Deep Underground Science and Engineering最新文献

{"title":"A case study on the stability of a big underground powerhouse cavern cut by an interlayer shear zone in the China Baihetan hydropower plant","authors":"Lifang Zou,&nbsp;Guotao Meng,&nbsp;Jiayao Wu,&nbsp;Wei Fu,&nbsp;Weijiang Chu,&nbsp;Weiya Xu","doi":"10.1002/dug2.12094","DOIUrl":"https://doi.org/10.1002/dug2.12094","url":null,"abstract":"<p>The big underground powerhouse cavern of the China Baihetan hydropower plant is 438 m long, 34 m wide, and 88.7 m high. It is cut by a weak interlayer shear zone and its high sidewall poses a huge stability problem. This paper reports our successful solution of this problem through numerical simulations and a replacement-tunnel scheme in the detailed design stage and close site monitoring in the excavation stage. Particularly, in the detail design stage, mechanical parameters of the shear zone were carefully determined through laboratory experiments and site tests. Then, deformation of the surrounding rocks and the shear zone under high in situ stress conditions was predicted using 3 Dimensional Distinct Element Code (3DEC). Subsequently, a replacement-tunnel scheme was proposed for the treatment on the shear zone to prevent severe unloading relaxation of surrounding rocks. In the construction period, excavation responses were closely monitored on deformations of surrounding rocks and the shear zone. The effect of local cracking in the replacement tunnels on sidewall stability was evaluated using the strength reduction method. These monitoring results were compared with the predicted numerical simulation in the detailed design stage. It is found that the shear zone greatly modified the deformation mode of the cavern surrounding rocks. Without any treatment, rock mass deformation on the downstream sidewall was larger than 125 mm and the shearing deformation of the shear zone was 60–70 mm. These preset replacement tunnels can reduce not only the unloading and relaxation of rock masses but also the maximum shearing deformation of the shear zone by 10–20 mm. The predictions by numerical simulation were in good agreement with the monitoring results. The proposed tunnel-replacement scheme can not only restrain the shear zone deformation but also enhance the safety of surrounding rocks and concrete tunnels. This design procedure offers a good reference for interaction between a big underground cavern and a weak layer zone in the future.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 2","pages":"305-315"},"PeriodicalIF":0.0,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144256482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy characteristics of saturated Jurassic sandstone in western China under different stress paths","authors":"Yi Yang,&nbsp;Jian Lin,&nbsp;Yun Wu,&nbsp;Shilong Peng,&nbsp;Wanhang Shao,&nbsp;Lining Yang","doi":"10.1002/dug2.12096","DOIUrl":"https://doi.org/10.1002/dug2.12096","url":null,"abstract":"<p>To study the energy evolution and failure characteristics of saturated sandstone under unloading conditions, rock unloading tests under different stress paths were conducted. The energy evolution mechanism of the unloading failure of saturated sandstone was systematically explored from the perspectives of the stress path, the initial confining pressure, and the energy conversion rate. The results show that (1) before the peak stress, the elastic energy increases with an increase in deviatoric stress, while the dissipated energy slowly increases first. After the peak stress, the elastic energy decreases with the decrease of deviatoric stress, and the dissipated energy suddenly increases. The energy release intensity during rock failure is positively correlated with the axial stress. (2) When the initial confining pressure is below a certain threshold, the stress path is the main factor influencing the total energy difference. When the axial stress remains constant and the confining pressure is unloading, the total energy is more sensitive to changes in the confining pressure. When the axial stress remains constant, the compressive deformation ability of the rock cannot be significantly improved by the increase in the initial confining pressure. The initial confining pressure is positively correlated with the rock's energy storage limit. (3) The initial confining pressure increases the energy conversion rate of the rock; the initial confining pressure is positively correlated with the energy conversion rate; and the energy conversion rate has a high confining pressure effect. The increase in the axial stress has a much greater impact on the elastic energy than the confining pressure. (4) When the deviatoric stress is small, the confining pressure mainly plays a protective role. Compared with the case of triaxial compression paths, the rock damage is more severe under unloading paths, and compared with the case of constant axial stress, the rock damage is more severe under increasing axial stress.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"158-168"},"PeriodicalIF":0.0,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12096","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deformation monitoring at shield tunnel joints: Laboratory test and discrete element simulation","authors":"Maoyi Mao,&nbsp;Xiaowei Yang,&nbsp;Chun Liu,&nbsp;Tao Zhao,&nbsp;Hui Liu","doi":"10.1002/dug2.12092","DOIUrl":"10.1002/dug2.12092","url":null,"abstract":"<p>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.