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学者姓名：龚秋明
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摘要 ：
隧道施工中,岩石的磨蚀性是影响各类破岩工具磨损的主要因素之一.国际上设计了许多评价岩石磨蚀性的小型试验,其中Cerchar试验因其操作简易性获得了普遍应用,其结果CAI(Cerchar Abrasivity Index)值能够较好地预测破岩工具连续、平稳的正常磨损,目前我国也广泛采用该试验进行岩石磨蚀性评价.由于我国引进该试验时间较晚,尚无国家试验规范,CAI值的等级划分不明确.本文收集了国际上各试验室与机构使用的分级标准,从CAI值分级所用的钢针硬度、CAI值对应的破岩工具磨损量、大量试验数据的分布3个方面综合比较,认为国际岩石力学协会推荐的CAI值分级比较合理.本文对国内Cerchar试验规范创立、岩石磨蚀性评价具有借鉴意义.
关键词 ：
CAI分级 CAI分级 磨蚀性试验 磨蚀性试验 工具磨损 工具磨损
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| GB/T 7714 | 龚秋明 , 许弘毅 , 李立民 . 岩石磨蚀性指数分级讨论 [J]. | 地下空间与工程学报 , 2021 , 17 (3) : 748-758 . |
| MLA | 龚秋明 等. "岩石磨蚀性指数分级讨论" . | 地下空间与工程学报 17 . 3 (2021) : 748-758 . |
| APA | 龚秋明 , 许弘毅 , 李立民 . 岩石磨蚀性指数分级讨论 . | 地下空间与工程学报 , 2021 , 17 (3) , 748-758 . |
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摘要 ：
以实际工程为背景,设计了具有单一卵石层和2个既有隧道的试验模型.基于自主研发的土压平衡盾构试验平台,开展了卵石地层盾构下穿既有马蹄形隧道和矩形隧道的模型试验.在试验过程中,记录了盾构机的施工动力和排土量,同时监测了试验模型的地表沉降,以及既有隧道的应变和作用在其上的土压力.通过盾构机施工动力和排土量的变化,分析了既有隧道对盾构施工状态的影响.利用盾构下穿过程中盾构排土量的变化,解释了既有隧道周围卵石土体发生塌落破坏的原因.基于实测的地表沉降和作用在既有隧道上土压力的变化规律,揭示了盾构下穿过程中既有隧道与卵石土体的相互作用机理.
关键词 ：
卵石地层 卵石地层 地表沉降 地表沉降 既有隧道 既有隧道 模型试验 模型试验 盾构下穿 盾构下穿 隧道变形 隧道变形
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| GB/T 7714 | 林庆涛 , 路德春 , 雷春明 et al. 下穿施工时盾构-卵石地层-既有隧道相互作用模型试验研究 [J]. | 北京工业大学学报 , 2021 , 47 (04) : 328-337 . |
| MLA | 林庆涛 et al. "下穿施工时盾构-卵石地层-既有隧道相互作用模型试验研究" . | 北京工业大学学报 47 . 04 (2021) : 328-337 . |
| APA | 林庆涛 , 路德春 , 雷春明 , 李晓强 , 苗金波 , 龚秋明 et al. 下穿施工时盾构-卵石地层-既有隧道相互作用模型试验研究 . | 北京工业大学学报 , 2021 , 47 (04) , 328-337 . |
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摘要 ：
盾构隧道施工刀盘状态实时监测系统研制
关键词 ：
刀盘状态 刀盘状态 实时监测系统 实时监测系统 滚刀磨损 滚刀磨损 滚刀转速 滚刀转速 盾构机 盾构机
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| GB/T 7714 | 龚秋明 , 王庆欢 , 王杜娟 et al. 盾构隧道施工刀盘状态实时监测系统研制 [J]. | 龚秋明 , 2021 , 58 (2) : 41-50 . |
| MLA | 龚秋明 et al. "盾构隧道施工刀盘状态实时监测系统研制" . | 龚秋明 58 . 2 (2021) : 41-50 . |
| APA | 龚秋明 , 王庆欢 , 王杜娟 , 邱海峰 , 吴帆 , 现代隧道技术 . 盾构隧道施工刀盘状态实时监测系统研制 . | 龚秋明 , 2021 , 58 (2) , 41-50 . |
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摘要 ：
下穿施工时盾构-卵石地层-既有隧道相互作用模型试验研究
关键词 ：
卵石地层 卵石地层 地表沉降 地表沉降 既有隧道 既有隧道 模型试验 模型试验 盾构下穿 盾构下穿 隧道变形 隧道变形
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| GB/T 7714 | 路德春 , 雷春明 , 李晓强 et al. 下穿施工时盾构-卵石地层-既有隧道相互作用模型试验研究 [J]. | 路德春 , 2021 , 47 (4) : 328-337 . |
| MLA | 路德春 et al. "下穿施工时盾构-卵石地层-既有隧道相互作用模型试验研究" . | 路德春 47 . 4 (2021) : 328-337 . |
| APA | 路德春 , 雷春明 , 李晓强 , 苗金波 , 龚秋明 , 杜修力 et al. 下穿施工时盾构-卵石地层-既有隧道相互作用模型试验研究 . | 路德春 , 2021 , 47 (4) , 328-337 . |
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摘要 ：
A new concept called the transmission ratio of ground volume loss (TRGVL) is proposed to describe the variation law of ground volume loss with depth above the tunnel. Based on the developed Gaussian function, the formula for TRGVL is deduced. Further, the first-order derivative of TRGVL is presented to evaluate the dilation and compression degree of the soil at any depth above the tunnel. A total of 15 cases, involving eight field project cases and seven model test cases, are investigated to validate rationality of the proposed formula. The results of field projects and model test cases indicate variation in TRGVL presents four forms. By analysing the volumetric deformation of the soil above the tunnel, formation mechanism of the each form of TRGVL is revealed. Finally, the evolution of the four forms of TRGVL is used to evaluate the disturbance degree of the soil above the tunnel.
