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Record W7162102040 · doi:10.82308/12585

Numerical and experimental modelling to support climate change adaptation of tailing management facilities in cold regions.

2024· dissertation· en· W7162102040 on OpenAlexaboutno aff
Khalil Hashem

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostClimate changeTailingsFlooding (psychology)Greenhouse gasCold climateClimate modelAdaptation (eye)

Abstract

fetched live from OpenAlex

Climate change, induced by increased anthropogenic emission of greenhouse gases, is one of today’s grand challenges. Changes are being experienced particularly intensely in the high latitudes, where permafrost degradation associated with warmer temperatures, and increasing intensity, duration and frequency of extreme events, are having significant impacts on engineering systems, including mines and mine life-cycle. This thesis addresses some of the critical knowledge gaps related to climate-mine interactions and adaptation strategies for Canada's high latitude regions, through advanced numerical and experimental modelling approaches, with a specific focus on mine tailings, i.e., waste generated by the mechanical and chemical processes involved in the extraction and separation of the desired mine ore in a processing plant. The main objective of this thesis unfolds in three main phases. The first phase of this thesis identifies potentially vulnerable mines and phases of the mine life cycle from climate change perspective for the Canadian permafrost regions. This involves utilizing an ensemble of climate change simulations performed using a state-of-the-art regional climate model GEM (Global Environmental Multiscale), at 50 km horizontal resolution. The second phase of this thesis assesses the climate resiliency of the Mont-Wright mine tailings management facility (TMF), specifically the potential for tailings erosion and flooding in a warmer future climate. This is done through climate simulations at a 1 km horizontal resolution, covering the life span of the mine, coupled with advanced diagnostics. The third phase investigates the properties of Mont-Wright mine tailings, for innovating an effective climate change adaptation strategy. Laboratory experiments and lab-scale and field-scale numerical models are developed to comprehensively explore the mechanical, thermophysical, and rheological properties of Mont-Wright tailings (i.e., with 20 and 30% water contents), and their suitability for the application of frozen paste surface disposal method.Results from the first phase identifies northernmost and northeastern mines to be more vulnerable, with air/soil temperature, precipitation and wind speed being the most influential climate variables, especially for managing various types of TMFs. Focused investigation of the Mont-Wright TMF in phase two suggests that higher wind magnitudes could potentially lead to slight increases in tailings internal erosion rate by up to 6% for a high emission scenario. Furthermore, results also suggest future increases in flooding, estimated in terms of changes to the probable maximum flood (PMF), with summer/fall PMF increases of up to 20%, which is larger than that for spring PMF. According to the laboratory investigation of the properties of Mont-Wright tailings, the unconfined compressive strength (UCS) of the tailings is found to be in the 0.26 MPa to 0.93 MPa range depending on the water content, ambient temperature, and number of freeze-thaw cycles (FTCs), with 30% water content resulting in higher strength compared to 20%. Additionally, investigation shows that the use of paste tailings with 30% water content provide enhanced rheological properties, where viscosity is 140% lower, compared with paste with 20% water content, favoring workability and pumpability. The experiments and numerical modelling lead to the conclusion that Mont-Wright tailings are suited for surface disposal in a frozen paste state.This thesis contributes significantly to the Canadian mining sector by quantifying climate change impacts on mines located in the Canadian permafrost region, for the first time. The developed actionable high-resolution climate projections provide unprecedented insights into the climate resiliency of Mont-Wright's tailings management facility. In addition, this thesis lays a strong foundation for the innovative use of frozen paste tailings surface disposal at Mont-Wright mine

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.091
GPT teacher head0.286
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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