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Record W7105981367 · doi:10.7939/83478

Interfacial Evaporation Systems for Volumetric Reduction of Complex Particle-laden Suspensions

2025· dissertation· en· W7105981367 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsnot available
Fundersnot available
KeywordsDewateringEvaporationRenewable energyEvaporatorTailingsBrineMoistureWastewater

Abstract

fetched live from OpenAlex

Wastewater generated from mining operations is stored in tailing ponds, which now occupy vast areas of land and have exceeded 1.18 trillion liters in volume, growing continuously annually, particularly in the Athabasca region of western Canada. Dewatering of tailings remains a significant challenge due to the cohesive nature of fine particles trapping water within its constitution. Existing dewatering methods employed, such as chemical flocculation, mechanical techniques (e.g., membrane filtration), freeze–thaw cycles, centrifugation, and tail-lift drying suffer from high energy requirements, elevated operational costs, and restricted throughput, particularly at elevated solid concentrations. Critically, most of these techniques struggle to achieve the target solid content of 75 wt%, which is considered essential for effective dewatering. Interfacial evaporation presents an optimal strategy for wastewater treatment, offering zero operational energy costs, minimal capital investment, and effective harnessing of renewable energy. While extensive research has focused on brine wastewaters, its application to particle-laden wastewater remains largely unexplored. This Ph.D. thesis focuses on exploration on the interfacial evaporation technology as a sustainable approach for the volumetric reduction of particle-laden wastewater. Firstly, solar-assisted interfacial evaporation systems are explored for particle-based suspensions, including industrial tailing wastewater. Convective flow is next introduced to develop a wind-assisted interfacial sailboat evaporator setup, with optimized dimensions and sailboat features. Furthermore, an optimized biomimetic root structure is designed especially for high solid concentration regime to enhance the evaporation performance and better utilize the inaccessible moisture within the suspension composition. These results are supported with an extensive analysis of the evaporation phenomena against particle-suspensions at the high solid concentration regime. Lastly, additional techniques are explored to further sustain efficient evaporation performance close to 80 wt% solid concentration, reducing variance in the spatial moisture distribution. This thesis will start with an Introduction, then a Literature review. The main findings are covered in Chapter 3 to 6. In Chapter 3, we introduce a novel root-based solar interfacial evaporation strategy aimed at accelerating slurry drying. By adjusting the total root surface area, the water conduction rate was optimized across different levels of solar radiation. The best-performing configuration achieved a high evaporation rate of 1.15 kg/(m²·h) under 1 sun, successfully drying the slurry to a solid concentration of 75 wt%. It further removed water until the solid content exceeded 90 wt% over a total duration of 40 hours. The drop-in evaporation rate at higher solid concentrations was linked to the breakdown of continuous capillary water bridges between particles. Large-scale outdoor trials using a 625 cm² setup maintained high evaporation rates like the smaller systems, confirming its scalability for large-volume wastewater treatment. In Chapter 4, we developed a sustainable, clean, and efficient wind-driven interfacial evaporation technology to accelerate the drying of particle-laden wastewater. A self-floating mini-boat setup achieved evaporation rates of 8 kg/(m²·h) at solid concentrations exceeding 75 wt%, performing 18 times faster than natural evaporation. Prior to reaching a critical solids threshold, the evaporation rate scaled with the wind Peclet number to the power of 0.5, driven by enhanced mass transfer at the sail interface. Trials with actual tailings wastewater demonstrated effective volumetric reduction, achieving over 80 wt% solids in the final dried product. In Chapter 5, we developed a bio-mimetic root structure that enables rapid water conduction from dense particle-water mixtures, paired with a porous sail surface optimized for wind-driven evaporation. This setup achieved an evaporation rate (ER) of 3.9 kg/(m²·h) for a 75 wt% slurry, representing a tenfold improvement over natural evaporation under mild wind conditions. The evaporator’s extended roots were also capable of drawing water from slurry layers located beneath a 75 cm thick supernatant water column. In large-scale outdoor trials with 20 L of real, concentrated industrial slurry, the system achieved significant volumetric reduction, reaching final solid concentrations above 75 wt%. In Chapter 6, we report a range of strategies to enhance evaporation in a sailboat-style interfacial evaporator designed for particle-laden wastewater. Through spatial replantation—relocating the evaporator to a different position within the slurry—we achieved an impressive evaporation rate (ER) of 4 kg/(m²·h) at approximately 80 wt% solids, representing a 25% increase compared to non-replanted samples. In addition, extended evaporation periods were sustained at high solid concentrations by applying hydrodynamic flushing to the evaporator roots, which effectively removed dense particulate deposits.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.036
GPT teacher head0.260
Teacher spread0.224 · 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 designBench or experimental
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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