关键词 ：
Developed Gaussian function Developed Gaussian function Ground volume loss Ground volume loss Soil volumetric deformation Soil volumetric deformation Surface and subsurface settlement Surface and subsurface settlement Tunnel excavation Tunnel excavation
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| GB/T 7714 | Lin, Qingtao , Tian, Yu , Lu, Dechun et al. A prediction method of ground volume loss variation with depth induced by tunnel excavation [J]. | ACTA GEOTECHNICA , 2021 , 16 (11) : 3689-3707 . |
| MLA | Lin, Qingtao et al. "A prediction method of ground volume loss variation with depth induced by tunnel excavation" . | ACTA GEOTECHNICA 16 . 11 (2021) : 3689-3707 . |
| APA | Lin, Qingtao , Tian, Yu , Lu, Dechun , Gong, Qiuming , Du, Xiuli , Gao, Zhiwei . A prediction method of ground volume loss variation with depth induced by tunnel excavation . | ACTA GEOTECHNICA , 2021 , 16 (11) , 3689-3707 . |
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摘要 ：
Real-time muck analysis is of great importance for assisting tunnel boring machines (TBMs) in intelligent tunneling. Typically, muck images are characterized by low contrast, large appearance differences, and object overlap, posing a great challenge to image segmentation. In this study, a deep learning-based approach, composed of a dual UNet with multi-scale inputs and side-output (MSD-UNet) and a post-processing algorithm, was proposed to solve the automatic segmentation of muck images and estimate the size and shape of rock chips. The MSD-UNet used a dual structure with two decoders to segment the regions and boundaries of rock chips in a unified network, aiming to solve the overlapping problem of rock chips by introducing the boundary information. It also integrated a multi-scale input and side outputs to enhance low-level image features and supervise the training of early layers of the network, respectively. An integrated loss function based on generalized dice loss was developed to solve the class imbalance problem. The multi-radius erosion and seed filling algorithms were employed to further separate the connected chips in the post-processing. To evaluate the effectiveness of the method, a dataset containing various muck images collected from a TBM construction site was set up, and the MSD-UNet was trained and tested. Experimental results showed that the segmentation using the proposed approach outperformed those of using U-Net and comparable conventional methods. It achieved the highest F1score of 0.867 and 0.640 on the region and boundary task respectively, and an average Hausdorff distance of 3.59 mm for the rock chip instance. The proposed approach can process a 2,048 x 2,048 image in about 4 s and can nearly meet the requirement of real-time TBM muck image analysis.
