Landslides最新文献

{"title":"A massive lateral moraine collapse triggered the 2023 South Lhonak Lake outburst flood, Sikkim Himalayas","authors":"Taigang Zhang, Weicai Wang, Baosheng An","doi":"10.1007/s10346-024-02358-x","DOIUrl":"https://doi.org/10.1007/s10346-024-02358-x","url":null,"abstract":"<p>On the night of October 3, 2023, the moraine-dammed South Lhonak Lake in Sikkim suddenly discharged a substantial volume of water, resulting in a glacial lake outburst flood (GLOF) that caused 178 fatalities and the destruction of three downstream hydropower projects, making it one of the most devastating GLOF events in the Himalayas. Leveraging satellite imagery and numerical modeling, this study analyzed the long-term evolution and outburst mechanisms of South Lhonak Lake, as well as the propagation of the GLOF, to provide valuable insight for regional GLOF risk assessment and management. The South Lhonak GLOF was triggered by the collapse of a massive lateral moraine, with an estimated collapse material volume of 16.75 × 10⁶ m³. Following the outburst flood, the lake area decreased by 15.38%, from 1.69 ± 0.03 to 1.46 ± 0.03 km². The impact of the GLOF extended to 169 km downstream, corresponding to a total inundation area of 32.04 ± 1.91 km². A multi-phase r.avaflow model was employed to simulate the mass flow and cascading process. An impulse wave displacement speed of approximately 26 m·s⁻¹ was observed after the collapse of the lateral moraine, and the overtopping height on the moraine dam reached 16.11 m. The hydrograph at the dam breach site revealed that approximately 38.49 × 10⁶ m³ of water was released during the drainage process and that the peak discharge of 3.02 × 10⁵ m³·s⁻¹ occurred 140 s after the dam breach. Upon entering the downstream channel, the peak discharge was attenuated, and its duration was prolonged because of the influence of the valley terrain. Given the current challenges in accurately identifying potential avalanche zones, we identified a discrepancy between GLOF triggers and modeling scenarios. A novel framework for GLOF hazard assessment involves driving collapses of varying magnitudes to strike the lake and subsequently simulating GLOF initiation and downstream propagation for the most plausible outburst scenario. This conceptual approach can be used to design artificial drainage and determine dam immobilization engineering criteria and to evaluate the resistance performance of remedial measures under specific striking probabilities.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"8 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In situ recurrent Hongshiyan paleolandslides at Ludian, China, and Implications on fault activity and hydro-project risk reduction","authors":"Liao Liye, Zeng Qingli, Shi Yongyue, Ma Xuping, Du Linlin, Zhou Jian, Zhang Luqing","doi":"10.1007/s10346-024-02338-1","DOIUrl":"https://doi.org/10.1007/s10346-024-02338-1","url":null,"abstract":"<p>Large landslides often cause catastrophic life losses and infrastructure damage. Identification of the driving forces of large ancient landslides is of utmost importance for the understanding of geohazard assessment and regional geomorphologic evolution and for the understanding of regional paleoclimate and paleoseismology. Through field geological survey, multi-temporal satellite image interpretation, sedimentological observation, and static and dynamic numerical simulation, the paper studied the geo-environments and deposit succession of the Hongshiyan paleolandslide (HSYPL), over against the Hongshiyan landslide (HSYL) triggered by the 2014 Ludian <i>M</i>_<i>S</i> (surface wave magnitude) 6.5 earthquake. The study reveals that (1) the HSYPL and HSYL are symmetrically distributed on the opposite banks of the Niulan River and on the opposite wings of a vertical anticline plunging west. Both landslides involved an anti-dip slope structure of upper hard rock while lower soft rock. (2) Two phases of deposit succession in the paleolandslide accumulations were recognized from their surficial appearances, planar distribution, spatial superimposition relationship, permeability test, and borehole survey. (3) The deposit did not result from one single paleolandslide event but two long-interval individual events, i.e., penultimate landslide (PL) and last landslide (LL), whose source volumes were estimated to be ~ 11.8 Mm³ and ~ 113.5 Mm³, respectively. (4) These two landslides kept stable under static conditions but failed when the SN component acceleration reached 1.4 and 1.2 times the value of the 2014 Ludian <i>M</i>_<i>S</i> 6.5 earthquake. The ground motions basically correspond to the earthquake magnitudes that are back-analyzed by their volumes. (5) Both the penultimate landslide and last landslide were seismically triggered with high probability. The former was more likely due to the seismic activity of the Zhaotong-Ludian fault than the Baogunao-Xiaohe fault, while the latter might be induced by either fault which was active since the Holocene. Our findings present new insights into the regional seismological history and considerations on the risk reduction of the new hydro-project constructed from the Hongshiyan co-seismic landslide dam.