ground settlement during tunnel excavation, incorporating Shapley additive explanations (SHAP) to perform interpretability analysis on the model’s estimation results. The model’s predictive performance was comprehensively assessed using datasets from two earth pressure balance shield tunneling projects in Changsha and Zhengzhou, China. Comparative analyses demonstrated the superior accuracy and generalization capability of the Optuna-NGBoost-SHAP model (training set: R² = 0.9984, MAE = 0.1004, RMSE = 0.4193, MedAE = 0.0122; validation set: R² = 0.9001, MAE = 1.3363, RMSE = 3.2992, MedAE = 0.3042; test set: R² = 0.9361, MAE = 0.9961, RMSE = 2.5388, MedAE = 0.2147). SHAP value analysis quantitatively evaluated the contributions of input features to the model’s estimations, identifying geometric factors (distance from the shield machine to the monitoring section and cover depth) as the most important features. The findings provide robust decision support for safety management during tunnel construction and demonstrate the reliability and efficiency of the Optuna-NGBoost-SHAP framework in estimating complex ground settlement scenarios.

本研究旨在开发和评估利用Optuna优化的自然梯度推进（NGBoost）模型估算隧道开挖过程中地面沉降，并结合Shapley加性解释（SHAP）对模型估算结果进行可解释性分析。利用长沙和郑州两个土压平衡盾构隧道工程的数据集，对该模型的预测性能进行了综合评估。对比分析表明，Optuna-NGBoost-SHAP模型具有较好的准确率和泛化能力(训练集：R2 = 0.9984, MAE = 0.1004, RMSE = 0.4193, MedAE = 0.0122；验证集：R2 = 0.9001, MAE = 1.3363, RMSE = 3.2992, MedAE = 0.3042；测试集:R2 = 0.9361,美= 0.9961,RMSE = 2.5388, MedAE = 0.2147)。SHAP值分析定量地评估了输入特征对模型估计的贡献，确定几何因素（从盾构机到监测段的距离和覆盖深度）是最重要的特征。研究结果为隧道施工期间的安全管理提供了强有力的决策支持，并证明了Optuna-NGBoost-SHAP框架在估算复杂地面沉降情景方面的可靠性和有效性。

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引用次数: 0

Enhanced safety assessment on tunnel excavation via refined rock mass parameter identification 精细化岩体参数识别增强隧道开挖安全性评价

IF 8.3 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-10-01 Epub Date: 2025-06-27 DOI: 10.1016/j.undsp.2024.09.007

Hongwei Huang , Tongjun Yang , Jiayao Chen , Zhongkai Huang , Chen Wu , Jianhong Man

This study employs computer vision and deep learning techniques to execute the refined extraction and quantification of rock mass information in tunnel faces. The integration of contact measurement data and surrounding environmental parameters leads to a proposal for rock mass quality prediction, utilizing integrated machine learning techniques. Subsequently, a 3D model is established by incorporating tunnel face features and environmental data. The safety factor of rock mass excavation is calculated through the utilization of the strength reduction method, and the analysis of rock mass stability on the continuous tunnel face is performed, considering factors such as rock stress and joint sliding. The investigation of variation patterns of excavation safety factors, influenced by multiple modelling factors, is conducted through the utilization of a response surface design method in 46 experimental studies. The research reveals the accurate characterization of complex fissure occurrence obtained in the field through a discrete fracture network. Furthermore, a negative correlation between the safety factor of tunnel excavation and the grade of surrounding rock is observed, with an increase in grade resulting in a decrease in the safety factor. The response surface method effectively discloses polynomial correlations between various parameters such as inclination angle, dip direction, spacing, density, number of groups, and the safety factor. This elucidates the impact patterns of these parameters and their coupling states on the safety factor. The study provides significant insights into the intelligent evaluation of safety for continuous tunnel excavation.

