dc.contributor.author | Wang, K | |
dc.contributor.author | Yang, P | |
dc.contributor.author | Hudson-Edwards, K | |
dc.contributor.author | Lye, W | |
dc.contributor.author | Yang, C | |
dc.contributor.author | Jing, X | |
dc.date.accessioned | 2018-08-16T11:45:10Z | |
dc.date.issued | 2018-08-16 | |
dc.description.abstract | Tailings dam failure accidents occur frequently, causing substantial damage and loss of human and animal life. The prediction of run-out tailings slurry routing following dam failures is of great significance for disaster prevention and mitigation. Using satellite remote sensing digital surface model (DSM) data, tailings pond parameters and the advanced meshless smoothed particle hydrodynamics (SPH) method, a 3D real-scale numerical modelling method was adopted to study the run-out tailings slurry routing across real downstream terrains that have and have not been affected by dam failures. Three case studies, including a physical modelling experiment, the 2015 Brazil Fundão tailings dam failure accident and an operating high-risk tailings pond in China, were carried out. The physical modelling experiment and the known consequences were successfully modeled and validated using the SPH method. This and the other experiments showed that the run-out tailings slurry would be tremendously destructive in the early stages of dam failure, and emergency response time would be extremely short if the dam collapses at its full designed capacity. The results could provide evidence for disaster prevention and mitigation engineering, emergency management plan optimization, and the development of more responsible site plans and sustainable site designs. However, improvements such as rheological model selection, terrain data quality, computing efficiency and land surface roughness need to be made for future studies. SPH numerical modelling is a powerful and advanced technique that is recommended for hazard assessment and the sustainable design of tailings dam facilities globally. | en_GB |
dc.description.sponsorship | This research was funded by the National Natural Science Foundation of China (grant number 51774045), National Key R&D Program of China (grant number 2017YFC0804600), China Scholarship Council (grant number 201706460051) and Natural Science Foundation project of Chongqing Science and Technology Commission (grant number cstc2016jcyjA0319 and cstc2018jcyjAX0231). | en_GB |
dc.identifier.citation | Vol. 10 (8), pp. 1087 - 1087 | en_GB |
dc.identifier.doi | 10.3390/w10081087 | |
dc.identifier.uri | http://hdl.handle.net/10871/33763 | |
dc.language.iso | en | en_GB |
dc.publisher | MDPI | en_GB |
dc.rights | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0). | en_GB |
dc.subject | disaster prevention and mitigation | en_GB |
dc.subject | tailings dam failure | en_GB |
dc.subject | digital surface model | en_GB |
dc.subject | smoothed particle hydrodynamics | en_GB |
dc.subject | slurry routing | en_GB |
dc.title | Integration of DSM and SPH to Model Tailings Dam Failure Run-Out Slurry Routing Across 3D Real Terrain | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2018-08-16T11:45:10Z | |
dc.identifier.issn | 2073-4441 | |
dc.description | This is the final version of the article. Available from MDPI via the DOI in this record. | en_GB |
dc.identifier.journal | Water | en_GB |