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"52 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive susceptibility assessment of continental glacier ice avalanches: a case study of glaciers on the northwestern Tibetan Plateau","authors":"Yuqi Shang, Hao Sun, Gaojian Miao, Chao Wang, Jinfeng Liu, Wentao Zhang, Huaquan Yang, Hang Fu","doi":"10.1007/s10346-024-02348-z","DOIUrl":"https://doi.org/10.1007/s10346-024-02348-z","url":null,"abstract":"<p>Glacial stability on the Tibetan Plateau has declined sharply in the context of global warming. Previously, continental glaciers on the northwestern Tibetan Plateau were considered stable and had little susceptibility to ice collapse. However, in recent years, numerous continental glacier ice collapses have resulted in significant economic losses, casualties, and ecological environmental damage. This study focused on eight watersheds in the Ngari Prefecture of the northwest Tibetan Autonomous Region, specifically in the upper reaches of Zecuo Lake. Continental glacier ice-avalanche disaster factors were examined based on topography, climate, and geological structure. This study proposes a continental glacier ice-avalanche susceptibility assessment method that considers both internal and external factors by combining the analytic hierarchy process (AHP) and cloud theory. A comprehensive evaluation and analysis revealed that the eight watersheds in the upstream study area of Zecuo Lake were greatly affected by climate change and geological structure, and the susceptibility assessment ratings for all glaciers were high. Therefore, it is essential to strengthen the monitoring and early warning systems in areas of human activity. The findings of this study provide a scientific basis for predicting, preventing, and mitigating continental glacier avalanche disasters on the northwestern Tibetan Plateau. Additionally, the proposed method can be applied to areas with similar geological conditions.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"47 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Landslide predictions through combined rainfall threshold models","authors":"Fausto Guzzetti, Massimo Melillo, Alessandro C. Mondini","doi":"10.1007/s10346-024-02340-7","DOIUrl":"https://doi.org/10.1007/s10346-024-02340-7","url":null,"abstract":"<p>Based on a minimum amount of rainfall that when reached or exceeded can trigger landslides, rainfall thresholds are used to predict potential landslide occurrence and are essential parts of many landslide early warning systems. Despite the extensive literature on the definition and use of rainfall thresholds, little attention has been given to examining and comparing the mathematical methods that can be used to define thresholds as lower bounds of clouds of empirical rainfall conditions known to have triggered landslides. When multiple thresholds are available, it is unclear how to combine them. Here, we address both issues. We test and compare four mathematical methods to define event cumulated rainfall—rainfall duration, ED thresholds using 2259 measurements of rainfall duration (<i>D</i>, in hours) and cumulated rainfall (<i>E</i>, in mm) that resulted in mostly shallow landslides in Italy between January 2002 and December 2012. The methods cover a broad spectrum of data driven approaches, including a frequentist least square method, a frequentist quantile regression method, a Bayesian quantile regression method, and a machine-learning symbolic regression method. We apply and compare the methods for three non-exceedance probability levels, <i>p</i> = 0.01, 0.05, 0.10, and we propose a voting strategy to combine the predictions into a single, dichotomous—i.e. ‘sharp’—non-probabilistic landslide prediction that we apply to the available dataset of rainfall measurements.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"203 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 hybrid approach combining physics-based model with extreme value analysis for temporal probability of rainfall-triggered landslide","authors":"Ho-Hong-Duy Nguyen, Ananta Man Singh Pradhan, Chang-Ho Song, Ji-Sung Lee, Yun-Tae Kim","doi":"10.1007/s10346-024-02366-x","DOIUrl":"https://doi.org/10.1007/s10346-024-02366-x","url":null,"abstract":"<p>The interplay between climate change–induced extreme rainfall and slope failure mechanisms presents a significant challenge. To address this, a new temporal modeling of landslides that integrates dynamic rainfall patterns with slope failure mechanisms is proposed. The approach features three steps: (1) analysis of the critical continuous rainfall (CCR) level using a physics-based model with Monte Carlo simulation; (2) calculation of the cumulative distribution function of the generalized extreme value distribution; and (3) estimation of the temporal probability map. Then, combined with the landslide spatial probability obtained from one-dimensional convolution neural network (1D-CNN), the landslide hazard probability was estimated for future periods of 5, 10, 20, and 50 years. The CCR and spatial probability maps were validated using the 2018 landslide event in Hiroshima Prefecture, Japan. The CCR map achieves an area under the receiver operating curve (AUC) of 74.8%. Cohesion and friction angle are the most sensitive in the hybrid model. The proportions of temporal probabilities &gt; 0.5 yielded by the non-stationary model (10, 19, 28, and 38%) were greater than those of the stationary model (6, 10, 16, and 24%) for periods of 5, 10, 20, and 50 years, respectively. The 1D-CNN model (AUC = 84.1%) outperformed logistic regression (AUC = 80.1%) and naïve Bayes (AUC = 80.1%) models. The landslide hazard probability obtained from the non-stationary model is more susceptible than that of the stationary model. These results indicate that the proposed approach is a valuable tool for future landslide risk assessment and may be applicable even in areas without a landslide inventory.