本研究采用计算机视觉和深度学习技术对巷道围岩信息进行精细化提取和量化。结合接触测量数据和周围环境参数，提出了利用集成机器学习技术进行岩体质量预测的建议。随后，结合隧道工作面特征和环境数据，建立三维模型。利用强度折减法计算岩体开挖安全系数，并考虑岩体应力、节理滑动等因素，对连续隧洞工作面岩体稳定性进行分析。采用响应面设计方法，对46项试验研究进行了多模型因素影响下开挖安全系数的变化规律研究。该研究揭示了通过离散裂缝网络在野外获得的复杂裂缝产状的准确表征。巷道开挖安全系数与围岩等级呈负相关关系，等级越大，安全系数越小。响应面法有效地揭示了倾角、倾斜方向、间距、密度、群数、安全系数等参数之间的多项式相关性。阐明了这些参数及其耦合状态对安全系数的影响规律。该研究对隧道连续开挖安全性的智能评价具有重要的指导意义。

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引用次数: 0

Non-parametric probabilistic seismic capacity model for the stochastic interaction system of soil-subway station structures 土-地铁车站结构随机相互作用体系的非参数概率抗震能力模型

IF 8.2 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-10-01 Epub Date: 2025-07-03 DOI: 10.1016/j.undsp.2025.03.003

Minze Xu , Chunyi Cui , Hailong Liu , Jingbo Li , Jingtong Zhao , Chengshun Xu

A reasonable seismic capacity model is crucial for establishing the seismic performance level system and evaluating the seismic reliability of subway station structures. However, the deterministic structural and geotechnical mechanical parameters are usually applied to calibrate the seismic performance levels of subway station structures in the traditional seismic capacity analysis, which ignores the stochasticity of the soil-subway station interaction system. To overcome the challenge caused by the stochastic interaction system, the probability space partition method and stochastic pushover analysis method are combined to develop a calibration strategy of seismic performance levels considering the complete probabilistic information of the stochastic interaction system, and the non-parametric probabilistic seismic capacity models of the subway station structure are further established based on the principle of probability conservation in this paper. A subway station is also taken as the prototype to investigate the applicability of the proposed strategy and the influence of system randomness on the seismic capacity of the subway station structure. The results demonstrate that the seismic performance levels calibrated according to the proposed strategy can effectively consider the complete probabilistic information of the interaction system, which are more rigorous than the existing performance levels. Meanwhile, the probability density evolution of the bearing capacity of the subway station structure is essentially a non-stationary stochastic process, and the non-parametric probability density curves of seismic capacity display noticeable multi-peak characteristic. Moreover, the seismic capacity for L_P1 and L_P2 levels is more sensitive to the variability of geotechnical parameters above and below the structure, while the former for L_P3 and L_P4 levels is more sensitive to that on both sides of the structure. The relevant conclusions can provide some guidance for seismic design and improvement of the performance limits of underground structures in the related codes.

合理的抗震能力模型是建立地铁车站结构抗震性能等级体系和评价其抗震可靠度的关键。然而，在传统的抗震能力分析中，通常采用确定性的结构和岩土力学参数来标定地铁车站结构的抗震性能水平，忽略了土-地铁车站相互作用体系的随机性。为克服随机相互作用系统带来的挑战，结合概率空间划分法和随机推覆分析法，建立了考虑随机相互作用系统完全概率信息的抗震性能等级标定策略，并基于概率守恒原理建立了地铁车站结构的非参数概率抗震能力模型。并以某地铁车站为原型，研究了该策略的适用性以及系统随机性对地铁车站结构抗震能力的影响。结果表明，根据该策略标定的抗震性能等级能有效地考虑相互作用体系的完整概率信息，比现有的性能等级更为严格。同时，地铁车站结构承载力的概率密度演化本质上是一个非平稳的随机过程，抗震能力的非参数概率密度曲线表现出明显的多峰特征。LP1和LP2水平的地震能力对结构上方和下方岩土参数的变化更为敏感，而LP3和LP4水平的地震能力对结构两侧岩土参数的变化更为敏感。相关结论可为相关规范中地下结构抗震设计和性能限值的提高提供一定的指导。

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引用次数: 0

Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements 基于改进粒子群算法和极限学习机的稀疏测量方法预测开挖引起的侧向位移

IF 8.2 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-08-01 Epub Date: 2025-05-19 DOI: 10.1016/j.undsp.2025.02.004

Cheng Chen , Guan-Nian Chen , Song Feng , Xiao-Zhen Fan , Liang-Tong Zhan , Yun-Min Chen

