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Small-scale fire tests in the underwater tunnel section model with new sidewall smoke extraction 在水下隧道断面模型中进行小规模火灾试验,采用新型侧壁排烟方式
Pub Date : 2024-05-29 DOI: 10.1002/dug2.12102
Shunyu Yue, Ruifeng Miao, Huihang Cheng, Maohua Zhong, Xiujun Yang

The Shenzhen–Zhongshan Bridge is a 24-km-long bridge and tunnel system, including a 6.8-km-long super cross section subsea tunnel. To solve the smoke exhaust problem of a super large cross-section subsea tunnel, the tunnel has a new smoke exhaust system that combines a horizontal smoke exhaust cross section at the top and sidewall smoke exhaust holes. In order to evaluate the potential fire hazards of this type of tunnel, a 1:30 tunnel model was established and 140 small-scale experiments on underwater tunnel fires were conducted. By changing the fire power, fire location, and fan operation mode, different scenarios of submarine immersed tunnel fire were simulated and the related key parameters such as fire smoke diffusion behavior and smoke temperature distribution were studied. On this basis, the optimal smoke control strategy was proposed for different fire scenarios. The research results indicate that the new smoke exhaust system can fully utilize the smoke flow characteristics, significantly improve smoke exhaust efficiency, and increase available evacuation time, thus further enhancing the fire safety of super large cross-section subsea tunnels.

深圳-中山大桥桥隧系统全长 24 公里,其中超大断面海底隧道长 6.8 公里。为解决超大断面海底隧道的排烟问题,该隧道采用了新型排烟系统,即顶部水平排烟断面和侧壁排烟孔相结合的排烟方式。为了评估这种隧道潜在的火灾危险,我们建立了一个 1:30 的隧道模型,并进行了 140 次小型水下隧道火灾实验。通过改变火力、着火位置和风机运行模式,模拟了海底沉管隧道火灾的不同场景,并研究了火灾烟雾扩散行为和烟温分布等相关关键参数。在此基础上,提出了针对不同火灾场景的最优烟气控制策略。研究结果表明,新型排烟系统能充分利用烟流特性,显著提高排烟效率,增加可用疏散时间,从而进一步提高超大断面海底隧道的消防安全水平。
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引用次数: 0
Deep sea mineral resources and underground space as well as infrastructure for sustainable and liveable cities 深海矿产资源和地下空间以及可持续宜居城市的基础设施
Pub Date : 2024-05-27 DOI: 10.1002/dug2.12104
Jianguo Wang, Heping Xie, Chunfai Leung, Xiaozhao Li

This issue covers the papers on two special themes: (1) Mineral resources from deep sea—Science and Engineering and (2) Planning and development of underground space and infrastructure for sustainable and liveable cities.

The special theme of “Mineral resources from deep sea—Science and Engineering” is on the exploration and transport of mineral resources from deep sea. The mineral resources are rich in deep sea and their rational development and utilization can meet the needs of social and economic development. The security and strategy of deep-sea mineral resource exploration are important to the successful development of high-quality marine economy. However, deep-sea science and mineral resource exploitations confront many unknowns. This special theme aims to provide a platform for the exploration and exchange in research and engineering progresses and six papers were received, including four Original Research Papers, one Review Paper, and one Short Communication. The authors are from Australian Catholic University, National University of Singapore, Ocean University of China, China University of Mining and Technology, and so on.

The idea for this special theme originates from the First Young Scholars Symposium on Deep-Sea Science and Mineral Resources (2022). Deep Underground Science and Engineering (DUSE) collaborated with the conference organizer and launched a call for a special theme: Mineral Resources from Deep Sea—Science and Engineering. Guest Editors of this special theme are Prof. Jianhua Yue (China University of Mining and Technology), Prof. Yonggang Jia (Ocean University of China), Prof. Chunhui Tao (Second Institute of Oceanography, Ministry of Natural Resources, China), Prof. Haiyan Yang (China University of Mining and Technology), Prof. Honglei Shen (China University of Mining and Technology), and Prof. Zhuangcai Tian (China University of Mining and Technology).

