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Record W2294753470 · doi:10.14288/1.0081165

Numerical modeling of horizontal drain drainage in an open pit slope

2010· article· en· W2294753470 on OpenAlexaff
Shemin Ge

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeologyDrainageGeotechnical engineeringGeomorphologyHydrology (agriculture)

Abstract

fetched live from OpenAlex

A study has been made to evaluate the effects of horizontal drain drainage on the water table drawdown in open pit slopes. Two major parameters of a horizontal drain drainage system, length and spacing, were studied. A two dimensional finite element computer model was constructed to simulate the water flow into drains in rock slopes. Water flow in the saturated zone was assumed. The computer model was tested by the field data obtained from the LORNEX Mine in British Columbia and the data taken from INTRODUCTION TO GROUNDWATER MODELING (Wang & Anderson, 1982). Satisfactory agreements were obtained. As the result of computer simulations, a series of graphs were plotted. These graphs show the relationship between hydraulic head distribution vs. drain spacing and length. They could be used in horizontal drain design as an aid to determine the spacing and length of a drain system. The computer simulations were also made to study the drainage characteristics of anisotropic rock slopes. The results indicated the influence of such rock conditions on the drainage effect. Another feature of mining slopes is that their height varies as the mining operation progresses. Therefore, the suitable vertical spacing between drain rows was investigated by computer simulation. A comparison of the drainage effects of different drain patterns, parallel drain and fanned drain layouts, was also made.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score0.969

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 science0.0010.000
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 head0.007
GPT teacher head0.171
Teacher spread0.164 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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