Development and Validation of a 2D Dam Break Process Model

Author(s):  
Yafei Jia ◽  
Yaoxin Zhang ◽  
Sherry Hunt
2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Fu-gang Xu ◽  
Xing-guo Yang ◽  
Jia-wen Zhou ◽  
Ming-hui Hao

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.


2018 ◽  
Vol 73 ◽  
pp. 29-41 ◽  
Author(s):  
Peter Ohlemüller ◽  
Falah Alobaid ◽  
Alberto Abad ◽  
Juan Adanez ◽  
Jochen Ströhle ◽  
...  

1995 ◽  
Vol 117 (1) ◽  
pp. 28-32 ◽  
Author(s):  
Xueshu Song

The strain-hardening and thermal-softening effects on shear stress and shear angle in orthogonal machining are discussed in this paper. The temperature effect on strain hardening was quantitatively related to the shear angle using Merchant’s upper bound condition to reduce the number of experimentally-obtained coefficients and thus to both reduce cost and increase accuracy in share angle prediction. This quantitative relationship was then integrated with a force based process model and an equal energy type approach in developing a new model. A statistical analysis with experiment data indicated that the new model yielded improved result in accuracy, reliability, insensitivity to nonmodel parameters, and adaptability.


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