The special theme of “Planning and development of underground space and infrastructure for sustainable and liveable cities” is on city development from the prospects of underground space and infrastructure. The utilization of urban underground space for accommodating urban functions, through developing underground commercial, transport, and public infrastructure, has been a common practice in urban development in past decades. Increased migration of populations to cities brings many urbanization problems, such as inadequate land and infrastructure, air and noise pollution, traffic congestion, and degraded environmental quality, thus providing an opportunity for underground infrastructure as an attractive solution to these problems. As a relatively new dimension of cities, underground space has been widely recognized as a valuable resource for city development. Urban underground space utilization is an effective way of developing and redesigning cities, promoting sustainable urban development, and building liveable cities. Underground infrastruc

本期论文涉及两个专题:(1) 深海矿产资源--科学与工程;(2) 可持续宜居城市的地下空间和基础设施规划与开发。"深海矿产资源--科学与工程 "专题涉及深海矿产资源的勘探与运输。深海矿产资源丰富,合理开发利用可以满足社会经济发展的需要。深海矿产资源勘探的安全和战略对于成功发展高质量的海洋经济具有重要意义。然而,深海科学和矿产资源开发面临诸多未知。本专题旨在为研究和工程进展提供一个探索和交流的平台,共收到 6 篇论文,包括 4 篇原创研究论文、1 篇综述论文和 1 篇短篇通讯。论文作者分别来自澳大利亚天主教大学、新加坡国立大学、中国海洋大学、中国矿业大学等。深海科学与工程(Deep Underground Science and Engineering,DUSE)与会议主办方合作,发起了专题征集活动:深海科学与工程的矿产资源。该专题的特邀编辑有:岳建华教授(中国矿业大学)、贾永刚教授(中国海洋大学)、陶春辉教授(中国自然资源部第二海洋研究所)、杨海燕教授(中国矿业大学)、沈红磊教授(中国海洋大学)。"可持续宜居城市的地下空间与基础设施规划与开发 "专题从地下空间与基础设施的前景出发,探讨城市发展问题。通过开发地下商业、交通和公共基础设施,利用城市地下空间容纳城市功能,是过去几十年城市发展的普遍做法。人口向城市迁移的增加带来了许多城市化问题,如土地和基础设施不足、空气和噪音污染、交通拥堵、环境质量下降等,从而为地下基础设施作为解决这些问题的一种有吸引力的方法提供了机会。作为城市的一个相对较新的层面,地下空间已被广泛认为是城市发展的宝贵资源。利用城市地下空间是开发和重新设计城市、促进城市可持续发展和建设宜居城市的有效途径。地下基础设施对土地利用、社会、环境和经济发展以及城市可持续发展都有相当大的影响。这些都是需要探讨的重要课题。此外,在不同城市环境中开发的地下空间和基础设施可能具有独特的特点,需要进一步研究。本期刊载了四篇关于这一特别主题的研究论文:两篇来自本次特别主题征集,两篇来自常规投稿。我们将这些论文放在一起是为了分享相似的知识。本期特邀编辑是澳大利亚格里菲斯大学的崔建强博士、中国重庆大学的翁妙成博士和英国阿伯丁大学的林东博士。DUSE 感谢特邀编辑的努力,并向所有作者和编辑致以特别的谢意。我们期待在未来与大家就深层地下科学与工程领域有趣的热点话题开展合作。
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引用次数: 0
Application of machine learning and deep learning in geothermal resource development: Trends and perspectives 机器学习和深度学习在地热资源开发中的应用:趋势与前景
Pub Date : 2024-05-23 DOI: 10.1002/dug2.12098
Abdulrahman Al-Fakih, Abdulazeez Abdulraheem, Sanlinn Kaka

This study delves into the latest advancements in machine learning and deep learning applications in geothermal resource development, extending the analysis up to 2024. It focuses on artificial intelligence's transformative role in the geothermal industry, analyzing recent literature from Scopus and Google Scholar to identify emerging trends, challenges, and future opportunities. The results reveal a marked increase in artificial intelligence (AI) applications, particularly in reservoir engineering, with significant advancements observed post-2019. This study highlights AI's potential in enhancing drilling and exploration, emphasizing the integration of detailed case studies and practical applications. It also underscores the importance of ongoing research and tailored AI applications, in light of the rapid technological advancements and future trends in the field.

