Underground Space最新文献

{"title":"Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line","authors":"Sahatsawat Wainiphithapong ,&nbsp;Chana Phutthananon ,&nbsp;Sompote Youwai ,&nbsp;Pitthaya Jamsawang ,&nbsp;Phattarawan Malaisree ,&nbsp;Ochok Duangsano ,&nbsp;Pornkasem Jongpradist","doi":"10.1016/j.undsp.2025.04.008","DOIUrl":"10.1016/j.undsp.2025.04.008","url":null,"abstract":"<div><div>This paper presents a study on multi-objective optimization (MOO) of shield operational parameters (SOPs) for soft ground tunneling using a tunnel boring machine (TBM) in an urban environment, focusing on the case study of the MRT Blue Line in Bangkok. The investigation aims to determine the optimal combination of SOPs, consisting of face pressure (<span><math><msub><mi>F</mi><mtext>p</mtext></msub></math></span>), thrust force (<span><math><msub><mi>T</mi><mtext>f</mtext></msub></math></span>), grout pressure (<span><math><msub><mi>G</mi><mtext>p</mtext></msub></math></span>), and percent grout filling (<span><math><msub><mi>G</mi><mtext>f</mtext></msub></math></span>), along with relevant environmental factors, including tunnel depth (<span><math><msub><mi>T</mi><mtext>d</mtext></msub></math></span>), inverted groundwater level (<span><math><msub><mi>W</mi><mtext>i</mtext></msub></math></span>), and type of surrounding soil (<span><math><msub><mi>T</mi><mtext>s</mtext></msub></math></span>). The primary objective is to enhance the penetration rate (<span><math><msub><mi>P</mi><mtext>avg</mtext></msub></math></span>, in terms of average value), as cost consideration, while mitigating ground surface settlement (<span><math><mi>S</mi></math></span>), as safety (serviceability) consideration. Using long short-term memory (LSTM) neural networks as predictive models, the results yield coefficient of determination (<em>R</em>²) values of 0.81 and 0.96, root mean square error (RMSE) values of 5.91 mm/min and 3.09 mm, and average bias factor values of 0.99 and 0.88 for the <span><math><mi>P</mi></math></span> and <span><math><mi>S</mi></math></span> predictive models, respectively, based on validation datasets. This integrated framework, which combines the non-dominated sorting genetic algorithm (NSGA-II) with LSTM neural networks, is applied to MOO to identify the optimal SOPs, while accounting for their influence on <span><math><mi>S</mi></math></span> variation as a time-series over 11 timesteps, as considered in this study. For simplification and practical field implementation, the same set of SOP values is applied across all 11 timesteps during the optimization process. Using the proposed optimization framework, the optimal results demonstrate improvements in <span><math><msub><mi>P</mi><mtext>avg</mtext></msub></math></span>, increasing by up to 109.8% (from 13.99 to 29.35 mm) and in <span><math><mi>S</mi></math></span>, reducing up to 79.6% (from 34.55 to 7.06 mm) when MOO is conducted as a time series using the simplified method. This finding provides a valuable approach to effectively address the sequential uncertainties of relevant factors in soft ground tunneling for similar projects.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 311-334"},"PeriodicalIF":8.3,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of a large and shallow twin-tunnel excavation on a high-speed railway bridge and related protective measures: A case study","authors":"Wenhui Yang ,&nbsp;Dingwen Zhang ,&nbsp;Daniela Boldini","doi":"10.1016/j.undsp.2025.05.001","DOIUrl":"10.1016/j.undsp.2025.05.001","url":null,"abstract":"<div><div>This case study examines a landmark engineering project in Suzhou, China, involving the construction of two large-diameter (13.2 m) shield tunnels beneath an active high-speed railway (HSR) bridge. This pioneering project is the first of its kind in both China and the world. Advanced numerical simulations were conducted to rigorously assess construction risks. To ensure the operational safety of the existing HSR bridge, an innovative protective system, consisting primarily of segmental steel casing concrete pile barriers, was employed. A comprehensive network of monitoring sensors was strategically deployed to track soil, pile barrier, and pier displacements throughout both the protective and tunnelling phases. Simulation results indicated that tunnelling without protective measures could cause pier displacements of up to 3.1 mm along the bridge—exceeding the maximum allowable displacement of 2 mm in accordance with regulations. Monitoring data revealed that the maximum pier displacement during protective scheme installation was limited to 0.5 mm. With these protective measures, pier displacement during each tunnelling phase remained consistently below 0.5 mm, representing an approximate 80% reduction compared to the unprotected scenario, thereby ensuring the continued safety of the HSR bridge.