Monitoring lateral displacement in deep excavation projects is crucial for structural stability and safety. Traditional methods, like manual inclinometers, are accurate but costly and labor-intensive. Automated systems provide real-time data but face challenges with dense sensor placement and high costs. This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. The IPSO-ELM approach utilizes sparse automated measurements to accurately predict lateral displacement profiles, minimizing the need for dense sensor deployment. A case study of a 30.2-m-deep excavation project in Hangzhou, China, demonstrates the method’s effectiveness. The results demonstrate that the IPSO-ELM model maintains high prediction accuracy, with low root mean square error (RMSE) and mean absolute error (MAE) values, even under conditions of sparse sensor placement. Across the entire test dataset, with a sensor spacing of 5.0 m, the model achieved maximum RMSE values ranging from 0.94 to 2.79 mm and maximum MAE values ranging from 0.77 to 2.18 mm, thereby showcasing its robustness and reliability in predicting lateral displacement. A detailed discussion was conducted on the errors associated with various sensor spacing intervals when implementing the proposed method. This study underscores the potential of IPSO-ELM as a cost-effective and reliable tool for automatic monitoring in increasingly complex urban excavation projects.

深基坑工程的侧向位移监测对结构的稳定和安全至关重要。传统的测量方法，比如手动测斜仪，虽然很精确，但成本高昂，而且需要耗费大量人力。自动化系统提供实时数据，但面临传感器密集和成本高的挑战。提出了一种基于改进粒子群优化算法的极限学习机（ELM）预测方法。IPSO-ELM方法利用稀疏的自动测量来准确预测横向位移剖面，最大限度地减少了对密集传感器部署的需求。以杭州某30.2 m深基坑工程为例，验证了该方法的有效性。结果表明，IPSO-ELM模型即使在传感器位置稀疏的情况下也能保持较高的预测精度，具有较低的均方根误差（RMSE）和平均绝对误差（MAE）值。在整个测试数据集中，在传感器间距为5.0 m的情况下，该模型的最大RMSE值为0.94 ~ 2.79 mm，最大MAE值为0.77 ~ 2.18 mm，显示了其在预测侧向位移方面的鲁棒性和可靠性。详细讨论了实现该方法时不同传感器间距所带来的误差。这项研究强调了IPSO-ELM在日益复杂的城市开挖工程中作为一种具有成本效益和可靠的自动监测工具的潜力。

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引用次数: 0

A multi-scale coupled method for nonlinear dynamic response analysis of mountain tunnels subjected to fault movement 断层运动作用下山地隧道非线性动力响应分析的多尺度耦合方法

IF 8.2 1区工程技术 Q1 ENGINEERING, CIVIL

Underground Space

Pub Date : 2025-08-01 Epub Date: 2025-04-02 DOI: 10.1016/j.undsp.2024.09.005

Zhongxian Liu , Jiaqiao Liu , Haitao Yu , Weiguo He

This paper introduces a novel two-step multi-scale coupled method for simulating the nonlinear dynamic behavior of a mountain tunnel subjected to fault movement. In the first step, the broadband seismic responses within a large-scale mountain-fault model can be accurately solved by the indirect boundary element method, converting them into effective input forces around the specified region of interest within the mountain. The second step involves finely simulating the nonlinear dynamic response of the tunnel cross-section in the designated region using the finite element method, with the implementation of a viscoelastic artificial boundary to absorb the reflection of scattered waves at truncated boundaries. Two verification processes are employed to validate the accuracy of the multi-scale coupled method. Furthermore, we illustrate the applicability and efficacy of the new method with an example involving the elastoplastic dynamic analysis of a mountain tunnel under the influence of normal fault movement. The presented example highlights the impact of fault motion parameters, including fault dislocation value and dip angle, on the responses of the mountain tunnel. The results demonstrate that the proposed multi-scale coupled method can achieve full-process seismic simulation, ranging from kilometer-scale fault rupture to centimeter-scale mountain tunnel section damage, with a considerably reduced computational expense.

本文介绍了一种新的两步多尺度耦合方法，用于模拟断层运动作用下山地隧道的非线性动力行为。第一步，采用间接边界元法精确求解大尺度山断层模型内的宽带地震响应，将其转化为山内指定感兴趣区域周围的有效输入力。第二步采用有限元方法精细模拟指定区域内隧道断面的非线性动力响应，采用粘弹性人工边界来吸收截断边界处散射波的反射。采用两个验证过程验证了多尺度耦合方法的准确性。最后，以某山地隧道正断层运动影响下的弹塑性动力分析为例，说明了该方法的适用性和有效性。该算例突出了断层位移值和断层倾角等断层运动参数对山间隧道响应的影响。结果表明，所提出的多尺度耦合方法可以实现从千米尺度断层破裂到厘米尺度山地隧道断面破坏的全过程地震模拟，且计算量大大降低。

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引用次数: 0