本研究深入探讨了机器学习和深度学习在地热资源开发中应用的最新进展,并将分析延伸至 2024 年。研究重点关注人工智能在地热行业中的变革作用,分析了 Scopus 和谷歌学术的最新文献,以确定新兴趋势、挑战和未来机遇。研究结果表明,人工智能(AI)的应用明显增加,尤其是在储层工程方面,2019 年后将有显著进步。本研究强调了人工智能在加强钻井和勘探方面的潜力,同时强调了详细案例研究与实际应用的结合。鉴于该领域的快速技术进步和未来趋势,它还强调了正在进行的研究和量身定制的人工智能应用的重要性。
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引用次数: 0
Performance analysis of deep borehole heat exchangers for decarbonization of heating systems 用于供热系统脱碳的深孔热交换器性能分析
Pub Date : 2024-05-16 DOI: 10.1002/dug2.12101
Andreas E. D. Lund

Meeting the climate change mitigation targets will require a substantial shift from fossil to clean fuels in the heating sector. Heat pumps with deep borehole exchangers are a promising solution to reduce emissions. Here the thermal behavior of deep borehole exchangers (DBHEs) ranging from 1 to 2 km was analyzed for various heat flow profiles. A strong correlation between thermal energy extraction and power output from DBHEs was found, also influenced by the heating profile employed. Longer operating time over the year typically resulted in higher energy production, while shorter one yielded higher average thermal power output, highlighting the importance of the choice of heating strategy and system design for optimal performance of DBHEs. Short breaks in operation for regenerating the borehole, for example, with waste heat, proved to be favorable for the performance yielding an overall heat output close to the same as with continuous extraction of heat. The results demonstrate the usefulness of deep boreholes for dense urban areas with less available space. As the heat production from a single DBHE in Finnish conditions ranges from half up to even a few GWh a year, the technology is best suitable for larger heat loads.

要实现减缓气候变化的目标,供热部门就必须从使用化石燃料大幅转向使用清洁燃料。采用深孔交换器的热泵是一种很有前景的减排解决方案。本文分析了 1 至 2 千米深孔交换器(DBHE)在不同热流剖面下的热行为。研究发现,DBHE 的热能提取与功率输出之间存在很强的相关性,这也受到所采用的加热曲线的影响。全年较长的运行时间通常会产生较高的能量产量,而较短的运行时间则会产生较高的平均热功率输出,这凸显了选择加热策略和系统设计对于 DBHE 最佳性能的重要性。事实证明,短时间中断运行以利用余热等方式对井眼进行再生有利于提高性能,从而使总热量输出接近连续采热时的热量输出。结果表明,在可用空间较小的密集城市地区,深井非常有用。在芬兰的条件下,单个 DBHE 的年产热量从一半到几千兆瓦时不等,因此该技术最适合较大的热负荷。
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引用次数: 0
Fluid-rock interaction experiments with andesite at 100°C for potential carbon storage in geothermal reservoirs 安山岩在 100°C 温度下的流体-岩石相互作用实验,用于地热储层中潜在的碳储存
Pub Date : 2024-05-08 DOI: 10.1002/dug2.12097
Grace E. Belshaw, Elisabeth Steer, Yukun Ji, Herwin Azis, Benyamin Sapiie, Bagus Muljadi, Veerle Vandeginste

Geothermal energy extraction often results in the release of naturally occurring carbon dioxide (CO2) as a byproduct. Research on carbon storage using volcanic rock types other than basalt under both acidic and elevated temperature conditions has been limited so far. Our study uses batch reactor experiments at 100°C to investigate the dissolution of andesite rock samples obtained from an active geothermal reservoir in Sumatra (Indonesia). The samples are subjected to reactions with neutral-pH fluids and acidic fluids, mimicking the geochemical responses upon reinjection of geothermal fluids, either without or with dissolved acidic gases, respectively. Chemical elemental analysis reveals the release of Ca2+ ions into the fluids through the dissolution of feldspar. The overall dissolution rate of the rock samples is 2.4 × 10–11 to 4.2 × 10–11 mol/(m2 · s), based on the Si release during the initial 7 h of the experiment. The dissolution rates are about two orders of magnitude lower than those reported for basaltic rocks under similar reaction conditions. This study offers valuable insights into the potential utilization of andesite reservoirs for effective CO2 storage via mineralization.

