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Record W2516109507 · doi:10.1177/0734242x16662332

Berm design to reduce risks of catastrophic slope failures at solid waste disposal sites

2016· article· en· W2516109507 on OpenAlexafffund
Bahram Gharabaghi, Ryan Clemmer, Mohammad Ali Jahanfar

Bibliographic record

VenueWaste Management & Research The Journal for a Sustainable Circular Economy · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsUniversity of TorontoUniversity of Guelph
FundersDivision of Ocean SciencesNatural Sciences and Engineering Research Council of Canada
KeywordsBermCatastrophic failureMunicipal solid wasteGeotechnical engineeringEnvironmental scienceDissipationEngineeringWaste managementWaste disposalCivil engineeringMaterials science

Abstract

fetched live from OpenAlex

Existing waste disposal sites are being strained by exceeding their volumetric capacities because of exponentially increasing rates of municipal solid waste generation worldwide, especially in densely populated metropolises. Over the past 40 years, six well-documented and analyzed disposal sites experienced catastrophic failure. This research presents a novel analysis and design method for implementation of a series of in-situ earth berms to slow down the movement of waste material flow following a catastrophic failure. This is the first study of its kind that employs a dynamic landslide analysis model, DAN-W, and the Voellmy rheological model to approximate solid waste avalanche flow. A variety of single and multiple berm configuration scenarios were developed and tested to find an optimum configuration of the various earth berm geometries and number of berms to achieve desired energy dissipation and reduction in total waste material runout length. The case study application of the novel mitigation measure shows that by constructing a series of six relatively inexpensive 3 m high earth berms at an optimum distance of 250 m from the slope toe, the total runout length of 1000 m and associated fatalities of the Leuwigajah dumpsite catastrophic failure in Bandung, Indonesia, could have been reduced by half.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.050
GPT teacher head0.328
Teacher spread0.278 · 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.

Study designNot applicable
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

Citations11
Published2016
Admission routes2
Has abstractyes

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Same venueWaste Management & Research The Journal for a Sustainable Circular EconomySame topicLandslides and related hazardsFrench-language works237,207