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Record W4414305697 · doi:10.1016/j.desal.2025.119389

Numerical simulation of desalination brine discharges: Effects of inlet boundary conditions

2025· article· en· W4414305697 on OpenAlexafffund
Danial Goodarzi, Abdolmajid Mohammadian, Saleh Rezaeiravesh

Bibliographic record

VenueDesalination · 2025
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du Canada
KeywordsInletNozzleTurbulenceLarge eddy simulationDesalinationBoundary value problemComputer simulationParticle image velocimetry

Abstract

fetched live from OpenAlex

This study examines the influence of inlet boundary conditions for a high-resolution numerical method of Large Eddy Simulation (LES) of desalination discharges and compares the results with high-resolution Particle Image Velocimetry (PIV). This study presents a robust nondimensional numerical model for high-resolution simulation of desalination jets, investigating the effects of various inlet boundary conditions, including Uniform Velocity (UV), Mapped Inlet (MI), Divergence-Free Synthetic Eddy Method (DFSEM), Turbulent Velocity (TV), and Fully Developed Constant Velocity (FDCV). Two approaches are employed for nozzle representation: an explicit method incorporating a 20 d 0 nozzle length, and an implicit method in which the nozzle geometry is omitted (the nozzle representations for Uniform Velocity (UV) and Turbulent Velocity (TV) boundary conditions are denoted by -p for explicit and -np for implicit, respectively). The results demonstrate that the choice of inlet boundary condition significantly impacts the velocity fields obtained from LES compared to the PIV, consequently influencing the mixing processes of a desalination discharge. The MI and DFSEM methods provide the closest agreement with experiments, capturing the intricate details of the jet velocity profile. In contrast, the UV and FDCV methods exhibited substantial discrepancies, particularly in the near-field region, where they failed to capture the expected turbulent development. Analyzing the turbulent flow characteristics revealed that the DFSEM, MI, TV-p and TV-np conditions more accurately reproduced the turbulence intensity and spectral scales observed in the PIV experiments. The application of Proper Orthogonal Decomposition (POD) to the concentration field revealed the presence of dominant flow structures, with the MI, DFSEM, and TV-np inlet conditions exhibiting spatial patterns consistent with the formation of helical structures near the nozzle. In contrast, the remaining boundary conditions did not exhibit these features, suggesting a less accurate representation of the flow physics. Although all tested boundary conditions could be applied for LES, the findings demonstrate that the DFSEM and MI approaches yield the most accurate and physically consistent results, showing strong agreement with experimental PIV data.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.698
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.237
Teacher spread0.233 · 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 teacher head, 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

Citations4
Published2025
Admission routes2
Has abstractyes

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