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"72 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthetic libraries of urban landslide simulations to identify slope failure hotspots and drivers across spatial scales and landscapes","authors":"Elisa Bozzolan, Elizabeth Holcombe, Francesca Pianosi, Thorsten Wagener","doi":"10.1007/s10346-024-02327-4","DOIUrl":"https://doi.org/10.1007/s10346-024-02327-4","url":null,"abstract":"<p>Rainfall-triggered landslides are most deadly in developing countries, and future urban sprawl and climate change could intensify existing risks. In these regions, enhancing efforts in urban landslide risk mitigation and climate change adaptation is crucial. Current landslide probability assessment methodologies struggle to support effective mitigation because they fail to represent local anthropogenic factors (e.g. informal housing) across space and time scales. To meet this challenge, we demonstrated in previous work that hillslope-scale mechanistic models representing such localised changes can be used to create synthetic libraries of urban landslides that account for both data and future scenario uncertainty. Here, we show how these libraries can become an explorative tool for researchers and stakeholders, allowing them to investigate slope stability variations across spatial scales and landscapes. Results highlight, for example, how the main slope instability drivers change according to the location (e.g., upper vs lower catchment), the landcover (e.g. forest vs urban) and the spatial scale analysed (e.g. at hillslope scale slope stability was mostly controlled by water table height, whereas at regional scale by slope geometry). Ultimately, we demonstrate that stochastic analyses can lead to a greater understanding of the system interactions and they can support the identification of mitigation strategies that perform well across spatial scales and uncertain scenarios. These strategies should be prioritised even if future conditions are unknown. This reasoning is shown on a data-scarce region with expanding informal housing. However, the same methodology can be applied to any urban context and with any mechanistic-based model.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"12 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on the spatial distribution pattern of correlation between surface deformation and reservoir water level in the Three Gorges Reservoir area","authors":"Hongwei Sang, Dan Zhang, Chengcheng Zhang, Chuanjie Xi, Ke Fang, Bin Shi, Ling Chang","doi":"10.1007/s10346-024-02356-z","DOIUrl":"https://doi.org/10.1007/s10346-024-02356-z","url":null,"abstract":"<p>The deformation characteristics of landslides in the Three Gorges Reservoir area have been proven to be closely related to periodic reservoir water level fluctuations and seasonal rainfall. However, most past studies have focused on the deformation characteristics of a single landslide that occurred on the reservoir bank and the influence pattern of reservoir water level. The spatial influence characteristics of reservoir water level need further analysis. To do so, we used multi-temporal InSAR monitoring technology with the Sentinel-1A images acquired between 2017 and 2019 to generate hillslope deformation time series data at the front edge of the Three Gorges Reservoir area. By conducting Pearson correlation coefficient analysis on the deformation and reservoir water level, it was found that in space, the slope units closer to the reservoir have a more significant response to the negative correlation with the reservoir water level: Within 2 km of the reservoir, the response relationship is the best, gradually weaken in turn, and is almost marginal at and beyond about 7 km. Meanwhile, the analysis between seasonal rainfall and relative deformation also reflects that the reservoir water level is the main controlling factor of hillslope deformation in the reservoir area. In short, the reservoir water level parameter does not have spatial attributes that are reflected in space using the Pearson correlation coefficient, supplementing a new reference index for stability analysis of landslides in the reservoir area, which is of great value for risk analysis in the reservoir area.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"50 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ML-CASCADE: A machine learning and cloud computing-based tool for rapid and automated mapping of landslides using earth observation data","authors":"Nirdesh Sharma, Manabendra Saharia","doi":"10.1007/s10346-024-02360-3","DOIUrl":"https://doi.org/10.1007/s10346-024-02360-3","url":null,"abstract":"<p>Landslides pose a significant threat to humans as well as the environment. Rapid and precise mapping of landslide extent is necessary for understanding their spatial distribution, assessing susceptibility, and developing early warning systems. Traditional landslide mapping methods rely on labor-intensive field studies and manual mapping using high-resolution imagery, which are both costly and time-consuming. While existing machine learning-based automated mapping methods exist, they have limited transferability due to low availability of training data and the inability to handle out-of-distribution scenarios. This study introduces ML-CASCADE, a user-friendly open-source tool designed for real-time landslide mapping. It is a semi-automated tool that requires the user to create landslide and non-landslide samples using pre- and post-landslide Sentinel-2 imagery to train a machine learning model. The model training features include Sentinel-2 data, terrain data, vegetation indices, and bare soil index. ML-CASCADE is developed as an easy-to-use application on top of Google Earth Engine and supports both pixel and object-based classification methods. We validate the landslide extent developed using ML-CASCADE with independent expert-developed inventories. ML-CASCADE is not only able to identify the landslide extent accurately but can also map a complex cluster of landslides within 5 min and a simple landslide within 2 min. Due to its ease of use, speed, and accuracy, ML-CASCADE will serve as a critical operational asset for landslide risk management.