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"149-157"},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140685856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance evaluation of rock fragmentation prediction based on RF-BOA, AdaBoost-BOA, GBoost-BOA, and ERT-BOA hybrid models","authors":"Junjie Zhao,&nbsp;Diyuan Li,&nbsp;Jian Zhou,&nbsp;Danial J. Armaghani,&nbsp;Aohui Zhou","doi":"10.1002/dug2.12089","DOIUrl":"10.1002/dug2.12089","url":null,"abstract":"<p>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, <i>X</i>₅₀) were adopted to train and validate the predictive models. The root mean square error (<i>RMSE</i>), the mean absolute error (<i>MAE</i>), and the coefficient of determination (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <msup>\u0000 <mi>R</mi>\u0000 \u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 </mrow>\u0000 <annotation> &lt;math xmlns=\"http://www.w3.org/1998/Math/MathML\" altimg=\"urn:x-wiley:20970668:media:dug212089:dug212089-math-0001\" wiley:location=\"equation/dug212089-math-0001.png\"&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;msup&gt;&lt;mi&gt;R&lt;/mi&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/msup&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;</annotation>\u0000 </semantics></math>) 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 <i>R</i>² value of 0.96 and the smallest values of <i>RMSE</i> and <i>MAE</i> 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 (<i>X</i>_B), elastic modulus (<i>E</i>), and stemming length-to-burden ratio (<i>T/B</i>) 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.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"3-17"},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140699963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment for shallow and large tunnel construction in weak ground conditions: Application of tunnel boring machines","authors":"Servet Karahan,&nbsp;Candan Gokceoglu","doi":"10.1002/dug2.12083","DOIUrl":"10.1002/dug2.12083","url":null,"abstract":"<p>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.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"132-148"},"PeriodicalIF":0.0,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140704580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ALSTNet: Autoencoder fused long- and short-term time-series network for the prediction of tunnel structure","authors":"Bowen Du,&nbsp;Haohan Liang,&nbsp;Yuhang Wang,&nbsp;Junchen Ye,&nbsp;Xuyan Tan,&nbsp;Weizhong Chen","doi":"10.1002/dug2.12081","DOIUrl":"10.1002/dug2.12081","url":null,"abstract":"<p>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.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"72-82"},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140743374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution law of pulsating seepage and thermal deformation by injecting high-temperature steam into coal for thermal coalbed methane recovery","authors":"Zhiqiang Li,&nbsp;Junliang Li,&nbsp;Jinsheng Chen,&nbsp;Ali Karrech,&nbsp;Ningchao Zhang,&nbsp;Ju Chang,&nbsp;Kaiqi Jin,&nbsp;Yangyang Yu,&nbsp;Hongbin Wang,&nbsp;Aijie Wang","doi":"10.1002/dug2.12087","DOIUrl":"10.1002/dug2.12087","url":null,"abstract":"<p>Chinese coal reservoirs are characterized by low pressure and low permeability, which need to be enhanced so as to increase production. However, conventional methods for permeability enhancement can only increase the permeability in fractures, but not the ultra-low permeability in coal matrices. Attempts to enhance such impermeable structures lead to rapid attenuation of gas production, especially in the late stage of gas extraction. Thermal stimulation by injecting high-temperature steam is a promising method to increase gas production. The critical scientific challenges that still hinder its widespread application are related to the evolution law of permeability of high-temperature steam in coal and the thermal deformation of coal. In this study, an experimental approach is developed to explore the high-temperature steam seepage coupled with the thermal deformation in coal under triaxial stress. The tests were conducted using cylindrical coal specimens of ϕ50 mm × 100 mm. The permeability and thermal strain in coal were investigated when high-temperature steam was injected at 151.11, 183.20, 213.65, and 239.76°C. The experimental results reveal for the first time that as the amount of injected fluid increases, the steam permeability shows periodic pulsation changes. This paper introduces and explains the main traits of this discovery that may shed more light on the seepage phenomenon. When the injected steam temperature increases, the amplitude of pulsating permeability decreases, whereas the frequency increases; meanwhile, the period becomes shorter, the pulsation peak appears earlier, and the stabilization time becomes longer. The average peak permeability shows a “U-shaped” trend, decreasing first and then increasing as the steam temperature increases. Meanwhile, with the extension of steam injection time, the axial, radial, and volumetric strains of coal show a stage-wise expansion characteristic at different temperatures of steam injection, except for the radial strains at 151.11°C. A two-phase flow theory of gas–liquid is adopted to elucidate the mechanism of pulsating seepage of steam. Moreover, the influencing mechanism of inward and outward thermal expansion on the permeability of coal is interpreted. The results presented in this paper provide new insight into the feasibility of thermal gas recovery by steam injection.