关键词 ：
Image segmentation Image segmentation Intelligent TBM tunneling Intelligent TBM tunneling MSD-UNet MSD-UNet Real-time analysis Real-time analysis Size distribution Size distribution
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| GB/T 7714 | Zhou, Xiaoxiong , Gong, Qiuming , Liu, Yongqiang et al. Automatic segmentation of TBM muck images via a deep-learning approach to estimate the size and shape of rock chips [J]. | AUTOMATION IN CONSTRUCTION , 2021 , 126 . |
| MLA | Zhou, Xiaoxiong et al. "Automatic segmentation of TBM muck images via a deep-learning approach to estimate the size and shape of rock chips" . | AUTOMATION IN CONSTRUCTION 126 (2021) . |
| APA | Zhou, Xiaoxiong , Gong, Qiuming , Liu, Yongqiang , Yin, Lijun . Automatic segmentation of TBM muck images via a deep-learning approach to estimate the size and shape of rock chips . | AUTOMATION IN CONSTRUCTION , 2021 , 126 . |
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摘要 ：
The initial stress of the surrounding rock mass will be redistributed during TBM tunneling in a deep tunnel. This process may induce brittle failure of the surrounding rock mass, which has a great impact on TBM construction. The southern section of the Yinhan Water Conveyance Tunnel is mainly composed of massive to intact granite, with a maximum overburden depth of nearly 2000 m. The paper discussed in detail the relationship between various brittle failure degrees at the typical tunnel faces and TBM performance. The typical patterns, such as undamaged, slabbing, and strain rockburst at the tunnel face, and the corresponding characteristics of the TBM performance parameters were revealed. As the severity of damage increases, the rock mass boreability is improved, the cutterhead thrust is reduced, and the penetration increases, but there is an upper limit. It is noteworthy that the field penetration index (FPI) fluctuation expressed by the coefficient of variation (CV) varies significantly in different stress states. Based on the excavation response of TBM, a Rockburst Warning Index (RWI) was proposed to assess the brittle failure degree of the excavated rock mass in real-time. The results of the study can provide some insights into the prediction of TBM performance and the early warning of rockburst in deep-buried hard rock grounds.
关键词 ：
Brittle failure Brittle failure Hard rock Hard rock In-situ stress In-situ stress Rockburst warning index (RWI) Rockburst warning index (RWI) TBM performance TBM performance
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| GB/T 7714 | Lu, Jianwei , Gong, Qiuming , Yin, Lijun et al. Study on the tunneling response of TBM in stressed granite rock mass in Yinhan Water Conveyance tunnel [J]. | TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY , 2021 , 118 . |
| MLA | Lu, Jianwei et al. "Study on the tunneling response of TBM in stressed granite rock mass in Yinhan Water Conveyance tunnel" . | TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 118 (2021) . |
| APA | Lu, Jianwei , Gong, Qiuming , Yin, Lijun , Zhou, Xiaoxiong . Study on the tunneling response of TBM in stressed granite rock mass in Yinhan Water Conveyance tunnel . | TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY , 2021 , 118 . |
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摘要 ：
断层作为TBM掘进过程中经常遇到的一种不利地质条件,不仅可能导致TBM掘进作业时间降低,甚至有可能导致TBM长时间卡机.为研究不同规模断层对TBM施工的影响,基于吉林引松供水工程四标段TBM施工段和引汉济渭引水隧洞岭北TBM施工段及收集到的大规模断层TBM施工案例,建立了TBM施工数据库.分析了断层宽度和断层与隧道轴线夹角对TBM利用率的影响,并根据TBM利用率的大小将断层分成五个等级,研究分析了不同等级断层对TBM施工参数的影响.结果表明,断层等级越高,TBM单刀推力、刀盘扭矩、刀盘转速、施工进度、利用率越小,但是掘进速度、贯入度越大,说明断层的存在有利于TBM的破岩作用,但是会导致TBM利用率降低,从而减慢TBM施工进度.