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 216-237"},"PeriodicalIF":8.3,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated design framework for excavation retaining structures: Extending IFC standards and integrating BIM with geotechnical simulation","authors":"Qiwei Wan,&nbsp;Yuyuan Zhu,&nbsp;Haibin Ding,&nbsp;Wentao Hu,&nbsp;Changjie Xu","doi":"10.1016/j.undsp.2025.04.007","DOIUrl":"10.1016/j.undsp.2025.04.007","url":null,"abstract":"<div><div>Challenges arise in automate design with building information modeling (BIM) in underground space. Industry foundation classes (IFC) standard lacks detailed entity objects for describing excavation retaining structures and geological information, and automated design based on BIM models is not yet for practical application. This study presents a novel automated framework. It integrates the extended IFC standard with mechanical analysis and BIM modeling, significantly advancing structural optimization and rebar detailing. Direct 3D model generation streamlines complex excavation projects, aligning with the trend towards automated, precision-driven design. Key contributions include: (1) the extension of the IFC standard to support excavation retaining structures with objects like IfcBracedPit and IfcPitWall, improving interoperability between geotechnical models and BIM systems; (2) the integration of heuristic algorithms for automated optimization of deformation control parameters, reducing manual intervention; and (3) the promotion of design methodology that bypasses two-dimensional modeling and directly generates three-dimensional models, enhancing efficiency and allowing engineers to focus on high-level decision-making. However, the framework is primarily suited for standard cross-section projects like subway stations and tunnels. Future work will focus on refining the framework for more complex geotechnical projects, addressing software independence and improving design robustness and independence.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 261-282"},"PeriodicalIF":8.3,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental study on ECC-based unreinforced shield tunnel segmental joints for future resilient infrastructure","authors":"Minjin Cai ,&nbsp;Timon Rabczuk ,&nbsp;Xiaoying Zhuang","doi":"10.1016/j.undsp.2024.09.009","DOIUrl":"10.1016/j.undsp.2024.09.009","url":null,"abstract":"<div><div>To advance resilient infrastructure, this study explores unreinforced shield tunnel segment technologies, a critical but under-researched area. It conducted experiments on ECC-based unreinforced segments (ECCUS), comparing them with ECC-based reinforced segments (ECCRS) and reinforced concrete segments (RCS), focusing on their mechanical properties, including material characteristics, segmental deflection, joint behavior, bolt strain, damage propagation, failure modes, joint toughness, and ductility. Key findings include: (1) ECCUS joints exhibited significantly enhanced bearing capacity, with ultimate strength 34% higher than RCS and 29% higher than ECCRS. In terms of initial cracking strength, ECCUS outperformed RCS by 200% and ECCRS by 34%. (2) The absence of reinforcement cages in ECCUS reduced stiffness but improved overall segment coordination and deformation, leading to deflections 100% greater than RCS and 85% than ECCRS. (3) ECCUS and ECCRS displayed numerous, fine cracks under 200 µm wide, while RCS showed fewer, wider cracks over 3 mm, leading to significant spalling. Cracks in ECCUS were densely distributed across shear and compression zones, in contrast to RCS and ECCRS where they concentrated on compression areas. (4) ECCUS joints exhibited remarkable toughness, with elastic phase toughness 13.47 times that of RCS and 1.91 times that of ECCRS. In the normal serviceability phase, the toughness of ECCUS was 12.17 times that of RCS and 2.53 times that of ECCRS. (5) Considering multi-scale mechanical effects, ECCUS joints amplified the material advantages of ECC over RC more than 11 times during the elastic stage. These findings offer valuable insights for future resilient infrastructure development based on unreinforced construction technologies.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 283-310"},"PeriodicalIF":8.3,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benchmark study of three statistical methods for six intact rock failure criteria constrained by different rock strength data","authors":"Peng-fei He ,&nbsp;Xin Li ,&nbsp;Xu-long Yao ,&nbsp;Zhi-gang Tao ,&nbsp;Yan-ting Du","doi":"10.1016/j.undsp.2025.04.006","DOIUrl":"10.1016/j.undsp.2025.04.006","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 238-260"},"PeriodicalIF":8.3,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A lifecycle carbon emission evaluation model for urban underground highway tunnel facilities","authors":"Guosheng Wang ,&nbsp;Dechun Lu ,&nbsp;Gangao Ji ,&nbsp;Xuhua Liang ,&nbsp;Qingtao Lin ,&nbsp;Jirui Lv ,&nbsp;Xiuli Du","doi":"10.1016/j.undsp.2025.04.005","DOIUrl":"10.1016/j.undsp.2025.04.005","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 352-370"},"PeriodicalIF":8.3,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144912429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land-sea integrated suitability evaluation of underground space based on Pythagorean fuzzy Bayesian