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"4 1","pages":"119-131"},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140743851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of rock mass classification in tunnel boring machine tunneling using the principal component analysis (PCA)–gated recurrent unit (GRU) neural network","authors":"Ke Man,&nbsp;Liwen Wu,&nbsp;Xiaoli Liu,&nbsp;Zhifei Song,&nbsp;Kena Li,&nbsp;Nawnit Kumar","doi":"10.1002/dug2.12084","DOIUrl":"10.1002/dug2.12084","url":null,"abstract":"<p>Due to the complexity of underground engineering geology, the tunnel boring machine (TBM) usually shows poor adaptability to the surrounding rock mass, leading to machine jamming and geological hazards. For the TBM project of Lanzhou Water Source Construction, this study proposed a neural network called PCA–GRU, which combines principal component analysis (PCA) with gated recurrent unit (GRU) to improve the accuracy of predicting rock mass classification in TBM tunneling. The input variables from the PCA dimension reduction of nine parameters in the sample data set were utilized for establishing the PCA–GRU model. Subsequently, in order to speed up the response time of surrounding rock mass classification predictions, the PCA–GRU model was optimized. Finally, the prediction results obtained by the PCA–GRU model were compared with those of four other models and further examined using random sampling analysis. As indicated by the results, the PCA–GRU model can predict the rock mass classification in TBM tunneling rapidly, requiring about 20 s to run. It performs better than the previous four models in predicting the rock mass classification, with accuracy <i>A</i>, macro precision <i>MP</i>, and macro recall <i>MR</i> being 0.9667, 0.963, and 0.9763, respectively. In Class II, III, and IV rock mass prediction, the PCA–GRU model demonstrates better precision <i>P</i> and recall <i>R</i> owing to the dimension reduction technique. The random sampling analysis indicates that the PCA–GRU model shows stronger generalization, making it more appropriate in situations where the distribution of various rock mass classes and lithologies change in percentage.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 4","pages":"413-425"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140769523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bibliometric analysis of research challenges and trends in urban underground space","authors":"You Zhang,&nbsp;Liang Zheng,&nbsp;Lingling He,&nbsp;Yuyong Jiao,&nbsp;Hanfa Peng,&nbsp;Ranjith P. Gamage","doi":"10.1002/dug2.12086","DOIUrl":"10.1002/dug2.12086","url":null,"abstract":"<p>The utilization and development of urban underground space play a crucial role in optimizing the layout of civic architecture and enhancing the urban ecological environment, which contributes toward increasing the overall carrying capacity and promoting sustainable development in megacities. To delve into the research progress of urban underground space, knowledge maps were created using the information visualization software VOSviewer. The literature was systematically extracted from three prominent databases, namely, Web of Science, Scopus, and China National Knowledge Infrastructure. According to the bibliometric analysis of the co-citation and core words co-occurrence, the trends and challenges of research on urban underground space were identified. As highlighted by the results obtained, it still remains highly challenging to achieve interdisciplinary collaboration in urban underground space research; the research trends of urban underground space consist of collaborative planning and whole life cycle sustainable development, multisource geological data informatization and resource evaluation, infrastructure design optimization, and intelligent construction. The knowledge map, drawn using bibliometric methods, offers a quantitative analysis of literature retrieval across various levels. It is recognized as an essential tool for exploring and identifying challenges and trends in urban underground space.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 2","pages":"207-215"},"PeriodicalIF":0.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140378999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A thermal stress loading technique for large-sized hot dry rock mechanical tests","authors":"Huiling Ci,&nbsp;Bing Bai,&nbsp;Hongwu Lei,&nbsp;Yan Zou,&nbsp;Jianfeng Liu","doi":"10.1002/dug2.12085","DOIUrl":"10.1002/dug2.12085","url":null,"abstract":"<p>Testing of large-sized specimens is becoming increasingly important in deep underground rock mechanics and engineering. In traditional mechanical loading, stresses on large-sized specimens are achieved by large host frames and hydraulic pumps, which could lead to great investment. Low-cost testing machines clearly always have great appeal. In this study, a new approach is proposed using thermal expansion stress to load rock specimens, which may be particularly suitable for tests of deep hot dry rock with high temperatures. This is a different technical route from traditional mechanical loading through hydraulic pressure. For the rock mechanics test system of hot dry rock that already has an investment in heating systems, this technology may reduce the cost of the loading subsystem by fully utilizing the temperature changes. This paper presents the basic principle and a typical design of this technical solution. Preliminary feasibility analysis is then conducted based on numerical simulations. Although some technical details still need to be resolved, the feasibility of this loading approach has been preliminarily confirmed.</p>","PeriodicalId":100363,"journal":{"name":"Deep Underground Science and Engineering","volume":"3 3","pages":"326-337"},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dug2.12085","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140230257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}