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"77 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 15-year history of repeated ice-rock avalanches from a single source area in the Qinghai-Tibet Plateau","authors":"Qiankuan Wang, Bin Li, Aiguo Xing, Yiwei Liu, Yu Zhuang","doi":"10.1007/s10346-024-02355-0","DOIUrl":"https://doi.org/10.1007/s10346-024-02355-0","url":null,"abstract":"<p>Four repeated ice-rock avalanches occurred in the Amney Machen Mountains between 2004 and 2019, exhibiting both spatial and temporal characteristics of a recurring disaster chain. These events serve as notable examples of large-scale ice-rock avalanche chain disasters in the Qinghai-Tibet Plateau. Integrating multi-source data including remote sensing imaging, meteorological records, and glacier field observations, the geological and climatic characteristics of recurring ice-rock avalanches were characterized. A comprehensive study of the dynamic glacial changes in the region using multiple approaches, including offset-tracking and support vector machine classification, reveals the underlying triggering mechanisms and spatio-temporal evolution of the ice-rock avalanches. To investigate the possible impact of seismic events on the occurrence of repeated ice-rock avalanches, we performed a time-series analysis of the avalanche-prone mass to assess disaster risk. The results suggest that ice-rock avalanches in Amney Machen are caused by long-term climate warming, short-term meteorological fluctuations, glacier retreats, and patterns of ablation rather than earthquakes. Regional warming has culminated in glacier melt and de-buttressing, while freeze–thaw cycles have caused the propagation of stress crevasses and the deterioration of the ice-rock masses. Meltwater and rainfall introduce external driving forces to the ice-rock system, acting to lubricate and soften the bedrock and accelerate glacier sliding. The glacier’s ablation pattern, characterized by significant thinning at its lower part and slight thinning or even localized thickening at the top, has further heightened the hazard of glacial disasters. Our findings reveal the characteristics, triggering mechanisms, and spatio-temporal evolution of typical ice-rock avalanches, providing insights for monitoring and preventing glacial disasters throughout the Qinghai-Tibet Plateau.\u0000</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"4 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of Storm Alex on the Vievola catchment: a quantitative analysis of sediment volume and morphological changes in the Roya River tributaries","authors":"Raphaël Kerverdo, Sara Lafuerza, Christian Gorini, Alain Rabaute, Didier Granjeon, Rémy Deschamps, Eric Fouache, Mina Jafari, Pierre-Yves Lagrée","doi":"10.1007/s10346-024-02361-2","DOIUrl":"https://doi.org/10.1007/s10346-024-02361-2","url":null,"abstract":"<p>This study investigates the sediment dynamics resulting from the extreme Storm Alex in October 2020 in the Roya Valley and its tributaries in the Alpes-Maritimes region, France. The storm, triggered by a low-pressure system, led to unprecedented rainfall, causing extensive flooding and erosion in the region. Despite limited pre-flood data, the study employs aerial and satellite imagery, digital elevation models, and field surveys to quantify sediment mobilization and its effects on the Viévola alluvial fan in the Roya Valley. The Roya Valley’s complex geomorphology, characterized by steep gradients, gullies, and torrential streams, played a significant role in sediment transport. The study reveals that the Dente and Rabay torrents were major sediment contributors, with gullies in these areas producing substantial erosion. Bank erosion in the Dente valley was particularly prominent, attributed to geological factors and glacial deposits. The analysis, relying on topographical comparisons and digital data, assesses sediment volumes eroded and deposited during the event. Despite challenges in data quality, the study offers valuable insights into sediment dynamics during extreme hydro-sedimentary events. The Viévola catchment area is a focal point, emphasizing the importance of scree and fluvio-glacial deposits as primary sources of sediment. The findings emphasize the need for improved pre-event data and monitoring in mountainous regions susceptible to extreme events. The study’s methodology, despite limitations, contributes to a better understanding of geomorphic responses to extreme events. Expanding similar studies to cover a wider range of catchment areas and incorporating field data offers potential for enhanced hazard assessment and management strategies. The research underscores the critical role of sediment transport in shaping landscapes and impacting human infrastructure during extreme flood events.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"26 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}