scholarly journals Experimental Research on the Dam-Break Mechanisms of the Jiadanwan Landslide Dam Triggered by the Wenchuan Earthquake in China

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Fu-gang Xu ◽  
Xing-guo Yang ◽  
Jia-wen Zhou ◽  
Ming-hui Hao
Keyword(s):  
Wenchuan Earthquake ◽  
Discharge Channel ◽  
Landslide Dam ◽  
Dam Break ◽  
Experimental Results ◽  
Dam Breaks ◽  
The Wenchuan Earthquake ◽  
Large Numbers ◽  
Dam Management ◽  
Break Process

Dam breaks of landslide dams are always accompanied by large numbers of casualties, a large loss of property, and negative influences on the downstream ecology and environment. This study uses the Jiadanwan landslide dam, created by the Wenchuan earthquake, as a case study example. Several laboratory experiments are carried out to analyse the dam-break mechanism of the landslide dam. The different factors that impact the dam-break process include upstream flow, the boulder effect, dam size, and channel discharge. The development of the discharge channel and the failure of the landslide dam are monitored by digital video and still cameras. Experimental results show that the upstream inflow and the dam size are the main factors that impact the dam-break process. An excavated discharge channel, especially a trapezoidal discharge channel, has a positive effect on reducing peak flow. The depth of the discharge channel also has a significant impact on the dam-break process. The experimental results are significant for landslide dam management and flood disaster prevention and mitigation.

A Survey of NGO Participation in Reconstruction after the Wenchuan Earthquake: The Social Work Perspective

2011 ◽  
Vol 3 (1) ◽  
pp. 131-159
Author(s):  
Wei Kenan ◽  
Zhang Qiongwen ◽  
Feng Hua
Keyword(s):  
Social Work ◽  
Wenchuan Earthquake ◽  
Social Services ◽  
The Wenchuan Earthquake ◽  
Large Numbers ◽  
The Social ◽  
Legal Space ◽  
The Government ◽  
Survey Responses

AbstractAfter the Wenchuan earthquake, large numbers of NGOs entered the quake area and provided large amounts of social services. Analysis of survey responses from 149 NGOs has allowed three basic models to be identified among NGOs engaging in post-quake reconstruction: (1) university social work stations; (2) civil organizations; and (3) government-embedded organizations. Because reconstruction is a long-term task, adjustments to current strategies may merit consideration. First, the disproportionate weight currently placed on heavy infrastructure over social services and society-building must be rebalanced. Second, all of society ‐ and especially the government ‐ should recognize the enormous significance and the enormous role NGO services have played in post-quake reconstruction. Third, cooperative arrangements should be explored between grant makers like the government, enterprises, and foundations and NGOs. Fourth, trial introduction of people-run non-enterprise units to the quake area should be explored. Fifth, relations between NGOs and the government should be smoothed to ensure that NGOs have a legal space in which to conduct their social work. Sixth, NGOs must put more work into capacity building.

Catastrophic debris flows triggered by the 20 August 2019 rainfall, a decade since the Wenchuan earthquake, China

Landslides ◽  
2021 ◽  
Author(s):  
Fan Yang ◽  
Xuanmei Fan ◽  
Srikrishnan Siva Subramanian ◽  
Xiangyang Dou ◽  
Junlin Xiong ◽  
...  
Keyword(s):  
Wenchuan Earthquake ◽  
Debris Flows ◽  
The Wenchuan Earthquake

scholarly journals Valuable Clues for DCNN-Based Landslide Detection from a Comparative Assessment in the Wenchuan Earthquake Area

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5191
Author(s):  
Chang Li ◽  
Bangjin Yi ◽  
Peng Gao ◽  
Hui Li ◽  
Jixing Sun ◽  
...  
Keyword(s):  
Wenchuan Earthquake ◽  
Remote Sensing Images ◽  
Machine Learning Methods ◽  
The Wenchuan Earthquake ◽  
Causative Factors ◽  
Multiple Structures ◽  
Sample Set ◽  
Larger Sample ◽  
Structure Layer ◽  
Earthquake Area

