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Record W7132885090

Simulation of Solute and Particle Transport in Fractured Media

2024· dissertation· W7132885090 on OpenAlexfundno aff
Salman Sabahi

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsParticle (ecology)Fracture (geology)AdvectionDispersion (optics)Flow (mathematics)Surface roughnessSurface finish
DOInot available

Abstract

fetched live from OpenAlex

This study comprehensively analyzes the influence of fracture properties, flow regimes, and particle characteristics in fractured media, illuminating key aspects of solute transport, particle dispersion, and attachment mechanisms. These insights are crucial for developing effective environmental remediation systems.The introduction of this study examines the dynamics of particle and solute transport within fractured media, highlighting the critical role of comprehending the interplay between flow regimes, properties of particles, and the unique features of fractures, including roughness and mismatch length. This foundation is vital for simulating solute/particle transport dynamics accurately. Next, the impact of fracture properties on solute advection and dispersion were investigated. The results revealed a complex interplay between the Peclet number (Pe), mismatch length over length (ML/L), and both longitudinal and transverse dispersion, with increasing nonlinearity at higher Pe and ML/L ratios, and a greater influence of ML/L on transverse dispersion compared to roughness. The investigation then turns to particle dispersion and attachment, focusing on the influence of particle characteristics and fracture roughness. A novel probabilistic approach for assessing particle attachment is introduced. The study highlights the necessity of including gravitational forces in particle tracking models, especially for particles denser than water, to provide an accurate representation of their movement in fractures. Another significant part of the study examines how fracture properties and flow regimes affect particle transport under varying electrolyte concentrations (favorable and unfavorable conditions). Systematic analyses reveal that increased roughness enhances the particle attachment ratio and time-to-attachment with a pronounced tendency for attachment in the peak of fractures. These findings offer valuable insights into the dynamics of particle transport under different conditions. Collectively, these chapters contribute to a comprehensive understanding of the complex interactions governing solute transport and particle behavior in fractured media. The findings have implications for diverse applications, from environmental remediation to understanding the transport of specific particles like SARS-CoV-2 in fractured systems. Finally, the conclusions drawn from the comprehensive investigations provide a roadmap for future research aimed at understanding and optimizing particle/solute transport in fractured media. This guidance is essential for advancing the field and developing more effective strategies for managing environmental challenges and risks.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
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)0.0010.000

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 head0.026
GPT teacher head0.335
Teacher spread0.309 · 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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