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| GB/T 7714 | 龚秋明 , 王瑜 , 卢建炜 et al. 基于对TBM隧道施工影响的断层带初步分级 [J]. | 铁道学报 , 2021 , 43 (9) : 153-159 . |
| MLA | 龚秋明 et al. "基于对TBM隧道施工影响的断层带初步分级" . | 铁道学报 43 . 9 (2021) : 153-159 . |
| APA | 龚秋明 , 王瑜 , 卢建炜 , 吴帆 , 许弘毅 , 班超 . 基于对TBM隧道施工影响的断层带初步分级 . | 铁道学报 , 2021 , 43 (9) , 153-159 . |
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摘要 ：
The rock mass classification methods developed to evaluate rock mass stability and tunnel support design for blast and drill tunnels are not suitable to guide tunneling by tunnel boring machine (TBM), such as selection of TBM types, determination of construction scheme and so on. By comprehensively considering the rock mass boreability and stability, a modified rock mass classification system for TBM tunnels is proposed on the basis of the hydropower rock mass classification (HC) method of China. The input parameters are five rock mass parameters as the same as the HC method. In addition, the tunnel diameter is needed to estimate the TBM advance rate. The structure and parameter determination of the classification system are explained and statistically analyzed in details. This system can be applied to evaluate the feasibility of TBM construction and serve as the basis for selection of TBM types and design parameters in the pre-construction phase. Furthermore, it can also be applied to estimate TBM performance and guide tunnel support for a given ground condition in the design phase, and to optimize TBM operational parameters during the construction phase as well. An example is presented to illustrate the application of the proposed system. The limitations of the proposed system and further studies are also discussed. © 2020 Elsevier Ltd
关键词 ：
Boring machines (machine tools) Boring machines (machine tools) Construction equipment Construction equipment Drilling machines (machine tools) Drilling machines (machine tools) Rock mechanics Rock mechanics Rocks Rocks Tunnels Tunnels
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| GB/T 7714 | Gong, Qiuming , Lu, Jianwei , Xu, Hongyi et al. A modified rock mass classification system for TBM tunnels and tunneling based on the HC method of China [J]. | International Journal of Rock Mechanics and Mining Sciences , 2021 , 137 . |
| MLA | Gong, Qiuming et al. "A modified rock mass classification system for TBM tunnels and tunneling based on the HC method of China" . | International Journal of Rock Mechanics and Mining Sciences 137 (2021) . |
| APA | Gong, Qiuming , Lu, Jianwei , Xu, Hongyi , Chen, Zuyu , Zhou, Xiaoxiong , Han, Bei . A modified rock mass classification system for TBM tunnels and tunneling based on the HC method of China . | International Journal of Rock Mechanics and Mining Sciences , 2021 , 137 . |
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摘要 ：
Intelligent tunnelling has become an important direction for the development of TBM technology recently. As a result of the interaction between rock mass and TBM cutterhead, mucks are very important for predicting rock mass conditions and evaluating rock breaking efficiency. A real-time muck analysis system for assistant intelligence TBM tunnelling is proposed in this paper. Machine vision was applied to take the muck images continuously in the high-speed conveyor belt. The image segmentation and feature extraction of the mucks are conducted by using a deep learning algorithm. The proposed system also measured the mass and volume flow of the muck by installing a belt scale and a scanner to monitor the stability of the rock mass on the tunnel face. After the system was completed, it was installed on an indoor simulation experimental platform. A series of experiments were conducted to verify the design functions and measurement accuracy. Additionally, the system was applied to a TBM tunnelling project. The application results showed that the proposed system reached its design requirements and functions, and can provide muck data support for further assistant intelligent TBM tunnelling. © 2020 Elsevier Ltd
关键词 ：
Belt conveyors Belt conveyors Deep learning Deep learning Image segmentation Image segmentation Learning algorithms Learning algorithms Rock mechanics Rock mechanics Rocks Rocks
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| GB/T 7714 | Gong, Qiuming , Zhou, Xiaoxiong , Liu, Yongqiang et al. Development of a real-time muck analysis system for assistant intelligence TBM tunnelling [J]. | Tunnelling and Underground Space Technology , 2021 , 107 . |
| MLA | Gong, Qiuming et al. "Development of a real-time muck analysis system for assistant intelligence TBM tunnelling" . | Tunnelling and Underground Space Technology 107 (2021) . |
| APA | Gong, Qiuming , Zhou, Xiaoxiong , Liu, Yongqiang , Han, Bei , Yin, Lijun . Development of a real-time muck analysis system for assistant intelligence TBM tunnelling . | Tunnelling and Underground Space Technology , 2021 , 107 . |
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