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Record W1983007206 · doi:10.1139/cgj-2014-0122

Long-runout mechanism and landsliding behaviour of large catastrophic landslide triggered by heavy rainfall in Guanling, Guizhou, China

2014· article· en· W1983007206 on OpenAlexvenueno aff
Aiguo Xing, Gonghui Wang, Bin Li, Yao Jiang, Zhen Feng, Toshitaka Kamai

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
Fundersnot available
KeywordsLandslideGeologyGeotechnical engineeringShear (geology)Shear zoneDiscrete element methodShear strength (soil)Run-outDirect shear testTriaxial shear testMining engineeringSeismologyTectonicsPetrologyEngineeringSoil scienceMechanics

Abstract

fetched live from OpenAlex

A large catastrophic landslide was triggered by a heavy rainfall on 28 June 2010 in Guanling, Guizhou, China. The landslide buried two villages and killed 99 people along the runout path. The landslide involved the failure of about 985 000 m 3 of sandstone from the source area, with a runout of about 1.4 km over a total vertical distance of about 420 m. To understand the possible long-runout mechanism and behaviour of the landslide, a detailed field survey of the landslide was conducted and samples were taken from the runout path. The shear behaviour of the sample based on a series of ring shear tests was examined, and numerical simulation of the landsliding behaviour by using a numerical runout model (DAN-W) was performed in which the shear strength obtained by ring shear tests was used. The experimental results reveal that the residual shear strength measured along the pre-existing shear surface is independent of the shear displacement rate under partially drained conditions, suggesting that the relationship between shear and normal stresses obeys the frictional model. A bulk basal friction angle of 14.4° at the base of the moving mass was then obtained from the test results. The simulated results show that the selected rheological model and parameters based on ring shear tests could provide the best performance in simulating the landslide. Therefore, it is expected that the model and parameters could improve the precision of hazard zonation for areas with geological, topographical, and climatic features similar to the Guanling landslide area.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.004
GPT teacher head0.206
Teacher spread0.202 · 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 designObservational
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

Citations77
Published2014
Admission routes1
Has abstractyes

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