network","authors":"Xinyu Liu ,&nbsp;Hongjun Liu ,&nbsp;Jie Dong ,&nbsp;Peng Yu ,&nbsp;Honghua Liu ,&nbsp;Guanghua Cheng","doi":"10.1016/j.undsp.2025.04.004","DOIUrl":"10.1016/j.undsp.2025.04.004","url":null,"abstract":"<div><div>Scientific development and utilization of urban underground space is an inevitable choice for sustainable urban development. However, in the previous suitability evaluation of underground space in coastal cities, the development potential of underground space in the sea area is not considered. Therefore, this study takes the coastal zone of Jiaozhou bay as the study area, establishes evaluation index systems for land and sea areas separately, and explores a new model for evaluating the suitability of underground space in coastal cities by integrating land and sea. In addition, an underground space suitability evaluation model based on the integration of Pythagorean fuzzy sets and Bayesian network is proposed. Firstly, the Pythagorean triangular fuzzy numbers are used to expand the fuzzy range of expert opinions. Then the Pythagorean triangular fuzzy hybrid geometric operator is used to realize the aggregation of expert opinions to solve the difficulty of obtaining the node conditional probability table by the traditional Bayesian network model of underground space suitability evaluation. Finally, the Pythagorean fuzzy Bayesian network is used as an evaluation tool to carry out the underground space suitability evaluation. Based on the evaluation result and urban planning, the overall planning and functional zoning guidelines for underground space development in the study area are given and the suitability and engineering construction difficulty analysis on the second subsea tunnel of Jiaozhou bay is conducted. The research results can provide a valuable reference for the coastal city planning department to develop and utilize underground space.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 197-215"},"PeriodicalIF":8.3,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of the Optuna-NGBoost-SHAP model for estimating ground settlement during tunnel excavation","authors":"Yuxin Chen ,&nbsp;Mohammad Hossein Kadkhodaei ,&nbsp;Jian Zhou","doi":"10.1016/j.undsp.2025.03.006","DOIUrl":"10.1016/j.undsp.2025.03.006","url":null,"abstract":"<div><div>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: <em>R</em>² = 0.9984, MAE = 0.1004, RMSE = 0.4193, MedAE = 0.0122; validation set: <em>R</em>² = 0.9001, MAE = 1.3363, RMSE = 3.2992, MedAE = 0.3042; test set: <em>R</em>² = 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.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 60-78"},"PeriodicalIF":8.2,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven modeling for evaluating deformation of a deep excavation near existing tunnels","authors":"Fengwen Lai ,&nbsp;Songyu Liu ,&nbsp;Jim Shiau ,&nbsp;Mingpeng Liu ,&nbsp;Guojun Cai ,&nbsp;Ming Huang","doi":"10.1016/j.undsp.2025.04.003","DOIUrl":"10.1016/j.undsp.2025.04.003","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 162-179"},"PeriodicalIF":8.3,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of ground motion characteristics on the seismic fragility of circular tunnels","authors":"Zhong-Kai Huang ,&nbsp;Dong-Mei Zhang ,&nbsp;Wu-Yu Zhang ,&nbsp;Yong-Bo Li","doi":"10.1016/j.undsp.2024.09.008","DOIUrl":"10.1016/j.undsp.2024.09.008","url":null,"abstract":"<div><div>The seismic performance of tunnel structure can be examined by fragility analysis, which determines the probability that demand will exceed capacity for a given hazard intensity. Although it is commonly understood that earthquake uncertainties dominate fragility features, the implication of ground motion characteristics on the shield tunnel fragility analysis has not been comprehensively explored. Thus, this study aims to compare the effects of various earthquake characteristics on the fragility of the investigated shield tunnels. To this end, a typical shield tunnel was chosen and modelled using the finite element software. In addition, to account for typical ground motion characteristics, various ground motion sets, including near-field no plus motions (NFNP), near-field motions with a pulse (NFP), and far-field motions (FF), are selected, and a fragility analysis was assessed for every set of ground motion. The fragility curves were generated employing peak ground acceleration (PGA) as the intensity measure (IM) and tunnel drift as the damage measure (DM). The findings indicate that shield tunnels subjected to NFP may be more vulnerable compared to those subjected to NFNP and FF ground motions. This study’s findings highlight the vital role of ground motion characteristics in evaluating the fragility of shield tunnels. Moreover, the results may inform future seismic risk and resiliency evaluations regarding the importance of considering or disregarding the impacts of ground motion characteristics on tunnel vulnerability.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"24 ","pages":"Pages 180-196"},"PeriodicalIF":8.3,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}