地热能源的开采通常会释放出天然生成的二氧化碳(CO2)作为副产品。迄今为止,利用玄武岩以外的火山岩类型在酸性和高温条件下进行碳储存的研究还很有限。我们的研究使用 100°C 的批量反应器实验来研究从苏门答腊岛(印度尼西亚)一个活跃地热储层中获得的安山岩岩石样本的溶解情况。样品分别与中性pH流体和酸性流体发生反应,模拟地热流体回注时的地球化学反应,其中分别不含或含有溶解的酸性气体。化学元素分析表明,Ca2+ 离子通过长石的溶解释放到流体中。根据实验最初 7 小时的硅释放量,岩石样本的总体溶解速率为 2.4 × 10-11 mol/(m2 - s) 至 4.2 × 10-11 mol/(m2 - s)。这些溶解速率比类似反应条件下玄武岩的溶解速率低两个数量级。这项研究为安山岩储层通过矿化作用有效封存二氧化碳的潜在利用提供了宝贵的见解。
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引用次数: 0
Interaction between internal solitary waves and the seafloor in the deep sea 深海内部孤波与海底之间的相互作用
Pub Date : 2024-05-06 DOI: 10.1002/dug2.12095
Zhuangcai Tian, Jinjian Huang, Jiaming Xiang, Shaotong Zhang, Jinran Wu, Xiaolei Liu, Tingting Luo, Jianhua Yue

Internal solitary wave (ISW), as a typical marine dynamic process in the deep sea, widely exists in oceans and marginal seas worldwide. The interaction between ISW and the seafloor mainly occurs in the bottom boundary layer. For the seabed boundary layer of the deep sea, ISW is the most important dynamic process. This study analyzed the current status, hotspots, and frontiers of research on the interaction between ISW and the seafloor by CiteSpace. Focusing on the action of ISW on the seabed, such as transformation and reaction, a large amount of research work and results were systematically analyzed and summarized. On this basis, this study analyzed the wave–wave interaction and interaction between ISW and the bedform or slope of the seabed, which provided a new perspective for an in-depth understanding of the interaction between ISW and the seafloor. Finally, the latest research results of the bottom boundary layer and marine engineering stability by ISW were introduced, and the unresolved problems in the current research work were summarized. This study provides a valuable reference for further research on the hazards of ISW to marine engineering geology.

