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Record W2318445740 · doi:10.1061/40549(276)307

The Falling Process of Rubble Dumped by a Barge

2001· article· en· W2318445740 on OpenAlexaff
Peter van Gelderen, Han Vrijling, W. H. Tutuarima

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsRubbleConstant (computer programming)Series (stratigraphy)Process (computing)Stage (stratigraphy)Deposition (geology)Geotechnical engineeringGeologyMechanicsApplied mathematicsComputer scienceMathematicsPhysics

Abstract

fetched live from OpenAlex

A reliable prediction model of the deposition mound of rubble can be helpful in designing and calculating the cost of a structure. One of such models devides the gradual deposition of rubble in three stages. This study was focussed on the first stage in the dumping process, in which the deposition of rubble is described by a diffusion process. The cross-section of the resulting mound of rubble in this first stage of the dumping process is shaped like a two-dimensional Gaussian probability density function. The mathematical description of the first stage in the dumping process is called the Single Stone Model (SSM) and is given by: δG = C ⋅ squareroot of h ⋅ Dn50 The SSM assumes that the parameter c can be taken as a constant for a certain type of dumped material. However, from the analysis of prior experimental research, this assumption could be doubted. Therefore, two (new) series of model tests were carried out to verify the assumption in the SSM. For each series the dumped material was broken gravel. From the analysis of the results, it is concluded that for each series of experiments the value of the parameter c is indeed a constant. By means of a Student t-test it is concluded that both values of the parameter c could be taken equal to 0.685. Based on the new model tests it is concluded that the assumption in the SSM is very plausible. The value of the parameter c in the SSM can be considered as a constant for a certain type of dumped material.

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: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.152

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 head0.198
Teacher spread0.194 · 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

Citations1
Published2001
Admission routes1
Has abstractyes

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