Landslide inventories could provide fundamental data for analyzing the causative factors and deformation mechanisms of landslide events. Considering that it is still hard to detect landslides automatically from remote sensing images, endeavors have been carried out to explore the potential of DCNNs on landslide detection, and obtained better performance than shallow machine learning methods. However, there is often confusion as to which structure, layer number, and sample size are better for a project. To fill this gap, this study conducted a comparative test on typical models for landside detection in the Wenchuan earthquake area, where about 200,000 secondary landslides were available. Multiple structures and layer numbers, including VGG16, VGG19, ResNet50, ResNet101, DenseNet120, DenseNet201, UNet−, UNet+, and ResUNet were investigated with different sample numbers (100, 1000, and 10,000). Results indicate that VGG models have the highest precision (about 0.9) but the lowest recall (below 0.76); ResNet models display the lowest precision (below 0.86) and a high recall (about 0.85); DenseNet models obtain moderate precision (below 0.88) and recall (about 0.8); while UNet+ also achieves moderate precision (0.8) and recall (0.84). Generally, a larger sample set can lead to better performance for VGG, ResNet, and DenseNet, and deeper layers could improve the detection results for ResNet and DenseNet. This study provides valuable clues for designing models’ type, layers, and sample set, based on tests with a large number of samples.

scholarly journals SPARQL Query Generator (SQG)

2021 ◽  
Author(s):  
Yanji Chen ◽  
Mieczyslaw M. Kokar ◽  
Jakub J. Moskal
Keyword(s):  
Data Retrieval ◽  
Data Representation ◽  
Sparql Query ◽  
Experimental Results ◽  
Generation Process ◽  
Manual Work ◽  
Retrieval Systems ◽  
Large Numbers ◽  
Query Generation ◽  
Good Coverage

AbstractThis paper describes a program—SPARQL Query Generator (SQG)—which takes as input an OWL ontology, a set of object descriptions in terms of this ontology and an OWL class as the context, and generates relatively large numbers of queries about various types of descriptions of objects expressed in RDF/OWL. The intent is to use SQG in evaluating data representation and retrieval systems from the perspective of OWL semantics coverage. While there are many benchmarks for assessing the efficiency of data retrieval systems, none of the existing solutions for SPARQL query generation focus on the coverage of the OWL semantics. Some are not scalable since manual work is needed for the generation process; some do not consider (or totally ignore) the OWL semantics in the ontology/instance data or rely on large numbers of real queries/datasets that are not readily available in our domain of interest. Our experimental results show that SQG performs reasonably well with generating large numbers of queries and guarantees a good coverage of OWL axioms included in the generated queries.

NUMERICAL SIMULATION OF DAM BREAK BY ADAPTIVE STENCIL DIFFUSE INTERFACE METHOD

2009 ◽  
Vol 23 (03) ◽  
pp. 293-296 ◽  
Author(s):  
L. DING ◽  
C. SHU ◽  
N. ZHAO
Keyword(s):  
Numerical Simulation ◽  
Adaptive Algorithm ◽  
Leading Edge ◽  
Dam Break ◽  
Experimental Results ◽  
Diffuse Interface ◽  
Fine Scale ◽  
Experiment Data ◽  
Interface Behavior

This paper presents the application of an adaptive stencil diffuse interface method to the simulation of dam break problem. The adaptive stencil diffuse interface method is the combination of the diffuse interface method and a stencil adaptive algorithm, where the diffuse interface method is used as the solver, and the adaptive stencil refinement scheme is applied to improve the resolution around the interface so that the fine-scale interface behavior can be captured. In this paper, we use this method to simulate the dam break problem, study the dam height and leading edge position, and compare our results with the experiment data available in the literature. It is shown that the results using the adaptive stencil diffuse interface method agree very well with the experimental results.

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