内孤波(ISW)作为一种典型的深海海洋动力过程,广泛存在于世界各地的大洋和边缘海中。内孤波与海底的相互作用主要发生在海底边界层。对于深海海底边界层而言,ISW 是最重要的动力过程。本研究通过 CiteSpace 分析了 ISW 与海底相互作用的研究现状、热点和前沿。围绕 ISW 对海底的作用,如转化和反应,系统分析和总结了大量的研究工作和成果。在此基础上,本研究分析了波浪相互作用以及 ISW 与海底床形或斜坡之间的相互作用,为深入理解 ISW 与海底之间的相互作用提供了新的视角。最后,介绍了 ISW 对海底边界层和海洋工程稳定性的最新研究成果,并总结了当前研究工作中尚未解决的问题。本研究为进一步研究 ISW 对海洋工程地质的危害提供了有价值的参考。
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引用次数: 0
Deformation monitoring at shield tunnel joints: Laboratory test and discrete element simulation 盾构隧道接缝处的变形监测:实验室测试和离散元模拟
Pub Date : 2024-04-18 DOI: 10.1002/dug2.12092
Maoyi Mao, Xiaowei Yang, Chun Liu, Tao Zhao, Hui Liu
Shield tunnel, composed of several segments, is widely used in urban underground engineering. When the tunnel is under load, relative displacement occurs between adjacent segments. In the past, distributed optical fiber sensing technology was used to perform strain monitoring, but there is an urgent need to determine how to transform strain into displacement. In this study, optical frequency domain reflectometry was applied in laboratory tests. Aiming at the shear process and center settlement process of shield tunnel segments, two kinds of quantitative calculation methods were put forward to carry out a quantitative analysis. Meanwhile, the laboratory test process was simulated numerically utilizing the discrete element numerical analysis method. Optical fiber, an atypical geotechnical material, was innovatively applied for discrete element modeling and numerical simulation. The results show that the measured displacement of the dial gauge, the calculated results of the numerical model, and the displacement quantitatively calculated from the optical fiber data agree with each other in general. The latter two methods can potentially be utilized in engineering application of deformation monitoring at shield tunnel joints, but need to be further calibrated and adjusted in detail.
盾构隧道由多个区段组成,广泛应用于城市地下工程。当隧道承受荷载时,相邻段之间会产生相对位移。过去,人们使用分布式光纤传感技术来进行应变监测,但如何将应变转化为位移却亟待解决。本研究将光学频域反射仪应用于实验室测试。针对盾构隧道节段的剪切过程和中心沉降过程,提出了两种定量计算方法进行定量分析。同时,利用离散元数值分析方法对实验室试验过程进行了数值模拟。创新性地将非典型岩土材料光纤应用于离散元建模和数值模拟。结果表明,千分表测量的位移、数值模型的计算结果以及根据光纤数据定量计算的位移基本吻合。后两种方法可用于盾构隧道接缝变形监测的工程应用,但还需要进一步的详细校准和调整。
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引用次数: 0
Performance evaluation of rock fragmentation prediction based on RF‐BOA, AdaBoost‐BOA, GBoost‐BOA, and ERT‐BOA hybrid models 基于 RF-BOA、AdaBoost-BOA、GBoost-BOA 和 ERT-BOA 混合模型的岩石破碎预测性能评估
Pub Date : 2024-04-15 DOI: 10.1002/dug2.12089
Junjie Zhao, Diyuan Li, Jian Zhou, D. J. Armaghani, Aohui Zhou
Rock fragmentation is an important indicator for assessing the quality of blasting operations. However, accurate prediction of rock fragmentation after blasting is challenging due to the complicated blasting parameters and rock properties. For this reason, optimized by the Bayesian optimization algorithm (BOA), four hybrid machine learning models, including random forest, adaptive boosting, gradient boosting, and extremely randomized trees, were developed in this study. A total of 102 data sets with seven input parameters (spacing‐to‐burden ratio, hole depth‐to‐burden ratio, burden‐to‐hole diameter ratio, stemming length‐to‐burden ratio, powder factor, in situ block size, and elastic modulus) and one output parameter (rock fragment mean size, X50) were adopted to train and validate the predictive models. The root mean square error (RMSE), the mean absolute error (MAE), and the coefficient of determination () were used as the evaluation metrics. The evaluation results demonstrated that the hybrid models showed superior performance than the standalone models. The hybrid model consisting of gradient boosting and BOA (GBoost‐BOA) achieved the best prediction results compared with the other hybrid models, with the highest R2 value of 0.96 and the smallest values of RMSE and MAE of 0.03 and 0.02, respectively. Furthermore, sensitivity analysis was carried out to study the effects of input variables on rock fragmentation. In situ block size (XB), elastic modulus (E), and stemming length‐to‐burden ratio (T/B) were set as the main influencing factors. The proposed hybrid model provided a reliable prediction result and thus could be considered an alternative approach for rock fragment prediction in mining engineering.
