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Record W4408436207 · doi:10.5194/egusphere-egu25-7900

Investigating interactions between flow and morphology in a step-pool unit combining physical and numerical modeling

2025· preprint· en· W4408436207 on OpenAlexaff
Chendi Zhang, Marwan A. Hassan, Yuncheng Xu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMorphology (biology)Unit (ring theory)Flow (mathematics)Computer scienceStatistical physicsMechanicsGeologyMathematicsPhysicsMathematics education

Abstract

fetched live from OpenAlex

Step-pools are common bedforms in mountain streams and have been utilized in river restoration or fish passage projects around the world. Step-pool units exhibit highly non-uniform hydraulic characteristics which have been reported to closely interact with the morphological evolution. Further understanding towards these interactions builds the basis for better prediction of channel evolution and more advanced design of artificial step-pool system. However, detailed information on the flow-morphology interactions has been limited due to the difficulty in measuring the flow structures or the flow forces in a step-pool unit.To fill in this knowledge gap, we established an approach combining physical experiment and computational fluid dynamics (CFD) simulation for a step-pool unit made of natural grains at six flow conditions. Structure from motion (SfM) was used to capture the detailed 3D reconstructions of the bed surfaces with various conditions of pool scour. The hydraulic measurement was applied both as input data at the inlet boundary and also in the validation for the CFD model. The high-resolution 3D flow structures for the step-pool unit were visualized, as well as the distributions of flow forces from both pressure and shear stress.The results illustrate the segmentation of flow velocity downstream of the step, i.e., the integral recirculation cell at the water surface, streamwise vortices formed at the step toe, and high-speed flow in between, resulting from the complex morphology of the step-pool unit. Both the recirculation cells at the water surface and the step toe perform as energy dissipaters to the flow with comparable magnitudes. Pool scour development during flow increase leads to the expansion of the recirculation cells until step-pool failure occurs. Significant transverse variability of the flow forces from both the shear stress and pressure has been revealed. The flow forces in both streamwise and transverse directions are closely related to the flow structures and morphology in the unit. The ratios between skin and form drag have large variations at low flows while show a relatively limited range of 0.05-0.1 at high flows, suggesting a small proportion occupied by the skin resistance in the total flow resistance in the step-pool channel. The drag coefficient of the step-pool unit is around 0.3 at high flows. Our results highlight the feasibility of the approach combining physical and numerical modeling in investigating the complex flow-morphology interactions of step-pool features.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.336
Teacher spread0.280 · 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
Published2025
Admission routes1
Has abstractyes

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