Simulation of Tailings Flow Resulting From a Dam Breach Using Smoothed Particle Hydrodynamics
Bibliographic record
Abstract
Research Article| August 24, 2018 Simulation of Tailings Flow Resulting from a Dam Breach Using Smoothed Particle Hydrodynamics Poulad Daneshvar; Poulad Daneshvar Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 2W1, Canada Search for other works by this author on: GSW Google Scholar Attila M. Zsaki Attila M. Zsaki 1 Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 2W1, Canada 1Corresponding email: am.zsaki@concordia.ca. Search for other works by this author on: GSW Google Scholar Author and Article Information Poulad Daneshvar Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 2W1, Canada Attila M. Zsaki 1 Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 2W1, Canada 1Corresponding email: am.zsaki@concordia.ca. Publisher: Association of Environmental & Engineering Geologists First Online: 25 Jul 2018 Online Issn: 1558-9161 Print Issn: 1078-7275 © 2018 Association of Environmental & Engineering Geologists Environmental & Engineering Geoscience (2018) 24 (3): 263–279. https://doi.org/10.2113/EEG-1891 Article history First Online: 25 Jul 2018 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Poulad Daneshvar, Attila M. Zsaki; Simulation of Tailings Flow Resulting from a Dam Breach Using Smoothed Particle Hydrodynamics. Environmental & Engineering Geoscience 2018;; 24 (3): 263–279. doi: https://doi.org/10.2113/EEG-1891 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyEnvironmental & Engineering Geoscience Search Advanced Search Abstract Failure of tailings dams often results in the release of substantial amounts of tailings into the environment, causing considerable damage. The flow of tailings presents a complex modeling challenge due to the free-surface flow and large deformations involved, rendering it intractable by conventional finite element or finite difference methods. A mesh-free formulation, based on smoothed particle hydrodynamics (SPH), was utilized to back-analyze documented tailings dam failures. As with any numerical model, the calibration of model parameters to corresponding physical quantities is a requirement prior to any application of the model. In addition to the effect of model parameters, such as the roughness of terrain, that are hard to quantify, the capabilities and limitations of the SPH model itself were investigated using a simple experimental flume flow setup. In this paper, the calibrated model was applied to literature-reported tailings dam failures. The outflow of tailings interacting with the terrain resulted in good agreement between the simulation results and the reported cases, enabling use of the modeling approach to assess the potential damage caused by tailings dam breaches and to predict flow paths of tailings. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".