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Record W4377028335 · doi:10.1061/9780784484852.009

Small-Scale Physical Model for Studying the Effect of Rock Mass Parameters in the Hydraulic Erosion Process of Unlined Spillways

2023· article· en· W4377028335 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsHydro-QuébecUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsErosionScale (ratio)Environmental scienceGeotechnical engineeringProcess (computing)GeologyHydrology (agriculture)GeomorphologyComputer scienceGeography

Abstract

fetched live from OpenAlex

Physical flow models are used to study parameters affecting the erodibility of rock in dam unlined spillways. Among the existing physical models, the parameters of joint orientation and of protrusion are the most studied. However, other rock mass parameters have an important contribution in the erosion mechanism, but they were given less attention in existing research, or when studied, mixed results were obtained. In addition, most of the models simulate rock mass considering a single block, which cannot simulate possible interactions between blocks. To address this problem, a scale model that simulates an existing spillway was built in a UQAC laboratory. This model is a 1:40 scale of the existing spillway and reproduces hydraulic conditions of the prototype. The physical model makes it possible to vary several rock mass parameters, such as joint orientation, joint opening, protrusion, block volume, as well as joint roughness, to evaluate their impact in the rock erosion process.

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.

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: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.235
Teacher spread0.214 · 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