岩石破碎是评估爆破作业质量的一个重要指标。然而,由于爆破参数和岩石特性的复杂性,准确预测爆破后的岩石破碎率具有挑战性。为此,本研究采用贝叶斯优化算法(BOA)进行优化,开发了四种混合机器学习模型,包括随机森林、自适应提升、梯度提升和极随机树。研究共采用了 102 组数据,包括 7 个输入参数(间距与荷载比、孔深与荷载比、荷载与孔径比、茎杆长度与荷载比、粉末系数、原位块体尺寸和弹性模量)和 1 个输出参数(岩石碎块平均尺寸 X50),对预测模型进行了训练和验证。采用均方根误差(RMSE)、平均绝对误差(MAE)和判定系数()作为评价指标。评估结果表明,混合模型的性能优于独立模型。与其他混合模型相比,由梯度提升和 BOA 组成的混合模型(GBoost-BOA)取得了最好的预测结果,其 R2 值最高,为 0.96,RMSE 和 MAE 值最小,分别为 0.03 和 0.02。此外,还进行了敏感性分析,以研究输入变量对岩石破碎的影响。将原位块度(XB)、弹性模量(E)和茎杆长度与负载比(T/B)设定为主要影响因素。所提出的混合模型提供了可靠的预测结果,因此可被视为采矿工程中岩石破碎预测的替代方法。
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引用次数: 0
Assessment for shallow and large tunnel construction in weak ground conditions: Application of tunnel boring machines 评估软弱地层条件下的浅层和大型隧道施工:隧道掘进机的应用
Pub Date : 2024-04-14 DOI: 10.1002/dug2.12083
S. Karahan, C. Gokceoglu
With recent technological advancements, tunnel boring machines (TBM) have developed and exhibited high performance in large diameters and weak ground conditions. Tunnels are crucial structures that significantly influence the timelines of highway and railway projects. Therefore, the construction of tunnels with TBMs becomes a preferred option. In this study, a comparative analysis between TBM and the New Austrian Tunneling Method (NATM) for tunnel construction is performed in the construction of the T1 tunnel with a diameter of 13 m, which is the longest tunnel in the Eşme‐Salihli section of Ankara‐İzmir High‐Speed Railway Project (Türkiye). The selection of TBM type, measures taken in problematic sections, and application issues of TBM are discussed. The impact of correct description of geological and geotechnical conditions on both selection and performance of TBM is presented. An earth pressure balanced type TBM is chosen for the construction of the T1 tunnel. Because of the additional engineering measures taken before excavation in problematic areas, the tunnel was completed with great success within the initially planned timeframe. From this point of view, this study is an important case and may contribute to worldwide tunneling literature.
随着近年来技术的进步,隧道掘进机(TBM)得到了发展,并在大直径和软弱地层条件下表现出了高性能。隧道是至关重要的结构,对公路和铁路项目的工期有重大影响。因此,使用隧道掘进机建造隧道成为首选。本研究以安卡拉-伊兹密尔高速铁路项目(图尔基耶)埃斯梅-萨利赫利段最长的隧道--直径 13 米的 T1 号隧道的施工为例,对隧道施工中的 TBM 和新奥地利隧道法(NATM)进行了比较分析。讨论了 TBM 类型的选择、在问题路段采取的措施以及 TBM 的应用问题。介绍了正确描述地质和岩土条件对 TBM 选择和性能的影响。T1 隧道的施工选择了土压平衡型 TBM。由于在问题区域开挖前采取了额外的工程措施,隧道在最初计划的时间内顺利完工。从这个角度来看,这项研究是一个重要案例,可为世界隧道工程文献做出贡献。
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引用次数: 0
ALSTNet: Autoencoder fused long‐ and short‐term time‐series network for the prediction of tunnel structure ALSTNet:用于隧道结构预测的自动编码器融合长短期时间序列网络
Pub Date : 2024-04-04 DOI: 10.1002/dug2.12081
Bo-wen Du, Haohan Liang, Yuhang Wang, Junchen Ye, X. Tan, Weizhong Chen
It is crucial to predict future mechanical behaviors for the prevention of structural disasters. Especially for underground construction, the structural mechanical behaviors are affected by multiple internal and external factors due to the complex conditions. Given that the existing models fail to take into account all the factors and accurate prediction of the multiple time series simultaneously is difficult using these models, this study proposed an improved prediction model through the autoencoder fused long‐ and short‐term time‐series network driven by the mass number of monitoring data. Then, the proposed model was formalized on multiple time series of strain monitoring data. Also, the discussion analysis with a classical baseline and an ablation experiment was conducted to verify the effectiveness of the prediction model. As the results indicate, the proposed model shows obvious superiority in predicting the future mechanical behaviors of structures. As a case study, the presented model was applied to the Nanjing Dinghuaimen tunnel to predict the stain variation on a different time scale in the future.
预测未来的力学行为对于预防结构性灾害至关重要。尤其是地下建筑,由于条件复杂,结构力学行为受到多种内外因素的影响。鉴于现有模型无法考虑所有因素,且使用这些模型很难同时对多个时间序列进行准确预测,本研究提出了一种改进的预测模型,即在大量监测数据的驱动下,通过自动编码器融合长期和短期时间序列网络进行预测。然后,在应变监测数据的多个时间序列上对所提出的模型进行了形式化。此外,还与经典基线和烧蚀实验进行了讨论分析,以验证预测模型的有效性。结果表明,所提出的模型在预测结构的未来机械行为方面显示出明显的优越性。作为案例研究,所提出的模型被应用于南京定淮门隧道,以预测未来不同时间尺度上的污渍变化。
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引用次数: 0
期刊
Deep Underground Science and Engineering
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